Exercises_Auto_Sales.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Arules and Pattern Mining\n",
    "\n",
    "The **`arlues`** package that is being used for mining association rules needs data to be of type factor. Therefore it takes lots of pre processing converting the data to right type for association rule mining. \n",
    "\n",
    "This notebook uses auto sales data for resale of cars. This could be a regression problem. The two fields of data **`dateCreated`** and **`lastSeen`** could be indicators of when a car came into the store and when it left the store (or sold). If we take the difference in days then we can try to predict number of days it took for the car to be re sold. \n",
    "\n",
    "Here lets try to find if there are patterns of features that occur frequently. Read the data from `/dsa/data/DSA-8630/autos.csv`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Read the auto_sales data into a variable called auto_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "'LC_CTYPE=C;LC_NUMERIC=C;LC_TIME=C;LC_COLLATE=C;LC_MONETARY=C;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C'"
      ],
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       "'LC\\_CTYPE=C;LC\\_NUMERIC=C;LC\\_TIME=C;LC\\_COLLATE=C;LC\\_MONETARY=C;LC\\_MESSAGES=en\\_US.UTF-8;LC\\_PAPER=en\\_US.UTF-8;LC\\_NAME=C;LC\\_ADDRESS=C;LC\\_TELEPHONE=C;LC\\_MEASUREMENT=en\\_US.UTF-8;LC\\_IDENTIFICATION=C'"
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       "'LC_CTYPE=C;LC_NUMERIC=C;LC_TIME=C;LC_COLLATE=C;LC_MONETARY=C;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C'"
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       "[1] \"LC_CTYPE=C;LC_NUMERIC=C;LC_TIME=C;LC_COLLATE=C;LC_MONETARY=C;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C\""
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   "source": [
    "Sys.setlocale(locale=\"C\")"
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  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: Matrix\n",
      "\n",
      "Attaching package: 'arules'\n",
      "\n",
      "The following objects are masked from 'package:base':\n",
      "\n",
      "    abbreviate, write\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>dateCrawled</th><th scope=col>name</th><th scope=col>seller</th><th scope=col>offerType</th><th scope=col>price</th><th scope=col>abtest</th><th scope=col>vehicleType</th><th scope=col>yearOfRegistration</th><th scope=col>gearbox</th><th scope=col>powerPS</th><th scope=col>model</th><th scope=col>kilometer</th><th scope=col>monthOfRegistration</th><th scope=col>fuelType</th><th scope=col>brand</th><th scope=col>notRepairedDamage</th><th scope=col>dateCreated</th><th scope=col>nrOfPictures</th><th scope=col>postalCode</th><th scope=col>lastSeen</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>2016-03-24 11:52:17                               </td><td>Golf_3_1.6                                        </td><td>privat                                            </td><td>Angebot                                           </td><td>  480                                             </td><td>test                                              </td><td>                                                  </td><td>1993                                              </td><td>manuell                                           </td><td>  0                                               </td><td>golf                                              </td><td>150000                                            </td><td> 0                                                </td><td>benzin                                            </td><td>volkswagen                                        </td><td>                                                  </td><td>2016-03-24 00:00:00                               </td><td>0                                                 </td><td>70435                                             </td><td>2016-04-07 03:16:57                               </td></tr>\n",
       "\t<tr><td>2016-03-24 10:58:45                               </td><td>A5_Sportback_2.7_Tdi                              </td><td>privat                                            </td><td>Angebot                                           </td><td>18300                                             </td><td>test                                              </td><td>coupe                                             </td><td>2011                                              </td><td>manuell                                           </td><td>190                                               </td><td>                                                  </td><td>125000                                            </td><td> 5                                                </td><td>diesel                                            </td><td>audi                                              </td><td>ja                                                </td><td>2016-03-24 00:00:00                               </td><td>0                                                 </td><td>66954                                             </td><td>2016-04-07 01:46:50                               </td></tr>\n",
       "\t<tr><td>2016-03-14 12:52:21                               </td><td>Jeep_Grand_Cherokee_Overland                      </td><td>privat                                            </td><td>Angebot                                           </td><td> 9800                                             </td><td>test                                              </td><td>suv                                               </td><td>2004                                              </td><td>automatik                                         </td><td>163                                               </td><td>grand                                             </td><td>125000                                            </td><td> 8                                                </td><td>diesel                                            </td><td>jeep                                              </td><td>                                                  </td><td>2016-03-14 00:00:00                               </td><td>0                                                 </td><td>90480                                             </td><td>2016-04-05 12:47:46                               </td></tr>\n",
       "\t<tr><td>2016-03-17 16:54:04                               </td><td>GOLF_4_1_4__3T<dc>RER                             </td><td>privat                                            </td><td>Angebot                                           </td><td> 1500                                             </td><td>test                                              </td><td>kleinwagen                                        </td><td>2001                                              </td><td>manuell                                           </td><td> 75                                               </td><td>golf                                              </td><td>150000                                            </td><td> 6                                                </td><td>benzin                                            </td><td>volkswagen                                        </td><td>nein                                              </td><td>2016-03-17 00:00:00                               </td><td>0                                                 </td><td>91074                                             </td><td>2016-03-17 17:40:17                               </td></tr>\n",
       "\t<tr><td>2016-03-31 17:25:20                               </td><td>Skoda_Fabia_1.4_TDI_PD_Classic                    </td><td>privat                                            </td><td>Angebot                                           </td><td> 3600                                             </td><td>test                                              </td><td>kleinwagen                                        </td><td>2008                                              </td><td>manuell                                           </td><td> 69                                               </td><td>fabia                                             </td><td> 90000                                            </td><td> 7                                                </td><td>diesel                                            </td><td>skoda                                             </td><td>nein                                              </td><td>2016-03-31 00:00:00                               </td><td>0                                                 </td><td>60437                                             </td><td>2016-04-06 10:17:21                               </td></tr>\n",
       "\t<tr><td>2016-04-04 17:36:23                               </td><td>BMW_316i___e36_Limousine___Bastlerfahrzeug__Export</td><td>privat                                            </td><td>Angebot                                           </td><td>  650                                             </td><td>test                                              </td><td>limousine                                         </td><td>1995                                              </td><td>manuell                                           </td><td>102                                               </td><td>3er                                               </td><td>150000                                            </td><td>10                                                </td><td>benzin                                            </td><td>bmw                                               </td><td>ja                                                </td><td>2016-04-04 00:00:00                               </td><td>0                                                 </td><td>33775                                             </td><td>2016-04-06 19:17:07                               </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllll}\n",
       " dateCrawled & name & seller & offerType & price & abtest & vehicleType & yearOfRegistration & gearbox & powerPS & model & kilometer & monthOfRegistration & fuelType & brand & notRepairedDamage & dateCreated & nrOfPictures & postalCode & lastSeen\\\\\n",
       "\\hline\n",
       "\t 2016-03-24 11:52:17                                    & Golf\\_3\\_1.6                                         & privat                                                 & Angebot                                                &   480                                                  & test                                                   &                                                        & 1993                                                   & manuell                                                &   0                                                    & golf                                                   & 150000                                                 &  0                                                     & benzin                                                 & volkswagen                                             &                                                        & 2016-03-24 00:00:00                                    & 0                                                      & 70435                                                  & 2016-04-07 03:16:57                                   \\\\\n",
       "\t 2016-03-24 10:58:45                                      & A5\\_Sportback\\_2.7\\_Tdi                               & privat                                                   & Angebot                                                  & 18300                                                    & test                                                     & coupe                                                    & 2011                                                     & manuell                                                  & 190                                                      &                                                          & 125000                                                   &  5                                                       & diesel                                                   & audi                                                     & ja                                                       & 2016-03-24 00:00:00                                      & 0                                                        & 66954                                                    & 2016-04-07 01:46:50                                     \\\\\n",
       "\t 2016-03-14 12:52:21                                      & Jeep\\_Grand\\_Cherokee\\_Overland                       & privat                                                   & Angebot                                                  &  9800                                                    & test                                                     & suv                                                      & 2004                                                     & automatik                                                & 163                                                      & grand                                                    & 125000                                                   &  8                                                       & diesel                                                   & jeep                                                     &                                                          & 2016-03-14 00:00:00                                      & 0                                                        & 90480                                                    & 2016-04-05 12:47:46                                     \\\\\n",
       "\t 2016-03-17 16:54:04                                          & GOLF\\_4\\_1\\_4\\_\\_3T<dc>RER                              & privat                                                       & Angebot                                                      &  1500                                                        & test                                                         & kleinwagen                                                   & 2001                                                         & manuell                                                      &  75                                                          & golf                                                         & 150000                                                       &  6                                                           & benzin                                                       & volkswagen                                                   & nein                                                         & 2016-03-17 00:00:00                                          & 0                                                            & 91074                                                        & 2016-03-17 17:40:17                                         \\\\\n",
       "\t 2016-03-31 17:25:20                                          & Skoda\\_Fabia\\_1.4\\_TDI\\_PD\\_Classic                     & privat                                                       & Angebot                                                      &  3600                                                        & test                                                         & kleinwagen                                                   & 2008                                                         & manuell                                                      &  69                                                          & fabia                                                        &  90000                                                       &  7                                                           & diesel                                                       & skoda                                                        & nein                                                         & 2016-03-31 00:00:00                                          & 0                                                            & 60437                                                        & 2016-04-06 10:17:21                                         \\\\\n",
       "\t 2016-04-04 17:36:23                                                    & BMW\\_316i\\_\\_\\_e36\\_Limousine\\_\\_\\_Bastlerfahrzeug\\_\\_Export & privat                                                                 & Angebot                                                                &   650                                                                  & test                                                                   & limousine                                                              & 1995                                                                   & manuell                                                                & 102                                                                    & 3er                                                                    & 150000                                                                 & 10                                                                     & benzin                                                                 & bmw                                                                    & ja                                                                     & 2016-04-04 00:00:00                                                    & 0                                                                      & 33775                                                                  & 2016-04-06 19:17:07                                                   \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "  dateCrawled         name                                               seller\n",
