slide_deck.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "# Prosper Loan Data Exploration\n",
    "## by Hind Al Ramah\n",
    "\n",
    "## Preliminary Wrangling\n",
    "\n",
    "> This data set contains 113,937 records of loans along with 81 variables on each\n",
    "loan, such as loan amount, interest rate, borrower income, and many others. Our exploration will foucs on only 10 to 13 variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# import all packages and set plots to be embedded inline\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sb\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# ignore warnings\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# load in the dataset into a dataframe\n",
    "df = pd.read_csv('prosperLoanData.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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",
      "ListingKey                             113937 non-null object\n",
      "ListingNumber                          113937 non-null int64\n",
      "ListingCreationDate                    113937 non-null object\n",
      "CreditGrade                            28953 non-null object\n",
      "Term                                   113937 non-null int64\n",
      "LoanStatus                             113937 non-null object\n",
      "ClosedDate                             55089 non-null object\n",
      "BorrowerAPR                            113912 non-null float64\n",
      "BorrowerRate                           113937 non-null float64\n",
      "LenderYield                            113937 non-null float64\n",
      "EstimatedEffectiveYield                84853 non-null float64\n",
      "EstimatedLoss                          84853 non-null float64\n",
      "EstimatedReturn                        84853 non-null float64\n",
      "ProsperRating (numeric)                84853 non-null float64\n",
      "ProsperRating (Alpha)                  84853 non-null object\n",
      "ProsperScore                           84853 non-null float64\n",
      "ListingCategory (numeric)              113937 non-null int64\n",
      "BorrowerState                          108422 non-null object\n",
      "Occupation                             110349 non-null object\n",
      "EmploymentStatus                       111682 non-null object\n",
      "EmploymentStatusDuration               106312 non-null float64\n",
      "IsBorrowerHomeowner                    113937 non-null bool\n",
      "CurrentlyInGroup                       113937 non-null bool\n",
      "GroupKey                               13341 non-null object\n",
      "DateCreditPulled                       113937 non-null object\n",
      "CreditScoreRangeLower                  113346 non-null float64\n",
      "CreditScoreRangeUpper                  113346 non-null float64\n",
      "FirstRecordedCreditLine                113240 non-null object\n",
      "CurrentCreditLines                     106333 non-null float64\n",
      "OpenCreditLines                        106333 non-null float64\n",
      "TotalCreditLinespast7years             113240 non-null float64\n",
      "OpenRevolvingAccounts                  113937 non-null int64\n",
      "OpenRevolvingMonthlyPayment            113937 non-null float64\n",
      "InquiriesLast6Months                   113240 non-null float64\n",
      "TotalInquiries                         112778 non-null float64\n",
      "CurrentDelinquencies                   113240 non-null float64\n",
      "AmountDelinquent                       106315 non-null float64\n",
      "DelinquenciesLast7Years                112947 non-null float64\n",
      "PublicRecordsLast10Years               113240 non-null float64\n",
      "PublicRecordsLast12Months              106333 non-null float64\n",
      "RevolvingCreditBalance                 106333 non-null float64\n",
      "BankcardUtilization                    106333 non-null float64\n",
      "AvailableBankcardCredit                106393 non-null float64\n",
      "TotalTrades                            106393 non-null float64\n",
      "TradesNeverDelinquent (percentage)     106393 non-null float64\n",
      "TradesOpenedLast6Months                106393 non-null float64\n",
      "DebtToIncomeRatio                      105383 non-null float64\n",
      "IncomeRange                            113937 non-null object\n",
      "IncomeVerifiable                       113937 non-null bool\n",
      "StatedMonthlyIncome                    113937 non-null float64\n",
      "LoanKey                                113937 non-null object\n",
      "TotalProsperLoans                      22085 non-null float64\n",
      "TotalProsperPaymentsBilled             22085 non-null float64\n",
      "OnTimeProsperPayments                  22085 non-null float64\n",
      "ProsperPaymentsLessThanOneMonthLate    22085 non-null float64\n",
      "ProsperPaymentsOneMonthPlusLate        22085 non-null float64\n",
      "ProsperPrincipalBorrowed               22085 non-null float64\n",
      "ProsperPrincipalOutstanding            22085 non-null float64\n",
      "ScorexChangeAtTimeOfListing            18928 non-null float64\n",
      "LoanCurrentDaysDelinquent              113937 non-null int64\n",
      "LoanFirstDefaultedCycleNumber          16952 non-null float64\n",
      "LoanMonthsSinceOrigination             113937 non-null int64\n",
      "LoanNumber                             113937 non-null int64\n",
      "LoanOriginalAmount                     113937 non-null int64\n",
      "LoanOriginationDate                    113937 non-null object\n",
      "LoanOriginationQuarter                 113937 non-null object\n",
      "MemberKey                              113937 non-null object\n",
      "MonthlyLoanPayment                     113937 non-null float64\n",
      "LP_CustomerPayments                    113937 non-null float64\n",
      "LP_CustomerPrincipalPayments           113937 non-null float64\n",
      "LP_InterestandFees                     113937 non-null float64\n",
      "LP_ServiceFees                         113937 non-null float64\n",
      "LP_CollectionFees                      113937 non-null float64\n",
      "LP_GrossPrincipalLoss                  113937 non-null float64\n",
      "LP_NetPrincipalLoss                    113937 non-null float64\n",
      "LP_NonPrincipalRecoverypayments        113937 non-null float64\n",
      "PercentFunded                          113937 non-null float64\n",
      "Recommendations                        113937 non-null int64\n",
      "InvestmentFromFriendsCount             113937 non-null int64\n",
      "InvestmentFromFriendsAmount            113937 non-null float64\n",
      "Investors                              113937 non-null int64\n",
      "dtypes: bool(3), float64(50), int64(11), object(17)\n",
      "memory usage: 68.1+ MB\n"
     ]
    }
   ],
   "source": [
    "# inspecting the dataset\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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>ListingNumber</th>\n",
       "      <th>Term</th>\n",
       "      <th>BorrowerAPR</th>\n",
       "      <th>BorrowerRate</th>\n",
       "      <th>LenderYield</th>\n",
       "      <th>EstimatedEffectiveYield</th>\n",
       "      <th>EstimatedLoss</th>\n",
       "      <th>EstimatedReturn</th>\n",
       "      <th>ProsperRating (numeric)</th>\n",
       "      <th>ProsperScore</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>count</th>\n",
       "      <td>1.139370e+05</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113912.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>84853.000000</td>\n",
       "      <td>84853.000000</td>\n",
       "      <td>84853.000000</td>\n",
       "      <td>84853.000000</td>\n",
       "      <td>84853.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "      <td>113937.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>6.278857e+05</td>\n",
       "      <td>40.830248</td>\n",
       "      <td>0.218828</td>\n",
       "      <td>0.192764</td>\n",
       "      <td>0.182701</td>\n",
       "      <td>0.168661</td>\n",
       "      <td>0.080306</td>\n",
       "      <td>0.096068</td>\n",
       "      <td>4.072243</td>\n",
       "      <td>5.950067</td>\n",
       "      <td>...</td>\n",
       "      <td>-54.725641</td>\n",
       "      <td>-14.242698</td>\n",
       "      <td>700.446342</td>\n",
       "      <td>681.420499</td>\n",
       "      <td>25.142686</td>\n",
       "      <td>0.998584</td>\n",
       "      <td>0.048027</td>\n",
       "      <td>0.023460</td>\n",
       "      <td>16.550751</td>\n",
       "      <td>80.475228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.280762e+05</td>\n",
       "      <td>10.436212</td>\n",
       "      <td>0.080364</td>\n",
       "      <td>0.074818</td>\n",
       "      <td>0.074516</td>\n",
       "      <td>0.068467</td>\n",
       "      <td>0.046764</td>\n",
       "      <td>0.030403</td>\n",
       "      <td>1.673227</td>\n",
       "      <td>2.376501</td>\n",
       "      <td>...</td>\n",
       "      <td>60.675425</td>\n",
       "      <td>109.232758</td>\n",
       "      <td>2388.513831</td>\n",
       "      <td>2357.167068</td>\n",
       "      <td>275.657937</td>\n",
       "      <td>0.017919</td>\n",
       "      <td>0.332353</td>\n",
       "      <td>0.232412</td>\n",
       "      <td>294.545422</td>\n",
       "      <td>103.239020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.000000e+00</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.006530</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.010000</td>\n",
       "      <td>-0.182700</td>\n",
       "      <td>0.004900</td>\n",
       "      <td>-0.182700</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-664.870000</td>\n",
       "      <td>-9274.750000</td>\n",
       "      <td>-94.200000</td>\n",
       "      <td>-954.550000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.700000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4.009190e+05</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>0.156290</td>\n",
       "      <td>0.134000</td>\n",
       "      <td>0.124200</td>\n",
       "      <td>0.115670</td>\n",
       "      <td>0.042400</td>\n",
       "      <td>0.074080</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-73.180000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.005540e+05</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>0.209760</td>\n",
       "      <td>0.184000</td>\n",
       "      <td>0.173000</td>\n",
       "      <td>0.161500</td>\n",
       "      <td>0.072400</td>\n",
       "      <td>0.091700</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-34.440000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>44.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.926340e+05</td>\n",
       "      <td>36.000000</td>\n",
       "      <td>0.283810</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>0.240000</td>\n",
       "      <td>0.224300</td>\n",
       "      <td>0.112000</td>\n",
       "      <td>0.116600</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>-13.920000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>115.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.255725e+06</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>0.512290</td>\n",
       "      <td>0.497500</td>\n",
       "      <td>0.492500</td>\n",
       "      <td>0.319900</td>\n",
       "      <td>0.366000</td>\n",
       "      <td>0.283700</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>32.060000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25000.000000</td>\n",
       "      <td>25000.000000</td>\n",
       "      <td>21117.900000</td>\n",
       "      <td>1.012500</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>33.000000</td>\n",
       "      <td>25000.000000</td>\n",
       "      <td>1189.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ListingNumber           Term    BorrowerAPR   BorrowerRate  \\\n",
       "count   1.139370e+05  113937.000000  113912.000000  113937.000000   \n",
       "mean    6.278857e+05      40.830248       0.218828       0.192764   \n",
       "std     3.280762e+05      10.436212       0.080364       0.074818   \n",
       "min     4.000000e+00      12.000000       0.006530       0.000000   \n",
       "25%     4.009190e+05      36.000000       0.156290       0.134000   \n",
       "50%     6.005540e+05      36.000000       0.209760       0.184000   \n",
       "75%     8.926340e+05      36.000000       0.283810       0.250000   \n",
       "max     1.255725e+06      60.000000       0.512290       0.497500   \n",
       "\n",
       "         LenderYield  EstimatedEffectiveYield  EstimatedLoss  EstimatedReturn  \\\n",
       "count  113937.000000             84853.000000   84853.000000     84853.000000   \n",
       "mean        0.182701                 0.168661       0.080306         0.096068   \n",
       "std         0.074516                 0.068467       0.046764         0.030403   \n",
       "min        -0.010000                -0.182700       0.004900        -0.182700   \n",
       "25%         0.124200                 0.115670       0.042400         0.074080   \n",
       "50%         0.173000                 0.161500       0.072400         0.091700   \n",
       "75%         0.240000                 0.224300       0.112000         0.116600   \n",
       "max         0.492500                 0.319900       0.366000         0.283700   \n",
       "\n",
       "       ProsperRating (numeric)  ProsperScore      ...        LP_ServiceFees  \\\n",
       "count             84853.000000  84853.000000      ...         113937.000000   \n",
       "mean                  4.072243      5.950067      ...            -54.725641   \n",
       "std                   1.673227      2.376501      ...             60.675425   \n",
       "min                   1.000000      1.000000      ...           -664.870000   \n",
       "25%                   3.000000      4.000000      ...            -73.180000   \n",
       "50%                   4.000000      6.000000      ...            -34.440000   \n",
       "75%                   5.000000      8.000000      ...            -13.920000   \n",
       "max                   7.000000     11.000000      ...             32.060000   \n",
       "\n",
       "       LP_CollectionFees  LP_GrossPrincipalLoss  LP_NetPrincipalLoss  \\\n",
       "count      113937.000000          113937.000000        113937.000000   \n",
       "mean          -14.242698             700.446342           681.420499   \n",
       "std           109.232758            2388.513831          2357.167068   \n",
       "min         -9274.750000             -94.200000          -954.550000   \n",
       "25%             0.000000               0.000000             0.000000   \n",
       "50%             0.000000               0.000000             0.000000   \n",
       "75%             0.000000               0.000000             0.000000   \n",
       "max             0.000000           25000.000000         25000.000000   \n",
       "\n",
       "       LP_NonPrincipalRecoverypayments  PercentFunded  Recommendations  \\\n",
       "count                    113937.000000  113937.000000    113937.000000   \n",
       "mean                         25.142686       0.998584         0.048027   \n",
       "std                         275.657937       0.017919         0.332353   \n",
       "min                           0.000000       0.700000         0.000000   \n",
       "25%                           0.000000       1.000000         0.000000   \n",
       "50%                           0.000000       1.000000         0.000000   \n",
       "75%                           0.000000       1.000000         0.000000   \n",
       "max                       21117.900000       1.012500        39.000000   \n",
       "\n",
       "       InvestmentFromFriendsCount  InvestmentFromFriendsAmount      Investors  \n",
       "count               113937.000000                113937.000000  113937.000000  \n",
       "mean                     0.023460                    16.550751      80.475228  \n",
       "std                      0.232412                   294.545422     103.239020  \n",
       "min                      0.000000                     0.000000       1.000000  \n",
       "25%                      0.000000                     0.000000       2.000000  \n",
       "50%                      0.000000                     0.000000      44.000000  \n",
       "75%                      0.000000                     0.000000     115.000000  \n",
       "max                     33.000000                 25000.000000    1189.000000  \n",
       "\n",
       "[8 rows x 61 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([36, 60, 12])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.Term.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Completed', 'Current', 'Past Due (1-15 days)', 'Defaulted',\n",
       "       'Chargedoff', 'Past Due (16-30 days)', 'Cancelled',\n",
       "       'Past Due (61-90 days)', 'Past Due (31-60 days)',\n",
       "       'Past Due (91-120 days)', 'FinalPaymentInProgress',\n",
       "       'Past Due (>120 days)'], dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.LoanStatus.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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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>0.1580</td>\n",
       "      <td>0.1380</td>\n",
       "      <td>...</td>\n",
       "      <td>-133.18</td>\n",
       "      <td>0.00</td>\n",
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       "      <td>0</td>\n",
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       "      <td>258</td>\n",
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       "    <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>0.0920</td>\n",
       "      <td>0.0820</td>\n",
       "      <td>...</td>\n",
       "      <td>0.00</td>\n",
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       "      <td>1.0000</td>\n",
