ComcastTelecomConsumerComplaint.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comcast Telecom Consumer Complaints "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    " 1)Import data into Python environment.\n",
    " 2)Provide the trend chart for the number of complaints at monthly and daily granularity levels.\n",
    " 3)Provide a table with the frequency of complaint types.\n",
    " 4)Which complaint types are maximum i.e., around internet, network issues, or across any other domains.\n",
    " 5)Create a new categorical variable with value as Open and Closed. \n",
    " 6)Provide state wise status of complaints in a stacked bar chart. Use the categorized variable \n",
    " 7)Which state has the maximum complaints\n",
    " 8)Which state has the highest percentage of unresolved complaints\n",
    " 9)Provide the percentage of complaints resolved till date, which were received through the Internet and customer care calls."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " # 1)Import data into Python environment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import required libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Ticket #</th>\n",
       "      <th>Customer Complaint</th>\n",
       "      <th>Date</th>\n",
       "      <th>Date_month_year</th>\n",
       "      <th>Time</th>\n",
       "      <th>Received Via</th>\n",
       "      <th>City</th>\n",
       "      <th>State</th>\n",
       "      <th>Zip code</th>\n",
       "      <th>Status</th>\n",
       "      <th>Filing on Behalf of Someone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>Comcast Cable Internet Speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>Payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>Speed and Service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>Comcast Imposed a New Usage Cap of 300GB that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>Comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Ticket #                                 Customer Complaint      Date  \\\n",
       "0   250635                      Comcast Cable Internet Speeds  22-04-15   \n",
       "1   223441       Payment disappear - service got disconnected  04-08-15   \n",
       "2   242732                                  Speed and Service  18-04-15   \n",
       "3   277946  Comcast Imposed a New Usage Cap of 300GB that ...  05-07-15   \n",
       "4   307175         Comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "  Date_month_year         Time        Received Via      City     State  \\\n",
       "0       22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland   \n",
       "1       04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia   \n",
       "2       18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia   \n",
       "3       05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia   \n",
       "4       26-May-15   1:25:26 PM            Internet   Acworth   Georgia   \n",
       "\n",
       "   Zip code  Status Filing on Behalf of Someone  \n",
       "0     21009  Closed                          No  \n",
       "1     30102  Closed                          No  \n",
       "2     30101  Closed                         Yes  \n",
       "3     30101    Open                         Yes  \n",
       "4     30101  Solved                          No  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# loading dataset into a pandas data frame using read_csv available with pandas\n",
    "file_path = \"Comcast_telecom_complaints_data.csv\"\n",
    "raw_df = pd.read_csv(file_path)\n",
    "raw_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "pd.options.display.max_rows = 10000\n",
    "pd.options.display.max_columns = None\n",
    "from matplotlib.pyplot import figure\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticket</th>\n",
       "      <th>complaint</th>\n",
       "      <th>dateN</th>\n",
       "      <th>dateT</th>\n",
       "      <th>time</th>\n",
       "      <th>issuedBy</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>status</th>\n",
       "      <th>behalf</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>Comcast Cable Internet Speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>Payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>Speed and Service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>Comcast Imposed a New Usage Cap of 300GB that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>Comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ticket                                          complaint     dateN  \\\n",
       "0  250635                      Comcast Cable Internet Speeds  22-04-15   \n",
       "1  223441       Payment disappear - service got disconnected  04-08-15   \n",
       "2  242732                                  Speed and Service  18-04-15   \n",
       "3  277946  Comcast Imposed a New Usage Cap of 300GB that ...  05-07-15   \n",
       "4  307175         Comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "       dateT         time            issuedBy      city     state    zip  \\\n",
       "0  22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland  21009   \n",
       "1  04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia  30102   \n",
       "2  18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia  30101   \n",
       "3  05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia  30101   \n",
       "4  26-May-15   1:25:26 PM            Internet   Acworth   Georgia  30101   \n",
       "\n",
       "   status behalf  \n",
       "0  Closed     No  \n",
       "1  Closed     No  \n",
       "2  Closed    Yes  \n",
       "3    Open    Yes  \n",
       "4  Solved     No  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_df.columns = [\"ticket\",\"complaint\",\"dateN\",\"dateT\",\"time\",\"issuedBy\",\"city\",\"state\",\"zip\",\"status\",\"behalf\"]\n",
    "raw_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ticket       0\n",
       "complaint    0\n",
       "dateN        0\n",
       "dateT        0\n",
       "time         0\n",
       "issuedBy     0\n",
       "city         0\n",
       "state        0\n",
       "zip          0\n",
       "status       0\n",
       "behalf       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#There are no null values in the dataset "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ticket       object\n",
       "complaint    object\n",
       "dateN        object\n",
       "dateT        object\n",
       "time         object\n",
       "issuedBy     object\n",
       "city         object\n",
       "state        object\n",
       "zip           int64\n",
       "status       object\n",
       "behalf       object\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#checking the data type of values in each column\n",
    "raw_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2224, 11)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticket</th>\n",
       "      <th>complaint</th>\n",
       "      <th>dateN</th>\n",
       "      <th>dateT</th>\n",
       "      <th>time</th>\n",
       "      <th>issuedBy</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>status</th>\n",
       "      <th>behalf</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>Comcast Cable Internet Speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>Payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Aug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>Speed and Service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>Comcast Imposed a New Usage Cap of 300GB that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Jul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>Comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "      <td>May</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ticket                                          complaint     dateN  \\\n",
       "0  250635                      Comcast Cable Internet Speeds  22-04-15   \n",
       "1  223441       Payment disappear - service got disconnected  04-08-15   \n",
       "2  242732                                  Speed and Service  18-04-15   \n",
       "3  277946  Comcast Imposed a New Usage Cap of 300GB that ...  05-07-15   \n",
       "4  307175         Comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "       dateT         time            issuedBy      city     state    zip  \\\n",
       "0  22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland  21009   \n",
       "1  04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia  30102   \n",
       "2  18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia  30101   \n",
       "3  05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia  30101   \n",
       "4  26-May-15   1:25:26 PM            Internet   Acworth   Georgia  30101   \n",
       "\n",
       "   status behalf month  \n",
       "0  Closed     No   Apr  \n",
       "1  Closed     No   Aug  \n",
       "2  Closed    Yes   Apr  \n",
       "3    Open    Yes   Jul  \n",
       "4  Solved     No   May  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extract the month from dateT and create a new column and put the corresponding month value\n",
    "# The year is 2015 so there is no need to extract the year into another column\n",
    "dateText = raw_df[\"dateT\"]\n",
    "month = dateText.str.extract(r'-(.*)-')\n",
    "raw_df[\"month\"] = month\n",
    "raw_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " # 2)Provide the trend chart for the number of complaints at monthly and daily granularity levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "month\n",
       "Apr     375\n",
       "Aug      67\n",
       "Dec      65\n",
       "Feb      59\n",
       "Jan      55\n",
       "Jul      49\n",
       "Jun    1046\n",
       "Mar      45\n",
       "May     317\n",
       "Nov      38\n",
       "Oct      53\n",
       "Sep      55\n",
       "Name: ticket, dtype: int64"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_month = raw_df.groupby(raw_df['month'])[\"ticket\"].count()\n",
    "groupby_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dateN\n",
       "04-01-15     18\n",
       "04-02-15     27\n",
       "04-03-15     15\n",
       "04-04-15     12\n",
       "04-05-15      6\n",
       "04-06-15     13\n",
       "04-07-15     25\n",
       "04-08-15     28\n",
       "04-09-15     21\n",
       "04-10-15     21\n",
       "04-11-15      5\n",
       "04-12-15     15\n",
       "05-01-15     12\n",
       "05-02-15      7\n",
       "05-03-15      5\n",
       "05-04-15     12\n",
       "05-05-15     14\n",
       "05-06-15     14\n",
       "05-07-15     15\n",
       "05-08-15     15\n",
       "05-09-15     11\n",
       "05-10-15      7\n",
       "05-11-15     12\n",
       "05-12-15      7\n",
       "06-01-15     25\n",
       "06-02-15     25\n",
       "06-03-15     25\n",
       "06-04-15     12\n",
       "06-05-15     29\n",
       "06-06-15     11\n",
       "06-07-15      9\n",
       "06-08-15     24\n",
       "06-09-15     23\n",
       "06-10-15     25\n",
       "06-11-15     21\n",
       "06-12-15     43\n",
       "13-04-15     24\n",
       "13-05-15     12\n",
       "13-06-15     32\n",
       "14-04-15     23\n",
       "14-05-15     15\n",
       "14-06-15     16\n",
       "15-04-15     12\n",
       "15-05-15     12\n",
       "15-06-15     34\n",
       "16-04-15     20\n",
       "16-05-15     16\n",
       "16-06-15     29\n",
       "17-04-15     21\n",
       "17-05-15      7\n",
       "17-06-15     32\n",
       "18-04-15      8\n",
       "18-05-15     14\n",
       "18-06-15     47\n",
       "19-04-15      9\n",
       "19-05-15     12\n",
       "19-06-15     29\n",
       "20-04-15     20\n",
       "20-05-15     15\n",
       "20-06-15     16\n",
       "21-04-15     12\n",
       "21-05-15     17\n",
       "21-06-15     12\n",
       "22-04-15     22\n",
       "22-05-15     14\n",
       "22-06-15     30\n",
       "23-04-15     23\n",
       "23-05-15     12\n",
       "23-06-15    190\n",
       "24-04-15     24\n",
       "24-05-15      7\n",
       "24-06-15    218\n",
       "25-04-15     16\n",
       "25-05-15     12\n",
       "25-06-15     98\n",
       "26-04-15      8\n",
       "26-05-15     27\n",
       "26-06-15     55\n",
       "27-04-15     25\n",
       "27-05-15     17\n",
       "27-06-15     39\n",
       "28-04-15     26\n",
       "28-05-15     26\n",
       "28-06-15     27\n",
       "29-04-15     22\n",
       "29-05-15     14\n",
       "29-06-15     51\n",
       "30-04-15     24\n",
       "30-05-15      9\n",
       "30-06-15     53\n",
       "31-05-15     10\n",
       "Name: ticket, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_date =  raw_df.groupby(raw_df['dateN'])[\"ticket\"].count()\n",
    "groupby_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 375,   67,   65,   59,   55,   49, 1046,   45,  317,   38,   53,\n",
       "         55], dtype=int64)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_month.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(num=None, figsize=(8, 6), dpi=80, facecolor='w', edgecolor='k')\n",
    "ax = sns.lineplot(x = groupby_month.index,y = groupby_month.values)\n",
