Lending_club.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Lending Club Loan Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import R libraries:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "library(dplyr)\n",
    "\n",
    "library(lubridate)\n",
    "library(ggplot2)\n",
    "library(dplyr)\n",
    "library(stringr)\n",
    "library(caret)\n",
    "library(rpart)\n",
    "#library(rattle)\n",
    "library(ROSE)\n",
    "library(ROCR)\n",
    "library(MASS)\n",
    "library(ipred)\n",
    "library(plyr)\n",
    "library(rpart.plot)\n",
    "require(gridExtra) # also loads grid\n",
    "\n",
    "library(data.table)\n",
    "options(datatable.print.nrows = 500)\n",
    "options(width = 110)\n",
    "options(repr.plot.width=11, repr.plot.height=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Set working path:\n",
    "wkdir = \"/Users/qiaolinchen/Documents/LendingClub/\"\n",
    "raw_data_path = paste0(wkdir, 'raw_data/')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.Load data from CSV files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_2017Q1 = read.csv(paste0(raw_data_path, \"LoanStats_securev1_2017Q1.csv\"))\n",
    "df_2017Q2 = read.csv(paste0(raw_data_path, \"LoanStats_securev1_2017Q2.csv\"))\n",
    "df_2017Q3 = read.csv(paste0(raw_data_path, \"LoanStats_securev1_2017Q3.csv\"))\n",
    "\n",
    "df_2016Q1 = read.csv(paste0(raw_data_path, \"LoanStats_securev1_2016Q1.csv\"))\n",
    "df_2016Q2 = read.csv(paste0(raw_data_path, \"LoanStats_securev1_2016Q2.csv\"))\n",
    "df_2016Q3 = read.csv(paste0(raw_data_path, \"LoanStats_securev1_2016Q3.csv\"))\n",
    "df_2016Q4 = read.csv(paste0(raw_data_path, \"LoanStats_securev1_2016Q4.csv\"))\n",
    "\n",
    "df_2015   = read.csv(paste0(raw_data_path, \"LoanStats3d_securev1.csv\"))\n",
    "df_2014   = read.csv(paste0(raw_data_path, \"LoanStats3c_securev1.csv\"))\n",
    "df_1213   = read.csv(paste0(raw_data_path, \"LoanStats3b_securev1.csv\"))\n",
    "df_2011   = read.csv(paste0(raw_data_path, \"LoanStats3a_securev1.csv\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_2016= rbind(df_2016Q1, df_2016Q2, df_2016Q3, df_2016Q4)\n",
    "df_2017= rbind(df_2017Q1, df_2017Q2, df_2017Q3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>1646781</li>\n",
       "\t<li>151</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 1646781\n",
       "\\item 151\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 1646781\n",
       "2. 151\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 1646781     151"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Concatenate all data in to a big dataset\n",
    "df_raw = rbind( df_2017, df_2016, df_2015,  df_2014,df_1213, df_2011 )\n",
    "dim(df_raw)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>issue_d</th><th scope=col>funded_amnt</th><th scope=col>funded_amnt_inv</th><th scope=col>last_credit_pull_d</th><th scope=col>next_pymnt_d</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>Mar-17</td><td>14000 </td><td>14000 </td><td>Dec-17</td><td>Jan-18</td></tr>\n",
       "\t<tr><td>Mar-17</td><td> 5000 </td><td> 5000 </td><td>Dec-17</td><td>Jan-18</td></tr>\n",
       "\t<tr><td>Mar-17</td><td> 4600 </td><td> 4600 </td><td>Dec-17</td><td>Jan-18</td></tr>\n",
       "\t<tr><td>Mar-17</td><td>14000 </td><td>14000 </td><td>Dec-17</td><td>Jan-18</td></tr>\n",
       "\t<tr><td>Mar-17</td><td>15000 </td><td>15000 </td><td>Dec-17</td><td>Jan-18</td></tr>\n",
       "\t<tr><td>Mar-17</td><td>15400 </td><td>15400 </td><td>Dec-17</td><td>Jan-18</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       " issue\\_d & funded\\_amnt & funded\\_amnt\\_inv & last\\_credit\\_pull\\_d & next\\_pymnt\\_d\\\\\n",
       "\\hline\n",
       "\t Mar-17 & 14000  & 14000  & Dec-17 & Jan-18\\\\\n",
       "\t Mar-17 &  5000  &  5000  & Dec-17 & Jan-18\\\\\n",
       "\t Mar-17 &  4600  &  4600  & Dec-17 & Jan-18\\\\\n",
       "\t Mar-17 & 14000  & 14000  & Dec-17 & Jan-18\\\\\n",
       "\t Mar-17 & 15000  & 15000  & Dec-17 & Jan-18\\\\\n",
       "\t Mar-17 & 15400  & 15400  & Dec-17 & Jan-18\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "issue_d | funded_amnt | funded_amnt_inv | last_credit_pull_d | next_pymnt_d | \n",
       "|---|---|---|---|---|---|\n",
       "| Mar-17 | 14000  | 14000  | Dec-17 | Jan-18 | \n",
       "| Mar-17 |  5000  |  5000  | Dec-17 | Jan-18 | \n",
       "| Mar-17 |  4600  |  4600  | Dec-17 | Jan-18 | \n",
       "| Mar-17 | 14000  | 14000  | Dec-17 | Jan-18 | \n",
       "| Mar-17 | 15000  | 15000  | Dec-17 | Jan-18 | \n",
       "| Mar-17 | 15400  | 15400  | Dec-17 | Jan-18 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  issue_d funded_amnt funded_amnt_inv last_credit_pull_d next_pymnt_d\n",
       "1 Mar-17  14000       14000           Dec-17             Jan-18      \n",
       "2 Mar-17   5000        5000           Dec-17             Jan-18      \n",
       "3 Mar-17   4600        4600           Dec-17             Jan-18      \n",
       "4 Mar-17  14000       14000           Dec-17             Jan-18      \n",
       "5 Mar-17  15000       15000           Dec-17             Jan-18      \n",
       "6 Mar-17  15400       15400           Dec-17             Jan-18      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(df_raw[,c('issue_d','funded_amnt', 'funded_amnt_inv','last_credit_pull_d','next_pymnt_d')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# check missingness of columns removed\n",
    "missing_pct <- function(df, type= 'pct'){\n",
    "    na_count <-sapply(df, function(y) sum(length(which(is.na(y)))))\n",
    "    if (type=='pct'){round( na_count/dim(df)[1] *100, digits=3)}\n",
    "    else {na_count}\n",
    "}                      \n",
    "# check missing percentage           \n",
    "#missing_pct(df_all)    \n",
    "\n",
    "# define a function to show frequency including missing: \n",
    "table1 = function (..., useNA = 'ifany') base::table(..., useNA = useNA)\n",
    "\n",
    "# define a function to count missing observation by year\n",
    "missing_by_year = function( df = df1 , column ){\n",
    "    aggregate(get(column) ~ Year, data= df, function(x) {sum(is.na(x))}, na.action = NULL)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Feature Engineering\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1 Parse dates and compute date intervals\n",
    "```R\n",
    "parse_date = function(dt){\n",
    "    # parse month-year as first day of the month\n",
    "    as.character( as.Date(paste0('01-',dt) , \"%d-%b-%y\") )\n",
    "}\n",
    "parse_date('Mar-17')\n",
    "date_list = c('issue_d', 'earliest_cr_line','last_pymnt_d')\n",
    "# apply( head(df_all[date_list]),1:2, parse_date )\n",
    "\n",
    "df_all[, date_list] = apply(df_all[, date_list] ,1:2, parse_date)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# make a copy\n",
    "df_all= data.frame(df_raw)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>issue_d</th><th scope=col>earliest_cr_line</th><th scope=col>last_pymnt_d</th><th scope=col>next_pymnt_d</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>2017-03-01</td><td>1996-05-01</td><td>2017-12-01</td><td>2018-01-01</td></tr>\n",
       "\t<tr><td>2017-03-01</td><td>2004-01-01</td><td>2017-12-01</td><td>2018-01-01</td></tr>\n",
       "\t<tr><td>2017-03-01</td><td>2003-12-01</td><td>2017-12-01</td><td>2018-01-01</td></tr>\n",
       "\t<tr><td>2017-03-01</td><td>1974-02-01</td><td>2017-12-01</td><td>2018-01-01</td></tr>\n",
       "\t<tr><td>2017-03-01</td><td>1974-11-01</td><td>2017-12-01</td><td>2018-01-01</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       " issue\\_d & earliest\\_cr\\_line & last\\_pymnt\\_d & next\\_pymnt\\_d\\\\\n",
       "\\hline\n",
       "\t 2017-03-01 & 1996-05-01 & 2017-12-01 & 2018-01-01\\\\\n",
       "\t 2017-03-01 & 2004-01-01 & 2017-12-01 & 2018-01-01\\\\\n",
       "\t 2017-03-01 & 2003-12-01 & 2017-12-01 & 2018-01-01\\\\\n",
       "\t 2017-03-01 & 1974-02-01 & 2017-12-01 & 2018-01-01\\\\\n",
       "\t 2017-03-01 & 1974-11-01 & 2017-12-01 & 2018-01-01\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "issue_d | earliest_cr_line | last_pymnt_d | next_pymnt_d | \n",
       "|---|---|---|---|---|\n",
       "| 2017-03-01 | 1996-05-01 | 2017-12-01 | 2018-01-01 | \n",
       "| 2017-03-01 | 2004-01-01 | 2017-12-01 | 2018-01-01 | \n",
       "| 2017-03-01 | 2003-12-01 | 2017-12-01 | 2018-01-01 | \n",
       "| 2017-03-01 | 1974-02-01 | 2017-12-01 | 2018-01-01 | \n",
       "| 2017-03-01 | 1974-11-01 | 2017-12-01 | 2018-01-01 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  issue_d    earliest_cr_line last_pymnt_d next_pymnt_d\n",
       "1 2017-03-01 1996-05-01       2017-12-01   2018-01-01  \n",
       "2 2017-03-01 2004-01-01       2017-12-01   2018-01-01  \n",
       "3 2017-03-01 2003-12-01       2017-12-01   2018-01-01  \n",
       "4 2017-03-01 1974-02-01       2017-12-01   2018-01-01  \n",
       "5 2017-03-01 1974-11-01       2017-12-01   2018-01-01  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_all$issue_d          <- as.character(parse_date_time(df_all$issue_d          , \"my\"))\n",
    "df_all$earliest_cr_line <- as.character(parse_date_time(df_all$earliest_cr_line , \"my\"))\n",
    "df_all$next_pymnt_d     <- as.character(parse_date_time(df_all$next_pymnt_d     , \"my\"))\n",
    "# 814989 failed to parse.\n",
    "df_all$last_pymnt_d     <- as.character(parse_date_time(df_all$last_pymnt_d     , \"my\"))\n",