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       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0EE9337825851032864889A</td>\n",
       "      <td>81716</td>\n",
       "      <td>2007-01-05 15:00:47.090000000</td>\n",
       "      <td>HR</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2009-12-17 00:00:00</td>\n",
       "      <td>0.28269</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.2400</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.20</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0EF5356002482715299901A</td>\n",
       "      <td>658116</td>\n",
       "      <td>2012-10-22 11:02:35.010000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.12528</td>\n",
       "      <td>0.0974</td>\n",
       "      <td>0.0874</td>\n",
       "      <td>...</td>\n",
       "      <td>-108.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0F023589499656230C5E3E2</td>\n",
       "      <td>909464</td>\n",
       "      <td>2013-09-14 18:38:39.097000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.24614</td>\n",
       "      <td>0.2085</td>\n",
       "      <td>0.1985</td>\n",
       "      <td>...</td>\n",
       "      <td>-60.27</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0F05359734824199381F61D</td>\n",
       "      <td>1074836</td>\n",
       "      <td>2013-12-14 08:26:37.093000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.15425</td>\n",
       "      <td>0.1314</td>\n",
       "      <td>0.1214</td>\n",
       "      <td>...</td>\n",
       "      <td>-25.33</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0F0A3576754255009D63151</td>\n",
       "      <td>750899</td>\n",
       "      <td>2013-04-12 09:52:56.147000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.31032</td>\n",
       "      <td>0.2712</td>\n",
       "      <td>0.2612</td>\n",
       "      <td>...</td>\n",
       "      <td>-22.95</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0F1035772717087366F9EA7</td>\n",
       "      <td>768193</td>\n",
       "      <td>2013-05-05 06:49:27.493000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.23939</td>\n",
       "      <td>0.2019</td>\n",
       "      <td>0.1919</td>\n",
       "      <td>...</td>\n",
       "      <td>-69.21</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0F043596202561788EA13D5</td>\n",
       "      <td>1023355</td>\n",
       "      <td>2013-12-02 10:43:39.117000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.07620</td>\n",
       "      <td>0.0629</td>\n",
       "      <td>0.0529</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0F043596202561788EA13D5</td>\n",
       "      <td>1023355</td>\n",
       "      <td>2013-12-02 10:43:39.117000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.07620</td>\n",
       "      <td>0.0629</td>\n",
       "      <td>0.0529</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.77</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0F123545674891886D9F106</td>\n",
       "      <td>587746</td>\n",
       "      <td>2012-05-10 07:04:01.577000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.27462</td>\n",
       "      <td>0.2489</td>\n",
       "      <td>0.2389</td>\n",
       "      <td>...</td>\n",
       "      <td>-214.04</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0F1734025150298088A5F2B</td>\n",
       "      <td>213551</td>\n",
       "      <td>2007-10-09 20:28:33.640000000</td>\n",
       "      <td>C</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2008-01-07 00:00:00</td>\n",
       "      <td>0.15033</td>\n",
       "      <td>0.1325</td>\n",
       "      <td>0.1225</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.88</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0F1A3597143888805163EF7</td>\n",
       "      <td>1081604</td>\n",
       "      <td>2013-12-15 20:01:10.757000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Past Due (1-15 days)</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.17969</td>\n",
       "      <td>0.1435</td>\n",
       "      <td>0.1335</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.40</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0F1C3583260311305D68F87</td>\n",
       "      <td>840820</td>\n",
       "      <td>2013-07-15 16:28:28.087000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.13138</td>\n",
       "      <td>0.1034</td>\n",
       "      <td>0.0934</td>\n",
       "      <td>...</td>\n",
       "      <td>-46.42</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0F353575943675863D1AFC0</td>\n",
       "      <td>757359</td>\n",
       "      <td>2013-04-19 11:17:41.700000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.11695</td>\n",
       "      <td>0.0949</td>\n",
       "      <td>0.0849</td>\n",
       "      <td>...</td>\n",
       "      <td>-138.07</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.7731</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0F483544120452347F48121</td>\n",
       "      <td>577164</td>\n",
       "      <td>2012-04-10 09:14:46.297000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Defaulted</td>\n",
       "      <td>2012-12-19 00:00:00</td>\n",
       "      <td>0.35797</td>\n",
       "      <td>0.3177</td>\n",
       "      <td>0.3077</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.81</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3790.25</td>\n",
       "      <td>3790.25</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0F4835843081468212F0892</td>\n",
       "      <td>841846</td>\n",
       "      <td>2013-07-16 12:42:48.680000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.30748</td>\n",
       "      <td>0.2809</td>\n",
       "      <td>0.2709</td>\n",
       "      <td>...</td>\n",
       "      <td>-23.01</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0FDF336575182398852A8DC</td>\n",
       "      <td>31540</td>\n",
       "      <td>2006-08-15 12:21:09.433000000</td>\n",
       "      <td>AA</td>\n",
       "      <td>36</td>\n",
       "      <td>Chargedoff</td>\n",
       "      <td>2008-05-22 00:00:00</td>\n",
       "      <td>0.13202</td>\n",
       "      <td>0.1250</td>\n",
       "      <td>0.1175</td>\n",
       "      <td>...</td>\n",
       "      <td>-54.61</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6012.65</td>\n",
       "      <td>6012.67</td>\n",
       "      <td>268.96</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0FF2357105361877390B58D</td>\n",
       "      <td>716058</td>\n",
       "      <td>2013-02-20 03:48:37.470000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.12528</td>\n",
       "      <td>0.0974</td>\n",
       "      <td>0.0874</td>\n",
       "      <td>...</td>\n",
       "      <td>-121.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0FFC35866018516621B0D3F</td>\n",
       "      <td>875565</td>\n",
       "      <td>2013-08-21 06:49:02.093000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.24754</td>\n",
       "      <td>0.2225</td>\n",
       "      <td>0.2125</td>\n",
       "      <td>...</td>\n",
       "      <td>-21.61</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>101635959323992333B3C70</td>\n",
       "      <td>1011916</td>\n",
       "      <td>2013-11-22 11:35:02.987000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.16732</td>\n",
       "      <td>0.1314</td>\n",
       "      <td>0.1214</td>\n",
       "      <td>...</td>\n",
       "      <td>-34.11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1017340630713945364DA6B</td>\n",
       "      <td>241498</td>\n",
       "      <td>2007-11-30 20:33:49.227000000</td>\n",
       "      <td>D</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2010-12-12 00:00:00</td>\n",
       "      <td>0.21488</td>\n",
       "      <td>0.2075</td>\n",
       "      <td>0.1975</td>\n",
       "      <td>...</td>\n",
       "      <td>-51.12</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>101735700321773921526BF</td>\n",
       "      <td>706927</td>\n",
       "      <td>2013-01-30 09:36:13.783000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.35356</td>\n",
       "      <td>0.3134</td>\n",
       "      <td>0.3034</td>\n",
       "      <td>...</td>\n",
       "      <td>-35.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>101B35764008108187B2EBA</td>\n",
       "      <td>758964</td>\n",
       "      <td>2013-04-22 13:29:19.073000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Defaulted</td>\n",
       "      <td>2013-12-26 00:00:00</td>\n",
       "      <td>0.28032</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.2319</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.89</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1882.27</td>\n",
       "      <td>1882.27</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>101B3596709094692AC79C0</td>\n",
       "      <td>1046345</td>\n",
       "      <td>2013-12-03 11:34:46.127000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.19859</td>\n",
       "      <td>0.1620</td>\n",
       "      <td>0.1520</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.72</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>10223590888942486E3826E</td>\n",
       "      <td>950067</td>\n",
       "      <td>2013-10-02 14:31:09.157000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.30182</td>\n",
       "      <td>0.2629</td>\n",
       "      <td>0.2529</td>\n",
       "      <td>...</td>\n",
       "      <td>-13.11</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0F4F3571508214190FD75CB</td>\n",
       "      <td>713131</td>\n",
       "      <td>2013-02-12 18:07:31.690000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2013-10-22 00:00:00</td>\n",
       "      <td>0.30748</td>\n",
       "      <td>0.2809</td>\n",
       "      <td>0.2709</td>\n",
       "      <td>...</td>\n",
       "      <td>-25.81</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0F5034867864161084F3789</td>\n",
       "      <td>463083</td>\n",
       "      <td>2010-06-16 16:23:44.533000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2013-07-03 00:00:00</td>\n",
       "      <td>0.11296</td>\n",
       "      <td>0.0920</td>\n",
       "      <td>0.0820</td>\n",
       "      <td>...</td>\n",
       "      <td>-64.62</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0F53359346357513247D86B</td>\n",
       "      <td>989519</td>\n",
       "      <td>2013-11-02 16:01:28.050000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.20268</td>\n",
       "      <td>0.1660</td>\n",
       "      <td>0.1560</td>\n",
       "      <td>...</td>\n",
       "      <td>-22.56</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0F563597161095613517437</td>\n",
       "      <td>1051243</td>\n",
       "      <td>2013-12-17 09:18:33.220000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.15223</td>\n",
       "      <td>0.1239</td>\n",
       "      <td>0.1139</td>\n",
       "      <td>...</td>\n",
       "      <td>-29.73</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113907</th>\n",
       "      <td>C982359388882926442DE72</td>\n",
       "      <td>1005215</td>\n",
       "      <td>2013-11-09 06:55:05.690000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.35356</td>\n",
       "      <td>0.3134</td>\n",
       "      <td>0.3034</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.99</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113908</th>\n",
       "      <td>C9843500054876019D611A1</td>\n",
       "      <td>486057</td>\n",
       "      <td>2010-11-29 10:40:09.730000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2011-01-31 00:00:00</td>\n",
       "      <td>0.35858</td>\n",
       "      <td>0.3220</td>\n",
       "      <td>0.3120</td>\n",
       "      <td>...</td>\n",
       "      <td>-11.02</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113909</th>\n",
       "      <td>C98635564651525938EB38E</td>\n",
       "      <td>635880</td>\n",
       "      <td>2012-09-08 10:34:38.837000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.27554</td>\n",
       "      <td>0.2498</td>\n",
       "      <td>0.2398</td>\n",
       "      <td>...</td>\n",
       "      <td>-78.65</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113910</th>\n",
       "      <td>C9873600264828351437CAB</td>\n",
       "      <td>1161059</td>\n",
       "      <td>2014-01-24 19:56:49.960000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.32446</td>\n",
       "      <td>0.2850</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>...</td>\n",
       "      <td>-3.29</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113911</th>\n",
       "      <td>C9883594035073098BC5D51</td>\n",
       "      <td>996496</td>\n",
       "      <td>2013-11-15 11:42:47.540000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.25330</td>\n",
       "      <td>0.2155</td>\n",
       "      <td>0.2055</td>\n",
       "      <td>...</td>\n",
       "      <td>-24.69</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113912</th>\n",
       "      <td>C98A3597264633447D66DF9</td>\n",
       "      <td>1083677</td>\n",
       "      <td>2013-12-16 16:36:00.990000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.06726</td>\n",
       "      <td>0.0605</td>\n",
       "      <td>0.0505</td>\n",
       "      <td>...</td>\n",
       "      <td>-7.15</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113913</th>\n",
       "      <td>D2013482695428940FAD9E3</td>\n",
       "      <td>455673</td>\n",
       "      <td>2010-04-25 15:13:27.963000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2013-05-05 00:00:00</td>\n",
       "      <td>0.12410</td>\n",
       "      <td>0.1030</td>\n",
       "      <td>0.0930</td>\n",
       "      <td>...</td>\n",
       "      <td>-129.82</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113914</th>\n",
       "      <td>D20533652658825353F6597</td>\n",
       "      <td>30223</td>\n",
       "      <td>2006-08-09 14:34:40.010000000</td>\n",
       "      <td>HR</td>\n",
       "      <td>36</td>\n",
       "      <td>Defaulted</td>\n",
       "      <td>2007-03-19 00:00:00</td>\n",
       "      <td>0.25757</td>\n",
       "      <td>0.2500</td>\n",
       "      <td>0.2450</td>\n",
       "      <td>...</td>\n",
       "      <td>-2.43</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2883.01</td>\n",
       "      <td>2883.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113915</th>\n",
       "      <td>D2053427325575423785798</td>\n",
       "      <td>374730</td>\n",
       "      <td>2008-07-29 05:22:29.390000000</td>\n",
       "      <td>D</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2011-09-28 00:00:00</td>\n",
       "      <td>0.22237</td>\n",
       "      <td>0.2000</td>\n",
       "      <td>0.1900</td>\n",
       "      <td>...</td>\n",
       "      <td>-51.71</td>\n",
       "      <td>-37.64</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113916</th>\n",
       "      <td>D2063562664602024E13D82</td>\n",
       "      <td>667047</td>\n",
       "      <td>2012-11-08 20:07:36.600000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.33286</td>\n",
       "      <td>0.2932</td>\n",
       "      <td>0.2832</td>\n",
       "      <td>...</td>\n",
       "      <td>-43.14</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113917</th>\n",
       "      <td>D2063594229009539839457</td>\n",
       "      <td>1028126</td>\n",
       "      <td>2013-11-23 04:52:50.057000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.32446</td>\n",
       "      <td>0.2850</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.80</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113918</th>\n",
       "      <td>D207342464194217591D1E1</td>\n",
       "      <td>353488</td>\n",
       "      <td>2008-06-19 12:02:53.300000000</td>\n",
       "      <td>A</td>\n",
       "      <td>36</td>\n",
       "      <td>Defaulted</td>\n",
       "      <td>2011-01-27 00:00:00</td>\n",
       "      <td>0.12201</td>\n",
       "      <td>0.1080</td>\n",
       "      <td>0.0980</td>\n",
       "      <td>...</td>\n",
       "      <td>-103.49</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2176.53</td>\n",
       "      <td>2176.51</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113919</th>\n",
       "      <td>D20C3577637248543A1F80C</td>\n",
       "      <td>772509</td>\n",
       "      <td>2013-05-07 18:49:59.750000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.27285</td>\n",
       "      <td>0.2346</td>\n",
       "      <td>0.2246</td>\n",
       "      <td>...</td>\n",
       "      <td>-25.59</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113920</th>\n",
       "      <td>D20E358076984586576526D</td>\n",
       "      <td>804763</td>\n",
       "      <td>2013-06-11 05:49:40.247000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.35356</td>\n",
       "      <td>0.3134</td>\n",
       "      <td>0.3034</td>\n",
       "      <td>...</td>\n",
       "      <td>-25.39</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113921</th>\n",
       "      <td>D21A33647075665665BE266</td>\n",
       "      <td>4</td>\n",
       "      <td>2005-11-09 20:44:28.847000000</td>\n",
       "      <td>AA</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2005-11-25 00:00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0400</td>\n",
       "      <td>0.0350</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.88</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113922</th>\n",
       "      <td>D2293427338962159DA5143</td>\n",
       "      <td>379986</td>\n",
       "      <td>2008-08-08 16:58:54.760000000</td>\n",
       "      <td>C</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2011-08-19 00:00:00</td>\n",
       "      <td>0.15094</td>\n",
       "      <td>0.1295</td>\n",
       "      <td>0.1195</td>\n",
       "      <td>...</td>\n",
       "      <td>-81.95</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113923</th>\n",
       "      <td>E334343080922352965DF86</td>\n",
       "      <td>395877</td>\n",
       "      <td>2008-09-10 08:26:30.537000000</td>\n",
       "      <td>B</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2011-09-23 00:00:00</td>\n",