    "ax.set(ylabel='Count of Tickets', xlabel='Month')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lmOTo317uYns5UUJg6CYiIiIispgWsPtOL1dUQLYpAMt+dchKN9vLieKLoZuIiIiIyGLegZXu4D/tqjr7/EqolV0jMXQTJQSGbiIiIiIii2lrulzB4KsNVLOrxdwXttItBN/H0E0UTwzdREREREQW8/oDk8r7nukG7AzdSqiyrdGe28dBakRxxdBNRERERGQx74BKtxaA7drVLfvV0OA0Dc90EyUGhm4iIiIiIouFVobF4Ey3qqrw+hVIA/Z0SyLby4kSAUM3EREREZHFQivDtEq3wwHAnvZyvxKoqmsBXxMK+jLby4niiaGbiIiIiMhioZVhAyvdNoRu7cy2UwzfXi4rrHQTxRNDNxERERGRxbQ2crfD/vZyn9J/J7iGZ7qJEgNDNxERERGRxXor3YHqs62V7gHPpQmtDGN7OVFcMXQTEREREVlMC9faWW63jSvD5OCZ7oGD1LRKtx3VdSLSj6GbiIiIiMhiWku3Vm22c2VYKOBLbC8nSkQM3UREREREFhsYhO08091b6Q7fXi772V5OFE8M3UREREREFgutDNNCt43t5b1VdbaXEyUihm4iIiIiIot55AF7um1dGda/lV3D9nKixGB76L7nnnswYcIECIKAbdu2hd4+YcIETJs2DfPnz8f8+fPx/PPPh9538OBBLF++HFOnTsWSJUuwe/duuy+TiIiIiMgy2u7sQe3lst+25xpc6Q5OL2foJoor20P3tddeizVr1mD8+PGD3vf8889j27Zt2LZtGz73uc+F3n7bbbfh1ltvxYEDB3D//fdj5cqVdl8mEREREZFlQivDYrCnWw5+TmmI9nKe6SaKL9tD95lnnomSkhLdj6+rq8PmzZtxww03AACuueYaHDt2DOXl5XZdIhERERGRpWJ5plsL8q4B7eV2Bn0i0i+uZ7pvuukmzJkzB7fccgvq6+sBAMeOHUNhYSEkSQIACIKA0tJSVFZWDvr4hx56CCUlJaFfHR0dMb1+IiIiIqJweoNw4OW229Yz3cHp5QMq3do0c7aXE8VX3EL3qlWrsGPHDmzduhW5ubm4+eabDX+Oe++9F1VVVaFfaWlpNlwpEREREZExQ60M89jYXj7oTHfwOX0y28uJ4kmK1xOXlpYCAJxOJ77xjW9g6tSpAIBx48bhxIkTkGUZkiRBVVVUVlaGHk9ERERElOi8/iHOdMdwerlWZfcprHQTxVNcKt2dnZ1oaWkJ/f65557DggULAAB5eXlYuHAhnn32WQDAyy+/jJKSEkyePDkel0pEREREZNigSrete7qHml4u9ns/EcWH7ZXu2267DW+++SZqampw4YUXIj09He+88w6uueYa+P1+qKqKsrIyPPPMM6GPeeyxx7By5Uo88MADyMjIwJNPPmn3ZRIRERERWcbnj/2ebu0Mt8YhChAFwGfDcxKRfraH7sceeyzs2z/99NMhP2batGlYv369XZdERERERGSr3pVhgSBs78qwYKVbGtzEKjlEDlIjirO4Ti8nIiIiIhqNfH4FLocIQQiG7hisDHOKg1/auxwiV4YRxRlDNxERERGRxTyy0m+wmSAIgQBsQ+iWhxikpr1N5pluorhi6CYiIiIispjPr4RayjUuyZ6qsy9Ce7mT7eVEccfQTURERERkMa+sDJom7pZEeOwYpKYM3V7O0E0UfwzdREREREQW8/nVsJVuW0K3rFW6w7eXe9leThRXDN1ERERERBbzykpoeJrGJdl0plvRVoaFr3TLrHQTxRVDNxERERGRxbzhznQ7RHhlvy3PpX3+gdheThR/DN1ERERERBYLd6bbrkFq2nRyKdz0ckkMDVojovhg6CYiIiIisljYSrdN7eW+0MqwMJVuUeCebqI4Y+gmIiIiIrKYzx/mTLdNe7pDK8PC7ulmezlRvDF0ExERERFZzCsrg/Zmx6XSLYmh9nMiig+GbiIiIiIii4WrdLttO9MdnF4eptLtcrC9nCjeGLqJiIiIiCykKGpwT3f/EOwKDjVTFGsrz6H28jArwyQx0F6uqqx2E8ULQzcRERERkYV8SvgVXtrvra48e/0KHKIAUQw/vVxVAb/FQZ+I9GPoJiIiIiKykHZuO9zKMMD60C37lbBD1ALXEHi7zNBNFDcM3UREREREFtLavcOtDANg+TA1n18N21oO2FddJyL9GLqJiIiIiCw0ZKXb4ej3fqv4/IMnpWu04Wo+G6amE5E+DN1ERERERBbSQrU7ZpVuBVKY89xAb/D3cW0YUdwwdBMRERERWUhr5R6yvdzqM92KGnZHN9DbXu5jezlR3DB0ExERERFZaKj2crdNlW6vHGmQGkM3UbwxdBMRERERWcg3VKU7GIA9FofuSJVutpcTxR9DNxERERGRhbT28SFXhtkxSG2I0B0apMZKN1HcMHQTEREREVlImxQeszPdfnXI9nKuDCOKP4ZuIiIiIiILebT28gFBOBSArT7THaHSrYVxme3lRHHD0E1EREREZKFhK91Wn+n2K6E28oG0/d1sLyeKH4ZuIiIiIiILDXum2++39Pl8/giD1ES2lxPFG0M3EREREZGFtEq2KwEGqTml4CA1i5+TiPRj6CYiIiIispDWyu0c0F7utulMdyB0R97TLSs8000ULwzdREREREQW0kK1e4hKt5V7uv2KCkUFpGH3dLPSTRQvDN1ERERERBbyBieFx2JlmM8fvpU99Jw2VdeJSD/DoVtVVbS3t9txLUREREREI54WcIccpGZhANZCtySGby/Xppr7uDKMKG50he5bbrkFLS0t8Hq9mD9/PvLz8/HII4/YfW1ERERERCNOqPo8sNJtQ9VZ27898Py4hu3lRPGnK3Rv2bIFWVlZePvtt7FgwQLU1NTg0UcftfvaiIiIiIhGnHhUup1DVLoZuoniT1foVtXAHbTVq1fjM5/5DDIyMuBwOGy9MCIiIiKikUgLuO5YnOkOTiUfamWYKxS62V5OFC+6QndBQQHuuOMOvPjiizjvvPPg8/ng9/vtvjYiIiIiohHHM0Sl2x0sWlla6Q5+rqGml/ee6WalmyhedIXuv/3tb5g2bRr+8Y9/ICsrC9XV1bj33nvtvjYiIiIiohHHO9SZbhvay2VFm17O9nKiRCXpedCjjz6K73//+6HfT5gwAVVVVbZdFBERERHRSOULVbr7B+HQnm4LA7BXDrSND1XpZns5UfzpqnS/8sorut5GRERERHSyG6rS7RAFOETBlkr3UGe6nRLby4niLWKl+z//+Q/efvvtQe3kra2ttl8YEREREdFIFFoZFiYIuxyiPdPLh2gvl0S2lxPFW8TQnZSUhKysLIiiiMzMzNDbx40bhx/84Ae2XxwRERER0UjjlRU4HQIEYXAQdklWh26908sZuoniJWLoXrFiBVasWIErr7wS8+bNi9U1ERERERGNWF6/GrbKDQRDt5Urw/x628t5ppsoXnSd6c7OzsZnPvMZzJ8/HwCwbds2/PrXv7bzuoiIiIiIRiSv7IdTGrrybOmZbr82SI3Ty4kSla7Qfdttt+H666+Hqga+qGfPno0nnnjC1gsjIiIiIhqJfBEq3W6L28u9Ec6PA4AkcpAaUbzpCt11dXW44YYbIAYHMUiSBEnStW2MiIiIiOikEjjTHZv28uEq3YIgwOkQQqvFiCj2dIVuSZJCVW4AaG5u7vd7IiIiIiIK8PkVuIdqL7d8kFrkM93a+1jpJoofXaH7uuuuw2233Ya2tjb8+c9/xvnnn49bbrnF7msjIiIiIhpxIlW63ZIIj+y37LmGWxkWeJ8Y2udNRLGnq0f8vvvuw3PPPYfW1la88847uPfee/GFL3zB7msjIiIiIhpxPLKCVHf4l9kuSYQnhivDtPf52F5OFDe6Qvd//vMffP7zn8fnP//50Nv+8Ic/4O6777btwoiIiIiIRiKfX4ErVtPLgxVsSYwUugVLz5ETkTG62su/9a1vYfv27aHfP/3003jmmWdsuygiIiIiopHK61eGbPfWBqlZNR9JC/AuKXJ7Oc90E8WPrtD9/PPP44tf/CKqqqrw4osv4qGHHsJbb71l97UREREREY04PlmBS3KEfZ9LckBVAVmxJnRr7eXDVbq1KedEFHu62stnzpyJhx9+GBdccAFEUcT777+PnJwcu6+NiIiIiGjE8foVuIaqdAfPXkcatmaErHN6uZUt7URkTMTQfe+99/b7vdPpxOTJk/Hggw8CAB566CH7royIiIiIaIRRVRU+vzr0mW6pN3Snus0/n57p5S5JRIdHNv9kRBSViKE7MzOz3++vvvpqWy+GiIiIiGgk8w5Tedb2d1s12MynDD+9XBIFnukmiqOIoftHP/pRrK6DiIiIiGjE085Yu4YIwX0r3ZY8X/DzSMPs6fbxTDdR3Og6SPKVr3wFjY2Nod83NDTgtttus+2iiIiIiIhGIi1MOyOsDANg2a5ubSDbUCEfCAR9VrqJ4kdX6N6yZUu/wWm5ubnYtGmTbRdFRERERDQShVZ4xajSPVw7u/Y+hm6i+NEVumW5/+AFVVXh9XptuSAiIiIiopFKC7fDDlKzKARr08sjtZcHznSzvZwoXnSF7mXLluHuu+9GRUUFjh49iq997WtYtmyZ3ddGRERERDSieIardDssPtPtH36QmlMS4VdUKBbtBiciY3SF7l/96lfo7OzEkiVLcMopp8Dj8eDXv/613ddGRERERDSi6K50Wxa6h28v14K+T2GLOVE8RJxersnIyMCTTz5p97UQEREREY1ooUFqw53p9vsteT6fX4EoAA4x0vRyIfhYFW5dr/6JyEoRv+w+/vhjrFixAq+99lrY919++eW2XBQRERER0Ug0XKXbbXGlW/arkCJUuQGE3u+TFcBtydMSkQERQ/ff/vY3rFixImwruSAIDN1ERERERH30Ti8PX3m2emWY169EXBfW9zk5wZwoPiKG7vT0dADAhx9+GJOLISIiIiIaybwxPtMdqHQP3VoO9LaXWzUxnYiMiXhbjGGbiIiIiEg//We6rRukFmmIWt9rkbk2jCgudE0vJyIiIiKi4WkrvIasdFu9MkxR4YwwRA3oDd1sLyeKj4jt5fv27cPChQuHfP/WrVstvyAiIiIiopFKm0o+bKXbqtAtK3AOEfA1bC8niq+Iobu4uJj7uImIiIiIdAoNUovhnm5Jd6Wb7eVE8TDsILUVK1bE6lqIiIiIiEY0bzDYuoeodLstPtMtK2rocw6l90w3K91E8RDxK1RVeTeMiIiIiEiv0CC1Ic90O/o9zornG3aQmsVBn4iMifgV+u9//ztW10FERERENOJpw8qG2p2ttZdbtadbVpTQme2haIPW2F5OFB8RQ3dhYWGsroOIiIiIaMSL/cowFZLOlWE+i4I+ERnDlWFERERERBYJVbpjOEhtqKq6RmsvlxWGbqJ4iPgV+vOf/xwA8MEHH8TkYoiIiIiIRrLQ9PKhKt1W7+n2D99e7gqtDGN7OVE8RAzdL774IgDgW9/6VkwuhoiIiIhoJPMOU+kO7cy26kw328uJEl7ElWEpKSm4+OKLceTIEVx99dWD3v/KK6/YdmFERERERCNN75nu8NVnQRDgkkRLznSrqgpZUYdtL5dCe7oZuoniIWLofv311/HOO+9gz549uOKKK2J1TUREREREI1KovTzC7my3Q7Sk0q1NI5eGm17u0KaXM3QTxUPE0D1mzBh87nOfQ25uLs4999xYXRMRERER0YikBdtIu7NdklWhe/jnAnrPkXNlGFF8RAzdmhUrVuAXv/gF3n33XQDAhRdeiK9//euQJF0fTkRERER0UvAOs6cbCIRujwVVZzkYoofd0832cqK40pWa77vvPpSXl+POO++EIAj485//jIqKCvzud7+z+/qIiIiIiEYMr6zC6RAgikMHYasq3V6dlW6J7eVEcaUrdH/44YfYtm0bRDHwBX3ppZdi4cKFtl4YEREREdFI4/Urutq9vbLf9HNpe7clUV97OVeGEcVH5K/QIFVVoShKv9+rKr9oiYiIiIj68slKxCFqACybXu6Tg+3lkr72cpmVbqK40FXpvuiii3DBBRdg5cqVAIBnnnkGF198sZ3XRUREREQ04uiqdFs1SC1YFHMOU+l2SjzTTRRPukL3gw8+iMcffxyvvfYaAODaa6/FrbfeauuFERERERGNND6/MuzebJdlK8P0nel2itqZbnaqEsWDrtAtiiJuv/123H777XZfDxERERHRiOXV215uQeiWde/p1s50s9JNFA+6znQTEREREdHwvDoq3W6LznTrWU8G9GkvtyDoE5FxDN1ERERERBbxysqwg81ckgifX4WimGv31kL08JXuwPtlk89HRNFh6CYiIiIisohX1lPpdgQea7LarYXo4c90s72cKJ50he4rr7xS19uIiIiIiE5mPr+OM93BkOwx2e7tDQ1Si1zpFkUBDlFgezlRnOgK3ZWVlYPedvjwYcsvhoiIiIhoJPPK+laGaY81QxukNtzzBR4jcGUYUZxEnF7+2GOP4dFHH8WBAwewcOHC0NtbW1sxa9Ys2y+OiIiIiGgk8flVuHVMLwfMt3trIVrSFbpFnukmipOIofuiiy7CtGnTcMcdd+DXv/516O0ZGRmYO3eu7RdHRERERDRSqKoKrz92lW5faHp55PbywGOsWVNGRMZFDN3jx4/H+PHjsXfv3lhdDxERERHRiOQLtnvrPdNtPnTrby+X2F5OFDcRQ7fm6NGjePDBB3Ho0CHIshx6+wcffGDbhRERERERjSS9g81idabbWHu5FtKJKLZ0he7PfvazOPfcc3H33XfD4XDYfU1ERERERCOONh18uEq3O3Sm22/u+XROLwcC1XVWuoniQ1fo7unpwc9//vOonuCee+7Ba6+9hoqKCnz66aeYP38+AODgwYO4+eab0dDQgMzMTDz11FOh4WyR3kdERERElIi8oTPW+irdZleGGWkvdzJ0E8WNrpVhs2fPDrs2TI9rr70Wa9aswfjx4/u9/bbbbsOtt96KAwcO4P7778fKlSt1vY+IiIiIKBF5dVa6rTvTra+dHQCcksD2cqI40VXprq+vx7x583DqqaciKSkp9PZXXnll2I8988wzB72trq4OmzdvxjvvvAMAuOaaa3D33XejvLwcGRkZQ75v8uTJuv5QRERERESxZrTSbfpMd3AFmCQO314uiax0E8WLrtB9ww034IYbbrDsSY8dO4bCwkJIUuDpBUFAaWkpKisrkZmZOeT7GLqJiIiIKFFpIVr3IDWTIVhvZR3gmW6ieNIVum+++Wa7ryMqDz30EB566KHQ7zs6OuJ4NURERER0MgvtzY5Re7msBKeX66h0s72cKH50he4vf/nLYd/+xBNPRPWk48aNw4kTJyDLMiRJgqqqqKysRGlpKTIyMoZ830D33nsv7r333tDvS0pKoroeIiIiIiKzeivdkUOwVe3lHKRGNDLoGqS2aNGi0K9Zs2Zh3759SElJifpJ8/LysHDhQjz77LMAgJdffhklJSWYPHlyxPcRERERESUqrV3cPVyl26L2ciOD1Ow8093W42OgJ4pAV6X7rrvu6vf7O+64A5dffrmuJ7jtttvw5ptvoqamBhdeeCHS09NRXl6Oxx57DCtXrsQDDzyAjIwMPPnkk6GPifQ+IiIiIqJEpPdMt9uySreBPd3B9nJVVSEIwz9erx6fHyv+70PcvHwCvnHeVMs+L9Fooit0D5SUlISqqipdj33sscfCvn3atGlYv3694fcRERERESUird17+DPdDgDm93TLweeTdLaXA4GJ53pCul5NnV40d/lwqL7Tss9JNNroCt19z037/X5s3rwZs2fPtu2iiIiIiIhGGsPTy02Gbr0ryvpek8+v6GpH16vTI/f7JxENpit0Z2Zm9n6AJOGee+7B1VdfbdtFERERERGNNF6/H4COSrdlZ7q1SreO6eXBx/hkFXCZetp+2oNhu4Ohm2hIukL3j370I7uvg4iIiIhoRPPJwfbyGFW6Zb+BlWEOa4L+QB09gbDd5WXoJhqKrt6S9vZ23HXXXZg6dSqmTp2Ku+++G+3t7XZfGxERERHRiOGJ8Z7uQKu4oGswWt/2civ1tpf7Lf28RKOJrtB95513QpZlvPDCC3jxxRehKAruvPNOu6+NiIiIiGjE8Mk6Q7eFe7r1ns8ODVILtqRbhe3lRMPT1V6+Y8cObN++PfT7Rx55BPPmzbPtooiIiIiIRhqvzr3Zbgv3dOsN3a7gmW6r28s5SI1oeLq+Sv1+f7928o6ODvj9bCEhIiIiItKEKt3Dnem2qL1c9utf/yXZ1F7ee6bbD0WxtopONFroqnTffPPNWLZsGT73uc8BAF544QV86UtfsvXCiIiIiIhGktAKLylyEBZFAZIomN7T7TVQ6bbrTHdHnwFqnV4Z6UlOSz8/0WigK3R/+9vfxpw5c/Dee+8BAH75y1/ioosusvXCiIiIiIhGkt692Y5hH+uSRNOt3rKi6FoXBvRZGWbxmW6t0g0EhqkxdBMNFjF0t7W1oampCRMmTMBFF10UCtpHjx5FW1sbMjIyYnKRRERERESJTmsXdw5T6QaCoVs2d1zTJ+sfpKYNb7NrejnAYWpEQ4n4Vfqd73wHW7ZsGfT2rVu34v7777ftooiIiIiIRhqfX9+Zbu0xpqeXKwqcor7QLYk2tZd7+la6GbqJwon4Vbpx40Zcc801g95+9dVXY9WqVbZdFBERERHRSNNb6dYRui1oL/f5FV1VdaBve7m1obu9h6GbaDgRvyPI8tBfOKLOu2pERERERCcDr87p5YDWXm5+ermk8zV5725wa890d3rZXk40nIhfpT6fD21tbYPe3traCp/PZ9tFERERERGNNNqQspi1l/sVXc8F9E4vlxV7VoYB/QM4EfWK+FV6/fXX48Ybb0Rzc3Pobc3NzfjSl76E66+/3vaLIyIiIiIaKTyyAkkUIIrDt3y7Lah0+/yqgenldp3p9of9dyLqFTF0f//730dWVhbGjRuHBQsWYMGCBRg3bhzS09Pxgx/8IFbXSERERESU8Hx+JdTGPRzLznTrrHRr4dxncXt5h8eHMSmBNWE8000UXsSVYQ6HA08//TR++MMfYuvWrQCAhQsXYtKkSTG5OCIiIiKikcIr6w/BLkmEx4Iz3U6dlW6tDd1s0O///Ap6fAom5KSiucvH0E00hIihWzNp0iQGbSIiIiKiCAxVuk2e6VZVFV4Dle7QmW4LQ3dnsJ08LyMJ+2raOUiNaAgcQU5EREREZAGvgcFmWnu5qkbX7i0rgY+TdIdubWWYde3lHcHBafnpbgBsLycaCkM3EREREZEFvLKRM90OqGpveDZKDoZnve3lThvay7XJ5fkZSQB6K99E1B9DNxERERGRBQLt3gbPWEfZYq6FZ6fOPd12TC/v8ARWCGcmO5HkFNleTjQEhm4iIiIiIgsYq3SbC93a2WynpLfSLQQ/zsL28mBlOy1JQppbYns50RAYuomIiIiILGBkhZdbMtfu7Qu1l8ex0h1sL091S0h1S+j0sr2cKByGbiIiIiIiC3hlY4PUtI+JhhaejawoA6w9061VttPdElJdrHQTDYWhm4iIiIjIAj6/qru9XKt0R7uruzd062svl0Rterl1obvd01vpZns50dAYuomIiIiILGCo0u3QQnd0LdmhlWF6B6kFQ75Ptu5Mtxay09wSUt0ODlIjGgJDNxERERGRSaqqBvZ0x2iQmvZxup9PO9OtWDm9vG/oluCRldCANyLqxdBNRERERGSS0cFmpqeXhyrdxvZ0+yydXh4M3cHp5QB3dROFw9BNRERERGSSdlbacKU76unlxgapOUQBggD4ogz54fROL3cgNRi6O7xsMScaiKGbiIiIiMgkrWKtu9LtsGp6ub5Kd+CxorUrwzwyXA4Rbqk3dHOYGtFgDN1ERERERCZpYdYdozPdRtvZgUDQ9ynWtpenJQXCdprbEXobEfXH0E1EREREZJJHNlZ5dptsL9cGlkkGQrfTIVjeXp4aDNusdBMNjaGbiIiIiMgkb5RnumO1pxsIBHQr28s7vTLS3E4A6DNIjaGbaCCGbiIiIiIik0KD1BwOXY/XHhfz9nIrz3T3yKG28lRXcJAap5cTDcLQTURERERkUmiQmqSv8mz+TLexwW2BxwrwWrwyTKtws72caGgM3UREREREJvVWumOzMkwOhmfJ4PRy2aJKt8+vwCMrSEvq317OQWpEgzF0ExERERGZpJ3N1n2m2+TKMK/BkA9YuzJMq2iH2suD/2Slm2gwhm4iIiIiIpO0M9aGK90m28sl0UilWwhdp1ntPVrolvr9k6GbaDCGbiIiIiIik0JnunWGbvMrw4KD1HRW1oHAtUX7fANpbeSpA850c5Aa0WAM3UREREREJvmiXBkW6/Zyq85097aXB8J2stMBQWClmygchm4iIiIiIpOMVrq1sBztnu6oBqlJonXt5QNCtygKSHE60Oll6CYaiKGbiIiIiMgkLXS7Y1TpjmplmChY1l4eqnQnSaG3pbolTi8nCoOhm4iIiIjIJG+07eVRhmCfEgzdYnyml3f09D/TDQSq3mwvJxqMoZuIiIiIyCSj7eWSKEAQAK8c3eAxn6wNUjPWXq6qgF8x32KuVbTT3f0r3Z0cpEY0CEM3EREREZFJRgepCYIAl0OMur1cVrSVYUYq3YGAbkW1uyNseznPdBOFw9BNRERERGRSb6Vbf+XZJUW/wssXxfRy7bFWnOvW2shTXWwvJxoOQzcRERERkUlaCNY7SE17bPSD1IxPL9ce64vyOfsKtZcPGKTm86vwRNkyTzRaMXQTEREREZnkiWKauJn28qimlwcfa8XasPYwg9S0f+e5bqL+GLqJiIiIiEzSBpvpPdOtPdbsnm5D7eyh0G1Ne7lbEvuF/rRQ6GaLOVFfDN1ERERERCZ5/YHqrqFKt4kz3V6/EpyAbmB6uYWhu8Mjh0K2RjvfzV3dRP0xdBMRERERmRRtpTvq6eV+xdB5bqDPmW4L2ss7PP5+k8uBwPRygJVuooEYuomIiIiITPJGOU3czCA1I1V1wOpKt6/f5HKgt72clW6i/hi6iYiIiIhM0sKzodBtcmWY0dBt7ZnucJVuDlIjCoehm4iIiIjIJO2MtSga2dPtMDW93MgQNaB36Jol7eU9MtLd4SvdbC8n6o+hm4iIiIjIJK8cXeXZTHu5JBp7PsmiSrdH9sPrV/qtCwN6K91sLyfqj6GbiIiIiMgkn18xNEQNANySCFlRoSjGK8/RPJ/WXh5tS7tGax/nIDUifRi6iYiIiIhMiqrSLUUfgn3BdnYjnFKwvTzK6rqmoycQqgeuDAsNUvMydBP1xdBNRERERGSSz6/AHWXl2RNFCJaV6KeXy1FU1vvS2scH7enmmW6isBi6iYiIiIhM8sjGB5uFKt1RhG6frMBpMORbtTJMC90Dz3SncXo5UVgM3UREREREJkV1xtpMe7miwmm0vTx4UyDa4W0arZI9cHq5WxLhEAUOUiMagKGbiIiIiMgkbzR7s81UuqN4vt5Kt7n28natvXzAIDVBEJDqcrC9nGgAhm4iIiIiIpO8solp4tGc6farkAzv6dbOdFtT6R7YXq69jaGbqD+GbiIiIiIik3x+NRSi9TJT6fb6FcPP5zQR8vsaano5EAjdbC8n6o+hm4iIiIjIpGgq3e7QmW7jg8dkvxJFpTu4Msxke/lQ08sBrdLNQWpEfTF0ExERERGZFE3lWQvpRleG+RUVigoTZ7qtmV4+8Ew3AKS5Hejknm6ifhi6iYiIiIhMUFUVXjmKQWpRtntroTnqPd1mQ7fWXu4KU+l2Bc50q6q5ajrRaMLQTURERERkgqwEAqbh9nJndJXu3tBtcC+4FvLNtpd7tUFqjkHvS3NLUFSgx2cu2BONJgzdREREREQmaJVq45VuR7+P10sOhmbJaKVb0s50m690JznFsM+vTTTnMDWiXgzdREREREQmaCHW8MqwKKeXh57PYOiWRGvOdHd6ZKS5nWHfp4Vurg0j6sXQTURERERkghaaXUbbvUPTyw2G7mA7uyRG115uxSC19DBD1IDAIDXtMUQUwNBNRERERGSCdibbcKU72kFqWju7wefrbS83vzIs3HlugJVuonAYuomIiIiITIh2mni07eWyEnw+g5VuK1eGhdvRDfQJ3VwbRhTC0E1EREREZII3yjPd7ijby71yoFJtNORr7ehmQreqqsEz3UO1l2uD1PxRPwfRaMPQTURERERkgk+ObmWY9vhoV4YZnV4uCAKcDiEU2qPhkRX4/OrwlW62lxOFMHQTEREREZng9QequkaniUd7pjvUXm5wcFvgY8TQx0dDG5CWOmSlO3DWm6GbqBdDNxERERGRCV6TlW6joTva5wMCodtMe7kWptOGmF7OPd1EgzF0ExERERGZ4DU7SM1v7PyzVqnW9m4b4XQIoXb4aLT3BEO3a4jQ7WJ7OdFADN1ERERERCb4Qnu6Y1Pp7p2WHl17udHBbX0NV+nmIDWiwRi6iYiIiIhMCFW6Y7Wn2x/d9HLtY8y0l2tt4xykRqQfQzcRERERkQlaiI16kJrBEBztXvDAxwiQ/dG3lw8Xul2SCJdDZOgm6oOhm4iIiIjIBG3ll0sy1u4titoKL4PTy4OhWYqyvdySSvcQ7eUAkOp2cJAaUR8M3UREREREJnhDZ7odhj/W5RAN7+n2RllZB8yf6e7oibwyTHtfp5ehm0jD0E1EREREZEKovTyKFV4uSYxxpVuwZGVYeqTQ7ZLQyUFqRCEM3UREREREJmihOZpp4i7JeOXZ3Jlu0dSZ7naPnko328uJ+mLoJiIiIiIyIdaVbjMrw6IJ+X0NtzIMCATyLoZuohCGbiIiIiIiE7xR7unWPiaWK8Mk0Vx7uVbBTnUNHbrT3BI6vX4oSvQVdaLRhKGbiIiIiMgEbzAER1fpdhiuPMvBx0titHu6zawM8yPF5YBDHLrKrrWed/nsOdf9yeFG7KhqseVzE9mBoZuIiIiIyITeM92xbS83uqIMAJySCL+iRl2F7ujxDbmjW6O9345d3aqq4q6/bcX9L++0/HMT2SXyVwwREREREUVk5ky3O5r28mBgjqbSrbXA+xQFbtH4irNOj3/Y0J3qDnzeDo+MfMPPEFljpxeNnV60e2T4FTVixZ0oUbDSTURERERkQswr3drzRRHyteFr0baYd3jkiEPUgN72cjsq3QdrOwAE/psfb+m2/PMT2YGhm4iIiIjIBO1MtjvK6eUeo2e6g5VuZxRVXkmrdBsM+pr2Hl/EIWpAb3u5HWvDyus7Qv9+uKHT8s9PsbHpaNNJtVaOoZuIiIiIyASvib3Z2vRyVdVfeTb7fACimmCuqio6vf7hK90urdJt/SC18tr20L8f7hPAaeSobOzCdY+uxxNrjsT7UmKGoZuIiIiIyASvrMAhClGdL9bOgRtp97akvTyKQWo9PgV+RdVxptvG9vK6jtB/58P1rHSPRBVNgf9vRxtPnv9/DN1ERERERCb4/EpUO7qB3tBtZG2YHBqkFsX0chPt5Vo7sN7p5ba0l9d1YGZhBlJdDhxuYKV7JKpt8wT/2RPnK4mduIbuCRMmYNq0aZg/fz7mz5+P559/HgBw8OBBLF++HFOnTsWSJUuwe/fueF4mEREREdGQvLISqiAbFQrdBkKwmfZyyUR7eSh0DztILTC93OpKd2uXD3XtHkzJT8PEsamsdFtEVdWYtuprYbumlaE7Zp5//nls27YN27Ztw+c+9zkAwG233YZbb70VBw4cwP3334+VK1fG9yKJiIiIiIbg8ytwScbXbwG9Z6yNhG7Zr0AUEF07e/DmgJHKuqbTYKXb6tBdXh84zz05Lw0Tc9NworUHXd6TZxiXXVYfbMA5v/oYHx+oj8nzaaFbq3ifDOIeugeqq6vD5s2bccMNNwAArrnmGhw7dgzl5eVxvjIiIiIiosG8shIKs0a5o6h0+/xqVFVuoLc6LkexMqy9R1/oTg21l1s7SK28LlCNnZKXjrLcVADAEU4wN23viTYAwNaK5pg8n1bh7vDIaO/xxeQ54y3uofumm27CnDlzcMstt6C+vh7Hjh1DYWEhJCnwxSoIAkpLS1FZWRnnKyUiIiIiGszrV0Nt4kb1nunWH1B9fsV06I6mvVyrXKfGaZCatqN7Sl4aysYGQjdbzM2rag7sOz9Y1z7MI61R295b4T5ZznXHNXSvWrUKO3bswNatW5Gbm4ubb77Z0Mc/9NBDKCkpCf3q6OAwBSIiIiKKLa/sjzoEa+3lHkOV7ujPkDtNtJfrHaSW6gq02ndY3Pp9sK4DLknEuOwUTBqbBoCh2wrVLYHQfaA2Nlmqts9Z7prWk6PFPK6hu7S0FADgdDrxjW98A6tXr8a4ceNw4sQJyHLgi1RVVVRWVoYe29e9996Lqqqq0K+0tLSYXj8RERERkc+KSrehM91qaCCaUb2V7ijay3WGbskhIskpWn+mu64DZbmpcIgCJgbbyznB3Lyq5i4AgVZ9j2z9bvW+/IqK+g5P6GZTDSvd9urs7ERLS0vo98899xwWLFiAvLw8LFy4EM8++ywA4OWXX0ZJSQkmT54cpyslIiIiIhpaYHp57EK3mRVlZlaGdeqcXg4EgrmVobvTI6O6pRtT8tMBBFrYCzKSWOk2SVVVVAfby/2KavsZ+cYOD/yKiplFGQBOnvby4b9ibFJbW4trrrkGfr8fqqqirKwMzzzzDADgsccew8qVK/HAAw8gIyMDTz75ZLwuk4iIiIgoIq9fseBMt7FBalK07eXB55OVKNrLQ4PUhp/UnuqWLB2kpoXryWN7O1vLxqZi+7EWqKoKQYjuv8fJrqXLh06vH+luCe0eGQdqOzC9IMO259Mmls8fl4Vtx1pOmrVhcQvdZWVl+PTTT8O+b9q0aVi/fn2Mr4iIiIiIyDifrISmkBsVzcowM4PUeleGGW8v7z3T7Rz2sakuKfR4K2hDvqbk94buibmpWHeoEXXtHuRnJFn2XCcT7Tz3mVPH4s2dJ3Cw1t5halo7+czCDEiiwPZyIiIiIupv74k2LPmf97C/JjZTfmlk8JgJwdGc6VZUSFHs6AYASYy+vbwjju3lB+t6J5dryoJV70P1PNcdLe089xlTcuEQBRywOXRr7eSFWUnIS3efNO3lDN1EREREOq0tb0B9uwcbjjTG+1IoQaiqauqMtTuK9nKvHH07u9ZebmZlWIpz+PbyFLfD0kp3eV0HHKKA8Tmpobdpa8O4qzt62rqwsrFpGJ+TYvsEcy1k52ckIT8z6aRpL2foJiIiItKpsilQFdJaMolkRYWq9oZZo7TwbGRlmKwoUVe6tZVhPiW69vI0twRRx3OnuiV4ZAVyFOE+nPK6DkzISel3s2FSLteGmaWF7uIxyZial46Kxk70+OybYN43dBdkJKG+wxPVDaCRhqGbiIiISKejjcHQ3czQTQFaYIi20u1yBKrGxs50q6b3gkfbXp6qY4gaAKS5Ai3onV7zAa7H50dFYyem5KX3e3vxmGS4JBGH2V4eteqWbkiigPx0N6YWpENR7W3Xr2nzIMkpIiNJQn5GElQVqG8f/bu6GbqJiIiIdKpsDFTUWOkmjRaWXVJ0lWe303il28wgNckRfXt5R4887I5uTWrwcVac6z7a2AlFBSb3Oc8NAA5RwIScFBxme3nUqpq7UZCZBMkhYmpwSN1BG1vM69p6UJCRBEEQUJAZGH53MgxTY+gmIiIi0kH2K6FWzOMM3RTkNV3pjnZ6ucn28mhCt0d/6NbWilkRurUQ2HdyuaYsNw3Hmrrgke1riR7Nqpu7UDImGQAwNbgD3c5hajVtPcgLTpovCP6z9iQ4183QTURERKTD8ZYeyMFzsHXtHkMhiUYv7e9BLKeXB/Z0mwz5Ua4M0zO5HOitdFsxTE2bXD6w0g0EhqkpKlAZPPpB+rX1+NDWI6M4KwUAMCEnFZKNE8x7fH60dPlCYZuVbiIiIiLqp6Ip0MKa5pagqsCJVla7qW97ucnQ7ddXqVUUFX5Fjbqyrt0cMDrgTFVVdHpkpLqMtpebr0AfquuAIACTxg4O3RNzAxPMD3GYmmHabAqt0u2SREzMTbVtgnldW+Dsdn6GG0BvpZuhm4iIKIYO1Xfg6//4FG09vnhfCtEgFcFK2tKJ2QA4TI0CfMGKcdSh22B7uU/RKutRtpdHuTKs2+eHourb0Q0g1IZuTaW7HePGpCApzKoybVf34QYOUzOq7+RyzdT8dBxr7kK3BQPwBqpt751cDvRWutleTkREFEMvbD6GV7cdx7u7a+N9KUSDVASHqC2flAOAw9QowGx7udtge7kcDPnRtpc7Re1Mt7H28o6eQHhOj/EgNdmv4EhDJ6aEaS0HgEnarm5Wug2rbg7cSCwZELpVNbCizWraTm4tdCc5HchMdrLSTUREFEs7jrUCADYdbYrzlRANVtHYBYco9Fa6GboJvYPU3Kbby3VWuv3mQr7TYez5NFrFOlV36A4OUvOaC90VTV3w+dWw57kBICvFhexUFyeYR0GrdJcEz3QDCE0wt+Nct7ajW6twA4EW8xpWuomIiGJDUVTsqg6E7o1HGLop8VQ2daEoKwnjcwKVNbaXE2DdIDW9K8O0CrXZ9nKjZ7q10B3r9nJtcvlQoRsAynJTuas7CtUt3RCF/iF4io0TzLXQnZ/e+3z5mUmoaeuBqhof7DeSMHQTEVFCONzQifbgi7PDDZ2ob/fE+YqIeqmqiorGLkzISUVmshPpbgnHOUiN0Ft5jtmZbtOV7ijby7XQHeP28kP12rqw9CEfUzY2Fc1dPjR3ek0918mmqrkb+RlJ/f7uTshJgcsh2hS6Az/X84KD1ACgIMONHp+Ctm7zZ/8TGUM3ERElhB1VLQCA0yfnAgA2s8WcEkh9uwfdPj9KswNtmEVZyax0EwDzlW7JIUIUojnTHWWlW4yyvbzHWOhOs2h6+cFg+NPObofDYWrRqW7p7neeGwj8fSwba88E85q2HmSlOPsNxDtZJpgzdBMRUULYURVoLb/ljIkAgA1sMacEUtEUGDg0PicQuovHJON4Sw8UZXS3RNLwzFa6tY/VG4K1x0W7MkwUBThEAT6De+aNn+m2qL28rgOFmUlIT3IO+RiuDTOuyyujqdOL4qzkQe+bmp+O6pZu010KA9W19YRCtib/JNnVzdBNREQJYXtVC7JSnDhr6ljkprk4TI0SytHgkCbtPHdxVjK8fgUNnTwGcbLrDcHRVZ4DHyvqr3QHV4ZJYvQv450OAbLBG0ZaANM7vTwlWM00E9wURcWh+o6I57mB3ir4YYZu3Xp3dKcMep82TO2ghRPMVVVFTVsP8gaE7sKTZG0YQzcREcWdz69gz/E2zCnOhCAIWDIhG3tOtHFfNyWMygGV7qJgdYgt5qQNQDNX6XboP9MtBwepSdGHfKdDNLynu93gIDVRFJDqcpiqdFe3dKPHpwwbukuzU+EQBduGqe2racP7e0fXKstwO7o1dgxTa+uR0eNTUNDnPDfQuz6MlW4iIiKb7a9ph0dWMK8kCwCwdGI2VBXYUtEc3wsjCqpoDIRu7Uy39kKVa8PI7GAzILBuTPfKsGCl22mq0q2/sq7pNNherj3WTKX7YF0g9E3JG3qIGhC44TFuTDKO2LQ27Mev7cZXn9mMuvbREwyrWrRKd/j2cgA4UGNd6A5NLh9Q6eaZbiIiohjRznPPLckEACyZENiDvInnuilBVDR2Ii/djRRXIHBo5yCPM3Sf9LTwGu0ZayB4plt3pVsL+WYq3YLhSrc2SE1vezkQGKZmZpBaeZ02uTxypRsIDFOraOyC3+I5C35FxY6qVigq8OaOE5Z+7niqag7cSAx3prs0OwVuScQBC9vLhwrd2akuuBziqN/VzdBNRERxp00unzcuCwAwozAD6W6J+7opYVQ0dYVay4HeF6psLydLBqkZOtOtTS83V+k2vjIsEJ6NVrrNtJeHdnSP1RG6c1Ph9SuhMGmVQ/Ud6PIG/uyvbjtu6eeOJ+17V1GY0O0QBUwamxaaHG8FLVQPDN2CICAvw83QTUREZLftVa3Iz3CHfhg7RAGLJozBjqpW9PjMrZshMqu1y4eWLh9Ks3tXFuWlu+F0CGwvJ9Mrw4BAYPfoDN1mp5drH2u40u3xQRCAFJdj+AcHpbod6PSaaS/vQG6aC2NSXcM+NrQ2zOJhatuPtQAActNc2HasBZWN1ob6eKlq7sbYdHe/9V19TStIx4nWHstmq9S1B4ZODpxerr2tlu3lRERE9un2+nGgth1zg+e5NUsmZMPrV7At+IKHKF4qmgIv4if0qXSLooDCzGRUt4zuF4o0PG+wYuyO0cows3u6gegGqXV6/EhzSRAE/c+bZuJMt6qqOFQ3/ORyTdlYbW2YtcPUtgc7sb55/lQAwGvbqy39/PFS1Tx4R3dfWkv/QYv2dfdWut2D3pefmYTGTi888ui9yc7QTUREcbXnRCv8iop5wfPcmlMm8lw3JYbQELWc/qt1irKSUG1xKyuNPJZUug20l1sxuE1yCIbby9s9su7J5ZoUlwSfX40qTNW2edDukfWH7uCu7sMWD1PbUdWKnFQXPrt4HLJTXfjXtuNQVWvPjcdaj8+Phg5P2PPcmql51k4wr2nrgUMUkJM2OHRr1e+6ttG7gpGhm4iI4mr7MW2IWla/t88pyYRLErGR+7opznrXhaX2e3txVgraemS0c7XdSc2SM91GBqn5rRikFkV7eY/P0HluoPf8d1cUw9RCQ9SGmVyuGZvuRppbsnRtmEf2Y++JNswtyYTTIeLSOYUor+vA3hPWnXWOh+qWoXd0a6ZavDasrq0HY9PccIiD/95qoXs0t5gzdBMRUVxpQ9TmDqh0uyUH5o/LwtaKZsgGXxwSWelow+D2coBrwyjAqjPduleGBSvUZivrRivdnR4/0gyG7jR34LxwNMPUeteF6at0C4KAsrGplp7p3neiHT6/GropfPn8IgDAa9tH9kC16gg7ujUlY5KR7HRY117e1oP8zMHnuQGgIHP0rw1j6CYiorjaUdWK8TkpyEoZPCjnlInZ6PT6sedEWxyujCigoqkLGUnSoL+jxVmBF4pcG3Zys6rS7VdUXeuurGgvd0pRrAzzyEg32F6uVbqjGaZ2MFjp1tteDgRazOvaPaYmpvfVu1kjcFN4UekYFGcl4/Xtx6FYvJoslqqah97RrRFFAVPy0yypdPsVFfXtHuSnD24tB/qE7lE8wZyhm4iI4qa124fDDZ2DWss12r5urg6LXluPL+pBRhRQ2dg1qLUcCLSXA1wbdrKzYk+3O/ixelrMtc4fM4PUJNFYe7miqOj0ykh1Ga10B0N3FN+Dyus6kJEkYewQQS0cbYL5EYuq3dur+h9/EkUBl80rQnVLN7ZUNlvyHPFQ3RI4MlMS4Uw3EGjtr2v3oKXLa+r5Gjo8UNTecD2Q1l7O0E1ERGSDXdWBFzQDh6hpFo4fA4coMHSb8NlH1+OWpzfF+zJGrB6fHzVtPf12dGu01swqVrpPah6LKt2AvtCtTUs3E/KNnunu8vmhqjA8SE2rdHdEeaZ7Sn66oWnp2gTzww3WtETvqGpBcVYycvsM/7p8XrDFfATv7K7S0V4OAFODE8wPmGwx185qD9zRrckLTjRnezkREZENtoda97LCvj/NLWFWUQY2HW0a8dNi46Gxw4N9Ne345HATzx1HqXeI2uDQXZiptZeP3heKNDyfrMAhCmEHROmlhW6Pf/hw2lvpNhPyA9PL9X5f1SrVRs90p0ZZ6W7s8KCp04vJY/W3lgNAWW7g8YcsqHR3emSU13UMmjcyozAdU/LS8ObOE4Zb9BNFdXM3clJdSBmmc8GqYWq968LCh2635EB2qouD1IiIiOyw41grRAGYVZQx5GOWTMhGc5cvNMmW9NsRbI0EgLd31cTxSkYubV3Y+OzB7eVJTgdy09xcG3aS8/oVU5PEgd6qtZ5Kt1XTywFA1nkuub0nutAd7SC10OTyfGOhe0Ju4OaYFRPMd1W3QlEHb9YQBAFXzC9CU6cXa8obTD9PPFQ1dw9b5Qb67uo2F7pr2wOrwMLt6NbkZySx0k1ERGSHHVUtmJqfHvFu+9Lgvm67VofpGVw0UmmdBADw9q4T8buQEayiMVAxC1fpBgLtmewiOLn5/IqpVm/AWHu5FdPLtY/VW6nVKtWGV4a5oqt0a0PUJhkYogYE9oIXZSZZMsFcu2kZ7vjTZSO4xdwrK6ht74k4RE1TnJWMVJfDfHt5sNJdMESlO/A+N2rbPKO2q42hm4iI4qK+3YPjrT2DWvcG0oapbbLhXPeh+g7M/OHbeHVbteWfOxHsqGqF0yHgvBl52FzRjLpRWEV4YdMxzPvJO2js8Njy+UOV7jCD1IDAIKK6do/uHcs0+nhlxdR5bqBP6NYRgi2ZXh6skvtkfQFHq1RHe6bbaOju3dFtLHQDgWFqRxo6TU8X125azg7zM2p8Tirmj8vCO7tr0O01fl49nk60dkNVA4F6OIIgYEp+emh9W7S0tvG8SKE7MwleWUFzl8/UcyUqhm4iIoqL3v3cWREfl53qwuS8NFuGqX20vx4eWcH/vb1/1IUmVVWxo6oF0wsycPn8Yqgq8J/do6/F/MP9dWjt9mFrZYstn7+iqQtuSUTeEBOUi7KSoKqje+ouReb1qzGtdGst4ZKJM+RaYNe7G7y3vdxh6HnSohykVl7XgRSXA0WZwwfDgcrGpqI7OADRjB1VrSgbm4qMJGfY918xvwidXj/e31dr6nlirTq0Lix8985AU/PT0NDhNXVjs6atB8lOBzIi3LTJH+UTzBm6iYgoLraHWveyhn3s0onZON7agyqLz85urQisfKlu6cYLm49Z+rnj7XhrDxo6vJhbkolzpufBJYl4axSe695XE6jA7D7eOswjo1PR2InxOSkQhwg4WrWoqoXnuk9WXlmB02yl28CZ7tCKMhPP2Xum21h7eZo7fAAdSrSV7oN17Zg0Nm3Ir7tIynIDXSlHGqJvMW/u9KKyqSviz6dL5xZCFIBXR1iLeWhyuY5KN9B3mFr0LeZ1bR7kZ7gjTqLXWs9H6zA1hm4iIoqLHVUtcDlETCtIH/axS23Y162qKjZXNGFibipyUl14+MNyeOSR1SYYyY5jLQACNzXS3BLOnDIWG4402daGHQ9dXhlHg2eudx9vs/zzy34F1c3dKA0zRE1THKwWcYL5ycuKM91uQ5Xu4PRyCyrdhtvLDQ9SMx6623p8qG3zRNVaDvTu6jYzTG1Htbafe+jjT3npSVg+KRcf769H6whqidZWHJZk6wvdU4Kh20yLeU1bz5CTyzXaDu8TrHQTERFZI9D63IoZRRm6qjVLgsPUNlk4TK26pRu1bR6cOikHt60ow4nWHjy/afRUu7VOgrnjAi8aL55dAL+i4t09I6sVMpL9Ne3QZu7ssSF0H2/pgayoQw5RAwLt5UBvyyYlvr9+UoHLfr8GLV1eSz6fV1ZMna8G+q4M03GmOxiUzVTXtTPdetvLow3dSU4RomBserl2nnuywcnlGm1Xt5m1YdpNy+GOP10+vwhev4K3d4+cQZVax5j+Sre2qzu60N3j86O126c7dI/WCeYM3UREFHNVzd1o6vSGnQobTnFWMoqzki2tdG8JtpYvHj8GNy6bgNw0Nx7+sBw9vtFR7d5R1YJkpyO05/a8GflwOoRR1WK+90TgRWBOqgvVLd2WhSiNVkWfECF0l2QF3lfN9vIR42+fVGBndSt++sZeSz6fpYPU9EwvD1a6nWLsppdHO0hNEASkuiV0eg2E7mAbs9Ed3ZqizGS4JRGHTbSXb69qhSQKEddZAsCFswrgcogjqsW8urkbmclOpA9xVn2ggowkpLulqNvLtXZxLVRHeh6gd9L5aMPQTUSUAFq6vLju0XVYN0J3fhqlrWIZrorQ19KJ2ThU34kGi9qjtfPci8aPQbLLgdtXlKG2zYPnNlZa8vnjSVFU7KxqxeziDEjBF9eZKU4sn5SLdYcabG2F/NOqw7j1mc2Qdb6YN2PviUB1+4r5xQCAPSesrXZXNAWCdOkQk8sBICNZQppbsq29vL3Hh+seXYd3RuEQvHg40dodmgPw8tYqfHyg3vTn9PktCN2OwIAyYyvDLNjT7dfXXt67MszYIDUgUB03MkitvF7b0T380aNwRFHAxNxUc+3lwXWWSc7If97MZCfOnj4W6w83jpizyFXN3bqr3EDgxsnUgnQcqG2Pap1XbVvgZ/ZQwyg1mclOuCWRlW4iIrLP+3vrsOloM/4xitqbI9Eml+utdAO9+7o3W9RivrmiGblpLpRmByqVNywbj7Hpbjzy0aERX+0+0tiJdo886KbGxbML4POreG+vPS3mXlnBwx+V4509tXguBn+X99W0ISNJwnkz8gBY32Jeqe3ozh660i0IAoqykmzb1f3xgXpsOtqMn7y+Z9RN2I+HVcGQff9F05HqcuC/XtlpqPU5HK8c2z3d2g0th6kz3Qbby4PTy9MNDlIDAsPUjJzpPljbDpckYpyOPdJDKRubiuqW7qi+l9e09qCu3YN54/T9fLoiuB3ijR2J32Iu+xXUtOnb0d3X1Pw0tHT5UB/FTe8anZVuQRBQkJk0Ym5eGMXQTTGnKCqeWX8UK5/cOGq/sIiMWhuscK8/3BjVneSRZntVC1JdjtDAGz20fd0bLGgx7/TI2HuiDYvGjwlNU01yOnDXWZNQ3+7Bs59UmH6OeOpdx9b/ReP5M/MhCrCtxXz1wXq0BKvoD72zH63d9lXUVVXFvhPtmFGYgZnBFlCrh6kdbeyCQxRQPMwL1OKsZFS3dJveCxyO9r2huqUbL245OW7K2emj/fUQBeD6JePw3Yuno7qlG794e5+pz+m1otJtcE+3yyFGnAQ9nGjay0UhcEbbKMOhu64DZbmpoS6daJTlpkFVe4+IGLFd5zpLzTnT85DmlvDatmrDzxVrNW098CvqsN/TBpqSFxymFkWLeV3wtf5wZ7q1x7DSTWSBow2duP5Pn+CHr+7GR/vr8f/+ueukCBhEkaiqijXBF9b17R5Tw19GAkVRsau6DbOLMw1VaiaNDUwZt2KY2vZjLVDUQGt5X9cvLUVBRhIe/fgQugycQUw024+FX8eWk+bGsrIcrDpYb7q6F452rvHr505Bc5cPf/jgoOXPoalq7ka7R8aMwgxkpbhQnJVsQ6W7C8VZycMOySoekwyvrKCh09rJ8KqqYvXBBhRnJSM71YU/fDC6JuzHms+vYM3BBswbl4UxqS588ZTxWDohG0+vr4j6+4qqqvD6FVOt3oCxlWE+vwrJ5PNFE7rT3FJUQT/N7dD9/abLK6O6pRuTo5xcrtGGqR2J4ufpUDcth5LkdOCCWfnYXtVqak1ZLBjd0a3pXRtmfJiatne7QEfoLshIQkuXb8R3m4XD0J2gHl91CI9+fCjel2EZv6Liz6sP46LfrsLGI024cdl4XDKnAO/trcXrI6Adh8hOB2o7UNfuCQ1rWn+4Mc5XZK/DDR3o8MiYNy7L0McJgoAlE7Kx53gb2nvMVVA39znP3VeS04G7zp6Ehg7viK5276hqQWayM+zU7YtnF8ArK/hgX52lz9nllfHunlosGj8GXz93CuYUZ+KpdUdtexGqneeeURh4MTizKAPl9R2WvVhTVRUVTZ0RJ5drioLnI60+113R2IWq5m6cNW0sbjszMGH/hZPkCIodtlY0o90j46ypgeMIoijgf6+ZA5ck4v6XdkT1d8evqFBVwCUZP+vcl6FBan7z09K1mwRGQrfewVsDpboClW49RZbD9Z1Q1d7KarRCa8Oi+P6zo6oVbkkMBU09tLkSr2+PfqCaoqg4UNuOf2ysxP0v7cAdz26xfMWj0R3dmt4J5sYr3bXtgT/D2GHOdAO9LeijsROWoTsBldd14H/f2odf/Gc/6ttH/j7V8rp2XPvoOvzszb3IS0/Cc19dhp9eORs/vWI2slNd+PFru9HUae3EWaKRRKtyf/28KRAE4JNRHrq1KqzeKkJfSyZmQ1F7J49Ha0tFM1wOEbOLB1/DZ5eMQ1FmEh79+LChlshE4fMr2H28DXNLMsNWpS6cVQBBAN7eZe0Nz3f31KLb58cV84sgigJ+eNlM+PwqHvi3NROiB9Iml88oDLSWzyrKgD/4otUKde0e9PgUXaFbewFr9dow7XvD6ZNzceOp45Gb5sIfRtGE/Vj7KHiee8W0saG3lY1NwzfPm4rDDZ347fvGOzO0dnCzlW63wfZyq1aU+XQOUuvwyFENUQMCg9QUFejxDf9n01q7pxeaDd3a2jBjIVFbZzmrKMPQf+PTJuUgJ9WFf22r1t3B2dzpxQf7avGrd/bjhj9vwLyfvIMLfr0K331lJ57ffAxv7arBl5/aZOnPIW32hNEz3WPT3chKcUb1/bW2tQdjUpzDDqUDelvQR+OubmNz/ykmfvf+QSgqAFXFvz6txlfPLIv3JUVF9it4fPVh/Oa9g/D5FXz5tIn41oVTkeIK/LXLSXPjR5fNxNf/sQ0/eX03fnv9gjhfMVF8rDlYD0kUcMHMAswsPIINwXPdZs7rJbLeIWpZhj926YTefd1nTcuL6vkVRcXWymbMKcmEO0x1yi05cNc5k/H//rkLz6yvwB1nTYrqeeLlQG07PLIy5E2NvIwkLB4/Bh/uq0e3149kl7kKnea1bcfhEAVcMqcQQOAM/qVzCvHmzhNYV96A5ZNzLXkezd4TbRCF3rbHmYW957qNTMUfSkVjYHL5+OyhJ5drtBewVq8NW3OwAaIALJ+UixSXhNtXTMLP3tyLf2ysxMrTJlr6XCeDj/bXIzvVhbkDbrZ99YyJeHPncTy+6jAunVMY9mbcULSd2W6LznR7dLaXmw35htvLe2TDQU2TEgzrnV552O832lpIbYZHtDKSnMhNc+OwwfbyisYutHb7DH8PkRwiLp1biGfWV+CmJzZGDOyqquJoY1e/LqAkp4i5xVlYUJqFBaVjsKA0C89+UoHff1CO25/dgr/cvMT03ACgd0e30f+XgiBgal469ta0GX59Utveo+s8NwAUstJNsXKgth2v7ziO5ZNykJnsxItbjo3IM8/7atpw1SPr8H9v70fJmGS8dPup+OFlM0OBW3P5vCKcNyMPr247jvdtmqZLlMi8soINR5qwsHQMUt0STi3LQUOHFwfrol91kui2V7ViTIozqhdwMwrTkeaWsOlI9JXu8voOtPfIg1rL+7pu0TgUZyXjsVWHTLeyx5qedWwXzS5Et8+Pjw9Y02Le3OnFxwfqcdrkXOSm9bYQfvfi6XBJIv77jT3wWzxkbF9NGybmpoaqJ7OCQcmqc90V2uRyXZXuwGOsbC/3KyrWHWrAnJIsZKYE2nq/eEpgwv7Do2DCfqzVtvVg74k2nDklF+KAWRKSQ8T/XTMPAoBvv7RDdxAFAI8/8P/BdOXZ0Jlu85VuSTTWXt7pkZHqjq5Wp33ccBVbVVWx8UgTpuSlITvVFdVz9VUWXBtm5HW0VmnXO7m8r88vLcWYFCc2HmnC2vKGIX+tO9QIRVVx1YJi/PcVs/DG107Hzh9fiBduPxXfu2QGLppdgPyMJNx7/lR8fmkpVh9swH0vbrdkUGN1SzfS3BIyk40fFZiSn4b2Hjm0AkwPVVVR06o/dGuPq2Glm+z22/cPQlWBb184Df/8tBrPrK/AjqpWw2cf4+mZ9Ufx0+ALrNtWlOGb500dsqVEEAT87Mo52HD4Y/y/f+7CkonZyIjyzBCRXu/srsG/d1rXWnvVwhKsmDp2+AeG8WllM7q8fpw+JVAFXFaWgz+vOYL1hxoNnSeLF1UNVI1f334C1y0uwayiyC9UvLKCPSfacGpZTlSVfMkhYuH4MfjkUCN6fH5d7WoDbT4a/jx3Xy5JxNfOmYzvvrITT687irvPmWL4eeJFTyfBRbML8NM39uCtXTW4aHah6ed8a1cNZEXFFfOK+r19XHYKvnL6RDzy0SG8sPkYPr+01PRzAYEX7xVNXbh0Tu+1F2UmISvFid3HWy15jlClO8KObs3YdDckUQidl7TCzupWtPXIOH1yTuhtyS4H7jxrEn7y+h78bUMlbjmd1W69Pt4faC0fqkNmZlEG7jhrEn7/QTke+/iQ7q95rT3b7Mowt9PIyjALBqlp7eXy8EFOUVR0ev1IT4ouNqQFCy7DDVOrau7GidYefPEUa75PlI1NxcajTWjo8Oo6Twzou2k5lBmFGfj0hxcY/rihBF4jz0Zzpxevbz+OnFQXfnTZTFNdcNqO7mg+R99hasOt/9K0dcvwyAryM/T999c+72icYM7QnUD21bThzR0ncPa0sVhQOgaSKOKZ9RV4ccuxERO6W7t8+Nmbe1GQmYQ/fH6hrusuyEzCf106A997ZSf+9619eOCqOfZfKJ3UfvrmHhxrsu7F8faqVnxw34qofohpZzZPC7beLi3LhigA6w814ublEyy7Rqv5/Ar+vfMEnlhzBNuDL1Je2HwMD39xIc6O0PZ9oLYdXlkxtJ97oFMmZmPVgXrsqGoN7e42QjsPvrB06NANANcsKsHDH5XjT6uP4KblE0bMDcHtx1qRl+6O+KKoOCsZ80oy8cHeOnhkf9g2eyNe3VYNtyTigln5g95359mT8cLmKvzyP/tx6dxCS/477q9th6r2nucGAi9QZxZm4NPKFvgV1dQOYwCoaAqE7tIIO7o1DlFAocW7utccDITE0yf3v6H3+aWlePTjQ/jjR4fwhaWllh0PGO0+OlAHQQDOjHCD9O5zJuOtXTX43fvluHBWAabouPGphWSn2fZyh9ZePnwHg8+KFWVae7kyfMjvDG5ySHWZrXRH/rNpE+Sj+b4ezoLSLPxj0zE8v6lS902UHVUtSHdLmKjjZlssOEQBv7l+PlY+uRFPrTuK3DRX1DeBFUXF8ZZunDkluiLBlNAwtfaIX0d9hXZ066x056W7IQijs72coTuB/Pa9wACPb54/FQAwuzgD0wvS8dq24/j+pTOjqujE2ms7jsMrK/jaOVMM3Si4fsk4vLbtOP6+oRKXzS3CqZNyhv8goihUNXfhWFM3Prd4HP77ylmmP98Db+7F0+srsLO6Nao742vKG5CeJIVCaEaSE7OLM7HhSCMURR3UBmmlf2ysRFuPDwtKx2BOcaau7zHNnV78fWMlnll/FLVtHiQ5RXzhlFKcWpaDH7y6C195ejP+58rZuH6IiqbR/afhaGf9Nh5pjOrF2dbKZozPSRm28uF0iPjaOVPwnZd24Mk1R/H18xK/2t3j82N/bXvEGx+ai+cU4n/f2oe15Q04Z/rgsKzXidZubDzahItnF4SdbpzmlvDtC6fi/pd34uEPy/G9i2dE/VyagZPLNbOKMrDuUCOONnZikoEd8OFUNnYiP8OtO9QWZyWHhrtZYU15A5KdDiwcn9Xv7YEJ+5Pxw1d349lPKkbs3JdYkv0KVh9swNySrIhty27JgQevmYtrH12H+1/egRdvXz7szRstdJutdBuaXq4oSHGYe00YOtOt4/m0CnVatJVune3lWug2e55bc9WCEjz28WE88tEhXLd43LAtzrJfwa7qNiwozbL1Z69RSU4HHr9pMT732Cf45TsHkJPmjqprqK7dA5/f+I5uTTRrw7TwnKczdDsdInJS3aOyvZxnuhPE7uOteGtXDc6bkR96MSoIAq5bPA5tPTLe2TMyzju/tPkYUlyOfi1/eghCYG1HklPEd1/ZgW4vz6qRPdYfCkwGXz45B27JYfrXFQsCa0Je22Z8TUhrtw/bj7Xg1LIcSH1esJ1aloPmLh/2WzSFOZzqlm5895WdeODf+3Ddo+sx+0f/weV/WIMfvboL//q0GhWNnf3OwZXXteO//rkTp/7v+/jFf/ZDgIDvXDQN6797Lh64ag4um1eEl+9YjqKsJHz3lZ146J39Yc/R7dAml0dxXk4ztyQTKS4H3o3i+2JDhwdHGjojtpb3dfWCYozPScGf1xxGa3fin+3efbwNfkXV1Ulw8ewCAMC/d9aYes43tp+AqgKXzyse8jHXLhqHmYUZeHLNUVQ2mh821hu6M/q9fWZR7zA1s442dukaoqYpykpGa7fPkv3nXV4ZWyqasXRidtguhM8tGYfCzJG/Tz5WPj3WgvYeGWfpqM4tGj8GX1o+EVsrW/D0uqPDPl47E2228pzsdMAtiTjeOny3hE9WzZ/pDq0MG769XAvLaSbPdA/3tbHhSBNKxiSHVvCZ5ZJE/NclM9Dl9eOX/9k/7OPL6zvQ7fNbMojRahlJTjz95SUozU7B//vnzqi2T2iDHqMdiJeb5kZ+htvQ9hCjlW4AKMh0Gzo3PlIwdCcIrcr9jQGVlCvnF0ESBby4OfH3ch6obcf2qlZcMqcwqmEb43NS8a0LpqGisQsPvTv8N0eiaHxyOHAn/dQya7opFozLwrjsZLy+47jhQVGfHG6EoiJ0nluzLHht2g0CO2iDC79x3hR8+8JpOGtaHqqbu/H0+gp84/ltWPGLj7DoZ+/hlqc24ca/bMB5D63C3zdUYmp+On57/Xysvv9s3HnWZIzpUzWaNDYNr9xxGuaWZOJ3H5Tjvhe3D6rabK9qQWFmEvLS9f8AHijJ6cAlcwqxvarV8PqSrUPs5x6K5BBxzzlT0N4j4y+rDxu+1ljTznPP1dFpND4nFTMKM/DunlpDg6MGenV7NdLdEs6aNnSgcYgCfvCZmfD6Ffz8LfMrxPadaEdmsnPQCzltpoDZYWqtXT60dvtQqmOImqbEwrVhG480wedXccaU8BPf3VKg2t3Y6cUz60fuPvlY+Wh/YGBgpL+jfX3rwqkYl52MX/xnP441Rb5J5LGo0i05RCyZkI1NR5uHHZInKwqcokWD23R87bf3mA3dwenlEUJ3Q4cHh+s7QxsqrHLujDycPjkXL22tws6qyPMetJvCZo4/2SkvPQl/vWUpslPduOcf2wyvF+3d0a3/+9pAZ0/Lw6H6zn6T1yOpC4ZuvYPUgEBAr23rsWRwXCJh6E4Au6pb8c6eWlw4K3/QmoqcNDfOnZGHNeUNlp4Vs4N2Y+C6RSVRf44vnTYR88dl4S9rjmDbsRaLrowoQFVVfHK4EWVjU3W3Og1HEARcMa8YtW0ebDhi7AfgmoO9O3j7WjIxGw5RwHob93W/u6cWLoeIr5xRhrvOnow/37wYm79/HlZ9+2z89vr5WLl8AkrGJOPjA/VYW96AS+YU4KXbT8Wrd52GK+YXD1llGZvuxj9uXYZzp+fhla3V+PJTm9AWnP7d7fXjYF1HVPu5B/rs4nEAYPiG5JZKY6EbAK6YX4Sysan485ojoRcQiSo0BEjnyqNLZhegtdsX9W74Q/Ud2FXdhotmFwx7POHUSTm4cFY+3tpVY2oXvaKo2FfTjhmF6YPmKJTlpsItiaaHqVU0BV5QTjAQurWWzeMW/KzWvjecFmHN2mcXByfsf3zIkur6aPbR/nqMSXHqrmCmuCQ8cNUcdPv8eOSjQxEfa1WlGwj8//bKSmjY41C8sgKnFLuVYVa1l0f6e7pJWxVm0XlujSAI+P5nZkAA8NM39kScZL7dwE3LeBmfk4qnvrQELoeIrz692dD3Oi10R1vpBoDzZgSOIundOKRVuvMz9Q1SAwIBXVZUNHSOrmo3Q3cC+M17BwAA3zhvatj3X7doHFQVeGVLVSwvyxCfX8E/P63GhJwUUwMwHKKA/7t2LhyigO+8NLhKRmTGsaZuVLd0W1bl1lwxPzCx+fXtxlrM15Q3oCgzCRNz+7ewprklzCnOxIbDjZavWQKA9p5AyDp1Uk6/yoUgCCjNScEV84vx48tn4bW7T8eun1yIrT84H498cREWT8jWNSwuxSXhsRsX4YZlpVhT3oDPProeJ1q7sft4K/yKaknr3pIJYzAhJwX//LTaUJV2y9FmpLslTM3TPxlecoj43sWBFsVf6GhRjKftVS0ozU7p14EQycVzzLWYa8cqrpg/dGt5X/91yQw4HUJow0U0qpq70eGRMb0gY9D7JIeI6QXp2HO8zdS6zaPBFvhSA8OUtJbYKitCd3kDctPcmF4w9N9TlyTi7nMmo7nLp6sNeqTr8sr456dVhrsy6tp7sPt4G86cOtbQcL0zpozF3JJM/OvT6tCNw3BCg9RMVroDzxm4ybK6vD7i42RFhWSy0q3t+ZZj2F4eaZDaRouHqPU1vSAD1y8txcajTXhr19Df63ZUtSI3zYUinZO542V2cSYev2kRPLKCm5/YpPvITqjSbSJ0nzY5F0lOUffxrto2DxyigJxU/aFb62CqbWXoJgttP9aC9/bW4ZI5BYPOpmnOmjYWuWluvLS1KmF3dn+0vx4NHV5cu6jE1CoDIDCo4WvnTMGB2g48/GG5RVdIBKw/HKgeWT2ob0p+OqYXpOPfO2t0TZ4FAgPdjjR04vQpuWG/Zk6dlIO2Hjl0dtVKqw40wOdXcd6M4YdtJTkdyEoxvi9Vcoj46RWzcf9F07Gvph1XPbwOL28N3DiMtMpKL0EQcO2iEjR0ePHR/sgvUDUe2Y8d1a1YMH6M4SE5583Iw2mTc/DS1irsqrZmJZXV2np8OFzfaaiTYHJeOibnpeHdPTWGQ7Cqqnht+3Hkprl1f02Nz0nFl0+biN3H20J/H4zaWxP4mpg5xM/MmUWZaOz0oq49+hdsldqObh2TyzXFFrWX17X3YF9NO06fPPxavWsXlWBcdjIeX3V4xO2TN+q37x/EN5/fjj+vPmLo43pXhRmf2HzDsvHo9vkjFj2srHTPLMzAmBQn1ga3WkR6TrMh30il22x7eWiQWoT5A5uONiE3zYWyXHumht97/lSkuyX8/K29Ydv3PbIf+2raMLcky/Tr2FhYPikXv/v8fDR2evC9f+7QlQ+qW7qR5BSRY2IHerLLgdMnj8Xmima0dHmHfXxtWw/y0t2GbniN1rVhDN1x9uv3DkAQgK+fG77KDQRevF6zsBgVjV3YGGy/STQvbj4GQQCuXhh9a3lft6+YhOkF6Xj4w3I8ufYI/rGxMuKvRP3vQolFO899ykTrp+NfMb8Yrd0+rDoQ+cWSRntRdfoQqzu0c91m2nCHorWFnTsj+onVegiCgDvOmoTfXj8fTZ1ePLcx0Ao+x6LzclcvLIEg6G8x3328DV5ZwaJhVoWFIwgCvn/pTAgA/nuYFsV42VWlnUfMMvRxF88uQEOHNzQ5WK+d1a040tCJz8wtNPSC6q5zJiMn1YVf/Gd/VG3RQw1R0/QOU4v+5oi2o3tCFJVus0fB1pUHvuYjtZZrnA4RXzt7Clq7fXhq7VFTz5vI2nt8+PsnlQCAhz8sR127/hfjHx0IhO4zoliTdNncImQmO/HXTyqG/JrvrXSbD2qiKGD55FzsPt6Gps7wgUZVVfj8qunncxo4061VuqOZ19P344b6em/v8WHP8TYsHq+vmyoauWlufO3cyTjW1I0nw3yt7D3RDp9fteT4U6xcNLsQ1y0qwdryRry3t27Yx1c1d0W9o7uv82bkwa+oum5417b1GD7Ox9BNltta2YyP9tfj0jmFmBahhQwArlscCLMvJmCLeUOHBx/sq8Ppk3MtnTj5f9fOBQD85PU9+O4rOyP++uKfP0Fr1+i+y0/mqKqK9YcaMSUvbdhVUdG4