    "# 1621 failed to parse\n",
    "\n",
    "date_list = c('issue_d', 'earliest_cr_line','last_pymnt_d','next_pymnt_d')\n",
    "df_all[1:5, date_list]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Compute duration (days) from loan issue to last payment:\n",
    "df_all[,'Year_issued'] = as.numeric(substr( df_all$issue_d ,1,4))\n",
    "df_all[,'Month_issued'] = as.numeric(substr(df_all$issue_d ,6,7))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Credit history days before loan issued\n",
    "df_all[,'credit_days'] = as.numeric(as.Date(df_all$issue_d) - as.Date(df_all$earliest_cr_line) )\n",
    "# impute missing credit days to 0:\n",
    "df_all[is.na(df_all$credit_days),'credit_days'] = 0\n",
    "\n",
    "# days since loan issued\n",
    "df_all[,'Days'] = as.numeric(as.Date(df_all$last_pymnt_d) - as.Date( df_all$issue_d) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>issue_d</dt>\n",
       "\t\t<dd>0</dd>\n",
       "\t<dt>earliest_cr_line</dt>\n",
       "\t\t<dd>0.002</dd>\n",
       "\t<dt>last_pymnt_d</dt>\n",
       "\t\t<dd>0.098</dd>\n",
       "\t<dt>next_pymnt_d</dt>\n",
       "\t\t<dd>49.49</dd>\n",
       "\t<dt>credit_days</dt>\n",
       "\t\t<dd>0</dd>\n",
       "\t<dt>Days</dt>\n",
       "\t\t<dd>0.098</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[issue\\textbackslash{}\\_d] 0\n",
       "\\item[earliest\\textbackslash{}\\_cr\\textbackslash{}\\_line] 0.002\n",
       "\\item[last\\textbackslash{}\\_pymnt\\textbackslash{}\\_d] 0.098\n",
       "\\item[next\\textbackslash{}\\_pymnt\\textbackslash{}\\_d] 49.49\n",
       "\\item[credit\\textbackslash{}\\_days] 0\n",
       "\\item[Days] 0.098\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "issue_d\n",
       ":   0earliest_cr_line\n",
       ":   0.002last_pymnt_d\n",
       ":   0.098next_pymnt_d\n",
       ":   49.49credit_days\n",
       ":   0Days\n",
       ":   0.098\n",
       "\n"
      ],
      "text/plain": [
       "         issue_d earliest_cr_line     last_pymnt_d     next_pymnt_d      credit_days             Days \n",
       "           0.000            0.002            0.098           49.490            0.000            0.098 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "missing_pct(df_all[, c(date_list,'credit_days', 'Days')])\n",
    "#head(df_all[c('Year_issued', 'Month_issued','issue_d','earliest_cr_line','last_pymnt_d','credit_days','Days')])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "\t<li>TRUE</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\item TRUE\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. TRUE\n",
       "2. TRUE\n",
       "3. TRUE\n",
       "4. TRUE\n",
       "5. TRUE\n",
       "6. TRUE\n",
       "7. TRUE\n",
       "8. TRUE\n",
       "9. TRUE\n",
       "10. TRUE\n",
       "11. TRUE\n",
       "12. TRUE\n",
       "13. TRUE\n",
       "14. TRUE\n",
       "15. TRUE\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Converting few relevant columns as factors\n",
    "factor_list = c( 'id', 'grade', 'sub_grade', 'home_ownership', 'emp_length', 'verification_status',\n",
    "                'pymnt_plan',  'application_type', 'loan_status', 'policy_code', 'initial_list_status','purpose', \n",
    "                'title', 'addr_state', 'term')\n",
    "\n",
    "# check if column names all valid\n",
    "factor_list %in% colnames(df_all)\n",
    "\n",
    "tmp=  head(df_all[,factor_list], 10)\n",
    "for (col in factor_list){\n",
    "    df_all[, col] = as.factor( df_all[, col] )\n",
    "}\n",
    "\n",
    "#str(df_all)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Combine loan status into fewer groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "                                        Charged Off                                             Current \n",
       "                                              10.21                                               47.91 \n",
       "                                            Default                                          Fully Paid \n",
       "                                               0.00                                               39.28 \n",
       "                                    In Grace Period                                   Late (16-30 days) \n",
       "                                               0.64                                                0.35 \n",
       "                                 Late (31-120 days)                                                     \n",
       "                                               1.44                                                0.00 \n",
       "Does not meet the credit policy. Status:Charged Off  Does not meet the credit policy. Status:Fully Paid \n",
       "                                               0.05                                                0.12 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "round(table(df_all$loan_status)/dim(df_all)[1]*100,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_all[,'Loan_Status'] = ''\n",
    "df_all[df_all[,'loan_status'] %in% c('In Grace Period','Late (16-30 days)','Late (31-120 days)') ,'Loan_Status'] = 'Late'\n",
    "df_all[df_all[,'loan_status'] %in% c('Charged Off','Default') ,'Loan_Status'] = 'Default'\n",
    "df_all[df_all[,'loan_status'] %in% c('Does not meet the credit policy. Status:Charged Off',\n",
    "                                     'Does not meet the credit policy. Status:Fully Paid') ,'Loan_Status'] = NA\n",
    "df_all[df_all[,'loan_status'] == 'Current', 'Loan_Status'] = 'Current'\n",
    "df_all[df_all[,'loan_status'] == 'Fully Paid', 'Loan_Status'] = 'Fully Paid'\n",
    "df_all[df_all[,'loan_status'] == '', 'Loan_Status'] = NA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "   Current    Default Fully Paid       Late \n",
       "    788950     168154     646902      40023 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "2752"
      ],
      "text/latex": [
       "2752"
      ],
      "text/markdown": [
       "2752"
      ],
      "text/plain": [
       "[1] 2752"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table(df_all[,'Loan_Status'])\n",
    "sum(is.na(df_all[,'Loan_Status']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add target variables for survival analysis\n",
    "- time to event\n",
    "- Default/ charge off\n",
    "- full paid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_all[,'Default'] = df_all[,'loan_status']  %in% c('Default','Charged Off')\n",
    "df_all[,'Fully_paid'] = df_all[,'loan_status']  %in% c('Fully_paid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_all = df_all[order(df_all$issue_d),]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "15.99"
      ],
      "text/latex": [
       "15.99"
      ],
      "text/markdown": [
       "15.99"
      ],
      "text/plain": [
       "[1] 15.99"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "remove_pct = function(x){\n",
    "    as.numeric(substr(x,1,nchar(x)-1))\n",
    "}\n",
    "remove_pct('15.99%')\n",
    "\n",
    "pct_list = c('int_rate','revol_util')\n",
    "df_all[, pct_list] = apply(df_all[, pct_list] ,1:2, remove_pct)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_all[, 'zip3d'] =  substr(df_all[ , 'zip_code'],1,3 ) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'02701'</li>\n",
       "\t<li>'06501'</li>\n",
       "\t<li>'08701'</li>\n",
       "\t<li>'78701'</li>\n",
       "\t<li>'07801'</li>\n",
       "\t<li>'65201'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item '02701'\n",
       "\\item '06501'\n",
       "\\item '08701'\n",
       "\\item '78701'\n",
       "\\item '07801'\n",
       "\\item '65201'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. '02701'\n",
       "2. '06501'\n",
       "3. '08701'\n",
       "4. '78701'\n",
       "5. '07801'\n",
       "6. '65201'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"02701\" \"06501\" \"08701\" \"78701\" \"07801\" \"65201\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_all[, 'zipcode'] = paste0( substr(df_all[ , 'zip_code'],1,3 ), \"01\")\n",
    "head(df_all[, 'zipcode'] )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use zipcode table to match to city:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>zip3d</th><th scope=col>city</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>005         </td><td>\tMID-ISLAND</td></tr>\n",
       "\t<tr><td>006         </td><td>\tSAN JUAN  </td></tr>\n",
       "\t<tr><td>007         </td><td>\tSAN JUAN  </td></tr>\n",
       "\t<tr><td>008         </td><td>\tSAN JUAN  </td></tr>\n",
       "\t<tr><td>009         </td><td>\tSAN JUAN  </td></tr>\n",
       "\t<tr><td>010         </td><td>\tHARTFORD  </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       " zip3d & city\\\\\n",
       "\\hline\n",
       "\t 005          & \tMID-ISLAND\\\\\n",
       "\t 006          & \tSAN JUAN  \\\\\n",
       "\t 007          & \tSAN JUAN  \\\\\n",
       "\t 008          & \tSAN JUAN  \\\\\n",
       "\t 009          & \tSAN JUAN  \\\\\n",
       "\t 010          & \tHARTFORD  \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "zip3d | city | \n",
       "|---|---|---|---|---|---|\n",
       "| 005          | \tMID-ISLAND | \n",
       "| 006          | \tSAN JUAN   | \n",
       "| 007          | \tSAN JUAN   | \n",
       "| 008          | \tSAN JUAN   | \n",
       "| 009          | \tSAN JUAN   | \n",