       "      <td>0.22378</td>\n",
       "      <td>0.2089</td>\n",
       "      <td>0.1989</td>\n",
       "      <td>...</td>\n",
       "      <td>-135.50</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113924</th>\n",
       "      <td>E340356181565702714DBCE</td>\n",
       "      <td>657862</td>\n",
       "      <td>2012-10-20 19:15:52.670000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.17317</td>\n",
       "      <td>0.1499</td>\n",
       "      <td>0.1399</td>\n",
       "      <td>...</td>\n",
       "      <td>-60.83</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113925</th>\n",
       "      <td>E3423576946812123E4798D</td>\n",
       "      <td>760946</td>\n",
       "      <td>2013-04-25 13:54:45.017000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.31032</td>\n",
       "      <td>0.2712</td>\n",
       "      <td>0.2612</td>\n",
       "      <td>...</td>\n",
       "      <td>-27.92</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113926</th>\n",
       "      <td>E34333654295683286C35C2</td>\n",
       "      <td>28121</td>\n",
       "      <td>2006-08-01 10:31:31.143000000</td>\n",
       "      <td>E</td>\n",
       "      <td>36</td>\n",
       "      <td>Defaulted</td>\n",
       "      <td>2007-09-06 00:00:00</td>\n",
       "      <td>0.29776</td>\n",
       "      <td>0.2900</td>\n",
       "      <td>0.2850</td>\n",
       "      <td>...</td>\n",
       "      <td>-9.34</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2536.11</td>\n",
       "      <td>2536.10</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113927</th>\n",
       "      <td>E3433419834735803891976</td>\n",
       "      <td>322787</td>\n",
       "      <td>2008-04-30 21:25:19.670000000</td>\n",
       "      <td>AA</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2011-05-09 00:00:00</td>\n",
       "      <td>0.07469</td>\n",
       "      <td>0.0679</td>\n",
       "      <td>0.0579</td>\n",
       "      <td>...</td>\n",
       "      <td>-68.47</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113928</th>\n",
       "      <td>E34935176664905343E01EA</td>\n",
       "      <td>510097</td>\n",
       "      <td>2011-06-06 19:02:44.443000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2011-09-19 00:00:00</td>\n",
       "      <td>0.22362</td>\n",
       "      <td>0.1899</td>\n",
       "      <td>0.1799</td>\n",
       "      <td>...</td>\n",
       "      <td>-4.41</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113929</th>\n",
       "      <td>E3553583161337791FCB87F</td>\n",
       "      <td>830413</td>\n",
       "      <td>2013-07-06 17:40:01.657000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2014-02-07 00:00:00</td>\n",
       "      <td>0.30285</td>\n",
       "      <td>0.2639</td>\n",
       "      <td>0.2539</td>\n",
       "      <td>...</td>\n",
       "      <td>-6.54</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113930</th>\n",
       "      <td>E35D3584034795373BCD69A</td>\n",
       "      <td>831523</td>\n",
       "      <td>2013-07-08 10:24:49.700000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.20053</td>\n",
       "      <td>0.1639</td>\n",
       "      <td>0.1539</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.51</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113931</th>\n",
       "      <td>E36F36005339663245C20F8</td>\n",
       "      <td>1141292</td>\n",
       "      <td>2014-01-16 20:13:08.040000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.15016</td>\n",
       "      <td>0.1274</td>\n",
       "      <td>0.1174</td>\n",
       "      <td>...</td>\n",
       "      <td>-21.23</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113932</th>\n",
       "      <td>E6D9357655724827169606C</td>\n",
       "      <td>753087</td>\n",
       "      <td>2013-04-14 05:55:02.663000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.22354</td>\n",
       "      <td>0.1864</td>\n",
       "      <td>0.1764</td>\n",
       "      <td>...</td>\n",
       "      <td>-75.58</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113933</th>\n",
       "      <td>E6DB353036033497292EE43</td>\n",
       "      <td>537216</td>\n",
       "      <td>2011-11-03 20:42:55.333000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>FinalPaymentInProgress</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.13220</td>\n",
       "      <td>0.1110</td>\n",
       "      <td>0.1010</td>\n",
       "      <td>...</td>\n",
       "      <td>-30.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113934</th>\n",
       "      <td>E6E13596170052029692BB1</td>\n",
       "      <td>1069178</td>\n",
       "      <td>2013-12-13 05:49:12.703000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.23984</td>\n",
       "      <td>0.2150</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>...</td>\n",
       "      <td>-16.91</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113935</th>\n",
       "      <td>E6EB3531504622671970D9E</td>\n",
       "      <td>539056</td>\n",
       "      <td>2011-11-14 13:18:26.597000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>60</td>\n",
       "      <td>Completed</td>\n",
       "      <td>2013-08-13 00:00:00</td>\n",
       "      <td>0.28408</td>\n",
       "      <td>0.2605</td>\n",
       "      <td>0.2505</td>\n",
       "      <td>...</td>\n",
       "      <td>-235.05</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113936</th>\n",
       "      <td>E6ED3600409833199F711B7</td>\n",
       "      <td>1140093</td>\n",
       "      <td>2014-01-15 09:27:37.657000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.13189</td>\n",
       "      <td>0.1039</td>\n",
       "      <td>0.0939</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.70</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0000</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>113937 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",
       "2       0EE9337825851032864889A          81716  2007-01-05 15:00:47.090000000   \n",
       "3       0EF5356002482715299901A         658116  2012-10-22 11:02:35.010000000   \n",
       "4       0F023589499656230C5E3E2         909464  2013-09-14 18:38:39.097000000   \n",
       "5       0F05359734824199381F61D        1074836  2013-12-14 08:26:37.093000000   \n",
       "6       0F0A3576754255009D63151         750899  2013-04-12 09:52:56.147000000   \n",
       "7       0F1035772717087366F9EA7         768193  2013-05-05 06:49:27.493000000   \n",
       "8       0F043596202561788EA13D5        1023355  2013-12-02 10:43:39.117000000   \n",
       "9       0F043596202561788EA13D5        1023355  2013-12-02 10:43:39.117000000   \n",
       "10      0F123545674891886D9F106         587746  2012-05-10 07:04:01.577000000   \n",
       "11      0F1734025150298088A5F2B         213551  2007-10-09 20:28:33.640000000   \n",
       "12      0F1A3597143888805163EF7        1081604  2013-12-15 20:01:10.757000000   \n",
       "13      0F1C3583260311305D68F87         840820  2013-07-15 16:28:28.087000000   \n",
       "14      0F353575943675863D1AFC0         757359  2013-04-19 11:17:41.700000000   \n",
       "15      0F483544120452347F48121         577164  2012-04-10 09:14:46.297000000   \n",
       "16      0F4835843081468212F0892         841846  2013-07-16 12:42:48.680000000   \n",
       "17      0FDF336575182398852A8DC          31540  2006-08-15 12:21:09.433000000   \n",
       "18      0FF2357105361877390B58D         716058  2013-02-20 03:48:37.470000000   \n",
       "19      0FFC35866018516621B0D3F         875565  2013-08-21 06:49:02.093000000   \n",
       "20      101635959323992333B3C70        1011916  2013-11-22 11:35:02.987000000   \n",
       "21      1017340630713945364DA6B         241498  2007-11-30 20:33:49.227000000   \n",
       "22      101735700321773921526BF         706927  2013-01-30 09:36:13.783000000   \n",
       "23      101B35764008108187B2EBA         758964  2013-04-22 13:29:19.073000000   \n",
       "24      101B3596709094692AC79C0        1046345  2013-12-03 11:34:46.127000000   \n",
       "25      10223590888942486E3826E         950067  2013-10-02 14:31:09.157000000   \n",
       "26      0F4F3571508214190FD75CB         713131  2013-02-12 18:07:31.690000000   \n",
       "27      0F5034867864161084F3789         463083  2010-06-16 16:23:44.533000000   \n",
       "28      0F53359346357513247D86B         989519  2013-11-02 16:01:28.050000000   \n",
       "29      0F563597161095613517437        1051243  2013-12-17 09:18:33.220000000   \n",
       "...                         ...            ...                            ...   \n",
       "113907  C982359388882926442DE72        1005215  2013-11-09 06:55:05.690000000   \n",
       "113908  C9843500054876019D611A1         486057  2010-11-29 10:40:09.730000000   \n",
       "113909  C98635564651525938EB38E         635880  2012-09-08 10:34:38.837000000   \n",
       "113910  C9873600264828351437CAB        1161059  2014-01-24 19:56:49.960000000   \n",
       "113911  C9883594035073098BC5D51         996496  2013-11-15 11:42:47.540000000   \n",
       "113912  C98A3597264633447D66DF9        1083677  2013-12-16 16:36:00.990000000   \n",
       "113913  D2013482695428940FAD9E3         455673  2010-04-25 15:13:27.963000000   \n",
       "113914  D20533652658825353F6597          30223  2006-08-09 14:34:40.010000000   \n",
       "113915  D2053427325575423785798         374730  2008-07-29 05:22:29.390000000   \n",
       "113916  D2063562664602024E13D82         667047  2012-11-08 20:07:36.600000000   \n",
       "113917  D2063594229009539839457        1028126  2013-11-23 04:52:50.057000000   \n",
       "113918  D207342464194217591D1E1         353488  2008-06-19 12:02:53.300000000   \n",
       "113919  D20C3577637248543A1F80C         772509  2013-05-07 18:49:59.750000000   \n",
       "113920  D20E358076984586576526D         804763  2013-06-11 05:49:40.247000000   \n",
       "113921  D21A33647075665665BE266              4  2005-11-09 20:44:28.847000000   \n",
       "113922  D2293427338962159DA5143         379986  2008-08-08 16:58:54.760000000   \n",
       "113923  E334343080922352965DF86         395877  2008-09-10 08:26:30.537000000   \n",
       "113924  E340356181565702714DBCE         657862  2012-10-20 19:15:52.670000000   \n",
       "113925  E3423576946812123E4798D         760946  2013-04-25 13:54:45.017000000   \n",
       "113926  E34333654295683286C35C2          28121  2006-08-01 10:31:31.143000000   \n",
       "113927  E3433419834735803891976         322787  2008-04-30 21:25:19.670000000   \n",
       "113928  E34935176664905343E01EA         510097  2011-06-06 19:02:44.443000000   \n",
       "113929  E3553583161337791FCB87F         830413  2013-07-06 17:40:01.657000000   \n",
       "113930  E35D3584034795373BCD69A         831523  2013-07-08 10:24:49.700000000   \n",
       "113931  E36F36005339663245C20F8        1141292  2014-01-16 20:13:08.040000000   \n",
       "113932  E6D9357655724827169606C         753087  2013-04-14 05:55:02.663000000   \n",
       "113933  E6DB353036033497292EE43         537216  2011-11-03 20:42:55.333000000   \n",
       "113934  E6E13596170052029692BB1        1069178  2013-12-13 05:49:12.703000000   \n",
       "113935  E6EB3531504622671970D9E         539056  2011-11-14 13:18:26.597000000   \n",
       "113936  E6ED3600409833199F711B7        1140093  2014-01-15 09:27:37.657000000   \n",
       "\n",
       "       CreditGrade  Term              LoanStatus           ClosedDate  \\\n",
       "0                C    36               Completed  2009-08-14 00:00:00   \n",
       "1              NaN    36                 Current                  NaN   \n",
       "2               HR    36               Completed  2009-12-17 00:00:00   \n",
       "3              NaN    36                 Current                  NaN   \n",
       "4              NaN    36                 Current                  NaN   \n",
       "5              NaN    60                 Current                  NaN   \n",
       "6              NaN    36                 Current                  NaN   \n",
       "7              NaN    36                 Current                  NaN   \n",
       "8              NaN    36                 Current                  NaN   \n",
       "9              NaN    36                 Current                  NaN   \n",
       "10             NaN    60                 Current                  NaN   \n",
       "11               C    36               Completed  2008-01-07 00:00:00   \n",
       "12             NaN    36    Past Due (1-15 days)                  NaN   \n",
       "13             NaN    36                 Current                  NaN   \n",
       "14             NaN    60                 Current                  NaN   \n",
       "15             NaN    36               Defaulted  2012-12-19 00:00:00   \n",
       "16             NaN    60                 Current                  NaN   \n",
       "17              AA    36              Chargedoff  2008-05-22 00:00:00   \n",
       "18             NaN    36                 Current                  NaN   \n",
       "19             NaN    60                 Current                  NaN   \n",
       "20             NaN    36                 Current                  NaN   \n",
       "21               D    36               Completed  2010-12-12 00:00:00   \n",
       "22             NaN    36                 Current                  NaN   \n",
       "23             NaN    36               Defaulted  2013-12-26 00:00:00   \n",
       "24             NaN    36                 Current                  NaN   \n",
       "25             NaN    36                 Current                  NaN   \n",
       "26             NaN    60               Completed  2013-10-22 00:00:00   \n",
       "27             NaN    36               Completed  2013-07-03 00:00:00   \n",
       "28             NaN    36                 Current                  NaN   \n",
       "29             NaN    36                 Current                  NaN   \n",
       "...            ...   ...                     ...                  ...   \n",
       "113907         NaN    36                 Current                  NaN   \n",
       "113908         NaN    36               Completed  2011-01-31 00:00:00   \n",
       "113909         NaN    60                 Current                  NaN   \n",
       "113910         NaN    36                 Current                  NaN   \n",
       "113911         NaN    36                 Current                  NaN   \n",
       "113912         NaN    36                 Current                  NaN   \n",
       "113913         NaN    36               Completed  2013-05-05 00:00:00   \n",
       "113914          HR    36               Defaulted  2007-03-19 00:00:00   \n",
       "113915           D    36               Completed  2011-09-28 00:00:00   \n",
       "113916         NaN    36                 Current                  NaN   \n",
       "113917         NaN    36                 Current                  NaN   \n",
       "113918           A    36               Defaulted  2011-01-27 00:00:00   \n",
       "113919         NaN    36                 Current                  NaN   \n",
       "113920         NaN    36                 Current                  NaN   \n",
       "113921          AA    36               Completed  2005-11-25 00:00:00   \n",
       "113922           C    36               Completed  2011-08-19 00:00:00   \n",
       "113923           B    36               Completed  2011-09-23 00:00:00   \n",
       "113924         NaN    60                 Current                  NaN   \n",
       "113925         NaN    36                 Current                  NaN   \n",
       "113926           E    36               Defaulted  2007-09-06 00:00:00   \n",
       "113927          AA    36               Completed  2011-05-09 00:00:00   \n",
       "113928         NaN    36               Completed  2011-09-19 00:00:00   \n",
       "113929         NaN    36               Completed  2014-02-07 00:00:00   \n",
       "113930         NaN    36                 Current                  NaN   \n",
       "113931         NaN    60                 Current                  NaN   \n",
       "113932         NaN    36                 Current                  NaN   \n",
       "113933         NaN    36  FinalPaymentInProgress                  NaN   \n",
       "113934         NaN    60                 Current                  NaN   \n",
       "113935         NaN    60               Completed  2013-08-13 00:00:00   \n",
       "113936         NaN    36                 Current                  NaN   \n",
       "\n",
       "        BorrowerAPR  BorrowerRate  LenderYield    ...     LP_ServiceFees  \\\n",
       "0           0.16516        0.1580       0.1380    ...            -133.18   \n",
       "1           0.12016        0.0920       0.0820    ...               0.00   \n",
       "2           0.28269        0.2750       0.2400    ...             -24.20   \n",
       "3           0.12528        0.0974       0.0874    ...            -108.01   \n",
       "4           0.24614        0.2085       0.1985    ...             -60.27   \n",
       "5           0.15425        0.1314       0.1214    ...             -25.33   \n",
       "6           0.31032        0.2712       0.2612    ...             -22.95   \n",
       "7           0.23939        0.2019       0.1919    ...             -69.21   \n",
       "8           0.07620        0.0629       0.0529    ...             -16.77   \n",
       "9           0.07620        0.0629       0.0529    ...             -16.77   \n",
       "10          0.27462        0.2489       0.2389    ...            -214.04   \n",
       "11          0.15033        0.1325       0.1225    ...              -0.88   \n",
       "12          0.17969        0.1435       0.1335    ...              -3.40   \n",
       "13          0.13138        0.1034       0.0934    ...             -46.42   \n",
       "14          0.11695        0.0949       0.0849    ...            -138.07   \n",