bF5gYv9rOlvM1wRfWC8fokK4ePwYSKJg+TA12a/gg/11mFWUYdnX63CumF+MZ25ZiowkCdML0pGZbM2+66KsZJw+ORcf7KtDQ8fwVU2jQ9QGmlEYbFE80oS3I7Qoxou2L93oi8aLZwf+7r6109g03N7W8iJDH5eR5MQ3z5+K+nYPXo7iZ9q+E+0Qhd6dsQPNCoZuM8PUKhq7kJnsRGaK/r+rSU4HctNcps90rwndkBs+dAPAVQsDE/b/tHpkTNiPxvObjqHdI+PCWfno8Mh46J0Duj5O9itYfaAec0sykZtm/Pt+ssuB6xaV4FB955AzNrTQ6rag0g0AZ0zOhaoC6w6Fv4ErBztSzFe6tenlBs502zRIbUtFMxTVntbyvm5ePgHjc1LC3rjRhlBa0YkVS9+6YBpSXQ78z5t7Ih7JVFUV1c3dKBkT/RA1zTnBLrl3hznXLfsV1Ld7UJBh7Guvt72coZss8ut3A1XugRPLw5mcl47547Lw5o4TCTcw5V+fVkNWVFwXHGxklbklWXj/vhV4+stLI/669cwy+PzqsGeg6OR2tLELNW09tu2ALxmTgsXjx+DdPTXD7iJVFBVryxswszBjyBeCqW4J88ZlYeORJsgmJksPtKWiGS1dvtAwlFhZVpaD9+4NfD1b6brF4yArKv71afWwj918tBmiAMwvzYr6+bQWxQfe2qv7KEGs7KhqgShg0EDO4cwoTMf4nBS8vbtG97RYv6Li9R3HUZqdgvlRDB26akEx3JKIfxsM+kCgvbxsbNqQg9umF6RDEMytDato6sR4A0PUNMVZyabay1VVxZqDDZg0NhWFmfpuijmDE/bbemQ8udZY6/VI4PMreGLNEYxNd+O31y/AsrJsPL/5mK5Ohm3HWtCmc1XYUL64bDwA4NlPwk+Jt/JMN9Db4aAN0xtIO4Mtma10B28S6DnT3RE8ix1t6HZLDjgdwpA/G7VuRbtDt1ty4HsXzwh742b7sehuWsZbXkYS7jx7Mo42duGZ9UeHfFxDhxceWTF1njv0nOlJmD8uCx/vr48Y9Bs7vVBUY5PLASCflW6y0uajTVh9sAGXzyvCZJ0Dfa5bXIJunx//3mH8RYpdVFXFi5urkJEk4YKZ1r+IH5+TihVTx0b8ddOpgR+IH+s810knJ61ibPUQtb6umF+EHp8y7ICRvTWB1sHhKlmnluWg3SNbsnNY8/6+QAtarEM3EHhxYPSH73AumJmPjCQJL26OPPNCVVVsqWzG9IKMqF84AoEWxbvPGbpFMZ52VLVicl6a4RZQQRBw6ZxC1LZ58P/+tUvXTZ4NRxpR2+bB5fOKompVTHVLWDF1LDYdbdLVpaDp8MioaOwasrUcCAzyK8tNxZ4o5yF0e/2obfNgvIHWck3xmGTUtvdEPQT0UH0Hatp6DLdCXzG/CGW5qfjjR4cMHxNIdG/sOI7jrT1YuXwCkpwO/OAzMwEMP4kaAD4OtpavmDb8/IqhTMxNxRlTcvGf3bWoDRMCvBae6QaAcdkpmJCTgtUHG8L++ULPZzLkG1kZ1uEJdFBEO70cCHzND1U02nS0CWluKeLXtVUunJUf9sbNjqoWFGclIyeKjoh4u+X0iSjOSsZv3z845LEE7diLmcnlfZ0/M9B1Eul4Z02r8XVhAJDulpDicoT9ehvJGLrj5NfvHYAoAPecO3yVW3PZvCK4JREvbkmcnd07q1uxv7YdV8wvHnZdjF1KxqRgcl4aPj5Qn5DnLCkxaGejT7ExdF8yJ3C2dbgW86FWhQ0U2tdt4bnu9/bUIj/DjdnF9r+4iYUkpwNXzC/G/tp27Iww4KyquRv17Z6oW8v7WnnaBJRmp+APH5Sj3sSwLis1dHhQ3dId9WT4O8+ejNMn5+K5jZW49a9bhu3W0Cb1G20t7+uSOYVQVOCd3fqm4ALA/prAXvZIU72BwL7uisauiFOnh1IZ3MtsZIiapigzGaqKqF8s6v3eMJDkEPGb6+dDEgXc8tQm7KuxfgBjPKiqisdXHUGKy4EbTgncYJ9VlInPLR6HTw434Z1hbnB+tL8eWSnOqLox+rpx2Xj4FRXPbawc9D6fRXu6+zptci6qW7pDswX60m6Kma10S6LWXq5nerm5SjcApLqksNPLe3x+bD/WikXjxxiaDREtQRAG3bjp8Mgor+/AvHEjq8qtSXI68L1LpqO9R8av3w1/9KKqOfB3qdiiY2XnBlvM34vQYl4bxY5uIPD/qCAjKRTaRwuG7jjYcLgRa8sbceX8YkwaG/5MWjgZSU5cNLsAm442615Kb7cXNwfO42lnzuPlrKljUdfuibqyQaObqqpYf7gR0wvSkW1iaudwctLcOGNKLlYdqB/ybjMQOLPpksRhW+kWjR8Dp0OwbJjaofoOHG7oxHkz8kfEdFa9QjMvNg99PnhzReBu/OIJ5kO3W3Lgvy4Jtii+mxgrxHrPI0b3ojHNLeGJlUtwzcISfLCvDtc//smQw6o8sh//3lmDGYUZmJKvf/XaQOfMyIPTIeCtXfq7t7QhakNNLtdow9T2RtElUhGcXF4aTXt5sIpUFWWL+ZryBjhEAaeUGW+znVuShcduXIxunx83/WUjjjXpWyOUyNaUN2DviTZ8bsm4fufr771gKlJdDjzw76GPedS3e7CzuhVnTDG2Kiycc6bnoSgzCc9trBx0BlqrFDstqnQDfVeHDW4x10Ky2XZ2hyhAEHpvGkTS3iNDEgVT59bT3FLYm3nbj7XA61dsby3va1ZRJj67qPfGza7qVqgqLFlnGS+XzinE4vFj8LcNFaGbk3317ug2f6YbAKblp6NkTDLe3VM7ZMFLC90FUXS45TN0kxV+/d4BOEQBXzNQ5dZctyhwbvqlBKh29/j8eHVbNablp2OOwTOEVjsr2Dqmd3UQnVwO1Xeivt0Tqhzb6fJ5RZAVdcizqj0+PzYeacLi8WOG7Q5JdjmwYNwYbDrSZHg3bTjvBatC59lwFCSe5hRnYlp+Ol7dVh12FQwQOMsOAAujmFwezoWz8nHKxGw8v+mYqYFdVuk9j5gV9edwSSJ+ed1c3HPuFOysbsXVj6xDeV3HoMetOtCA1m6fqSo3ELiRfPrkXKw/1Khr9Qww/ORyTWiYWhQ3YrVKt5HJ5ZpiExPMfX4FnxxuwoJxWUhPim7Y4OlTcvHrz81HfYcHNz+xEY0GWvcT0eOrDsMhCvjyaRP7vT0vPQl3nTMZFY1deGZd+LPWq4Kt5WbOc2skh4gvnFKK2jZP6PuoRgvBVla6Ty3LhSgAa8Oc6/ZZ1F4uCAKcDlHnIDUf0pIkUzdrU92OsO3lm2zczx3JfRf23rjRfj6MtPPcfQmCgB9eNhOKCvzszcFHL6qbrW0vFwQB583IR3VLN/aFCflAYEc3AOQbHKQGBCaYt3vkYbuuRhKG7hhbf6gRnxxuwlULijExil2EyyfloDgrGS9vqTa8U9Vq7+6pRVuPjOsWm9/NbdaSiWOQ4nLwXDeFpbVn2zVEra8LZhXALYlDtphvqWiGR1Z0TyZeNikHnV5/xNZpvd7fW4cUl8PWc+3xIAgCrltcgrYeech20y0VLchLd1v6guMHn5kJFfrOltptR1ULnA4B0wujrzwDgT/XvedPxYPXzMGJ1h5c88d1g84Ia3+3L5tnLnQDgcnpsqIOOwdBs6+mHVkpzmFfxGmV8GjmIRzVdnSbqHRHM8F8+7EWdHhk3d8bhvKZuUX4yeWzcLihE196alPCDV/Va8/xNqw+2IBL5hRiXJhW/y+fNhElY5Lxu/cPhr25oK0KO9OC0A0An10yDk6HgL8OGKjmka090w0AmSlOzCnJwrpDDYNe6/ksai8HAsHdp+O1ZKfHj1RX9K3lQOBMd7gAteFIE1ySGPPA2/fGzcMflkMQEPcCkllzS7Jw9cJirD7YgA/3918hVtXcBZdDxFgLz6yfH7yB//4QLebaIDRtMJoRWkv6aBqmxtAdYzOLMnDPuVPwtXMmR/XxoijgmkUlqGnrweqD8Q2YL2w+BkkUcOWC4rheBxBo91w+KQdbKptH7coUit4nhxshCMApMbiTnuaWcN7MfGw80hT2hXdoHZDOM5vLgm2mZleHNXV6sbmiCWdMyY3b/AU7XbmgGJIohN3Z3d7jw/6aNiyeMMbSG4SziwMtiusPN+oOjXZQVRU7qloxozADbsma/7efW1KKv9y8GLJfwRf/vAFvBgd4dnpkvLunBksmjLHkbOD5M/PhEAVdK9gURcW+E22YUZAx7P/HnDQ3CjKSoupCqGjsQpJTRF4UqwVDle4o2stXR3meO5ybTp2Ae86ZjB1Vrbj9r1viOmk/2krVn1YfBgDcekZZ2PcnOQPHPNo9Mh4acI7Vr6hYfbAec4ozLVsRmZeehItmF2LdoUaU1/VW9qyqPA90xuRctPXIg264WtVeDgSCu5728g6PjHQTQ9SAYHu5199vQ4LsV7C1ohnzS7Is+95lhHbjpsvrR1luatQdJonkOxdOR7LTgZ+9ubdfF0N1SzeKxyRDtPDc/JIJ2Uh3S3h3iB3htW09SHY6kB7FLIDCzNG3NoyhO8Yyk5249/ypUU1F1Vy3KP47u4+3dGNNeQPOmZ4X1e5LO6yYlgd/cBUTkUZVVWw43IgZBRnISrHvPHdflwcrgK+HqXavOdiArBQnZhXpu6O+sHQMXJJo+lz3h/vqoKjxmVoeC7lpbpwzPQ9ryhsG3ezYdqwFimpda3lffVsUo51YbVZ1SzcaO72WV4rOmpaH5287FZnJTtz196348+rDeHdPLXp8Ci6fb83N1jGpLpxaloPVBxvQPszQs2PNXej0+nVX82cVZeBgXbvh/y+VTV0Yn50a1Q2azGQnUl2OqNrL15Y3IC24KtAK3zx/Kj6/tBRryhtw3wvbda+Ds9Lbu05g/n+/g//6505D3SDHW7rx+vbjOLUsB3Mi/L2+eHYBlk7IxnMbK/udY912rAUtXT6cNc2aKrfmxtD6sN6BaqGVYRZWuoG+q8P6F1i0IGVF6NbfXi4b3oowkPbxXX2OAO090Y5Orz/mreWaJGdghRgAy77u4q0gMwl3nDUJh+s7Q2vuVFVFVXO3ZUPUNC5JxIppY7H9WAvqwlSka9t6UJCZFNX3Ula6KSGMy07BsrJsvLu7Vvc5OKu9srUKqgrLd3OboZ3b+mh/+DtudHI6WNeBhg5vTFrLNWdNG4v0JAmvbusfups7vdh1vBWnTcrVPdgnyenAwtIsbD7abCrUvbe3FoIQGAg0Wl23eBxUNfD9qS/tvJ4Vk8sHykvXtyO1Lyv3rgOBVWGAPUOAZhdn4p93LseUvDT87M29+NFru+EQBVwyu8Cy57hodgG8fgUf7Iv8vXvviUCo0rtWaGZRBnx+FQfrwp83DMfnV1DV3B3VEDUg0J5fPCbZcHt5e48Pnx5rwbKybMv2PQuCgJ9dORsXzSrAGztO4Cev79YdfK34O7r+UCPueW4bfH4Vf99QiV+9E36qcjhPrj0CWVFx64rwVW7NUMc8Pg6+DlhhUWu5ZsmEMZiWn46Xt1Shyxuo4NtV6V44PgvJTkeoA0LTG7otai/XE7p7ZFOTy4Heyed9Ox82HAncTF4Sp9ANAJfMKcAvrp2Lb5w7NW7XYLWvnlGGoswk/Oa9g2ju9KKly4cur9+y41V9aS3m4b5/17Z5ouoYAgI3DwCGbkoA1y0aB69fGXY1kR1UVcVLW6qQm+ay/C6yGeOyU1A2NpWrw6ifWOznHsgtOXDJ7ELsOdHWrw1x3aFGqGpvBUOvU8ty0e3zhyZUG+WR/Vh1oB4LS8eMyB2kep01bSxy01x4aUv/nd1bKprhlkTd3QVG9d2ROvBsqaKoOFjbjhc2HcP3XtmBi36zClO//xZufWazZQNitocml2dZ8vkGKhmTgpduX45TJmajtduHM6bkWvr36MJZBRAE4K2dkVvM9U4u12jD1Iyc6z7e0g2/oka1LkxTlJWM6pZuQz+HNhxugl9RLWkt78shCvjN9fOxrCwbT6+vwO8/KB/0GFVVcaShE69srcIP/rULn/n9akz7wdu4/vH1aI6whSGS3cdbceszmwNrTm8/FfNKMvGHD8vx1Nojw35sW48Pz208hqn5abqGoM0pycQ1C0uwprwh9ML/owP1yEiSTK8KG0gQBNxw6ni0e+TQTVWvDSvDgMDPkVPKsrG1sjkU8AFADnYsSKL553M7RVQ1d0ecdO9XVHT7/KZDd6o70D7e9/vepqNNEAVgYWmWqc9tRmAmyLiob7QlomSXA/dfPB2t3T789v2DocnlVle6AeCsqXlwiMKg1WE9Pj9au32h8GyUNvGc7eUUdxfPKUCaW4q4Iscum44242hjF65aUGzZHXmrnDU1D7VtniEnKZI+iqJC9ivD/hoJNzfWH2qEKABLo1jBY4Y22fm1PtXuNeWBNsEzDA5KMnuu+5PDTej0+kdta7nG6RBx1YJiHG3swqajgeq2X1HxaWUL5pVkWTroqK/Q2dIeGQ++vQ8f7q/DQ+8ewI1/2YB5//0Ozv/1Knzn5R14buMxtHX7MLckC+/sqcX1j39iyZ7vHcdakeJyYHKe/hWURmWmOPHMLUvx/Utn4EeXzbL0c49Nd2PJhGx8dKCuX7gYaF9NGxyioPvPObMwcJPFyLlubS/y+CgGnWqKs5LhkRU0dOgPrKFZD1Osv5Gd5HTgTzctxszCDDz07gE8ufYI1hxswO/fP4gvP7UJC3/6Ls7+5Ue494Xt+OsnFahp9WBhaRY+OdyEax5dh8owu6IjqWjsxM1PbILHr+DxmxZjyYRsPLFyCcrGpuInb+wZtljw3IZKdHhkfPWMMt1tqd++cBpSXA78z5t7UdPagx1VrThj6lhINrxGuWpBMVJdDvx1fQVUVQ2tDLPj+8vpk3Ph86vYcKR3mKHPwnb2W88oQ1OXF1f/cR12DTGsUxvEZzZ0p7i0SnegvVxVVWw62oxZRZmj4ix1orl8XhEWlGbhr59U4OMDgZtRJdnWh+7MFCeWTBiD1Qcb0O3tPToQ7Y5uTW6aC6Iwuird5r6CKG5SXBIunVOI5zcfw8MfluO2M8ts+eESjjaoKJFayzVnTRuLJ9YewUf763W3IGpUVcWNf9mIDo+MB66aE9rzOtqpqooTrT34tLIFn1Y2Y2tlM3Ydb9PVyjw5Lw2P37gIZQb2zceSoqjYcKQRs4szkRHjH+qnlOUgL92NV7cfxzfPnwpBELCmvAGl2SlhJ/FGMr80C25JxPrDjVGtGtRW3Jw/c/S2lmuuWzwOf1p9BC9uPoalE7NxoLYdHR4ZC21oLe/rkjkFWDJhDF7YXIUXgjdD3cGJvAtKx2BhaRbmjxuDgswkqKqK37x3EL99/yCuemQtnvrS0qgDs6Ko2FXditlFmaZ3EQ/HLTnwlSGGWpl18ewCbDzShI/21+OSOYVhH7P3RDvKclN1DwIcl52M9CTJYOgOTi43UenuO8Fc7xCv1QfrUZCRhEljow/7kaQnOfHUl5fg2j+ux09e3xN6u9MhYFZRJq5ckIWFpWOwoDQLxVnJEAQBT687ih+/vhtX/3Et/nLzEl1nXuvae3DTExvR1OnBI19cGDrWk5PmxjNfXopr/7ge972wDWNSnDgjzA0Gr6zgybVHkZ/hxhUG5gbkZyThzrMm4ZfvHMDdf98KwJpVYeGkuSVcvbAEf/2kAlsrW3rPdFvQ7j2QNsl+7cEGnB1cjapNG3da8PV+/dJSZCY78fXnt+Gzj63Hw19cGHoejVaZTrNgkBrQG+IP1XegqdOLKy2aD0H9aUcvrn5kHX73fqDDpTjLnmr+eTPy8cnhJqwpbwi1m2s7tqMN3ZJDxNh096ja1c3QPYLddfZkbKpowi/+sx/v7K7B/107D9MKzK2LGU6nR8abO09g3rgsTM2397misXRiNpKdDny0vw53nDXJ0MeuOtgQqjZc/oc1uPPsybj77Mm2VcfipccXWD+1taI5ELSPNYd2KQKBQUCnTMzGmGGGjsmKgv/srsU1f1yHP9+8GIvGx+9M1lD217ajucuH6xbHfkWWQxTwmblFeGLtEeyoakVWihPHmrrxhVNKDX8ut+TA4gljsPloMzyy39CUV1VV8f7eWkzIScGkBL05YqWp+emYNy4Lb+48gR9fPit0nnuxzaFbEAQ8eM1c/HnNEUwvSMeCcWMwvTA9bDeQIAj45vlTUZyVjO/9c2foa2jJBONfQ4cbOtHukUf0flkgcK77J6/vwVu7asKG7vYeHyqbukJDCvUQBAEzCzOw+3gbFEXVNbU3VOk20Wrad1e3nqB6orUbh+o7ce0ie9dv5qUn4dlbTsGjqw6hLDcVC8ePwczCjCFvYty8fAIKMpNwz3Of4vrHP8EfvrAA50bolmnr8WHlE5tQ0diFn189BxfN7v//sWRMCp7+8lJc9+g63PbXLXjuq8sG/fd5fftx1LT14P6Lphv+2fuVM8rw3MZj2Bz8ml9h4/G3G5aNx18/qcCzn1TAKysQBdhS+JiWn47cNHfotQnQp9Jt0fNdPKcQY9Pd+Mozm/GVpzfjZ1fOxueX9v6c0kKyVYPUtBC/8Ujg/9PSifZ+bz6ZLSwdgyvnF+FfwY47O850A4Fz3T97cy/e31sbCt217dHv6NYUZCSx0k2JoTQnBf++5wz8+r0D+NOqw/jM71fjnnOm4PazJtnW9v3mzhPo8vpDE9QTTZLTgVMn5WDVgXq09/gMtSw9vuoQHKKAP35xIX793kH87v2D+M+uGvziurm2DCiySpdXxitbq/HX9RU41jx8G2CPzw9tiK0oANMKMnDejHwsCFY5Juak6l4p8eG+Otz19634wp824LfXzx/0Iive4nGeu68r5gdC96vbjqMsWME6I8ozm6eW5WBteSO2VbbgFAN/nj0n2nC8tQe3nD7R1hf0ieS6RSX4/r924c2dJ0Kh2+5KNwCUjU3DA1fN0f34zy4Zh/zMJNz57BZ88c8b8OvPzselc419DWnn/OeO8Mm7hZnJWFCahQ/21qLH5x8UBA/UBo4MGd1DPrMoAxuONOFYc9ewW0NUVcXO6lY4RAFFJs4+Gl0btsbCVWHDKc1JMfR39MJZBXju1mX4ytOb8dVnNuO/r5iNG4ITvPvq8flx6zObsedEG+4LTk0PZ1pBOp5YuQQ3/GUDVj65ES/dsTx0M1BVVfxp9WGkuhxR3ZxMcgbOsd7z3KeYVZSBvPToKmx6TCtIx9KJ2XhzxwnMKEy37ea8IAg4fXIO/rXtOOrae5CXngRZsW5Pt2bxhGy8fMdyrHxyI773yk4cb+nGvcEOrfaeQEiOZu1TX2namW6vFrqDQ9SiuNlI+n3noul4e3cNZL8addV5OONzUjE5Lw3v7a0L3eDUzmIXmHjO/Iwk7KxuhexXYtbNa6eR/yc4yWnrDv5552mYmJuKX717AFf8Ye2QZ3PMemlzFdySiMsMVBti7axpYyEbXB22q7oVa8sb8Zm5hbhgVgFeves03Hv+VBxu6MBVj6zDg2/vQ48vfntOwzne0o3/fWsfTv35B/j+v3ahpq0HSyZkY+nEyL8unFWA71w0Dc99dRl2/vhCvPX1M/A/V83BtYtKMGlsmqEdjmdPz8Pzt56K9CQn7vjbVjyxZvghObG0/nAjHKIQt8moc0syMT4nBa/vOI5VB+ohCIh6irr2cesNrg57b0/gLNdoP8/d12XziuCWRLy0uQpbKppRlpuK7NTYrIszasXUsXj+tlORFVzL9adVhw3NStAml88b4ZVuINBi3un1D5rWDAB7DE4u12jD8/QMU/vrJxXYcKQJF88uMHXjWmsv17s2TPtZZXTAYqwsLB2DV+5YjtLsFHz/X7vw4Nv7+q0f8ysqvvGPbfjkcBNuPnU87j5ncsTPt3hCNh754kK09ci46S8bQ+2jHx+ox76adnw+2PIcjcvmFuLOsybhvgvsn0R947Lx8PoVbK9qtXW+jXbOf1154Hu/N7in2+rBbZPGpuGVO07DvJJM/P6Dctz3wnZ4ZSVUmbaq0q1VzjcdbcaksamjerhnIijKSsaD18zFty+cZusRpPNm5KOhwxMa7Gn2TDcQmGCuqDA0HyORsdI9Sswbl4XXv3Y6/vBBOR756BCufHgt7jhrEu4+Z7KhVtRIDta2Y+PRJlw+ryjqH4ixcNbUPAC78dH+et2V1z+tPgwgsGYBCAxEuefcKbhgVj6+/eIO/PGjQ6EWfjvWDhnxaWUznlh7FP/eeQJ+RUVZbiq+deE0XLOwODSoJJbmlARWCq18ciP++409qGruxvcvnWEovNtBUVRsPNKEOcWZpgfAREsQBFwxrwi/+6Ac7+6txdzizKh3hc8pDqyPWX+oEd84T//Hvbe3FpnJTiyecPK08GUmO3HhrILQwKZE7czRzC7OxD/vOg0rn9iI//n3XlS3dOMHn5mp6wXS9qoWZKU4UWriDHKiuHh2IR749z68tetEqEVRY3RyuUZ7/O7jrUOeFQeA7cda8NM39qA0OwX/Y6ASHE5eehIkUdAVulVVxZryRkwvSNd9/jseJuSm4uU7luMrz2zGHz86hOMt3fi/a+fC5RDxg1d34e3dNbhsXhF+dNksXR0150zPx4PXzMW3XtyOm5/YiBduOxV/Wn0YDlHAl06fGPV1CoKA71w0PeqPN+LCWQXITXOjocMDt43H0LQOiNUHG3DlguLQOjc7Kn9j09147tZluOe5T/HKp9Wobe8JHekwe6a7b3t5VXMXqlu6h+yIIGsZmY8QrfNn5uHRjw/hvb21WFA6JtQWnmemvbzP2rBop6AnEla6RxG35MB9F0zDq3edhqn56fj9B+W47PdrsO1Yi+nPrSgq/uufOyEIwJdOm2D689mpNCcFZbmp+Gi/vtVh1S3deGPHCZw2OQezi/tXi6YXZOCfdy7Hdy6ahmPN3bj20XX46Rt7+k1ojAXZr+CNHcdx1SNrcdUj6/D69uNYPikHT65cgvfuXYEbl42PS+DWjMtOwct3LMfSCdl4Yu0R3PX3rXHvDNhzog2t3T4si1Nrueby4BTzaFaF9eWSRCyeMAafVrbo/m9b09qDndWtOHva2ITbNGC36xb3Bu143yjTozgrGS/dvhzLyrLx1LqjuOPZLcN+n/H5Few53oY5xZmj4ujAuOwUzC7OwLt7agcNctx3og1jUpyGd75OzkuDyyFGHKbW2uXDXX/fCkEQ8MgXF5q+qewQBRRkJulqL99X046GDk9MWsvNyklz4+9fWYYLZubj1W3HcfMTG/Hzt/bh7xsqccaUXPzqunmGbrZeu6gE/3XJdOyvbcd1j63D2vJGXDa30Ja1RnZwSSI+vzQwUNbO768FmUmYnJeGteUNUFXV0j3d4aS4JDx6wyLcsKwUa8sb8YNXdwPobQ+PVu8gNT82HQ1MY+d57tFj/rgxyEl14f29ge66ujYPxqQ4TRX+tNb00TJMjZXuUWh2cSZevfs0/PGjQ/j9Bwdx9SNr8aPLZuHm5ROi/px//aQCm442Y+XyCVhQmvjfJM+cOhZPrTuK/bXtmF4QuTLyxJoj8Csqbj0z/OA1ySHizrMm44KZ+fj2SzvwlzVH8MG+Ojzz5aWGp1BHo7yuAzc/sRHVLd1wSSKuXzIOXzptou1D84zKSnHhmVuW4r4Xt+PNHSdQ174Bf75pMcZY1Nb76rZqvLbtOH5+zRxdZ/U+CbZhR9vObZXJeemYVRQY5nS6wVVhA506KQerDzZga0Uzlut4kf7+vsDU8kjDj0ar5ZNyURzclzwSQjcQWL3y9JeX4jsv7cCr245jxS8+jBgAZUWFR1Zs288dDxfPLsQv/rMf6w414KzgFGVFUbGvph3zx2UZvrngkkRMyU8bsr1cVVXc9+I2VDV343+umj3oxmu0irOSh11d6fMreGZ9BQCY/t4QK8kuB/54wyL89I09eGrdUXxyuAlzSzLxxxsWRXWu+dYzJ6Ghw4vHVwW7zc60Zzq+XT6/tBQPf1hu+8DV0yfn4ql1R3GovgO+YHu5nUFfcoj46RWzUZyVggff3gcASHObuxnVt9KtDVHjee7RwyEKOHt6Hl7aUoVjTV2oaesxfYY8tKt7lAxTO7lKHycRpyPQHv3G187AhJxU/Pcbe7DB4FlQTVVzFx58ex9KxiTj2xdOs/hK7XFWcGrpR/vrIz6utduHf2ysxPSCdJw5zIueyXnpeOn25fivS6bjaGMnbn5iIxo7zO/YjcSvqPjWi9txorUb3zxvKtZ/9xz87zVzEy5wa5KcDvz++gW49cwybKloxjV/NL7jNZz/7K7BN5/fhvf31eHmJzahrcc37MesP9QISRRsn1qtx9fPnYKLZxdgsckJ79pAuE90fi2/t6cWkijYOsU3UTlEAd++cBquWlA8oqa2uyUHfv3Z+fjmeVORmeyECgz5yyEKmF2cYXj4WiK7aHYBAODtXTWht1U2daHL6x/2BupQZhVloK7dE3Yn+p9WH8Z7e+twxfwifMHCVtfirGS0dvtC51cH2n28FVc+vBbPbazEjMKMuHfkGOEQBfzospn48WUzce70PDy5compIzzfvWg67jxrEm5bURY6gz9SFGUl455zp+CahfYeYdE6IdYcbOhT6bb3JbwgCLjjrEn4/ecX4PTJuYaHGA6U5uobuhtRnJWMkjEj/1gM9dJmx7y3txa1FoTu/D7t5aMBK92j3LSCdDx+0yJc/oe1+Npzn+LNe84wdG5MVVV875Wd6PL68diNc0wP0oiVZWU5cEsiPt5fj9tXDL067O8bKtHp9eOrZ5TpqqA4RAG3njkJbsmBH722G196ahP+/tVltp0ZfnLtEWw71oKvnD4RXz/P+H7meBBFAf91yQwUZyXjx6/vxlWPrMUTK/XteA1nw+FGfO25T5Gd6sJn5hbhqXVH8dWnN+PpLy8dctWNP3iee964rIT4O3vBrAJcMKvA9OeZXZyJVJcDb+w4gXNm5GN+hP+mXV4Zaw81YllZTsx3lCeKKxcU48oFI28HrCgK+Pp5U0bM17yVJo1Nw9T8NLyzpxY/uzIwsXZfTaBKPSPKF/2BIFeFPSfasCK99wbUpqNNePDt/Zg0NhUPXDXH0hb9vru6+67X9MoK/vDBQTzy0SGoAO46exLuOXeKZbNXYkUQBKw8bSJWnhb9+WuNKMbuHLYdvnGe/UPblk3KgUMUsKa8AadMDNygsXJ6eSSXzSuyZHhuarA9vbKpC4fqO3Hl/MQdyEvROWNKLlySiJe3VsEjK6YmlwOjr72cle6TwOS8dPz86jmoa/fgG89/Cr+ifzLuy1ursfpgA65bVIIzpoycapm2OmxzRdOQlQaP7MeTa4+gICPJ8A+Um5dPwD3nTMaOqlbc/tctg84fWqGisRO/fGc/xuek4L4LRkaHQV83L5+AR29YhE6vjOsf/wTv7ak1/Dn2nmjDV57ZDJdDxFNfWoofXTYTK5dPwIYjTfjGP7YN+Xd59/FWtHvkuK0Ks4vTIeLGUyfgcEMnrnx4La754zq8ueNEaLBOX6sPNsArKzhvRl4crpQoehfPLkRTpxcbjwTOfUY7uVwzsyjwcX3PdTd2eHD337fC5RDxxxsWWX5zLtzasB1VLbjs92vwuw/KMTkvDa/edRq+feH0ERe4KfbS3BIWjMvCJ4eb0BWc9WD19HK7SQ4RbkkMneeO11YRsk+qW8Jpk3KwqzrwvdbMjm7t86W7JYZuGlmumF+ML5wSGIrxu/cP6vqYuvYe/PSNPRib7sb3L51p8xVa76ypY+HzD7067LVtx1HX7sGXTpsQ1XmsbwZ3ka4pb8C9L2zrt0LFLFVV8d2Xd6LHp+DnV89Bsmtkvii7cFYB/v7VZUh2OXDrXzfjr59U6P7YY01duOmJjfD4FDx+0yLMDg6L+uFnZuKyeUV4e3cNvv+vXWGH5Wn7uUdSy6Ze3714Ot76+hn47OIS7KxuxV1/34oVv/gIj686hNbu3rZ77SbHyXiem0a2i+cEukLeCraY7zvRBocoYHJedMcEZvSZYA4EV1w9vw21bR78z1Wz+1WirdJ3bViPz4//fWsfrnx4LQ7Vd+Ab503Ba3efbtn5cTo5nD4lFx0eGZsrAqE1VpVuK6W5pdCZ9FMYukelvq858i2YOJ6fmcQz3TTy/PAzMzGrKAO/++AgVh2IfNYZAH74r91o7fbhp1fMRmbKyGtP1YbwhDvXraoq/rT6MNLcEj5/SnTn+ARBwM+unI2LZhXgjR0n8JPXdxvarxvJPzYdw/rDjfj80lIsnzQyBuwMpe+O1x/8axf+9619w96gaOjw4Ma/bEBDhwe/uX5+v/8GoijgV9fNwxlTcvHcxko89O6BQR+//nAjnA5hxAzQMmpGYQb+79p5WPfdc/DN86bCIyt44N/7cOrP38ePX9uNQ/Ud+GBfHaYXpMdk2B+Rlablp2Nibire3l0DRVGxt6YNk8amDnmcZDhpbgkTclJCle4/fFCO1QcbcP2ScbjaprO4RcFK94f76nDp71bj0Y8PYVZRJl7/2un4xnlTbR+8RaOPdq57w+FA6B6JGym0jpLsVNeImrVB+p3bp7suX8fQ2+EUZibBG6abbyQaeV+xFLUkpwOPfHEh0lwSvvH8tojtGm/tPIG3d9fg0jmFocE2I82E3FRMyEnBx/vrBoXhjw7U40BtBz6/dJyp864OUcBvrp+PZWXZeHp9Bf7wQbnZy0ZNaw8eeHMvCjKS8L1LRu45t760Ha8LSrPw6MeH8I3nt8Ejh1+H1N7jw8onN+JoYxd+esXssLt1XVKgJXReSSZ+/0E5nlp7JPQ+n1/BpiNNWDBuzIjtENArN82Nr583BWu/ezZ+ed08jM9JxVPrjuLcX32Mxk5vaKgJ0UgiCAIunl2A+nYPPj5Qj2NN3VG3lmtmFWXiSGMn3tldg9+8fwAzCjPw48tnWXTFg2nt5e/vq8Oxpm5856Jp+Oedy03/OejkNW9cFtLcUiiAjLT2cqA3dC8eP2ZUrDmkwQozkzEn2MVjxW7tp760FGvuP8f050kEI+8rlkwZn5OKX1w3F02dXtz9962hKZh9tXR58YNXdyMrxWnri5JYOGtaHo639uBgXUe/tz/+8WFIooAvWTAEJsnpwOM3LcbMwgz86t0D+PuGyqg/l6qq+P6/dqLdI+OBq2ePqgFY2o7XC2fl47Xtx3HTXzaitav/FHKP7Mdtf92CXdVt+OZ5U3HDsvFDfr40t4QnVi5BWW4qfvLGHry+/TgAYFd1Kzq9fiyL86qwWHJLDly7qAT/vud0PPfVZTh/Zj7GpDhxBQfV0Ah18ezAzbbfvBfoZIl2crlmZlEGVBW4+++fItUl4ZEvLoy6cq5HktOBM6bkYunEbPz766fjzrMmQxqBIYkSh9Mh9jsyNTLbywNfc0vZWj6qffGUUpRmp2BCbqrpz+UQR97f86HwJ8BJ6KLZhbjl9InYXNGMX/5n/6D3//SNvWjo8OCHn5lpaNJ5IloRWh1WF3rbzqpWrD/ciMvnFYVaAM3KSHLiqS8vQWl2Cr7/r514+/+3d+bRUVXp2n8rYQhTkCQggUpSQckAAZJIBQgIRBHp2GLagWapkaBccbU2S+nvgve23YIifW+LfmCjdnttBGO3IHiRofF+C8Io2swEItoMAcIQEkggDCGBSp7vj9w6XUUqyVtk165Tyftbq9aq1Hnqfd495Jy9zzl1dkHxbcVZnX/WWL7mvoSWd5WyQ7tg+uCpe4yHoT3+x2/p9MW6JcVqakGvLNtP3x4ro2eGxdC0++9uMl545/b06XNp1KNLe5r+xX7aduQ8fedcn7sF/p67KSwWCw27K5z+65nBtO+3Y6mvD36rKgg6SOodStZuHSj/dN3vsG/3yeVOnA9Tu1FTS//52ECKVTAYbIrc54bQF1OH0d095P9QUMOIu/95XAvk28tl0t2ymZgWTVtnZPhsZZ9AJfD+YwUlzByXQCnRd9CfthbSepenSm/+Ryl9ufc0jY7vTj8LwKV2bmVobDi1axPk9rvuj7YVEhHRlHv7KPXq0SWEcp9Lo7BO7Wna0v3Gw7y4lF2tptlrDlFYp3b0+sOBfYdBYzjXeH3toUQ6UnqVfvbBt1RwpoJeX11A6w7W/aTh9Yf7s289s3brSJ8+O4Q6tA2mqbl76L/3nqF2bYIoJfoO3xZEEASfYbFYaJzLMnv9mnlbdkrUHRQa0oaeH9mnRa1rLrQuRrisItM2KPCG8Em9ulJsRKdm/z8LQiASeP+xghLatQmihU+m0h0d29KvvthPp8or6Wq1g369soA6tQumtxSvWeovOrQLpqF9wmnXiXK6Vu2gU+WVtO5gMd3bN8K48qGSmPBOtHiyndoFB9Hzn+6mTR5+T94Qs9ccovJrN2jW+P4U1qmd8tzMhMVioSn39qH3n0ylius3Kev97fTZ34to+N3h9O7PB3l9O1F8zy60KMdONbWgo6VXKTX6Dp/eOioIgu/5yf8+zyGsU7tm33V1R8d2tOc3D9C/ZyaqSE0Q/MJd3TsZaxe3bRN4Y7T/82A8bfzVKPmphdAqkV7fiul9Rwf6vz9PpstVDnrxr3vprb8dojOXrtOrmYnGQ2BaAs6lw749VkaLth+nmlrQ8yPVXuV2Jal3V/qvZwZTdU0tTf5kF42bv42W7SqiqpueHxxGVLe80+r8szQm8U56uBVdhXloYCT9ZcoQ6hzShgZZu9Kfsgff9pq1g21h9MFTqdQ22CIPEBOEFkBK1B10d4/ONOyucCUngQPxdlxBcMVisdBPB0ZSjy7tA3Z995ZwQUcQbgcLVK1xZAKsViudPn3a32kEHG//vx/p/U3HiKjudzZL/2UoBbWgBxcUnr9K972zhX46MJI2/lhKtvBO9LdpI3y+4z9VXkmfbD9BX+w+RVerHRTWqR09NSSasofGUI/Qfz7R8XLVTRr77la6dsNBG6aPojtDm/+0x0Cj8oaD2gUHKTn7fbnqJnVp30YO7ILQAqi6WUPBQRaZMAvC/+KoqSVHLeRuLkEwGU3NQ+UoJtArY+Io/a5w6tQumP7j0QEtasJNRBQb0YmiwzrS2gPFVHmjhp4f2UfLhCwqrCP99uF+9N2/3Ue/+Wk/6tQ+mP6w8SgN/8+NNH3Zfio4U/eAoN+t+5HOXa6iX2cmtsoJNxFRx3ZtlN1uFhrSVibcgtBCCGkbLBNuQXChTXCQTLgFIQCRK90CEdU9Obri+s0W+1vi364qoE+/O0m9uobQlhkZfhnE1dSC1h8qoUXbj9PO4+VEVLfuZv6pS5R+Vzj9ZcoQmSwKgiAIgiAIQoAhV7oFFsFBlhY74SYiGtuv7im4U+7t47erJsFBFhqX1JO+mDqM1v5yBD2a0psOna2gju2C6T8eHSgTbkEQBEEQBEFogciVbqHV8OO5yxR/ZxdTTW7PX6mmqps1FBXW0d+pCIIgCIIgCIJwGzQ1D5VVy4VWQ0JP860L2dxlcARBEARBEARBMDdye7kgCIIgCIIgCIIg+AiZdAuCIAiCIAiCIAiCj5BJtyAIgiAIgiAIgiD4CJl0C4IgCIIgCIIgCIKPkEm3IAiCIAiCIAiCIPgI0066jxw5Qunp6RQXF0d2u52+//57f6ckCIIgCIIgCIIgCF5h2kn31KlT6fnnn6fDhw/TzJkzKScnx98pCYIgCIIgCIIgCIJXmHLSXVpaSrt376ann36aiIgee+wxOnXqFB09etTPmQmCIAiCIAiCIAgCH1NOuk+dOkWRkZHUpk0bIiKyWCwUHR1NRUVFbrp3332XrFar8bp69ao/0hUEQRAEQRAEQRAEj5hy0s1l+vTpdPr0aePVuXNnf6ckCIIgCIIgCIIgCAamnHRHRUVRcXExORwOIiICQEVFRRQdHe3nzARBEARBEARBEASBjykn3T169KDU1FT67LPPiIjoyy+/JKvVSnfffbefMxMEQRAEQRAEQRAEPhYA8HcSnvjHP/5BOTk5VFZWRqGhofTJJ5/QgAEDGv2O1Wql06dPa8pQEARBEARBEARBaO00NQ9tozEXr4iPj6fvvvvO32kIgiAIgiAIgiAIwm1jytvLBUEQBEEQBEEQBKElIJNuQRAEQRAEQRAEQfARMukWBEEQBEEQBEEQBB8hk25BEARBEARBEARB8BEy6RYEQRAEQRAEQRAEH2HaJcNuh/bt21P37t39nQaLq1evUufOnbVozBpLcvdPrJbupzKW5O6fWJK7f2JJ7ub1UxlLcvdPLMndP7Ekd/P6qY7lb86fP0/V1dUNCyD4hd69e2vTmDWW5O6fWC3dT2Usyd0/sSR3/8SS3M3rpzKW5O6fWJK7f2JJ7ub1Ux3L7Mjt5YIgCIIgCIIgCILgI2TSLQiCIAiCIAiCIAg+QibdfmL69OnaNGaNJbn7J1ZL91MZS3L3TyzJ3T+xJHfz+qmMJbn7J5bk7p9Ykrt5/VTHMjst6kFqgiAIgiAIgiAIgmAm5Eq3IAiCIAiCIAiCIPgImXQLgiAIgiAIgiAIgo+QSbcgCIIgCIIgCIIg+AiZdAuCIAiCIAiCIAiCj5BJtyAIgiAIgiAIgiD4CJl0+4GLFy82qamsrKR9+/bRlStXTBVLlR83JzPmzoXj549YKv1U1btKzFrvZq2Hlt6GgtBaUHm85Oi8OV6q2M+cOnWKVq5cSUePHm12XirHKUTq9qOcMpp1jMXR6fbT3Wd0+3E9/dHfBQ9A8Cnz58833hcWFqJfv34ICQmBzWbDgQMHjG0zZsww3u/fvx+RkZGIj49H9+7dsWXLFr/EUunH0Zg19y+++MLQnD9/HpmZmQgNDcWoUaNw8uRJr/x0x1Lpp7LededuxlicOKpzV9WG/sjdE+Xl5Y1uV8m1a9ewd+9eXL58uUktJy9VGtWYsU5V1ZVKP47O134qxw0cHfc4rmo/8/TTTxuaTZs2oUePHnjwwQfRs2dP/Pd//7dX9aBynKLyWMgpoxnHWFydbj/dfUa3H9dTd39XNabzRheIyKTbx6SkpBjvJ06ciIULFwIAVqxYgTFjxnjUPfzww1i5ciUA4LvvvkN6erpfYvnKryFNIOQ+ZcoUzJw5E8XFxXjnnXeQlZV12366Y6n0U1nvunM3SyxOHF/m3pw29Efuuk8G6B6A6z5hpbJOuX5mPKkayBMMX40bOP/33ON4c/YzycnJhub+++/H9u3bAQCHDx/G4MGDPfo1Zwyiu3zcMppxjHU79aDDT3ef0e3H9fRnf2/OmM4bXSAik24f49p5Bg4c6LZt0KBBHnWunwP//AfTHctXfg1pzJq7a34DBw6Ew+GoF5vrpzuWSj+V9a47dzPG4sRRnbuqNvR37rpPBugYgOs+YaWyTm/Hz4wnVQNtguGrcQNn38A9jjdnP+OqcY3fmF9zxiC6y3errqEymnGMxdX50093n9Hhx/XU3d9Vjem80QUibfx9e3tL59KlS7RmzRoCQDdv3nTbBsB4X1paSu+99x4BqPd7itraWr/EUunH0Zg196qqKjp48CABIIvFQsHBwYbGYrF45ac7lko/lfWuO3czxuLEUZ27qjb0R+6uHDp0iD7//HMiInrsscfozTffrKffuXMn7d27l4KDg2n69Om0ZMkSj3Eb0zkpKiqirKwsIiIaOnQoVVZWepWXSg0nd2/L15inr/w4daqqPlX6cXU6/FSOGzg67nFc1X7m9OnTNH36dAJAFy5coJqaGmMfUlNTY+hVjUF0l49bRjOOsbg63X66+4xuP66n7v6uakznjS4QkUm3j4mOjqZ3332XiIjuvPNOOnPmDPXu3ZtKS0upXbt2hu6BBx6gffv2ERHRyJEjqbi4mCIjI+nMmTPUo0cPv8RS6cfRmDX369ev0yOPPOK2U7darVRRUUFBQUFe+emOpdJPZb3rzt2MsThxzNqG/shd98kA3QNw3SesVNYp18+MJ1UDeYKhctzA0XGP46r2My+++KIRc8qUKVRWVkY9evSgM2fOUGpqqrFN1RhEd/m4ZTTjGEtln1Hpp7vP6PbzR59RNSZQOW4IVCxo6FKC4FNqamqourqaOnbsGHCxVPqpRHfulZWVVFJSQrGxsc320x1LpZ/KeteduxljceKozl1VG/oy99GjR7tN4D777DPjwP/QQw/Rrl27yGazUVBQkHGw3rZtm3GwzsjIoL179xIRsXSTJ092y2fu3LnGgCQnJ4fWr1/PzkuVhps7tx5U1SnXj1OnKutKlR+3rnT7NQeV+waVnmYdX3CQ8nmnM5uf4B2qxgQqxw2mB4LfuHDhAku3f/9+08VS6cfRcHW6c+fA9dMdS6WfynpXhVnr3az1EKht6HA4cO3atUY1165dQ2FhYZOxuDoOnLxUaQBe7tzyqapTM9anSj+Vnqr9VI4bODru8VLVfmbNmjUsP1VjEN3lA3hlNOMYi6vT7ae7z+j243rq7u/CP5FJtx+JiopSptMdS3Kvo2/fvsr8dMdS6aey3nXnbsZYnDgq/bg6s+au+8CvewDuj4GNGetU90nVQJ5gmPHYqzJWS/dTGUty908syb0OVWM6b3RmRX7T7WNWr17d4Laqqirj/XvvvedRA4CuXr3ql1gq/Tgas+Z+4MCBBmM5f7fH9dMdS6WfynrXnbsZY3HiqPTj6syae2OkpKRQUVFRo5q4uDg6fPhwk7E4uocffrhJP25eqjREvNy59aCqTrl+nDpVWVeq/Lg6X/ipHDdwdNzjuKr9zPTp0xv0q6ioMP5WNQbRXT4iXhnNOMbi6nT76e4zuv24nrr7u6oxnTe6QEQm3T7mZz/7GY0aNcrtASlOXDvPr371K3rqqac8PpnP+RAV3bFU+nE0Zs09OTmZbDabx1hlZWVe+emOpdJPZb3rzt2MsThxVOeuqg39kbvukwG6B+C6T1hxPVX6mfGkaiBPMFSOGzg67nFc1X7mgw8+oBkzZrg9mM+Jaw6qxiC6y8ctoxnHWFydbj/dfUa3H9dTd39XNabzRheQ3O4lcoFHfHw8jh8/7nGb1Wo13g8YMAA//vhjozrdsVT6cTRmzd1ms+HMmTNK/HTHUumnst51527GWJw4qnNX1Yb+yD0oKAgZGRkYPXp0vVdISAgAwGKxIDY2Fjabrd6rbdu2RiyOrk2bNpg0aRJycnLqvTp37uxVXqo03Ny59aCqTrl+nDpVWVeq/Lg63X4qxw0cHfc4rmo/c8899+DAgQNN+qkag+guH8AroxnHWFydbj/dfUa3H9dTd39XNabzRheIyJVuHzNp0iS6cOEC2Wy2etteeOEF4/0rr7xCN27c8Bhjzpw5foml0o+jMWvu48ePp8LCQurVq1c9zUMPPeSVn+5YKv1U1rvu3M0YixNHde6q2tAfufft25cWLVrkURcVFUVERDExMfTNN9949HNquLrExET6t3/7N4qPj6+n2bBhg1d5qdJwc+fWg6o65fpx6lRlXany4+p0+6kcN3B03OO4qv3MG2+8QR06dPDo57r+u6oxiO7yEfHKaMYxFlen2093n9Htx/XU3d9Vjem80QUk/p71C4IgCEJTzJ07F7t27fK4bc6cOQCAadOmYdu2bR41U6dONd5zdIsWLWrwasLixYu9ykuVhps7tx5U1SnXj1OnKutKlR9Xp9tPEARBCBxk0u0H5s6dy9K99NJLpoul0o+j4ep05+466G6un+5YKv1U1rvu3M0YixNHpR9XZ9bcBUFwR+W4gaPjHsdV7WceffRRlp+qMYju8gG8MppxjMXV6fbT3Wd0+3E9dfd3VWM6b3RmRybdfiAlJUWZTncsyd28fipjSe7+iSW5exdL98kA3QNw3SesuJ4q/cx4UjWQJxhm/V8N1P2M1JV/Yknu/okVyH6BQJC/b29vjcDDE/luV6c7luRuXj+VsSR3/8SS3L2LtXz58iY1CxYsYMXi6LZv386KxclLlYaIlzu3HlTVKdePU6cq60qVH1en28+s/6uBup+RuvJPLMndP7EC2S8gaM6MXbg9NmzYwNIdOnTIdLFU+nE0XJ3u3D/99FNlfrpjqfRTWe+6czdjLE4clX5cnVlzT05OVqIxayzJ3bx+KmOp9FM5buDouMdxVfuZS5cusfxUjUF0lw/gldGMYyyuTref7j6j24/rqbu/qxrTeaMzO3Kl2w/cf//9ROR5vbna2lrjfWJiIhERXbx40WMch8NBYWFhVFFR0aTnX//61yY1qampjW4/ePAgnTx5knbv3u32eUFBQT2tM3dXfvzxRyotLTXef/vtt7Rjx456uurqavrqq69o/vz5tHDhQjp37lw9TU1NDW3cuJEWL15MixcvJovFQjU1NY3mr6reiYiys7Mb9XL1a4qf/vSnTWqOHj3KitVUXufPn6fevXtTcXGx8dmlS5fq6RrK/dq1a+RwOIiIqLy8nIiITp8+XU+3f/9++uqrr2jt2rUUGxvbYD6FhYW0efNm2rx5Mw0fPrzR3InU1rsZ25CTk5na0Nv2I1Jb7/PmzWtSM336dFYsjo6zHyXi5aVKQ8TLnVsPquqU68epU5V1pcqPqzOjX1PHeqKGj/e348fx5Pq9/PLLTXpVVlZSVVWV2xrPN27ccLtatm7dOvr888/pyy+/bDSW7vIRNV1GleUjMmefUemnu8/o9uN4qvZTMZ7xNJa53VgBg1+n/K2cqKgo4/2uXbtgs9nQrl07ZGVlobS01Njm/C1DXl4ewsLCEB4ejs2bN8NutyMhIcH428mCBQvqvcLDw433ADB//nxDX1hYiH79+iEkJAQ2m814+up9992HkpISAMCyZcvQq1cvPPHEE4iJicEf//hH4/sWiwUDBw7EggULUFZW5rGsv//979GjRw9ERUUhNzcXUVFReOKJJxAdHe2Wy8aNGxEdHY2BAweiffv2GDNmDBITE2G323H69GkAwNatW2G1WjFkyBBMmDABEyZMQFpaGqxWK7Zs2aK83hujb9++AICjR49i9OjRiI2NxSuvvILr168bmqFDhxrv9+3bh0GDBiElJQUFBQXIzMxEhw4dEBUVhfz8fADAqlWr6r3uvPNO472TL774wnh//vx5ZGZmIjQ0FKNGjcLJkycBANnZ2UYb5uXlISIiAna7Hd27d8fKlSsBAG3btsX48eOxevVq1NTUNFjWJUuWICQkBFarFXl5eYiMjITdbkd4eDiWLl0KAMjPz0dSUhJCQ0MRFBSEpKQkdOvWDY8//jgqKiqMWIcOHYLdbkfPnj2RlpaGtLQ09OzZE3a7HQUFBcrrXWUsVW3IaT/AnG3Y3Pa7nXr3hOt+qDmUlpYiLy8PZ8+ebVT32muvseKVl5c3uv3AgQP485//3ODTqZ3oLp8qT2/8OHWqqj5V+Xnj6Us/Vcd6gHe85/hxPTl+r7zySr1X165djfdOZsyYYbzfv38/IiMjER8fj+7duxtjguTkZFy4cAEA8N5776F///7413/9V9jtdsyaNcsv5eOWUVX5zNpnVPrp7jO6/fzRZ1SNZzhjGW6sQEUm3T7GU2d1vrp3727oRowYgbVr1+LChQt47bXXkJCQYEwynbeUpaWlYd++fdi0aRPCw8ORl5cHANixYwdGjBhhxAoODsb48eORk5NjvDp37oycnBxMnjwZgPuEcuLEiVi4cCEAYMWKFRgzZgwAYMCAAYZm6NChOHHiBACgrKzMbVtSUhJWrFiBn/zkJ+jUqRN+/vOfY/369W710K9fP5SXl6OoqAgdO3ZEYWEhgLp/qP79+xu6lJQUHD58GACwc+dOZGdnAwA++ugjPPLII0ZengY6O3fuRFJSkvJ6z8/Pb/DVs2dPAMDYsWOxcOFC7N69G9nZ2UhPT8fly5fd4gDAyJEjsXLlSnzyySeIjo42bplZuXIlHnjgAQB1JzHS09MxevRo4xUSEoLRo0cjIyPDra6cTJkyBTNnzkRxcTHeeecdZGVlAQAGDhzo5r1v3z4AdQc2Z15xcXGYN28eEhMTERkZiZkzZ+If//hHvfodMGAATpw4gfz8fHTt2tVogyNHjhg+w4YNM5YOWrVqFX75y1+iuroav/71r/HMM88YsdLS0rBixYp6HsuXL4fdblde72ZsQ077mbUNOe2nut51n8jQPQDXfbJNZZ1y/XSfEG7pEwxVx3qAd7zn+HE9OX4dO3bE008/jVmzZhmvO+64w3jvye/hhx82+tx3332H9PT0en52u92YbFRWVhrjBt3l45ZRVfm4ZdTdZ1T66e4zuv24nir9VI1nOGMZbqxARSbdPiYoKAgZGRlundW10zq59bdaubm5iIuLQ1FRkdEBXTV33XWXm951W15eHtLS0rBmzRrjM5vN5qZ37dSu/wgAMGjQIAB1A3mHwwEAGDJkiJvG9R/SNVZRURHefPNN9OnTBzExMZg9e3Y9TXR0dIO5O72dpKamGu/j4uIA/PMKmSec21TWu8ViQWxsLGw2W71X27ZtPcZ56623YLfbcenSJbeyu+pcr7i7ln3RokVIT0/H3r17jW23tt+tsQYOHGi0lfNv1/oAgMGDB7t937nDdc1v+/bteO6559ClSxfce++9WLJkiUe/mJgYj7nc2n6unq65ONvSE85tKuvdjG3IaT/AnG3IaT9AfRvqPJGhewCu+2Sbyjrl+uk+IdzSJxiqjvUA73jP8eN6cvwOHTqEe++9F3/4wx/Yfrfuv5z9LzExEVeuXAEADB8+HLW1tYamX79+fikft4yqyscto+4+o9JPd5/R7cf1VOmnajzDGctwYwUqMun2MfHx8Th+/LjHbVar1XgfFxdX77bQpUuXom/fvsYk1bWzvfrqq25a1w4LABUVFcjOzkZOTg4qKioQGxvrtj02NharV6/GqlWrkJiY6LbN6fP666/jsccew5EjR/D2229jzpw5OH78OD744AOMHz/e0Dd0G/aGDRvw5JNPAqgbNKxduxa5ubmIiYkxbmXduHEj7rnnHuM7w4cPx8aNGwHUXTUbN26cWx0BwLhx4zB79mzjKgAAlJSUYNasWRg7diwAtfVus9lw5syZRmPFx8fX2/b222/jnnvuwd1332185rrzc73yC7i374kTJzBmzBjMnj0bDoejXvsBQEJCAg4cOID8/Px6O1Xn3y+99BKmTZuGK1eu4NVXX8Vnn32G2tparFu3zuOg2snVq1fx8ccfY/jw4cZnqampKCgowLZt2xAREYFvvvkGAPDDDz8Y/W/w4MH44YcfANSdUR01apRbvk7S09Px6aefutV9TU0NFi9ejGHDhgFQW+9mbENO+wHmbENO+wFq6133iQzdA3DdJ9u4nir9dJ8QbukTDEDNsR7gH++b8uN6cv1u3ryJ3/zmN3jggQdw4sQJj369e/fGggULMH/+fPTp08ej3/vvv48RI0Zg/fr1mDt3Lp5//nls2rQJM2bMwKRJk/xWPk4ZVZaPU0bdfUa1n+4+o9uP46naT8V4hjOW4cYKVGTS7WPmzp3b4G++5syZY7yfPHmy24HaybJly4wrQpMnT3b7XayTo0ePug2sXVm+fDmSk5ONWzmdjBo1yu3qhvOW6pKSErdB0/z582G1WtG2bVtYLBaEhoZi6tSpbr/dvnVA4ImdO3ciOTkZqamp2L9/PyZOnIj27du73Sbv1FmtVoSEhCA2Nta43a64uNi4al5aWopnn30WnTt3RkhICEJCQtC5c2dMnjzZmIirrPdp06YZt9veytSpUwEAWVlZ+Prrr+ttf+edd2CxWIy/x44d67ENz549i7S0NLfPamtrMW/ePAwbNgy9evWq952YmBi3q4inTp0CALcrhNXV1Xj55ZcRGhoKm80Gi8WCNm3a4MEHHzRu8ec+Ofdvf/sbwsLCEBERgQ0bNmD06NGIj49HaGiocRLl66+/Rnh4OOLj4xEREWE8a6C4uBj/8i//YsQ6cuQI7rvvPnTt2hUJCQlISEhA165dkZGRYdwWrbLezdiGnPYDzNmGnPYD1NY7oPdEBqB/AK7zZJvKOvXGT+cJYVV+3njq9nPS3GM9wDveN+Xnjac3fn//+99xzz33oEePHvW2ud5ZkJOTYzxL4PTp0253D3z11VcYMWIEwsLCEBoaiqSkJPzud79DVVWV38vXWBl9Ub7Gyqi7z/jKT3ef0e3XmKcv/Jo7nuGMZbixAhWZdLcAbt68icrKyga3nzt3Dn/7299YsRwOB65du1bv88uXL7Me9uINFy5caPChT87fljRFWVlZgwcwnVRVVTW4U3QeQBrj0qVLDT4goqCgAB9++CE7l2vXrrntwJyfHThwAHv37q1Xt7dbfw6HA7t373a74wAALl68iN27d3ucmN5KaWkp9uzZgz179rg9xI5Lc+tdZSxVbeip/Zyfm60Nm9t+gPf1rutEhis6B+C6TraprFNv/RqrU19NaFr6BANQc6wH+Md7b/wa8+T6VVZW4uDBg2y/5qK7fIC5y6i7z6jw012fuv384dnc8UxjYxlvYwUaFqClrDhuXmpqamjLli1UVFRERETR0dE0atQoCg4O9lqnO9atmpiYGBo5cqTfc2+IsrIyCg8Pb7bGk66wsNAtpz59+tT7Dkdj1lj+yF03ZqyHQO4z/uT777+nbdu20QsvvNCktrKykkpKSuotfVZZWUnHjh0jh8NB0dHRje4XSkpKaM+ePZSZmcnKr6amhqqrq6ljx45un1+5coUcDgd169at0e97Uz4iz2X0pnzeeqrw86ZOm1ufqvy88dTh58tjr6fjvS/HIJ78Ll68SCtXrnSLk5WVRWFhYW5+HB1Ho7t8KnPn1pUZ+4xKP919RrefP3InMueYJ9CQSbeP2bZtGz355JPUu3dviomJISKiEydO0NmzZ+kvf/kLjRw5kq3THcusuTdGdHS08U/aHI2r7tChQ5STk0OnTp2i6OhoIiIqKiqiqKgo+uSTT6h///4sDRGxdD/88ANNmjRJWyyVuTs1p0+fpqioqAZjNUZcXBwdPnxYqcaMbcj1C7Q25LTN7bShE50HdX8MwAP5JAxH05JOCPt7ghHIx3GO5ssvv6Rf/OIXlJGR4abZsmULvf/++/TYY48RERm60aNHk81m86jjaPxRV5wyqiqfWdtZpZ/uPqPbzx99RtUYROXYNmDx74X2lg9neSuuTncss+bOWQ6Mu2QYR8dZHom7hJIZY/kjd85SUqo0Zq2HQO4z3HpX2YactcG///571vrhnFhbt26F1WrFkCFDMGHCBEyYMAFpaWmwWq3GOqdcHUfDXfucU0ZuLFV1yvVTVVe628asuQfycZyjaeiBqIWFhW4PYOToOBp/1JWq3Ll1ZcZ2Vumnu8/o9vNH7mYc8wQqMun2MZzlrbg63bHMmjtnOTDukmEcHWd5JO4SSmaM5Y/cOUtJqdKYtR4Cuc9w611lG+o+qOseeAbySRiunxkH6YE8wQjk4zhH47p6wa24LpvK0XE0/qgrVblz68qM7azST3ef0e2nMhbXz4xjnkAlyN9X2ls6d911F73xxhtUWlpqfFZaWkqzZ892+y0cR6c7lllz79u3Ly1atIg2bdpU7xUREcHWcHURERGUm5tLtbW1xvdqa2tpyZIlxm8WORqzxvJH7jExMfTNN9/Q8ePH673uvPNOpRqz1kMg9xluvatsw0uXLhm3u7ny+OOPU0VFBVvD1VVVVdHgwYPraex2O1VXVxt/c3Qcjcrcdcfi+qmqK91tY9bcA/k4ztHY7XZ69tlnaefOnVRSUkIlJSW0c+dOevbZZ93qhqPjaPxRV6py59aVGdtZpZ/uPqPbzx+5m3HME7D4e9bf0uEsb8XV6Y5l1tw5y4Fxlwzj6DjLI3GXUDJjLH/kzllKSpXGrPUQyH2GW+8q25CzNjh3/XCObty4cZg9e7bb/qmkpASzZs3C2LFjjc84Oo5GZe66Y3H9VNWV7rYxa+6BfBznaCorK/HGG2+gf//+6NKlC7p06YL+/ftj1qxZbk+15ug4Gn/UlarcuXVlxnZW6ae7z+j280fuZhzzBCoy6dYId3krjk53LLPmrhPO8kjcJZTMGMsfuevGjPUQyH1GJ7oP6roHnoF8EobrZ8ZBeiBPMFwJ5OO42Y71QMsvH2DOdg7U8WFrwIxjnkBDJt1+YO7cucp0umNJ7nUsXrxYicassSR3/8SS3JvW+OOgrnPgGcgnYbwZJJlxkN4SJhhmPPaqjPXSSy+x/Dg6jsYfdaUqd25dmbGdVfrp7jO6/VTG4vqZcdwQCMik2w+kpKQo0+mOJbmb109lLMndP7Ekd+9i6T6o6x54toaTMGYcpAfyBMOs/6uBup+RuvJPLMndP7EC2S8QkAep+QEwl0bn6HTHktzN66cyluTun1iSu3exFixYoETD1S1fvpwVi6PjaFTmrjsW109VXeluG5WxVPqZ9X81UPczUlf+iSW5+ydWIPsFBM2ZsQu3x4YNG5TpdMeS3Ov49NNPlWjMGkty908syd27WMnJyUo0Zo0luZvXT2UslX5mPPaqjHXo0CGWH0fH0fijrlTlzq0rM7azSj/dfUa3n8pYXD8zjhsCAbnS7QeOHj2qTKc7luReR3Z2thKNWWO19NzPnz9PvXv3puLi4mZpVMbS7RfouRMRTZ8+XYmGq5s3bx4rFkfH0ajMXXcsrp+qutLdNipjNcevpqaGNm7cSIsXL6bFixeTxWKhmpoarzXe6Fy5//77iYiorKys2bqGNK5LByUmJhIR0cWLF+t9n6PjxiIicjgcFBYW5rbs3e3quLGIiP76179q0xARpaamKtFwdAcPHqSTJ0/S7t27m6VpSFdQUFBP52xnVzg6bqwff/zRWMbsxx9/pG+//ZZ27NhxWzpurOrqavrqq69o/vz5tHDhQjp37pzPNE4KCwtp8+bNtHnzZho+fLhPNbfCHUeaHn/P+ls6q1atqve68847jffe6HTHktzrdF988YWhP3/+PDIzMxEaGopRo0bh5MmTbI1ZY7WG3LOzs40n/ubl5SEiIgJ2ux3du3fHypUr2RqVsXT7BXrunigvL290O1fD1f3xj39kxeLouLF0Ulpairy8PJw9e9YnmosXLzaZgyqNk6tXr+LmzZsA6h5ItmHDBpw6dcprjTe6ffv2YeXKlVizZg2OHTvmMS+Opind1q1bYbVaMWTIEEyYMAETJkxAWloarFYrtmzZwtZ4o2uIqKioJjVcnVOza9cu2Gw2tGvXDllZWW4P53P9jSdHx9Hk5eUhLCwM4eHh2Lx5M+x2OxISEoy/nXB03FgLFiyo9woPDzfeq9QAwPz58433hYWF6NevH0JCQmCz2XDgwAG2hqu77777jP37smXL0KtXLzzxxBOIiYkx9oEcDVdnsVgwcOBALFiwoNGHD3J0HM3vf/979OjRA1FRUcjNzUVUVBSeeOIJREdHu9UPR8eNtXHjRkRHR2PgwIFo3749xowZg8TERNjtdpw+fVqpBqi7+m2329GzZ0+kpaUhLS0NPXv2hN1uR0FBgVJNU/Tt25elMysy6fYxFosF6enpGD16tPEKCQnB6NGjkZGR4ZVOdyzJvU7nenCfMmUKZs6cieLiYrzzzjvIyspia8waqzXkPnDgQOP9yJEjsW/fPgB1AwXnLZscjcpYuv0CPfd9+/Zh0KBBSElJQUFBATIzM9GhQwdERUUhPz+freHqdJ8o9MfJL90nYdq2bYvx48dj9erVbmt6u6JKAwBLlixBSEgIrFYr8vLyEBkZCbvdjvDwcCxdupSt4ery8/ORlJSE0NBQBAUFISkpCd26dcPjjz+OiooKtoarGzBgAHbt2lWv3Dt37kRSUhJbw9V56sfOV/fu3Y3vcHQczYgRI7B27VpcuHABr732GhISEozJgOu+gaPjaNLS0rBv3z5s2rQJ4eHhyMvLAwDs2LEDI0aMMPw4Om6s4OBgjB8/Hjk5Ocarc+fOyMnJweTJk5VqAPdj5sSJE7Fw4UIAwIoVKzBmzBi2hqsbMGCAoRk6dChOnDgBoO6klXMbR8PVJSUlYcWKFfjJT36CTp064ec//znWr1+PW+HoOJp+/fqhvLwcRUVF6NixIwoLCwHU7Xf79+/vlY4bKyUlBYcPHwZQ9/+ZnZ0NAPjoo4/wyCOPKNUAdX15