       "| 010          | \tHARTFORD   | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  zip3d city        \n",
       "1 005   \\tMID-ISLAND\n",
       "2 006   \\tSAN JUAN  \n",
       "3 007   \\tSAN JUAN  \n",
       "4 008   \\tSAN JUAN  \n",
       "5 009   \\tSAN JUAN  \n",
       "6 010   \\tHARTFORD  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "zip_city = read.csv(paste0(raw_data_path, \"3-digit_zip_code.csv\"))\n",
    "\n",
    "zip_city$nchar     = apply(matrix(zip_city$City), c(1,2), nchar)\n",
    "zip_city$zip3d   = substr(zip_city$City, zip_city$nchar -2, zip_city$nchar )\n",
    "zip_city$city      = substr(zip_city$City, 1, zip_city$nchar -7)\n",
    "#zip_city$city_state = paste(zip_city$city, substr(zip_city$City, zip_city$nchar -5, zip_city$nchar -4), sep= ',')\n",
    "\n",
    "drops <- c(\"City\",\"zip\", 'nchar')\n",
    "zip_city = zip_city[ , !(names(zip_city) %in% drops)]\n",
    "head(zip_city)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_all = merge( df_all, zip_city, by ='zip3d', all.x = TRUE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exclude some columns\n",
    "Exclude columns with > 97% missing, happened after loan default, or are almost the same as other existing columns:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "join_applicant_info = c( 'settlement_term', 'annual_inc_joint','dti_joint','revol_bal_joint', 'sec_app_fico_range_low', 'sec_app_fico_range_high',\n",
    "                'sec_app_earliest_cr_line' ,'sec_app_inq_last_6mths' ,'sec_app_mort_acc' ,'sec_app_open_acc',\n",
    "                'sec_app_revol_util', 'sec_app_open_act_il' ,'sec_app_num_rev_accts', 'sec_app_chargeoff_within_12_mths',\n",
    "                'sec_app_collections_12_mths_ex_med', 'sec_app_mths_since_last_major_derog')\n",
    "\n",
    "duplicate_variables = c('funded_amnt', 'funded_amnt_inv','last_credit_pull_d','next_pymnt_d')\n",
    "# potential target leaks\n",
    "hardship_settlement = c('member_id','hardship_flag', 'hardship_type',\n",
    "                'hardship_reason', 'hardship_status', 'deferral_term', 'hardship_amount', 'hardship_start_date',\n",
    "                'hardship_end_date', 'payment_plan_start_date', 'hardship_length', 'hardship_dpd', 'hardship_loan_status',\n",
    "                'orig_projected_additional_accrued_interest', 'hardship_payoff_balance_amount', 'hardship_last_payment_amount',\n",
    "                'disbursement_method', 'debt_settlement_flag', 'debt_settlement_flag_date', 'settlement_status',\n",
    "                'settlement_date', 'settlement_amount', 'settlement_percentage')\n",
    "col_exclude= c(join_applicant_info, duplicate_variables, hardship_settlement)\n",
    "\n",
    "# check missingness of columns removed\n",
    "missing_pct <- function(df){\n",
    "    na_count <-sapply(df, function(y) sum(length(which(is.na(y)))))\n",
    "    tmp=round( na_count/dim(df)[1] *100, digits=2)\n",
    "}\n",
    "                      \n",
    "# check missing percentage           \n",
    "#missing_pct(df_all[, col_exclude])    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exclude some loan records\n",
    "Exclude loan records with data issue: \n",
    "1. loan amount missing \n",
    "2. status is \"Does not meet the credit policy. Status:Charged Off\" or \"Does not meet the credit policy. Status:Fully paid\". This population is different from the population we are interested in modeling.\n",
    "3. Last payment date (last_pymnt_d) is not missing. These records are not valid for future time to event modeling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#tmp= df1[is.na(df1$Days), c('loan_amnt','revol_bal','Days','issue_d' ,'last_pymnt_d','next_pymnt_d','loan_status')]\n",
    "df1= df_all[ df_all$loan_amnt >0 , !(names(df_all) %in% col_exclude)]\n",
    "df1 = df1[!is.na(df1$Loan_Status),  ]    # remove 2752 records\n",
    "df1 = df1[!is.na(df1$last_pymnt_d),  ]   # remove 1606 records"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Missing data imputation\n",
    "Many of the missing values for this dataset is not missing at random, but have special meanings. \n",
    "Columns containing missing values can be grouped into different groups and use different methods to do imputation:\n",
    "- Text\n",
    "    - desc: missing -> ''\n",
    "\n",
    "- impute to maximum: \n",
    "    - mths_since_last_delinq, mo_sin_old_il_acct\n",
    "- Remove if the variable is almost a duplicate of other existing varialbes: \n",
    "    - 'next_pymnt_d','verification_status_joint', \n",
    "- impute using median or knn: dti, 'il_util'\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Loan description provided by the borrower\n",
    "df1[is.na(df1$desc), 'desc'] = ''\n",
    "\n",
    "levels(df1[,'verification_status_joint']) <- c(levels(df1[,'verification_status_joint']),\"Missing\")\n",
    "df1[is.na(df1$verification_status_joint), 'verification_status_joint'] = 'Missing'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"pct_tl_nvr_dlq: missing %= 4.11\"\n",
      "[1] \"bc_open_to_buy: missing %= 3.87\"\n",
      "[1] \"bc_util: missing %= 3.92\"\n",
      "[1] \"percent_bc_gt_75: missing %= 3.9\"\n",
      "[1] \"mths_since_recent_bc: missing %= 3.81\"\n",
      "[1] \"num_tl_120dpd_2m: missing %= 8.01\"\n",
      "[1] \"mo_sin_old_il_acct: missing %= 6.9\"\n",
      "[1] \"mths_since_recent_inq: missing %= 13.17\"\n"
     ]
    }
   ],
   "source": [
    "# impute using median\n",
    "\n",
    "# pct_tl_nvr_dlq\tPercent of trades never delinquent\n",
    "# bc_open_to_buy\tTotal open to buy on revolving bankcards.\n",
    "# bc_util\tRatio of total current balance to high credit/credit limit for all bankcard accounts.\n",
    "# percent_bc_gt_75\tPercentage of all bankcard accounts > 75% of limit.\n",
    "# mths_since_recent_bc\tMonths since most recent bankcard account opened.\n",
    "# num_tl_120dpd_2m\tNumber of accounts currently 120 days past due (updated in past 2 months)\n",
    "# mo_sin_old_il_acct\tMonths since oldest bank installment account opened\n",
    "#- mths_since_recent_inq\tMonths since most recent inquiry.\n",
    "\n",
    "col_list = c('pct_tl_nvr_dlq', 'bc_open_to_buy','bc_util','percent_bc_gt_75',  'mths_since_recent_bc',\n",
    "             'num_tl_120dpd_2m','mo_sin_old_il_acct', 'mths_since_recent_inq')\n",
    "\n",
    "for (col in col_list){\n",
    "    print(paste0(col, ': missing %= ', round(sum(is.na(df1[, col]))/dim(df1)[1]*100, digits=2 )) )\n",
    "    df1[is.na(df1[, col]), col ] = median( df1[, col], na.rm =T)  # this is impute using median\n",
    "}\n",
    "\n",
    "# if impute using kNN \n",
    "#library(VIM)\n",
    "#df1[ , col_list] = kNN(df1[ , col_list],imp_var = FALSE) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"mths_since_last_delinq: missing %= 49.62\"\n",
      "[1] \"Max value= 195\"\n",
      "[1] \"mths_since_last_record: missing %= 83.13\"\n",
      "[1] \"Max value= 129\"\n",
      "[1] \"mths_since_last_major_derog: missing %= 73.43\"\n",
      "[1] \"Max value= 197\"\n",
      "[1] \"mths_since_recent_bc_dlq: missing %= 75.84\"\n",
      "[1] \"Max value= 195\"\n",
      "[1] \"mths_since_recent_revol_delinq: missing %= 65.79\"\n",
      "[1] \"Max value= 197\"\n"
     ]
    }
   ],
   "source": [
    "# Impute using a large number \n",
    "\n",
    "# These variables are missing be cause deliquency/public record/worse rating never happened. \n",
    "# A set of new missing indicator variables should be created,\n",
    "# if we want to do imputation, the time since these events should be imputed to a very long time, say 200 months (~17 years). \n",
    "\n",
    "# mths_since_last_delinq\tThe number of months since the borrower's last delinquency.\n",
    "# mths_since_last_record\tThe number of months since the last public record.\n",
    "# mths_since_last_major_derog\tMonths since most recent 90-day or worse rating\n",
    "# mths_since_recent_bc_dlq\tMonths since most recent bankcard delinquency\n",
    "# mths_since_recent_revol_delinq\tMonths since most recent revolving delinquency.\n",
    "\n",
    "col_list= c('mths_since_last_delinq', 'mths_since_last_record', 'mths_since_last_major_derog',\n",
    "           'mths_since_recent_bc_dlq', 'mths_since_recent_revol_delinq')\n",
    "for (col in col_list){\n",
    "    print(paste0(col, ': missing %= ', round(sum(is.na(df1[, col]))/dim(df1)[1]*100, digits=2 )) )\n",
    "    print( paste0( 'Max value= ', max( df1[, col], na.rm =T)) )\n",
    "    df1[, paste0(col,'_miss')] = is.na(df1[, col])\n",
    "    df1[is.na(df1[, col]), col ] = 200\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmp16 = missing_pct(df1[df1$Year >= 2016, ])\n",
    "tmp15 = missing_pct(df1[df1$Year == 2015, ])\n",
    "tmp14 = missing_pct(df1[df1$Year == 2014, ])\n",
    "tmp13 = missing_pct(df1[df1$Year == 2013, ])\n",
    "tmp12 = missing_pct(df1[df1$Year == 2012, ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>tmp16</th><th scope=col>tmp15</th><th scope=col>tmp14</th><th scope=col>tmp13</th><th scope=col>tmp12</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>mths_since_rcnt_il</th><td> 2.701</td><td>95.059</td><td>100   </td><td>100   </td><td>100   </td></tr>\n",
       "\t<tr><th scope=row>il_util</th><td>13.240</td><td>95.579</td><td>100   </td><td>100   </td><td>100   </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & tmp16 & tmp15 & tmp14 & tmp13 & tmp12\\\\\n",
       "\\hline\n",