       "1 2016-03-24 11:52:17 Golf_3_1.6                                         privat\n",
       "2 2016-03-24 10:58:45 A5_Sportback_2.7_Tdi                               privat\n",
       "3 2016-03-14 12:52:21 Jeep_Grand_Cherokee_Overland                       privat\n",
       "4 2016-03-17 16:54:04 GOLF_4_1_4__3T\\334RER                              privat\n",
       "5 2016-03-31 17:25:20 Skoda_Fabia_1.4_TDI_PD_Classic                     privat\n",
       "6 2016-04-04 17:36:23 BMW_316i___e36_Limousine___Bastlerfahrzeug__Export privat\n",
       "  offerType price abtest vehicleType yearOfRegistration gearbox   powerPS model\n",
       "1 Angebot     480 test               1993               manuell     0     golf \n",
       "2 Angebot   18300 test   coupe       2011               manuell   190          \n",
       "3 Angebot    9800 test   suv         2004               automatik 163     grand\n",
       "4 Angebot    1500 test   kleinwagen  2001               manuell    75     golf \n",
       "5 Angebot    3600 test   kleinwagen  2008               manuell    69     fabia\n",
       "6 Angebot     650 test   limousine   1995               manuell   102     3er  \n",
       "  kilometer monthOfRegistration fuelType brand      notRepairedDamage\n",
       "1 150000     0                  benzin   volkswagen                  \n",
       "2 125000     5                  diesel   audi       ja               \n",
       "3 125000     8                  diesel   jeep                        \n",
       "4 150000     6                  benzin   volkswagen nein             \n",
       "5  90000     7                  diesel   skoda      nein             \n",
       "6 150000    10                  benzin   bmw        ja               \n",
       "  dateCreated         nrOfPictures postalCode lastSeen           \n",
       "1 2016-03-24 00:00:00 0            70435      2016-04-07 03:16:57\n",
       "2 2016-03-24 00:00:00 0            66954      2016-04-07 01:46:50\n",
       "3 2016-03-14 00:00:00 0            90480      2016-04-05 12:47:46\n",
       "4 2016-03-17 00:00:00 0            91074      2016-03-17 17:40:17\n",
       "5 2016-03-31 00:00:00 0            60437      2016-04-06 10:17:21\n",
       "6 2016-04-04 00:00:00 0            33775      2016-04-06 19:17:07"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code here..\n",
    "library(\"arules\")\n",
    "auto_sales = read.csv('/dsa/data/DSA-8630/autos.csv')\n",
    "head(auto_sales)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'dateCrawled'</li>\n",
       "\t<li>'name'</li>\n",
       "\t<li>'seller'</li>\n",
       "\t<li>'offerType'</li>\n",
       "\t<li>'price'</li>\n",
       "\t<li>'abtest'</li>\n",
       "\t<li>'vehicleType'</li>\n",
       "\t<li>'yearOfRegistration'</li>\n",
       "\t<li>'gearbox'</li>\n",
       "\t<li>'powerPS'</li>\n",
       "\t<li>'model'</li>\n",
       "\t<li>'kilometer'</li>\n",
       "\t<li>'monthOfRegistration'</li>\n",
       "\t<li>'fuelType'</li>\n",
       "\t<li>'brand'</li>\n",
       "\t<li>'notRepairedDamage'</li>\n",
       "\t<li>'dateCreated'</li>\n",
       "\t<li>'nrOfPictures'</li>\n",
       "\t<li>'postalCode'</li>\n",
       "\t<li>'lastSeen'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'dateCrawled'\n",
       "\\item 'name'\n",
       "\\item 'seller'\n",
       "\\item 'offerType'\n",
       "\\item 'price'\n",
       "\\item 'abtest'\n",
       "\\item 'vehicleType'\n",
       "\\item 'yearOfRegistration'\n",
       "\\item 'gearbox'\n",
       "\\item 'powerPS'\n",
       "\\item 'model'\n",
       "\\item 'kilometer'\n",
       "\\item 'monthOfRegistration'\n",
       "\\item 'fuelType'\n",
       "\\item 'brand'\n",
       "\\item 'notRepairedDamage'\n",
       "\\item 'dateCreated'\n",
       "\\item 'nrOfPictures'\n",
       "\\item 'postalCode'\n",
       "\\item 'lastSeen'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'dateCrawled'\n",
       "2. 'name'\n",
       "3. 'seller'\n",
       "4. 'offerType'\n",
       "5. 'price'\n",
       "6. 'abtest'\n",
       "7. 'vehicleType'\n",
       "8. 'yearOfRegistration'\n",
       "9. 'gearbox'\n",
       "10. 'powerPS'\n",
       "11. 'model'\n",
       "12. 'kilometer'\n",
       "13. 'monthOfRegistration'\n",
       "14. 'fuelType'\n",
       "15. 'brand'\n",
       "16. 'notRepairedDamage'\n",
       "17. 'dateCreated'\n",
       "18. 'nrOfPictures'\n",
       "19. 'postalCode'\n",
       "20. 'lastSeen'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"dateCrawled\"         \"name\"                \"seller\"             \n",
       " [4] \"offerType\"           \"price\"               \"abtest\"             \n",
       " [7] \"vehicleType\"         \"yearOfRegistration\"  \"gearbox\"            \n",
       "[10] \"powerPS\"             \"model\"               \"kilometer\"          \n",
       "[13] \"monthOfRegistration\" \"fuelType\"            \"brand\"              \n",
       "[16] \"notRepairedDamage\"   \"dateCreated\"         \"nrOfPictures\"       \n",
       "[19] \"postalCode\"          \"lastSeen\"           "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "              dateCrawled                      name               seller      \n",
       " 2016-03-08 15:50:29:     5   Ford_Fiesta        :   336   gewerblich:     2  \n",
       " 2016-03-20 16:50:22:     5   Volkswagen_Golf_1.4:   335   privat    :189347  \n",
       " 2016-03-26 10:51:07:     5   BMW_318i           :   334                      \n",
       " 2016-03-31 17:57:07:     5   Opel_Corsa         :   316                      \n",
       " 2016-04-02 14:50:21:     5   BMW_316i           :   258                      \n",
       " 2016-03-05 15:48:41:     4   BMW_320i           :   256                      \n",
       " (Other)            :189320   (Other)            :187514                      \n",
       "   offerType          price              abtest          vehicleType   \n",
       " Angebot:189341   Min.   :       0   control:91131   limousine :48701  \n",
       " Gesuch :     8   1st Qu.:    1150   test   :98218   kleinwagen:40759  \n",
       "                  Median :    2950                   kombi     :34498  \n",
       "                  Mean   :   10895                             :19437  \n",
       "                  3rd Qu.:    7200                   bus       :15532  \n",
       "                  Max.   :99999999                   cabrio    :11668  \n",
       "                                                     (Other)   :18754  \n",
       " yearOfRegistration      gearbox          powerPS            model       \n",
       " Min.   :1000                : 10395   Min.   :    0.0   golf   : 15286  \n",
       " 1st Qu.:1999       automatik: 39220   1st Qu.:   70.0   andere : 13453  \n",
       " Median :2003       manuell  :139734   Median :  105.0   3er    : 10528  \n",
       " Mean   :2005                          Mean   :  114.7          : 10398  \n",
       " 3rd Qu.:2008                          3rd Qu.:  150.0   polo   :  6714  \n",
       " Max.   :9999                          Max.   :19208.0   corsa  :  6415  \n",
       "                                                         (Other):126555  \n",
       "   kilometer      monthOfRegistration    fuelType                brand      \n",
       " Min.   :  5000   Min.   : 0.000      benzin :114106   volkswagen   :40687  \n",
       " 1st Qu.:125000   1st Qu.: 3.000      diesel : 54968   bmw          :20545  \n",
       " Median :150000   Median : 6.000             : 16936   opel         :20427  \n",
       " Mean   :125640   Mean   : 5.733      lpg    :  2732   mercedes_benz:17931  \n",
       " 3rd Qu.:150000   3rd Qu.: 9.000      cng    :   308   audi         :16676  \n",
       " Max.   :150000   Max.   :12.000      hybrid :   142   ford         :13093  \n",
       "                                      (Other):   157   (Other)      :59990  \n",
       " notRepairedDamage              dateCreated      nrOfPictures   postalCode   \n",
       "     : 36542       2016-04-03 00:00:00:  7392   Min.   :0     Min.   : 1067  \n",
       " ja  : 18410       2016-04-04 00:00:00:  7185   1st Qu.:0     1st Qu.:30559  \n",
       " nein:134397       2016-03-20 00:00:00:  6860   Median :0     Median :49661  \n",
       "                   2016-03-12 00:00:00:  6853   Mean   :0     Mean   :50892  \n",
       "                   2016-03-21 00:00:00:  6843   3rd Qu.:0     3rd Qu.:71577  \n",
       "                   2016-03-14 00:00:00:  6691   Max.   :0     Max.   :99998  \n",
       "                   (Other)            :147525                                \n",
       "                lastSeen     \n",
       " 2016-04-07 00:46:04:    14  \n",
       " 2016-04-06 04:17:47:    12  \n",
       " 2016-04-06 05:44:34:    12  \n",
       " 2016-04-06 08:15:55:    12  \n",
       " 2016-04-06 09:46:11:    12  \n",
       " 2016-04-06 09:46:51:    12  \n",
       " (Other)            :189275  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t189349 obs. of  20 variables:\n",
      " $ dateCrawled        : Factor w/ 164590 levels \"2016-03-05 14:06:22\",..: 96234 96080 44613 62122 135465 158918 142369 82743 161561 60299 ...\n",
      " $ name               : Factor w/ 128113 levels \"!!!!!!!!!!!!!!Renault_Clio_5_Tuerig_Servolenkung_!!!!!!!!!!!!!!!!!\",..: 43061 2167 49293 41673 93697 14869 79671 103410 34778 104506 ...\n",
      " $ seller             : Factor w/ 2 levels \"gewerblich\",\"privat\": 2 2 2 2 2 2 2 2 2 2 ...\n",
      " $ offerType          : Factor w/ 2 levels \"Angebot\",\"Gesuch\": 1 1 1 1 1 1 1 1 1 1 ...\n",
      " $ price              : int  480 18300 9800 1500 3600 650 2200 0 14500 999 ...\n",
      " $ abtest             : Factor w/ 2 levels \"control\",\"test\": 2 2 2 2 2 2 2 2 1 2 ...\n",
      " $ vehicleType        : Factor w/ 9 levels \"\",\"andere\",\"bus\",..: 1 5 9 6 6 8 4 8 3 6 ...\n",
      " $ yearOfRegistration : int  1993 2011 2004 2001 2008 1995 2004 1980 2014 1998 ...\n",
      " $ gearbox            : Factor w/ 3 levels \"\",\"automatik\",..: 3 3 2 3 3 3 3 3 3 3 ...\n",
      " $ powerPS            : int  0 190 163 75 69 102 109 50 125 101 ...\n",
      " $ model              : Factor w/ 251 levels \"\",\"100\",\"145\",..: 119 1 120 119 104 13 10 42 63 119 ...\n",
      " $ kilometer          : int  150000 125000 125000 150000 90000 150000 150000 40000 30000 150000 ...\n",
      " $ monthOfRegistration: int  0 5 8 6 7 10 8 7 8 0 ...\n",
      " $ fuelType           : Factor w/ 8 levels \"\",\"andere\",\"benzin\",..: 3 5 5 3 5 3 3 3 3 1 ...\n",
      " $ brand              : Factor w/ 40 levels \"alfa_romeo\",\"audi\",..: 39 2 15 39 32 3 26 39 11 39 ...\n",
      " $ notRepairedDamage  : Factor w/ 3 levels \"\",\"ja\",\"nein\": 1 2 1 3 3 2 3 3 1 1 ...\n",
      " $ dateCreated        : Factor w/ 97 levels \"2014-03-10 00:00:00\",..: 83 83 73 76 90 94 91 80 94 76 ...\n",
      " $ nrOfPictures       : int  0 0 0 0 0 0 0 0 0 0 ...\n",
      " $ postalCode         : int  70435 66954 90480 91074 60437 33775 67112 19348 94505 27472 ...\n",
      " $ lastSeen           : Factor w/ 111190 levels \"2016-03-05 14:15:08\",..: 107390 106918 92424 25353 100813 104198 94797 50176 88971 71117 ...\n"
     ]
    }
   ],
   "source": [
    "names(auto_sales)\n",
    "summary(auto_sales)\n",
    "str(auto_sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Trim both the leading and trailing white spaces from name column in auto_sales"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>dateCrawled</th><th scope=col>name</th><th scope=col>seller</th><th scope=col>offerType</th><th scope=col>price</th><th scope=col>abtest</th><th scope=col>vehicleType</th><th scope=col>yearOfRegistration</th><th scope=col>gearbox</th><th scope=col>powerPS</th><th scope=col>model</th><th scope=col>kilometer</th><th scope=col>monthOfRegistration</th><th scope=col>fuelType</th><th scope=col>brand</th><th scope=col>notRepairedDamage</th><th scope=col>dateCreated</th><th scope=col>nrOfPictures</th><th scope=col>postalCode</th><th scope=col>lastSeen</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>2016-03-24 11:52:17                               </td><td>Golf_3_1.6                                        </td><td>privat                                            </td><td>Angebot                                           </td><td>  480                                             </td><td>test                                              </td><td>                                                  </td><td>1993                                              </td><td>manuell                                           </td><td>  0                                               </td><td>golf                                              </td><td>150000                                            </td><td> 0                                                </td><td>benzin                                            </td><td>volkswagen                                        </td><td>                                                  </td><td>2016-03-24 00:00:00                               </td><td>0                                                 </td><td>70435                                             </td><td>2016-04-07 03:16:57                               </td></tr>\n",
       "\t<tr><td>2016-03-24 10:58:45                               </td><td>A5_Sportback_2.7_Tdi                              </td><td>privat                                            </td><td>Angebot                                           </td><td>18300                                             </td><td>test                                              </td><td>coupe                                             </td><td>2011                                              </td><td>manuell                                           </td><td>190                                               </td><td>                                                  </td><td>125000                                            </td><td> 5                                                </td><td>diesel                                            </td><td>audi                                              </td><td>ja                                                </td><td>2016-03-24 00:00:00                               </td><td>0                                                 </td><td>66954                                             </td><td>2016-04-07 01:46:50                               </td></tr>\n",
       "\t<tr><td>2016-03-14 12:52:21                               </td><td>Jeep_Grand_Cherokee_Overland                      </td><td>privat                                            </td><td>Angebot                                           </td><td> 9800                                             </td><td>test                                              </td><td>suv                                               </td><td>2004                                              </td><td>automatik                                         </td><td>163                                               </td><td>grand                                             </td><td>125000                                            </td><td> 8                                                </td><td>diesel                                            </td><td>jeep                                              </td><td>                                                  </td><td>2016-03-14 00:00:00                               </td><td>0                                                 </td><td>90480                                             </td><td>2016-04-05 12:47:46                               </td></tr>\n",
       "\t<tr><td>2016-03-17 16:54:04                               </td><td>GOLF_4_1_4__3T<dc>RER                             </td><td>privat                                            </td><td>Angebot                                           </td><td> 1500                                             </td><td>test                                              </td><td>kleinwagen                                        </td><td>2001                                              </td><td>manuell                                           </td><td> 75                                               </td><td>golf                                              </td><td>150000                                            </td><td> 6                                                </td><td>benzin                                            </td><td>volkswagen                                        </td><td>nein                                              </td><td>2016-03-17 00:00:00                               </td><td>0                                                 </td><td>91074                                             </td><td>2016-03-17 17:40:17                               </td></tr>\n",
       "\t<tr><td>2016-03-31 17:25:20                               </td><td>Skoda_Fabia_1.4_TDI_PD_Classic                    </td><td>privat                                            </td><td>Angebot                                           </td><td> 3600                                             </td><td>test                                              </td><td>kleinwagen                                        </td><td>2008                                              </td><td>manuell                                           </td><td> 69                                               </td><td>fabia                                             </td><td> 90000                                            </td><td> 7                                                </td><td>diesel                                            </td><td>skoda                                             </td><td>nein                                              </td><td>2016-03-31 00:00:00                               </td><td>0                                                 </td><td>60437                                             </td><td>2016-04-06 10:17:21                               </td></tr>\n",