xYoV9epw+fLlsNvtSjVA3b6voVfPnj3rfT+QkEm3j1m0aBHS09Oxd+9e4zObzXZbOt2xJPc6bp1EOBwOt7+5GrPGag25u54dHTx4MFxxHqw5GpWxdPsFeu4jR47EypUr8cknnyA6Otr4jdfKlSvxwAMPsDVcne4Thf44+aX7JExcXBzmzZuHxMREREZGYubMmW7reKvUAHX958SJE8jPz0fXrl2NSeWRI0eMnDkarm7YsGHYtm0bgLpJ5S9/+UtUV1fj17/+NZ555hm2hqtr7KqPcxtHw9UFBQUhIyPDrR+79mcnHB1Hc+tv2HNzcxEXF4eioiK3Ps7Reau566673PSu2zg6bqy8vDykpaVhzZo1xme3jkFUaQD3fYNr/waAQYMGsTVcXVxcnHFcHjJkiJvGeTKHo+HqXHMqKirCm2++iT59+iAmJgazZ8/2mHtDOm810dHRbjm5tjNHx43l2gYAkJqaaryPi4tTqrn1/a04t6nSAHXHy9jYWNhstnqvtm3bNhgjEJBJtwZOnDiBMWPGYPbs2XA4HIiNjb1tne5YkjuQkJCAAwcOID8/v95Oyvk3R2PWWK0h95deegnTpk3DlStX8Oqrr+Kzzz5DbW0t1q1bZ0x6OBqVsXT7BXruroOOW29RdbY1R8PV6T5R6I+TX7pPwrgOKrdv347nnnsOXbp0wb333oslS5Yo1dxaDzExMW55eZocNaTh6m7dB7nWhbOOOBqubty4cZg9e7ZxlwEAlJSUYNasWRg7dixbw9XFx8fj+PHj8ITVajXec3QcTVxcXL07GZYuXYq+ffu6TUo4Oo7G9X/j1VdfddO69mOOjhsLACoqKpCdnY2cnBxUVFR4HKuo0sTGxmL16tVYtWoVEhMT3bY5c+ZouLrXX38djz32GI4cOYK3334bc+bMwfHjx/HBBx9g/PjxbA1X19DSUhs2bMCTTz5p/M3RcTRDhw7F2rVrkZubi5iYGOOul40bN+Kee+4xvsPRcWMNHz4cGzduBFB3lXjcuHHGNufkVZUGANLT0/Hpp5+6/f/U1NRg8eLFGDZsmFINUHdsPHPmjMe6d93PBCIy6dZEbW0t5s2bh2HDhqFXr17N0umO1dpzj4mJMc6yxcbGGr/hu3TpkrFT5mjMGqs15F5dXY2XX34ZoaGhsNlssFgsaNOmDR588EHjFi6ORmUs3X6BnrvrJMT1iiDwzwEeR+ONTueJQn+c/NJ9EsbTIPbq1av4+OOPMXz4cKUaoO7KTUFBAbZt24aIiAh88803AIAffvjBmPhwNFzd4MGD8cMPPwAAvvvuO4waNcr4fkJCAlvD1ZWWlmLy5Mno3LkzQkJCEBISgs6dO2Py5MnG5Jmj4ermzp3r8RZ0AJgzZ47xnqPjaCZPnux25dbJsmXL3K54cXRcjest/k6OHj3q1q84Om4sV5YvX47k5ORGb6FtrmbUqFFudxU4b7EvKSkxTuxwNN7o5s+fD6vVirZt28JisSA0NBRTp051+500R8PR3XoFvCE4Oo5mx44dSE5ORmpqKvbv34+JEyeiffv2CA8Pd3uyOkfHjbVz505YrVa0b98esbGxxu/ni4uLjSvwqjRA3d089913H0JDQ5GQkID4+HiEhoYiIyPDuMNIlQYApk2bZtzlcytTp05tsk3MjAVoKYufmZvCwkIqKiqigwcPUlBQEL344ou3rdMdS3Kv49ixY1RUVEQWi4Wio6MpMjKSzp07R7GxsV5pzBqrNeR+4MAB2rJlC9XU1NDIkSM9PmmVo1EZS7dfoOb+4IMP0vLlyyk0NNTt8+LiYsrKyqIdO3awNNxYTgDQu+++S19++SWdPHmSzpw547GMHF1jGpvNRkFBQeQ8JG/bto2sVitVVFRQRkYG7d27l63jxrpx4wbNnDmTFi1aRGFhYXTy5EkKDg6m+++/nz788EOKjY1VpiEiSklJoX379nmsPyeqNERE69ato+zsbAoKCqKlS5fSnDlzqLi4mIqLi+lPf/oTTZw4kaXhxvqf//kfevrppykiIoLKyspoxYoVNGrUKDp37hz99re/pY8++oilISK2zkl5eTkREYWFhTVYHxyNN7rWgsPhIIfDQSEhIc3WNaUpKSmhPXv2UGZmZoMxVGlcqampoerqaurYsWOzNI3prly5Qg6Hg7p169bgdzkab3T+oKysjLp160ZBQY0vEMXRNaYpKyuj8PDwJj1UaIjqVhY5deoUERFFRUVR9+7dfaa5lYsXL5qyrb3Gf/P91oHr0/qGDBnS4NP6ODrdsSR391iRkZHN0pg1VmvI/fvvvzd0DT01k6NRGUu3X6Dn3hCXLl1CUVFRszVN6QoKCvDhhx82GYOj48YCgGvXrjV4G663uoY0165dw4EDB7B3715cuHChwe82V9PY04RVazzhcDiwe/dutyu8t6NpTHfx4kXs3r3b41VObzQc3dGjRzF69GjExsbilVdewfXr141tQ4cOZWu4umPHjrFicXSqNIHsx613le187NgxZGRkNJl7UxqurjX0UVV1pTsW10/VQ0y5Dzrdv39/gzrXp+cHIjLp9jHcp/WpfPKf7icNmjFWS/eT3CX31pZ7Y3CWEeEuNWLGWJK7ef1UxvLWb+zYsVi4cCF2796N7OxspKen4/LlywD++TtzjsassVq6n+QuuQdC7qoeYqryQaeBiky6fQz3aX0qn/yn+0mDZozV0v1UxpLcJXdvY/kjd84yItylRswYS3I3r59Zc7/1idxvvfUW7Ha72zMtOBqzxmrpfpK75B5ouTfnIaYqH3QaqLTx9+3tLZ2IiAjKzc2lp556yvhNRm1tLeXm5rr9hoKj0x1Lcjevn+Quube23JOTk8lmsxm/U3alrKyMrTFrLMndvH5mzf369etun//7v/87tWvXju6//366cuUKW2PWWC3dT3KX3AMhd9d9UEZGhtt3nNtUabzRBSRapvatGOfT+rp27YqEhAQkJCSga9eu9Z7Wx9HpjiW5m9dPcpfcW1vunGVEuEuNmDGW5G5eP7PmnpWVha+//rre9nfeeQcWi4WtMWuslu4nuUvugZD72LFjPT5X4uzZs0hLS1Oq8UYXiMikWxOlpaXYs2cP9uzZg9LS0mbpdMeS3M3rJ7lL7q0ld84yItylRswYS3I3r59Zc6+qqkJVVZVHjXP5Jo7GrLFaup/kLrkHQu4NcenSJZw8eVKLxhudmZElwwRBEARBEARBEATBRzS+iJwgCIIgCIIgCIIgCLeNTLoFQRAEQRAEQRAEwUfIpFsQBEEQBEEQBEEQfIRMugVBEAShBWKz2Sg+Pp4GDRpEd999Nz3yyCP07bffNvm9r776iv7+979ryFAQBEEQWgcy6RYEQRCEFsqyZcsoPz+fjh49SpMmTaLMzEzasWNHo9+RSbcgCIIgqEUm3YIgCILQCnj00UfphRdeoHnz5lFeXh4NGzaMUlJSqH///vTnP/+ZiIjWrVtHq1evprfffpuSk5Pp448/JiKi3NxcGjJkCKWmptLIkSMpPz/fn0URBEEQhICijb8TEARBEARBD0OGDKHVq1dTamoqffPNNxQcHEzl5eWUkpJCDz74IGVmZtL48eMpOTmZXn75ZSIi2r59O33++ee0detWat++PW3bto2efPJJ+v777/1bGEEQBEEIEGTSLQiCIAitBABERFRWVkbPPfccHT58mNq0aUNlZWVUUFBAVqu13ndWrVpF+fn5NGTIEOOz8vJyun79OnXo0EFb7oIgCIIQqMikWxAEQRBaCbt27aKkpCR64YUXKDMzk7788kuyWCyUmppKVVVVHr8DgCZNmkRz587VnK0gCIIgtAzkN92CIAiC0ApYtWoVffjhh/SrX/2KLl68SDExMWSxWGjr1q1uv9EODQ2liooK4+/x48fTZ599RkVFRUREVFtbS7t379aevyAIgiAEKhY47zUTBEEQBKHFYLPZqH379hQSEkLXrl2jfv360auvvkrp6em0fv16+sUvfkGdOnWi5ORkOnz4MM2YMYOysrJo165dlJOTQ+3ataMXX3yRpkyZQkuXLqW3336bHA4H3bhxgx566CGaN2+ev4soCIIgCAGBTLoFQRAEQRAEQRAEwUfI7eWCIAiCIAiCIAiC4CNk0i0IgiAIgiAIgiAIPkIm3YIgCIIgCIIgCILgI2TSLQiCIAiCIAiCIAg+QibdgiAIgiAIgiAIguAjZNItCIIgCIIgCIIgCD5CJt2CIAiCIAiCIAiC4CNk0i0IgiAIgiAIgiAIPuL/Az+CtKSUvk69AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1200x640 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(num=None, figsize=(15, 8), dpi=80, facecolor='w', edgecolor='k')\n",
    "ax = sns.lineplot(x = groupby_date.index,y=groupby_date.values)\n",
    "ax.set(xlabel='Date', ylabel='Count of Tickets')\n",
    "plt.xticks(groupby_date.index,groupby_date.index, rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3)Provide a table with the frequency of complaint types."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# keeping a copy of original data \n",
    "df = raw_df.copy(deep=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticket</th>\n",
       "      <th>complaint</th>\n",
       "      <th>dateN</th>\n",
       "      <th>dateT</th>\n",
       "      <th>time</th>\n",
       "      <th>issuedBy</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>status</th>\n",
       "      <th>behalf</th>\n",
       "      <th>month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>comcast cable internet speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Aug</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>speed and service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Apr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>comcast imposed a new usage cap of 300gb that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Jul</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "      <td>May</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ticket                                          complaint     dateN  \\\n",
       "0  250635                      comcast cable internet speeds  22-04-15   \n",
       "1  223441       payment disappear - service got disconnected  04-08-15   \n",
       "2  242732                                  speed and service  18-04-15   \n",
       "3  277946  comcast imposed a new usage cap of 300gb that ...  05-07-15   \n",
       "4  307175         comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "       dateT         time            issuedBy      city     state    zip  \\\n",
       "0  22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland  21009   \n",
       "1  04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia  30102   \n",
       "2  18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia  30101   \n",
       "3  05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia  30101   \n",
       "4  26-May-15   1:25:26 PM            Internet   Acworth   Georgia  30101   \n",
       "\n",
       "   status behalf month  \n",
       "0  Closed     No   Apr  \n",
       "1  Closed     No   Aug  \n",
       "2  Closed    Yes   Apr  \n",
       "3    Open    Yes   Jul  \n",
       "4  Solved     No   May  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "df[\"complaint\"] = df[\"complaint\"].astype(str)\n",
    "df[\"complaint\"] = df[\"complaint\"].str.lower()\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "183"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nltk.corpus import stopwords\n",
    "from nltk.stem import WordNetLemmatizer \n",
    "lemmatizer = WordNetLemmatizer()\n",
    "stopwordSet = set(stopwords.words('english'))\n",
    "stopwordSet.update([\"comcast\",\"telecom\",\"issue\",\"complaint\"])\n",
    "len(stopwordSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def identify_tokens(row):\n",
    "    complaint = row['complaint']\n",
    "    tokens = nltk.word_tokenize(complaint)\n",
    "    # taken only words (not punctuation)\n",
    "    token_words = [w for w in tokens if w.isalpha()]\n",
    "    token_stopwords = [w for w in token_words if w not in stopwordSet]\n",
    "    token_lem = [lemmatizer.lemmatize(w) for w in token_stopwords]\n",
    "    \n",
    "    return token_lem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                             [cable, internet, speed]\n",
       "1     [payment, disappear, service, got, disconnected]\n",
       "2                                     [speed, service]\n",
       "3      [imposed, new, usage, cap, punishes, streaming]\n",
       "4                             [working, service, boot]\n",
       "5    [isp, charging, arbitrary, data, limit, overag...\n",
       "6       [throttling, service, unreasonable, data, cap]\n",
       "7       [refuse, help, troubleshoot, correct, service]\n",
       "8                                   [extended, outage]\n",
       "9                     [raising, price, available, ask]\n",
       "Name: tokens, dtype: object"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['tokens'] = df.apply(identify_tokens, axis=1)\n",
    "df['tokens'].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticket</th>\n",
       "      <th>complaint</th>\n",
       "      <th>dateN</th>\n",
       "      <th>dateT</th>\n",
       "      <th>time</th>\n",
       "      <th>issuedBy</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>status</th>\n",
       "      <th>behalf</th>\n",
       "      <th>month</th>\n",
       "      <th>tokens</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>comcast cable internet speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[cable, internet, speed]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Aug</td>\n",
       "      <td>[payment, disappear, service, got, disconnected]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>speed and service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[speed, service]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>comcast imposed a new usage cap of 300gb that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Jul</td>\n",
       "      <td>[imposed, new, usage, cap, punishes, streaming]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "      <td>May</td>\n",
       "      <td>[working, service, boot]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ticket                                          complaint     dateN  \\\n",
       "0  250635                      comcast cable internet speeds  22-04-15   \n",
       "1  223441       payment disappear - service got disconnected  04-08-15   \n",
       "2  242732                                  speed and service  18-04-15   \n",
       "3  277946  comcast imposed a new usage cap of 300gb that ...  05-07-15   \n",
       "4  307175         comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "       dateT         time            issuedBy      city     state    zip  \\\n",
       "0  22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland  21009   \n",
       "1  04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia  30102   \n",
       "2  18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia  30101   \n",
       "3  05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia  30101   \n",
       "4  26-May-15   1:25:26 PM            Internet   Acworth   Georgia  30101   \n",
       "\n",
       "   status behalf month                                            tokens  \n",
       "0  Closed     No   Apr                          [cable, internet, speed]  \n",
       "1  Closed     No   Aug  [payment, disappear, service, got, disconnected]  \n",
       "2  Closed    Yes   Apr                                  [speed, service]  \n",
       "3    Open    Yes   Jul   [imposed, new, usage, cap, punishes, streaming]  \n",
       "4  Solved     No   May                          [working, service, boot]  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# using ngram to get more meaning from the text and group similar ones\n",
    "from nltk.util import ngrams\n",
    "from nltk import everygrams,word_tokenize\n",
    "from itertools import chain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticket</th>\n",
       "      <th>complaint</th>\n",
       "      <th>dateN</th>\n",
       "      <th>dateT</th>\n",
       "      <th>time</th>\n",
       "      <th>issuedBy</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>status</th>\n",
       "      <th>behalf</th>\n",
       "      <th>month</th>\n",
       "      <th>tokens</th>\n",
       "      <th>ngrams</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>comcast cable internet speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[cable, internet, speed]</td>\n",
       "      <td>[comcast, cable, internet, speeds, comcast cab...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Aug</td>\n",
       "      <td>[payment, disappear, service, got, disconnected]</td>\n",
       "      <td>[payment, disappear, -, service, got, disconne...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>speed and service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[speed, service]</td>\n",
       "      <td>[speed, and, service, speed and, and service, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>comcast imposed a new usage cap of 300gb that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Jul</td>\n",
       "      <td>[imposed, new, usage, cap, punishes, streaming]</td>\n",
       "      <td>[comcast, imposed, a, new, usage, cap, of, 300...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "      <td>May</td>\n",
       "      <td>[working, service, boot]</td>\n",
       "      <td>[comcast, not, working, and, no, service, to, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ticket                                          complaint     dateN  \\\n",
       "0  250635                      comcast cable internet speeds  22-04-15   \n",
       "1  223441       payment disappear - service got disconnected  04-08-15   \n",
       "2  242732                                  speed and service  18-04-15   \n",
       "3  277946  comcast imposed a new usage cap of 300gb that ...  05-07-15   \n",
       "4  307175         comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "       dateT         time            issuedBy      city     state    zip  \\\n",
       "0  22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland  21009   \n",
       "1  04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia  30102   \n",
       "2  18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia  30101   \n",
       "3  05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia  30101   \n",
       "4  26-May-15   1:25:26 PM            Internet   Acworth   Georgia  30101   \n",
       "\n",
       "   status behalf month                                            tokens  \\\n",
       "0  Closed     No   Apr                          [cable, internet, speed]   \n",
       "1  Closed     No   Aug  [payment, disappear, service, got, disconnected]   \n",
       "2  Closed    Yes   Apr                                  [speed, service]   \n",
       "3    Open    Yes   Jul   [imposed, new, usage, cap, punishes, streaming]   \n",