       "\tmths\\_since\\_rcnt\\_il &  2.701 & 95.059 & 100    & 100    & 100   \\\\\n",
       "\til\\_util & 13.240 & 95.579 & 100    & 100    & 100   \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | tmp16 | tmp15 | tmp14 | tmp13 | tmp12 | \n",
       "|---|---|\n",
       "| mths_since_rcnt_il |  2.701 | 95.059 | 100    | 100    | 100    | \n",
       "| il_util | 13.240 | 95.579 | 100    | 100    | 100    | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "                   tmp16  tmp15  tmp14 tmp13 tmp12\n",
       "mths_since_rcnt_il  2.701 95.059 100   100   100  \n",
       "il_util            13.240 95.579 100   100   100  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp = data.frame(cbind(tmp16, tmp15, tmp14, tmp13, tmp12))\n",
    "tmp[tmp$tmp16 > 1, ]\n",
    "#tmp[(tmp$tmp16 <= 1) & (tmp$tmp15 > 0.01) , ]\n",
    "#tmp[(tmp$tmp15 <= 0.01) & (tmp$tmp14 > 0.01) , ]\n",
    "#tmp[(tmp$tmp14 <= 0.01) & (tmp$tmp13 > 0.01) , ]\n",
    "#tmp[(tmp$tmp13 <= 0.01) & (tmp$tmp12 > 0.01) , ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "list_1617_only = c( 'revol_util','open_acc_6m','open_act_il','open_il_12m','open_il_24m',\n",
    "            'open_rv_12m','open_rv_24m', 'total_bal_il','max_bal_bc','all_util','inq_fi','inq_last_12m','total_cu_tl',\n",
    "                  'mths_since_rcnt_il', 'il_util')\n",
    "# il_util: Ratio of total current balance to high credit/credit limit on all install acct\n",
    "\n",
    "# open_acc_6m\tNumber of open trades in last 6 months\n",
    "# open_act_il\tNumber of currently active installment trades\n",
    "# open_il_12m\tNumber of installment accounts opened in past 12 months\n",
    "# open_il_24m\tNumber of installment accounts opened in past 24 months\n",
    "# open_rv_12m\tNumber of revolving trades opened in past 12 months\n",
    "# open_rv_24m\tNumber of revolving trades opened in past 24 months\n",
    "# total_bal_il\tTotal current balance of all installment accounts\n",
    "# max_bal_bc\tMaximum current balance owed on all revolving accounts\n",
    "# all_util\tBalance to credit limit on all trades\n",
    "# inq_fi\tNumber of personal finance inquiries\n",
    "# inq_last_12m\tNumber of credit inquiries in past 12 months\n",
    "# total_cu_tl\tNumber of finance trades\n",
    "# mths_since_rcnt_il\tMonths since most recent installment accounts opened\n",
    "# il_util\tRatio of total current balance to high credit/credit limit on all install acct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>758390</li>\n",
       "\t<li>123</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 758390\n",
       "\\item 123\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 758390\n",
       "2. 123\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 758390    123"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"revol_util: missing %= 0.07\"\n",
      "[1] \"open_acc_6m: missing %= 0.01\"\n",
      "[1] \"open_act_il: missing %= 0.01\"\n",
      "[1] \"open_il_12m: missing %= 0.01\"\n",
      "[1] \"open_il_24m: missing %= 0.01\"\n",
      "[1] \"open_rv_12m: missing %= 0.01\"\n",
      "[1] \"open_rv_24m: missing %= 0.01\"\n",
      "[1] \"total_bal_il: missing %= 0.01\"\n",
      "[1] \"max_bal_bc: missing %= 0.01\"\n",
      "[1] \"all_util: missing %= 0.02\"\n",
      "[1] \"inq_fi: missing %= 0.01\"\n",
      "[1] \"inq_last_12m: missing %= 0.01\"\n",
      "[1] \"total_cu_tl: missing %= 0.01\"\n",
      "[1] \"mths_since_rcnt_il: missing %= 2.7\"\n",
      "[1] \"il_util: missing %= 13.24\"\n"
     ]
    }
   ],
   "source": [
    "# Create a subset of loans issued 2016-2017\n",
    "df_2016_2017 = df1[df1$Year>= 2016, ]\n",
    "dim( df_2016_2017)\n",
    "# impute missing values with median\n",
    "for (col in list_1617_only){\n",
    "    print(paste0(col, ': missing %= ', round(sum(is.na(df_2016_2017[, col]))/dim(df_2016_2017)[1]*100, digits=2 )) )\n",
    "    df_2016_2017[is.na(df_2016_2017[, col]), col ] = median( df_2016_2017[, col], na.rm =T)  # this is impute using median\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>1414677</li>\n",
       "\t<li>123</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 1414677\n",
       "\\item 123\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 1414677\n",
       "2. 123\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 1414677     123"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"revol_util: missing %= 0.06\"\n",
      "[1] \"open_acc_6m: missing %= 44.89\"\n",
      "[1] \"open_act_il: missing %= 44.89\"\n",
      "[1] \"open_il_12m: missing %= 44.89\"\n",
      "[1] \"open_il_24m: missing %= 44.89\"\n",
      "[1] \"open_rv_12m: missing %= 44.89\"\n",
      "[1] \"open_rv_24m: missing %= 44.89\"\n",
      "[1] \"total_bal_il: missing %= 44.89\"\n",
      "[1] \"max_bal_bc: missing %= 44.89\"\n",
      "[1] \"all_util: missing %= 44.89\"\n",
      "[1] \"inq_fi: missing %= 44.89\"\n",
      "[1] \"inq_last_12m: missing %= 44.89\"\n",
      "[1] \"total_cu_tl: missing %= 44.89\"\n",
      "[1] \"mths_since_rcnt_il: missing %= 46.37\"\n",
      "[1] \"il_util: missing %= 52.17\"\n"
     ]
    }
   ],
   "source": [
    "# Create a subset of loans issued 2016-2017\n",
    "df_2014_2017 = df1[df1$Year>= 2014, ]\n",
    "dim( df_2014_2017)\n",
    "# impute missing values with median\n",
    "for (col in list_1617_only){\n",
    "    print(paste0(col, ': missing %= ', round(sum(is.na(df_2014_2017[, col]))/dim(df_2014_2017)[1]*100, digits=2 )) )\n",
    "    #df_2014_2017[is.na(df_2014_2017[, col]), col ] = median( df_2014_2017[, col], na.rm =T)  # this is impute using median\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "drop_list = c('zip3d', 'id', 'url', 'zip_code' )\n",
    "\n",
    "drop_from_model = c('issue_d', 'loan_status','out_prncp', 'out_prncp_inv',   'total_rec_prncp', \n",
    "                    'total_rec_int', 'total_rec_late_fee', 'recoveries', 'collection_recovery_fee',\n",
    "                   'last_pymnt_d', 'last_pymnt_amnt', 'Loan_Status', 'fully_paid', 'year_issued' )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>1414677</li>\n",
       "\t<li>123</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 1414677\n",
       "\\item 123\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 1414677\n",
       "2. 123\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 1414677     123"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(df1[df1$Year>= 2014, ])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Save datasets to CSV files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>1646781</li>\n",
       "\t<li>161</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 1646781\n",
       "\\item 161\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 1646781\n",
       "2. 161\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 1646781     161"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(df_all)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>813517</li>\n",
       "\t<li>123</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 813517\n",
       "\\item 123\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 813517\n",
       "2. 123\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 813517    123"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_paid_chargeOff = df1[df1$loan_status %in% c('Fully Paid','Charged Off') ,]\n",
    "dim(df_paid_chargeOff )\n",
    "write.csv(df_paid_chargeOff, file= paste0(wkdir ,'loan_paid_chargeOff.csv') )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>200000</li>\n",
       "\t<li>123</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 200000\n",
       "\\item 123\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 200000\n",
       "2. 123\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 200000    123"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_sample = df_paid_chargeOff[sample(nrow(df_paid_chargeOff), 200000), ]\n",
    "dim(df_sample)\n",
    "write.csv(df_sample, file= paste0(wkdir ,'loan_200K.csv') )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>758390</li>\n",
       "\t<li>123</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 758390\n",
       "\\item 123\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 758390\n",
       "2. 123\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 758390    123"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(df_2016_2017)\n",
    "write.csv(df_2016_2017, file= paste0(wkdir ,'loan_2016-2017.csv') )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>1414677</li>\n",
       "\t<li>123</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 1414677\n",
       "\\item 123\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 1414677\n",
       "2. 123\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] 1414677     123"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dim(df_2014_2017)\n",
    "df_sample_2014_2017 = df_2014_2017[sample(nrow(df_2014_2017), 50000), ]\n",
    "write.csv(df_sample_2014_2017, file= paste0(wkdir ,'loan_2014-2017_50K.csv') )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_sample_2014_2017 = df_2014_2017[sample(nrow(df_2014_2017), 50000), ]\n",
    "write.csv(df_2014_2017, file= paste0(wkdir ,'loan_2014-2017_50K.csv') )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Exploratory Data Analysis\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loan status over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plot_over_time = function(col ='Loan_Status'){\n",