       "\t<tr><td>2016-04-04 17:36:23                               </td><td>BMW_316i___e36_Limousine___Bastlerfahrzeug__Export</td><td>privat                                            </td><td>Angebot                                           </td><td>  650                                             </td><td>test                                              </td><td>limousine                                         </td><td>1995                                              </td><td>manuell                                           </td><td>102                                               </td><td>3er                                               </td><td>150000                                            </td><td>10                                                </td><td>benzin                                            </td><td>bmw                                               </td><td>ja                                                </td><td>2016-04-04 00:00:00                               </td><td>0                                                 </td><td>33775                                             </td><td>2016-04-06 19:17:07                               </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllll}\n",
       " dateCrawled & name & seller & offerType & price & abtest & vehicleType & yearOfRegistration & gearbox & powerPS & model & kilometer & monthOfRegistration & fuelType & brand & notRepairedDamage & dateCreated & nrOfPictures & postalCode & lastSeen\\\\\n",
       "\\hline\n",
       "\t 2016-03-24 11:52:17                                    & Golf\\_3\\_1.6                                         & privat                                                 & Angebot                                                &   480                                                  & test                                                   &                                                        & 1993                                                   & manuell                                                &   0                                                    & golf                                                   & 150000                                                 &  0                                                     & benzin                                                 & volkswagen                                             &                                                        & 2016-03-24 00:00:00                                    & 0                                                      & 70435                                                  & 2016-04-07 03:16:57                                   \\\\\n",
       "\t 2016-03-24 10:58:45                                      & A5\\_Sportback\\_2.7\\_Tdi                               & privat                                                   & Angebot                                                  & 18300                                                    & test                                                     & coupe                                                    & 2011                                                     & manuell                                                  & 190                                                      &                                                          & 125000                                                   &  5                                                       & diesel                                                   & audi                                                     & ja                                                       & 2016-03-24 00:00:00                                      & 0                                                        & 66954                                                    & 2016-04-07 01:46:50                                     \\\\\n",
       "\t 2016-03-14 12:52:21                                      & Jeep\\_Grand\\_Cherokee\\_Overland                       & privat                                                   & Angebot                                                  &  9800                                                    & test                                                     & suv                                                      & 2004                                                     & automatik                                                & 163                                                      & grand                                                    & 125000                                                   &  8                                                       & diesel                                                   & jeep                                                     &                                                          & 2016-03-14 00:00:00                                      & 0                                                        & 90480                                                    & 2016-04-05 12:47:46                                     \\\\\n",
       "\t 2016-03-17 16:54:04                                          & GOLF\\_4\\_1\\_4\\_\\_3T<dc>RER                              & privat                                                       & Angebot                                                      &  1500                                                        & test                                                         & kleinwagen                                                   & 2001                                                         & manuell                                                      &  75                                                          & golf                                                         & 150000                                                       &  6                                                           & benzin                                                       & volkswagen                                                   & nein                                                         & 2016-03-17 00:00:00                                          & 0                                                            & 91074                                                        & 2016-03-17 17:40:17                                         \\\\\n",
       "\t 2016-03-31 17:25:20                                          & Skoda\\_Fabia\\_1.4\\_TDI\\_PD\\_Classic                     & privat                                                       & Angebot                                                      &  3600                                                        & test                                                         & kleinwagen                                                   & 2008                                                         & manuell                                                      &  69                                                          & fabia                                                        &  90000                                                       &  7                                                           & diesel                                                       & skoda                                                        & nein                                                         & 2016-03-31 00:00:00                                          & 0                                                            & 60437                                                        & 2016-04-06 10:17:21                                         \\\\\n",
       "\t 2016-04-04 17:36:23                                                    & BMW\\_316i\\_\\_\\_e36\\_Limousine\\_\\_\\_Bastlerfahrzeug\\_\\_Export & privat                                                                 & Angebot                                                                &   650                                                                  & test                                                                   & limousine                                                              & 1995                                                                   & manuell                                                                & 102                                                                    & 3er                                                                    & 150000                                                                 & 10                                                                     & benzin                                                                 & bmw                                                                    & ja                                                                     & 2016-04-04 00:00:00                                                    & 0                                                                      & 33775                                                                  & 2016-04-06 19:17:07                                                   \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "  dateCrawled         name                                               seller\n",
       "1 2016-03-24 11:52:17 Golf_3_1.6                                         privat\n",
       "2 2016-03-24 10:58:45 A5_Sportback_2.7_Tdi                               privat\n",
       "3 2016-03-14 12:52:21 Jeep_Grand_Cherokee_Overland                       privat\n",
       "4 2016-03-17 16:54:04 GOLF_4_1_4__3T\\334RER                              privat\n",
       "5 2016-03-31 17:25:20 Skoda_Fabia_1.4_TDI_PD_Classic                     privat\n",
       "6 2016-04-04 17:36:23 BMW_316i___e36_Limousine___Bastlerfahrzeug__Export privat\n",
       "  offerType price abtest vehicleType yearOfRegistration gearbox   powerPS model\n",
       "1 Angebot     480 test               1993               manuell     0     golf \n",
       "2 Angebot   18300 test   coupe       2011               manuell   190          \n",
       "3 Angebot    9800 test   suv         2004               automatik 163     grand\n",
       "4 Angebot    1500 test   kleinwagen  2001               manuell    75     golf \n",
       "5 Angebot    3600 test   kleinwagen  2008               manuell    69     fabia\n",
       "6 Angebot     650 test   limousine   1995               manuell   102     3er  \n",
       "  kilometer monthOfRegistration fuelType brand      notRepairedDamage\n",
       "1 150000     0                  benzin   volkswagen                  \n",
       "2 125000     5                  diesel   audi       ja               \n",
       "3 125000     8                  diesel   jeep                        \n",
       "4 150000     6                  benzin   volkswagen nein             \n",
       "5  90000     7                  diesel   skoda      nein             \n",
       "6 150000    10                  benzin   bmw        ja               \n",
       "  dateCreated         nrOfPictures postalCode lastSeen           \n",
       "1 2016-03-24 00:00:00 0            70435      2016-04-07 03:16:57\n",
       "2 2016-03-24 00:00:00 0            66954      2016-04-07 01:46:50\n",
       "3 2016-03-14 00:00:00 0            90480      2016-04-05 12:47:46\n",
       "4 2016-03-17 00:00:00 0            91074      2016-03-17 17:40:17\n",
       "5 2016-03-31 00:00:00 0            60437      2016-04-06 10:17:21\n",
       "6 2016-04-04 00:00:00 0            33775      2016-04-06 19:17:07"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "auto_sales$name <- trimws(auto_sales$name) \n",
    "head(auto_sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Replace the underscores between the words in name column with white spaces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>dateCrawled</th><th scope=col>name</th><th scope=col>seller</th><th scope=col>offerType</th><th scope=col>price</th><th scope=col>abtest</th><th scope=col>vehicleType</th><th scope=col>yearOfRegistration</th><th scope=col>gearbox</th><th scope=col>powerPS</th><th scope=col>model</th><th scope=col>kilometer</th><th scope=col>monthOfRegistration</th><th scope=col>fuelType</th><th scope=col>brand</th><th scope=col>notRepairedDamage</th><th scope=col>dateCreated</th><th scope=col>nrOfPictures</th><th scope=col>postalCode</th><th scope=col>lastSeen</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><td>2016-03-24 11:52:17                               </td><td>Golf 3 1.6                                        </td><td>privat                                            </td><td>Angebot                                           </td><td>  480                                             </td><td>test                                              </td><td>                                                  </td><td>1993                                              </td><td>manuell                                           </td><td>  0                                               </td><td>golf                                              </td><td>150000                                            </td><td> 0                                                </td><td>benzin                                            </td><td>volkswagen                                        </td><td>                                                  </td><td>2016-03-24 00:00:00                               </td><td>0                                                 </td><td>70435                                             </td><td>2016-04-07 03:16:57                               </td></tr>\n",
       "\t<tr><td>2016-03-24 10:58:45                               </td><td>A5 Sportback 2.7 Tdi                              </td><td>privat                                            </td><td>Angebot                                           </td><td>18300                                             </td><td>test                                              </td><td>coupe                                             </td><td>2011                                              </td><td>manuell                                           </td><td>190                                               </td><td>                                                  </td><td>125000                                            </td><td> 5                                                </td><td>diesel                                            </td><td>audi                                              </td><td>ja                                                </td><td>2016-03-24 00:00:00                               </td><td>0                                                 </td><td>66954                                             </td><td>2016-04-07 01:46:50                               </td></tr>\n",
       "\t<tr><td>2016-03-14 12:52:21                               </td><td>Jeep Grand Cherokee Overland                      </td><td>privat                                            </td><td>Angebot                                           </td><td> 9800                                             </td><td>test                                              </td><td>suv                                               </td><td>2004                                              </td><td>automatik                                         </td><td>163                                               </td><td>grand                                             </td><td>125000                                            </td><td> 8                                                </td><td>diesel                                            </td><td>jeep                                              </td><td>                                                  </td><td>2016-03-14 00:00:00                               </td><td>0                                                 </td><td>90480                                             </td><td>2016-04-05 12:47:46                               </td></tr>\n",
       "\t<tr><td>2016-03-17 16:54:04                               </td><td>GOLF 4 1 4  3T<dc>RER                             </td><td>privat                                            </td><td>Angebot                                           </td><td> 1500                                             </td><td>test                                              </td><td>kleinwagen                                        </td><td>2001                                              </td><td>manuell                                           </td><td> 75                                               </td><td>golf                                              </td><td>150000                                            </td><td> 6                                                </td><td>benzin                                            </td><td>volkswagen                                        </td><td>nein                                              </td><td>2016-03-17 00:00:00                               </td><td>0                                                 </td><td>91074                                             </td><td>2016-03-17 17:40:17                               </td></tr>\n",