       "4  Solved     No   May                          [working, service, boot]   \n",
       "\n",
       "                                              ngrams  \n",
       "0  [comcast, cable, internet, speeds, comcast cab...  \n",
       "1  [payment, disappear, -, service, got, disconne...  \n",
       "2  [speed, and, service, speed and, and service, ...  \n",
       "3  [comcast, imposed, a, new, usage, cap, of, 300...  \n",
       "4  [comcast, not, working, and, no, service, to, ...  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['ngrams'] = df['complaint'].apply(lambda x: [' '.join(ng) for ng in everygrams(word_tokenize(x), 1, 3)])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cleanData(olist):\n",
    "    return [l for l in olist if l not in stopwordSet]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticket</th>\n",
       "      <th>complaint</th>\n",
       "      <th>dateN</th>\n",
       "      <th>dateT</th>\n",
       "      <th>time</th>\n",
       "      <th>issuedBy</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>status</th>\n",
       "      <th>behalf</th>\n",
       "      <th>month</th>\n",
       "      <th>tokens</th>\n",
       "      <th>ngrams</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>comcast cable internet speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[cable, internet, speed]</td>\n",
       "      <td>[cable, internet, speeds, comcast cable, cable...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Aug</td>\n",
       "      <td>[payment, disappear, service, got, disconnected]</td>\n",
       "      <td>[payment, disappear, -, service, got, disconne...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>speed and service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[speed, service]</td>\n",
       "      <td>[speed, service, speed and, and service, speed...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>comcast imposed a new usage cap of 300gb that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Jul</td>\n",
       "      <td>[imposed, new, usage, cap, punishes, streaming]</td>\n",
       "      <td>[imposed, new, usage, cap, 300gb, punishes, st...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "      <td>May</td>\n",
       "      <td>[working, service, boot]</td>\n",
       "      <td>[working, service, boot, comcast not, not work...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ticket                                          complaint     dateN  \\\n",
       "0  250635                      comcast cable internet speeds  22-04-15   \n",
       "1  223441       payment disappear - service got disconnected  04-08-15   \n",
       "2  242732                                  speed and service  18-04-15   \n",
       "3  277946  comcast imposed a new usage cap of 300gb that ...  05-07-15   \n",
       "4  307175         comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "       dateT         time            issuedBy      city     state    zip  \\\n",
       "0  22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland  21009   \n",
       "1  04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia  30102   \n",
       "2  18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia  30101   \n",
       "3  05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia  30101   \n",
       "4  26-May-15   1:25:26 PM            Internet   Acworth   Georgia  30101   \n",
       "\n",
       "   status behalf month                                            tokens  \\\n",
       "0  Closed     No   Apr                          [cable, internet, speed]   \n",
       "1  Closed     No   Aug  [payment, disappear, service, got, disconnected]   \n",
       "2  Closed    Yes   Apr                                  [speed, service]   \n",
       "3    Open    Yes   Jul   [imposed, new, usage, cap, punishes, streaming]   \n",
       "4  Solved     No   May                          [working, service, boot]   \n",
       "\n",
       "                                              ngrams  \n",
       "0  [cable, internet, speeds, comcast cable, cable...  \n",
       "1  [payment, disappear, -, service, got, disconne...  \n",
       "2  [speed, service, speed and, and service, speed...  \n",
       "3  [imposed, new, usage, cap, 300gb, punishes, st...  \n",
       "4  [working, service, boot, comcast not, not work...  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['ngrams'] = df['ngrams'].apply(cleanData)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import string\n",
    "def get_all_ngrams(data,col):\n",
    "    all_ngrams = []\n",
    "    for i in range(len(data)):\n",
    "        each_row = data.iloc[i,col]\n",
    "        for j in range(len(each_row)):\n",
    "            tok = each_row[j]\n",
    "            #print(tok)\n",
    "            all_ngrams.append(tok)\n",
    "    all_ngrams = [ng.translate(str.maketrans('', '', string.punctuation)) for ng in all_ngrams ] \n",
    "    all_ngrams = [ng for ng in all_ngrams if len(ng)>1]\n",
    "    all_ngrams = [ng for ng in all_ngrams if ng not in stopwordSet]  \n",
    "    all_ngrams = [lemmatizer.lemmatize(w) for w in all_ngrams]\n",
    "    return all_ngrams"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "21323"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_ngrams = get_all_ngrams(df,13)\n",
    "len(all_ngrams)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "#finding all unique ngram values and getting their frequency\n",
    "#using the unique word as the index of the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>internet</th>\n",
       "      <td>518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>service</th>\n",
       "      <td>496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>billing</th>\n",
       "      <td>283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>data</th>\n",
       "      <td>219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>speed</th>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cap</th>\n",
       "      <td>181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>comcast internet</th>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>comcast data</th>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>charge</th>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customer</th>\n",
       "      <td>93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>issue</th>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>internet service</th>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>practice</th>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>data cap</th>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>customer service</th>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bill</th>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>data caps</th>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>comcast billing</th>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>xfinity</th>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  frequency\n",
       "internet                518\n",
       "service                 496\n",
       "billing                 283\n",
       "data                    219\n",
       "speed                   187\n",
       "cap                     181\n",
       "comcast internet        123\n",
       "comcast data            101\n",
       "charge                   94\n",
       "customer                 93\n",
       "issue                    90\n",
       "internet service         84\n",
       "practice                 81\n",
       "data cap                 80\n",
       "customer service         71\n",
       "bill                     66\n",
       "data caps                66\n",
       "comcast billing          66\n",
       "xfinity                  62\n",
       "price                    60"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique, counts = np.unique(all_ngrams, return_counts=True)\n",
    "frequency_df = pd.DataFrame(np.asarray(( counts)).T,columns=[\"frequency\"],index=unique)\n",
    "sorted_freq = frequency_df.sort_values(by=\"frequency\",ascending=False)\n",
    "sorted_freq[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "def getTopWOrds(corpus,n=None,ngram_len=1):\n",
    "    vec = CountVectorizer(ngram_range=(1,ngram_len)).fit(corpus)\n",
    "    bagOfWords = vec.transform(corpus)\n",
    "    sum_words = bagOfWords.sum(axis=0)\n",
    "    words_freq = [(word,sum_words[0,idx]) for word,idx in vec.vocabulary_.items()]\n",
    "    words_freq = sorted(words_freq,key = lambda x:x[1],reverse=True)\n",
    "    return words_freq[:n]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('comcast', 1246),\n",
       " ('internet', 535),\n",
       " ('service', 456),\n",
       " ('billing', 294),\n",
       " ('and', 279),\n",
       " ('data', 219),\n",
       " ('to', 187),\n",
       " ('for', 180),\n",
       " ('comcast internet', 130),\n",
       " ('speed', 122),\n",
       " ('of', 111),\n",
       " ('cap', 106),\n",
       " ('comcast data', 103),\n",
       " ('xfinity', 103),\n",
       " ('not', 97),\n",
       " ('customer', 94),\n",
       " ('issues', 93),\n",
       " ('internet service', 87),\n",
       " ('my', 84),\n",
       " ('data cap', 81),\n",
       " ('caps', 78),\n",
       " ('with', 77),\n",
       " ('customer service', 76),\n",
       " ('practices', 74),\n",
       " ('comcast billing', 74),\n",
       " ('speeds', 72),\n",
       " ('complaint', 71),\n",
       " ('charges', 71),\n",
       " ('no', 68),\n",
       " ('data caps', 66),\n",
       " ('comcast xfinity', 65),\n",
       " ('bill', 64),\n",
       " ('on', 59),\n",
       " ('unfair', 59),\n",
       " ('cable', 56),\n",
       " ('services', 55),\n",
       " ('throttling', 54),\n",
       " ('me', 50),\n",
       " ('billing practices', 50),\n",
       " ('slow', 49),\n",
       " ('in', 49),\n",
       " ('usage', 47),\n",
       " ('internet speed', 47),\n",
       " ('is', 47),\n",
       " ('comcast service', 45),\n",
       " ('poor', 45),\n",
       " ('the', 44),\n",
       " ('pricing', 42),\n",
       " ('by', 41),\n",
       " ('price', 40),\n",
       " ('from', 39),\n",
       " ('connection', 37),\n",
       " ('over', 37),\n",
       " ('data usage', 34),\n",
       " ('service and', 33),\n",
       " ('with comcast', 33),\n",
       " ('business', 33),\n",
       " ('internet speeds', 32),\n",
       " ('unfair billing', 32),\n",
       " ('contract', 30),\n",
       " ('phone', 30),\n",
       " ('issue', 30),\n",
       " ('from comcast', 30),\n",
       " ('by comcast', 29),\n",
       " ('false', 27),\n",
       " ('charged', 27),\n",
       " ('was', 26),\n",
       " ('account', 26),\n",
       " ('charging', 25),\n",
       " ('about', 25),\n",
       " ('without', 25),\n",
       " ('high', 25),\n",
       " ('fees', 24),\n",
       " ('slow internet', 24),\n",
       " ('comcast is', 24),\n",
       " ('problems', 24),\n",
       " ('that', 23),\n",
       " ('internet and', 23),\n",
       " ('billing issues', 23),\n",
       " ('billing and', 23),\n",
       " ('deceptive', 23),\n",
       " ('of service', 23),\n",
       " ('charge', 23),\n",
       " ('hbo', 22),\n",
       " ('tv', 22),\n",
       " ('fee', 22),\n",
       " ('prices', 21),\n",
       " ('monopoly', 21),\n",
       " ('switch', 21),\n",
       " ('paying', 21),\n",
       " ('paying for', 21),\n",
       " ('service issues', 21),\n",
       " ('fraudulent', 21),\n",
       " ('or', 21),\n",
       " ('modem', 20),\n",
       " ('advertised', 20),\n",
       " ('comcast throttling', 20),\n",
       " ('comcast cable', 19),\n",
       " ('after', 19),\n",
       " ('failure', 19),\n",
       " ('go', 19),\n",
       " ('access', 19),\n",
       " ('hbo go', 19),\n",
       " ('bait', 19),\n",
       " ('than', 19),\n",
       " ('terrible', 19),\n",
       " ('are', 19),\n",
       " ('lack', 18),\n",
       " ('lack of', 18),\n",
       " ('overage', 17),\n",
       " ('being', 17),\n",
       " ('equipment', 17),\n",
       " ('bait and', 17),\n",
       " ('and switch', 17),\n",
       " ('comcast customer', 17),\n",
       " ('for internet', 17),\n",
       " ('and billing', 17),\n",
       " ('internet connection', 17),\n",
       " ('of internet', 17),\n",
       " ('blocking', 16),\n",
       " ('against', 16),\n",
       " ('home', 16),\n",
       " ('comcast unfair', 16),\n",
       " ('service from', 16),\n",
       " ('horrible', 15),\n",
       " ('they', 15),\n",
       " ('have', 15),\n",
       " ('unable', 15),\n",
       " ('credit', 15),\n",
       " ('pay', 15),\n",
       " ('bad', 15),\n",
       " ('poor customer', 15),\n",
       " ('my internet', 15),\n",
       " ('up', 15),\n",
       " ('monthly', 15),\n",
       " ('low', 15),\n",
       " ('poor service', 15),\n",
       " ('lies', 15),\n",
       " ('down', 15),\n",
       " ('email', 14),\n",
       " ('failure to', 14),\n",
       " ('never', 14),\n",
       " ('unable to', 14),\n",
       " ('as', 14),\n",
       " ('has', 14),\n",
       " ('more', 14),\n",
       " ('issues with', 14),\n",
       " ('cancel', 14),\n",
       " ('no internet', 14),\n",
       " ('get', 14),\n",
       " ('charged for', 14),\n",
       " ('new', 13),\n",
       " ('refuses', 13),\n",
       " ('help', 13),\n",
       " ('comcast refuses', 13),\n",
       " ('availability', 13),\n",
       " ('provide', 13),\n",
       " ('what', 13),\n",
       " ('at', 13),\n",
       " ('incorrect', 13),\n",
       " ('comcast business', 13),\n",
       " ('against comcast', 13),\n",
       " ('unauthorized', 13),\n",
       " ('fraud', 13),\n",
       " ('refund', 13),\n",
       " ('outage', 13),\n",
       " ('quality', 13),\n",
       " ('and service', 12),\n",
       " ('300gb', 12),\n",
       " ('no service', 12),\n",
       " ('refuses to', 12),\n",
       " ('billed', 12),\n",
       " ('internet billing', 12),\n",
       " ('bandwidth', 12),\n",
       " ('complaint against', 12),\n",
       " ('problem', 12),\n",
       " ('it', 12),\n",
       " ('rental', 12),\n",
       " ('days', 12),\n",
       " ('advertising', 12),\n",
       " ('throttled', 12),\n",
       " ('high speed', 12),\n",
       " ('comcast complaint', 12),\n",
       " ('bundle', 12),\n",
       " ('lied', 12),\n",
       " ('when', 12),\n",
       " ('usage cap', 11),\n",
       " ('time', 11),\n",
       " ('comcast blocking', 11),\n",
       " ('promised', 11),\n",
       " ('playstation', 11),\n",
       " ('my bill', 11),\n",
       " ('comcast bill', 11),\n",
       " ('overage charges', 11),\n",
       " ('to cancel', 11),\n",
       " ('speed internet', 11),\n",
       " ('limit', 11),\n",
       " ('month', 11),\n",
       " ('one', 11),\n",
       " ('loss', 11),\n",
       " ('billing complaint', 11),\n",
       " ('with no', 11),\n",
       " ('speed and', 10),\n",
       " ('working', 10),\n",