    "    options(repr.plot.width=11, repr.plot.height=5)\n",
    "    count = table( df_all$Year, df_all[,col]  )\n",
    "    counts = melt( count ) \n",
    "    colnames(counts) = c('Year', col ,'Frequency')\n",
    "\n",
    "    pct = melt( round( count/ apply( count,1,sum) *100 ,digits= 2) )\n",
    "    colnames(pct) = c('Year', col ,'Percentage')\n",
    "\n",
    "    p1 = ggplot(data= counts, aes(x= as.factor(Year), y= Frequency, group= get(col) , colour= get(col) )) +\n",
    "        geom_line() + geom_point() +ggtitle(paste0('Frequency of Loans by ', col,' Over Time') )\n",
    "\n",
    "    p2 = ggplot(data= pct, aes(x= as.factor(Year), y= Percentage, group= get(col) , colour= get(col) )) +\n",
    "        geom_line() + geom_point() +ggtitle(paste0('Percentage of Loans by ', col,' Over Time') )\n",
    "\n",
    "    grid.arrange(p1, p2, ncol=2)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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VOWfofrulAEb2k/SLivlwCtqiuS+mDJXSCY+5ANmpTKJ0G2VrMlOFY0z/hFarAy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\nnRRmzpxZjdLzPJdZP33J7C27iiMsDRqa3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wwnn3xyQEnJXzUQ74ILLvD2Xnrppe4LaNNNN/WyqvFymLTVGeUk/i+pO3WAlYIIiIAIiIAI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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_over_time(col= 'Loan_Status')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            \n",
       "                  A      B      C      D      E      F      G       \n",
       "  Current    137090 241574 250558 100484  42930  12191   4123      0\n",
       "  Default      8705  31746  50693  38958  24748  10389   2915      0\n",
       "  Fully Paid 124771 203493 175253  88722  38817  12728   3118      0\n",
       "  Late         2060   8193  13651   8657   4930   1856    676      0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "table(df_all$Loan_Status, df_all$grade)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/Cyyy6Detipcq5y2P7Sc9SIq8mylkV/jALfXP122o05Sf5TDwblrL8Ba2y2x4L9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jBjQ3NfczASbQRgJsoGwjMD6dCTABJsAE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\nKN27RFVpjJP4k65gK3U0HYGlW++FzV41wyvvb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9y5E7t27VJhYtwZz7vpRu7+lm3mYhQc/Bo6spwMaT3W/Q02QQuGrVvAtrWWpH5N0Hrz\na1Kr1WNyn9fQJnIIOJHN8j0PuQTC7mNfYt3h1xFhbKPq12rcF8O/UR2m+Oqm4SOhKSmBYePG\nRlUlFwsBISAEhEDdBJx28V67di1mzJih4rglJSWpIPliOVk3YDkjBISAEGhuBDLyTisoIwYp\n60kevzHOs+7d2qNHocnNURY2NfiTklK/PxmW3n1rnJIDQkAIeIbAgQMHMHz4cGU1yS1yNu/f\nf/9dNc6Jcp555hnce++9+NOf/uSZDvlRKwWpX8NuKUJ4zxug0XqpwqcRvDWnTkJ3JA2WDh1h\nj4hsRE1yqTMEDOTWPT1pHj76Yxq2ZX6G4IBojOvccEXlsYJd+Gr3n2HQBmFa0jtUn3eHXzEP\nG4GAVT8j4LfVMA8fAVphcQaflBUCQkAICIF6EHBaQblo0SIVg3Lz5s3o0qVLPZqQIkJACAgB\nIdCcCKSTgjJAF4K40G7I3l2eIMfoYQtKTWkJmUxqOKBdDfRsRRm4ZDEFvN8CW2IbWHmjOGaU\noaZGWTkgBISAewiw501+fn5F5d26dQPHpHQIe+pwYrj09PQKJabjnLyenUB+8mn37s7Tzl7Q\nR88atm5VPbf08+zCl4/icmm3jYYIzKQYlB9snIJ1qa8hxBCNoe2cX0Tg7OCLtt0Ci60UU8gy\nMz6sh0v76Y7K7GFhMA8cjIANv0O/cwcsfb0nkY87xit1CgEhIASagoDTCsqjZJUyaNAgUU42\nxd2SNoWAEBACXk6gsCwLuSVpaN9iFOkHtactKDUIjPGstaK1VUKdpFhlqbFZYaAHDPB2WmzR\n0bC2JmVlmzawtU6k96S0DHRdIgBHO/LqvQQ4i7qnpLm7L3fv3h0LFiwAx57kzPDs4p2amoq0\ntDS0bdtWuXlzHEqDweCpW+IX7ZjyDqD0xB8Iih+KgAj/zADP2bvt9NkwixV8k3xmwwLjcc2A\nT/Dhpin4MeUJsnxsgT6tpta7LzabBUt23I780gyMaH83esRfWu9rm7qgedR5MJCCMmDNL6Kg\nbOqbIe0LAS8mIPPJht8cpxWUrJx8/PHHUUyZUT0JvuFDlCuFgBAQAkLAUwTYepKFE+TYbWaU\nndqFgMgu0AWEeaoL5e0EBcE0dhzYHUtjs1W0bdfpYOnVG6XXzIImOxu6jCPQkYWWNp1eMzJg\noMQLvLHYyQLTFhN7xsqSksHZ2NJSFCYVPP3tjV7v9LSoUQiac4bq66+/XrlxszfOV199hXHj\nxiEkJARTp07F5MmTMW/ePOUCzspLkfoTyHNYT/ppchztsaPQHT8GS7fuoA9M/cFISZcSaBHc\nHjP7fUju3tOVm7bREElJdC6oVxsrUh5HWs7v6BwzDmM7/ble13hLIVtcPKw9ekK/Zzd0hw7C\nSmEGRISAEBAC1QnIfLI6kfrvOz0Tnz17Nt555x3861//wr///W8EUNBgESEgBISAEBACTCA9\nd5MCkRg5CGUnd8FuLfN4/EnHnTCNnwjt0UwY6EGCxX46yD0fV/sxMbDwlnTaTZAUmdrsrHJl\nJSktdaS05EzguqwTMGwpV7wqpWV8S1JakoXlafdwW8tWgIcVW2oA8p/LCfDiq62SQtvlDVSq\nMIiU6Gwh2FyFs3UvXboUf//73ylnValKtshZu2+66SZs2rRJWU4+/fTTzRVPg8ZtJ8u0ggNL\noTWEIrT9xQ2qw9sv4tAcLOZ+Hk685u1gmqB/LcN7q5iUn26Zhc+3345rB3wK/u0/m2zLXIhN\nR95Hi+COuKL3K8rT4mzlvfGcafRYpaAMWL0KJaKg9MZbJH0SAk1OQOaTDb8FTisoV65cCZ5U\nPvfcc3jllVdUXCBe8a4u27Ztq35I9oWAEBACQsDPCWTkbVYjbB3RH6XJS9R7T8efrIxYW1io\nMr0GP/MCitiqkhRQdQopi9g6gjfLgNMPWay0JGsdZWXJ1pZHSGnJFjy0GTaVZ/Jkq0xWUlrJ\nLdwR09LGVl903Bmxm0ywWcy1xs10ph4p23ACFsr07ikFZXO2nnTcoZEjR+KXX36hULHlsWJn\nzZqF8ePHY8uWLejVqxfaULgFkfoTKDryE6wlWYjodi20+qD6X+hDJQ3btsJOC0KWnr18qNf+\n29V2LYbjyj7/UwrKz7beiFmDFqv407WNOCNvC77d83eKUR2qFJtGfXhtxbz+GFtN8u+9jhY/\nNVlZsNNzsYgQEAJCoDIBmU9WpuHce6cVlDk5OSgrK8PgwYOda0lKCwEhIASEgF8TsNpMOFqw\nA7Eh3cAPHjknyi1djLFNk8hAk5cHLWV6tdPDhK5lS1BGDuf5s9KS4lnyhsFDyq+nJDucJZzd\nw5VrOLuIk6WmLiMdoNhULPwAzdeUW1mWKy5tsXG1Zv3UFBZQ0p5FsO/dg2JS1ASFhKJ00mWk\nJB1Y3p78LwT8kMCHH36InTt34tlnnyUrKkpodVrYpXvixIlYtmwZRo0ahb1794KtTUXOTaAi\nOY6/uncfToU25xTMfSg5SWDguYFICY8Q6B43ERf3eArL9/wNn26+DjcM/hyRQVUXFwrKjmPx\ntlthtZsxtc+biA7p5JG+uasR05ixCJr/sYpFWTblKnc14xf15lqK8O7xH7A+ORl6jQ7jwvri\n2rixMGrFC9MvbrAMQgi4mIDTCspbb70VvIkIASEgBISAEKhM4GjBTlhtZWgdUe56V5q1Wbka\nBkR2rlzMY+/1O7aD1R42V2d6ZYtJjkdJG4YOLx+P2VyupCS3cEdMS6W8JAWpQ+yGAJV4p9zK\nkpPwtIE9MhLBr8+Fhh66HRnHNUWFMC76DKWktLH0FzdGBz959X0CWWRtZCJLYRa2ktywYQMy\nKPZrdeEyy5cvVwlz2P1bFJTVCdXctxSfQFHGLwiIogUiDyclq9kb9xwxUHIcFsne7R6+jam1\nf+urUWw6iVUHnsX8zddiat83sSubMl2jCKGadli9/yUUmo5TzMm/1DtWZWP64+5rLb36wBYZ\nBcPmTeCwMfbQUHc36ZP1nzIX4Op9zyLXUgiz3arGsL8oAz/lbsX7Xe9HgFaSoPnkjZVOCwE3\nEnBaQVm5L9u3b0cyrYaEhYVhwoQJOHz4MNq1a1e5iLwXAkJACAiBZkIgoyL+5EBYSrJhKUxH\nUKuRTRZjSr9zm3LvtvUlaxt3CyXOsbVtpzZy0i4XU5lKvFOegKc8pqUu9RD0tDnEzgl3SLl5\nxn6s/IzGbkPgN1+JgtIBSl79gsB7772Hv/3tb1XGksiK/jqkX79+KjZlHaflcCUC+fsX0yKH\nFeFdZlQ66kdvKdyGfjt9pxuN5Qly/Gho/jKUkR3uRrH5FDakvYN31k+AXmukodlhIe8Kfu0a\nMx4jO9zjH8OlhUrTeaNh/OoLGNb9BtNFE/xjXC4exdyjXyPHXEiK6nLlJFfPisoDpUexKPtX\nsqQ838UtSnVCQAj4OoEGKSh3796N22+/HWvWrFHjnzFjhlJQJiUlYc6cOXjkkUfI80JcL3z9\nwyH9FwJCQAg4Q+BMBu9BKD1RHovSGNdE7t0FBdDRopmtTVsgqoUzw3Bd2YBAleGT41VVKC1L\nS5SFJbuDs+JSn7yvhnLS0QEtuX6DY2YGBzsOyasQ8GkC999/Pzguk5mU8hzTnBe2Z1PyxerC\n2S+joqIwbdq06qdkvw4C+SkLKYSEAeGdJtdRwrcP6w7sB8cUNg2iUBuSlMxrb+aA1rNIQTmP\n+seKydIq/Qw0hFXZ9/Ud86DBCFzxPQy/r4Vp7DhQZi9fH5LL+78mb1cV5aSjAVZSrsrbIQpK\nBxB5FQJCoIKA0wrKfIrhdckll6jJ5YMPPoi1a9eqyqwUk4tjBj3xxBPKXWfePP5xEhECQkAI\nCIHmQiA9dzOCDJEUW6ojsvcsUsMOim0aF2Xl3k3xHM19+sK5VDVuvlvGIFg7d1EbtxTw0woE\n/PwjNPQbWl3snOGZMo+LCAF/IWCgB3jO2s3SvXt38IL3o48+6i/Da7JxlBxbD3N+KmXungSd\nMarJ+uHOhg2ns3eLe7c7KTe+7t3Hv4BOY6BYk+WhHCrXuPvYl7i05/PQUhxCv5BAI0zDRiBw\n1c8w/LERZnovUpWAXfmxVD3m2HMkR3Psy6sQEAJCgAnQ049z8tZbbyGPEg+sW7cOzz//vMri\nzTXoyNR9wYIFeOCBB8CBz4uKipyrWEoLASEgBISAzxLIK0lX8aUSI8qzX5dmORLk9GuSMel3\nblftcpwobxYzu5+T62J1sXP8yV69xVKoOhjZ9xsC7H3z2GOP+c14mnIgecmfqebD/TQ5Dpnd\nQr9rB2yhYbB27NSUqKXtcxAoMmXXqpzkyzhBjsnqX8+H5uEjwYuJAb+urvW3/By4/P50UkiH\nWseoId+RMRHePT+rteNyUAgIAbcTcFpByUHNx44di7ZtyW2uFpk5c6Zy30lNTa3lrBwSAkJA\nCAgBfyTgcO/mBDl2mxWl2dthCG9P1jyed6/W0AKZ7tBBSkKTCHt0tFfjtlNm77Ip08AKSeW2\nSA86duqxhqw/LT16eXXfpXNCoLEElixZghEjRqB169Zo0aKFcutm1+7KW2Pb8PfrraYCFKYu\nhz4kAcEJo/xyuPq9e6ChZEkWCiUF+o4U8V4CcaHdoasjO3OwIRpGfbj3dr4BPbNHRKhY0drs\nbOj37G5ADf57ydbCg1hfkKwGqK0WzIYtK1NKMik3IM94RISAEBACZwg47eIdTLGwNm3adKaG\nau+KOV4WSbSXPxRW67bsCgEhIASEQCMIpFckyBkEU+4+2C3FMMY2TfxJ/c4d5Qo+cu/2BTEP\nHgJLhw4Io3iUeorNV0S6SsN338L49RcoIndwe7h/PdD5wj1xpo8l1jIY6YFcw0rmRsrRo0fB\nnioOYe8Unk9xspjhw09njHec9PFXDhHEVpScoZtjmMfFxbmEoY9jcbr7hQe/pNw4pZQcZ1qT\nJSRzutNOXqA/nb3bnNQ0vylOdrdZF+/TairWHHqZMnpnw3Y6azMDYbfu8zs/5JdsTKNGk4v3\nJhhWryr3fPDLUTo3KI4v+fCh9ykhjgX3J1yJY+YcrC9Khp4+ByNCumNN/k58nbOBsnjr8Uib\nGfLd7xxeKe2nBGQ+WX5jnVZQDhkyBO+88w6WLl2KyZOrBuLm+JTsrpOQkICWLVv66UdHhiUE\nhIAQEALVCbAFpYYmngnhSShO+VydbjIF5Y5tqn2zl7t3V2Zoj4mFplNnBNIiYN6JE7BptDBS\nFm/jwk9RcvOtZFLZeOVX5fbkfeMJfJ21Hs8fXozjplwEaPS4LHYYHu4wAyE6zlzbMMnMzMS/\n/vUv8FwrNDQUJpMJ6enpOHLkCMaMGYOvvvqKcib5R9KkRYsWwUgZmTdv3owuXbo0DJhchbyU\n0+7dpKD0SykrVZZpNrKwtbVt55dD9KdBGXRBmD1oKZbtnIP0vHKDlgBdCMZ1eRj9Wvtnhnlb\nqwRYunZTSe+0aZScr5l/Tpdmr8V/jnymlJHPd7gZYyPLF4tZN8BJ0rLJ2nRW/DjcmvIqPj+5\nlmKWavFwm+n+9GcgYxECThGQ+WRVXE4rKG+88Ua1uj9lyhS1ms9KSV79vvbaa5XSsqSkBJ99\nVj5ZqtqU7AkBISAEhIA/EiizFOF44R60DO0FfjgpqYg/2QQJcsiKX3fwAKytWsEeG+uzuM1k\nkaHftxf6/SkwrPkF5tFjfXYs/tjxpSfW4p/7P4AV5fFDTWQl8mXWOqQUZ2BBn4cbbQ3CVpRs\nVeiQn3/+WS0K/+Uvf8HcuXMdh336la1FBw0aJMrJRtzFslN7UUbhNNi12xCa2IiaXHeptZLV\nnCtq1e/aCQ0pNUxiPekKnB6pIyIoETcM/hx6oxk2XSnsxaHkyuvfi2wm+o3WkxdEwOpfUHrd\n9R7h7I2NvH3se7x+9BuE0VzwpY63on9o7TFjo/SheLPz3fhTyitYlP2rUlL+NfEqbxyS9EkI\nuJWAzCdr4nU6kIter8fy5ctx0003Yf369di1a5dy+Z4/fz4iIyPx0UcfYfp0WQWpiVqOCAEh\nIAT8k8CRU3/Qw4cViZED1QA5QY5GF4jAFt09PmADP8xS0hlLb99w764TEFlMlk6fCTtZywV+\n/y20RzPrLConXE8g25SPY2Wnat0yS7Px1KEFFcpJR+tm+hvYXZSGZaS8rOtaPm6yWRyX1Pt1\n3Lhx+Pe//43XXnsNGRkZ9b7OmwuycpKtJx2hgby5r97at/wK68mmt0xblLUGozf9GYnfzsSQ\n3+fgHVJU2Ow1E4A5y9Kwdau6RLJ3O0uu6cuHGmMRH96VwoY6bQ/T9J13sgdWCsdibdlKJXPS\nnDzp5NW+X5z/1p86slApJ+MMkXi3y311Kicdo21hCMObXe5Bu8A4LMhajRfTlzpOyasQ8BsC\nMp90/lY26BcjlqxS5s2bhxdeeAEpKSnKVLtjx47gzWAwON8LuUIICAEhIAR8lkBq9u+q760j\nBsJalgdz3gEY4wdD0wQPJfodp7N39/b97JD28AiUUgKdoI8/gPHTT1B8z30UnFJ+Yz3xh3LT\nbprfFDuvFLaQkvLvB94/axfZwjIprONZy9R20hGDcufOnSqpTG1lfOnY7NmzVcggdmln5WtA\nQIAvdb/J+2q3mpB/YCm0AREIaTe+Sfvz5tFvMY8UkpbTFsV5ZFX/1rHvkFF2Eo+2u6bBfVMJ\nz/YnK8WPLV5CRzUYpFzoEQJsRRlEYVk4o3fZFVXDoHmkA03UiMlmxiOpH+KnvG3oYGyJuZ3u\nQMuAqHr1JsYQrpSUbEn5cdZKZUl5b+sr6nWtuwppcnMR+POPKDqcCntgIAxJ/WAeNgKgmNAi\nQsBZAjKfdJYY0CAFpaMZtpgcPHiwY1dehYAQEAJCoBkSOJS9Xo2aLShLs8qtXZok/mRpCXQH\nUmCNi4e/PMxaSNFqGjIMARt+R+Dyr+ihZ0oz/IR