       "\t<tr><td>2016-03-31 17:25:20                               </td><td>Skoda Fabia 1.4 TDI PD Classic                    </td><td>privat                                            </td><td>Angebot                                           </td><td> 3600                                             </td><td>test                                              </td><td>kleinwagen                                        </td><td>2008                                              </td><td>manuell                                           </td><td> 69                                               </td><td>fabia                                             </td><td> 90000                                            </td><td> 7                                                </td><td>diesel                                            </td><td>skoda                                             </td><td>nein                                              </td><td>2016-03-31 00:00:00                               </td><td>0                                                 </td><td>60437                                             </td><td>2016-04-06 10:17:21                               </td></tr>\n",
       "\t<tr><td>2016-04-04 17:36:23                               </td><td>BMW 316i   e36 Limousine   Bastlerfahrzeug  Export</td><td>privat                                            </td><td>Angebot                                           </td><td>  650                                             </td><td>test                                              </td><td>limousine                                         </td><td>1995                                              </td><td>manuell                                           </td><td>102                                               </td><td>3er                                               </td><td>150000                                            </td><td>10                                                </td><td>benzin                                            </td><td>bmw                                               </td><td>ja                                                </td><td>2016-04-04 00:00:00                               </td><td>0                                                 </td><td>33775                                             </td><td>2016-04-06 19:17:07                               </td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllll}\n",
       " dateCrawled & name & seller & offerType & price & abtest & vehicleType & yearOfRegistration & gearbox & powerPS & model & kilometer & monthOfRegistration & fuelType & brand & notRepairedDamage & dateCreated & nrOfPictures & postalCode & lastSeen\\\\\n",
       "\\hline\n",
       "\t 2016-03-24 11:52:17                                & Golf 3 1.6                                         & privat                                             & Angebot                                            &   480                                              & test                                               &                                                    & 1993                                               & manuell                                            &   0                                                & golf                                               & 150000                                             &  0                                                 & benzin                                             & volkswagen                                         &                                                    & 2016-03-24 00:00:00                                & 0                                                  & 70435                                              & 2016-04-07 03:16:57                               \\\\\n",
       "\t 2016-03-24 10:58:45                                & A5 Sportback 2.7 Tdi                               & privat                                             & Angebot                                            & 18300                                              & test                                               & coupe                                              & 2011                                               & manuell                                            & 190                                                &                                                    & 125000                                             &  5                                                 & diesel                                             & audi                                               & ja                                                 & 2016-03-24 00:00:00                                & 0                                                  & 66954                                              & 2016-04-07 01:46:50                               \\\\\n",
       "\t 2016-03-14 12:52:21                                & Jeep Grand Cherokee Overland                       & privat                                             & Angebot                                            &  9800                                              & test                                               & suv                                                & 2004                                               & automatik                                          & 163                                                & grand                                              & 125000                                             &  8                                                 & diesel                                             & jeep                                               &                                                    & 2016-03-14 00:00:00                                & 0                                                  & 90480                                              & 2016-04-05 12:47:46                               \\\\\n",
       "\t 2016-03-17 16:54:04                                & GOLF 4 1 4  3T<dc>RER                              & privat                                             & Angebot                                            &  1500                                              & test                                               & kleinwagen                                         & 2001                                               & manuell                                            &  75                                                & golf                                               & 150000                                             &  6                                                 & benzin                                             & volkswagen                                         & nein                                               & 2016-03-17 00:00:00                                & 0                                                  & 91074                                              & 2016-03-17 17:40:17                               \\\\\n",
       "\t 2016-03-31 17:25:20                                & Skoda Fabia 1.4 TDI PD Classic                     & privat                                             & Angebot                                            &  3600                                              & test                                               & kleinwagen                                         & 2008                                               & manuell                                            &  69                                                & fabia                                              &  90000                                             &  7                                                 & diesel                                             & skoda                                              & nein                                               & 2016-03-31 00:00:00                                & 0                                                  & 60437                                              & 2016-04-06 10:17:21                               \\\\\n",
       "\t 2016-04-04 17:36:23                                & BMW 316i   e36 Limousine   Bastlerfahrzeug  Export & privat                                             & Angebot                                            &   650                                              & test                                               & limousine                                          & 1995                                               & manuell                                            & 102                                                & 3er                                                & 150000                                             & 10                                                 & benzin                                             & bmw                                                & ja                                                 & 2016-04-04 00:00:00                                & 0                                                  & 33775                                              & 2016-04-06 19:17:07                               \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "  dateCrawled         name                                               seller\n",
       "1 2016-03-24 11:52:17 Golf 3 1.6                                         privat\n",
       "2 2016-03-24 10:58:45 A5 Sportback 2.7 Tdi                               privat\n",
       "3 2016-03-14 12:52:21 Jeep Grand Cherokee Overland                       privat\n",
       "4 2016-03-17 16:54:04 GOLF 4 1 4  3T\\334RER                              privat\n",
       "5 2016-03-31 17:25:20 Skoda Fabia 1.4 TDI PD Classic                     privat\n",
       "6 2016-04-04 17:36:23 BMW 316i   e36 Limousine   Bastlerfahrzeug  Export privat\n",
       "  offerType price abtest vehicleType yearOfRegistration gearbox   powerPS model\n",
       "1 Angebot     480 test               1993               manuell     0     golf \n",
       "2 Angebot   18300 test   coupe       2011               manuell   190          \n",
       "3 Angebot    9800 test   suv         2004               automatik 163     grand\n",
       "4 Angebot    1500 test   kleinwagen  2001               manuell    75     golf \n",
       "5 Angebot    3600 test   kleinwagen  2008               manuell    69     fabia\n",
       "6 Angebot     650 test   limousine   1995               manuell   102     3er  \n",
       "  kilometer monthOfRegistration fuelType brand      notRepairedDamage\n",
       "1 150000     0                  benzin   volkswagen                  \n",
       "2 125000     5                  diesel   audi       ja               \n",
       "3 125000     8                  diesel   jeep                        \n",
       "4 150000     6                  benzin   volkswagen nein             \n",
       "5  90000     7                  diesel   skoda      nein             \n",
       "6 150000    10                  benzin   bmw        ja               \n",
       "  dateCreated         nrOfPictures postalCode lastSeen           \n",
       "1 2016-03-24 00:00:00 0            70435      2016-04-07 03:16:57\n",
       "2 2016-03-24 00:00:00 0            66954      2016-04-07 01:46:50\n",
       "3 2016-03-14 00:00:00 0            90480      2016-04-05 12:47:46\n",
       "4 2016-03-17 00:00:00 0            91074      2016-03-17 17:40:17\n",
       "5 2016-03-31 00:00:00 0            60437      2016-04-06 10:17:21\n",
       "6 2016-04-04 00:00:00 0            33775      2016-04-06 19:17:07"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "auto_sales$name <- chartr(\"_\", \" \", auto_sales$name)\n",
    "head(auto_sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets generate the days column by substracting the **lastSeen** and **dateCreated** columns. \n",
    "\n",
    "**Reference: **\n",
    "\n",
    "- [lubridate](https://www.r-statistics.com/2012/03/do-more-with-dates-and-times-in-r-with-lubridate-1-1-0/)\n",
    "- [Handling date-times in R](http://biostat.mc.vanderbilt.edu/wiki/pub/Main/ColeBeck/datestimes.pdf)\n",
    "\n",
    "\n",
    "You can work with dates data type in R using either built-in POSIXt library or external packages like chron package, lubridate package. There are two POSIXt types, POSIXct and POSIXlt. \"ct\" stands for calendar time, it stores the number of seconds since the origin. \"lt\", or local time, keeps the date as a list of time attributes (such as \"hour\" and \"mon\").\n",
    "\n",
    "In below piece of code, we are trying to substract two dates. You can directly substract the dates if there are in proper date format. So we are converting them in to Posixt class with a format and then converting them into date type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Attaching package: 'lubridate'\n",
      "\n",
      "The following object is masked from 'package:base':\n",
      "\n",
      "    date\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Import lubridate package that has cool functions to play with dates\n",
    "library(lubridate)\n",
    "\n",
    "auto_sales$days = as.Date(format(as.POSIXct((auto_sales$lastSeen) ,format = \"%Y-%m-%d %X\"))) - as.Date(format(as.POSIXct((auto_sales$dateCreated),format =\"%Y-%m-%d %X\")))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Time differences in days\n",
       "[1] 14 14 22  0  6  2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'dateCrawled'</li>\n",
       "\t<li>'name'</li>\n",
       "\t<li>'seller'</li>\n",
       "\t<li>'offerType'</li>\n",
       "\t<li>'price'</li>\n",
       "\t<li>'abtest'</li>\n",
       "\t<li>'vehicleType'</li>\n",
       "\t<li>'yearOfRegistration'</li>\n",
       "\t<li>'gearbox'</li>\n",
       "\t<li>'powerPS'</li>\n",
       "\t<li>'model'</li>\n",
       "\t<li>'kilometer'</li>\n",
       "\t<li>'monthOfRegistration'</li>\n",
       "\t<li>'fuelType'</li>\n",
       "\t<li>'brand'</li>\n",
       "\t<li>'notRepairedDamage'</li>\n",
       "\t<li>'dateCreated'</li>\n",
       "\t<li>'nrOfPictures'</li>\n",
       "\t<li>'postalCode'</li>\n",
       "\t<li>'lastSeen'</li>\n",
       "\t<li>'days'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'dateCrawled'\n",
       "\\item 'name'\n",
       "\\item 'seller'\n",
       "\\item 'offerType'\n",
       "\\item 'price'\n",
       "\\item 'abtest'\n",
       "\\item 'vehicleType'\n",
       "\\item 'yearOfRegistration'\n",
       "\\item 'gearbox'\n",
       "\\item 'powerPS'\n",
       "\\item 'model'\n",
       "\\item 'kilometer'\n",
       "\\item 'monthOfRegistration'\n",
       "\\item 'fuelType'\n",
       "\\item 'brand'\n",
       "\\item 'notRepairedDamage'\n",
       "\\item 'dateCreated'\n",
       "\\item 'nrOfPictures'\n",
       "\\item 'postalCode'\n",
       "\\item 'lastSeen'\n",
       "\\item 'days'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'dateCrawled'\n",
       "2. 'name'\n",
       "3. 'seller'\n",
       "4. 'offerType'\n",
       "5. 'price'\n",
       "6. 'abtest'\n",
       "7. 'vehicleType'\n",
       "8. 'yearOfRegistration'\n",
       "9. 'gearbox'\n",
       "10. 'powerPS'\n",
       "11. 'model'\n",
       "12. 'kilometer'\n",
       "13. 'monthOfRegistration'\n",
       "14. 'fuelType'\n",
       "15. 'brand'\n",
       "16. 'notRepairedDamage'\n",
       "17. 'dateCreated'\n",
       "18. 'nrOfPictures'\n",
       "19. 'postalCode'\n",
       "20. 'lastSeen'\n",
       "21. 'days'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"dateCrawled\"         \"name\"                \"seller\"             \n",
       " [4] \"offerType\"           \"price\"               \"abtest\"             \n",
       " [7] \"vehicleType\"         \"yearOfRegistration\"  \"gearbox\"            \n",
       "[10] \"powerPS\"             \"model\"               \"kilometer\"          \n",
       "[13] \"monthOfRegistration\" \"fuelType\"            \"brand\"              \n",
       "[16] \"notRepairedDamage\"   \"dateCreated\"         \"nrOfPictures\"       \n",
       "[19] \"postalCode\"          \"lastSeen\"            \"days\"               "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(auto_sales$days)\n",
    "names(auto_sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Remove the columns dateCrawled, dateCreated and lastSeen from dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'name'</li>\n",
       "\t<li>'seller'</li>\n",
       "\t<li>'offerType'</li>\n",
       "\t<li>'price'</li>\n",
       "\t<li>'abtest'</li>\n",
       "\t<li>'vehicleType'</li>\n",
       "\t<li>'yearOfRegistration'</li>\n",
       "\t<li>'gearbox'</li>\n",
       "\t<li>'powerPS'</li>\n",
       "\t<li>'model'</li>\n",
       "\t<li>'kilometer'</li>\n",
       "\t<li>'monthOfRegistration'</li>\n",
       "\t<li>'fuelType'</li>\n",
       "\t<li>'brand'</li>\n",
       "\t<li>'notRepairedDamage'</li>\n",
       "\t<li>'nrOfPictures'</li>\n",
       "\t<li>'postalCode'</li>\n",
       "\t<li>'days'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'name'\n",
       "\\item 'seller'\n",
       "\\item 'offerType'\n",
       "\\item 'price'\n",
       "\\item 'abtest'\n",
       "\\item 'vehicleType'\n",
       "\\item 'yearOfRegistration'\n",
       "\\item 'gearbox'\n",
       "\\item 'powerPS'\n",
       "\\item 'model'\n",
       "\\item 'kilometer'\n",
       "\\item 'monthOfRegistration'\n",
       "\\item 'fuelType'\n",
       "\\item 'brand'\n",
       "\\item 'notRepairedDamage'\n",
       "\\item 'nrOfPictures'\n",
       "\\item 'postalCode'\n",
       "\\item 'days'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'name'\n",
       "2. 'seller'\n",
       "3. 'offerType'\n",
       "4. 'price'\n",
       "5. 'abtest'\n",
       "6. 'vehicleType'\n",
       "7. 'yearOfRegistration'\n",
       "8. 'gearbox'\n",
       "9. 'powerPS'\n",
       "10. 'model'\n",