       "15          0.35797        0.3177       0.3077    ...              -9.81   \n",
       "16          0.30748        0.2809       0.2709    ...             -23.01   \n",
       "17          0.13202        0.1250       0.1175    ...             -54.61   \n",
       "18          0.12528        0.0974       0.0874    ...            -121.47   \n",
       "19          0.24754        0.2225       0.2125    ...             -21.61   \n",
       "20          0.16732        0.1314       0.1214    ...             -34.11   \n",
       "21          0.21488        0.2075       0.1975    ...             -51.12   \n",
       "22          0.35356        0.3134       0.3034    ...             -35.80   \n",
       "23          0.28032        0.2419       0.2319    ...              -4.89   \n",
       "24          0.19859        0.1620       0.1520    ...              -6.72   \n",
       "25          0.30182        0.2629       0.2529    ...             -13.11   \n",
       "26          0.30748        0.2809       0.2709    ...             -25.81   \n",
       "27          0.11296        0.0920       0.0820    ...             -64.62   \n",
       "28          0.20268        0.1660       0.1560    ...             -22.56   \n",
       "29          0.15223        0.1239       0.1139    ...             -29.73   \n",
       "...             ...           ...          ...    ...                ...   \n",
       "113907      0.35356        0.3134       0.3034    ...              -9.99   \n",
       "113908      0.35858        0.3220       0.3120    ...             -11.02   \n",
       "113909      0.27554        0.2498       0.2398    ...             -78.65   \n",
       "113910      0.32446        0.2850       0.2750    ...              -3.29   \n",
       "113911      0.25330        0.2155       0.2055    ...             -24.69   \n",
       "113912      0.06726        0.0605       0.0505    ...              -7.15   \n",
       "113913      0.12410        0.1030       0.0930    ...            -129.82   \n",
       "113914      0.25757        0.2500       0.2450    ...              -2.43   \n",
       "113915      0.22237        0.2000       0.1900    ...             -51.71   \n",
       "113916      0.33286        0.2932       0.2832    ...             -43.14   \n",
       "113917      0.32446        0.2850       0.2750    ...              -9.80   \n",
       "113918      0.12201        0.1080       0.0980    ...            -103.49   \n",
       "113919      0.27285        0.2346       0.2246    ...             -25.59   \n",
       "113920      0.35356        0.3134       0.3034    ...             -25.39   \n",
       "113921          NaN        0.0400       0.0350    ...              -0.88   \n",
       "113922      0.15094        0.1295       0.1195    ...             -81.95   \n",
       "113923      0.22378        0.2089       0.1989    ...            -135.50   \n",
       "113924      0.17317        0.1499       0.1399    ...             -60.83   \n",
       "113925      0.31032        0.2712       0.2612    ...             -27.92   \n",
       "113926      0.29776        0.2900       0.2850    ...              -9.34   \n",
       "113927      0.07469        0.0679       0.0579    ...             -68.47   \n",
       "113928      0.22362        0.1899       0.1799    ...              -4.41   \n",
       "113929      0.30285        0.2639       0.2539    ...              -6.54   \n",
       "113930      0.20053        0.1639       0.1539    ...             -16.51   \n",
       "113931      0.15016        0.1274       0.1174    ...             -21.23   \n",
       "113932      0.22354        0.1864       0.1764    ...             -75.58   \n",
       "113933      0.13220        0.1110       0.1010    ...             -30.05   \n",
       "113934      0.23984        0.2150       0.2050    ...             -16.91   \n",
       "113935      0.28408        0.2605       0.2505    ...            -235.05   \n",
       "113936      0.13189        0.1039       0.0939    ...              -1.70   \n",
       "\n",
       "        LP_CollectionFees  LP_GrossPrincipalLoss  LP_NetPrincipalLoss  \\\n",
       "0                    0.00                   0.00                 0.00   \n",
       "1                    0.00                   0.00                 0.00   \n",
       "2                    0.00                   0.00                 0.00   \n",
       "3                    0.00                   0.00                 0.00   \n",
       "4                    0.00                   0.00                 0.00   \n",
       "5                    0.00                   0.00                 0.00   \n",
       "6                    0.00                   0.00                 0.00   \n",
       "7                    0.00                   0.00                 0.00   \n",
       "8                    0.00                   0.00                 0.00   \n",
       "9                    0.00                   0.00                 0.00   \n",
       "10                   0.00                   0.00                 0.00   \n",
       "11                   0.00                   0.00                 0.00   \n",
       "12                   0.00                   0.00                 0.00   \n",
       "13                   0.00                   0.00                 0.00   \n",
       "14                   0.00                   0.00                 0.00   \n",
       "15                   0.00                3790.25              3790.25   \n",
       "16                   0.00                   0.00                 0.00   \n",
       "17                   0.00                6012.65              6012.67   \n",
       "18                   0.00                   0.00                 0.00   \n",
       "19                   0.00                   0.00                 0.00   \n",
       "20                   0.00                   0.00                 0.00   \n",
       "21                   0.00                   0.00                 0.00   \n",
       "22                   0.00                   0.00                 0.00   \n",
       "23                   0.00                1882.27              1882.27   \n",
       "24                   0.00                   0.00                 0.00   \n",
       "25                   0.00                   0.00                 0.00   \n",
       "26                   0.00                   0.00                 0.00   \n",
       "27                   0.00                   0.00                 0.00   \n",
       "28                   0.00                   0.00                 0.00   \n",
       "29                   0.00                   0.00                 0.00   \n",
       "...                   ...                    ...                  ...   \n",
       "113907               0.00                   0.00                 0.00   \n",
       "113908               0.00                   0.00                 0.00   \n",
       "113909               0.00                   0.00                 0.00   \n",
       "113910               0.00                   0.00                 0.00   \n",
       "113911               0.00                   0.00                 0.00   \n",
       "113912               0.00                   0.00                 0.00   \n",
       "113913               0.00                   0.00                 0.00   \n",
       "113914               0.00                2883.01              2883.00   \n",
       "113915             -37.64                   0.00                 0.00   \n",
       "113916               0.00                   0.00                 0.00   \n",
       "113917               0.00                   0.00                 0.00   \n",
       "113918               0.00                2176.53              2176.51   \n",
       "113919               0.00                   0.00                 0.00   \n",
       "113920               0.00                   0.00                 0.00   \n",
       "113921               0.00                   0.00                 0.00   \n",
       "113922               0.00                   0.00                 0.00   \n",
       "113923               0.00                   0.00                 0.00   \n",
       "113924               0.00                   0.00                 0.00   \n",
       "113925               0.00                   0.00                 0.00   \n",
       "113926               0.00                2536.11              2536.10   \n",
       "113927               0.00                   0.00                 0.00   \n",
       "113928               0.00                   0.00                 0.00   \n",
       "113929               0.00                   0.00                 0.00   \n",
       "113930               0.00                   0.00                 0.00   \n",
       "113931               0.00                   0.00                 0.00   \n",
       "113932               0.00                   0.00                 0.00   \n",
       "113933               0.00                   0.00                 0.00   \n",
       "113934               0.00                   0.00                 0.00   \n",
       "113935               0.00                   0.00                 0.00   \n",
       "113936               0.00                   0.00                 0.00   \n",
       "\n",
       "       LP_NonPrincipalRecoverypayments  PercentFunded  Recommendations  \\\n",
       "0                                 0.00         1.0000                0   \n",
       "1                                 0.00         1.0000                0   \n",
       "2                                 0.00         1.0000                0   \n",
       "3                                 0.00         1.0000                0   \n",
       "4                                 0.00         1.0000                0   \n",
       "5                                 0.00         1.0000                0   \n",
       "6                                 0.00         1.0000                0   \n",
       "7                                 0.00         1.0000                0   \n",
       "8                                 0.00         1.0000                0   \n",
       "9                                 0.00         1.0000                0   \n",
       "10                                0.00         1.0000                0   \n",
       "11                                0.00         1.0000                0   \n",
       "12                                0.00         1.0000                0   \n",
       "13                                0.00         1.0000                0   \n",
       "14                                0.00         0.7731                0   \n",
       "15                                0.00         1.0000                0   \n",
       "16                                0.00         1.0000                0   \n",
       "17                              268.96         1.0000                0   \n",
       "18                                0.00         1.0000                0   \n",
       "19                                0.00         1.0000                0   \n",
       "20                                0.00         1.0000                0   \n",
       "21                                0.00         1.0000                0   \n",
       "22                                0.00         1.0000                0   \n",
       "23                                0.00         1.0000                0   \n",
       "24                                0.00         1.0000                0   \n",
       "25                                0.00         1.0000                0   \n",
       "26                                0.00         1.0000                0   \n",
       "27                                0.00         1.0000                0   \n",
       "28                                0.00         1.0000                0   \n",
       "29                                0.00         1.0000                0   \n",
       "...                                ...            ...              ...   \n",
       "113907                            0.00         1.0000                0   \n",
       "113908                            0.00         1.0000                0   \n",
       "113909                            0.00         1.0000                0   \n",
       "113910                            0.00         1.0000                0   \n",
       "113911                            0.00         1.0000                0   \n",
       "113912                            0.00         1.0000                0   \n",
       "113913                            0.00         1.0000                0   \n",
       "113914                            0.00         1.0000                0   \n",
       "113915                            0.00         1.0000                1   \n",
       "113916                            0.00         1.0000                0   \n",
       "113917                            0.00         1.0000                0   \n",
       "113918                            0.00         1.0000                0   \n",
       "113919                            0.00         1.0000                0   \n",
       "113920                            0.00         1.0000                0   \n",
       "113921                            0.00         1.0000                0   \n",
       "113922                            0.00         1.0000                0   \n",
       "113923                            0.00         1.0000                0   \n",
       "113924                            0.00         1.0000                1   \n",
       "113925                            0.00         1.0000                0   \n",
       "113926                            0.00         1.0000                0   \n",
       "113927                            0.00         1.0000                2   \n",
       "113928                            0.00         1.0000                0   \n",
       "113929                            0.00         1.0000                0   \n",
       "113930                            0.00         1.0000                0   \n",
       "113931                            0.00         1.0000                0   \n",
       "113932                            0.00         1.0000                0   \n",
       "113933                            0.00         1.0000                0   \n",
       "113934                            0.00         1.0000                0   \n",
       "113935                            0.00         1.0000                0   \n",
       "113936                            0.00         1.0000                0   \n",
       "\n",
       "       InvestmentFromFriendsCount InvestmentFromFriendsAmount Investors  \n",
       "0                               0                         0.0       258  \n",
       "1                               0                         0.0         1  \n",
       "2                               0                         0.0        41  \n",
       "3                               0                         0.0       158  \n",
       "4                               0                         0.0        20  \n",
       "5                               0                         0.0         1  \n",
       "6                               0                         0.0         1  \n",
       "7                               0                         0.0         1  \n",
       "8                               0                         0.0         1  \n",
       "9                               0                         0.0         1  \n",
       "10                              0                         0.0        19  \n",
       "11                              0                         0.0        53  \n",
       "12                              0                         0.0         1  \n",
       "13                              0                         0.0       171  \n",
       "14                              0                         0.0       371  \n",
       "15                              0                         0.0        10  \n",
       "16                              0                         0.0         8  \n",
       "17                              0                         0.0        85  \n",
       "18                              0                         0.0       303  \n",
       "19                              0                         0.0         1  \n",
       "20                              0                         0.0         1  \n",
       "21                              0                         0.0        53  \n",
       "22                              0                         0.0        94  \n",
       "23                              0                         0.0        30  \n",
       "24                              0                         0.0         1  \n",
       "25                              0                         0.0         3  \n",
       "26                              0                         0.0        37  \n",
       "27                              0                         0.0       121  \n",
       "28                              0                         0.0         1  \n",
       "29                              0                         0.0         1  \n",
       "...                           ...                         ...       ...  \n",
       "113907                          0                         0.0         3  \n",
       "113908                          0                         0.0        98  \n",
       "113909                          0                         0.0         9  \n",
       "113910                          0                         0.0         1  \n",
       "113911                          0                         0.0         1  \n",
       "113912                          0                         0.0         1  \n",
       "113913                          0                         0.0       265  \n",
       "113914                          0                         0.0         1  \n",
       "113915                          0                         0.0       135  \n",
       "113916                          0                         0.0        87  \n",