5fsgjI3uhY1CrWhs2kwXkzznlcU6rF+BM\npZ2DW6NDUHz1UxX7keTa1hBhl29OmrNv3z5MmDChIVV41TUrV64EL3g/99xzeOWVV5CYmIiQ\nkJAafdy2rXbWNQo2swOFaT/AVpaLiB6zoSWL9aaSfEqIxtaSjnAHjn6wsv7LU79jdvyFaGeM\ncxx26lVP8YSVRXy//k5dJ4WFQFMQsJAiy/bdNzBs2oiyi+g72k/iBZ+NZYG1BPcffBubC/ej\nb0gHvExu3RH6mt/jZ6sjzhCBt8jd+xZSUn5w4idKqKTFPQmXne0St53TUHzMkFf/C1DCQjt5\n47AEZqRDv3cPSm68hbI9Oe186ra+SsW+QUDmk87fJ6cVlC+++CJefvnlc7Z0+PDhc5aRAkJA\nCAgBIeDbBOx2Ow6fXI+wwHhEGFvjZNYiNaCgJsjgraeQIxqrFRYfyd5d3ztfdull0B/cj4B1\na2Hp1gPW7j3qe6mUayCBv7U/e6ia63c+h835+2soZbi5ud3vRCK5NrpaCgsLYaXPd0REhKur\nbpL6cnJyUFZWJgvdDaSfn1we7z2i69k/qw2svt6X7S1JJ7V87RKoMWBHcWrDFZRbN6uKzX37\n1d6AHBUC3kSAFpA4o7dx+dcI+H0tTOMu9KbeubwvWeY83L3/daSUZmJ0eG883WE2jNqGWcLH\nk8XlW+TuzUrK946vUJaUd7aa5PI+n6tC4xeU5JGS02lobusQnlfqDuyHfucOWPomOQ7LqxCo\nFwGZT9YLU5VCTisoY2Ji0LVr1yqV8IQ5LS0NrJSMiopSCXOqFJAdISAEhIAQ8DsCmeTOsz7z\nZRSbctAp+nw1Po4/yWKM83yCHMPO0+7dfqagREAgSmZei+DXXoVx8Wcovu9B2EPDFGf5r2kI\nPNPlZly94ynkmAvBCXIMlMHeQjG4nuh0g1uUkzzKvXv3qsF27ty5aQbt4lZvvfVW8CbiPAFz\nYQaKM39FYHQfivXb0/kKXHBFelk2fszdiq9pgcrh2l29Wo7LGqxpmMKC3Sx1qamwUkZkO2Xw\nFhECvkDAPGQoAn9cAcPa38Au36DcDf4oqaXHcdf+13DUnIMroofhH21mKqViY8baKqAF3u58\nj0qcw1bZBujwp1YTG1Ol09eyIrKycrKiArKmZCtKUVBWEJE3LiIg88maIJ3+1rz++uvBW21y\n8OBB5XbUirKniggBISAEhIB/ErCTIuaLnfdi9/GvyNulPCbPgZOrsOHwu4gmBaU+hALFB9ft\n4uoWKmSJpUtJhi06BjYKVO9vYktsA9P4iQj8bjkpKReiZPbN/jZEnxpPq8AWWN7/3/iCMnfv\nLkxDNAX7vzR2KLl3J7htHE899ZSK9T1s2DC3tSEV+waB/BS2VLcjvKtnk+OklZ7AT7nbsCJ3\nC9hy0iGsoGdlZHVht++3j/+AVoHR6BHcpvrps+7rt1GyNSphFvfus3KSk15GwBgEVlJyHErD\nlj9gHjzUyzrY+O7sKErFvQfeRK61CDfHj8ddCZc2vtLTNSTQdwUnzmFLytePLYeevltubHmR\ny+o/a0WVrCZrK6ejeLj6zZtg6dmLVuGDaisix4SA0wRkPlkTmdMKyppVnDnCSXIeeeQRzJkz\nBw8++KCKlXTmrLwTAkJACAgBfyDw++E3sefEcno8tsF6OkYPPyyvSHkM42iA7WNHeXyY+j27\nobFYYOrr49m7z0KOrTF0+/aqVXy2zjCPGHmW0nLK3QSCKe7f1S3HuqUZzm6dn59PYbDMKmv3\nkiVL8O2334JfOQ6lv8n27duRnJyMsLAwtdDNHjnt2rXzt2G6ZDwcViN//2Jo6PMX1vFyl9R5\ntkoOkaUUW0r+SErJlJJMVZRjrQ4K7YKLIvthXGQSMk2ncNv+/8FKi1dmZVGsVxm8ewW3xXZy\n8Z6173nMiB2NO1pdglBd/R7sDVu3wK7RiMXS2W6OnPNKAqaRo8iC8lcY1qyGedAQgD7H/iK/\n5e3GX1LfRRklxvlb4lXq79rVY0sMjFHu3n9KfhmvHv1KWWZeH3+Bq5upUZ+O5pFnu1da+k0O\nWrgAdvoNtnbtBnOfpNPKSmONuuSAEHCGgMwnq9JyqYKSq27Tpg0KCgpUdu/u3btXbU32hIAQ\nEAJCwOcJbEr/gB4+zTXGwVPwA6F2dG+K+JMV2bv9OD4QBWcvnXE1Ql56QSXMsZKrr40SAon4\nH4GbbrpJDUpL9zwuLg79+/fHDz/8gPPPLw+l4C8j3r17N26//XasWbNGDWnGjBlKQckJgXix\nmxe9AymLqsgZAuzabSlMJ+XkldAFhJ854cJ3B0qOnlZKbsWB0qOqZh20GBrWDReyUjKiL6LI\natgh0ZSJ94ue/8TXeRtxxHISLXWRuCR8IFjRwAqNp9MX4dOsX7AiZwv+kjgVF0WdPemN9sQJ\n6I5mwtKlq4SzcECWV58hYI9qoRTrrGTnRUV/iRv9FYVzeDztU5XE5pn2s3HhOf6OG3PD2gbG\nVmT3finzC6WkvDbOPb9/GlI8Bn61DAaaR/KiCCsgQQtBnKCLRSkkO3RC2aRLoacynLyLF8V5\n43OWbt0p9jkrKyncRqAoKxtz3+Va1xPwxfmkSxWUxcXFeO2119Tqftu2bV1PWGoUAkJACAiB\nJidQTNYytYmdrChLaF5njPVw/EkKaK5P3gsbPRTYWreurWt+c8weGYXSyVch6NOPYfz0ExTf\nNcdvY1z5zU1zYiADBw6k56IzwfmduNTnirKF6CWXXKKsRNnrZu3atWoMHNd84sSJeOKJJ5T1\n6Lx583xubO7scH7KQlW9q927k0sy8CMpENlaMrXshGpDT0rJEWE9SBHRD+eTUvJs2XljKRPv\nHYmXqlj0fG+LiopUHSMjemJR2MMq0/eHJ37G31Lfw9KT6/Bwm2loQ0qI2oTdu1nMSWdXZNZ2\nrRwTAt5AwDRqDFhBGbB6FUr8ILHd+8d/xCuZXyJUa8SLHf+EQWFd3I65vTG+Qkn5QsZSUlLq\nMJMssV0m9Ftr2LAegd9+DU1pKawUSqd06jTYg4IR+NMKBKSlwk4xwMsoO7t5OHmskDLS1CpB\nhdvR0gIKKysN27fCsHuX2uwUb9RClpUWSupl6UHJDEVZ6bJbJRU5T8CX55NOKyjffvtt1DZZ\nZDckdsk5efIkZs+ejeDgYOdJyhVCQAgIASHg9QRiQjrjWMHOGv3Ukl4lyqylxA0Un8eDwoHL\nNfQbZPK35Dh1MLTwZHnfHhg2/6FiUpZd6n43zzq6IoeFQIMJvPXWW8jLy8O2bdvAi9rTp5dn\no2YX9gULFqA1LTa88soragsJCWlwO/50obUsF0WHKXlEWFsEtWx8LNI9xUcqLCWPlGUpVAaN\nHueF91KWkmMj+iBM3/j5PGf2vTvhMkxqMQRPHvkMvxfsxbQ9T+HmlhNwQ9w4BGgNVW6Tcu+m\nz4Gld+8qx2VHCPgKAVtiIiydOkNPSVe0Gem0eJroK12v0k9eMHs+43NlAR2jD8f/Ot2BrsGe\nWwjuaGyJNzvfjVtTXsWz6YuVJeW0mMaHEdIeP4bAzxdDf5iVkAEovfSK8rA55LXAUnbVdES1\nbIlSUlyac3KqMOEdGysqHcrKTFZWkqKSQpVUUVayZSVl/bZ070nKSvEEqAFRDgiBOgg4raA0\nkaWKY1W0cp08oexNE4kJEybg3nvvrXxK3gsBISAEhIAfERjb6a/4bOtsFYPyzLA0KvNhL30P\naPWedXHhVWwWSzNRUPJYS6+YDN2hQzD8upomvz1g7ex+awZuV0QIuIrAli1bMHbsWKWcrK3O\nmTNn4sUXX0QqZXLu1cuzix619ccbjhUcWAa7zYTwLtMpVFrD4trtKjqsktywpSTHjmQJIKXk\nGFJGsvv2mIje9Y4T6SyTDmQR9XaXOZT5ewP+m7kMrx/9Bt+c2kDWlNOV+zjXp00/Au3JbJh7\n9ZFEFM4ClvJeRcA0eoxSULIVZenV13lV3+rTGbPNgv87/DG+z90Mdrl+rdOd4CQ2npbOQQl4\no8vduI2UlE8dWQi27J4cM6Jh3bBYELDyJwSs+hkasta39OhJ86kpsEdGNqw+usqWQMpK3iZc\nAm1mBvTbt5G7OG27dqpNWVZ261GurGTLSrLKFBECQqBuAk4rKO/AbImHAABAAElEQVS66y7w\nJiIEhIAQEALNk0CnmLHo2fJy7Dq2rAJAZEA8BqUdR3RnD2esJMtJPVkT2iIiwJmum42Q61DJ\nzGsQ/MZcGD/7FEX3/xnkutBshi8D9X0C7GmzadOmOgfCYYNYoqM9/0BcZ6ea+ERe8meUxEFL\nCspp9e4JW0BxopqfcjjRzVYcM5dbAxk1BlwQkYQLyH17dHhvcJB+T8ml0UMwmhSh7DL6+cm1\nuGP/XFwcNQgPtL4SCeQWy2Lp189T3ZF2hIBbCFi7doc1Nk65AmsuziElWJRb2nFHpUXWUjx4\n6B1sKEgGJ7t6pdPtiNKHuqOpetXZNag1Xu98l0rG9cSRBcrd+/Jo5+abuoMHYCSrSW12Fmyh\nYSi9/Arljl2vDtSzkC2hNSkraZtIysoMUlY6LCt37SBl5Q4oZSVZVFoooaOyrCTrTREhIASq\nEnBaQVn1ctkTAkJACAiB5kbATplaM/K2UB5XPeaM/wGhhnic2vgRTh54FkFxno0ZpqcA9Bqy\n7DcPIXfHBloU+er9s7VrD9MFFyHwxx9gXLIIpbNu8NWhSL+bIYEhQ4bgnXfewdKlSzF58uQq\nBDiG4WOPPYYEskppSW52zVGyaPFl0dHjSDlwCLE6PS7CCUTm7EFw4vnQB589OZaNvqO3FR1S\nCsmfcrfhhDlXIWRX64si+ytLyVERvRBE+00l4eQ6/o+2M8FKhv+Q2/e3OZuwJm8XHszV4mp6\naFcP703VOWlXCLiCAM1JzKPH0u/zQgT8uga+Eo7lpDkf9xx4A3tL0lUM2uc63IQgDy5g1IW+\ne3AbvEZKSl7QeCxtvnL3ntRicF3FzxwvKaE4k99QvMnf1THT4KEou+RSICjoTBk3vOOY6Cbe\nJk4iy/B0UlaetqzcSa7gtNkNBuUBo9zAycISoqx0w12QKn2RgNMKSna3efnll50aK088X3rp\nJaeukcJCQAgIASHgnQRSsn9Ebslh9Gl1FbrEnwcO/ZGZVW714ukEOXqa5LGYm5F7d+VPhWnc\nhZQgaJ9ambdSsHfzEOcsCirXJe+FgCcJ3HjjjeA4lFOmTMHw4cPBSskgemC89tprldKyhB4q\nP/uMLAaboSQXl+DGffthJutH3jgq2mJ6vSF6Em7uelmtRFgpubnwgFJK/kxKyWxLvioXrA3E\nxKiBSik5IrwHWEnpTdI3pAPmd/sr5metwhsZ3+CxXmYs6RSCh83H0MPQjKzivemmSF9cRsDc\nfwACvl+ukrGUXXiR14ct4Fi0d+1/HemmbEyKGoxH210DPSWn8RZha052NWcl5aPkfq6jb8eJ\nLQbW2T12tw78chm0hQVkzRqLsinTYO3Qsc7y7jrBMUlNvF3MysojFK+SMoFzkp3Tm93AizKn\n3cDpFaS89FfR7U+BgRbWC7NOAGHhMFACIvPQxsdU9ldezXFcTisoe1DshPbt22P16tXo0KED\nOENQVFQUMilA7MqVK8EuOeeddx7Fgj3jKtJcV7+b4wdKxiwEhID/E9iY9p4a5KDEMxZ7pVlb\noTNGU/IGDz5QUiwhTpBjowmOrW07/wdf2wi1WpTMuAYhL7+IwK++gKVjR9hjas+MW9vlckwI\nNBUBPWU8Xb58OR566CG8//77sNlsqivs9t2qVSulvHQkzmmqPjZVuw8fOowS4mE/3QFFhqyx\nPki4BVPiusLhaGklpeSmwhTlvv1T3jbkWArVFZxpl5UL7L49Iqx7jSQ0TTWuutrVkdv6LEqW\nc9naTDyt24gfEoswa9/zmEEZe+9odYnbYmLW1R85LgRcRoC+58wj6Ln4h28RsP53mMac77Kq\nXV0RJ826+8Dr6nvkevp7vDfhigbHunV13yrX1zukHf7X+Q5SpL6Gfxz+UFlSXhRV1XtHk5sD\n47LP1RzRTnkyysjbxHT+BQDdj6YWDkdUxhtZcWqPpFVSVpZbWCplJelbKiwr/UhZqd+2BcYF\n8wFacGPRFBUh8IvPoT12FGUUW11ECDABp/9KO9LDz86dO/HCCy+oZDicHMchx48fx6RJk9Cl\nS5daM307ysmrEBACQkAI+CaB7KIUpOb8hsSIQUig+GUspXmHYS3JQkibCz06KF1KMjScYXEA\nrZ7Tw3tzFXt0tEqaE7RoAYJo4ld8x91Apd/m5sqlIeMODXWofhpytXPXNDTJiXOteHfpWLJo\nmTdvnppTpqSkIDs7GzzP5M3gRw9lztyFY2SRfrC0rNZLdLDhl/widDSnKUvJVbnbkWstUmXD\ndEG4jLJkswv30LBuMGidnuLX2qbHDlLCisRt+/CqNhLfj7oKT2cuUZmDf8zZgj8nTkV1BYTH\n+iUNCYFGEjANG06JWX6E4bc1MI0a7ZW/z+vz96mYk8W2MooFOxnXxXmvIpVvRxJZXr9KcTHv\nIoXq31M/gJYWOS6IpDkpLewY1v2GwO+/VeF/LGRUxVaTtrizh8Vo5C1u8OW2Nm1Rxtukyyop\nK0lRyYl2aOMM45zIx9KHsoFTVvA6LStp3LZTJ2lRy4vnwvQdb/x8iUqoWRmYhu/Z72thpr8T\nW7z/hHSR+WTlu+zce6dnLx9++KGymnzggQdqtBQfH68mmRdccIFy6Q4LC6tRRg4IASEgBISA\n7xLYkPau6vzgtjdWDKIwc6N6b4ytuoJdUcBNb9g1hsXSu6+bWvCdai0DB8FM1qScOTLgx+9V\nNknf6b339FRLFqmeFE5g0pyFrSZZQdmuXTuMHz9eoViyZAluu+02/O1vf8PFF1/c7PCUEZO6\nxELPnq9mfgsz/lBFInUhuDJ6uHLfHhzWFQYvcsWsawx1HddRqAoNufWbh43AqKg+WBzRDW8f\n+x4fnfgZf0t9D8tOrsNDbaahDWUTFhECPkWAEoKZBw1BACnO2ILMMmCQV3X/u1N/ULbuj1Sf\nnmx3w1ldpr2p4/1DO+HVjrepeJkPH3oPz0dMxsTl5M2TfgR2oxGlk6f6VHzyCmVlFctKUlRu\n26o2O2X/tvQ8razs2q1CWWlYv45ibC5HcWmJWqw3kiKz7KoZsHtiwZV/r8rK6Lu7mLZSMhoo\nUd/jOP3K3+nlx+hc7ikqW1r7R4gsWzmJkT8pKGU+Wfutrs9RpxWUqampyvWmrspDQkJgJQ05\nW1OKgrIuSnJcCAgBIeB7BEopptnOo58jNCAO3WInVgyg8OgG9d7oyQQ59Duj37MLtpBQWNt3\nqOhLbW8sdiuOlZ6C3ubfyqDSKVdBl5aKgFUrobKHNkGcpdr4+9KxgoKCCldjd/eb50uVvVDc\n3Z631W+mJDCDBw/Gtm3bMHfu3AoFJTPZuHGj8sj5+OOPcc0113hb193an2AtW0/yQ5yxlna0\nZCl0DFNbjMCF5NI4KLSLcm+spaDPHTJs3az6bOlXvtDFsTLvSbgMl5JV6JOURGddwV5M2/MU\nbo4fj9nxF/qehajP3RHpsCsJmEadp6zEAlb/4lUKyo9PrMSLGUtVwqwXOtyCYeFkpedDMjCs\nC15qdzPuPfQW/pKzBMFWPUb17oeyy6+EPTzch0ZSqavkEcRhi8p4Y8vKtMNn3MC3boGBNoey\n0m4MUsl/2ApRCS16clxy7ZtzUXzfn89trcuLpCZWMJYrFvkV5JlUse9QNLLy01FGHStXRqqy\nlbreqLeUDM6fROaTDb+bTn8Sxo4dq+IFHTp0SMWgrNw0WwI8/fTTiCZ3s06dOlU+Je+FgBAQ\nAkLAxwlszVgAs60EI9rcBZ32TADvwqNkQUnuNcaYcpdvTwyTg2zzBIpdQlCH1RsnjXjr2Hf4\nkCxwSm0mFej9ihbD8GDiZK9LFOESZpRgpJTiUQa9/QaMn81H0X0Pen1AfpeM24WV8DymuVs1\nuhDnWatatWoVduzYga+//lopIx2Fr7zyShw5cgRXX3012Ftn5syZ9CfuWctWR1+a4rXQRspJ\nzTqK0TWGmmd3Pd5YrPTuMG6O641bEiaVH/KX/+kBWb97N2yRkbC2a19lVB2M8Xi7yxx8fXID\nXsxchtePLcdyyvj9cJvpGEJWoyJCwBcI2KNjYOnVR2Vv5vA01i5N+9nl37lXMr/EByd+QpQ+\nVLlL96QENL4mzPL8pcvwhkGL286z4a7RNrzYaRBG+qpysvoNYGUlfSeW8Xbp5aeVlVvLE+yQ\norI2YWWl9uRJBH6+CPYW0SoUklIuOpSNrGg8/V4pGFlJ6YTYydqRFaMc/x2xcbDT3JP37cHl\nr5wdXe0HGelcsLJm5TIINCL4lf9CU5Bf8atW0SzFlLd0bdq/iYq+uOiNzCcbDtJpBeUVV1yB\np556Cv3798fNN9+M3r17g60ADh8+DHb/5viUCxYs8Mqgug3HJFcKASEgBJo3ATsp+/5I/5Cs\ndwzo3/qMRZPNUoai4+RWHNkVWkOIxyBx9kOWs7l3v5TxBRZkrwZbUKqy9Prlqd9xwpyLlzvd\npo7523/Wjp0oCP9YBJIVpXHpEpRefZ2/DVHG4ycEvvjiC4wZM6aKctIxtBYtWuC+++7DJZdc\nAl4Qb06L3q0QAKMtGaVaEykp2RU0gja2qtxD+Wq3IiqnD5DgIOUfr6yc1JhNMPUdQfpYh0K2\n6tgujR6C0RG98XLmF1hK7t637/8fLo4aRPHyrkS0wUctpaoOUfb8nIDpvNFKQRmwehVKmlBB\nyXOix9Lm45tTG5EYEIO5lHDG10InqOQq33wJw+Y/YKfvjCHDz8ML7TvigfQP8ODBd/AyuX4P\nDSc3aH+SKsrKK2hRZxeCPnq/1hGykjLgj021nrPTgp9SKgaHgBXn7A6v9k8rE5WCsULJSMpG\nVi6yAvK0wrExiYZKr74WQfPeUgvB3EelGqVxlU26HPbIqFr7KwebHwGnFZRxcXHYsGGDWtl+\n6aWXqrhCcQyhhQsXYtq0ac2PpIxYCAgBIeDHBJKzViC3JA19W01DCE1o7VYT8g8sRdaqFbDb\nzNAFeTAAOU1q2L3bTnGdrHW4MedaivBJ1iqa/FRdGTbTxPy3/N3gbJU9gj2YcdyDnw3TRROh\np4QjHLeIg6p7W7wrD6KQprycwNkS4bCSkiWAkgQ0J9GUZmPm0T34uLUWVm16xdD19L3XoTgX\nx06lw9SDHj79yKrUQHH5WCz9BlSMt7Y34fpg/LPt1bgiehj+Q27f35Il5Zr8XcoVfGr0CJUo\no7br5JgQ8AYCbAnHSVv0ZPXHWYttLVt5vFsl1jL85dC7WFuwB92DEpXlpK8p+PWbNyHw6y+h\nLS6GlRiWTqUkOJRoZiTRfM5wE/58aB7uO/gWXqGFaI7N65dCSj0LJSVm5aymFgtIVkLyAr55\nAH2nKuXiGatGUCzLphJeRC8i1/Og39bAcPwYrGQ1X0LxWa2dOjdVl6RdLyTQIJ+ZmJgYrFix\nAvn5+fjtt9/w5ZdfYjetfnIGRlFOeuFdli4JASEgBBpJYOOR91QNA9tcD5u5CGlfXYET6/6J\n3EM/quMlmatxfM1fGtlK/S7nQNraoiKYe/WuM77O/pLMOmOz6cgdfXPB/vo15oulKIZfycxr\nYacsyMYvlkJz6pQvjkL67OcEzj//fKxcuVLNI6sPlZPnPPfcc+BF8TZt/HMhofqYHfv64Ja4\n5ORh3Ji+A2Fkoc6iIx6jctLxcOom7NXE4OWMo47ivv9KSgZOkGMlV0FbQv1MQ/tSBt/53f6K\n+8l60kqLTk8dWYgbkl/EXlp4EhEC3kzAfN5Y1T22ovS05FgKcev+V5VyksMjcOgEX1JOasht\nOeidNxG0kDw1TSaUTbgYxffcp5STDpZsZf1s+xvV98K9B97EH4V+PNfjpDmU4ZuVkbVJ2cWX\nwNq9p4rTzsln7BFkjd+EyklHH+2xsbBMn4ngfz0B3HyrKCcdYOS1goDTFpQVV9Ibdu0eMYLc\nMUSEgBAQAkLAbwlkF6XgcM5aJEYMQkJ4ErLWPwZTHk36yHLyjNjJovJzhLQZh9D27s28W+He\n3SfpTPPV3kXqKWEbPbjWJmxF+ULmUmV9MyKiJ8Uq6onewe3qVGjWVoe3H+MJYNllV8D4+WIV\nj7LktjvrjNXp7WOR/vkngQkTJmDo0KEYS7HNp0+fjn79+qnkihkZGVi8eDH27t2LTz75xD8H\nf5ZR6QLCEN5pKi46uAwXkqKySGdAkNUCHUXt0hpbID12NH49kY1REeEYHh52lpp845Rh53Zo\nKOmZIzlOfXvNC02z4sZhfGR/PJe+BD/nbcd1+57HDOJzZ6tJCNHVlmSovrVLOSHgHgKsULJR\nrgY9xQ/UTLyEErlwCAf3S2bZSdx54DWklWVhQuQAPN7uOt9JNEXfDwG/rkbAiu+h4ViFZG3H\nSQHZPbk2GRvZF092mI2HD72POQfewNxOd6JfaMfaivr8sbKp0ykhzmsUczK7PK4jKSvtxIvj\nkdujyr0QfH6QMoBmR6BRCsrt27cjOTlZTSh5oslxKNnNW0QICAEhIAT8h8CGtHlqMIPb3qhe\nCw5+UU05eXqspPgrOPSVexWU7N69a6eKmXM2l5DOQQloGxiHw2UnatyIAI0eXYNaY3dxGnaX\nHME7x75HuC4Yw8O6K2XlcMpi6UtWBTUGePqAecgw6PbugYHiFAX8/CNMF46vq6gcFwIeJxAa\nGqq8cW699VZwPMr58+dX9IGtJnmfE+U0R4kd/gSs5gIUHf4O4fR9ZdPQ915IKyRc9B4e0yfg\npn378X+paVjUsxsiKWGBLwsraljMSeXZu50dS3xAFJ7veAt+zduFp9MX4dOsX/Bjzhb8JXGq\nynTubH1SXgi4lQApkEznjYFx2ecw/PYrTBe7P+FVcnEG7j7wOrIt+bg6dgz+3HqKz+SK0B5J\no4XWRdAdParC+pRMngrLwMHnvEUXRvaDrf31+HvqB2rsr3W+E2x57W9iJ2Ox4nsfQCDN9UJy\nTsFCFpKFlGxG4jn6251uXuNp0KyG3blvv/12rFmzRtGaMWMGWEGZlJSEOXPm4JFHHkFgYNPF\nN2het1BGKwSEgBBwH4FScx52Hl2K0IB4dIudqBqyWSjLbB1iNeXXccY1h3Wph6AtLIB5ICWP\nIFfms8ntrS4hl8j3VRG2ttGzDRLF63m10+0YGNoZ+ZZirCvYq2JSrsvfg+9zN6uNL+gR1IaU\nlT3KrStD2vusdSWvruuOPK8UlJau3WBrK4uI6gMh/zU5gaysLJjITY8TLHK2S06Gw9aTHTp0\nQOvWrX3mAdodILV6IxLGvQFbURoCLZmwaMNhC+kGjVaHvtTgrQnxeD3zOB47fAT/7eS7D92a\n/DzoDh2ENbEN7BQ+qjEyKqIXFod1wdu04PTR8Z/w19T3MOLk73iozTQkBjau7sb0S64VAtUJ\nmEnBFvjDdwhYvw6mcRdSdmP3PTNvKkjBAwffRqGtVMVqvTH+ourd8c79sjLFyLD2VxVj0dyv\nP2WxvgJ2Wtiqr4yPGkCeNDb84/BHuGv/63ij813oFeKHcyCaC1uT+iGQPGesFDLDnpdXX0RS\nTgh4JQGnFZQcd5KzKprNZjz44INYu3atGpiVzIknTpyIJ554Qk0w580rt7jxylFLp4SAEBAC\nQqBeBLZmLoDZVoKRbe6GTmtQ1xhj+6PkKH/326vWoQ1AcCv3hv1wuHeb+/Bjet3Ck9L3jq9Q\nBW5odSGCjcGI1oTg/ODeiDKUu0VywoUJNIHljRUke0vSlbJyLSkrdxSlYg9bVx7/AaG6oCrW\nlbEGz7hk1T26+p/h1fXSaTMR9O7bCFowH0W00u7Oh6H690xK1kbgxIkTeP3112s7pY7x/Gvw\n4HNbj9RZgRed4HkiL2jzone3bt3QsWNHtXlRF5u8K4GRnRATMxSFhYUoKCio6M/NLeOxNq8A\nq3LzsSTrJKbGRlec86U3ekrkxQkeWPngCjHSb9A9CZdhUovBeJLiUnIikKv2PImbW07A7LgL\nfMel1RUwpA7vJUDxoU3DRyLwpxUwbFwP86jRbukrWxI/Qso5G82HHmt7LS6LHuqWdlxdqW7P\nboqf/Tm0ubmwkZsyW01aaYG1IXJxi0GwwoZHD3+CO8jFnZWUPYPbNqQqueb/2TsP+Ciqrg//\ntyWb3ntCCQkd6UoRBBQQxQaooCJ2fbF8dn3tvbz23hVFBewggl2RKr0GCDWN9N6zJd85EzZk\nkw2QZHezm5zDb9iZOzO3PLNJ7px7ihBwKwLuPJ9ssYLy/fffRzFp5rdt24YuXboocYP4aWlI\ne79w4UJl1fv1118HbxyjUkQICAEhIATck0AtTWo3pc8n60EPDIo55moZOux+pP14vvWgyA1R\nqw9BQO/Z1uX2PKIXWe2uHaglawNTQs/j1vxFzl9IrszAuUHDcV+3SxAUFKQkdiun5Dq2hC0r\nOas3b9fRy2wpWVeuK91bb135W9EW8MbSizJfWqwrB5B1pVZ1fEtOW+05s4wn9vwCxDGcOGlO\nFQUnF7EPgUJarD1QUYlgeuGM9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/+smK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\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efANoQSEXXNO7zl2HHCDEz7ZB/jMh5K\nbeO7re9hunLf2wl7H8l7D9W1F5cifCUD30jQU4sUWziF0O9a4XmxDzb2gqeqnOh9bzXiS8a2\nY+5IT9e5vR+hX7XAtTOmwl8lFvrQ+4EapOqGPi+P9FjSYVNXV3ek1ej9NQIjInAktl5nJztM\n+8fvg9X7FOO7/qkN9i4+u1x8d54XQt+11fTeGK4HdsRTHd+V/JTwPchn7X1dxrPWy2ftcj5r\n38lnLbM4W67wORv4azv8j7ATq58kRJCqqbeWIXqZhKmxYHtptwbvbIXv6V7YEiTQyhzou5qu\nneeP3Ol/tHC38X0b+m0LPCvCxjutxoXea6sQX2ytd5qJT3Irk4bc2o6yTuP7KuzxofNddXAv\nt5AxYzaWY0dTHKFfNsO1qV99GyRme9D7/lokZ7Dj2ILFuY22w6/zbIcTsrZD7djbDmNx+rbn\n2V7ev94wbR1W2DuDgpXPViBTYc37wfNiL4J3tTH8TpKfv/x2O5sign9jGAD/IRr3YwHeKOrw\nPtaF4F+ZtbuH7zY3321vLEXfu/muoMBlPIq2J8cD1fGt03IEpfRk33DDDfj+97+PU089Fclk\nUpGJixcvVuNDgeOee+5BKBTCRRddNGi3u+++G/fdd58iQQOBAHbt2oXrrrsOt99+O+bPn48j\nbcN4EJS/ePAR3HL3PDjZpWP+fOWhKcqlr13Yi4/feNqgc8yfEQ46me5ncpB+xOPdSNDNOU43\n6ASViHEShQm6ISdEkchxVNSBzPAc4xDlPv3MPh0neRijYjBOIi1OqjBOGk2GBI8uOkJyTpzn\nP5JAF73wCG4iCZRv3glJKSTLle/6J1oqn1ZkoyIahVxUJCOJRp6VQT6SrOEyw0DMr8U8o2LL\nDm2dLeXDY7/5GOZ10/BXrx5jf2nniuo6fPlDD2Oqp57rPFTUMS4cyU7qypBI0+Am8SxEoxCK\nkSzRmDgCjt9rtyPIwU9Gx0elXG5MwrTvtRrc+fe9cDNojtlO45oDP1x0AjzXUtUm+LFd+QSi\nTAuxGBcyMY9YNIjGAcJREYxZwtHc53CIw++/0oVrt72mQDSvjmAZc7hxzRsWY0WNPUskMiZQ\njkzMIxXzSEa/Y+g2fhKN+fsJOXmo3w/JMANlf6YPDX37c1hKgw0CvZaGB3uhaXcMIhZNojFL\nMKbMTI0m4ch5k1gUUlIxNsatdBj/DVdoG++tpXtWw0slsXnNpTK57muqF8F9JQlMqnwVEVlA\nMk4kKSjGZvnX96jfvHnNRcSaDjnQ8b1GZALWMIoCf26D/x+d/EAauCTSjxE7I4ieT0wZWHg0\np/ihXPGl3XDs51M0v5180Pd8vA6xpRJH8+gXx54YKr6ymw/8gacEozsgQyKi47uN/GAeW8Nd\nG5RH/5of6y04UltvPAlKn3zAsdMiX2wkz67EHB+6/u80y12awP/yWftAkWctn189H7NeR0PJ\nbQfYIUSyL/+Zy9dWhARl+N1M6GGxUvbNvXBtiUqI71yR56+QENGLmLjDSoXePhVf3AVHM0O9\n5OPL9nZ/corlSEpbJIWKz++Cnck6zPaKzUUjDJ1fnYbkXIlJaJ1ib0+g4pZdsMVoC6uGZs1P\nElMd35qO1BRrkX6O3VnbgfdCzl4U28FnRztth0zp2NoOR3qlXK9HUPZtulrxmzbXXj4b0uVO\ntP93I2MEsPEWKp7nelDy8+bB7wq2N9ngQed/NPA+Ns/CGo32/6MDgT+3535r0ip5t8UX+dH9\n+fpxaaS2J8cF1nGt1FpPBZ7qihUrMHXqVEVOypk7nU5ccsklEFJRVI9SwuEw7rrrLmzcuBFl\nZWW49NJLIQRmYXn11VdRVVU1hKB89tln1TIhJ6U0NjZi0aJFePTRRxVBOZo2mMfqY+opGfKL\n/BDsJJ3Gspz95GKSk1QB5VVqPHIy+NCKetziXUsSQygNY1BvVnm0igWjHrFCGMgevOSZar7U\najkr89QFklmQQdarv9w+xhIhXtQ2an9ZZuzj4ZTEK85uRXViB67f1JbdSpYbRVrkS/bj2pff\nihfqrlcL1eE4lX23qilz2hzzoEYFg7bjPnJauTXGhFmfzMm63Ho5rew8HU3UdCgew/zuA0Xb\neWbrfkx74RI4Mn5uO3DeFOXBT1xKORYlpcSMFETtXCbzahCc5AgcS2I1NaeWmY3INpzrMiQO\nOVINNbCV7Tmo/WQFcH7zAbjyyElZlq0J12/eg5/fdYKxjyzP7idmFL1xc8vlIKre7L7GdiS4\nOC/vLBE2MO2OmpaHgdwtslyumXnHyDayXLaTc5KWq3XZ5Yt3b+PagbbJtOzvJrn9pQ1NQAeV\nf2yHKnljxevm5mUPKaw5uyzH+9JIEJu8h1j2yCa5fThpTstyKXm4qnmul20cqSTO6tussFDL\ns//kqPXhA3jp51OQJKE66mKXQOfMhifB0enybOeN4ZB4itlg6WbmxcFZGLkPO7dzgdS5vQqy\nno3BqH6O94XhoTrNRCO/PQvCWxE9kT7phUXAmWAvpNDv6U6UZ7xJk+TestPQD/ydqqJLx0bt\nXniqhzIvHx3++/jBzHbmF/nA86zog2ddFKn6Q7jm+ZWM4bR7Zd8QclKql3aLqjI1V55FR78E\n76RiO+8DQ1qksKWyx/9gFyLvrRnTRsp7VBeNwHgicCi2XjweR0fH4Lhp0vk71raeOl8SPMG7\naUsVeXa5NkfhpdI6Od86pImo5VRHUMH7WD1rX+iFm+qY9DiorA/33rAfiMPzPMnJwvby+ea/\nvxPxc0qQoaLSKsW5KUqlHMnJwvuB83KfJE6jKtFCKlX3il44WgaTk4KleqdRldY92zr3rrTL\n+09D9WuSk6qt/CeJVeQd3PvZ8SFN5DiHU/x/IrlDFW3+/SvTEoNQ7ofw+/h9Z6ES/EMRe1Hu\nZSqXg/d0IPo2KucsVEQ5OcS+5bPB3pVE4CF6AF5Qap3W8h0k9viQZwPb62Snsu8pCpBONbgO\nSzSa7myBvwwmJ6Vd8q5wvxaBe1tsXDoEtD1piat/SI2wHEEpbtf19YNfBkJYtrW1Kbdpcff+\nwAc+ACEXr7jiCmzYsAG33HKLGoTIHE2RY0id+UXmW1r4UGI5WBvyDdLf//73+OEPf5hfFYQA\nra6mG84YloWdTUVJC/mEq4v04bcPeYscTawvPqVUERZjfEuHk0o5xusoVoRwOYFxpq/btL3Y\n6gld9lg9XRKp3nSK9VFQhIL7t40JvKlpW8GaiZ/d6y9TpGDhkeWal8X78KW1LxWuOirzcpcV\noxKE0Jzb2Yby5h1HpV35B+1lBnNRS0qbCouod0/o3IySBGO7WrQIvt5IP3w3H/3fz0gQiZEh\nKhoZrFzEmC/91l4rN1G1TVw7K6x+zfmK8W9NIFQ7th9FVo7BafkbRzdwVAgciq0nHd7vfe97\nB9X7ve99D295y1sGLRuLmczuCDPODn1XSd3yIVry4/1jcZgJqUOetaL+myxF2lv+hV2TpblK\nRVfxyR2Tpr0Oxim3+jvNBFPsLtcOqv8s/g7OtZfPBs8qdnKvsradmGsvbQffY0zsw2EyFLFv\nhVyTYTIUIdwlDMBkKTa6d5cz6ZP93LG1JeX8tT05We6CgXZajqA8cOAASkoGx1QRN22J6djd\n3Y37778f7e3tyj1bEue8/e1vR0NDA2677TYsX75cuW4/+OCD6gz37qVLhMuFdevWqfn3vOc9\nOOeccxTZWXgMmd+8ebPa7mBtyI+FOWfOHKXwHIBUFFsZRKPR/EVHPN3H+ENirhYjguKMM7i9\n3KfWSS+B+lMbcorjwnlpjBKnqG2NSmUbVYGsZFHrjcnc/0HL8hqSPZSSqqV3iMpTWjq4CPGX\nYQ/vgVmj6CkbuvvgymRuNNuYexVsW8ZkK3aR1RUpgnItYze2zqTLrwmJjLPTaiwWLIsxbcBm\nTudXKctypWA6N5ub4JZ507KvY4ckHxm0OFddUhS6p7IXL2+f/Gm1eJh1Cjyuy63OTWSrz5sf\ndA6yOm+dTMts5rluKk5pGRUUWcIcQEgvPPpqOh97Pm3GY6CglXIOVPjOZYiBiqPfTtt2JpfZ\nHxvUM55rMMFOn3P02yjtsb3EOE3swS8sakmVC5kFFogz1cdrvoYqmcJGcp5iXGTms1e56ugr\nKG27+K7YyzhSQ+FUv//MMrrvWcBFx/ayEautCJxIB+yIj/E7T96jfr811KPFzlkvm/wIHIqt\nJwkbCzvBpSN6rG09haojgeGeTOLgkpnJ38UUC8WaO9izdgGftZXDndFRuI/aGU5jI2MjDvfM\nPYWGS8hCn0diE+yIDFFJmcill9IWdIufizXKZHmnmWjZNrFzulUFqjIX5cYSzy9zlrVc6G2v\n9cDG2H3FSsbPL7DTLaTwYyNtK2k70NOisKifH92mMyfy92ahYnt+qOeNNE+1l0rwzBwLKRKp\nmrW9YMRNLYRQ2bnTqVZuKCZgKtx6guaZ8M22ivdvkcOpcHRM2JkeY1tSDqXtySKAW3yRhd7A\nBlJCKErcyfxizsvHiigmxVD8wx/+kNuktbUVEgtIFJBCGF588cVqnRCVorSUZDtSpk2bBgfJ\nPFFAmnWqFfwn86bL98HaYO4jYzmWeTxzucSg7OrqMmfHZLz5pB7MedYghPIrFFXYS9NsWPSf\n1ointuvzaTQ2dQ8hKYUEqrq+BPZTmLjmKJeGaBrJD9npPs0HZV5b5OUTdbpR81907yEhoF5G\neesnetK1ksTFrUPvI7nmfTRAkp8eBdk7AY320R0twCQ5hcS0YBv/cCkiJ1rAnUdiIn2ULlJh\nklZ5mMg1ljg4nZ+ne6oFDHzn1mxsx7w2yiRzPzHodQi9N1UVrDk6s4EykkcP0yga/KhWD6ju\n6xkI/3QLEJQkuCo/HYW9jde84Mec8djQ/tlaSwQQd+ylQuMLu4dcSLnmcbrmdH9sbNX4Qw40\nygX+v9uYVILJugq+i4Qw6T3Lh9gYv/Oks00TlKO8OHqzw0LgUGy92bNnD/GWEbtzrG09dSL8\nTZUz6YWT6q1C1z15gXV8qpYdahYy35mpufJTfNZ2FHnWMl5b++fqVKzaw7pI47CTJMWpvHkH\nbLQF84t80Auu7Z+jgscCnUJm2+ydSVQWUUnKs1eSonR+cmzDa5jHPdyxijn4xeLvtNjpAcYk\ntcY7zTw/92s+lH6nKctAmUs5y59Y9M1M3nGdNewus2XeJ10q4cyQdzFthr63VxiJnsyNLTD2\n19J2+Dtth0J7kfdvz3urEDvLWgRlyJmC9xmSaAW2jjx7uz5Ug4SFwmvI5S3ti8H9+tAQELKu\n8xPjk8RQ6j7cUnFLv0ryVGiXy0d35zx+e4+xLSnt1Pbk4V6to7cfHw/WKhIzsrd3cEC1np4e\nlcHb42GWMq7zer3qZlNqQX7E1NTUKNcbIR5PPPFEvPOd71SDEJJz587NzYuBKfsIwVnsGGbG\n0IO14WggtvSmuXhlKhO28OBiUhljG/YFvTiRQZytUgJfIbZ+j3KnNdso451vqoPfAuSk4GQj\nIdX0wXqGK5SEPAZdJeMkk9S0f5pEr0UM0/QSH3ouZNY4tllISXMcr/MieZM1lHSCZ/8HKpCc\n6lZ4Gm007s/wW8qRtAI5KY1kL3jP5/mRxGxx6ez1lbFkRu35LK+5BchJaWZyjpcZpo1rLgSV\nFOnBlyzJEgzfKkUysyZmeBVxKj8haat83EWZIdsS5KQAxd9396emKgJarrMUGctHRw8D9Vsl\nu2Fqmgd9NNLltyPXWrVTrnmlEz3MkG2VErm8AvEFvoFrTutBPpD7zw0hxphtumgEJhsCVrT1\nTAy