       "11. 'kilometer'\n",
       "12. 'monthOfRegistration'\n",
       "13. 'fuelType'\n",
       "14. 'brand'\n",
       "15. 'notRepairedDamage'\n",
       "16. 'nrOfPictures'\n",
       "17. 'postalCode'\n",
       "18. 'days'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"name\"                \"seller\"              \"offerType\"          \n",
       " [4] \"price\"               \"abtest\"              \"vehicleType\"        \n",
       " [7] \"yearOfRegistration\"  \"gearbox\"             \"powerPS\"            \n",
       "[10] \"model\"               \"kilometer\"           \"monthOfRegistration\"\n",
       "[13] \"fuelType\"            \"brand\"               \"notRepairedDamage\"  \n",
       "[16] \"nrOfPictures\"        \"postalCode\"          \"days\"               "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code here..\n",
    "auto_sales$dateCrawled <- NULL \n",
    "auto_sales$dateCreated <- NULL \n",
    "auto_sales$lastSeen <- NULL \n",
    "names(auto_sales)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Convert the columns \"Price\", \"yearOfRegistration\", \"powerPS\", \"kilometer\",\"monthOfRegistration\",\"nrOfPictures\",\"postalCode\" and \"days\" to factor type using lapply function. You can use column indices (1, 4, 7, 9, 11, 12, 16, 17, 18) for the operation. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df[cols] <- lapply(df[cols], FUN)  # use this pattern  \n",
    "df[,c(1,2,5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# code here..\n",
    "auto_sales[,c(1, 4, 7, 9, 11, 12, 16, 17, 18)] <- lapply(auto_sales[,c(1, 4, 7, 9, 11, 12, 16, 17, 18)], as.factor)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Verify the data type of all columns. Make sure all columns are of factor type before we create transactions from auto-sales dataframe. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'data.frame':\t189349 obs. of  18 variables:\n",
      " $ name               : Factor w/ 128113 levels \"     AUDI A4 S LINE      VOLLAUSSTATUNG      \",..: 43092 2369 49334 41709 93792 14742 79782 103515 34722 104650 ...\n",
      " $ seller             : Factor w/ 2 levels \"gewerblich\",\"privat\": 2 2 2 2 2 2 2 2 2 2 ...\n",
      " $ offerType          : Factor w/ 2 levels \"Angebot\",\"Gesuch\": 1 1 1 1 1 1 1 1 1 1 ...\n",
      " $ price              : Factor w/ 4230 levels \"0\",\"1\",\"2\",\"3\",..: 199 2759 1992 558 1053 266 735 1 2463 404 ...\n",
      " $ abtest             : Factor w/ 2 levels \"control\",\"test\": 2 2 2 2 2 2 2 2 1 2 ...\n",
      " $ vehicleType        : Factor w/ 9 levels \"\",\"andere\",\"bus\",..: 1 5 9 6 6 8 4 8 3 6 ...\n",
      " $ yearOfRegistration : Factor w/ 127 levels \"1000\",\"1111\",..: 75 93 86 83 90 77 86 62 96 80 ...\n",
      " $ gearbox            : Factor w/ 3 levels \"\",\"automatik\",..: 3 3 2 3 3 3 3 3 3 3 ...\n",
      " $ powerPS            : Factor w/ 624 levels \"0\",\"1\",\"2\",\"3\",..: 1 191 164 76 70 103 110 51 126 102 ...\n",
      " $ model              : Factor w/ 251 levels \"\",\"100\",\"145\",..: 119 1 120 119 104 13 10 42 63 119 ...\n",
      " $ kilometer          : Factor w/ 13 levels \"5000\",\"10000\",..: 13 12 12 13 10 13 13 5 4 13 ...\n",
      " $ monthOfRegistration: Factor w/ 13 levels \"0\",\"1\",\"2\",\"3\",..: 1 6 9 7 8 11 9 8 9 1 ...\n",
      " $ fuelType           : Factor w/ 8 levels \"\",\"andere\",\"benzin\",..: 3 5 5 3 5 3 3 3 3 1 ...\n",
      " $ brand              : Factor w/ 40 levels \"alfa_romeo\",\"audi\",..: 39 2 15 39 32 3 26 39 11 39 ...\n",
      " $ notRepairedDamage  : Factor w/ 3 levels \"\",\"ja\",\"nein\": 1 2 1 3 3 2 3 3 1 1 ...\n",
      " $ nrOfPictures       : Factor w/ 1 level \"0\": 1 1 1 1 1 1 1 1 1 1 ...\n",
      " $ postalCode         : Factor w/ 8014 levels \"1067\",\"1068\",..: 4822 4545 6889 6928 4145 2326 4566 1138 7428 1902 ...\n",
      " $ days               : Factor w/ 94 levels \"0\",\"1\",\"2\",\"3\",..: 15 15 23 1 7 3 5 5 1 15 ...\n"
     ]
    }
   ],
   "source": [
    "# code here..\n",
    "str(auto_sales)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "library(\"arules\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Now, coerce the data set into transactions. Save this transactions to auto_trans variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "transactions in sparse format with\n",
       " 189349 transactions (rows) and\n",
       " 141549 items (columns)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code here..\n",
    "auto_trans <- as(auto_sales, \"transactions\")\n",
    "auto_trans\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Draw a frequency plot for the generated transactions with a support of 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Ekiza67fPudXdfseF/Du7+wYX/Xj9Gd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\nRK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code here..\n",
    "itemFrequencyPlot(auto_trans, support = 0.5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Generate association rules for the transactions in auto_trans with support of 0.3 and confidence of 0.6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Apriori\n",
      "\n",
      "Parameter specification:\n",
      " confidence minval smax arem  aval originalSupport maxtime support minlen\n",
      "        0.6    0.1    1 none FALSE            TRUE       5     0.3      1\n",
      " maxlen target   ext\n",
      "     10  rules FALSE\n",
      "\n",
      "Algorithmic control:\n",
      " filter tree heap memopt load sort verbose\n",
      "    0.1 TRUE TRUE  FALSE TRUE    2    TRUE\n",
      "\n",
      "Absolute minimum support count: 56804 \n",
      "\n",
      "set item appearances ...[0 item(s)] done [0.00s].\n",
      "set transactions ...[141549 item(s), 189349 transaction(s)] done [0.42s].\n",
      "sorting and recoding items ... [9 item(s)] done [0.03s].\n",
      "creating transaction tree ... done [0.09s].\n",
      "checking subsets of size 1 2 3 4 5 6 done [0.00s].\n",
      "writing ... [480 rule(s)] done [0.00s].\n",
      "creating S4 object  ... done [0.06s].\n"
     ]
    }
   ],
   "source": [
    "# code here..\n",
    "rules <- apriori(auto_trans, parameter = list(support = 0.3, confidence = 0.6))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: grid\n"
     ]
    }
   ],
   "source": [
    "library(\"arulesViz\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Draw a scatter plot for the generated rules using 'support' as the measure and 'confidence' for shading."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6DHDgAAQBIEOwAAAEkQ7AAAACRBsAMAAJAEwQ4AAEASBDsAAABJMN0JAAAwnqKY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\nCHYAAAAGQbADAAAwCIIdAACAQfw/i0r3SnTSW4kAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code here..\n",
    "\n",
    "plot(rules, method = \"scatter\", measure = \"support\", shading = \"confidence\", interactive = FALSE, data = auto_sales,)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Draw a matrix plot for the generated transactions using measures 'confidence', 'lift'. Draw the plot with ordered transactions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Itemsets in Antecedent (LHS)\n",
      "  [1] \"{seller=privat,gearbox=manuell,notRepairedDamage=nein}\"                                    \n",
      "  [2] \"{seller=privat,gearbox=manuell,notRepairedDamage=nein,nrOfPictures=0}\"                     \n",
      "  [3] \"{gearbox=manuell,notRepairedDamage=nein,nrOfPictures=0}\"                                   \n",
      "  [4] \"{gearbox=manuell,notRepairedDamage=nein}\"                                                  \n",
      "  [5] \"{offerType=Angebot,gearbox=manuell,notRepairedDamage=nein}\"                                \n",
      "  [6] \"{seller=privat,offerType=Angebot,gearbox=manuell,notRepairedDamage=nein}\"                  \n",
      "  [7] \"{seller=privat,offerType=Angebot,gearbox=manuell,notRepairedDamage=nein,nrOfPictures=0}\"   \n",
      "  [8] \"{offerType=Angebot,gearbox=manuell,notRepairedDamage=nein,nrOfPictures=0}\"                 \n",
      "  [9] \"{offerType=Angebot,gearbox=manuell,nrOfPictures=0}\"                                        \n",
      " [10] \"{seller=privat,offerType=Angebot,gearbox=manuell,nrOfPictures=0}\"                          \n",
      " [11] \"{seller=privat,offerType=Angebot,gearbox=manuell}\"                                         \n",
      " [12] \"{offerType=Angebot,gearbox=manuell}\"                                                       \n",
      " [13] \"{gearbox=manuell}\"                                                                         \n",
      " [14] \"{gearbox=manuell,nrOfPictures=0}\"                                                          \n",
      " [15] \"{seller=privat,gearbox=manuell,nrOfPictures=0}\"                                            \n",
      " [16] \"{seller=privat,gearbox=manuell}\"                                                           \n",
      " [17] \"{seller=privat}\"                                                                           \n",
      " [18] \"{seller=privat,abtest=test}\"                                                               \n",
      " [19] \"{abtest=test}\"                                                                             \n",
      " [20] \"{}\"                                                                                        \n",
      " [21] \"{nrOfPictures=0}\"                                                                          \n",
      " [22] \"{abtest=test,nrOfPictures=0}\"                                                              \n",
      " [23] \"{seller=privat,abtest=test,nrOfPictures=0}\"                                                \n",
      " [24] \"{seller=privat,nrOfPictures=0}\"                                                            \n",
      " [25] \"{seller=privat,notRepairedDamage=nein,nrOfPictures=0}\"                                     \n",
      " [26] \"{notRepairedDamage=nein,nrOfPictures=0}\"                                                   \n",
      " [27] \"{notRepairedDamage=nein}\"                                                                  \n",
      " [28] \"{seller=privat,notRepairedDamage=nein}\"                                                    \n",
      " [29] \"{seller=privat,offerType=Angebot,notRepairedDamage=nein}\"                                  \n",
      " [30] \"{offerType=Angebot,notRepairedDamage=nein}\"                                                \n",
      " [31] \"{offerType=Angebot,notRepairedDamage=nein,nrOfPictures=0}\"                                 \n",
      " [32] \"{seller=privat,offerType=Angebot,notRepairedDamage=nein,nrOfPictures=0}\"                   \n",
      " [33] \"{seller=privat,offerType=Angebot,nrOfPictures=0}\"                                          \n",
      " [34] \"{seller=privat,offerType=Angebot,abtest=test,nrOfPictures=0}\"                              \n",
      " [35] \"{seller=privat,offerType=Angebot,abtest=test}\"                                             \n",
      " [36] \"{seller=privat,offerType=Angebot}\"                                                         \n",
      " [37] \"{offerType=Angebot}\"                                                                       \n",
      " [38] \"{offerType=Angebot,abtest=test}\"                                                           \n",
      " [39] \"{offerType=Angebot,abtest=test,nrOfPictures=0}\"                                            \n",
      " [40] \"{offerType=Angebot,nrOfPictures=0}\"                                                        \n",
      " [41] \"{offerType=Angebot,abtest=control,nrOfPictures=0}\"                                         \n",
      " [42] \"{abtest=control,nrOfPictures=0}\"                                                           \n",
      " [43] \"{seller=privat,abtest=control,nrOfPictures=0}\"                                             \n",
      " [44] \"{seller=privat,offerType=Angebot,abtest=control,nrOfPictures=0}\"                           \n",
      " [45] \"{seller=privat,offerType=Angebot,abtest=control}\"                                          \n",
      " [46] \"{offerType=Angebot,abtest=control}\"                                                        \n",
      " [47] \"{abtest=control}\"                                                                          \n",
      " [48] \"{seller=privat,abtest=control}\"                                                            \n",
      " [49] \"{seller=privat,kilometer=150000}\"                                                          \n",
      " [50] \"{seller=privat,fuelType=benzin}\"                                                           \n",
      " [51] \"{seller=privat,fuelType=benzin,nrOfPictures=0}\"                                            \n",
      " [52] \"{seller=privat,kilometer=150000,nrOfPictures=0}\"                                           \n",
      " [53] \"{seller=privat,kilometer=150000,notRepairedDamage=nein,nrOfPictures=0}\"                    \n",
      " [54] \"{seller=privat,fuelType=benzin,notRepairedDamage=nein,nrOfPictures=0}\"                     \n",
      " [55] \"{seller=privat,fuelType=benzin,notRepairedDamage=nein}\"                                    \n",
      " [56] \"{seller=privat,kilometer=150000,notRepairedDamage=nein}\"                                   \n",
      " [57] \"{kilometer=150000,notRepairedDamage=nein}\"                                                 \n",
      " [58] \"{fuelType=benzin,notRepairedDamage=nein}\"                                                  \n",
      " [59] \"{fuelType=benzin,notRepairedDamage=nein,nrOfPictures=0}\"                                   \n",
      " [60] \"{kilometer=150000,notRepairedDamage=nein,nrOfPictures=0}\"                                  \n",
      " [61] \"{kilometer=150000,nrOfPictures=0}\"                                                         \n",
      " [62] \"{fuelType=benzin,nrOfPictures=0}\"                                                          \n",
      " [63] \"{offerType=Angebot,fuelType=benzin,nrOfPictures=0}\"                                        \n",
      " [64] \"{offerType=Angebot,kilometer=150000,nrOfPictures=0}\"                                       \n",
      " [65] \"{offerType=Angebot,kilometer=150000,notRepairedDamage=nein,nrOfPictures=0}\"                \n",
      " [66] \"{offerType=Angebot,fuelType=benzin,notRepairedDamage=nein,nrOfPictures=0}\"                 \n",
      " [67] \"{seller=privat,offerType=Angebot,fuelType=benzin,notRepairedDamage=nein,nrOfPictures=0}\"   \n",
      " [68] \"{seller=privat,offerType=Angebot,kilometer=150000,notRepairedDamage=nein,nrOfPictures=0}\"  \n",
      " [69] \"{seller=privat,offerType=Angebot,kilometer=150000,nrOfPictures=0}\"                         \n",
      " [70] \"{seller=privat,offerType=Angebot,fuelType=benzin,nrOfPictures=0}\"                          \n",
      " [71] \"{seller=privat,offerType=Angebot,fuelType=benzin}\"                                         \n",
      " [72] \"{seller=privat,offerType=Angebot,kilometer=150000}\"                                        \n",
      " [73] \"{seller=privat,offerType=Angebot,kilometer=150000,notRepairedDamage=nein}\"                 \n",
      " [74] \"{seller=privat,offerType=Angebot,fuelType=benzin,notRepairedDamage=nein}\"                  \n",
      " [75] \"{offerType=Angebot,fuelType=benzin,notRepairedDamage=nein}\"                                \n",
      " [76] \"{offerType=Angebot,kilometer=150000,notRepairedDamage=nein}\"                               \n",
      " [77] \"{offerType=Angebot,kilometer=150000}\"                                                      \n",
      " [78] \"{offerType=Angebot,fuelType=benzin}\"                                                       \n",
      " [79] \"{fuelType=benzin}\"                                                                         \n",
      " [80] \"{kilometer=150000}\"                                                                        \n",
      " [81] \"{gearbox=manuell,fuelType=benzin}\"                                                         \n",
      " [82] \"{gearbox=manuell,kilometer=150000}\"                                                        \n",
      " [83] \"{abtest=control,notRepairedDamage=nein}\"                                                   \n",
      " [84] \"{abtest=test,gearbox=manuell}\"                                                             \n",
      " [85] \"{abtest=test,notRepairedDamage=nein}\"                                                      \n",
      " [86] \"{abtest=test,fuelType=benzin}\"                                                             \n",
      " [87] \"{abtest=control,gearbox=manuell}\"                                                          \n",
      " [88] \"{gearbox=manuell,fuelType=benzin,notRepairedDamage=nein}\"                                  \n",
      " [89] \"{abtest=test,kilometer=150000}\"                                                            \n",
      " [90] \"{gearbox=manuell,kilometer=150000,notRepairedDamage=nein}\"                                 \n",
      " [91] \"{abtest=control,kilometer=150000}\"                                                         \n",
      " [92] \"{kilometer=150000,fuelType=benzin}\"                                                        \n",
      " [93] \"{seller=privat,abtest=test,gearbox=manuell}\"                                               \n",
      " [94] \"{seller=privat,abtest=test,notRepairedDamage=nein}\"                                        \n",
      " [95] \"{seller=privat,abtest=control,notRepairedDamage=nein}\"                                     \n",