       "113917                          0                         0.0         1  \n",
       "113918                          0                         0.0       173  \n",
       "113919                          0                         0.0         1  \n",
       "113920                          0                         0.0         1  \n",
       "113921                          0                         0.0         1  \n",
       "113922                          0                         0.0       145  \n",
       "113923                          0                         0.0       270  \n",
       "113924                          0                         0.0        83  \n",
       "113925                          0                         0.0         1  \n",
       "113926                          0                         0.0        39  \n",
       "113927                          0                         0.0       194  \n",
       "113928                          0                         0.0        25  \n",
       "113929                          0                         0.0        26  \n",
       "113930                          0                         0.0        52  \n",
       "113931                          0                         0.0         1  \n",
       "113932                          0                         0.0         1  \n",
       "113933                          0                         0.0        22  \n",
       "113934                          0                         0.0       119  \n",
       "113935                          0                         0.0       274  \n",
       "113936                          0                         0.0         1  \n",
       "\n",
       "[113937 rows x 81 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read the dataframe\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# drop irrelevant columns for our investigation \n",
    "df.drop([\"ListingKey\", \"ListingNumber\", \"LoanKey\", \"LoanNumber\", \"ListingCreationDate\", \n",
    "         \"ClosedDate\", \"DateCreditPulled\", \"MemberKey\", \n",
    "         \"LoanCurrentDaysDelinquent\", \"LoanFirstDefaultedCycleNumber\", \"LoanMonthsSinceOrigination\", \"LP_CustomerPayments\",\n",
    "         \"LP_CustomerPrincipalPayments\", \"LP_InterestandFees\", \"LP_ServiceFees\", \"LP_CollectionFees\", \"LP_GrossPrincipalLoss\",\n",
    "         \"LP_NetPrincipalLoss\", \"LP_NonPrincipalRecoverypayments\", \"PercentFunded\", \"Recommendations\",\n",
    "         \"InvestmentFromFriendsCount\", \"InvestmentFromFriendsAmount\", \"CurrentlyInGroup\",\"TotalCreditLinespast7years\",\n",
    "        \"OpenRevolvingAccounts\", \"OpenRevolvingMonthlyPayment\", \"InquiriesLast6Months\", \"TotalInquiries\",\n",
    "        \"DelinquenciesLast7Years\", \"PublicRecordsLast10Years\", \"PublicRecordsLast12Months\", \"IncomeVerifiable\", \n",
    "        \"TradesOpenedLast6Months\", \"IsBorrowerHomeowner\"], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# rename the columens that have () to avoid any issue when refering to them\n",
    "df.rename(columns={'ProsperRating (numeric)': 'ProsperRatingNumeric', \n",
    "                   'ProsperRating (Alpha)': 'ProsperRatingAlpha', \n",
    "                   'ListingCategory (numeric)': 'ListingCategory',\n",
    "                   'TradesNeverDelinquent (percentage)': 'TradesNeverDelinquent'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# rename BorrowerRate to InterestRate \n",
    "df.rename(columns={'BorrowerRate': 'InterestRate'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 113937 entries, 0 to 113936\n",
      "Data columns (total 46 columns):\n",
      "CreditGrade                            28953 non-null object\n",
      "Term                                   113937 non-null int64\n",
      "LoanStatus                             113937 non-null object\n",
      "BorrowerAPR                            113912 non-null float64\n",
      "InterestRate                           113937 non-null float64\n",
      "LenderYield                            113937 non-null float64\n",
      "EstimatedEffectiveYield                84853 non-null float64\n",
      "EstimatedLoss                          84853 non-null float64\n",
      "EstimatedReturn                        84853 non-null float64\n",
      "ProsperRatingNumeric                   84853 non-null float64\n",
      "ProsperRatingAlpha                     84853 non-null object\n",
      "ProsperScore                           84853 non-null float64\n",
      "ListingCategory                        113937 non-null int64\n",
      "BorrowerState                          108422 non-null object\n",
      "Occupation                             110349 non-null object\n",
      "EmploymentStatus                       111682 non-null object\n",
      "EmploymentStatusDuration               106312 non-null float64\n",
      "GroupKey                               13341 non-null object\n",
      "CreditScoreRangeLower                  113346 non-null float64\n",
      "CreditScoreRangeUpper                  113346 non-null float64\n",
      "FirstRecordedCreditLine                113240 non-null object\n",
      "CurrentCreditLines                     106333 non-null float64\n",
      "OpenCreditLines                        106333 non-null float64\n",
      "CurrentDelinquencies                   113240 non-null float64\n",
      "AmountDelinquent                       106315 non-null float64\n",
      "RevolvingCreditBalance                 106333 non-null float64\n",
      "BankcardUtilization                    106333 non-null float64\n",
      "AvailableBankcardCredit                106393 non-null float64\n",
      "TotalTrades                            106393 non-null float64\n",
      "TradesNeverDelinquent                  106393 non-null float64\n",
      "DebtToIncomeRatio                      105383 non-null float64\n",
      "IncomeRange                            113937 non-null object\n",
      "StatedMonthlyIncome                    113937 non-null float64\n",
      "TotalProsperLoans                      22085 non-null float64\n",
      "TotalProsperPaymentsBilled             22085 non-null float64\n",
      "OnTimeProsperPayments                  22085 non-null float64\n",
      "ProsperPaymentsLessThanOneMonthLate    22085 non-null float64\n",
      "ProsperPaymentsOneMonthPlusLate        22085 non-null float64\n",
      "ProsperPrincipalBorrowed               22085 non-null float64\n",
      "ProsperPrincipalOutstanding            22085 non-null float64\n",
      "ScorexChangeAtTimeOfListing            18928 non-null float64\n",
      "LoanOriginalAmount                     113937 non-null int64\n",
      "LoanOriginationDate                    113937 non-null object\n",
      "LoanOriginationQuarter                 113937 non-null object\n",
      "MonthlyLoanPayment                     113937 non-null float64\n",
      "Investors                              113937 non-null int64\n",
      "dtypes: float64(31), int64(4), object(11)\n",
      "memory usage: 40.0+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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>CreditGrade</th>\n",
       "      <th>Term</th>\n",
       "      <th>LoanStatus</th>\n",
       "      <th>BorrowerAPR</th>\n",
       "      <th>InterestRate</th>\n",
       "      <th>LenderYield</th>\n",
       "      <th>EstimatedEffectiveYield</th>\n",
       "      <th>EstimatedLoss</th>\n",
       "      <th>EstimatedReturn</th>\n",
       "      <th>ProsperRatingNumeric</th>\n",
       "      <th>...</th>\n",
       "      <th>ProsperPaymentsLessThanOneMonthLate</th>\n",
       "      <th>ProsperPaymentsOneMonthPlusLate</th>\n",
       "      <th>ProsperPrincipalBorrowed</th>\n",
       "      <th>ProsperPrincipalOutstanding</th>\n",
       "      <th>ScorexChangeAtTimeOfListing</th>\n",
       "      <th>LoanOriginalAmount</th>\n",
       "      <th>LoanOriginationDate</th>\n",
       "      <th>LoanOriginationQuarter</th>\n",
       "      <th>MonthlyLoanPayment</th>\n",
       "      <th>Investors</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>C</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>0.16516</td>\n",
       "      <td>0.1580</td>\n",
       "      <td>0.1380</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9425</td>\n",
       "      <td>2007-09-12 00:00:00</td>\n",
       "      <td>Q3 2007</td>\n",
       "      <td>330.43</td>\n",
       "      <td>258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>0.12016</td>\n",
       "      <td>0.0920</td>\n",
       "      <td>0.0820</td>\n",
       "      <td>0.07960</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>0.05470</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000</td>\n",
       "      <td>2014-03-03 00:00:00</td>\n",
       "      <td>Q1 2014</td>\n",
       "      <td>318.93</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>HR</td>\n",
       "      <td>36</td>\n",
       "      <td>Completed</td>\n",
       "      <td>0.28269</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.2400</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3001</td>\n",
       "      <td>2007-01-17 00:00:00</td>\n",
       "      <td>Q1 2007</td>\n",
       "      <td>123.32</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>0.12528</td>\n",
       "      <td>0.0974</td>\n",
       "      <td>0.0874</td>\n",
       "      <td>0.08490</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>0.06000</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10000</td>\n",
       "      <td>2012-11-01 00:00:00</td>\n",
       "      <td>Q4 2012</td>\n",
       "      <td>321.45</td>\n",
       "      <td>158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>36</td>\n",
       "      <td>Current</td>\n",
       "      <td>0.24614</td>\n",
       "      <td>0.2085</td>\n",
       "      <td>0.1985</td>\n",
       "      <td>0.18316</td>\n",
       "      <td>0.0925</td>\n",
       "      <td>0.09066</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>9947.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15000</td>\n",
       "      <td>2013-09-20 00:00:00</td>\n",
       "      <td>Q3 2013</td>\n",
       "      <td>563.97</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 46 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  CreditGrade  Term LoanStatus  BorrowerAPR  InterestRate  LenderYield  \\\n",
       "0           C    36  Completed      0.16516        0.1580       0.1380   \n",
       "1         NaN    36    Current      0.12016        0.0920       0.0820   \n",
       "2          HR    36  Completed      0.28269        0.2750       0.2400   \n",
       "3         NaN    36    Current      0.12528        0.0974       0.0874   \n",
       "4         NaN    36    Current      0.24614        0.2085       0.1985   \n",
       "\n",
       "   EstimatedEffectiveYield  EstimatedLoss  EstimatedReturn  \\\n",
       "0                      NaN            NaN              NaN   \n",
       "1                  0.07960         0.0249          0.05470   \n",
       "2                      NaN            NaN              NaN   \n",
       "3                  0.08490         0.0249          0.06000   \n",
       "4                  0.18316         0.0925          0.09066   \n",
       "\n",
       "   ProsperRatingNumeric    ...     ProsperPaymentsLessThanOneMonthLate  \\\n",
       "0                   NaN    ...                                     NaN   \n",
       "1                   6.0    ...                                     NaN   \n",
       "2                   NaN    ...                                     NaN   \n",
       "3                   6.0    ...                                     NaN   \n",
       "4                   3.0    ...                                     0.0   \n",
       "\n",
       "   ProsperPaymentsOneMonthPlusLate  ProsperPrincipalBorrowed  \\\n",
       "0                              NaN                       NaN   \n",
       "1                              NaN                       NaN   \n",
       "2                              NaN                       NaN   \n",
       "3                              NaN                       NaN   \n",
       "4                              0.0                   11000.0   \n",
       "\n",
       "  ProsperPrincipalOutstanding ScorexChangeAtTimeOfListing LoanOriginalAmount  \\\n",
       "0                         NaN                         NaN               9425   \n",
       "1                         NaN                         NaN              10000   \n",
       "2                         NaN                         NaN               3001   \n",
       "3                         NaN                         NaN              10000   \n",
       "4                      9947.9                         NaN              15000   \n",
       "\n",
       "   LoanOriginationDate LoanOriginationQuarter  MonthlyLoanPayment  Investors  \n",
       "0  2007-09-12 00:00:00                Q3 2007              330.43        258  \n",
       "1  2014-03-03 00:00:00                Q1 2014              318.93          1  \n",
       "2  2007-01-17 00:00:00                Q1 2007              123.32         41  \n",
       "3  2012-11-01 00:00:00                Q4 2012              321.45        158  \n",
       "4  2013-09-20 00:00:00                Q3 2013              563.97         20  \n",
       "\n",
       "[5 rows x 46 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Prosper Loan Data Exploration\n",
    "\n",
    "### Dataset Overview\n",
    "\n",
    "The data set contains 113,937 records of loans along with 81 variables on each loan. After dropping some irrelevant features of our investigation, we have only 46 variables. The data set includes 31 float, 4 int, and 11 object variables.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "### Investigation Overview\n",
    "\n",
    "The main features we will investigate in this project are associated directly with answering the following questions: \n",
    "- What factors affect users ability to get a loan?\n",
    "- What factors impact a high prosper loan risk?\n",
    "- What features affects the borrower’s APR or interest rate?\n",
    "- Are there differences between loans depending on how large the original loan amount was?\n",
    "\n",
    "These answers associated with many features but mainly 'CreditGrade', 'Term','BorrowerAPR', 'InterestRate', 'ProsperRatingAlpha', 'LoanStatus' and 'LoanOriginalAmount'."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Univariate Exploration\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "First, I'm going to investigate Loan Status feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Current                   56576\n",
       "Completed                 38074\n",
       "Chargedoff                11992\n",
       "Defaulted                  5018\n",
       "Past Due (1-15 days)        806\n",
       "Past Due (31-60 days)       363\n",
       "Past Due (61-90 days)       313\n",
       "Past Due (91-120 days)      304\n",
       "Past Due (16-30 days)       265\n",
       "FinalPaymentInProgress      205\n",
       "Past Due (>120 days)         16\n",
       "Cancelled                     5\n",
       "Name: LoanStatus, dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['LoanStatus'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a1ce8e860>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "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": [
    "base_color = sb.color_palette()[0]\n",
    "order = df['LoanStatus'].value_counts().index\n",
    "sb.countplot(data = df, y = 'LoanStatus', color = base_color, order=order)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> The distribution is not clear, therefore I'm going to use the log function to balance the scale and show the distribution more clearly. Also, I'm going to combine the past due category into one category, add in progress category to current and drop cancelled because this will be more relevant for our analysis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Current       56781\n",
       "Completed     38074\n",
       "Chargedoff    11992\n",
       "Defaulted      5018\n",
       "Past Due       2067\n",
       "Name: LoanStatus, dtype: int64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# replace categories\n",
    "df.LoanStatus.replace(('Past Due (1-15 days)','Past Due (31-60 days)', 'Past Due (61-90 days)','Past Due (16-30 days)'\n",
    "                       ,'Past Due (91-120 days)', 'Past Due (>120 days)')\n",
    "                      ,('Past Due'), inplace=True)\n",
    "\n",
    "df.LoanStatus.replace(('FinalPaymentInProgress'),('Current'), inplace=True)\n",
    "\n",
    "# drop cancelled records\n",
    "df = df[df.LoanStatus != 'Cancelled']\n",
    "\n",
    "# check changes\n",
    "df['LoanStatus'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "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": [
    "# bar chart \n",
    "plt.figure(figsize = [15, 5])\n",
    "order = df['LoanStatus'].value_counts().index\n",
    "plt.xscale('log')\n",
    "plt.title('Loan Status count')\n",
    "ax = sb.countplot(data = df, y = 'LoanStatus', color = '#ff6666', order=order)\n",
    "sb.set()\n",
    "x=[10, 100, 1000, 10000, 90000]\n",
    "plt.xticks(x,x)\n",
    "\n",
    "# Source https://robertmitchellv.com/blog-bar-chart-annotations-pandas-mpl.html\n",
    "# https://matplotlib.org/api/text_api.html?highlight=get_text#matplotlib.text.Text\n",
    "# list to collect plt.patches data\n",
    "totals = []\n",
    "\n",
    "# add values to the list\n",
    "for i in ax.patches:\n",
    "    totals.append(i.get_width())\n",
    "\n",
    "total = sum(totals)\n",
    "\n",
    "# loop to print the %\n",
    "for i in ax.patches:\n",
    "    ax.text(i.get_width()+.3, i.get_y()+0.38, \\\n",
    "            str(round((i.get_width()/total)*100, 2))+'%', fontsize=12,\n",