7b56iko7lnl18JsgztucjddYiJ6XBfJd203aShFm59maftd2ftBY5Kc2VdnZ/iu0VTPPf\nDbLcQjagtFWKJOeQ664UUeY7gu2WpHTdH7eGOMFoqfE/NZ3vNGbsNt5pxjJlx9C7ovf91nmn\nmW2OnxxA5NIyA99sLE+xaZJyHldZQwhgtlXGkrk9tiSo3r/yDjZtMEkyEl1uLbWntDfy1gok\nmGhI2bR8hkmble1wHs/DYuSktFfu3RS/acRWlGLat+G38TwsRk5K+3o/zHeCKFHNZ0P2XdH7\nvmr17SDbWKlIoqwMvW4GPXv5e+u+mc84PtN00QgIAhbqgjUuyMyZM/Hwww8rRaMkyJHy+uuv\n5+JSSnzKpqYmfPCDH8wFJ9+3bx/Wrl2rEuYYtYz8f9asWarOyy+/PLfh+vXrceWVV6r5g7Uh\nt9MET0z/7nRseJTJCJ7oUz07jlM8mCrZBi1CqCk4Sh2I/WwaYo+GkVlP8yRog/PNTgRmW0hi\nzob6z/OgY+EMJP4Wh70lhcxU5sN+uxueMc5Ee6S3SOzGSnSd50dwVQr2fr4456URo5LOStdc\niJ6ubzeowP0le2jw05Or82RmPifZZqUimRjbb52Bkuej8DBEYoIcryi/5MVupRJhwHAxmEtf\nTcAh15z9D9GzqUjMGh+WaCsJ3a6vTYPnpT6U7jZIv+4TmemeBJaViqhL2r8/A6HnI/C285rT\n86nnTC/S/FCyUoleUo7EQj9KVsfhpHA6zBDJkbPpRmQR4lxhxfuv+4v1cL8cRtkOPtv53ula\nYEeCH0W6aAQmIwJWtfUEy3SNCx3/MwOB58PwM4xYkq+AniUey2XoNa97cqYX7T/Ie9aSJ1HP\n2kprPWvN9spzq/37jQi92A9PNxAjD9W7zG/ZD+TYshA6ZnpQsjIGVx9tAoo8w8sCqgPOPCcr\njaPMhp44wY/SNXE4zHca2wvGmbNiCV9brbKLl66jCjjJjuuGDMkz/uis9H1lAsfO1x4S0+7X\nwijdRMkKmevu2fS4oDpVOmYtV2g7dH25Hp6VbO8Oto4cVNdC2g4nWtN2kG+ajm9ON75p9rIj\ngIksuymwSVrsO9a8ziq7+PcaEXgujADDE6cCvB/OcEE6v61YJDml2OXB5yLwtdEuZ/92z1La\n5Xzn6aIRMBGw0S9fOrksUyQJjiggr7rqKlx33XXYuXMnPvGJT+BLX/oSli1bply8P/ShD+GG\nG27A1VdfDdn+y1/+MmoZoP8b3/jGoPPYtGkT3G43xAjNLy+++CK++tWv4tZbb8XChQtxzz33\n4I477lBu4xLX8mBtyK+r2LS4eEvMzPEq0usv5K3ET7JqETWrXBOJzzQuLlBjdOLiQlhaWqpC\nBPT3kw2yaBHVryiIJai/VYuok0WFLL+fwmynVmqzz+dTnRkS0zYSiVipaYPaIrFuRS0+3s+T\nQQc9jJkpU6ZAMtxKbGCrFsFR8BQ1fjjMeFMWLfIskmeShCuxclBvebZL+yR53XgV83kyXvXr\nejUCR2rr/f/tnQe8FLX2x6OiYgUBlaJSLChWFGzYBSv23ntXRJ+9K/pEeDbsDbtYsQJiw/7E\njgWsiBXFgqCoiDr/8zt/M2927u4kszu7d9b7y+dz75RkkpNvdmbOnCQnmOJdbb0B09Ch8/38\n888NZv7ksQXr5Vlr2dWLDmjlhU9+fKfg2Ttr1ix7Orfbli1bGuhceX+nWYD1oGtbWbGFH1x8\nb0FPrIeAbwS4VKum7pAVB6uD4BmPZ33eA+wC+D3guwbfN3kPsM+0bt1a32t4v1Uz2LasZhnM\nO1sC+Ro6JHWDEWbAgAHm7LPPNrfffru+2Lbffns1TqLqMCjCuDhkyBCNh/LWo0cP079//wZk\nunbt2uAcTqy55ppm1113NUcccYQuooNRmaeddpq+9BHvkgFpGEiABEiABEiABEiABOqTAHW9\n+mw3Sk0CJEACJEACJPDPJZA7AyVQd+/e3TzwwAPaI2R7h6JN0KdPH4M/LI6D3jkYKdOG/fff\nX/1WYkQNeqfjwSVDPD2PSYAESIAESIAESIAE6ocAdb36aStKSgIkQAIkQAIk8M8nkEsDpcWO\naWRJAcbLSgKGFxczTkbzdMkQTct9EiABEiABEiABEiCB+iJAXa++2ovSkgAJkAAJkAAJ/DMJ\n5NNb8T+TNWtFAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiQQI0ADZQwID0mABEiABEiABEiA\nBEiABEiABEiABEiABEiABGpHgAbK2rFmSSRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAAjEC\nNFDGgPCQBEiABEiABEiABEiABEiABEiABEiABEiABEigdgRooKwda5ZEAiRAAiRAAiRAAiRA\nAiRAAiRAAiRAAiRAAiQQI0ADZQwID0mABEiABEiABEiABEiABEiABEiABEiABEiABGpHgAbK\n2rFmSSRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAAjECNFDGgPCQBEiABEiABEiABEiABEiA\nBEiABEiABEiABEigdgRooKwda5ZEAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiQQI0ADZQwI\nD0mABEiABEiABEiABEiABEiABEiABEiABEiABGpHgAbK2rFmSSRAAiRAAiRAAiRAAiRAAiRA\nAiRAAiRAAiRAAjECNFDGgPCQBEiABEiABEiABEiABEiABEiABEiABEiABEigdgRooKwda5ZE\nAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiQQI0ADZQwID0mABEiABEiABEiABEiABEiABEiA\nBEiABEiABGpHYLZAQu2Kaxol/fDDD6aaWCdNmmRmzpxpunbtmlugs2bNMh999JFp0aKFad++\nfW7lnDp1qvn6669Nhw4dzIILLphbOT/77DMzY8YMs+yyy5rZZpstl3L++eef5oMPPjDzzz+/\nWXzxxXMpI4T68ccfzeTJk027du1My5Ytcyvnl19+aaZPn26WXnpp06xZs9zKOWHCBDPffPOZ\nJZZYIrcy/vzzz+bzzz83iyyyiGndunVu5fzqq6/MtGnTzJJLLmnmmmuu3Mr5/vvvmznnnNN0\n6dKlajLiOdeqVauq5c+MSaBSAj/99JP5/fffK80m8fpff/3VQOfDvbDooosmps1DJJh88cUX\nKms93L/Q17/55huz2GKLmQUWWCAPCBNlmDJlivn+++9Np06dzDzzzJOYNg+R9p221FJL6Tsj\nDzIlyVAPunZU/o8//thA915mmWWip3O7D90Buk3nzp1zK6MV7I8//jAffvhh7r9prLywC0yc\nONEstNBCpm3btvZ0brdWL1944YVNmzZtqion9cmq4q1O5jBQMtQXge222y7o1q1broUWpSSQ\nF2bQr1+/XMt5yy23qJwPP/xwruXca6+9VM7ffvstt3KKMU1l3H///XMrIwQbPny4yjls2LBc\ny3nYYYepnN99911u5fzrr79Uxl122SW3MkKw0aNHq5zXXXddruU8/vjjVU4xSORazlVWWSXY\ncsstcy0jhSOBfwKBV199VZ8J559/fl1UZ+TIkSrv0KFD60LeG2+8UeUdMWJEXcg7cOBAlRe/\ni3oIxxxzjMorHYT1IG6w++67q7xi7KkLeXv37h2sscYadSErhFxxxRWDrbbaqi7klcEM+ls4\n8MAD60JeMf6qvKeeempdyPvcc8+pvEOGDKkLeSlkbQlwind17L7MlQRIgARIgARIgARIgARI\ngARIgARIgARIgARIwIMADZQekJiEBEiABEiABEiABEiABEiABEiABEiABEiABEigOgRooKwO\nV+ZKAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiRAAiTgQYCL5HhAyluSsWPHGjgiF98jeRMtlEd8\nJRrxL6GO0ldaaaXwfN52sHDGe++9Z8QvSq6dCou/IYMFfTbeeGMz++z57FeAQ+kxY8boIiSr\nrrpq3po6lAdO2999912z3HLLqWP8MCJnO+PGjTNwiL/++uvnesGUxx9/XBcb6tmzZ84I/k8c\nLILw1ltv6YJDWFwgr+Gdd97RBZx69epl5p133ryKaZ566inTvHlzs/baa+dWRgpGAv8EAljU\n7ZVXXjEdO3asi4Uw7LMWizjmeeE0+9vAoihYuAN6aj0sQoSFCD/99FOD922eF/mzfN9++21d\niHKdddapi0V9rK6N76u8Lkhp2WL7wgsvGOje0BPrITz55JOq26y11lq5FxeLvT799NO6gEv3\n7t1zLy8Wnfnvf/+ri77KOhW5lxeLfb3++uu62CIWhmQggSgBGiijNLhPAiRAAiRAAiRAAiRA\nAiRAAiRAAiRAAiRAAiRQUwL5HIpVUwQsjARIgARIgARIgARIgARIgARIgARIgARIgARIoLEI\n0EDZWORZLgmQAAmQAAmQAAmQAAmQAAmQAAmQAAmQAAmQgJnjLAnk0HgE4A9v5MiR6gcR/mQW\nWGCBAmHgH2fUqFEG6eAfZ6655iqIhy9K+P1744039NoWLVpoPHzXPf/88+bjjz9u8Ae/Kq1a\ntSrIJ+ngr7/+Uv9to0ePVl8yiy++uGnWrFl4yZ9//qnlw7fI77//rv4vwsi/d1z1gN8icMD1\nbdu2Lcv3yy+//GKeeeYZrTdkateuXYEYpVjZRK56wBfUY489pnWdb775zEILLWQvTbWttM1t\nYc8++6z54YcfUtfTXp+0dbU5rnW1KdKA6a233qo+Ruaee26cKgiu+ILERQ5cbe5qU5vll19+\nafD7Xn755e2pcOtqrzBhwo4rD9dv02Zdqs3hgwi+aRGPUI4vrVq1OeT77rvvzJ133ql+v9L6\nVK12m3/00UcGfqiiz074f23fvj1E9w7VbnO014svvqg+krCPNk/rM6uabZ7lO8gbOhOSQI4J\nuO431/sqKR4+dt98882C55Z9hkEXiuuOPpgqfdYmyWvLz0L3s3m55HW9Z13yZqUDZiWvzaeU\n/uKqj73ed1vtd5qVo1R9bLzv1iWvjw6LskrpXa7fm6+cNl215bW/X/jdx7di/HvTyuGzdT3L\nkIcPX/xGk74RkE8l+iKuR3DJ63uvlJI3K73x/6WtvrwoBzLDh/wXX3yh35HlvCOsvK57wZdv\nsXu/Gu82Kze3+SVAA2Ujts3pp59urrjiCjP//POrE/Qbb7xRnaDDAIiAhzbSwBj20ksvmQcf\nfNBsuOGGoaPpTz75xOy22266qAIWpbn88sv1+sUWW8xMmDDBDBkyRB3Qwgkt/l5++WU1wiB+\nhRVW8Ko5Xgx77LGHOt7Fog3Dhw9XQ+Imm2xiYHDCQ+fQQw81Dz/8sBrsbrvtNjViRh0gu+rx\n73//21x66aVaz0ceecTcfvvtZt1110318nz00UfNkUceaaZNm6Z/119/vb7U7CIOSawAwlUP\nXH/IIYeY1157TeuNdps5c6ZZbbXVvDjaRJW2uc0HHyInnniiOqGPLkLkqqe9PmnranNc62pT\nmz84Ie0222xTtD1d8TafYltXm7va1OYJx9LHHHOMmTRpktl6663tad262qsgcYkDVx6+bVaq\nzaF07rrrrtrJAQMVfvu4D1ZfffUSEjU8Xcs2D4LAnHHGGWbEiBFmr732MnPMMUdDgUqcqUWb\n4zd51113GSxYg/sdf+C5wQYblJCq4elqtzmct5900knaebXgggvqMxMGdvx+fY2U1W7zrN5B\nDenyDAnUHwHX/eZ6X7ni8cy6//77C3Q+dNii43jbbbdVPTMNtUqftS55IUsWup+tk0te13vW\nJW9WOmBW8tp8SukvrvrY63231X6nWTlK1cfG+25d8vrqsKX0LtfvzVdOm67a8mJhu6OOOspA\n/4Jh6rrrrtOFItN2vEJe17MMaXz5ur4BKtEXIQeCS94090opebPQG/9f2trIi2/5s88+Wxcs\ngo4L+wG+l1u3bm3F8N667gVfvqXu/azfbd4VY8LGJSA3P0MjEJAerGC99dYLpPc4LF0GswZi\naNBjWaUvEGNkICMj9Vg+SIMDDjgguOqqq8L0Bx10UHDxxRcH0jOk52666aZg5513Do/DhH/v\nXHjhhYEYNINff/01HlXyGOUddthhYbz0kgSbbbZZcO211+q5O+64Q2WWB4sei5EnEONigPoh\nuOrx4YcfBrK6XyCrVGp61GWXXXYJLrjgAj32+ScPP5Xh7rvvDpOLYq75In8EFytXPfr16xfs\ns88+gRiCNT+0m6yaF8gIJj32+ZdFm+N3MHToUP1tiMEkEINwQdGuehYkLnHganNXmyLbr7/+\nOjjuuOOCjTbaSNtBesUKSnPFFyQucuDT5q42RbZi+A+23357lRP3VzS42iuattS+Tx6uNnO1\nuXREBAcffHAogqzip8zB2DfUos2tLLhP8QzBfS9Gfnvaua1Fm0OIPffcM7jnnnuc8pRKUIs2\nl46coG/fvsG3336rYuC5hGMZ4V1KrAbna9nmtvBy3kH2Wm5JoJ4JuO431/vKFR9nM2PGjGCn\nnXYKLrvssniU8ziLZ61L3ix0P1sRH3ld71mXvFnogFnKi7yS9BdXfawsPttavNNc9fGR06Zx\nyeujwybpXT6/NyuLz7ba8srMNH0WDBs2LBRHOgcK9MYwwmPH9Szz4ev7DVCuvhithkten3vF\nJW+lemMt5ZWZd/rNE9UX8Xs4+eSTo2J47fvcCz58k55lcUEqebfF8+JxfgnQB2Uj2YcxZVAM\nImaRRRYJJejevbuOPpSfi452RM/WKqusovGYUi0f9TocGye+//57HSWJkWl2xIx8oOpU8PHj\nx4d52h1MWcQoR4xcat68uT3t3GLU5N577x2mm2eeecyyyy6r5eAkppH36dNHRz/iuGPHjjo6\nE8PGETBqM6keogRoOssBdcEITzGi6nmff5jm3LNnT5XDpgdLBEyZ8GGVVA9MDcBoKjtqFPlC\nXrQNpnz7hkrbHOVgGjxGnmHkgR1pa8v3qadNm7R1tbmrTZH3wIEDtadWDM1Fi3LFF70octLV\n5kia1KaIx3SvU045xWy++eY6EhnnosHVXtG0pfZdefi0WVKbo1wxlJsTTjghFMG6HkDZvqEW\nbQ5ZMArl5ptvNtLp4StamK4WbY5R0ZiW1LVr17DctDu1aHOMlNpxxx1NmzZtVDyMZscI/OjI\ndZfctWpzK0e57yB7PbckUM8EXPeb633lio+zufLKK3W2jXRexaOcx1k8a13yZqH72Yq45PV5\nzybJm5UOmKW8Lv0lqT5WDt9tLd5prvr4yop0Lnl9dNgkvcv1e0sjay3kFSOSzjCLzhCCnoh6\nlBNczzIfvj7fAJXoi9F6ueT1uVeS5M1Cb6ylvPht4zsb3+42SAeMOfbYY+2h99bnXnDxTXvv\nV/Ju864YEzY6gf85Emx0UZqWAGuuuabBXzRgKs5yyy2nBsfJkyc38OUIQx+GqkNZkt4cvTQ6\nPB9Ds+FDAr6/or708PDEwxXTQGFcTBOixklch4cR/F0eccQRmg3kjMqAkziGDAiuesAQsPLK\nK5vBgwerfJh6AGMgDHC+AR/p8QcrWGLqKPL3YeWqB2SZc845C0QCVxhAfUOlbQN0Yx8AACHA\nSURBVA5ffb169TJbbLGF+gDFQzoafOoZTV9q36fNO3ToUHB59LcJOTH9FD7xpCe1IJ09cMXb\ndKW2rjbHda42hbFdemd1SoOMPm5QlKu9GlxQ5IQrD582S2pzFGmn+OP3iOlIMADi3DLLLFNE\nouKnatHm+CDFlBJ8MMd/P8WlKjxbizaHQoznK1xqXHLJJQZTTuBWY7/99lPXDoUSFT+qRZvD\niIp7Dm0N9x342JAefLPUUksVF6rI2Vq0uS22kneQzYNbEqhnAj73m0uXSoqPsoGOBpdAN9xw\nQ1m+J7N41rrev1nofrbOLnl93rMueVFWpTpglvK69Bef+lh5XNtavNNc9XHJGI13yQs2cR0k\nrsMm6V2u31tUFp/9asuLQSkyY09FgbEeBkR0cmKQTDnB51nm4uv6BqhUX4zWy0de17M1Sd4s\n9MZayvv555/rYKIXXnhBB73ARdzGG2+s35ZROXz2fe4F17Mozb1f6bvNp05Mkw8CHEGZj3ZQ\nn2fjxo0zRx99tEoEhQq+xaIBDo3x8Qx/aLjhMWomvvAI0sRHTj399NNq2MSIm0oCFrCRaej6\nYINPIyzMAYNpXE4c2545Vz1gzIJvR5nioHnDfx4elDBalhvgGP6aa65R35kwkrlYueoBGWHw\nwQhUy/bdd99VQyocA5cb4FcjTZujHBihowsURct21TOa1nc/3ua4ztWmSONapMUVjzzShHib\nu9oUeYNjGn8r8fZKI59NG8/Dp82S2tzmi+1DDz2kPmvx2xQ3CQa/23JCtdocPo8w8jjai1+O\nfPaaarS5TDvU7GFQQycMnkX40JepybbY1Nus2xzPHIwwh3ESBmmZKq/3JJ6jk8SPajmhWm1u\nZcnqHWTz45YE6plA/H5zva9c8XEWeOasuuqqqTqp4nlEj9M+a33krYbuZ2WOy+t6z7rkrZYO\nWK68uC5Jf3HVx5Zb7jbrd5qrPuXKaa+Ly+ujw/rqXSgj/nuz5Za7raa855xzjhk0aJDOvoCv\n/0pD/FmG/Hz4ur4BstYXbT3j8vreK0nyVkNvrKa84hpI/ZCK+w8dFIUObgwSwvoPlYb4veDD\nN+lZFpcn63dbPH8e54cAR1DmoC3Ep6A+GM4777xwaiF6anFjR4M9xnD1YvFIi6H8iI8GGNYw\nDTSNMSZ6PfanT59uxD+FbsXvpZaPqehQ3Kxc9hocY2EfhGJy2vSQE9P+MPoRvVMYbo4Rdxg9\niZFWeJGmDVjtC3mJ78O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vLo3LlzPJlx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\nEcyen3cT/JUAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_over_time(col= 'grade')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.4.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}