      " [96] \"{seller=privat,abtest=test,fuelType=benzin}\"                                               \n",
      " [97] \"{seller=privat,kilometer=150000,fuelType=benzin}\"                                          \n",
      " [98] \"{seller=privat,abtest=control,gearbox=manuell}\"                                            \n",
      " [99] \"{seller=privat,gearbox=manuell,fuelType=benzin,notRepairedDamage=nein}\"                    \n",
      "[100] \"{seller=privat,abtest=test,kilometer=150000}\"                                              \n",
      "[101] \"{seller=privat,gearbox=manuell,kilometer=150000,notRepairedDamage=nein}\"                   \n",
      "[102] \"{seller=privat,abtest=control,kilometer=150000}\"                                           \n",
      "[103] \"{seller=privat,gearbox=manuell,kilometer=150000}\"                                          \n",
      "[104] \"{seller=privat,gearbox=manuell,fuelType=benzin}\"                                           \n",
      "[105] \"{seller=privat,gearbox=manuell,fuelType=benzin,nrOfPictures=0}\"                            \n",
      "[106] \"{seller=privat,gearbox=manuell,kilometer=150000,nrOfPictures=0}\"                           \n",
      "[107] \"{seller=privat,abtest=test,gearbox=manuell,nrOfPictures=0}\"                                \n",
      "[108] \"{seller=privat,abtest=test,notRepairedDamage=nein,nrOfPictures=0}\"                         \n",
      "[109] \"{seller=privat,abtest=control,notRepairedDamage=nein,nrOfPictures=0}\"                      \n",
      "[110] \"{seller=privat,abtest=test,fuelType=benzin,nrOfPictures=0}\"                                \n",
      "[111] \"{seller=privat,kilometer=150000,fuelType=benzin,nrOfPictures=0}\"                           \n",
      "[112] \"{seller=privat,abtest=control,gearbox=manuell,nrOfPictures=0}\"                             \n",
      "[113] \"{seller=privat,gearbox=manuell,fuelType=benzin,notRepairedDamage=nein,nrOfPictures=0}\"     \n",
      "[114] \"{seller=privat,abtest=test,kilometer=150000,nrOfPictures=0}\"                               \n",
      "[115] \"{seller=privat,gearbox=manuell,kilometer=150000,notRepairedDamage=nein,nrOfPictures=0}\"    \n",
      "[116] \"{seller=privat,abtest=control,kilometer=150000,nrOfPictures=0}\"                            \n",
      "[117] \"{kilometer=150000,fuelType=benzin,nrOfPictures=0}\"                                         \n",
      "[118] \"{abtest=control,kilometer=150000,nrOfPictures=0}\"                                          \n",
      "[119] \"{gearbox=manuell,kilometer=150000,notRepairedDamage=nein,nrOfPictures=0}\"                  \n",
      "[120] \"{abtest=test,kilometer=150000,nrOfPictures=0}\"                                             \n",
      "[121] \"{gearbox=manuell,fuelType=benzin,notRepairedDamage=nein,nrOfPictures=0}\"                   \n",
      "[122] \"{abtest=control,gearbox=manuell,nrOfPictures=0}\"                                           \n",
      "[123] \"{abtest=test,fuelType=benzin,nrOfPictures=0}\"                                              \n",
      "[124] \"{abtest=test,notRepairedDamage=nein,nrOfPictures=0}\"                                       \n",
      "[125] \"{abtest=test,gearbox=manuell,nrOfPictures=0}\"                                              \n",
      "[126] \"{abtest=control,notRepairedDamage=nein,nrOfPictures=0}\"                                    \n",
      "[127] \"{gearbox=manuell,kilometer=150000,nrOfPictures=0}\"                                         \n",
      "[128] \"{gearbox=manuell,fuelType=benzin,nrOfPictures=0}\"                                          \n",
      "[129] \"{offerType=Angebot,gearbox=manuell,fuelType=benzin,nrOfPictures=0}\"                        \n",
      "[130] \"{offerType=Angebot,gearbox=manuell,kilometer=150000,nrOfPictures=0}\"                       \n",
      "[131] \"{offerType=Angebot,kilometer=150000,fuelType=benzin,nrOfPictures=0}\"                       \n",
      "[132] \"{offerType=Angebot,abtest=test,fuelType=benzin,nrOfPictures=0}\"                            \n",
      "[133] \"{offerType=Angebot,abtest=control,kilometer=150000,nrOfPictures=0}\"                        \n",
      "[134] \"{offerType=Angebot,gearbox=manuell,kilometer=150000,notRepairedDamage=nein,nrOfPictures=0}\"\n",
      "[135] \"{offerType=Angebot,abtest=test,kilometer=150000,nrOfPictures=0}\"                           \n",
      "[136] \"{offerType=Angebot,gearbox=manuell,fuelType=benzin,notRepairedDamage=nein,nrOfPictures=0}\" \n",
      "[137] \"{offerType=Angebot,abtest=control,gearbox=manuell,nrOfPictures=0}\"                         \n",
      "[138] \"{offerType=Angebot,abtest=test,notRepairedDamage=nein,nrOfPictures=0}\"                     \n",
      "[139] \"{offerType=Angebot,abtest=test,gearbox=manuell,nrOfPictures=0}\"                            \n",
      "[140] \"{offerType=Angebot,abtest=control,notRepairedDamage=nein,nrOfPictures=0}\"                  \n",
      "[141] \"{offerType=Angebot,abtest=control,notRepairedDamage=nein}\"                                 \n",
      "[142] \"{offerType=Angebot,abtest=test,gearbox=manuell}\"                                           \n",
      "[143] \"{offerType=Angebot,abtest=test,notRepairedDamage=nein}\"                                    \n",
      "[144] \"{offerType=Angebot,abtest=control,gearbox=manuell}\"                                        \n",
      "[145] \"{offerType=Angebot,gearbox=manuell,fuelType=benzin,notRepairedDamage=nein}\"                \n",
      "[146] \"{offerType=Angebot,abtest=test,kilometer=150000}\"                                          \n",
      "[147] \"{offerType=Angebot,gearbox=manuell,kilometer=150000,notRepairedDamage=nein}\"               \n",
      "[148] \"{offerType=Angebot,abtest=control,kilometer=150000}\"                                       \n",
      "[149] \"{offerType=Angebot,abtest=test,fuelType=benzin}\"                                           \n",
      "[150] \"{offerType=Angebot,kilometer=150000,fuelType=benzin}\"                                      \n",
      "[151] \"{offerType=Angebot,gearbox=manuell,kilometer=150000}\"                                      \n",
      "[152] \"{offerType=Angebot,gearbox=manuell,fuelType=benzin}\"                                       \n",
      "[153] \"{seller=privat,offerType=Angebot,gearbox=manuell,kilometer=150000,nrOfPictures=0}\"         \n",
      "[154] \"{seller=privat,offerType=Angebot,gearbox=manuell,fuelType=benzin,nrOfPictures=0}\"          \n",
      "[155] \"{seller=privat,offerType=Angebot,gearbox=manuell,fuelType=benzin}\"                         \n",
      "[156] \"{seller=privat,offerType=Angebot,gearbox=manuell,kilometer=150000}\"                        \n",
      "[157] \"{seller=privat,offerType=Angebot,abtest=control,kilometer=150000}\"                         \n",
      "[158] \"{seller=privat,offerType=Angebot,abtest=control,gearbox=manuell}\"                          \n",
      "[159] \"{seller=privat,offerType=Angebot,gearbox=manuell,fuelType=benzin,notRepairedDamage=nein}\"  \n",
      "[160] \"{seller=privat,offerType=Angebot,kilometer=150000,fuelType=benzin}\"                        \n",
      "[161] \"{seller=privat,offerType=Angebot,gearbox=manuell,kilometer=150000,notRepairedDamage=nein}\" \n",
      "[162] \"{seller=privat,offerType=Angebot,abtest=test,notRepairedDamage=nein}\"                      \n",
      "[163] \"{seller=privat,offerType=Angebot,abtest=test,kilometer=150000}\"                            \n",
      "[164] \"{seller=privat,offerType=Angebot,abtest=test,fuelType=benzin}\"                             \n",
      "[165] \"{seller=privat,offerType=Angebot,abtest=control,notRepairedDamage=nein}\"                   \n",
      "[166] \"{seller=privat,offerType=Angebot,abtest=test,gearbox=manuell}\"                             \n",
      "Itemsets in Consequent (RHS)\n",
      "[1] \"{offerType=Angebot}\"      \"{nrOfPictures=0}\"        \n",
      "[3] \"{seller=privat}\"          \"{fuelType=benzin}\"       \n",
      "[5] \"{kilometer=150000}\"       \"{notRepairedDamage=nein}\"\n",
      "[7] \"{gearbox=manuell}\"       \n"
     ]
    },
    {
     "data": {
      "image/png": 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4/GVxGovjSCe0KCW4uEpboOnJpB3u8Z\nqTlT9brdMScnh32xb9efPxfEWUVFRapxluXg4HDx4sUHOzTDMFeuXOn2NkrVRVjU99PW1hYW\nFta1ByKaPHkyOwvIMIxUKlWdBVQ1evTo5ubm+/pJAkDfQbADMCCd/u52dHRwy2QIBAJu2Y5u\n/2afPHkyMDDQ1tbWx8dn8eLFbFzw8/OzsLCwsLDgXrTw66+/hoaG2tnZCYXCGTNm9HRoNaM6\nduwY1/LXv/6VK/vwww+59piYGPVnum/fPq5Y9UIkt35KtwsIdzvI+z0jNWeqXk87tra2fvLJ\nJ9OmTRs+fLilpeUTTzzxyiuvsO/V6OTXX3997bXXhg4dyufzXV1dIyIifvvtt94cmmGYy5cv\nh4WFubq68vl8kUj04osv/vDDDwzDWPxBYz8dHR2ff/75iy++6OXlZWlpOWzYsBkzZmRlZXV6\nL1xTU9O2bdsCAwMfffRRc3PzIUOGjB8/ftu2bexldAAwEDymy4t3AAAAAGAg6vEZKAAAAAAY\nWBDsAAAAAIwEgh0AAACAkUCwAwAAADASCHYAAAAARgLBDgAAAMBIINgBAAAAGAkEOwAAAAAj\ngWAHAAAAYCQQ7AAAAACMBIIdAAAAgJFAsAMAAAAwEgh2AAAAAEYCwQ4AAADASCDYAQAAABgJ\nBDsAAAAAI4FgBwAAAGAkEOwAAAAAjASCHQAAAICRQLADAAAAMBIIdgAAAABGAsEOAAAAwEgg\n2AEAAAAYCQQ7AAAAACOBYAcAAABgJBDsAAAAAIwEgh0AAACAkUCwAwAAADASCHYAAAAARgLB\nDgAAAMBIINgBAAAAGAkEOwAAAAAjgWAHAAAAYCQQ7AAAAACMBIIdAAAAgJFAsAMAAAAwEgh2\nAAAAAEbCTN8DMGjZ2dlZWVn6HgUAAHTj+eefDw0N1fcojBz+DvYbXf17RrBT59ChQ3l5ecHB\nwfoeCBHRmbry3ndi3S7rfSdE1Gxmq4tueL3vwqa9kf3gKfmf6ef/c1GyHyzbW9gPQ6s6j/k3\nUeefRk8198wE3R7lfg/UUz+67eSpwU8RgLE7ffq0XC5HsOtrhw4dyjv7U3DQJA11La2a+2rW\nXKPUoh+5VjX3NNa0adNPsxb9NOqgn6vUqKt/zwh2GkyYMGHXrl36HgUR0av/zuh9J66tN3rf\nCRHdtnqs950wugh2Q1sr2A+Lc//nH/P+Z9rZD4+0SNgP088O67Tv8cBfOrX0VFMjcOn2KPd7\noJ760W0n74+PJQBjFx4eru8hPCwm+I/f9Y+dGooqqzV3JNFco6is0VjToMWx7lbWaq6RaFFz\nS4ua65pr6pul6gvS6LrGTrSEe+wAAAD61cqVK729vbWpZBhGLBYHBATY2dn5+/uLxWKGYVQL\nysvLw8PDPTw8rKysPDw8wsPDy8t1cHkHBi4EOwAAgP5TWVmZnp6uZXFkZGRUVFRNTU1YWFhN\nTU1UVNSKFSu4b0tLS/38/Pbv3z9s2LBFixYNGzZs//79fn5+paWlfTN2GABwKRYAAKDPKRSK\n7Ozs4uLivXv3SqVSJycnjbvk5+enpKT4+vrm5eUJBILm5uaJEyeKxeKFCxf6+/sT0aZNm2Qy\n2eeffz537lx2ly+++GLevHmJiYkHDhzo2/MBQ4VgBwAA0OcaGhpmzpx5X7uw4Sw6OlogEBCR\ntbV1dHT0yy+/nJGRwQa7srIyIpo2bRq3C/v5ypUrOhw5DCy4FAsAANDnnJycWv+g5S4lJSVE\nFBISwrVMnTqViLgrrU8//TQRrV+/vqWlhYhaWlo2bNhARIGBgbocOgwomLEDAADoczwez9LS\n8r52kUgkNjY2Dg4OXIujo6ONjU1lZSW7+dFHH5mZmSUlJaWmpopEoqqqqra2tlWrVm3evFmX\nQ4cBBcEOAADAEEkkEqFQ2KlRKBRywc7U1NTGxobH47W1td28eZOITExMXFxc+Hy+Nv3HxMRs\n2rRJY5nzIOf7HDjoE4IdAACAIWIYhsfrvN4nwzByuZz9vHv37ri4uCeffDIlJWXkyJF5eXkR\nERGrVq0aNWqU6gXcnqxatUrjbX8zZ87kmyIqDCT4bQEAABgikUhUW9t58dv6+noXl99XKf/0\n00+J6NChQ8OHDyeiadOm7dy5c8aMGbt27dIm2Dk6Ovr5+amvsbCwICWjvgYMCh6eAAAAMEQi\nkaixsVEm++/LD2UyWVNT05AhQ9jN8vJyFxcXNtWxgoKCiKiioqKfhwqGAzN2AAAAhigwMPCn\nn37Kzc0NCwtjW06dOkVEEyZMYDfd3d1v3rwpl8vNzc3ZlpqaGiIaOnSoLsfBU5JZvYYaM82v\nAiPz2xpLWi1vaaxpttKixvpXjTUy+xsaaxruFWqsqVfKNdbUCTQUtGnxSjYtYcYOAADAIEil\n0vr6/0aopUuXElFycnJ7ezsRKRSKjz/+mIgiIiLYgilTprS1tW3atIl9z1hHR0dCQgIRPfPM\nM/0/eDAQmLEDAAAwCM7Ozl5eXuyyw0Tk6em5ZMmStLS0oKCg4ODg3NzcwsLC5cuXe3h4sAWb\nNm367rvv4uPjc3JyfHx8zp07d+nSpTFjxrzxxhv6OwnQM8zYAQAAGKjU1NT4+PiqqqqkpKTa\n2trExMSdO3dy3zo4OFy4cOGdd95pbGzMzMxUKpXR0dFnzpzRcrkTMEqYsQMAAOhX7JVTbdr5\nfH5sbGxsbGxPXdnb2ycnJ+tycDDAYcYOAAAAwEgg2AEAAPSrlStXent7a1PJMIxYLA4ICLCz\ns/P39xeLxV1n9U6cOBEUFGRjY+Pp6blx48aOjo4+GDIMGAh2AAAA/aeysjI9PV3L4sjIyKio\nqJqamrCwsJqamqioqBUrVqgW7Nu3b/r06VevXn3++ectLS3ff//9qKioPhg1DBi4xw4AAKDP\nKRSK7Ozs4uLivXv3SqVSJycnjbvk5+enpKT4+vrm5eUJBILm5uaJEyeKxeKFCxf6+/sTUXNz\n81tvveXu7p6fny8SieRy+dNPP71r166oqCgfH5++PycwRJixAwAA6HMNDQ0zZ87cuHHj7dua\n1+llHThwgIiio6MFAgERWVtbR0dHE1FGRgZbcPDgQZlMtm7dOpFIRETm5uarV69mGCY7O7tP\nzgEGAszYAQAA9DknJ6fW1lb2s5WVlTa7lJSUEJHqW1+nTp1KRKWlpezmV199RUQvvPACVzBl\nypRt27Z5eXnpaNQw8CDYAQAA9Dkej2dpaXlfu0gkEhsbGwcHB67F0dHRxsamsrKS3bx165a1\ntTURhYaGnj592sXFZfLkyZs3b3Z0dNSm/59++uno0aPqa+rq6qwF9zds0C8EOwAAAEMkkUiE\nQmGnRqFQyAW76upqa2vr0NDQc+fOubi4VFRUXLt27fjx4xcvXrS3t9fY/y+//HL+/Hn1NW1t\nbebmpmQu09CXpaaXyRLdtarVWHNHoPk69R2b65prWos11tS1lWvuR6GxhOq6X5Twf2s03fjW\n0qi5Ey0h2AEAABgihmF4PF7XRrn897fO19XVtbe3+/j4SCSSIUOG3L17d9GiRUePHo2Pj09K\nStLY/4IFCxYsWKC+ZsSIEURapBswGHh4AgAAwBCJRKL6+s4zYfX19S4uLuxnR0dHHo+XmZk5\nZMgQInJwcNizZw+Px8vJyenvsYLBQLADAAAwRCKRqLGxUSb772VQmUzW1NTExjgiGjJkiIuL\nC/tILMvZ2Zm9JtvfYwWDgWAHAABgiAIDA4koNzeXazl16hQRTZgwgd308fGpqqpSTX6tra3V\n1dUeHh79O1IwIAh2AAAABkEqlapee126dCkRJScnt7e3E5FCofj444+JKCIigi2IjIzs6OhY\ns2YN+xoxhmFiYmLa29tDQ0P1MHowDHh4AgAAwCA4Ozt7eXmVlZWxm56enkuWLElLSwsKCgoO\nDs7NzS0sLFy+fDk3ITdx4sRnn312165deXl5Y8eOvXjx4vnz50eNGhUTE6O/kwA9w4wdAACA\ngUpNTY2Pj6+qqkpKSqqtrU1MTNy5cyf3LY/HO3ToUGxsrJWV1cGDB+Vy+dq1awsKCtg3VcDD\nCTN2AAAA/Yphul/6rGs7n8+PjY2NjY3tqSuBQBAfHx8fH6/L8cFAhhk7AACAfrVy5Upvb29t\nKhmGEYvFAQEBdnZ2/v7+YrG4p1CoVCqnT5/edd07eNgg2AEAAPSfysrK9PR0LYsjIyOjoqJq\namrCwsJqamqioqJWrFjRbWVycvKJEyd0N0wYqHApFgAAoM8pFIrs7Ozi4uK9e/dKpVInJyeN\nu+Tn56ekpPj6+ubl5QkEgubm5okTJ4rF4oULF/r7+6tWFhUVrV27ts/GDgMJgh0AAECfa2ho\nmDlz5n3tcuDAASKKjo5mH4awtraOjo5++eWXMzIyVIOdTCabO3duYGDgrVu3rl27ptth/860\nXf33UgvNrx2rtWrTXCNo1Vxjrfm9qtJWze+Bld7TWEJSueYard4nq+HnRzJzzZ1oCZdiAQAA\n+pyTk1PrH7TcpaSkhIhCQkK4lqlTpxJRaWmpallkZOSdO3fS09NNTU11N14YqDBjBwAA0Od4\nPJ6lpeV97SKRSGxsbBwcHLgWR0dHGxubyspKriU9PT0jI+PQoUNubm46GysMZJixAwAAMEQS\niUQoFHZqFAqFXLArLy+PjIyMiIiYNWvWA/QfExPD0+TatWt1dXd7eybQjwbwjJ2ah7p7ehoc\nAABgoGAYputfOoZh5HI5Ecnl8nnz5rm4uLDvGXsAq1at0njb38yZM/n8B+se9GMAB7vJkyd3\nbczPz7e2tu7/wQAAAOiWSCSqra3t1FhfX+/i4kJEcXFxly5d6s1fPUdHRz8/P/U1FhYWRFo8\nHQAGYwAHu++//75Ty08//RQYGJiWlqaP4QAAAOiSSCS6fv26TCaztbVlW2QyWVNT0+jRo4no\n4sWLCoWiazJjJ/nq6+tVb86Dh8cADnadyOXyV199ddasWbNnz9b3WAAAAHorMDDwp59+ys3N\nDQsLY1tOnTpFRBMmTCAiNzc3Ly8v1fqKigqFQsE2mpjgHvqHlPEEuw8//PDWrVvsP3oAAIAB\nRyqVmpqaOjo6sptLly798MMPk5OTQ0NDzczMFAoFeztdREQEEaWkpHTa3dvb++rVq2VlZf08\nbDAoRhLsJBJJYmLi2rVrRSKRlrvcuHHj3Llz6mvKysq4/8AAAAD6lLOzs5eXF5fMPD09lyxZ\nkpaWFhQUFBwcnJubW1hYuHz5cg8PD/2OEwyZkQS7hIQEgUDw9ttva7/Ll19++cEHH6ivaWho\n6PqoOQAAQP9ITU0dPnz43r17k5KS3NzcEhMT16xZo+9BgUEzhmB348aN3bt3r1+/3s7OTvu9\n3n333XfffVd9zYgRI3o3NAAAgM56WpOrazufz4+NjY2NjdWmW1yEBTKOYCcWizs6OpYuXarv\ngQAAABgbJfHqSMOrTCUWml+qIbEQaKy5bal5gkZi5ay5RjBG87GsizTW/KbF+2RLtahRaHxN\nru7i2IB/aqa9vT09PX3q1KlDhgzR91gAAAA0W7lypbe3tzaVDMOIxeKAgAA7Ozt/f3+xWNxp\nVq+iomLRokVDhgyxtLT09vZesWJFXV1d34waBoYBH+yOHz9eXV29YMECfQ8EAABAs8rKyvT0\ndC2LIyMjo6KiampqwsLCampqoqKiVqxYwX1bXl7u5+eXnp7u7u6+aNEia2vr7du3jx49Gtnu\nYTbgg11WVhb18BYKAAAANXg8XkZGRtf2xMREnV8FUigU33zzzfvvvz927FipVKrNLvn5+Skp\nKb6+viUlJenp6SUlJb6+vmKxuKCggC1Yv3793bt3t2/fnp+fn5qaWlRU9N577926deu9997T\n7eBhABnwwe7UqVPDhg3DdVgAANCJ9vb28vJynU96NTQ0zJw5c+PGjbdv39ZylwMHDhBRdHS0\nQCAgImtr6+joaCJiwyjDMFlZWS4uLm+88QZbz+Px4uLiLC0tsaTrw2xgB7ubN29WVFSMHz9e\n3wMBAIAB47HHHuPxeOyrtxYuXMj7X3w+Py0tbejQobo9qJOTU+sftNylpKSEiEJCQriWqVOn\nElFpaSkRyWSyQYMGTZ8+XXUXc3NzBwcHXIp9mA3sp2Ld3d17emgcAACgW48//t1etTQAACAA\nSURBVLilpSURXb16VSQS2dvbdyoQCATr16/X7UF5PB57UO1JJBIbGxvVV746Ojra2NhUVlYS\nkZ2d3Y0bNzrtcurUqaqqqk5pryd5eXns7Uxq1NXVWVnf37BBvwZ2sAMAALhf3JVKHo+3detW\ng338TiKRdF0kXygUssGuq2PHjs2ZM8fCwmLjxo3a9F9RUXH+/Hn1NW1tbXxzU216AwOBYAcA\nAA8pA7/mwzAMe724U6NcLu/U+Ouvv0ZHRx84cEAoFGZkZIwZo3kVNyJasGCBxlA7YsQIJbVr\nP2bQu4F9jx0AAID2bGxsNm/ezG329FSsgRCJRPX19Z0a6+vrXVxcuE2lUrlz584nnnji888/\nDw8PLy0tffbZZ/t3mGBYEOwAAOBhwefzv/nmm19//VXfA9GKSCRqbGyUyWRci0wma2pq4haC\nUCqVCxcujIyMHDVq1H/+85+9e/eKRCI9DRYMBYIdAAA8LP76178WFha6u7ureSqWo+/BUmBg\nIBHl5uZyLezdgRMmTGA3N23alJmZ+eabb545c+aJJ57QyyDB0OAeOwAAeFhs37598ODBP/74\nY2NjI/X8VKy+SKVSU1NTR0dHdnPp0qUffvhhcnJyaGiomZmZQqH4+OOPiSgiIoKI7t27949/\n/GP8+PGffPJJn8bQDjK5Qxpe4Vpl1vkhj65+4Wte5+Waueb7+UotNM9JnbCw0lhDFoM111je\n0FxjVapFjaYC3cUxBDsAAHhY2NnZbd26lds0tKdinZ2dvby8ysrK2E1PT88lS5akpaUFBQUF\nBwfn5uYWFhYuX77cw8ODiIqLi+vq6m7dusUubtfJ999/369DB4OBYAcAAA8pA38qlohSU1OH\nDx++d+/epKQkNze3xMTENWvWsF9VVFQQ0W+//fbbb7/pdYxgWHCPHQAAPCzYm+fefvtt1c3+\nv8eOYRhuWk59O5/Pj42N/eWXX+RyeUVFxdq1a83Mfp+RWbBgAdOzvhs8GDjM2AEAwMPCy8uL\niB555BHVTeOwcuXKY8eOdZsX4aGCYAcAAA+LTrnHaGJQZWVlenq6k5OTvgcC+odgBwAAMCAp\nFIrs7Ozi4uK9e/dKpVIEOyAEOwAAeHjc151zhn+nWkNDw8yZM/U9CjAsCHYAAPCwMKab6ojI\nycmptfX3xeGsrLRYuQ0eAgh2AADwsDCam+pYPB7P0tJS36MAw4LlTgAAAB5GMTEx6hd84fF4\n165du1t3R98jhfuAGTsAAICH0cqVK4ODg9XXLF682NTCvF+GA7qBYAcAAPAwEgqFU6ZMUV8j\nEAjaiJpJw6tg7/IUGg9Xo8WDK//H42usOWFirbkjEwfNNaZavCvWzF1zDX+U5hpzTbOeJlq8\ncFY7uBQLAAAAYCQQ7AAAAACMBIIdAAAAgJFAsAMAAAAwEgh2AAAAAEYCT8UCAAAMeIb/AjTo\nH5ixAwAAADASCHYAAAD9gWEYsVgcEBBgZ2fn7+8vFos1TrO1tLRER0f7+vra2toGBARs2LCB\nezksq7y8PDw83MPDw8rKysPDIzw8vLy8vC9PAgwdgh0AAEB/iIyMjIqKqqmpCQsLq6mpiYqK\nWrFihZr6lpaWcePGbd682cLCYt68effu3YuLi5szZw4XB0tLS/38/Pbv3z9s2LBFixYNGzZs\n//79fn5+paU6W+0WBhwEOwAAgD6Xn5+fkpLi6+tbUlKSnp5eUlLi6+srFosLCgp62iUhIaG0\ntHT16tUFBQWpqanFxcWvvfZadnZ2Xl4eW7Bp0yaZTJaZmXny5Mldu3adPHkyMzNTJpMlJib2\n12mBwUGwAwAA6HMHDhwgoujoaIFAQETW1tbR0dFElJGR0dMu3377LZ/Pj4+P5/F4RGRiYrJl\nyxYTE5MdO3awBWVlZUQ0bdo0bhf285UrV/rwTMCw4alYAACAPldSUkJEISEhXMvUqVOJSM1l\n0+vXrw8ePNjKyoprsbW1FYlEly9fZjeffvrpCxcurF+//oMPPhAIBC0tLRs2bCCiwMBAHY6c\nR2Sqqca0w1ljP6YdGrsh0w4LzQPqsNGiRot3xSoHaVHToLmG0aKG16ipolpzJ9pBsAMAAOhz\nEonExsbGweG/gcPR0dHGxqaysrKnXR577LGysjKpVDpo0CCuE4lE0tHRwW5+9NFHZmZmSUlJ\nqampIpGoqqqqra1t1apVmzdv1mZIeXl5WVlZ6mvq6urMra216Q0MBIIdAABAn5NIJEKhsFOj\nUChUE+xCQkIuX768bNmyzz77zN7eXiKRzJ8/n4ju3LnDFpiamtrY2PB4vLa2tps3bxKRiYmJ\ni4sLn8/XZkgVFRXnz59XX9PW1mZibq5Nb2AgEOwAAAD6HMMw7K1ynRrlcnlPu6xfv/7w4cNZ\nWVlOTk4ikej27dsBAQHOzs6mpr9f09y9e3dcXNyTTz6ZkpIycuTIvLy8iIiIVatWjRo1SvWa\nb08WLFiwYMEC9TUjRozocXxgkPDwBAAAQJ8TiUT19fWdGuvr611cXHraxcHB4cKFCxEREe7u\n7nfu3JkxY0Z2dnZTU5NIJGILPv30UyI6dOjQuHHjbG1tp02btnPnTiLatWtXn50HGDrM2AEA\nAPQ5kUh0/fp1mUxma2vLtshksqamptGjR6vZSygUpqamcpvV1dWtra2urq7sZnl5uYuLy/Dh\nw7mCoKAgIqqoqND9CcAAgRk7AACAPsc+qZqbm8u1nDp1iogmTJjQ0y5HjhzZsGFDVVWVagsR\nzZkzh910d3evq6tTvZhbU1NDREOHDtXx6GHgQLADAADoc0uXLiWi5OTk9vZ2IlIoFB9//DER\nRUREcDVSqVT1cm1dXV1cXNzWrVvZzaqqqsTERHt7ey7YTZkypa2tbdOmTey7KDo6OhISEojo\nmWee6aezAsODS7EAAAB9ztPTc8mSJWlpaUFBQcHBwbm5uYWFhcuXL/fw8OBqnJ2dvby82GWH\niWjevHnbtm1LTk4uLi52dXXNycmpra1NS0tjlzgmok2bNn333Xfx8fE5OTk+Pj7nzp27dOnS\nmDFj3njjDT2cIRgGBLv+sL1kZ+87cbX5fWqdR7+/JVDxx1JGZqadf4/tHe3sB/4fD08xxCOi\n9aNjej8SIoq79q3qUThqRtK1RqmLCeNZ9rHshxOhSf