    "color='r')\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "After the transformation of loan statues feature, the current loan statues ranked first with 49.84% while past due ranked last with only 1.81%. Prosper completed loan statues were equal to 33.42% which represented a positive users commitment.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [10, 5])\n",
    "plt.title('Loan Risk Factor Distrbution')\n",
    "order = df['ProsperRatingAlpha'].value_counts().index\n",
    "ax = sb.countplot(data = df, x = 'ProsperRatingAlpha', order=order, color='#999999')\n",
    "plt.xlabel('Risk Category')\n",
    "sb.set();\n",
    "\n",
    "# representing %\n",
    "totals = []\n",
    "\n",
    "for i in ax.patches:\n",
    "    totals.append(i.get_height())\n",
    "\n",
    "total = sum(totals)\n",
    "\n",
    "for i in ax.patches:\n",
    "    ax.text(i.get_x()+.12, i.get_height()-3, \\\n",
    "            str(round((i.get_height()/total)*100, 2))+'%', fontsize=12,\n",
    "                color='#999999')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "The bar graph above demonstrates the prosper risk factor distribution. The graph shows 21.62% of loans were under C risk category, 18.36% under B and 17.15% under A. All the higher ranked categories A, B & C has risk from 9-18% based on prosper predefined rules which considered as a reasonable risk, not a higher risk. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [10, 5])\n",
    "plt.title('Income Range Distrbution')\n",
    "order = df['IncomeRange'].value_counts().index\n",
    "ax = sb.countplot(data = df, y = 'IncomeRange', order=order, color='#eee888')\n",
    "plt.ylabel('Income Range')\n",
    "sb.set();\n",
    "totals = []\n",
    "\n",
    "# add values to the list\n",
    "for i in ax.patches:\n",
    "    totals.append(i.get_width())\n",
    "\n",
    "total = sum(totals)\n",
    "\n",
    "# loop to print the %\n",
    "for i in ax.patches:\n",
    "    ax.text(i.get_width()+.3, i.get_y()+0.38, \\\n",
    "            str(round((i.get_width()/total)*100, 2))+'%', fontsize=10,\n",
    "color='g')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> The graph shows that 28.25% of prosper loans beneficial had from 25000 to 49999 dollars income range while 27.25% had a range of around 50000-74999 dollars.\n",
    "\n",
    "Now, let's investigate borrower state variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [20, 10])\n",
    "plt.title('Borrower State Distrbution')\n",
    "order = df['BorrowerState'].value_counts().index\n",
    "sb.countplot(data = df, x = 'BorrowerState', order=order, color='#ff6666')\n",
    "plt.xlabel('Borrower State')\n",
    "sb.set();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "The graph shows that CA is the top state of borrowing prosper loans among all the state followed by TX, NY, and FL with a slight difference among them. On the other hand, IA, WY, ME and ND were the least state in borrowing prosper loans. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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9ezfNmjXD2dkZgE6dOvHBBx9k6+fUqVOcPXuW/v37m48ZDAZsbW2pXbs2b731Fs2bN6dXr164ubnRtGlTxo8fz5YtW/D09KRZs2bZ+tuxYwcfffQRACVKlKB58+bs2rWLokWLUrt2bYoWLQpAuXLlSElJoX79+hQvXpzvvvuOEydOcOrUKW7cuJE7kyYiIiLyBFO4/gf+vOb6bg4ODgAYjcZsx00mE5mZmdmOGY1GnnvuOXNfWVlZJCUlAfDpp5/y66+/8tNPP/Hvf/+bjz/+mFatWlG7dm1++OEHFixYwObNm5k4cWK2Mf48ZlZWVra6AGxsbDCZTGzatInZs2fTvXt32rdvzx9//HFPHyIiIiLyaFoWksvq169PXFwcV69eBW7vEOLu7p7tnAoVKpCSksKePXsAiIiIYPjw4Vy5cgUvLy9efvll3nnnHRo2bMjRo0cZOnQoBw4cICAggHfeeYfDhw9n68/Dw4OVK1cCcOXKFTZt2kT9+vUfWOP27dtp3bo1/v7+PPPMM+zcudMcxkVEREQk53TnOpdVqVKFt99+m8DAQDIyMqhevTrjxo3Ldo69vT2zZs1i0qRJ3Lp1i6JFizJ16lRKlChBp06deOuttyhSpAjly5fH39+fevXq8Z///Id58+ZRuHBhQkJCsvU3cOBAQkJC8PHxISsri379+lG9enWOHj163xo7dOjA8OHDiY6OpnDhwtSpU4eEhITcmhIRERGRJ5aNSb//FwsLDw/HYDDkdRkiYgVBQUFcvnw9V8dwdXXK9TEkO8259WnOrc/V1SlX+tWyEBERERERC1G4FhERERGxEIVrERERERELUbgWEREREbEQhWsREREREQvRVnxicV26dMnrEkTEStLTM/K6BBGRx4rCtVhccrIBo1E7PFqLtm+yLs23iIg8jJaFiIiIiIhYiMK1iIiIiIiFKFyLiIiIiFiIwrWIiIiIiIXogUaxOBeXonldwhMhPT2DlJS0vC5DRERE/gKFa7G48PBwDAZDXpeR7wUFBQEK1yIiIvmJloWIiIiIiFiIwrWIiIiIiIUoXIuIiIiIWIjCtYiIiIiIhShci4iIiIhYiNV2CzEYDMyYMYPdu3dja2vLM888Q3BwMNWrV7dWCWY//PADp06dolevXn+r/Zw5c1i6dCklS5YEIC0tjVatWvHuu+9askwRERERyWesEq6NRiN9+/bF3d2d1atXY2dnx44dO+jbty/R0dE4OztbowyzgwcP/uM+AgICGDx4MAA3btzAy8uLunXr0rhx43/ct4iIiIjkT1YJ1zt37uTChQsMGTKEQoVur0Tx8PBg8uTJGI1GAD7//HPWrl2Lra0tDRs2ZMSIEVy4cIGBAwdSoUIFjh8/TrVq1ahduzarVq0iJSWFefPmUbFiRTw9PWnVqhXbtm0D4KOPPqJatWoEBgYyaNAg3N3dSUhIoHv37oSFhbF06VIAypQpQ6tWrRg/fjzHjh0jKyuLvn374u3tTWRkJKtWreLq1as0a9aMYcOGPfD6nnrqKWrWrMmxY8ewt7dn+vTpGI1GKlWqREhICKNHj+bo0aPY2NjQp08f2rZtS0ZGBh9++CG//PILbm5u2NjYMGDAAIBs7YcNG8aoUaO4fv06ly5dol27drzzzjtERkayefNmrl69yqVLlwgICODcuXPs2LGD4sWL89VXX3H58uUczd/+/fuZPHkyaWlpODs7M27cOMqVK0dgYCDFihXj2LFjzJw5k6pVq+bmPxMRERGRfM8q4frw4cNUqVLFHKzvaNq0KQA//vgjcXFxREREULhwYQYPHszSpUtp2rQpR48eZfLkyVSpUoWWLVtSqlQpli1bxty5c1m2bBmjRo0Cbgfc1atXExcXx8iRI4mKirpvLS+99BIBAQEA+Pv78/HHH1O9enWmTp2KwWAgICCAWrVqAZCYmEhMTAx2dg+fpnPnzrF371569OhBZmYmp06d4ocffsDJyYlp06bh7OzMunXruHLlCh06dKBKlSrs3r2bmzdv8v3333P+/Hl8fHzM/d3d/uuvv8bb25t27dpx/fp1mjZtSmBgIAAHDhwgKiqKlJQUPD09+eqrr/jPf/5DYGAgW7ZsoUqVKo+cv+HDhzN69Gg+//xzypQpw5YtWxgzZgwLFiwAoHLlysydO/cv/o2LiIiIFExWCdeFChXCwcHhgd/v2LGDNm3aUKRIEeB26F29ejVNmzalZMmSVKtWDYBnn32W119/Hbh91zkhIcHcR8eOHQHw9PQkODiYK1eu5Ki2bdu2kZaWRkREBHB7icexY8cAqFat2gOD9dKlS9m4cSNGoxFbW1v69evHa6+9xs6dOylfvjxOTk7ma/voo48AKFGiBM2bN2fXrl1s27aNjh07YmNjQ9myZc3XBWRr36dPH3bs2MHXX3/NsWPHyMjI4ObNmwDUqVOHokWLUrTo7deN3+mjbNmyXLt2DeCR83fq1CnOnj1L//79zePf/XbFmjVr5mgeRURERMRK4bpGjRqEh4djMpmwsbExHw8NDaVBgwbmpSF3y8zMBMDe3j7bcVtb2/uOcXcIvhN4AUwmU7b+/sxoNDJ9+nTzg5VJSUkUK1aMqKgoHB0dH3hNd6+5/rO7290Z/+7PWVlZ2Nra3ve6/9x+ypQpnD17Fm9vb1q0aMG2bdvMfRYuXDhbu/v9IPCo+TMajTz33HOsWbMGgKysLJKSku5bi4iIiIg8nFW24qtbty4uLi7MnTuXrKwsALZs2UJkZCQvvfQSHh4eREdHk5aWRmZmJhEREXh4ePylMaKjowHYsGEDFStWpFixYjg7O3P8+HEANm7caD7X1tbWHLY9PDxYsmQJAJcuXcLX15cLFy7842u+w8PDg5UrVwJw5coVNm3aRP369WnQoAExMTGYTCYSExPZtWtXth887ti6dSt9+vShdevWnDx5ksTExAeG8r+jQoUKpKSksGfPHgAiIiIYPny4xfoXERERKUiscufaxsaGTz/9lMmTJ+Pt7Y2dnR3Ozs6EhYVRsmRJmjVrxpEjR/D39yczM5NGjRrRrVs3Ll68mOMx9u7dy8qVKylSpAhTpkwB4N///jfBwcFERETQvHlz87n16tVj5MiRlCxZkkGDBhESEoK3tzdZWVmMGDGC559/3hw2/6mBAwcSEhKCj48PWVlZ9OvXj+rVq/Pyyy8THx+Pj48Prq6ulClTBkdHR/OSjzvefvtt3n//fRwdHXn22WepUaNGtuUw/5S9vT2zZs1i0qRJ3Lp1i6JFizJ16lSL9S8iIiJSkNiY/rxuIR/y9PRk0aJFPPfcc3ldSo5t3rwZk8lEs2bNuH79Om3btiUiIoLixYvndWn/WHh4eLZ12/L3BAUFcfny9Uee5+rqlKPzxDI039anObc+zbn1ac6tz9XVKVf6tdpLZCS7ihUr8v777zNz5kwAhgwZ8kQEaxEREZGC7IkI13FxcXldwl9Wrlw581pvEREREXkyWOWBRhERERGRgkDhWkRERETEQhSuRUREREQs5IlYcy2Ply5duuR1CU+E9PSMvC5BRERE/iKFa7G45GQDRmO+3+FRRERE5C/TshAREREREQtRuBYRERERsRCFaxERERERC1G4FhERERGxED3QKBbn4lI0r0vIt9LTM0hJScvrMkRERORvUrgWiwsPD8dgMOR1GflSUFAQoHAtIiKSX2lZiIiIiIiIhShci4iIiIhYiMK1iIiIiIiFKFyLiIiIiFiIwrWIiIiIiIVotxArSkhIoFWrVlSsWDHb8Y4dO9K1a9dcG3f58uU89dRTeHt7M2vWLGrUqEHz5s1zbTwRERGRgkrh2spKlSrFmjVrrDrm3r17qV+/PgDvvPOOVccWERERKUi0LOQxcOjQIRo2bMiVK1e4evUqzZo148iRI6SmpjJy5Ejat2+Pn58f69atA+DWrVuMGjWKli1b4u3tTUxMDACenp4kJCQAsHPnTgIDA9m2bRtxcXHMnj2bLVu2EBwcTGRkJJMnT+abb74x1zB48GA2bNhAUlISAwYMoH379vj7+7Nt2zbrT4iIiIhIPqU711Z26dIl/Pz8sh2bNm0anTp1Ytq0aWRkZNC5c2eqVq3Kxx9/TPXq1Zk6dSoGg4GAgABq1apFbGwsN27cYP369SQnJ9OzZ09atGhx3/EaNGiAp6cn9evXp3HjxkRHRwPg5+fH6NGj6d27NwaDgX379jFjxgxGjhyJv78/zZs359KlS3Tp0oXVq1dTtKjeuigiIiLyKArXVvagZSEVKlTA398fR0dHpk+fDsC2bdtIS0sjIiICgBs3bnDs2DF2795Nx44dKVSoEK6urubA/FdUq1aN9PR0Tp8+zb59+/D09MTe3p5t27Zx4sQJZs+eDUBmZiZnz56latWq/+CqRURERAoGhevHxPXr10lNTSU1NZWrV69SokQJjEYj06dPp3r16gAkJSVRrFgxIiIisLGxMbc9ffo0pUuXBsBkMgG3Q/Gj+Pr6EhMTw759+/7/a7fBaDSycOFCihcvDty+0+7i4mLRaxURERF5UmnN9WNi3LhxdOvWjS5dujBu3DgAPDw8WLJkCXA75Pr6+nLhwgXq1atHTEwMJpOJ5ORkunXrRnp6Os7Ozhw/fhyATZs2mfu2tbUlKyvrnjF9fHyIiYnh9OnTvPbaa+Yxw8PDATh+/Dg+Pj7cvHkzV69dRERE5EmhO9dWdr811xkZGTg6OhIaGorJZMLf35+YmBgGDRpESEgI3t7eZGVlMWLECJ5//nm6dOnCxIkT8fX1BWDMmDEULVqUIUOGMGHCBObOnUujRo3M/Tdo0IDQ0FCcnJyyjVu6dGmcnZ2pXbu2+U746NGjGTt2LD4+PsDt9eBaby0iIiKSMzamO+sIRCwkPDwcg8GQ12XkS0FBQVy+fP0vtXF1dfrLbeTv03xbn+bc+jTn1qc5tz5XV6dHn/Q3aFmIiIiIiIiFKFyLiIiIiFiIwrWIiIiIiIUoXIuIiIiIWIjCtYiIiIiIhShci4iIiIhYiPa5Fovr0qVLXpeQb6WnZ+R1CSIiIvIPKFyLxSUnGzAatX26iIiIFDw5Ctf79u0jNDSUlJQU7n7nTFRUVK4VJiIiIiKS3+QoXI8dO5b27dtTrVo182uyRUREREQkuxyFazs7O3r16pXbtYiIiIiI5Gs5CteVKlXi6NGjVK5cObfrkSeAi0vRvC7hsZOenkFKSlpelyEiIiK5LEfh+uzZs/j7+1OmTBkcHBzMx7XmWu4nPDwcg8GQ12U8VoKCggCFaxERkSddjsL1u+++m9t1iIiIiIjkezl6iUz9+vVxcHBg165dbN261XxMRERERET+T47C9erVqxkyZAgpKSmkpqby3nvvsXz58tyuTUREREQkX8nRspAFCxawYsUKSpUqBUDfvn3p06cPHTt2zNXiRERERETykxzduTYajeZgDeDm5kahQjlqKiIiIiJSYOQoIRcvXpyNGzeaP2/cuJFixYrlWlEiIiIiIvlRjpaFjBkzhgEDBjBhwgQAChcuzNy5c3O1sIJm3Lhx7N27l4yMDM6cOUPFihUB6N69O/7+/v+4/86dO/Pee+9Rt27df9yXiIiIiNxfjl8i8/3333Pq1CmysrKoUKECdnY5aio59OGHHwKQkJBA9+7dWbNmTR5XJCIiIiJ/1UMT8pdffknfvn2ZMGECNjY293w/evToXCtMbjMYDIwfP57jx49jNBoJCgrCy8uL69evM2rUKC5dusSlS5do1KgREyZMwGQyMW3aNOLi4rC1taVLly5069YNgGXLlvHRRx+RkpLC2LFjadq0KZcvX2bs2LEkJiZSqFAhhg8fjoeHB5988gmHDh3i/Pnz9OjRg06dOuXxTIiIiIg8/h4arp2cnABwdna2SjFyr3nz5lGrVi2mTZvG9evXCQgIoFatWuzZs4dXXnmFoKAg0tPTadWqFfHx8Rw/fpwDBw4QFRVFeno6nTt3xsvLC7i9dj4yMpKNGzfy6aef0rRpUyZMmEBAQABNmzYlMTGRrl27mt+8mZmZSUxMTF5evoiIiEi+8tBwHRAQAECJEiXo0qVLtu/CwsJyryox27ZtGxkZGeZ9xW/evMnx48fx8/Pj119/ZcGCBfzvf/9eIX65AAAgAElEQVTj2rVrpKamsmvXLlq3bo29vT329vbZXlHfokULAF566SX++OMPALZv387p06cJDQ0FICMjg7NnzwJQq1Yta16qiIiISL730HC9ZMkS0tLSWLBgAbdu3TIfz8jIYOnSpQQFBeV6gQWd0WgkNDSUKlWqAJCUlESxYsVYsGABmzZtomPHjjRq1Ij4+HhMJhOFCxfOtoQnISEBFxcXAGxtbQGwsbHBZDIBkJWVxbfffmv+LUViYiKurq4AODg4WO06RURERJ4ED92Kz87Ojt9//520tDR+//13839nzpwhODjYWjUWaO7u7ixZsgS4HXx9fHy4dOkSW7dupXPnzvj4+HDjxg2OHj2K0Wikbt26xMbGkpmZyY0bN+jduzdJSUk56v/o0aP4+vqSlpZmlWsTERERedI89M51hw4d6NChAxs3bjQvKRDreueddwgJCcHHx4esrCyCg4MpW7YsPXv2ZPz48Xz22Wc4OTlRu3ZtEhISaNeuHYcOHaJdu3YYjUb69OlDuXLlHth/SEgIY8aMMS8fmTFjBk899ZS1Lk9ERETkiWJjurM+4CGuXLnC2rVrSU1NxWQyYTQaOX36NDNmzLBGjZLPhIeHYzAY8rqMx0pQUBCXL1/Plb5dXZ1yrW+5l+bb+jTn1qc5tz7NufW5ujrlSr852qx66NChODo6cvz4cRo0aMC2bdt47bXXcqUgEREREZH8KkevPz9//jxhYWE0adKEbt26sWTJEk6cOJHbtYmIiIiI5Cs5CtclS5YE4MUXX+T333/Hzc2NzMzMXC1MRERERCS/ydGyEBcXF7766iteffVV5syZQ9GiRbWjhIiIiIjIn+TozvX48eOxt7enbt261KhRg9mzZzN8+PDcrk1EREREJF/J0W4hcPtlI0ePHqVQoUJUrlw524tKROTh0tMzSEnJnd/26Alz69J8W5/m3Po059anObe+PN0tZM+ePbz77rvY2tpiNBopXLgwn376KZUrV86VoiR/S042YDTm6Gc2ERERkSdKjsL1xIkTmTRpEk2aNAEgLi6ODz/8kKVLl+ZqcSIiIiIi+UmO1lwD5mAN4Onpyc2bN3OlIBERERGR/CpH4bpmzZrExMSYP//888+8/PLLuVaUiIiIiEh+lKMHGj09PTl//jzFihXDzs6O5ORkHBwcKFSoEDY2Nuzdu9catYrkO7n5IOMdegjGujTf1qc5tz7NufVpzq0vTx9oXLx4ca4MLk+m8PBwDAZDXpfxWAgKCgK0J7yIiEhBkaNwffXq1fser169ukWLERERERHJz3IUrgcPHmz+c0ZGBpcvX6ZGjRqsXLky1woTEREREclvchSu4+Lisn3euXMnUVFRuVKQiIiIiEh+leOt+O7m7u7OoUOHLF2LiIiIiEi+lqM713cHaZPJxMGDB0lL00NaIiIiIiJ3+8trrm1sbChRogQhISG5VZOIiIiISL6Uo2UhcXFxrF27lri4OGJiYvj8889xd3fP0QC///47lStXJjY29r7f79y5k8DAwBwXvGTJEpYsWfLQc/r27UtiYuIDv//ggw84d+5cjsf8c5tH9f9XDB48GB8fn7/dftasWWzatOmB3y9fvpx169b9rb7Pnj3LqFGj/m5pIiIiIgVOjsJ1TEwM7du3B+D8+fN4e3vf85Djg0RERNCqVSuWLVv296u8S+fOnencufNDz/nyyy9xc3N74Pc7d+4kB+/OeWCbR/WfU1euXOHw4cM8/fTTf/tFPO+88w7Nmzd/4Pd79+4lPT39b/V9/vx5zp49+7faioiIiBREOVoW8vnnn7No0SIAypcvT2RkJAMGDMDT0/Oh7TIyMoiKiuK7774jICCAM2fO8Pzzz/Pzzz8zefJkHBwcKF++vPn8wMBAqlWrxi+//MKtW7cYPnw4ixYt4n//+x89e/akZ8+ezJkzB7h9x7dRo0a0bNmSX375BVtbW2bOnEm5cuXw9PRk0aJFGAwGxo4dS2ZmJg4ODkyePJn//ve/XLp0iaCgIL777jv8/f2pWbMmR44cITw8nEWLFrF9+3ZSUlIoVaoUn3zyCZGRkfe0WbRoEYMHD2bChAnUqFGDrKwsmjVrxqpVqzh37hyTJ08mLS0NZ2dnxo0bR7ly5e6Zn6ioKOrVq8fLL7/M0qVLqVOnDgDx8fH31F22bFlGjRrFsWPHAOjSpQsdO3YkODiY+vXr8+abbzJs2DCSkpIAGDhwIEWKFCEuLo4dO3bg6uqKm5sbEyZM4MaNG1y5coWgoCA6d+7MnDlzSExM5PTp05w7d44OHTrQv39/Jk6cSEJCAuPGjePDDz/MyT8VERERkQItR3eujUYjzz77rPlz6dKlMRqNj2z3448/UqZMGcqXL0+LFi1YtmwZ6enpBAcHM3v2bCIjI3F0dMzWxmQysXLlSlq2bMnEiROZO3cu3333HfPmzbun/8uXL/P666+zevVq6tWrx3fffZft+4ULF9KrVy8iIyPp2LEjv/76K0FBQZQqVYqwsDCcnZ0BaNKkCbGxsRgMBk6cOMHSpUuJjY2ldOnSrF279r5tAPz8/IiOjgZgx44dVKlSBScnJ0aPHs2MGTNYtWoVvXr1YsyYMfedn8jISFq3bk3r1q2JjY01v6znfnXv27ePlJQUVq9ezRdffMGePXuy9bVhwwbKli1LZGQkkyZNYs+ePTRo0ABPT0+GDBlC48aNWbFiBQMGDCAiIoJFixYxbdo0c/ujR4/y9ddfs2LFCsLCwrh27RqjR4+mRo0aCtYiIiIiOZSjcF2iRAmWLl1KZmYmWVlZrFy5kpIlSz6yXUREBN7e3gB4eXkRGRlJfHw8pUqVomLFigC0a9cuW5smTZoAUKZMGWrVqkWRIkUoW7Ys165du+8YjRs3BqBSpUqkpKRk+65p06ZMmDCBUaNG4eTk9MC1zbVq1QLghRdeYOTIkaxYsYIpU6bw66+/cuPGjQdeX5s2bYiNjcVkMrFu3Tp8fX05deoUZ8+epX///vj5+fHxxx/fd2nFkSNHuHjxIg0aNKB06dJUrVqV1atXP7DuSpUqcfLkSfr06cP333/P+++/n62/2rVrs3HjRgYMGMCBAwcYOHDgPWMGBwdz69YtvvjiC2bOnJnt2tzd3bG3t8fFxYXixYtz/fr1B163iIiIiNxfjsL1+PHjWb58ObVq1aJmzZosX778kXczk5OT2bJlC9988w2enp6MHj2aa9eusXXr1mzrnW1tbbO1K1y4sPnPdnaPXrXi4OAA3N7F5M/rqFu1asWqVauoWbMmCxYseGDNd/o4ePAgffr0wWg00rJlS1q0aPHQtdmurq6UL1+enTt3sn37dpo3b47RaOS5555jzZo1rFmzhsjISMLDw+9pGxERQXp6Oi1btsTT05OTJ0+ydOnSB9bt7OxMdHQ03bp14+TJk7Rr1y7bDxwvvvgi69evx8fHhz179vDWW2/d89uFoUOHsmHDBipWrMjQoUPvOwcPmksRERERebQcrbl+8cUXWbx4MZmZmdja2nLr1i1cXFwe2mbNmjV4eHjw1VdfmY/NmTOHH3/8kaSkJOLj46lSpYp5WUVuGDp0KN7e3gQEBFCxYkUmT54M3A70WVlZ95y/e/du6tevT+fOnfnjjz/YvHkzb7755kPb+Pn5MXXqVNzd3SlSpAgVKlQgJSWFPXv2ULduXSIiIoiKimLx4sXmNunp6URFRbFgwQLzXXODwUDTpk3ZuXMnS5YsuafuTZs2sXbtWmbOnEnjxo3Zvn07Fy5cMPf57bffcvbsWT744AOaNGlCs2bNMBgM2ereunUr69evx83NzbyE5n7XdIetrS2ZmZl/ddpFRERECqwc7xbSrl07ihUrxuXLl3O0W8iqVavo0qVLtmNdu3blyJEjhIaGMmLECNq1a8fNmzf/fvWP0K9fPz777DPatWvH9OnTzXtz/+tf/yIoKOie5RpeXl7Ex8fj4+ND9+7dqVGjBgkJCQ9t88Ybb3Dq1Cl8fX0BsLe3Z9asWUyZMgUfHx9WrVrFpEmTsrWJi4ujbNmy5mANULRoUTp06MDSpUvvW3eTJk1wdHSkTZs2dOjQAV9fXypXrmxu37ZtW06ePImPjw9du3ZlxIgRPPPMMzRo0IDPP/+c77//nsGDB9OlSxe8vLz45ZdfKFu2rPn67qdixYpcv36dESNG/PXJFxERESmAbEw5+P2/r68vYWFh5ocaL1y4wIABA1i1alWuFyj5T3h4OAaDIa/LeCwEBQVx+XLurl93dXXK9THk/2i+rU9zbn2ac+vTnFufq6tTrvSbq7uFiIiIiIgUJLm6W4iIiIiISEGSa7uFiIiIiIgUNI/cLSQxMZHFixeTlZVFxYoVeeWVVxg0aBClS5e2Rn0iIiIiIvnGQ+9cX7hwgQ4dOmBra8vQoUMZOHAgDg4OdOjQgXPnzlmrRhERERGRfOGhu4WMHDmS119/nbZt22Y7HhERwY4dO5g+fXquFyiSn6WnZ5CSkparY+gJc+vSfFuf5tz6NOfWpzm3vtzaLeShy0IOHz7M1KlT7znu7+9PWFhYrhQk+V9ysgGjUW94FBERkYLnoctCHrYFtr29vcWLERERERHJzx4arm1tbUlMTLzneGJiosK1iIiIiMifPDRcBwQEMGrUqGxv20tOTub999+/59XmIiIiIiIF3UPXXHfu3JkzZ87QuHFjXnrpJTIzMzl16hTdu3fH39/fWjVKPuPiUjSvS3gsWONhRhEREXm8PHKf65EjR9KzZ09+++03AGrVqoWbm1uuFyb5V3h4eLbfdhRUQUFBgMK1iIhIQfLIcA3g5ubGm2++mdu1iIiIiIjkazl6/bmIiIiIiDyawrWIiIiIiIUoXIuIiIiIWIjCtYiIiIiIhShci4iIiIhYiMJ1PvD7779TuXJlYmNj/3YfwcHBREZG/qU2169fZ+DAgX97TBEREZGCRuE6H4iIiKBVq1YsW7bMquOmpKRw5MgRq44pIiIikp8pXD/mMjIyiIqKYujQoRw6dIgzZ84A4OnpycyZM3nrrbdo06YNBw8eBGDXrl107tyZdu3a0bx5czZu3Jitv5kzZ/LJJ5+YPwcHBxMTE0NUVBR+fn60b9+eIUOGcOvWLSZOnMilS5d091pEREQkhxSuH3M//vgjZcqUoXz58rRo0SLb3evixYuzcuVKAgIC+OKLLwD49ttvmThxIqtWrWLixInMmjUrW3/+/v5ERUVhMpm4efMmO3bsoHnz5sycOZNvvvmGyMhIypYty4kTJxg9ejSlSpVi3rx5Vr1mERERkfxK4foxFxERgbe3NwBeXl5ERkaSnp4OQOPGjQGoVKkSV69eBWD69OkcO3aMefPmMX/+fFJTU7P1V65cOcqWLcvu3buJjY2ladOmODg40KxZMzp37sy0adNo2bIlVatWteJVioiIiDwZcvT6c8kbycnJbNmyhUOHDrFo0SJMJhPXrl1jw4YNADg4OABgY2NjbtOlSxfc3d1xd3fn9ddfZ/jw4ff06+/vz7p16zh//jyDBw8GYPTo0cTHx/Pjjz8yYsQIBg0axGuvvWaFqxQRERF5cihcP8bWrFmDh4cHX331lfnYnDlzWLp06X3Pv3r1KqdOnSI8PBx7e3s+/vhjsrKy7jmvVatWzJs3j6effppatWqRmZmJl5cXixcv5u233yYjI4MjR47g7u5OZmZmrl2fiIiIyJNGy0IeY6tWraJLly7ZjnXt2pX9+/dz69ate84vXry4+QHH1q1bk5qaSlpaGjdu3Mh2nqOjI6+++ipt2rQBwM7OjiFDhtC7d2/at2/Pb7/9Rt++fXFxcaFMmTIEBgbm3kWKiIiIPEFsTCaTKa+LEOsxmUykpqbSqVMnFixYgKurq8XHCA8Px2AwWLzf/CYoKIjLl6/n+jiurk5WGUdu03xbn+bc+jTn1qc5tz5XV6dc6Vd3rguYAwcO4OnpSceOHXMlWIuIiIgUZFpzXcDUrFmTXbt25XUZIiIiIk8k3bkWEREREbEQhWsREREREQtRuBYRERERsRCtuRaL+/P2gQVVenpGXpcgIiIiVqZwLRaXnGzAaNQOjyIiIlLwaFmIiIiIiIiFKFyLiIiIiFiIwrWIiIiIiIVozbVYnItL0bwuIc+kp2eQkpKW12WIiIhIHlG4FosLDw/HYDDkdRl5IigoCFC4FhERKai0LERERERExEIUrkVERERELEThWkRERETEQhSuRUREREQsROFaRERERMRCFK5FRERERCwkX4Tr77//nvbt2+Pr64uPjw9fffXVI9sEBgayc+fOXKvJZDIxf/58/Pz88PPzo127dkRHR+faeH+2adMmZs2a9ZfaJCYm0rdv31yqSEREREQe+32uExMTmTp1KpGRkTg7O5OamkpgYCDly5enefPmeVbXJ598wuHDh/n2229xcnLi4sWLdOvWDWdnZxo0aJDr4zdv3vwvX7+bmxtffvllLlUkIiIiIo99uP7jjz/IyMggLe32izmefvpppkyZgoODAwDr169n/vz5pKWlkZ6ezkcffUSdOnWy9REWFsb69evJysqiUaNGjBgxgtTUVIYNG0ZSUhIAAwcOzHFYTU1NZeHChaxduxYnJycAnn32WUJDQylSpAgAP/zwAzNnzsRoNFKuXDnGjx9PyZIl8fT0pE2bNmzduhU7OzsGDBjAN998w+nTpxk5ciReXl4EBwdTpEgRDh8+zLVr1xg2bBhr1qwhPj6eFi1aEBwcTGRkJLt27WLKlClMnTqVrVu3UqhQIVq0aMGgQYPYvn0706dPB6BYsWLMmDGDGzdu0L17d+Li4khKSuI///kP58+fx87OjnfffZcmTZowZ84cEhMTOX36NOfOnaNDhw7079//n/9FioiIiBQAj/2ykCpVqtC8eXNatGjBW2+9xfTp0zEajbzwwgsYjUaWLl3K559/ztq1a/n3v/9NWFhYtvY//fQTBw8eZOXKlaxevZrExETWrl3Lhg0bKFu2LJGRkUyaNIk9e/bkuKYTJ05gZ2fHCy+8kO14zZo1qVSpEsnJyYwdO5Z58+YRFRVFnTp1GD9+vPm8kiVLEhkZScWKFQkLC+Obb75h+vTp2Wq/dOkSy5YtIygoiA8++IBx48axevVqli9fzvXr183nnTt3jp9++om1a9eyZMkSjh8/zq1bt/j0008JCQkhMjKSBg0acPjw4Wy1TpgwAQ8PD6Kiopg9ezajRo0y/6Bx9OhRvv76a1asWEFYWBjXrl3L8dyIiIiIFGSP/Z1rgHHjxjFgwAB+/vlnfv75Zzp27MjHH3/Mm2++ybx584iLi+PkyZPs2rWLQoWy/7ywfft29u/fT/v27QFIS0ujTJky+Pv7ExoaSmJiIv/6178YOHBgjuspVKgQ9vb2D/x+//791KxZk+eeew6ATp06ZQvOTZo0AaBMmTKUKlUKOzs7ypQpky3E3n1OpUqVcHFxAaB48eKkpKSYz3Nzc8PBwYGAgACaNWvG8OHDcXBwoHnz5gwaNIgWLVrQvHlzGjZsSEJCgrndjh07mDhxIgDlypWjVq1a/PbbbwC4u7tjb2+Pi4sLxYsX5/r16zzzzDM5nh8RERGRguqxD9ebN2/mxo0beHl54e/vj7+/P8uXL2flypU0bNiQt956C19fX+rVq0flypX57rvvsrXPysqiR48e9OrVC4Br165ha2vL008/zfr169myZQs//PAD33zzDTExMeZwnpiYSFBQEAClSpXKtla5YsWKpKWlcf78ecqUKWM+Hh0dTVJSkjlU32EymcjMzDR/Lly4sPnPdnb3/yvIyTl3vluxYgW7du3ip59+IiAggMWLF9OzZ0+aNWvGDz/8wPTp09m/fz8+Pj7ZavpzjVlZWQDmJTcANjY295wrIiIiIvf32C8LcXR0ZMaMGea7riaTiSNHjlC1alVOnTqFjY0N/fr1w93dnQ0bNpgD4h0eHh6sWbOG1NRUMjMzGThwILGxsXz77bfMmTOH1q1b8+GHH3LlyhUMBoO5nZubG2vWrGHNmjX3PATo6OhI165dCQkJMbdJSEggNDSUihUrmu8C36l52bJluLu758r8HD58mG7dulGvXj1GjhxJxYoVOXnyJB06dCA1NZWePXvSs2fPe5aFeHh4sHLlSgDOnj3L3r17efXVV3OlRhEREZGC4rG/c+3h4cGgQYPo168fGRkZADRu3JiBAwdia2tL1apVad26NTY2NjRq1IhffvklW3tPT0/i4+Pp2LEjWVlZNG7cmHbt2pkfaPTx8cHW1pYRI0b8paUP7777LvPmzaNjx47Y2dlha2vLe++9R6NGjQAYP348gwYNIiMjgzJlyjBp0iTLTcpdqlWrxquvvoq3tzdFihShTp06NGnShCJFihAcHIydnR1PPfWUeQnIHf/5z38YO3YskZGRAEycOJFSpUrlSo0iIiIiBYWNSb/zFwsLDw/P9luAgiQoKIjLl68/+kQLcnV1svqYBZnm2/o059anObc+zbn1ubo65Uq/j/2yEBERERGR/ELhWkRERETEQhSuRUREREQsROFaRERERMRCFK5FRERERCzksd+KT/KfLl265HUJeSY9PSOvSxAREZE8pHAtFpecbMBo1A6PIiIiUvBoWYiIiIiIiIUoXIuIiIiIWIjCtYiIiIiIhShci4iIiIhYiB5oFItzcSma1yVYTXp6BikpaXldhoiIiDwmFK7F4sLDwzEYDHldhlUEBQUBCtciIiJym5aFiIiIiIhYiMK1iIiIiIiFKFyLiIiIiFiIwrWIiIiIiIUoXIuIiIiIWEiBC9e///47lStXJjY2Nk/r2L9/P9OnT//b7QMDA7N9HjVqFMePH8dkMjF//nz8/Pzw8/OjXbt2REdHm8/z9PTEy8sLPz8/fH19ad++PTt27MjW15QpU/Dw8CA9Pf1v1yciIiJSEBW4rfgiIiJo1aoVy5Yto2XLlnlWx/Hjx0lOTv7b7Xft2pXt8//+9z9eeuklQkNDOXz4MN9++y1OTk5cvHiRbt264ezsTIMGDQAICwvjueeeAyAuLo7hw4fz888/A5CZmcn69eupXbs2sbGx+Pj4/O0aRURERAqaAnXnOiMjg6ioKIYOHcqhQ4c4c+YMANu2bcPX1xcfHx/efvttDAYDt27dYtSoUbRs2RJvb29iYmIA+PXXX+nQoQO+vr706NGD06dPA7fvJO/cuROAhIQEPD09AQgODmbixIl07twZT09PIiIiuHbtGrNnzyYuLo7PPvsMg8HAkCFD6NSpE82aNWPUqFGYTCZ27txJ7969GTBgAC1btmTIkCGkp6czceJEADp06ABAfHw8lStXJjU1lYULFzJmzBicnJwAePbZZwkNDcXV1fW+c+Lu7s7ly5f5448/ANi8eTPPP/88bdu2ZenSpbnx1yAiIiLyxCpQ4frHH3+kTJkylC9fnhYtWrBs2TLS09MZPnw4U6dOJSoqipdffplVq1axePFibty4wfr165k/fz7z5s0jPT2dYcOGMWbMGNauXUtAQADDhg175LgXL14kPDyczz77jGnTpvHMM88wZMgQPD096d+/P5s3b6Zq1aosW7aM2NhYdu/ezaFDhwDYt28fY8eOZf369Zw/f56ff/6Z0aNHA7BixQoAfvrpJ5o0acKJEyews7PjhRdeyDZ+zZo1qVSp0n1rW7duHS+++CLOzs4AREZG0qpVK5o2bcqRI0c4fvz4355vERERkYKmQIXriIgIvL29AfDy8iIyMpL4+Hjc3NyoWrUqAO+99x6BgYHs3r0bHx8fChUqhKurK9HR0Zw6dYpnnnmGmjVrAtC6dWvOnDnD9ev/r727j6my/v84/jqHg1qDiTC8ybv2dd2tZra0yJxOnSBygGXODESMKdlcNZcVdDNtWTRyat60NEuzIG0pmgl5E6VFDMtuzNRqpSZJpAjKQW4OnM/vj9ZJFDV+Xecc9Dwff3F9uM7F+/O+PrDXLj4cai/6de+++27ZbDZdf/31qqmpOe/zTqdTd999t1avXq158+appqZGZ86ckSRdd9116tmzp+x2uwYMGKBTp06d9/rS0lLFxMTIbrerU6dOl+xDZmamkpOTNW7cOG3btk2LFi2SJFVVVamkpETx8fHq0qWLRo4cydNrAACAdgiaPddVVVX67LPP9MMPP2jNmjUyxuj06dPatWuXbDab97za2lrV1dXJ4XC0Gj9y5Ig8Hs951zXGqKWlxfux9Ne+5bN17txZklpd72xvv/22tm7dqokTJ2ro0KH66aefvNf6+7V/v/7v8b+5XC7Z7XaFhYVpwIABamho0LFjx3TNNdd4z9myZYtOnDih9PR0Sa33XJ/tgw8+kDFGEyZMkCQ1NDTI7XZr9uzZ6tKlS5u1AwAA4B9B8+R606ZNiomJ0a5du1RcXKxPPvlEM2bM0K5du1RVVeXd/rBy5Uq9++67GjJkiAoLC2WMUVVVlSZPnqzevXurpqZGe/fulSQVFhbqmmuuUUREhLp16+a9xo4dOy5ZT0hIiDeEl5SU6L777lNSUpIaGxt18ODBNoN8W68vKSnx/qFily5dlJqaqrlz58rlckn6a//3ggULNGDAgEvWtGHDBr300ksqLi5WcXGxPv/8c3Xt2tW73xwAAAAXFzRPrgsKCjRr1qxWY6mpqVq5cqVef/11PfHEE3K73erXr59yc3MVGhqqefPmKSkpSZK8fyS4cOFCPf/886qvr1fXrl21cOFCSdK0adOUlZWl9evXa/To0ZesZ+DAgVq6dKnmz5+v9PR0zZ07VytWrFBYWJhuu+02lZeXq1+/fhd8/ejRo5WcnKxBgwZ5n0hL0qxZs7Rs2TJNnDhRDodDISEheuyxxzRs2LCL1vP999+rurpaY8aM8Y7Z7Xalp6dr7dq1Gj9+/CXnBAAAEOxs5tx9BsB/lJ+f731yfqXLzMzU8eMX33Pva9HR4QGvIU5b9TQAAA0KSURBVJjQb/+j5/5Hz/2PnvtfdHS4T64bNNtCAAAAAF8jXAMAAAAWIVwDAAAAFiFcAwAAABYhXAMAAAAWCZq34oP/pKSkBLoEv2lqcge6BAAA0IEQrmG5qiqXPB7e4REAAAQftoUAAAAAFiFcAwAAABYhXAMAAAAWIVwDAAAAFuEPGmG5qKiwQJfgF01Nbp061RDoMgAAQAdCuIbl8vPz5XK5Al2Gz2VmZkoiXAMAgH+wLQQAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhugNzuVx67rnn5HQ6lZycrLS0NP3www8qKytTWlpau641ffp0VVZWtruGtLQ0lZWVtft1AAAAwYhw3UF5PB5Nnz5dXbt21caNG7Vp0ybNnDlT06dPV01NTbuv9/rrr6tHjx4+qBQAAAB/I1x3UGVlZaqoqNAjjzwih+OvtyOPiYlRTk6OWlpavOcdOXJEDzzwgO655x7df//92r9/vyQpKytLM2bMUHx8vIqLizVq1CiVl5ersbFRTz31lOLi4uR0OlVYWChJKioq0sSJE5WUlKSxY8fq66+/9v+kAQAALnOE6w5q//79uvHGG2W3t75FI0aMUFRUlPf4ySef1OOPP66CggI9//zzmjVrlvdzERERKioq0qhRo7xjb7/9ts6cOaOioiKtWrVKy5YtU1NTk9auXavXXntNH3zwgaZNm6YVK1b4fpIAAABXGP5DYwdlt9vVuXPni55TV1enffv2KTs72zt25swZVVdXS5IGDhx43mu+/PJLTZw4UXa7XdHR0dqyZYskadmyZSouLtahQ4e0e/fu80I9AAAALo1w3UHdcsstys/PlzFGNpvNO75gwQINHTpU0l/7sjt16qRNmzZ5P//HH38oIiJCktSlS5fzrutwOFpd78iRI4qKitKECROUlJSkIUOG6IYbblBeXp6vpgYAAHDF4vFkBzV48GBFRUVp6dKl3j3Wn332mTZs2KCTJ09KksLDw3Xttdd6w3VJSYlSU1Mvet0hQ4aosLBQxhhVVVVp8uTJ2r9/v2w2m2bMmKE777xT27dvb7WvGwAAAP8OT647KJvNpldffVU5OTlyOp1yOBzq1q2bVqxYodraWu95L7/8subOnauVK1cqNDRUCxcubPVk+lwpKSmaN2+ekpKSJEnPPvusbr/9dt10002Kj4+XzWbTsGHDtGfPHp/PEQAA4EpjM8aYQBeBK0t+fr5cLlegy/C5zMxMHT9ee+kTfSw6OrxD1BEs6Lf/0XP/o+f+R8/9Lzo63CfXZVsIAAAAYBHCNQAAAGARwjUAAABgEcI1AAAAYBHCNQAAAGARwjUAAABgEd7nGpZLSUkJdAl+0dTkDnQJAACggyFcw3LV1XXyeILj7dPt9gv/wx5/6ih1BAv67X/03P/ouf/R8ysD/0QGAAAAsAh7rgEAAACLEK4BAAAAixCuAQAAAIsQrgEAAACLEK4BAAAAixCuAQAAAIsQrgEAAACLEK4BAAAAixCuAQAAAIsQrgEAAACLEK5hic2bN2vcuHGKjY1VXl5eoMu57KWlpSkhIUHJyclKTk7Wd999d8Eef/HFF0pMTFRsbKwWLlzoHT9w4IDGjx+vuLg4Pf3002pubg7EVDo0l8slp9Op8vJySe3v5bFjx5SamqqxY8fqoYceUl1dnSTp9OnTyszMVHx8vFJTU3X8+HH/T66DOrfn2dnZio2N9a717du3S7LuXgS7pUuXKiEhQQkJCcrNzZXEOve1tnrOOvetV155RePGjVNCQoJWrVolKcDr3AD/0R9//GFGjhxpqqurTV1dnUlMTDQ///xzoMu6bHk8HjNs2DDjdru9YxfqcX19vRkxYoT57bffjNvtNhkZGebTTz81xhiTkJBgvvnmG2OMMdnZ2SYvLy8g8+movv32W+N0Os3NN99sjh49+v/qZWZmpvnwww+NMcYsXbrU5ObmGmOMee6558zy5cuNMcYUFBSYRx991N/T65DO7bkxxjidTlNZWdnqPCvvRTArKSkx9913n2lsbDRNTU1mypQpZvPmzaxzH2qr59u2bWOd+1BZWZmZNGmScbvdpr6+3owcOdIcOHAgoOucJ9f4z7744gvFxMQoIiJCV199teLi4vTRRx8FuqzL1q+//ipJysjIUFJSkt55550L9njv3r3q37+/+vbtK4fDocTERH300Uf6/fff1dDQoEGDBkmSxo8fzz05x3vvvac5c+aoe/fuktTuXrrdbn355ZeKi4trNS5Jn376qRITEyVJTqdTu3btktvtDsAsO5Zze15fX69jx47pqaeeUmJiohYvXiyPx2PpvQhm0dHRysrKUqdOnRQaGqoBAwbo8OHDrHMfaqvnx44dY5370B133KE1a9bI4XCoqqpKLS0tOn36dEDXucOH80WQ+PPPPxUdHe097t69u/bu3RvAii5vp0+f1l133aVnn31WbrdbU6ZMUXx8fJs9bqv3lZWV541HR0ersrLSr/Po6F544YVWx+3tZXV1tcLCwuRwOFqNn3sth8OhsLAwnTx5Uj169PD1tDq0c3t+4sQJxcTEaM6cOQoPD9eDDz6o999/X1dffbVl9yKYXXfddd6PDx8+rKKiIk2ePJl17kNt9TwvL0+7d+9mnftQaGioFi9erDfffFNjx44N+M9znlzjP/N4PLLZbN5jY0yrY7TPbbfdptzcXIWHhysyMlITJkzQ4sWL2+zxhXrPPWm/9vayrZ5eqMfGGNnt/Lg9V9++fbVs2TJ1795dV111ldLS0rRz506f3otg9PPPPysjI0NPPPGE+vbtyzr3g7N7/r///Y917gePPPKISktLVVFRocOHDwd0nfNdgP+sZ8+erTb4Hz9+3PtrX7TfV199pdLSUu+xMUa9e/dus8cX6v254ydOnOCeXEJ7exkZGana2lq1tLS0Ol/66ynJiRMnJEnNzc2qq6tTRESEH2dzefjxxx+1detW77ExRg6Hw9J7Eez27NmjqVOn6rHHHtM999zDOveDc3vOOvetX375RQcOHJAkXXXVVYqNjVVZWVlA1znhGv/Z0KFDVVpaqpMnT6q+vl7btm3T8OHDA13WZau2tla5ublqbGyUy+VSQUGBXn755TZ7fOutt+rQoUM6cuSIWlpa9OGHH2r48OHq3bu3OnfurD179kiSNm3axD25hPb2MjQ0VIMHD1ZhYaEkaePGjd4ejxgxQhs3bpQkFRYWavDgwQoNDQ3MxDowY4xefPFFnTp1Sm63W+vWrdOYMWMsvRfBrKKiQjNnztT8+fOVkJAgiXXua231nHXuW+Xl5XrmmWfU1NSkpqYmffzxx5o0aVJA17nNGGN8OGcEic2bN2v58uVyu92aMGGCpk+fHuiSLmuLFi3S1q1b5fF4lJKSovT09Av2uLS0VDk5OWpsbNSIESOUnZ0tm82mgwcP6plnnpHL5dLNN9+snJwcderUKcAz63hGjRqlNWvWqE+fPu3u5e+//66srCxVVVWpV69eWrBggbp27aqamhplZWXp6NGjCg8P1/z589WnT59AT7XDOLvneXl5ysvLU3Nzs2JjYzV79mxJ7V/XF7oXwWzevHlav369+vXr5x2bNGmSrr32Wta5j1yo5x6Ph3XuQ0uWLFFRUZFCQkIUGxurhx9+OKA/zwnXAAAAgEXYFgIAAABYhHANAAAAWIRwDQAAAFiEcA0AAABYhHANAAAAWIRwDQC44mRkZOjkyZOBLgNAECJcAwCuOCUlJYEuAUCQIlwDAPzq/fffV0JCghITEzVlyhRVVFRo3bp1cjqdSkpKUkZGhg4dOiRJysrK0htvvOF97dnHo0aN0pIlS5SSkqKRI0dq0aJFkqTs7GxJUnp6uioqKvw8OwDBzhHoAgAAwePgwYOaP3++CgoK1KtXL61evVpTp06Vx+PRunXrFBkZqQ0bNmjmzJnasmXLJa935swZ5efnq7KyUmPGjNG9996rnJwcbdiwQW+99ZYiIyP9MCsA+AdPrgEAflNaWqphw4apV69ekqSpU6dq9OjRGjdunDcIjx8/XpWVlSovL7/k9UaPHi1J6tGjh6KionTq1CnfFQ8A/wLhGgDgNyEhIbLZbN7jhoYGHT169LzzjDFqbm6WzWaTMcY77na7W53XuXNn78fnngsAgUC4BgD4zZ133qnS0lL9+eefkqS1a9dq586dKiws9L67x/r16xUREaH+/furW7du2rdvnySpsrJSu3fv/ldfJyQkRM3Nzb6ZBABcBHuuAQB+c8MNN+jxxx/XtGnTJEnR0dHavn27duzYofT0dHk8HkVGRmr58uWy2+1KS0vT7NmzFRcXpz59+igmJuZffZ2xY8cqLS1NS5Ys0fXXX+/LKQFAKzbD79AAAAAAS7AtBAAAALAI4RoAAACwCOEaAAAAsAjhGgAAALAI4RoAAACwCOEaAAAAsAjhGgAAALDI/wFmU0l2b/dMUgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Top ten Occupation for Beneficiaries of loans\n",
    "plt.figure(figsize = [10, 5])\n",
    "plt.title('Occupation Distrbution')\n",
    "order = df['Occupation'].value_counts().index[:10]\n",
    "sb.countplot(data = df, y = 'Occupation', order=order, color='#999999')\n",
    "sb.set();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> The chart above represents the top ten occupations for beneficiaries of prosper loans, a significant amount of users select other and professional as their occupation which was irrelevant for our investigation.\n",
    "\n",
    "Now, let's inspect the interest rate distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[15, 10])\n",
    "sb.distplot(df['InterestRate'])\n",
    "plt.title('Interest Rate Distrbution')\n",
    "plt.ylabel('Probability')\n",
    "sb.set();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "The interest rate distribution seems bimodal, since it has two peaks. Also, a major lack of fit exists on the right side of the observed distribution where the second peak appears. Thus to conclude from the analysis, the continuous normal distribution probably does not provide adequate information for the observed distribution."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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OFRFTzJ7ODWiINmcK0dZHISoiZjW7a6IiIiKtnUJURETEJIWoiIiISQpRERERkxSiIiIiJilERURETFKIioiImKQQFRERMUkhKiIiYpJCVERExCSFqIiIiEkKUREREZMUoiIiIiYpREVERExSiIqIiJikEBURETFJISoiImKSQlRERMQkhaiIiIhJClERERGTFKIiIiImKURFRERMUoiKiIiYpBAVERExSSEqIiJikkJURETEJIWoiIiISQpRERERkxSiIiIiJilERURETFKIioiImKQQFRERMUkhKiIiYpJCVERExCSFqIiIiEkKUREREZMUoiIiIiYpREVERExSiIqIiJikEBURETFJISoiImKSQlRERMQkhaiIiIhJClERERGTFKIiIiImKURFRERMUoiKiIiYpBAVERExSSEqIiJikkJURETEpICG6IYNG8jIyCA1NZV58+YBkJubS3p6OsOHD2fx4sX+vnv37iUjI4OUlBRmzJiBx+MB4NixY4wdO5YRI0YwadIkampqAKiqquKhhx4iNTWVsWPH4nQ6AzkUERGRswQsRPPz85k9ezZLly5l7dq1fPHFF2zatInp06ezdOlSsrOz2bNnD5s2bQJg6tSpzJo1i/fffx/DMFi1ahUAc+bMYcyYMeTk5DBw4ECWLl0KwJIlS0hMTGT9+vWMHj2a+fPnB2ooIiIi5xSwEP3www+55ZZbSEhIwGazsXjxYsLCwujRowfdunXDarWSnp5OTk4OBQUF1NXVMXjwYAAyMjLIycnB7XazY8cOUlJSGrQDbNy4kfT0dABGjhzJ5s2bcbvdgRqOiIjIWayB2nFeXh42m42JEydSWFjITTfdRN++fXE4HP4+cXFxFBUVUVxc3KDd4XBQVFREeXk5ERERWK3WBu1Ag22sVisRERGUlZURHx/fqPpiYyMu1lClGXE4Ipu6BBFpQwIWol6vl507d7JixQrCw8OZNGkSoaGhWCwWfx/DMLBYLPh8vnO2n/nz6765/PVtgoIaP7EuLT2Bz2c0ur9+ObcMTmd1U5cgIi1QUJDF1OQqYKdzO3bsyJAhQ4iJiSE0NJRhw4aRm5vb4AtATqeTuLg4EhISGrSXlJQQFxdHTEwM1dXVeL3eBv3h1Cy2pKQEAI/HQ01NDVFRUYEajoiIyFkCFqI333wzW7dupaqqCq/Xy5YtWxgxYgSHDx8mLy8Pr9fLunXrSEpKokuXLoSEhLBr1y4A1qxZQ1JSEjabjcTERLKzswHIysoiKSkJgOTkZLKysgDIzs4mMTERm80WqOGIiIicxWIYRuPPaV6gt956i1dffRW3280NN9zAzJkz+fTTT1m4cCH19fUkJyczbdo0LBYL+/btY+bMmZw4cYIBAwawcOFC7HY7BQUFZGZmUlpaSqdOnXj22Wfp0KEDFRUVZGZmkp+fT2RkJIsWLaJr166Nrs3M6dzS6dPN/DXIJRK7YIFO54qIKWZP5wY0RJszhWjroxAVEbOa3TVRERGR1k4hKiIiYpJCVERExCSFqIiIiEkKUREREZMUoiIiIiYpREVERExSiIqIiJikEBURETFJISoiImKSQlRERMQkhaiIiIhJClERERGTFKIiIiImKURFRERMUoiKiIiYpBAVERExSSEqIiJikkJURETEJIWoiIiISQpRERERkxSiIiIiJilERURETGpUiBYVFZ3VduDAgYtejIiISEty3hCtqKigoqKCn//851RWVvqXS0pKeOSRRy5VjSIiIs2S9Xwrp0yZwrZt2wC47rrr/rWR1UpKSkpgKxMREWnmzhuiy5cvB2DatGksXLjwkhQkIiLSUpw3RM9YuHAhBQUFVFZWYhiGv33AgAEBK0xERKS5a1SIPv/88yxfvpzY2Fh/m8Vi4aOPPgpYYSIiIs1do0I0KyuLDz74gPj4+EDXIyIi0mI06haXTp06KUBFRES+oVEz0SFDhvDMM8/w7//+74SGhvrbdU1URETaskaF6OrVqwHIycnxt+maqIiItHWNCtENGzYEug4REZEWp1Eh+sorr5yz/YEHHrioxYiIiLQkjQrRL7/80v+zy+Vix44dDBkyJGBFiYiItASNftjC1xUVFTFjxoyAFCQiItJSmHoVWnx8PAUFBRe7FhERkRblgq+JGobBnj17Gjy9SEREpC264GuicOrhC7/+9a8DUpCIiEhLcUHXRAsKCvB4PPTo0SOgRYmIiLQEjQrRvLw8fvnLX1JcXIzP5yM6OpqXXnqJ3r17B7o+ERGRZqtRXyyaO3cuEyZMYMeOHezatYtJkyYxZ86cQNcmIiLSrDUqREtLSxk1apR/+Y477qC8vDxgRYmIiLQEjQpRr9dLRUWFf7msrCxgBYmIiLQUjbomeu+99/LTn/6U1NRULBYL2dnZ3H///YGuTUREpFlr1Ew0OTkZALfbzcGDBykqKuInP/lJQAsTERFp7ho1E83MzGTs2LGMGzeO+vp6XnvtNaZPn86f//znQNcnIiLSbDVqJlpeXs64ceMACAkJYfz48TidzoAWJiIi0tw1+otFRUVF/uWSkhIMwwhYUSIiIi1Bo07njh8/nttvv50bb7wRi8VCbm5uox/79/TTT1NeXs5TTz3F3r17mTFjBjU1NSQmJjJnzhysVivHjh1j6tSplJaWctlll7Fo0SLatWtHVVUVTz75JPn5+cTExLBkyRIcDgcul4sZM2awZ88eQkNDWbRokR78ICIil1yjZqJ33nknr7zyCv3792fgwIEsX76c9PT079xu+/btvPPOO/7lqVOnMmvWLN5//30Mw2DVqlUAzJkzhzFjxpCTk8PAgQNZunQpAEuWLCExMZH169czevRo5s+fD8CKFSsICwtj/fr1TJ8+nWnTpl3wwEVERL6vRr8KrV+/fowfP5777ruPyy+//Dv7V1RUsHjxYiZOnAiceu5uXV0dgwcPBiAjI4OcnBzcbjc7duwgJSWlQTvAxo0b/WE9cuRINm/ejNvtZuPGjdx6660AXHPNNZSVlXHs2LELGLaIiMj316jTuWbMmjWLxx9/nMLCQgCKi4txOBz+9Q6Hg6KiIsrLy4mIiMBqtTZo/+Y2VquViIgIysrKzrmv48eP07lz50bXFxsb8b3HKM2PwxHZ1CWISBsSkBB988036dSpE0OGDGH16tUA+Hw+LBaLv49hGFgsFv+fX/fN5a9vExQUdNY2Z9ovRGnpCXy+xn85Sr+cWwans7qpSxCRFigoyGJqchWQEM3OzsbpdHLbbbdRWVnJyZMnsVgsDW6LKSkpIS4ujpiYGKqrq/F6vQQHB+N0OomLiwMgLi6OkpISEhIS8Hg81NTUEBUVRXx8PMXFxXTv3r3BvkRERC6lC5u+NdIrr7zCunXrWLNmDY899hhDhw5l4cKFhISEsGvXLgDWrFlDUlISNpuNxMREsrOzAcjKyiIpKQk49aSkrKws4FQwJyYmYrPZSE5OZs2aNQDs3LmTkJCQCzqVKyIicjEEJES/zaJFi1i4cCEjRozg5MmT/gc4zJ49m1WrVnHLLbewc+dOfvWrXwEwefJk/ud//oe0tDRWrlzJrFmzALjvvvtwuVykpaUxf/58nnnmmUs5DBEREQAsRht9aoKZa6Kl06cHsCL5vmIXLNA1URExxew10Us6ExUREWlNFKIiIiImKURFRERMUoiKiIiYpBAVERExSSEqIiJikkJURETEJIWoiIiISQpRERERkxSiIiIiJilERURETFKIioiImKQQFRERMUkhKiIiYpJCVERExCSFqIiIiEkKUREREZMUoiIiIiYpREVERExSiIqIiJikEBURETFJISoiImKSQlRERMQkhaiIiIhJClERERGTFKIiIiImKURFRERMUoiKiIiYpBAVERExSSEqIiJikrWpCxCRi8dVXIzz9b9Se2A/QSEhRCZeS2zGHQTZ7P/qU1RE3n/MpM8Lf8ISHPyt+zo84ze4i4oatHWfNYfQ7j0atFVtz+X48mVc/p+v+tsqNvyNkrVZBLeLIOFnEwjr3ce/7uiCuSRMmIg9Lu57jlak6SlERVoJw+Ph2B+WYO/cmW6ZM/FWV1H06nIAHD+9BwB3WSkFf1iM4Xafd18+txu300m3zBnYHA5/e3BEZIN+nqoqit9Y2bCtugrnm2/QZfIT1B06SPFfV9Bj1hwATvzj79g7d1GASquh07kirUTd4UO4iotIeGACIZ07E35FP2Jvz6Dq0+0AnPjHLo7+9j+wWG3fuS/38eNgsRDa8zKsHaL8/3xz5lq88r8J6dS54bZOJ0Hh7QjvdyURV/8I1/FCAAzDoPS9d4lNu/UijVik6SlERVoJW0ICXSY/QVBo6NdaLRgeDwA1e/YQO+oO4u4e8537qi8swNbRgcX67SerTvxjF66Cr4hOTWtYR0wMvpoTuEtLqcs7gjUm5lT/v+8kpFu3BjNbkZZOp3NFWglrZHus/Qf4lw2fj4oNfyOs7+UAxN93PwAn9+39zn25jh3DEhTEV0t+T/3RPOwJneh4512E9eoNgPdkDcUr/5tOD/0Sn9vVsI6oaKKGDefwtKlYbDY6PTQJwzAoe28dnX/5yMUarkizoBAVaaWcq16jPv8o3WfMvuBtXYXH8J6soeMdo7FGR1O5eRNfLXqannPnY+vowPnG67Qb/EPC+val5ovPz9receddxKSmYbHbCLLZqd7xGaE9LyM4IpKCPz5PfV4eHW5MIjb9tosxVJEmoxAVaWUMw8D5+koqNm6g88SHCenS5YL30ennE/G53QSHhQEQcm8Pag/sp2p7LqG9enNy7+f0nDv/vPsIbtfuVD0+H2XZ6+j8yGQqNvwNS3AwPebMI2/2TMIHDPTPbkVaIoWoSCti+HwUvfoyVZ9up9NDk4j44dWm9mOxWgn+2vVQi8WCvVMnPOXlVH/6CZ7KSg5O+dWplT4fAPsf/gVdJj9B+OVXNNhX9Y5PCe3VG1tsLLUHD9Duqh8QHBZGWO/e1B06qBCVFk0hKtKKOFe9TvVnn9D5l48SMWiw6f3kzZtD5I8SiTn9pSHD56P+q3yikm4m8vohxKSl+/vWHTzA8Zf/TI9Zc7FGRzfYj+HzUbY+my6PnQ5ciwUMw7/uzM8iLZVCVKSVqD14gIq/fUDHjDsJ7dkTT2WFf521Q9R5tzV8PrzVVQS3i8BitRIxaDBl76/H3qUr9rg4yj94H19NDe3/7UaCw8OhfXv/tu7SEgDs8fFn7bf6k+2E9e2LLSYWgNAePanetZOwPn2p/fJLon+ScjGGLtJkFKIiFyimfQjBIfbv7niJHV63G4CS1W9RsvqtBut+vHqV/x7PyuPhfAU4HJH+trqiYnZN+RUD582hw1UD6Xj/PeSHWilauQJPVRURl/flqnlzaNfj7KC0dQij4PT+vs7wevnqo/fpP2smIR1PrYu+axT/97vf89Wip0gYkUL3IeZON5+Pt95FWVX9Rd+vyLlYDKNtnk8pLT2Bz9f4oTsckZROnx7AiuT7il2wAKezOuDH0WehebtUnwNpXYKCLMTGRlz4dgGoRUREpE1QiIqIiJikEBURETFJISoiImKSQlRERMQkhaiIiIhJClERERGTFKIiIiImBTREX3jhBdLS0khLS+OZZ54BIDc3l/T0dIYPH87ixYv9fffu3UtGRgYpKSnMmDEDz+kXCR87doyxY8cyYsQIJk2aRE1NDQBVVVU89NBDpKamMnbsWJxOZyCHIiIicpaAhWhubi5bt27lnXfeISsri88//5x169Yxffp0li5dSnZ2Nnv27GHTpk0ATJ06lVmzZvH+++9jGAarVq0CYM6cOYwZM4acnBwGDhzI0qVLAViyZAmJiYmsX7+e0aNHM3/++V/LJCIicrEFLEQdDgeZmZnY7XZsNhu9e/fmyJEj9OjRg27dumG1WklPTycnJ4eCggLq6uoYPPjUWycyMjLIycnB7XazY8cOUlJSGrQDbNy4kfT0U2+SGDlyJJs3b8btdgdqOCIiImcJ2APo+/bt6//5yJEjrF+/nnvvvReHw+Fvj4uLo6ioiOLi4gbtDoeDoqIiysvLiYiIwHr6vYZn2oEG21itViIiIigrKyP+HG+SOBczz0iU5u+bD0GXtkmfA7lUAv4Wl/2iimUCAAAMnklEQVT79/OLX/yCX//61wQHB3PkyBH/OsMwsFgs+Hw+LBbLWe1n/vy6by5/fZugoMZPrM08gF6av0v1AHpp3vQAerlQzfIB9Lt27WL8+PFMmTKFUaNGkZCQ0OALQE6nk7i4uLPaS0pKiIuLIyYmhurqarxeb4P+cGoWW1Jy6j2GHo+HmpoaoqLO/85EERGRiylgIVpYWMjDDz/MokWLSEtLA2DQoEEcPnyYvLw8vF4v69atIykpiS5duhASEsKuXbsAWLNmDUlJSdhsNhITE8nOzgYgKyuLpKQkAJKTk8nKygIgOzubxMREbDZboIYjIiJyloCdzl2+fDn19fU89dRT/ra7776bp556ikcffZT6+nqSk5MZMWIEAIsWLWLmzJmcOHGCAQMGMG7cOABmz55NZmYmL774Ip06deLZZ58FYPLkyWRmZpKWlkZkZCSLFi0K1FBERETOSS/lbiS9iLn500u5BfRSbjGnWV4TFRERac0UoiIiIiYpREVERExSiIqIiJikEBURETFJISoiImKSQlRERMQkhaiIiIhJClERERGTFKIiIiImKURFRERMUoiKiIiYpBAVERExSSEqIiJikkJURETEJIWoiIiISQpRERERkxSiIiIiJilERURETFKIioiImKQQFRERMUkhKiIiYpJCVERExCSFqIiIiEkKUREREZMUoiIiIiYpREVERExSiIqIiJikEBURETFJISoiImKSQlRERMQkhaiIiIhJClERERGTFKIiIiImKURFRERMUoiKiIiYpBAVERExSSEqIiJikrWpCxARkcDwud0c/e1/4Lh7DO36DzhvX8PjIW/uLCJ+dA0dbxt1qs3rpfTdNVRt34avpobQy3rhuOdeQjp3BqB2/36Ov7wMX20dsRl3EJV0k39/zjdeI6Rbd9r/+IaAja850ExURKQV8rldHF/2J1zHChrVv3TdWlzHjjVoK1v/HlXbthA/7gG6z5yNNTqagiW/x1dfD0DxyhV0uDGZTr+YhPO1v+KtrgbAU1nByX1fEHn9kIs7qGZIISoi0srUHysgf8FvcTmLG9c/P5/KLZuxJ3Rq0F61bSsxI2+l3YCB2BM6ET/uAbw1J6jd/38AuI4XEnF1IuFX9icoPByX0wlAWfZ7RA9PxRLU+iOm9Y9QRKSNqd3/JeH9B9J92szv7Gv4fBx/dTmOO0cTFBHRYF38uPFEDL76Xw0WCxgGhtsNgDUmlrqjR3CXluCrqcEWE42nopzaL/cRed31F3VMzZWuiYqItDJRyTc3um/5++sJjoig/ZAbqNi0scG68Cv7N1iu3LIJw+sltFdvADreMZrj//kShsdDzC0jsUZFU/TX/yJ6xC1tYhYKClERkTbLdfw4Ze+vp8fM2d/Zt3b/fpyrXj8Vlh2iAIi8+ke0W/IChsdNcHg73GWl1B3YT9w991Ky+i2qPsklrHcf4sc/SFBISKCH0yTaxv8qiIhIA4ZhUPSXl4m9JR1bR8d5+57ct5eC535PxKDBxKbf1mBdkN1OcHg7AMree5fo1DTqDh+i6rNP6Dl3PobPR8WGvwVsHE1NM1ERkTbIU1ZK7f4vqcs7Qsma1QAYLhd1hw9Rd/gQXX81BYATu/+XwhdfIGLwD0mY8ItvPU3rLi2h7tAh4saOo+JvHxB2WS+CQsMIv7I/NZ/vuWTjutQUoiIibZA1Kpqe859u0Fa47EXCevchOjUNgNpDB08FaOI1JDww4bzXOUvfXUvMLSNP97FgGAZw6otLnP65NVKIioi0IZ7qKoJsdoJCQ7HHxzdYZ7HZCGrXDlt09KnTva8ux965C447RuOtrvL3CwoLJ8hu9y+7nMXUH80j/v4HAAjp2ZOy9e9Rn3+UE3/f9Z0PemjJFKIiIm3I0XlzaP/jf/M/lejbuI4V+B++cOjJxxusix/3AB2Skv3LZWdmoRYLAOGXX0HkddeR/8xCwi6/gqihwy7yKJoPi2G04nn2eZSWnsDna/zQHY5ISqdPD2BF8n3FLliA01kd8OPos9C8XarPQUz7EIJD7N/dUZqEt95FWVV9o/sHBVmIjY347o7f0KJnou+++y4vvvgiHo+H+++/n7FjxzZ1SSLSRgSH2PU/U81Y7IIFQOND1KwWG6JFRUUsXryY1atXY7fbufvuu7nuuuvo06dPU5cmIiJtRIsN0dzcXK6//nqiok7d9JuSkkJOTg6PPPJIo7YPCrJc8DGDTh9Lmi8z/15NHUefhWZNnwOBC/scmP3MtNgQLS4uxuH41w3CcXFx7N69u9HbR0e3u+BjRv/61xe8jVxaZq5pmKHPQvOmz4HApfkctNgnFvl8Pv83weDU0ze+viwiIhJoLTZEExIScJ5+7Q6A0+kkLi6uCSsSEZG2psWG6I9//GO2b99OWVkZtbW1fPDBByQlJTV1WSIi0oa02Gui8fHxPP7444wbNw63282dd97JD37wg6YuS0RE2pA2+7AFERGR76vFns4VERFpagpRERERkxSiIiIiJilERURETFKIioiImKQQbSOee+45brnlFtLS0njllVcA+Mc//sFdd91FWloaTzzxBC6Xq4mrlEDbsGEDGRkZpKamMm/ePODUc6jT09MZPnw4ixcvbuIK5VI5ceIEI0eO5KuvvgLgjTfeYOTIkaSnpzNt2jT9PmgkhWgb8Nlnn/HJJ5+wdu1a3n77bVasWMG+fft49NFHmTt3Lu+99x4Ab731VhNXKoGUn5/P7NmzWbp0KWvXruWLL75g06ZNTJ8+naVLl5Kdnc2ePXvYtGlTU5cqAfa///u/3HPPPRw5cgSAw4cPs3z5cl5//XXWrl2Lz+dj5cqVTVtkC6EQbQOuvfZa/uu//gur1UppaSler5e9e/cyePBg+vXrB8DMmTP5yU9+0sSVSiB9+OGH3HLLLSQkJGCz2Vi8eDFhYWH06NGDbt26YbVaSU9PJycnp6lLlQBbtWoVs2fP9j8q1W63M3v2bCIiIrBYLFx++eUcO3asiatsGVrsE4vkwthsNp5//nlefvllRowYgdPpJDw8nMcff5xDhw5x9dVXk5mZ2dRlSgDl5eVhs9mYOHEihYWF3HTTTfTt2/estyEVFRU1YZVyKcyfP7/BcpcuXejSpQsAZWVl/PWvf2XhwoVNUVqLo5loG/LYY4+xfft2CgsLcblcbN26lSeeeILVq1dTW1vLsmXLmrpECSCv18v27dtZsGABb7zxBrt37yY/P19vQxK/oqIi7r//fu644w6uu+66pi6nRVCItgEHDx5k7969AISFhTF8+HCWLVvGoEGD6NatG8HBwaSmpl7Q+1il5enYsSNDhgwhJiaG0NBQhg0bRm5urt6GJMCp3xN33303o0aN4uGHH27qcloMhWgb8NVXXzFz5kxcLhcul4uPPvqIuXPn8vnnn1NYWAjAxx9/zIABA5q4Ugmkm2++ma1bt1JVVYXX62XLli2MGDGCw4cPk5eXh9frZd26dXobUht04sQJHnzwQSZPnszPfvazpi6nRdE10TYgOTmZ3bt3c/vttxMcHMzw4cO5/fbbiYqKYuLEidTX13PllVfym9/8pqlLlQAaNGgQEyZMYMyYMbjdbm644QbuueceevXqxaOPPkp9fT3JycmMGDGiqUuVS+ytt96ipKSEV155xX8L3NChQ5k8eXITV9b86S0uIiIiJul0roiIiEkKUREREZMUoiIiIiYpREVERExSiIqIiJikW1xEWol58+axY8cO4NSN8126dCE0NBQ49YaOMz+LyMWjW1xEWqGhQ4fy3HPPcdVVVzV1KSKtmmaiIm3A/v37mT9/vv9pRePHj2fUqFHk5ubyzDPPEBISQl1dHVOnTuWPf/wjDoeDvLw8wsPDmTBhAitWrODIkSOkpqbqoRwiX6MQFWnl3G43kydP5tlnn6Vfv35UVVVx11130adPHwC+/PJLNmzYQEJCArm5uezevZu3336bfv368cADD7B8+XL+8pe/UFVVxY033siECROIjY1t4lGJNA8KUZFW7uDBg+Tn5zeYQbpcLvbu3UvXrl3p0qULCQkJ/nXdu3f3v2e2W7dudOzYEZvNRmxsLOHh4VRUVChERU5TiIq0cj6fj6ioKNasWeNvczqdtG/fnl27dhEeHt6gv91ub7BsterXhMi30S0uIq1cnz59CAoK4r333gOgoKCAkSNHsm/fviauTKTlU4iKtHJ2u50XX3yR1157jfT0dCZMmMCUKVMYNGhQU5cm0uLpFhcRERGTNBMVERExSSEqIiJikkJURETEJIWoiIiISQpRERERkxSiIiIiJilERURETPr//LsBidwlzYkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 504x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [7, 5])\n",
    "order = df['Term'].value_counts().index\n",
    "plt.title('Term (in months)')\n",