/bvpb94DPsj6bJnfd9rWt3PdSU/kLd\nHuV+D9RTP7rtZN+FLewHV4d32Q8hw2gAyfnjBG/f3dLpq4F4RkZ2OtTdGbEnYjQn2HdSU1OH\nDx++d+/epKQkNze3xMTENWvWqKm3srLKyclZt27dsWPHCgoK/Pz80tPTVd8zwT5dERcXd+LE\niczMzMcffzw6OjomJkbL5U7AKCHYAQAA9Ac+nx8bGxsbG9tTAXtFVZWzs7PqwxNd2dvbJycn\n62Z8YBRwjx0AAEB/YBhGLBYHBATY2dn5+/uLxeKuSa6TlpaW6OhoX19fW1vbgICADRs2tLa2\ndqo5ceJEUFCQjY2Np6fnxo0bufdSwMMJM3YAAAD9ITIyMiUlZdiwYWFhYWfPno2Kirpy5cr2\n7dt7qm9paRk3blxpaenYsWPnzZtXWFgYFxdXVFR09OhRbq3jffv2LV261NnZ+fnnny8pKXn/\n/fclEgm7mp2umBDZa6p5RK55nqi5zUljjfye5lhi2qL5fbKHWwQaa6jZVosamRY1LZprWjUt\n89zxk+ZOtIMZOwAAgD6Xn5+fkpLi6+tbUlKSnp5eUlLi6+srFosLCgp62iUhIaG0tHT16tUF\nBQWpqanFxcWvvfZadnZ2Xl4eW9Dc3PzWW2+5u7tfunQpMzOzqKjI399/165dpaWl/XVaYHAQ\n7AAAAPrcgQMHiCg6Opp9ptXa2jo6OpqIMjIyetrl22+/5fP58fHx7PyciYnJli1bTExMduzY\nwRYcPHhQJpOtW7eOfReFubn56tWrGYbJzs7uhzMCw4RLsQAAAH2upKSEiFRf4Tp16lQiUjO7\ndv369cGDB1tZWXEttra2IpHo8uXL7OZXX31FRC+88AJXMGXKlG3btnl5eel6+DBgINgBAAD0\nOYlEYmNj4+DgwLU4Ojra2NhUVlb2tMtjjz1WVlYmlUoHDRrEdSKRSLjHI27dumVtbU1EoaGh\np0+fdnFxmTx58ubNmx0dHfvyVMCg4VIsAABAn5NIJEKhsFOjUChUE+xCQkKUSuWyZcsaGhrY\nHubPn09Ed+7cYQuqq6utra1DQ0OPHTvm4OBQUVGxa9euJ598kq3XKDY2lqfJtWvX7v5xOBgQ\nMGMHAADQ5xiG4R5lVW1UfdNrJ+vXrz98+HBWVpaTk5NIJLp9+3ZAQICzs7PpHyvP19XVtbe3\n+/j4SCSSIUOG3L17d9GiRUePHo2Pj09K6ryaeldvv/32pEmT1NcsXrzYzELzU6hgOBDsAAAA\n+pxIJKqtre3UWF9f7+Li0tMu7Isl3nvvvVOnTlVWVs6YMWP//v1ubm7cLXSOjo5SqTQzM5N9\neMLBwWHPnj2DBw/OycnRZkhOTk5TpkxRXyMQCDq/PggMG4IdAABAnxOJRNevX5fJZLa2vy+f\nJpPJmpqaRo8erWYvoVCo+uaJ6urq1tZWV1dXdnPIkCHm5uZsqmM5Ozu7uLhUVFT0wRnAwIB7\n7AAAAPpcYGAgEeXm5nItp06dIqIJEyb0tMuRI0c2bNhQVVWl2kJEc+bMYTd9fHyqqqpksv8u\notva2lpdXe3h4aHr4cOAgWAHAADQ55YuXUpEycnJ7e3tRKRQKD7++GMiioiI4GqkUml9fT23\nWVdXFxcXt3XrVnazqqoqMTHR3t6eC3aRkZEdHR1r1qxhn5NlGCYmJqa9vT00NLS/TgsMDi7F\nAgAA9DlPT88lS5akpaUFBQUFBwfn5uYWFhYuX75cdXbN2dnZy8urrKyM3Zw3b962bduSk5OL\ni4tdXV1zcnJqa2vT0tLYJY6JaOLEic8+++yuXbvy8vLGjh178eLF8+fPjxo1KiYmRg9nCIYB\nwQ4AAKA/pKamDh8+fO/evUlJSW5ubomJiWvWrFFTb2VllZOTs27dumPHjhUUFPj5+aWnp0+b\nNo0r4PF4hw4d+uCDD06cOHHw4MHhw4evXbs2JiaGS346YUr0iFJDjfKe5n74LZ0fCu7KtslK\nY82QRoXGmlF3OzTWVNZpLKFbUlONNVdqNY/5RrWmfhp19itDsAMAAOgPfD4/NjY2Nja2pwKG\nYTq1ODs7qz480ZVAIIiPj4+Pj9fNEGHgwz12AAAAAEYCwQ4AAKA/MAwjFosDAgLs7Oz8/f3F\nYnHXKbpOWlpaoqOjfX19bW1tAwICNmzY0Nra2m2lUqmcPn161zWQ4WGDYAcAANAfIiMjo6Ki\nampqwsLCampqoqKiVqxYoaa+paVl3LhxmzdvtrCwmDdv3r179+Li4ubMmdNtHExOTj5x4kSf\njR0GDAQ7AACAPpefn5+SkuLr61tSUpKenl5SUuLr6ysWiwsKCnraJSEhobS0dPXq1QUFBamp\nqcXFxa+99lp2dnZeXl6nyqKiorVr1/bxGcDAgGAHAADQ5w4cOEBE0dHR7COr1tbW0dHRRJSR\nkdHTLt9++y2fz4+Pj2cvsJqYmGzZssXExGTHjh2qZTKZbO7cuYGBgViXGAjBDgAAoB+UlJQQ\nUUhICNcydepUIiotLe1pl+vXrw8ePNjK6r+radja2opEosuXL6uWRUZG3rlzJz093dRU89oc\nYPSw3AkAAECfk0gkNjY2Dg4OXIujo6ONjU1lZWVPuzz22GNlZWVSqXTQoEFcJxKJhH3PBCs9\nPT0jI+PQoUNubm73O6Sff/6ZfUeZGnV1dQJr6/vtGfQIwQ4AAKDPSSQSoVDYqVEoFKoJdiEh\nIZcvX162bNlnn31mb28vkUjmz59PRHfu3GELysvLIyMjIyIiZs2a9QBDunbt2vnz59XXMAwj\nECDYDSQIdgAAAH2OYZiua5EwDCOXy3vaZf369YcPH87KynJychKJRLdv3w4ICHB2dmYvucrl\n8nnz5rm4uLDvnH0ACxcuXLhwofqa8PDwDg1LsoBhQbADAADocyKRqLa2tlNjfX29i4tLT7s4\nODhcuHDhvffeO3XqVGVl5YwZM/bv3+/m5ubl5UVEcXFxly5dys/Pt+7jS6X5P+dFvfY39TUt\n3S+u9z9UF+BraZYV5p90cHTuVNOuRYpsb9fwgrMmmdTC0p5nouEpggc4lqJNZmpmYWJqrtrY\npk3ybddUIK/+97+9NfejBQQ7AACAPicSia5fvy6TyWxtbdkWmUzW1NQ0evRoNXsJhULVV4pV\nV1e3tra6uroS0cWLFxUKhZ+fX6dd2HnB+vp61fv5Htjs2bPNzc01ltlq8aZT1ZpbrQ1370pF\nokFdZjG1WWBZ3TMiDMNUSe4McrKzstI87PtVUVFpKzATCjW/HPZ+SSQWuuoKwQ4AAKDPBQYG\n/vTTT7m5uWFhYWzLqVOniGjChAk97XLkyJELFy689tprIpGIayGiOXPmEBE3dcepqKhQKBRs\no4mm+SothYaGhoaG6qQrVfn5+ceOHbtw4YKlpaVue1YoFObm5hkZGRMnTtRtz0T05z//OSIi\nQv2y0g8mPDxcV10h2AEAAPS5pUuXfvjhh8nJyaGhoWZmZgqFgr03LiIigquRSqWmpqaOjo7s\nZl1dXVxcnEwmS0pKIqKqqqrExER7e3s22KWkpHQ6hLe399WrV8vKyvrplMAgIdgBAAD0OU9P\nzyVLlqSlpQUFBQUHB+fm5hYWFi5fvlx1VWFnZ2cvLy8umc2bN2/btm3JycnFxcWurq45OTm1\ntbVpaWnsEscA3cICxQAAAP0hNTU1Pj6+qqoqKSmptrY2MTFx586dauqtrKxycnIiIiLKy8sP\nHz7s5eV1/PjxxYsX99uAYSDCjB0AAEB/4PP5sbGxsbGxPRUwTOfnK52dnVUfnlAPF2GBMGMH\nAAAAYDQQ7AAAAACMBIIdAAAAgJFAsAMAAAAwEgh2AAAAAEYCwQ4AAADASAz4YHfixImgoCAb\nGxtPT8+NGzd2dHToe0QAAACgjpeX17p163T+PjEi4vP5MTExI0eO1HnPRPT666//5S9/6Yue\nZ8+ePXv2bJ10NbDXsdu3b9/SpUudnZ2ff/75kpKS999/XyKRqF/vEQAAAPTL0dExISGhjzrf\nuHFjH/X8+uuv91HPOnwh7wCesWtubn7rrbfc3d0vXbqUmZlZVFTk7++/a9eu0tJSfQ8NAAAA\nQA8GcLA7ePCgTCZbt26dSCQiInNz89WrVzMMk52dre+hAQAAAOjBAL4U+9VXXxHRCy+8wLVM\nmTJl27ZtXl5e+hsUAAAAgN4M4GB369Yta2trIgoNDT19+rSLi8vkyZM3b97s6Oio76EBAAAA\n6MEADnbV1dXW1tahoaHnzp1zcXGpqKi4du3a8ePHL168aG9vr3H3ffv2icVi9TW//fabNl0B\nAAAAGIIBHOzq6ura29t9fHwkEsmQIUPu3r27aNGio0ePxsfHJyUladx91KhRc+bMUV9z48YN\nCwsLHY0XAAAAoG8N4GDn6OgolUozMzPZhyccHBz27NkzePDgnJwcbXYfO3bs2LFj1dfs3r1b\nBwMFAAAA6BcDONgNGTLE3NycTXUsZ2dn9pqsHkcFAAAAoC8DeLkTHx+fqqoqmUzGtbS2tlZX\nV3t4eOhxVAAAAAD6MoCDXWRkZEdHx5o1a9jXiDEMExMT097ersPlmwEAAAAGkAF8KXbixInP\nPvvsrl278vLyxo4de/HixfPnz48aNSomJkbfQwMAAADQgwE8Y8fj8Q4dOhQbG2tlZXXw4EG5\nXL527dqCggKBQKDvoQEAAADowQCesSMigUAQHx8fHx+v74EAAAAA6N8AnrEDAAAAAFUIdgAA\nAABGAsEOAAAAwEgg2AEAAIAuMQwjFosDAgLs7Oz8/f3FYjHDMGrqeT3rfedEVF5eHh4e7uHh\nYWVl5eHhER4eXl5erpOeW1paoqOjfX19bW1tAwICNmzY0Nraqn6XnqxcudLb2/vB9lU1sB+e\nAAAAAEMTGRmZkpIybNiwsLCws2fPRkVFXblyZfv27T3VT548uWtjfn6+tbV17zsvLS0dP358\nU1PT5MmTJ0+eXFFRsX///q+++urnn3/28fHpTc8tLS3jxo0rLS0dO3bsvHnzCgsL4+LiioqK\njh492m0kVaOysjI9Pd3Jyem+9uoWgh0AAADoTH5+fkpKiq+vb15enkAgaG5unjhxolgsXrhw\nob+/f7e7fP/9951afvrpp8DAwLS0tN53vmnTJplM9vnnn8+dO5dt+eKLL+bNm5eYmHjgwIHe\n9JyQkFBaWrp69eotW7bweDylUvnGG2+kpKTk5eVNnDhRix8VKRSK7Ozs4uLivXv3SqVSnQQ7\nXIoFAAAAnWHTUnR0NLusrLW1dXR0NBFlZGRo2YNcLn/11VdnzZo1e/bs3ndeVlZGRNOmTeNa\n2M9XrlzpZc/ffvstn8+Pj49n5+dMTEy2bNliYmKyY8cOLc+0oaFh5syZGzduvH37tpa7aIRg\nBwAAADpTUlJCRCEhIVzL1KlTiai0tFTLHj788MNbt251ew30ATp/+umniWj9+vUtLS1E1NLS\nsmHDBiIKDAzsZc/Xr18fPHiwlZUV12JraysSiS5fvqzhDP/g5OTU+gctd9EIl2IBAABAZyQS\niY2NjYODA9fi6OhoY2NTWVmp5e6JiYlr164ViUQ66fyjjz4yMzNLSkpKTU0ViURVVVVtbW2r\nVq3avHlzL3t+7LHHysrKpFLpoEGDuE4kEgn7Cntt8Hg8S0tLLYu1hBk7AAAA0BmJRCIUCjs1\nCoVCLYNdQkKCQCB4++23ddW5qampjY0Nj8dra2u7efNmW1ubiYmJi4sLn8/vZc8hISFKpXLZ\nsmUNDQ1sD/PnzyeiO3fuqD3FvoVgBwAAADrDMEzXZ0IZhpHL5Rr3vXHjxu7du1euXGlnZ6er\nznfv3h0XFzd69OiCgoLGxsbjx4+7urquWrUqJyenlz2vX7/+0UcfzcrKcnJycnNzc3V1vXfv\nnrOzs06egXhgCHYAAACgMyKRqL6+vlNjfX29i4uLxn3FYnFHR8fSpUt12Pmnn35KRIcOHRo3\nbpytre20adN27txJRLt27eplzw4ODhcuXIiIiHB3d79z586MGTOys7Obmpq6vYjcbxDsAAAA\nQGdEIlFjY6NMJuNaZDJZU1PTkCFD1O/Y3t6enp4+depUNZUP0Hl5ebmLi8vw4cO5lqCgICKq\nqKjo/bCFQmFqaur169dbWlqOHj2qUChaW1tdXV3VnmjfQrADAAAAnWGfNs3NzeVaTp06RUQT\nJkxQv+Px48erq6sXLFig287d3d3r6upUr6jW1NQQ0dChQ3vZ85EjRzZs2FBVVaXaQkRz5sxR\ncwp9DcEOAAAAdIa9kJqcnNze3k5ECoXi448/JqKIiAiuRiqVdr3umZWVRT28haI3nU+ZMqWt\nrW3Tpk3s+8E6OjoSEhKI6Jlnnullz3V1dXFxcVu3bmU3q6qqEhMT7e3t9RvssNwJAAAA6Iyn\np+eSJUvS0tKCgoKCg4Nzc3MLCwuXL1/u4eHB1Tg7O3t5ebFLB3NOnTo1bNgw9Zc+H6DzTZs2\nfffdd/Hx8Tk5OT4+PufOnbt06dKYMWPeeOONXvY8b968bdu2JScnFxcXu7q65uTk1NbWpqWl\nsUsc6wtm7AAAAECXUlNT4+Pjq6qqkpKSamtrExMT2ecV1Lh582ZFRcX48eN13jn7iMM777zT\n2NiYmZmpVCqjo6PPnDnTabmTB+jZysoqJycnIiKivLz88OHDXl5ex48fX7x4scZT6FOYsQMA\nAABd4vP5sbGxsbGxPRWwV0VVubu7d23UVef29vbJycl90bOzs3NqaqrGnrWh5elrhBk7AAAA\nACOBYAcAAABgJBDsAAAAAIwEgh0AAACAkUCwAwAAADASCHYAAAAARgLBDgAAAMBIINgBAAAA\nGAkEOwAAAAAjgWAHAAAAYCQQ7AAAAACMBIIdAAAAgJFAsAMAAAAwEgh2AAAAAEYCwQ4AAADA\nSCDYAQAAABgJBDsAAAAAI4FgBwAAAGAkEOwAAAAAjASCHQAAAICR4DEMo+8xGK4RI0a0M5R7\nubyX/dxsOd37wdzlO7MfTEwtOn2l7Gjr1NJTzVQLn96PhIhOtpX2ciREZMa0934kM2x8e98J\nAAw44eHhRLRv3z59DwT6iUwmW7FiRVZWlkKhkMlkROTt7X316lU1MUZjgVEy0/cAAAAAADTY\nuHHj/v37x44dO3PmTH2PxaAh2AEAAIChO336NBEdOnTo0UcfZVsWLVpUU1OjzzEZJAQ7AAAA\nMHSNjY1ExKU6IoqOjtbfcAwXHp4AAAAAMBIIdgAAAKADHR0dycnJ48ePt7Oz8/b2Dg8Pr6qq\n4r5tbm5evXr1n//8Z2tra19f39WrVzc3N3Pfent783g8hUIRExPj5uZmaWnp7e394YcfdnR0\nEBGPx7t69Sr7gcfjqe7CfmYYZv/+/ZMmTXJ0dPTw8Fi0aFF5eecHHxsbG9kBCASCoUOHRkRE\n/Prrr1oOQJsTVN9/v8GlWAAAAOgtpVL53HPP5eTkeHt7v/zyyzU1Nenp6ceOHcvLy3v88cfv\n3bvn7+9fWlo6evToV155pbi4OCkp6bvvvisqKrKysuI6iYiIKC4uXrBgQUtLy/79+9977z25\nXB4bG5uenr5mzZqqqqr09PRujx4REbFnzx5bW9tnnnnG2to6Nzf3+PHjSqWSK2hoaHjyyScl\nEsm0adOefvrpqqqqL7744uuvvz537tywYcM0DkDjCWrZfz9AsAMAAIDeSktLy8nJeemllzIy\nMvh8PhF9/fXXL7744qeffvqPf/zjk08+KS0tXbJkyZ49e0xMTJRKZURExN69ez/99NO///3v\nXCfV1dVFRUXm5uZENHPmzGeeeebIkSOxsbELFixISEioqqpasGBB10OfjvHMHQAAIABJREFU\nPHlyz549Hh4e33//vbu7OxHJZLIXX3zx+++/52piY2N//fXXS5cuPfHEE2xLZWXlU089FRMT\nc+DAAY0D0HiCWvbfDxDsAAAAoLf2799PRFu3bmVDDxG98MILW7duHTp0KBF9/fXXRLR582YT\nExMiMjExSUhI2Lt37zfffKMa7OLj49lQRURBQUFE1NTUpPHQX3zxBXtoNtURka2trVgs9vLy\n4mpOnjzJ4/FefPFF1R0bGxt/+OEH1RY1A1B/glr23w8Q7AAAAKC3ysrKBg0apPrUKo/HW716\nNfu5vLx88ODBIpGI+3bIkCHOzs7Xrl1T7cTH57+r6JuZaRtRLl++TESBgYGqjZ6enkKh8M6d\nO+zmjRs32tvb2Rv1VLW3/89S+WoGoP4Etey/H+DhCQAAAOgtuVyufRRjmZiYdMo9AoHgAQ7N\nTaF17Z/77Orq6ubmxnTR1vY/L0xSMwD1J6hl//0AwQ4AAAB6y9vbu6qqSvUpUSJavnz5mjVr\niMjDw6O6urq6upr7qrKysrq6WvVqaW8OTURnz55Vbbx27ZpUKuU2R4wYUVlZqbqgsVKpXLdu\n3T//+U/tj6LmBHvfv64g2AEAAEBvzZkzh4hWr17NTcIdPXp0z5497JTVCy+8QETr1q1jn1Tt\n6OhglxcOCwvr/aFfeeUVIlqzZs2NGzfYlqampqioKNWa119/vaOjIyoqihveP//5z8TExJaW\nFi2Pov4Ee9+/rvAetpfj3pcRI0a0M5R7ufNaOPfrZsvp3g/mLt+Z/WBiatHpK2VH55nenmqm\nWviQLpxsK+3lSIjIjNHBnQczbHx73wkADDjh4eFEtG/fPn0PBH6nUCiefvrp/Pz8J554YuLE\nibW1tUePHnV0dLx48aKLi0tra+uYMWMuX7781FNP+fn5FRUVXbhwwcfHp6ioyNLSkoi8vb2v\nXr3aKZPweDwvL6+ysrJuC1Rb/va3v6WmptrY2EyePNnW1vb06dMCgaC5ufn27dtsAcMwL7zw\nQlZWlpeXV1BQ0M2bN0+ePOnn5/evf/2LXW9F4wDUn6DG/vsNZuwAAACgt/h8/o8//piQkCAQ\nCDIzM8+fP//yyy8XFBS4uLgQkZWVVWFh4cqVK+Vy+YEDB9rb21evXl1YWMimut5LSUn57LPP\nnnrqqTNnzhw9enTixImnT5+2sbHhCng83uHDhzdv3mxra5uZmVlRUbFq1aqTJ09qn7rUn2Dv\n+9cVzNipgxm7nmDGDgD0CzN2AN3CjB0AAACAkUCwAwAAADASCHYAAAAARgLBDgAAAMBIINgB\nAAAAGAkEOwAAAAAjgWAHAAAAYCQQ7AAAAACMBIIdAAAAgJFAsAMAAAAwEgh2AAAAAEYCwQ4A\nAADASCDYAQAAABgJBDsAAAAAI4FgBwAAAGAkEOwAAAAAjASCHQAAAICRQLADAAAAMBIIdgAA\nAABGAsEOAAAAwEgg2AEAAAAYCQQ7AAAAACOBYAcAAABgJBDsAAAAAIzEAA52DQ0NvO6cPXtW\n30MDAAAA0AMzfQ/gwV27do2IvL29XV1dVdvt7e31NCIAAAAAfRrAwa68vJyIkpOTn332WX2P\nBQAAAED/BvClWHbGbuTIkfoeCAAAAIBBGNjBzsrK6ubNm7Nnzx4zZszChQsPHz6s70EBAAAA\n6M3AvhQrl8uDg4PZzfPnz2dkZCxdunT37t08Hk/j7o2NjezFXDXa2tp4ZvzeDxUAAACgHwzg\nYHft2rWOjo7Y2Njw8HA7O7sTJ0689dZbe/fufe6552bNmqVx982bN3/wwQcay+wdHHUxWAAA\nAIA+N1CDHcMwBw4cEAqFTz31FNvyyiuv2NjYhIWF7dixQ5tgl5iY+O6776qvGTNmjJI3gK9W\nAwAAwENloAY7Ho83ZcqUTo0zZsywtLQsLS3VsgdHRw2zcSYmJkrmAUcIAAAA0M+MajrKxMRE\nKBR2dHToeyAAAAAAejBQg112draHh8eePXtUG6VSqUQi+fOf/6yvUQEAAADo0UANdmPHjr11\n69aGDRskEgnb0tbW9uabbxJReHi4XocGAAAAoB8D9R67Rx555KOPPlqxYsXIkSOfe+45c3Pz\ns2fPVlRUvPTSS/Pnz9f36AAAAAD0YKAGOyKKiory8PDYvXt3fn7+3bt3//SnP8XExCxZskSb\nRewAAAAAjM8ADnZENH369OnTp+t7FAAAAAAGYaDeYwcAAAAAnSDYAQAAABiJ3l6KraurO3ny\n5IkTJy5evCiRSO7cuTN48GAXFxd/f/9p06YFBwdbW1vrZKAAAAAAoN6DB7srV64kJSWlp6fL\n5XIiMjU1FQqFbm5ud+/ePXfuXGFh4bZt2xwcHCIjI1esWCESiXQ3ZgAAAADoxoNcim1paVm5\ncqWPj8+RI0eWLVuWmZl5/fp1hUJRU1NTUVFx584dhULxn//8Z/fu3c8999w//vGP4cOHb9u2\nTalU6nz0AAAAAMB5kBm70aNHDx48+OjRoyEhIXw+v2uBqanpqFGjRo0atWzZsubm5kOHDiUm\nJp49e/bgwYO9HjAAAAAAdO9Bgt22bdtCQkK0XC7O2tp68eLF8+fPP3369AMcCwAAAAC09CDB\nbtq0afd9GDOzKVOmPMCxAAAAAEBLD7jcCcMwn3322dy5c9PT07nGK1euLFq0aMyYMfPnz//y\nyy8ZhtHRIAEAAABAsweZsWMYZtGiRRkZGUQ0ZswYtrGkpGT8+PFNTU1EdP78+czMzOzs7LS0\nNLzgCwAAAKB/PMiM3XfffZeRkTF27NiCgoI333yTbVy7dm1TU9Prr79eV/f/27vv+Kiq/P/j\nn0nPpJICJCQkkEASpEMILIiwdJAqoiIoKKg0dRX3JxaKhUVZdFdA9oGroFiWtQAqCqvgfsUC\ngqB+6SXSgyE9ISGTzJzfH3e/szFl5mZmIOT6ev5FTs58zrln7r15c2fmTu7//u//Dhw48I03\n3ti4caNHZwsAAIA6uRLsVqxYERgY+NFHH/Xo0cPPz09EcnNzN2/enJSU9Ne//jUiIqJ9+/bv\nvfdecHDwqlWrPD1hAAAA1M6VYHf06NH+/fs3a9bM3rJt2zal1MSJE+13PwkLC0tPTz927Jhn\npgkAAABnXAl2Z8+ejYuLq9ry2WeficjQoUOrNoaFhZ0/f96dyQEAAEA/V4JddHR0QUGB/Ueb\nzfavf/0rNDS0R48eVbudOHEiPDzc3QkCAABAH1eCXXJy8r///e+ysjLtx08++eT06dP9+/f3\n8fnvZ2x/+umnQ4cOde3a1TPTBAAAgDOuBLtp06ZlZ2dPnTr1zJkzp0+fnj9/vojcdNNN9g57\n9uy5+eabKysrp0yZ4qmJAgAAwDFX7mN36623vvnmm+vXr7d/92u7du3Gjx8vIpWVlTExMTk5\nOVq3CRMmeHCuAAAAcMCVYOft7f3xxx8vX75827ZtWVlZ6enp8+fPDwwM1H5rsVg6d+587733\nTp8+nbsTAwAAXDWuBDsR8fb2fvDBBx988MHq5Xx8CgsL3Z4VAAAA6s3F74oFAADAtcaVK3ap\nqan6Ox8+fNiFIQAAAFBfrgS7I0eOeHweAAAAcJMrL8WqGlJSUmptV0p5esIAAACoHe+xAwAA\nMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYhGduUJyZmVlru3CDYgAAgKvFkzco\n5sbFAAAADciVYMdthwEAAK5BvMcOAADAIK5gsKusrPzggw+uXH0AAABU5cpLsSJy5syZ559/\n/scff7x06VJaWtqcOXMyMjIuXrz4zDPP7N69u7CwsKioKD8//9KlS7xuCwAAcHW4EuyOHTvW\nrVu34uJi7ce9e/f+4x//eP/99xctWrRv3z57t+bNm7dv394z0wQAAIAzrrwUO2/evOLi4nvv\nvTczM7OkpGTXrl0dO3a86aab9u3bN3ny5MzMzMrKSqVUVlbWzp07PT5jAAAA1MrkwkulLVu2\nNJvNBw8e9PL6Ty787rvvMjIyAgIC8vPzAwICPD3JBtOmTRuxVB77eLu7hXwt7k/mUGqM9g+r\nWF14uLd4i0iQZLs/ExEpkkj3i7SXJu4XAfDbNHXqVBFZs2ZNQ08EuLa4csXuzJkz1113nT3V\niUiHDh1EJC4uzkipDgAAoHFx8VOxgYGBNX/09vb2wIwAAADgEu5jBwAAYBAEOwAAAIMg2AEA\nABiEizco/vDDD1NTU6s1ZmZm1mw8fPiwa0MAAACgXlwMdsXFxUeOHKnWWFFRUbMRAAAAV4cr\nwY5vCQMAALgG8R47AAAAgyDYAQAAGIQrwe6ll166fPlyvR6Sl5f397//3YWxAAAAoJMrwe7j\njz9u27btiy++mJWV5bTz4cOHH3vssVatWvG5CgAAgCvKlQ9PbN269W9/+9ujjz46d+7cfv36\n9e3bNyMjo02bNhEREcHBwYWFhTk5OQcOHNi1a9e2bdv27t0bHx//j3/8Y9iwYR6fPQAAAOxc\nCXYmk2nGjBkTJ05cvXr1Sy+9tH379rp6dujQYc2aNRMnTvTz83NjkgAAAHDOxfvYiUhYWNgj\njzzy8MMP//DDD1u3bv3hhx+ysrIKCgqio6NjY2MzMjKGDBmSnJxsMpk8OF0AAADUxfVgp/Hy\n8uratWvXrl09MhsAAAC4jNudAAAAGATBDgAAwCAIdgAAAAZBsAMAADAIgh0AAIBBEOwAAAAM\ngmAHAABgEB4IdiaT6c0336zZvnjx4piYGPfrAwAAQI8rdcWusrLy2LFjubm5V6g+AAAAqnE9\n2CUmJppMJu0bwyZPnmz6NV9f37Vr18bHx3tuqgAAAHDE9a8US0pKCggIEJEjR440b948LCys\nWgez2bxgwQK3ZgcAAADdXA9227Zt0/5hMpmWLl06adIkD00JAAAArnA92NkppdwvAgAAADd5\nINhZrdbFixdv2rSppKSk5m8PHz7s/hAAAABwygPBbunSpfPnz3e/DgAAANzhgdudrFmzJiws\nbPv27RUVFaoG9+sDAABADw8Eu1OnTk2ZMqV///4+Ph64/gcAAADXeCDYRUREmM1m9+sAAADA\nHR4IdlOmTNm8ebPFYnG/FAAAAFzmgWC3aNGiLl26jBkzZvfu3aWlpe4XBAAAgAs88K44Pz8/\n7R+ffvppzd/y+QkAAICrwwPBLiUlxf0iAAAAcJMHgh23IAYAALgWeOA9dtcCm802dOhQk8nU\n0BMBAABoMJ4Jdj///PPtt98eGxvr7+8vIq+88spLL71UVlbmkeJ6vPDCC1u3br1qwwEAAFyD\nPBDsTp8+nZ6e/sUXXxQWFmo3PTl58uQDDzzQt2/fgoIC9+s7tWfPnnnz5l2FgQAAAK5lnrnd\nSXl5+ffffx8fH6+1PP300y+//PKePXsWL17sfn3HiouLb7311j59+iQnJ1/psQAAAK5lHgh2\nW7ZsGTp0aExMzH+LennNmDFjwIABmzZtcr++YzNnzszLy1u3bp23t/eVHgsAAOBa5oFPxebl\n5TVv3rxme6tWrXbu3Ol+fQfWrVv35ptvvvfee3FxcfV97ObNmz/88EPHfbKzs4P8A12dHQAA\nwFXlgSt2ycnJZ86cqdZYWVm5Y8eO6667zv36dTl27NjMmTOnT59+0003XblRAAAAGgsPXLEb\nPHjwypUrDx06ZG/Jzs6eNWvWkSNHlixZ4n79Wlkslttuuy02NvbFF190rcKIESNGjBjhuM/2\n7dvFUulafQAAgKvMA8Fu/vz5GzZs6Nixo/ZjfHx8VlaW1WodNWrU3Llz3a9fq0WLFv300087\nd+4MCgq6QkMAAAA0Lh54KTYsLGzfvn333XdfcnJyQECAv7//oEGDNm3atHHjxiv3gYYff/yx\noqKiW7dupv9z5MgREdH+fXVuswIAAHBN8cAVOxEJCwtbvny5R0rpFBcXV+07ajMzMysqKrRG\nLy+DfKMGAACAfp4Jdlff3/72t2otqampR44c4YtrAQDAb5YHgl1qaqqD35K0AAAArg4PBDvt\nzW0AAABoWB54L5r6tdLS0t27d48YMWLMmDFlZWXu19fp8OHDSqmrNhwAAMC1xvMfMggMDOze\nvfsHH3yQmZk5f/58j9cHAABAra7Up0f9/PyGDx/+5ptvXqH6AAAAqOYK3haktLQ0Pz//ytUH\nAABAVVfkdidWq/Wbb755/fXXExMTr0R9AAAA1OSBYGcymer61aOPPup+fQAAAOjhgWBX7Rsg\nNGazedSoUY888oj79QEAAKCHB4IdtyAGAAC4FvCdqgAAAAZxZd9jVw03EAYAALhyPPMeu/z8\n/OzsbBGJiIjw8vLKyckRkejo6IiICPfrAwAAQA8PvBT72Wef+fn5DRo06MiRI7m5uRcvXjx2\n7NjgwYO9vb03b958uAr3xwIAAEBdPBDsFi5caDKZPvjgg7Zt22otycnJ77//vo+Pz4IFC9yv\nDwAAAD08EOz+/e9/33DDDcHBwVUbg4ODb7jhhp07d7pfHwAAAHp4INgVFBQUFxfXbC8uLtbe\nbAcAAICrwAPBrmPHjtu3bz916lTVxpMnT27fvr19+/bu1wcAAIAeHgh2M2fOLC4uHjBgwIYN\nG3JycnJycjZs2DBw4MCSkpLJkye7Xx8AAAB6eOB2JzfffPPDDz+8bNmycePGVW2/9dZb77nn\nHvfrAwAAQA8PBDsR+fOf/zx+/PjXX3/90KFDZWVlqamp48ePHzlypEeKAwAAQA/PBDsR6dmz\nZ8+ePT1VDQAAAPXlme+K/fnnn2+//fbY2Fh/f38ReeWVV1566aWysjKPFAcAAIAeHgh2p0+f\nTk9P/+KLLwoLCy0Wi4icPHnygQce6Nu3b0FBgfv1AQAAoIcHgt2iRYvKy8u///77+Ph4reXp\np59++eWX9+zZs3jxYvfrAwAAQA8PBLstW7YMHTo0Jibmv0W9vGbMmDFgwIBNmza5Xx8AAAB6\neCDY5eXlNW/evGZ7q1atzp075359AAAA6OGBYJecnHzmzJlqjZWVlTt27Ljuuuvcrw8AAAA9\nPBDsBg8evGXLlkOHDtlbsrOzb7vttiNHjlS7ZTEAAACuHA/cx27+/PkbNmzo2LGj9mN8fHxW\nVpbVah01atTcuXPdrw8AAAA9PHDFLiwsbN++fffdd19ycnJAQIC/v/+gQYM2bdq0ceNGb29v\n9+sDAABAD89880RYWNjy5cs9UgoAAACu8cw3TwAAAKDBeSDYWSyWhx56KDExUfvxtddea9q0\naUJCwpIlS5RS7tcHAACAHh4Idi+88MKLL75YWloqImfOnJkxY0ZeXl5+fv68efPWrFnjfn0A\nAADo4YFgt27dutjY2BMnTojIxo0bLRbLN998c/r06aZNm65atcr9+gAAANDDA8Hu5MmTN9xw\nQ0hIiIj8z//8T6dOnXr06BEeHj5o0KCjR4+6Xx8AAAB6eCDYBQQElJeXi4jVat2xY0efPn20\ndpPJZDKZ3K8PAAAAPTxwu5OUlJQdO3YUFhZu27YtOzt7wIABIlJaWrpt2zb7JyoAAABwpXng\nit1999138eLF+Pj4m266KTw8fODAgT/++GPr1q2zsrLuuusu9+sDAABADw9csZs8efKZM2de\nfvnloKCglStXhoSEXLhwwWw2L1y4cObMme7Xb2B+PtKhVdUG0921v76sXq1+b5eaPfX0qatn\nWo0+dT3WYZ1Qd+ZWs09d9MxNf3F3ZqKHC7PVwyOTdGVuDh7hkWX7v/rq74a6n5Fpmn3DPFLO\npUddoaGv8BYZbE8AGjUPBDuTyfT4448//vjj9pYhQ4ZkZma6XxkAAAD68c0TAAAABuGBK3ZW\nq3Xx4sWbNm0qKSmp+dvDhw+7PwQAAACc8kCwW7p06fz5892vAwAAAHd44KXYNWvWhIWFbd++\nvaKiQtXgfn0AAADo4YFgd+rUqSlTpvTv39/HxwPX/wAAAOAaDwS7iIgIs9nsfh0AAAC4wwPB\nbsqUKZs3b7ZYLO6XAgAAgMs8EOwWLVrUpUuXMWPG7N69u7S01P2CAAAAcIEH3hXn5+en/ePT\nTz+t+Vs+PwEAAHB1eCDYpaSkuF8EAAAAbvJAsOMWxAAAANcCvlIMAADAIDwT7MrKyp577rle\nvXpFR0c3adKkZ8+eS5YsuXz5skeKAwAAQA8PvBR76dKlHj16HDx4UESio6P9/f137dq1a9eu\nt956a9euXdziDgAA4OrwwBW7+fPnHzx48O677z5//nx2dvaFCxfOnz9/55137t+/f+HChe7X\nBwAAgB4eCHb/+te/unXrtnr16piYGK0lJibm1Vdf7dy589atW92vDwAAAD08EOwyMzO7du3q\n5fWrUt7e3t27dz9x4oT79QEAAKCHB4Jd69atv//+e5vNVrXRZrN9//33SUlJ7tcHAACAHh4I\ndoMHD967d++0adMuXLigtVy4cGH69On79u0bNGiQ+/UBAACghwc+FfvUU09t2bJlzZo1a9as\nadasmYj88ssvItKuXbtFixa5Xx8AAAB6eOCKXVBQ0J49exYvXtyjRw+LxWKxWNLT0xcvXrxn\nz56goCD36wMAAEAPD1yxE5HAwMB58+bNmzfPI9UAAADgAreu2FX7wMRPP/1UUFDg3nwAAADg\nIheD3ZYtW8aOHTtp0qSqjfPnz4+MjExPT//88889MTcAAADUgyvB7vHHHx82bNjGjRt9fH71\nSm6/fv3i4uL27NkzaNCgxx9/3EMzBAAAgC71Dnbbt29fvHhxSkrKN9988/rrr1f91YMPPnjy\n5Mlvv/22devWixcv3rlzp+fmCQAAACfqHeyWLl1qMpnWr1/fq1cvk8lU7bcmk6lnz54bN27U\nenpmjgAAANCh3sHu0KFDHTt27NSpk4M+HTp06NGjx8GDB92YGAAAAOqn3sHu/PnziYmJTrvF\nxsaeOnXKlRkBAADAJfUOdmFhYZmZmU677d+/PyEhwaUpAQAAwBX1DnY9evQ4cODAmTNnHPQ5\nePDg8ePHr7vuOjcmBgAAgPqpd7CbNm2azWYbPXr0pUuXau1QUFAwbtw4ERk/fry7swMAAIBu\n9Q52Y8aMufXWW/ft25eamrp8+fLz589r3z9hs9nOnj37wgsvtG3b9siRI+PGjZswYcIVmDAA\nAABqV+/vijWZTG+88UZCQsLSpUvvv//++++/39/fv1mzZr/88kt5ebnW4cEHH3zuuee8vNz6\nvjIAAADUiyvZy9fXd8mSJcePH3/ssccyMjKCg4PPnTtnNpu7du06d+7cw4cPv/jii35+fh6f\nKwAAAByo9xU7u1atWj377LPPPvusB2cDAAAAl/FqKQAAgEEQ7AAAAAyicQe7vLy8WbNmpaWl\nmc3mNm3aTJ06la+7AAAAv1mNONiVlZX16NHj5ZdfDgoKmjRpUnx8/Nq1a7t06XL27NmGnhoA\nAEADaMTBbuXKlSdOnHjiiSf27NmzevXq7du3P//88/n5+YsXL27oqQEAADSARhzsvv32WxGZ\nM2eOveXuu+8WkX379jXYnAAAABqO67c7aXDDhw/PyMho2rSpvSUnJ0dEuIUeAAD4bWrEwU67\nPiciVqv1woULp06devzxx0Vk0qRJeh6ulCooKHDcx2az8f0ZAACgsWjEwc7ulVdemTFjhoh4\ne3svW7Zs