    "ax = sb.countplot(data = df, x = 'Term', color = '#ff6666', order=order)\n",
    "sb.set()\n",
    "\n",
    "totals = []\n",
    "\n",
    "for i in ax.patches:\n",
    "    totals.append(i.get_height())\n",
    "\n",
    "total = sum(totals)\n",
    "\n",
    "for i in ax.patches:\n",
    "    ax.text(i.get_x()+.29, i.get_height()-3, \\\n",
    "            str(round((i.get_height()/total)*100, 2))+'%', fontsize=14,\n",
    "                color='r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> The graph demonstrates that around 77.04% of users prefer to have a 3 years term loan, while only 1.42% tend to take a one-year loan term.\n",
    "\n",
    "Next, I'm going to inspect the Monthly Loan Payment feature."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# insight into the monthly loan payment\n",
    "# since we have multiple values, we're going to take top 5 only\n",
    "plt.figure(figsize = [10, 5])\n",
    "plt.title('Monthly Loan Payment')\n",
    "order = df['MonthlyLoanPayment'].value_counts().index[:5]\n",
    "sb.countplot(data = df, y = 'MonthlyLoanPayment', order=order, color='#ff7777')\n",
    "sb.set();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> The graph shows that most borrowers pay 137.71 dollars per month.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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",
    "> Initially, I dropped multiple columns to decrease the overhead of the dataset. For loan status the distribution was not clear, therefore I used the log function to balance the scale and show the distribution more clearly. Also, I combined the past due category into one category, add in progress category to current and drop cancelled because this will be more relevant for our analysis. For the Occupation feature, the list has a lot of unique values, therefore I selected only the top ten values. For the monthly loan payment, I followed the same approach of the previous feature while taken only the top five values.\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 univariate exploration was as expected with some interesting insights:\n",
    "- Loan Status: most loans were current and least were past due. \n",
    "- ProsperRatingAlpha: the most risk scale fills under C, B, and A respectively, those categories indicate a risk from 9-18%, moderate risk levels. \n",
    "- IncomeRange: most income range for prosper loans beneficial had from 25000 to 49999 dollars.\n",
    "- BorrowerState: CA is the top state of borrowing prosper loans among all the state followed by TX, NY, and FL with a slight difference among them.\n",
    "- Occupation: the result was irrelevant, no need to further investigating this feature.\n",
    "- InterestRate: the distribution seems bimodal, since it has two peaks. Also, a major lack of fit exists on the right side of the observed distribution where the second peak appears.\n",
    "- Term: most loans have a 3 years period.\n",
    "- MonthlyLoanPayment: most borrowers pay 137.71 dollars per month.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Bivariate Exploration\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### ProsperRatingAlpha vs LoanStatus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [15, 20])\n",
    "ax = plt.subplot(3, 1, 3)\n",
    "sb.countplot(data = df, x = 'ProsperRatingAlpha', hue = 'LoanStatus', palette = 'Greens')\n",
    "ax.legend(loc = 1, ncol = 2) # re-arrange legend to remove overlapping\n",
    "plt.title('Risk Factor VS Loan Status')\n",
    "plt.xlabel('Risk Types')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "I was interested to compare the risk level with the loan status. As expacted, most of the current loans were under C, B, and A respectively moderate risk levels while most completed loans fill under D risk category. The graph also indicates that a little amount of current and completed loans were under AA (lower risk) risk category only. This an interesting relationship as almost a significant amount of prosper's loan borrowers tend to take moderate to higher level category risk."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### CreditGrade vs LoanOriginalAmount"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [9, 5])\n",
    "plt.title('CreditGrade vs LoanOriginalAmount ($)')\n",
    "base_color = sb.color_palette()[0]\n",
    "# use count scale to get grasp into the distribution\n",
    "sb.violinplot(data = df, x = 'CreditGrade', y = 'LoanOriginalAmount', color = base_color,\n",
    "              inner = 'quartile', scale='count');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "A very interesting relation represented using the above violin plot. The graph shows the distribution shape of all credit grade compared to loan original amount. Almost credit grade AA, A, B, C, and D had the largest values and reasonable distribution shape. According to the loan original amount values, the median of credit grade A was the largest followed by B then AA respectively. This correlation indicates that as credit grade get higher as the original amount of loans increases. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### CreditGrade vs Term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [11, 10])\n",
    "ax = plt.subplot(3, 1, 3)\n",
    "sb.countplot(data = df, x = 'CreditGrade', hue = 'Term', palette = 'Blues')\n",
    "ax.legend(loc = 1, ncol = 2) \n",
    "plt.title('Credit Grade VS Term (in months)')\n",
    "plt.xlabel('Credit Grade')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> The graph shows the relation between credit grade and term, a great portion of C credit grade owners tend to have a 3 years period loan. Since there is no relevant relation indicated no need to investigate it more."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### Term vs InterestRate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [12, 6])\n",
    "base_color = sb.color_palette()[0]\n",
    "\n",
    "# violin plot\n",
    "plt.subplot(1, 2, 1)\n",
    "ax1 = sb.violinplot(data = df, x = 'Term', y = 'InterestRate', color = base_color, scale='count')\n",
    "plt.title('Interest Rate % vs Term(in months)')\n",
    "\n",
    "# box plot\n",
    "plt.subplot(1, 2, 2)\n",
    "sb.boxplot(data = df, x = 'Term', y = 'InterestRate', color = base_color)\n",
    "\n",
    "plt.title('Interest Rate % vs Term(in months)')\n",
    "plt.ylim(ax1.get_ylim());\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "The box plot above shows that the higher median of interest rate was represented in the 5 years term loans which approximately reach a 0.19. Also, the lowest median was associated with one-year term loans as expected. The violin graph shows the distribution more clearly, which indicate most contributed loans were 3 years term period with a median of interest rate equal to 0.17 approximately. As represented, loans taken by one year period have less interest rates than the longer term loans."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### LoanOriginalAmount vs MonthlyLoanPayment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [12, 10])\n",
    "bin_size = 0.25\n",
    "xbin_edges = np.arange(0.5, df['LoanOriginalAmount'].max()+bin_size, bin_size)\n",
    "xbin_centers = (xbin_edges + bin_size/2)[:-1]\n",
    "\n",
    "# compute each bin\n",
    "data_xbins = pd.cut(df['LoanOriginalAmount'], xbin_edges, right = False, include_lowest = True)\n",
    "y_means = df['MonthlyLoanPayment'].groupby(data_xbins).mean()\n",
    "y_sems = df['MonthlyLoanPayment'].groupby(data_xbins).sem()\n",
    "\n",
    "# error bar represent the amount of data by points\n",
    "plt.errorbar(x = xbin_centers, y = y_means, yerr = y_sems)\n",
    "plt.title('Loan Original Amount VS Monthly Payment line graph(Mean)')\n",
    "plt.xlabel('Loan Original Amount ($)')\n",
    "plt.ylabel('Monthly Payment ($)');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> The line graph above represents the mean of the original amount of loans with monthly payment rate. The plot has a healthy trend line, the monthly payment amount increases as the amount of the orignal loan get higher. To resolve the higher monthly payment amount, first borrower has to minimize the amount of original loan amount; secondly, they should extend the term of the loan for example from 3 years to 5."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "#### BorrowerAPR vs CreditGrade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [16, 7])\n",
    "base_color = sb.color_palette()[0]\n",
    "\n",
    "# strip plot\n",
    "ax1 = sb.stripplot(data = df, x = 'BorrowerAPR', y = 'CreditGrade',\n",
    "                   color = base_color)\n",
    "\n",
    "plt.title('Borrower APR % VS CreditGrade');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "> The plot above indicates a strong correlation between ARP rate and credit grade. As the credit grades get higher as the ARP rates get lower.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### InterestRate vs CreditGrade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize = [16, 7])\n",
    "base_color = sb.color_palette()[0]\n",
    "\n",
    "# strip plot\n",
    "ax1 = sb.stripplot(data = df, x = 'InterestRate', y = 'CreditGrade',\n",
    "                   color = base_color)\n",
    "\n",
    "plt.title('Interest Rate % vs CreditGrade');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "As expected as the credit grade increases as the interest rate decrease. A strong correlation indicated in the above graph."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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",
    "> A significant amount of insights between the features investigated were as expected:\n",
    "- ProsperRatingAlpha vs LoanStatus: most of the current loans were under C, B, and A respectively moderate risk levels while most completed loans fill under D risk category. The graph also indicates that a little amount of current and completed loans were under AA (lower risk) risk category only. This an interesting relationship as almost a significant amount of prosper's loan borrowers tend to take moderate to higher level category risk.\n",
    "- CreditGrade vs LoanOriginalAmount: A very interesting relation represented, the graph shows the distribution shape of all credit grade compared to loan original amount. Almost credit grade AA, A, B, C, and D had the largest values and reasonable distribution shape. According to the loan original amount values, the median of credit grade A was the largest followed by B then AA respectively. This correlation indicates that as credit grade get higher as the original amount of loans increases.\n",
    "- CreditGrade vs Term: a great portion of C credit grade owners tend to have a 3 years period loan. Since there is no relevant relation indicated no need to investigate it more.\n",
    "- Term vs InterestRate: the higher median of interest rate was represented in the 5 years term loans which approximately reach a 0.19. Also, the lowest median was associated with one-year term loans as expected. The distribution indicates that the most contributed loans were 3 years term period with a median of interest rate equal to 0.17 approximately. As represented, loans taken by one year period have less interest rates than the longer term loans.\n",
    "- BorrowerAPR vs CreditGrade: a strong correlation was indicated between ARP rate and credit grade. As the credit grades get higher as the ARP rates get lower.\n",
    "- InterestRate vs CreditGrade: As expected as the credit grade increases as the interest rate decrease. A strong correlation indicated.\n",
    "\n",
    "### Did you observe any interesting relationships between the other features (not the main feature(s) of interest)?\n",
    "\n",
    "> A few usual relations were represented \n",
    "- LoanOriginalAmount vs MonthlyLoanPayment: the plot has a healthy trend line for the mean of both variables, the monthly payment amount increases as the amount of the orignal loan get higher. To resolve the higher monthly payment amount, first borrower has to minimize the amount of original loan amount; secondly, they should extend the term of the loan for example from 3 years to 5."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Multivariate Exploration\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### LoanOriginalAmount vs MonthlyLoanPayment vs Term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "g = sb.PairGrid(data = df, vars = ['LoanOriginalAmount', 'MonthlyLoanPayment', 'Term'])\n",
    "g.map_diag(plt.hist)\n",
    "g.map_offdiag(plt.scatter)\n",
    "g.fig.subplots_adjust(top=0.93, wspace=0.3)\n",
    "g.fig.suptitle('Loan Original Amount vs MonthlyLoanPayment vs Term (in months)');\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "The pair grid above used to investigate the relation between LoanOriginalAmount, MonthlyLoanPayment and Term more. One indication from the read of the above graph that almost all the one year borrowers tend to pay there monthly amount comparing with the other terms. Also, as the higher number of users tend to have three years period term they don't show commitment to pay their monthly portion. To resolve this issue, the borrowers who struggle with their monthly payment rate should extend the term from 3 years to 5 years and borrow a lesser amount of loan.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### BorrowerAPR vs InterestRate vs ProsperRatingNumeric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [16, 7])\n",
    "plt.scatter(data = df, x = 'BorrowerAPR', y = 'InterestRate', c = 'ProsperRatingNumeric')\n",
    "plt.colorbar()\n",
    "plt.xlabel('Borrower APR')\n",
    "plt.ylabel('Interest Rates')\n",
    "plt.title('Borrower APR vs Interest Rates vs ProsperRating');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "The scatter plot above shows a strong correlation between APR, interest rate and prosper rating of the risk. As the prosper rating gets higher as both APR & interest rate get lower. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### LoanOriginationQuarter vs InterestRate vs Term"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = [16, 7])\n",
    "ax = sb.pointplot(data = df, x = 'LoanOriginationQuarter', y = 'InterestRate', hue = 'Term',\n",
    "                  dodge = 0.3, linestyles = \"\")\n",
    "plt.xlabel('Loan Origination Quarter')\n",
    "plt.ylabel('Interest Rates')\n",
    "plt.title('Loan Origination Quarter vs Interest Rates vs Term (in months)')\n",
    "plt.xticks(rotation = 90);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Observation:\n",
    "\n",
    "The point plot above shows the relation between Loan Origination Quarter, Interest Rates, and Term to inspect if the interest rate is fixed with term and loan quarter. For one-year term loans specifically in Q4 of 2010, the interest rate was the lowest, While in Q2 and Q3 of 2011 was the highest. Moreover while reading the three years term interest rate,  almost all rates have a fixed interest rate amount between 0.14 - 0.24 distributed among all quarters; while the lowest was in Q4 of 2005 which was equal to 0.089. Moving to the five years term, the interest rate doesn't have a fixed range but the lowest was in Q4 of 2010. To conclude the 1 year period loan had the lowest interest rate among all quarters as shown in the above graph. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "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",
    "> Interesting insights were extracted:\n",
    "- LoanOriginalAmount vs MonthlyLoanPayment vs Term: almost all the one year borrowers tend to pay there monthly amount comparing with the other terms. Also, as the higher number of users tend to have three years period term they don't show commitment to pay their monthly portion. To resolve this issue, the borrowers who struggle with their monthly payment rate should extend the term from 3 years to 5 years and borrow a lesser amount of loan.\n",
    "- BorrowerAPR vs InterestRate vs ProsperRatingNumeric: a strong correlation between APR, interest rate and prosper rating of the risk was represented. As the prosper rating gets higher as both APR & interest rate get lower.\n",
    "- LoanOriginationQuarter vs InterestRate vs Term: for one-year term loans specifically in Q4 of 2010, the interest rate was the lowest, While in Q2 and Q3 of 2011 was the highest. Moreover while reading the three years term interest rate, almost all rates have a fixed interest rate amount between 0.14 - 0.24 distributed among all quarters; while the lowest was in Q4 of 2005 which was equal to 0.089. Moving to the five years term, the interest rate doesn't have a fixed range but the lowest was in Q4 of 2010. To conclude the 1 year period loan had the lowest interest rate among all quarters as shown in the above graph.\n",
    "\n",
    "\n",
    "### Were there any interesting or surprising interactions between features?\n",
    "\n",
    "> I expected the interest rate for one year term period to be the lowest of all times but surprisingly at Q2 and Q3 of 2011 was slightly higher than the five years term period. I think there might be factors based on the years quarters would affect the normal interest rate distribution. As among the rest of the quarters represented in the 'LoanOriginationQuarter vs InterestRate vs Term' graph, the interest rate for a one-year period has a normal and lower interest rates as expected. "
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    "### Resources:\n",
    "- https://www.udacity.com/\n",
    "- https://en.wikipedia.org/wiki/Prosper_Marketplace\n",
    "- https://www.lendingmemo.com/risk-grades-lending-club-prosper/\n",
    "- https://help.lendingclub.com/hc/en-us/articles/216127747-What-is-the-difference-between-a-loan-that-is-in-default-and-a-loan-that-has-been-charged-off-\n",
    "- https://robertmitchellv.com/blog-bar-chart-annotations-pandas-mpl.html\n",
    "- https://matplotlib.org/api/text_api.html?highlight=get_text#matplotlib.text.Text\n",
    "- https://datavizcatalogue.com/methods/violin_plot.html\n",
    "\n"
   ]
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