2rRpeh712GOPLVmyxGm3Jk2auDs/AACAq8IIwS48PDwpKencuXOXL19eu3btuHHj\nEhMTnT5q3rx548ePd9xn7Nixvr6+npklAADAFWaEYHfrrbfeeuutFovlmWeeefrpp2fNmrV5\n82anjwoNDe3WrZvjPv7+/h6aIwAAwBXXWN9AVllZefLkSe3TEho/P79FixaFhYV99dVXDTgx\nAACAhtJYg53Vak1KSpowYUK1dpPJZDabG2RKAAAADauxBjt/f/9evXp9+eWXVa/PrVu3rqCg\noHfv3g04MQAAgIbSiN9jt2TJkv79+99www1Dhw6Ni4s7fvz49u3bw8LC/vznPzf01AAAABpA\nY71iJyJ9+vT59ttvR40a9d13361du/bs2bPTpk07cOCAno/EAgAAGE8jvmInIt27d9+wYUND\nzwIAAOCa0Iiv2AEAAKAqgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAAwCAI\ndgAAAAZBsAMAADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAAwCAIdgAA\nAAZBsAMAADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAAwCAIdgAAAAZB\nsAMAADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAAwCAIdgAAAAZBsAMA\nADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGIRJKdXQc7h2tWnT5nj2cblZRET9\nvfpCmaaZan1UzZ411fXYmg930NO1ofXPRH9ZjxRxrawLA12h2brAtQ38Dbo6T4fxXLUdzJ2z\nluu+lCm9p6xZs+ZqjAU0HlyxAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAY\nBMEOAADAIAh2AAAABkGwAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEO\nAADAIAh2AAAABkGwAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADA\nIAh2AAAABkGwAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2\nAAAABkGwAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIBp3sMvM\nzLzjjjtiYmICAgJSU1PnzJmTm5vb0JMCAABoGI042B07dqxbt27r1q1LSEi44447goKCVqxY\n0blzZ7IdAAD4bWrEwW7BggUFBQUrVqzYuXPn6tWr9+zZ8+ijj55iXW73AAAgAElEQVQ9e/bR\nRx9t6KkBAAA0gMYa7JRSH374YWxs7KxZs7QWk8m0aNGigICAbdu2NezcAAAAGoRPQ0/ARcXF\nxVFRUQMGDKja6OfnFx4ezkuxAADgt6mxBrvQ0NCTJ09Wa9y2bduFCxeGDh2qp8Lu3bu3b9/u\nuE9+fr5YXZsgAADA1dZYg11Nn3zyyc033+zv7//000/r6b9///53333XcZ+SkpJG+2I1AAD4\nzTFCsDt9+vRjjz321ltvRUREvPnmm927d9fzqKlTp06dOtVxnzZt2hzPPu6JOQIAAFxxjft6\nlM1mW7VqVbt27d55552pU6ceOHBg2LBhDT0pAACAhtGIr9jZbLbJkye//fbbGRkZr732Wrt2\n7Rp6RgAAAA2pEV+xe/bZZ99+++3777//yy+/JNUBAAA01it2ly9f/utf/9qrV6+//OUvJpOp\noacDAADQ8BprsNu7d29ubu7Zs2cHDRpU87eff/751Z8SAABAw2qswS4zM1NEzpw5c+bMmYae\nCwAAwDWhsb7HbtKkSapuDT07AACABtBYgx0AAACqIdgBAAAYBMEOAADAIAh2AAAABkGwAwAA\nMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2AAAABkGwAwAAMAiC\nHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2AAAABkGwAwAAMAiCHQAA\ngEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2AAAABkGwAwAAMAiCHQAAgEEQ\n7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2AAAABkGwAwAAMAiTUqqh53DtatOm\nzfHs4zLeSTf1qgfW0HS3yf0iHuGRzakX07Rfbbv6e50TqNZTRKSB9t+rv0oOXDs7D/S4pnae\nxmvq1KkismbNmoaeCHBt4YodAACAQRDsAAAADIJgBwAAYBAEOwAAAIMg2AEAABgEwQ4AAMAg\nCHYAAAAGQbADAAAwCIIdAACAQRDsAAAADIJgBwAAYBAEOwAAAIMg2AEAABgEwQ4AAMAgCHYA\nAAAGQbADAAAwCIIdAACAQRDsAAAADIJgBwAAYBAEOwAAAIMg2AEAABgEwQ4AAMAgCHYAAAAG\nQbADAAAwCIIdAACAQRDsAAAADIJgBwAAYBAEOwAAAIMg2AEAABgEwQ4AAMAgCHYAAAAGQbAD\nAAAwCIIdAACAQRDsAAAADIJgBwAAYBAEOwAAAIMg2AEAABgEwQ4AAMAgCHYAAAAGYZBg99BD\nD6Wmpjb0LAAAABqSEYJdVlbWunXrGnoWAAAADcynoSfguoqKis2bN+/du/e1117LycmJjIxs\n6BkBAAA0pEYc7AoLC8eOHdvQswAAALhWNOJgFxkZWVZWpv07MDCwYScDAADQ4BpxsDOZTAEB\nAQ09CwAAgGtFIw52bnr++eeXLFniuE9hYaH4XZ3pAAAAuOu3G+wmTJjQqlUrx31eeOGFnWd3\nXp35AAAAuOm3G+wSExMTExMd9/nkk0925hLsAABA42CE+9gBAABACHYAAACGQbADAAAwCIId\nAACAQRDsAAAADMIgn4pVSjX0FAAAABoYV+wAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAA\nwCAIdgAAAAZBsAMAADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAAwCAI\ndgAAAAZBsAMAADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAAwCAIdgAA\nAAZBsAMAADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAAwCAIdgAAAAZB\nsAMAADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDYAQAAGATBDgAAwCB8GnoC17wLIm+L\nBIjYRCwiASJWkUoRf5FKEZuIn7T8rKWIBAcHFxUV+fj4mM3m/Px8s9ns7++fm5sbGhrq6+ub\nnZ0dFRUlIjk5OdHR0VarNT8/Pzo62mKxlJSUREREyFkRq4ifSKWIEvEVqRAxifiIWES8RbxF\nykV8RbxELov4i4jIZZFAESVS/n+TrBDxF7HWv5rpP/9I+SolLy8vOjq6oqKiqKgoMjKyvLy8\ntLS0SZMmpaWllZWVoaGhxcXFXl5eQUFBhYWFfn5+gYGBeXl5wcHBfn5+OTk54eHhPj4+VTe5\nadOmlZWVBQUFUVFR9mplZWUWiyUsLExOi4iIr4hFxEvafdPOvoDVq12osqUWZ5tsEfES8REp\nF/GpYwG1avVfwHbftrM/uRcvXoyIiPDy8rp48WJ0dLTNZqu2gJcvX758+XJ4eHjNBSwoKPD3\n96+6gBcvXmzSpIm3t/fFixerLqCDp6PaAv5qky+L+NW2yXXvz1JR/2oe2QOvzP78q022V6u5\nyQ6qeXoB233brq6jw35CsB8dly5dstlsISEhDk4vde2B9mr2PbBqNW9vb20PDAgICAgIuHb2\n55KSEu2M6uD0cvHixdDQ0L59+165cz/QSHHFzpHx48eP/v1ouSxtm7aND4v3snilxaTFBMf4\nWf3SYtKiAqLMYk6LSSsuLi4qKhKRgoIC7ZSUn59fWloqIrm5uZcvX7bZbLm5uRaLpbKyMjc3\n12q1lpeX5+TkiEhZWVleXp6IRAdEB6rAtJi0Jr5NQr1D02LSgk3BEX4RaTFpAbaAZuZmaTFp\nPhU+LUJapDZPlcuS2CQxOTpZyiU5KjkhPEEuS1pMWouQFj4VPmkxaU0Dm2rVIvwiQrxC0mLS\nQr1Dm/g2SYtJC1SBTQObatVig2PTYtLksiSEJ7SJbiOXJSkqyWKx5OTkKKUuX76cm5srIpcu\nXSooKBCRkpKSwsJCESkqKrJv8qVLl0QkLy9P2+ScnJzy8nKr1Zqbm1tRUWGxWHJzc202m71a\naWmptsn2amE+YWE+YWkxaUGmoKiAqKrVqi1g68jW2tPRMrylqdyUFpMWExTjW+mbFpMWHRCt\nPR3hPuH/WUCv4Ej/yLSYtAD1nwX0tnjHhcbZFzApKkkuS5voNvYFjA2OrbaA9qcjxCtEezq0\nBdQmWVZWZt9k7cmtrKy0L6D9yS0tLc3PzxeR4uJi+wIWFxdXW8Cq1bQF1KrVXECtWklJifa8\nhPmEhfuGp8WkmcUcFRCVFpPmZ/WLCY5Ji0nzsnjFh8W3bdpWLkvryNb2BXSwP4f7htufDm0B\n/W3+zYOap8WkeVd4x4XGpTRLkcvSKqKVfQFbhrW0L6D96bhG9ufEJolyWVKbp8aFxnlbvNNi\n0pqZmwWogLSYtEj/yGCvYK1auM9/FjA6IDotJs230jcmKCYtJs1UbmoZ3tK+gK0iWsllSWmW\nYl/A5kHN7QsYZApKi0mrtj9rT4e2gNrTYd+fKyoqqp0Q7EeH/aCzH2uFhYXa6cW+z2hHh1Iq\nJyen1mplZWXVDmH7yaqoqKhatWtnf65ardYzqtVqzcnJ6dChw/jx4z17zgeMQMGhH3/8UURy\nc3M3b95sNpuVUqtXr27Tpo1SasGCBf3791dK3X333ZMnT1ZKDRkyZN68eUqp9u3bL1++XCkV\nHh6+YcMG7SS1e/fuQ4cOiUhWVtbnn3/u7e2tlFq7dm1CQoJS6plnnundu7dSasaMGbfccotS\nauTIkQ8//LBSqmvXrsuWLVNKNW3adP369eXl5SLy9ddfnzhxQkROnTr15ZdfikhlZeXbb78d\nExOjlHr++efT09OVUg888MDYsWOVUuPHj589e7ZSqmfPnn/605+UUnFxcevWrVNKicgXX3xx\n9uxZETl69OjOnTtFpLS09L333ouMjFRK/eUvf+nUqZNS6o9//OPw4cOVUhMnTrznnnuUUn37\n9l20aJFSqnXr1q+++qpSyt/ff8uWLdnZ2SKyf//+vXv3ikhBQcGHH34YEhKilFq1alVqaqpS\n6oknnhg4cKBSasqUKVOmTFFKDRw48IknnlBKpaamrlq1SikVEhLy4Ycfaqf7vXv37t+/X0Sy\ns7O3bNni7++vlHr11Vdbt26tlFq0aFHfvn2VUvfcc8/EiROVUsOHD//jH/+olOrUqdNf/vIX\npVRkZOR7772n/YXYuXPn0aNHReTs2bNffPGFdiysW7cuLi5OKfWnP/2pZ8+eSqnZs2ePHz9e\nKTV27NgHHnhAKZWenv78888rpWJiYt5+++3KykoR+fLLL0+dOiUiJ06c+Prrr0WkvLx8/fr1\nTZs2VUotW7asa9euSqmHH3545MiRSqlbbrllxowZSqnevXs/88wzSqmEhIS1a9cqpby9vT//\n/POsrCwROXTo0O7du0WkuLh4w4YN4eHhSqnly5e3b99eKTVv3rwhQ4YopSZPnnz33Xcrpfr3\n779gwQKlVJs2bVavXq2UMpvNmzdv1v6C/vjjj+zP7M9G2p9rnrEBcMUOAADAIAh2AAAABkGw\nAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2AAAABuG9cOHC\nhp7DNS0oKEgpNWLEiJCQkKCgoL59+wYFBUVGRmZkZAQEBLRs2bJTp06+vr5paWkpKSleXl7d\nu3dv2bKliNxwww3a1+8MGzYsMjLSYrGMGjUqIiLCZrPdeOONoaGhgYGB/fr1Cw4ObtKkSa9e\nvQIDA+Pi4rp06eLn55eSkpKamurt7d21a9fExESTyXT99dc3b95cKTV48ODIyMjKykqtWmVl\n5ciRI8PCwvz9/QcMGBAcHBweHv673/3ObDbHxsZ27drVz88vOTm5Xbt2Pj4+nTp1at26tclk\n6t27d2xsrFJq0KBBERERSqmRI0dGRkZWVFSMHDkyPDzc29t78ODBwcHBoaGhffr0CQoKatas\nWffu3f39/Vu3bt2+fXtfX98OHTokJyd7eXn16tWrRYsWIjJgwIDIyEibzTZixAjt68xHjRrV\npEkTERk2bFhISEhwcLC2gFFRUT169AgICEhMTOzYsaOvr2+7du3atm3r7e2dnp4eHx8vIv37\n99e+gFxbwIqKitGjRzdp0kSrHxISYjabb7jhBu3p6NmzZ2BgYHx8fOfOnf38/FJTU1NSUry9\nvbt165aQkKA9Hc2aNVNKDRkyRKumLaDVar3xxhvDwsICAwP79+8fFBSkLWBgYKB9Adu2bZuW\nlubt7d25c+dWrVqZTKY+ffpoX3U1ePBg7TmttoA+Pj6DBg0KCgoKCwvr3bu32Wxu3rx5t27d\n/P39k5KSrrvuOh8fn44dOyYlJZlMJm0BlVIDBw607yH2SYaHh5tMpqFDh4aEhISEhFx//fVm\ns7lp06bp6en+/v6JiYkdOnTw8fFp3759mzZtvLy8MjIytG+R+v3vfx8VFaWUGj58uPZ0aAvI\n/sz+bJj92c/Pr6H+NADXLJNSqqHnAAAAAA/gpVgAAACDINgBAAAYBMEOAADAIAh2AAAABkGw\nAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2AAAABkGwAwAA\nMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDvnHnroodTU1JrthYWFptp89dVX9j6lpaWPPfZYp06d\nQkJCevbsuXDhwrKysnoNpGcUEcnMzLzjjjtiYmICAgJSU1PnzJmTm5tbtUNeXt6sWbPS0tLM\nZnObNm2mTp166tSpamPp6eN4TfQUqdea2Gy2oUOHmkymqo21LoimXkunc21FZOvWrddff31w\ncHDbtm2ffvppq9Var03WOWHHa6uniJ61PXbs2NSpU5OTkwMDA5OTk6dOnXrs2LH6TtXxQPoX\n1ulWK6VWrlzZs2fP0NDQjIyMlStXKqVcHsjBfuugQ72ePscDOT1O63V06NmiWo+gelWoq4+e\nxdd/SnE6GQfHoAv7G2BgPg09gWtdVlbWunXrIiMja/7q+PHjIpKamtqiRYuq7WFhYdo/SktL\ne/ToceDAgfT09Ntuu+27775btGjRnj17Pvroo5rn2boGcjqKiBw7dqxHjx4FBQUZGRkjR478\n/vvvV6xYsXHjxh9++EErWFZW1qNHjxMnTnTr1m3SpEnHjx9fu3btpk2bfvrpp7i4OK2Inj5O\n18RpkXqtiYi88MILW7durdY4YMCAmj137twZFBRUr6XTs7YismbNmrvuuis6OnrUqFH79++f\nP3/++fPnV61apX/ddE5YHK6t0yJ61vbAgQO9evUqKSkZMGDAgAEDMjMzX3/99ffff//bb7+9\n7rrrdE7V6UA6F1bPVs+cOfNvf/tbq1atRo8e/dVXX82ePfvQoUMrVqzQfluvgRyM4riD/qfP\ncR2nx2l9jw6nWyR1HEH1quDyqUn/KcXpZBwfg/Xd3wCDU6iNxWLZsGHDk08+qZ0pUlJSavZ5\n5513ROSTTz6pq8i8efNEZO7cuTabTSlltVrvu+8+Efnqq6/0D+R0FKXUbbfdJiIrVqzQfrTZ\nbI8++qiITJs2TWtZunSpiDzxxBP2hzz//PMiMmPGDHuL0z561sRpET1rYrd7924fHx89O6r2\nX/N33323aqPTpdOztiUlJSEhIQkJCVlZWUqp8vLyjIwMk8m0f/9+nZusZ8J61tZpET1rq+0q\n77zzTrVFmDhxos5R9AykZ2H1bPW3334rIp06dbp06ZJSqqSkpFOnTiKyc+dO/QM5HcWFxa91\nf3Nax+lxqvPo0D/huo4gPRXcPzXpPDScDuT0GNS5vwG/EQS72l28eLFq/K31xPf000+LyM8/\n/1xXkQ4dOvj6+paWltpbioqKvLy8qv4RdTqQ01FsNltQUFBsbGzVxvLy8oCAgFatWmk/jhs3\nTkR++eUXewftBaCePXvaW5z20bMmTovoWRN7e1JSUr9+/ZKTkx0Hu/Ly8nbt2t10003V2p0u\nndMOSqlXX31VRFavXm1veffdd0Xkueee037Us7ZOJ6xnbZ0W0bO2Xbp0EZG8vDx7S15enoh0\n6dJF5yh6BtKzsHq2evbs2SKyfv16e8v69etFZPbs2foHcjpKfRe/rv3NcR09x6nOo0PnhB0c\nQXoquH9q0nloOB3I6TGoc38DfiN4KbZ2kZGR9re2BAYG1trn+PHjgYGBp06dmjt37smTJ9PS\n0saOHaudyzQnTpxo1qxZ1YeHhIQ0b9784MGD+gdyOkpxcXFUVFS1V4v8/PzCw8Ptb98ZPnx4\nRkZG06ZN7R1ycnK0bvYWp330rInTInrWRDNz5sy8vLx///vfAwcOrHUsu+eee+7s2bPbtm2r\n1u506Zx2EJH3339fRMaMGWNvGThw4PLly1NSUnRusp4J61lbp0X0rG3fvn337du3YMGCJUuW\nmM3m0tLShQsXikifPn10jqJnID0Lq2er9+/fLyKDBw+2twwaNEhEDhw4oH8gp6PUd/Hr2t8c\n19FznOo8OnRO2MERpKeC+6cmnYeG04GcHoM69zfgt6Khk2UjIHX8j/Z3v/udt7d3tfW86667\ntJdRlFLt2rXz8vK6ePGi/SHnzp0TkWbNmukfyOkotfr8889FZOjQodXaKysrz549+/XXX/fr\n109+/Z/gevWpa02cFtG5Jm+88YaIvPfee0op7fRd10Dnzp0LCAhYtGhRzV85XTo9a9uxY8eg\noKDs7Ozhw4ebzebk5OR777236hWveq2b4wlrnK5tXUX0rG1FRcXDDz8sIv7+/gkJCf7+/iLy\n8MMPWywW/VN1OpALO22tW922bdvg4OBqjcHBwampqa4N5HRtnXZw+vTprKOpdpzW94zhYCD9\nR5Ceqbp5atJ5aNQ1kNNj0LWTJGBUBDvn6jrxaf8TffLJJzMzM3Nyct56662oqCj7yVQp9eCD\nD4rIqFGjCgoKlFLnzp3Tzmu+vr76B3I6Sk2bN282m83+/v67d++u9iv72429vb2XLVtW64lP\nTx+nfwzqKqJnTY4ePRocHDx9+nTtR8d/lmbMmBEREVFYWFjzV06XTs/aNmvWrGnTpunp6SIS\nGxvr5eUlIgkJCdr867tujies0fOHttYietbWZrMtWLCg6jvxvby8li1bVq+pOh3IhZ221q0O\nDg5u2bJltcaWLVuGhYW5NpD7wc7p06ezjqrtOK3vGaOugep1BLkc7PQvvs5Do66BnB6DLuxv\ngIER7Jyr9Vxjs9k+++yz77//vmrjpk2bROT3v/+99mN+fn7Lli2105n2vuCePXtGR0c3b95c\n50B6Rqnq1KlTt99+u4hERETU+lbid955JykpKSAgQEQ6dOhQ67tS9PRx+segriJO16S8vLxb\nt25t27YtKSnRWhz8Wfr55599fX2feeaZmr9yunQ611Z773n//v3Pnz+vzX/kyJEi8tBDD+nc\nZJ0TtnO6tnUV0bO/rV69WkS6dOmya9euoqKiLVu2xMfHi8jWrVv1T9XxQPXdaR1sdVBQUEJC\nQrXG+Pj4wMBA1wZyM9jpefr01KnrOK3vGaPWgep1BDmdal196rX4eg4NB5NxfAy6tr8BBkaw\nc07PiU9jtVoDAgKqvm6Sm5s7ffr01q1bBwYG3njjjbm5uYGBgZ07d3ZnoJqjaI0vv/xyUFCQ\nl5fX1KlTtY+P1aW8vPzJJ58UkeHDh7vWR+dUay3ieE0ee+wxX1/fqqdpB3+W5s6d6+XlpZ3u\n9ah16Rx3iI6ONplMVdczOzvbZDK1b9++1gqO103PhJ2urYMiTve39u3bi8iJEyfsLR9//LGI\njBs3rl5TrdeOrXSsfK1bnZSUFBoaWq0xODg4KSnJtYHcDHb697e66jg9Tuu7sDUHqtcR5GCq\n9e2jnC2+ntNOrQPV9xh0OhPA2Ah2zukPdkqp2NjYqKioun574cIFERkxYoSbA1UbxWq1Tpw4\nUUQyMjIOHDhQrXNFRcXPP/9c9Y07SimbzRYWFmb/q6mnj9Op1reIptqajBgxQuqWn59fdbhm\nzZoNGTKkrsq1cvwE1ezQsWPHFi1aVOvTokULs9ms6rnJOifseDeo11bX3N/8/f2rfTCzsLBQ\nRKpFh/qureMdW+N45Wvd6t69e4tIUVGRvaWoqEhE+vTp49pA7gS7eq1JrXUcH6e1crqwNQfS\nfwQ5mKoLfTT2xXftbFDrQI6PQaczAX5r+OYJF23evDk5OVn7HL5dTk7O+fPnO3bsqP24adOm\nhQsXaqdme4uI3HzzzR4cRUSeffbZt99++/777//yyy/btWtXrYjVak1KSpowYUK1dpPJZDab\n9fdxSk8Rp2sSFxeX8mu+vr4iov1be3uNZsuWLb/88sukSZNqnYzTpdO5ttddd92FCxeKi4vt\nLWVlZb/88ot2C4l6rZvjCevkoIie/S0hISE3N9disdhbsrOzRUR7QVbnVB0PpHNh9dA+q7t9\n+3Z7i/ZZ1N/97neeHUgP958+x8epeOKMIfU5gtzhdPE9ckrROD4Gr/JuADQCDZ0sGwGp7T+R\nv/zyi7+/f1xc3Llz57SWy5cvazcgXbdundainWvsb8bKyspKSEgICwvT7raqZyA9o5SVlUVG\nRvbq1cvBW5J79+7t7e29Y8cOe8vrr78uIlXvxaWnj+M10VOkvmui6n4hafr06SJS1+tiTpdO\nz9oqpXbs2CEi9957b2VlpVLKZrM99NBDIjJv3jydm6xzwnZ1ra3TInrWdubMmSIyf/58bW+p\nrKy88847ReTFF1/UP1XHA+lcWD1bfeTIERHp27dvRUWFUspisfTt21dEjh075tpAjtfWcQed\nT19ddfQcpy4cHU63SF2Zl2L1LH69TikOJuP4GHRtfwMMjGDnXF0nvuXLl4tIaGjorbfeescd\nd7Ru3VpEJkyYYD9xl5aWdu7cWUT69et3++23R0dHi8jatWvrNZDTUb7++msRiY+PH1Abrc+O\nHTt8fHy8vLyGDx9+zz33/P73vxeRsLCwqu9i1tPH6Zo4LVLfNVF1/1lq3bq1/c6utXK6dE47\nKKVsNtuwYcNEpEOHDnfddVe3bt1EpH379va/tfrXzemENY7/0Dooomdt8/PzW7VqJSI9e/a8\n++67tUsa3bt3r3a7E8dTdTqQnoXVudVTpkzRZvvoo4/26NFDqnxPgwsDuRPsdD59ddXRc5y6\ncHQ0VLBTOha/XqcUBwM5PQZd2N8AAyPYOefgxPfpp5/edNNNiYmJ4eHh119//WuvvVbtVJKd\nnT19+vQWLVoEBgb26dNny5YtLgzkeJR169bpuSK7e/fuMWPGREVF+fn5tW3bdtq0aWfPnq02\nkJ4+TtfEaZF6rYmq48/SyZMnxeEXYWmcPkFOOyilLl269OSTT/bo0SMoKKhDhw7z5s2rdgVF\nz7rpnLByuLZOi+hZ24KCgj/84Q/t2rULDAxs3779Y489VvWrDnRO1elAeha2qrq22mKxPPXU\nU4mJib6+vq1atVq8eLF29c61gVwOdvqfvrrq6DxO63t0NGCwUzoWX/8pxfFATo/B+u5vgIGZ\nlFIOTjcAAABoLPjwBAAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2AAAA\nBkGwAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBAAAYBMEOAADAIAh2AAAABkGw\nAwAAMAiCHQAAgEEQ7AAAAAyCYAcAAGAQBDsAAACDINgBv9KvXz+TyRQREVFRUdHQc3FRamqq\nyWS6+uMqpQYPHvzSSy9pP5pMJqfTMJlMqampen5ltVrfeeedAQMGJCQkBAYGtm3b9sYbb9yy\nZYtSSuuwdevWlJSUsrIyT2wKADRWBDvgv86fP//ll1+KSH5+/rZt2xp6Oo3M6tWrDx06dM89\n93i8stVqHTly5MSJE//3f/83PT198uTJycnJ27ZtGzZs2J133qllu8GDB0dHRz/xxBMeHx0A\nGhGCHfBf7733nnbZSUT++c9/1vfhAwYMSExM9Py0GpTOjXMbz7MAAAiJSURBVCosLPzjH//4\nhz/8ISAgwONzWLFixaeffjphwoSTJ0++9957q1ev/uSTT37++ef09PR169atW7dOREwm06OP\nPvriiy8ePnzY4xMAgMaCYAf81/r1600m06pVq0JCQjZu3GixWOr18HPnzp06deoKza2h6Nyo\n1atXl5SUTJw48UrM4fPPPxeRP//5z2az2d7YvHnzFStWiMgnn3yitQwZMiQyMnLZsmVXYg4A\n0CgQ7ID/OHPmzDfffNOnT5/WrVuPGDGCV2P1s9lsL730Ur9+/Zo3b34l6mdlZdXa3rlz56VL\nl44YMUL70dfXd/z48W+88UZubu6VmAYAXPsIdsB/aK+93nLLLSIyduxYqfFqrPahhIqKiiee\neCIuLi4gICA1NfW5556zWq0iYjKZjhw5IjU+NFBUVDR37tyOHTuazeb4+Pjp06efPn26almr\n1frCCy/06tUrNDQ0NTV16tSpFy5c0PlwpdTrr79+ww03NGnSJDk5+Y477jh27Fi17XJcwbWN\nqubHH388e/Zs37599a51PXXv3l1ERo8evXnzZpvNZm/38/ObO3fu5MmT7S3XX3+9xWL57LPP\nrtBMAOBapwAopZRKT0/38vLKyspSShUVFfn7+4eHh5eXl9s7pKSkiMidd97ZoUOH//f//t+c\nOXNCQ0NF5KmnnlJKrVu3Trtepb3rS3tIQUFBq1at/P39R40aNWvWrJtuuik4ODgyMjIzM1Pr\nYLVatbf0paamTps2bdSoUd7e3k2bNj1+/Lieh999990iEhISMnr06IkTJ7Zo0SI6OjoyMtJ+\naDut4MJG1bR48WIR+fTTT6s26jnDiIivr29KbUQkJSVF63bu3Dn7J2Rbtmw5ffr0f/7znzk5\nOTULHj9+XESmTJnieFwAMCqCHaCUUidOnBCR/v3721tuvPFGEdm8ebO9RUsbQ4cOtae97du3\ni0i3bt2qdqhads6cOd7e3gcOHLC3nD9/vnnz5hMnTtR+fPXVV0VkwoQJFotFa/nggw9E5P77\n73f68H/9618ikpycfPLkSe23RUVFAwcOrJqonE7AhY2qacKECSKihVE7ncHOAXuwU0pdunRp\n7dq1o0aNCgkJ0X7r5eU1atSo/fv3Vy1otVq9vLy6dOnieFwAMCofly/1AUZS9XVYzbhx4z7+\n+ON33313+PDhVXs+9dRTfn5+2r+vv/56ESkpKamr7GeffWYymcaNG1e1saio6IsvvtD+/frr\nr4vI0qVLfX19tZYxY8YsXbo0Pj7e6cP/8Y9/aI9NSEjQfhUSErJy5UotiumcgAsbVZP2HriI\niAj9D7FLSUmp9XOs1V75NZvNd95555133llRUfHdd99t2bLlrbfe+vDDD7/44otdu3alpaVp\n3by8vCIiIs6fP+/CTADACBo6WQLXhM6dO9d6gISFhdkvZWmB6dKlS1UfKFUuLNW8uFXXvT/8\n/Py0Dk2bNo2KiqprVo4f3rNnTxG5ePFitUdpAUvnBFzYqJo6dOggIvaLjvYiTh8ov74sV9ev\nKioqKioqqnWwWCz33XefiEyePLlqe6tWrXx9fR2PCwBGxYcnADl69OgPP/wQEBBQ7W1eQUFB\nhYWF1d6JX/WOG061aNEiLi6u5oFXXl6udbBYLD4+dV44d/xw+0W+ary8vHRWcG2jaoqKihKR\nwsJCd4o4EBkZGRMTU63R19f32WefFZGDBw9WbS8oKGjatOkVmgkAXOMIdoCsX79eRGbPnn34\n1x5//HEReffdd12u3KZNm6ysrOzsbHuLzWZ7/PHHX3nlFe3H1NTUCxcuVP0YrIhMmzbtkUce\ncfpw7fMEX331VdXHHj9+PCcnR/8EPCI2NlZEqo7rWa1bt87JydmzZ0+1du0l16ovPVut1oKC\nAm0+APAbRLAD/hPsJk2aVK39tttuE5H63qlYu1GIZsaMGVardfbs2ZWVlVrLK6+8snjx4tLS\nUu3Hm2++WUTmzp1r7/DRRx+9+uqr2hU1xw/X7gb8yCOPnDx5UvttSUnJ7Nmzq07G6QRc2Kia\nMjIypMaVMw+69957ReT222//6aef7I1FRUV/+MMfRGT06NH2xkOHDimltPkAwG+Rx1/cBRqX\n/fv3i0iHDh1q/W3v3r1F5OOPP1Z1vNtMqrwVrEuXLiIyderUZ599Vmux2WyjRo3S+kybNm3Q\noEEi0q1bt9LSUq2DxWLR3irXrl276dOnjxkzxtvbOyoq6ty5c3oern0xa3Bw8OjRoydNmhQX\nF9e2bdsWLVrY5+m0ggsbVdPRo0dF5JFHHqlWRERur02tAzmYQ2VlpfbBWx8fn44dO44dO3bA\ngAHax2PvuOMOm81mf9Tf//53Efnoo4/qmioAGBvBDr918+fPF5Hnnnuu1t+uXLlSSw9KRwba\nsGFDYmKir69vs2bN7B0qKyv/9Kc/de/e3Ww2JyUlPfzww3l5eVUrlJeXP/PMM927dw8KCoqP\nj584ceKJEyd0Ptxms73xxht9+/Zt0qRJWFjYLbfccv78+WrzdFzBtY2qxmaztW/fvmvXrtWK\nOP3/pM5gpw3xzjvvDBkyJDo62tfXNyEhYeDAge+//77Vaq36qNtvvz08PLykpKSuqQKAsZmU\ns1tJAYBTa9asueuuuw4fPlz1HW9X2aVLl5o1a3b//fdrN0wGgN8g3mMHwAMmTpwYFxen3Zav\nobz//vs2m23OnDkNOAcAaFhcsQPgGZ988snEiRMzMzNdu1OxmyorK9u3bz9r1iyCHYDfMu+F\nCxc29BwAGEGbNm1yc3MvXrzYtWvXqz/69u3bz50799xzz1X7ygoA+E3hih0AAIBB8B47AAAA\ngyDYAQAAGATBDgAAwCAIdgAAAAZBsAMAADAIgh0AAIBBEOwAAAAMgmAHAABgEAQ7AAAAgyDY\nAQAAGATBDgAAwCD+P7dYBMNrMKEBAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code here..\n",
    "\n",
    "plot(rules, method=\"matrix\", measure=c(\"lift\", \"confidence\"), control=list(reorder=TRUE))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Draw a grouped matrix plot for the rules."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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L0Y0QDQHuD3gaF2EO8L8fcsxKteESc3N9fLyysxMZFhmOXLl4tEouHDh9+/f59v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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code here..\n",
    "plot(rules, method=\"grouped\", k=20)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Write the generated rules to a csv file called \"auto_sales.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "write(rules, file = \"rules_auto_sales.csv\", sep = \",\", col.names = NA)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "ERROR",
     "evalue": "Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class \"structure(\"rules\", package = \"arules\")\" to a data.frame\n",
     "output_type": "error",
     "traceback": [
      "Error in as.data.frame.default(x[[i]], optional = TRUE): cannot coerce class \"structure(\"rules\", package = \"arules\")\" to a data.frame\nTraceback:\n",
      "1. write.csv(rules, file = \"rules_auto_sales.csv\")",
      "2. eval.parent(Call)",
      "3. eval(expr, p)",
      "4. eval(expr, envir, enclos)",
      "5. write.table(rules, file = \"rules_auto_sales.csv\", col.names = NA, \n .     sep = \",\", dec = \".\", qmethod = \"double\")",
      "6. data.frame(x)",
      "7. as.data.frame(x[[i]], optional = TRUE)",
      "8. as.data.frame.default(x[[i]], optional = TRUE)",
      "9. stop(gettextf(\"cannot coerce class \\\"%s\\\" to a data.frame\", deparse(class(x))), \n .     domain = NA)"
     ]
    }
   ],
   "source": [
    "# another way to write the file, but didn't work in our case. \n",
    "write.csv(rules, file = \"rules_auto_sales.csv\")"
   ]
  },
  {
   "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": "3.3.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}