       " ('outages', 10),\n",
       " ('to provide', 10),\n",
       " ('and customer', 10),\n",
       " ('monopolistic', 10),\n",
       " ('information', 10),\n",
       " ('comcast speed', 10),\n",
       " ('plan', 10),\n",
       " ('support', 10),\n",
       " ('intermittent', 10),\n",
       " ('installation', 10),\n",
       " ('comcast charging', 10),\n",
       " ('billing issue', 10),\n",
       " ('too', 10),\n",
       " ('increase', 10),\n",
       " ('fraudulent billing', 10),\n",
       " ('unfair pricing', 10),\n",
       " ('payment', 9),\n",
       " ('blocking hbo', 9),\n",
       " ('but', 9),\n",
       " ('wifi', 9),\n",
       " ('10', 9),\n",
       " ('sales', 9),\n",
       " ('go on', 9),\n",
       " ('connectivity', 9),\n",
       " ('xfinity comcast', 9),\n",
       " ('of comcast', 9),\n",
       " ('and internet', 9),\n",
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       " ('why', 2),\n",
       " ('raising prices', 2),\n",
       " ('asked', 2),\n",
       " ('service was', 2),\n",
       " ('violating', 2),\n",
       " ('consoles', 2),\n",
       " ('comcast violating', 2),\n",
       " ('violating open', 2),\n",
       " ('open internet', 2),\n",
       " ('go access', 2),\n",
       " ('access on', 2),\n",
       " ('disconnects', 2),\n",
       " ('need', 2),\n",
       " ('horrible internet', 2),\n",
       " ('apartment', 2),\n",
       " ('contract with', 2),\n",
       " ('comcast agent', 2),\n",
       " ('well', 2),\n",
       " ('wifi internet', 2),\n",
       " ('refunding', 2),\n",
       " ('not refunding', 2),\n",
       " ('my credit', 2),\n",
       " ('am paying', 2),\n",
       " ('evening', 2),\n",
       " ('etc', 2),\n",
       " ('after cancellation', 2),\n",
       " ('after more', 2),\n",
       " ('provide service', 2),\n",
       " ('service refusal', 2),\n",
       " ('spotty', 2),\n",
       " ('without service', 2),\n",
       " ('with xfinity', 2),\n",
       " ('rent', 2),\n",
       " ('cable modem', 2),\n",
       " ('collections', 2),\n",
       " ('like', 2),\n",
       " ('incorrect bill', 2),\n",
       " ('comcast added', 2),\n",
       " ('policy', 2),\n",
       " ('connect', 2),\n",
       " ('and telephone', 2),\n",
       " ('treatment', 2),\n",
       " ('business phone', 2),\n",
       " ('bank', 2),\n",
       " ('also', 2),\n",
       " ('corporate', 2),\n",
       " ('my services', 2),\n",
       " ('services for', 2),\n",
       " ('discontinuation', 2),\n",
       " ('discontinuation of', 2),\n",
       " ('caps in', 2),\n",
       " ('bad customer', 2),\n",
       " ('usage charges', 2),\n",
       " ('bill or', 2),\n",
       " ('or service', 2),\n",
       " ('comcast atlanta', 2),\n",
       " ('atlanta data', 2),\n",
       " ('deceptive advertising', 2),\n",
       " ('upload', 2),\n",
       " ('download speeds', 2),\n",
       " ('change of', 2),\n",
       " ('becoming', 2),\n",
       " ('xfinity home', 2),\n",
       " ('setup', 2),\n",
       " ('order', 2),\n",
       " ('waiting', 2),\n",
       " ('bundling of', 2),\n",
       " ('recognize', 2),\n",
       " ('to recognize', 2),\n",
       " ('termination fee', 2),\n",
       " ('cable bill', 2),\n",
       " ('turned', 2),\n",
       " ('for complaints', 2),\n",
       " ('comcast does', 2),\n",
       " ('the internet', 2),\n",
       " ('on my', 2),\n",
       " ('disclosed', 2),\n",
       " ('not disclosed', 2),\n",
       " ('intermittent service', 2),\n",
       " ('consistently slow', 2),\n",
       " ('slow and', 2),\n",
       " ('throttled internet', 2),\n",
       " ('slow service', 2),\n",
       " ('monopoly on', 2),\n",
       " ('more money', 2),\n",
       " ('money for', 2),\n",
       " ('hidden fees', 2),\n",
       " ('internet monopoly', 2),\n",
       " ('no cable', 2),\n",
       " ('and intermittent', 2),\n",
       " ('comcast account', 2),\n",
       " ...]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topwords = getTopWOrds(df[\"complaint\"],ngram_len=2)\n",
    "topwords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "vectorizer = TfidfVectorizer(stop_words=\"english\")\n",
    "X = vectorizer.fit_transform(df[\"complaint\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Using Elbow method to determine number of clusters\n",
    "cost =[] \n",
    "for i in range(1, 20): \n",
    "    KM = KMeans(n_clusters = i, max_iter = 2000) \n",
    "    KM.fit(X) \n",
    "      \n",
    "    # calculates squared error \n",
    "    # for the clustered points \n",
    "    cost.append(KM.inertia_)      \n",
    "  \n",
    "# plot the cost against K values \n",
    "plt.plot(range(1, 20), cost, color ='g', linewidth ='3') \n",
    "plt.xlabel(\"Value of K\") \n",
    "plt.ylabel(\"Sqaured Error (Cost)\") \n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(init='random', max_iter=100, n_clusters=6, n_init=20, random_state=1,\n",
       "       tol=1e-06)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#chosing 6 means as the areas of interest are mainly around 6 types of issues\n",
    "# The optimum k values using elbow method = 6\n",
    "true_k = 6\n",
    "model = KMeans(n_clusters=true_k, init='random', max_iter=100, n_init=20,tol=0.000001,random_state=1)\n",
    "model.fit(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 5 terms per cluster:\n",
      "Cluster 0:\n",
      " data\n",
      " cap\n",
      " caps\n",
      " comcast\n",
      " usage\n",
      " limit\n",
      " 300gb\n",
      " internet\n",
      " charges\n",
      " meter\n",
      "\n",
      "\n",
      "Cluster 1:\n",
      " comcast\n",
      " internet\n",
      " complaint\n",
      " essentials\n",
      " equipment\n",
      " erroneous\n",
      " error\n",
      " errors\n",
      " escalation\n",
      " esl01877347\n",
      "\n",
      "\n",
      "Cluster 2:\n",
      " service\n",
      " comcast\n",
      " internet\n",
      " customer\n",
      " poor\n",
      " complaint\n",
      " xfinity\n",
      " issues\n",
      " terrible\n",
      " horrible\n",
      "\n",
      "\n",
      "Cluster 3:\n",
      " internet\n",
      " comcast\n",
      " speed\n",
      " xfinity\n",
      " speeds\n",
      " throttling\n",
      " charges\n",
      " cable\n",
      " slow\n",
      " services\n",
      "\n",
      "\n",
      "Cluster 4:\n",
      " unfair\n",
      " practices\n",
      " billing\n",
      " pricing\n",
      " comcast\n",
      " throttling\n",
      " internet\n",
      " xfinity\n",
      " bundles\n",
      " policies\n",
      "\n",
      "\n",
      "Cluster 5:\n",
      " billing\n",
      " comcast\n",
      " issues\n",
      " service\n",
      " practices\n",
      " internet\n",
      " complaint\n",
      " issue\n",
      " fraudulent\n",
      " dispute\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Top 5 terms per cluster:\")\n",
    "order_centroids = model.cluster_centers_.argsort()[:, ::-1]\n",
    "terms = vectorizer.get_feature_names()\n",
    "for i in range(true_k):\n",
    "    print(\"Cluster %d:\" % i),\n",
    "    for ind in order_centroids[i, :10]:\n",
    "        print(' %s' % terms[ind])\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 4)Which complaint types are maximum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticket</th>\n",
       "      <th>complaint</th>\n",
       "      <th>dateN</th>\n",
       "      <th>dateT</th>\n",
       "      <th>time</th>\n",
       "      <th>issuedBy</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>status</th>\n",
       "      <th>behalf</th>\n",
       "      <th>month</th>\n",
       "      <th>tokens</th>\n",
       "      <th>ngrams</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>comcast cable internet speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[cable, internet, speed]</td>\n",
       "      <td>[cable, internet, speeds, comcast cable, cable...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Aug</td>\n",
       "      <td>[payment, disappear, service, got, disconnected]</td>\n",
       "      <td>[payment, disappear, -, service, got, disconne...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>speed and service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[speed, service]</td>\n",
       "      <td>[speed, service, speed and, and service, speed...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>comcast imposed a new usage cap of 300gb that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Jul</td>\n",
       "      <td>[imposed, new, usage, cap, punishes, streaming]</td>\n",
       "      <td>[imposed, new, usage, cap, 300gb, punishes, st...</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "      <td>May</td>\n",
       "      <td>[working, service, boot]</td>\n",
       "      <td>[working, service, boot, comcast not, not work...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ticket                                          complaint     dateN  \\\n",
       "0  250635                      comcast cable internet speeds  22-04-15   \n",
       "1  223441       payment disappear - service got disconnected  04-08-15   \n",
       "2  242732                                  speed and service  18-04-15   \n",
       "3  277946  comcast imposed a new usage cap of 300gb that ...  05-07-15   \n",
       "4  307175         comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "       dateT         time            issuedBy      city     state    zip  \\\n",
       "0  22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland  21009   \n",
       "1  04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia  30102   \n",
       "2  18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia  30101   \n",
       "3  05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia  30101   \n",
       "4  26-May-15   1:25:26 PM            Internet   Acworth   Georgia  30101   \n",
       "\n",
       "   status behalf month                                            tokens  \\\n",
       "0  Closed     No   Apr                          [cable, internet, speed]   \n",
       "1  Closed     No   Aug  [payment, disappear, service, got, disconnected]   \n",
       "2  Closed    Yes   Apr                                  [speed, service]   \n",
       "3    Open    Yes   Jul   [imposed, new, usage, cap, punishes, streaming]   \n",
       "4  Solved     No   May                          [working, service, boot]   \n",
       "\n",
       "                                              ngrams  cluster  \n",
       "0  [cable, internet, speeds, comcast cable, cable...        3  \n",
       "1  [payment, disappear, -, service, got, disconne...        3  \n",
       "2  [speed, service, speed and, and service, speed...        2  \n",
       "3  [imposed, new, usage, cap, 300gb, punishes, st...        3  \n",
       "4  [working, service, boot, comcast not, not work...        2  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"cluster\"] = model.labels_ \n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     207\n",
       "1     163\n",
       "2     292\n",
       "3    1306\n",
       "4      56\n",
       "5     200\n",
       "Name: ticket, dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_cluster = df.groupby([model.labels_])[\"ticket\"].count()\n",
    "groupby_cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Maximum tickets belong to cluster 0 which relate to [internet,high throttling,slow connection ,price,paying]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 5)Create a new categorical variable with value as Open and Closed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def change_status(status):\n",
    "    if status in [\"Open\",\"Pending\"]:\n",
    "        return \"OPEN\"\n",
    "    elif status in [\"Closed\",\"Solved\"]:\n",
    "        return \"CLOSED\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ticket</th>\n",
       "      <th>complaint</th>\n",
       "      <th>dateN</th>\n",
       "      <th>dateT</th>\n",
       "      <th>time</th>\n",
       "      <th>issuedBy</th>\n",
       "      <th>city</th>\n",
       "      <th>state</th>\n",
       "      <th>zip</th>\n",
       "      <th>status</th>\n",
       "      <th>behalf</th>\n",
       "      <th>month</th>\n",
       "      <th>tokens</th>\n",
       "      <th>ngrams</th>\n",
       "      <th>cluster</th>\n",
       "      <th>updated_status</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>250635</td>\n",
       "      <td>comcast cable internet speeds</td>\n",
       "      <td>22-04-15</td>\n",
       "      <td>22-Apr-15</td>\n",
       "      <td>3:53:50 PM</td>\n",
       "      <td>Customer Care Call</td>\n",
       "      <td>Abingdon</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>21009</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[cable, internet, speed]</td>\n",
       "      <td>[cable, internet, speeds, comcast cable, cable...</td>\n",
       "      <td>3</td>\n",
       "      <td>CLOSED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>223441</td>\n",
       "      <td>payment disappear - service got disconnected</td>\n",
       "      <td>04-08-15</td>\n",
       "      <td>04-Aug-15</td>\n",
       "      <td>10:22:56 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30102</td>\n",
       "      <td>Closed</td>\n",
       "      <td>No</td>\n",
       "      <td>Aug</td>\n",
       "      <td>[payment, disappear, service, got, disconnected]</td>\n",
       "      <td>[payment, disappear, -, service, got, disconne...</td>\n",
       "      <td>3</td>\n",
       "      <td>CLOSED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>242732</td>\n",
       "      <td>speed and service</td>\n",
       "      <td>18-04-15</td>\n",
       "      <td>18-Apr-15</td>\n",
       "      <td>9:55:47 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Closed</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Apr</td>\n",
       "      <td>[speed, service]</td>\n",
       "      <td>[speed, service, speed and, and service, speed...</td>\n",
       "      <td>2</td>\n",
       "      <td>CLOSED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>277946</td>\n",
       "      <td>comcast imposed a new usage cap of 300gb that ...</td>\n",
       "      <td>05-07-15</td>\n",
       "      <td>05-Jul-15</td>\n",
       "      <td>11:59:35 AM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Open</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Jul</td>\n",
       "      <td>[imposed, new, usage, cap, punishes, streaming]</td>\n",
       "      <td>[imposed, new, usage, cap, 300gb, punishes, st...</td>\n",
       "      <td>3</td>\n",
       "      <td>OPEN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>307175</td>\n",
       "      <td>comcast not working and no service to boot</td>\n",
       "      <td>26-05-15</td>\n",
       "      <td>26-May-15</td>\n",
       "      <td>1:25:26 PM</td>\n",
       "      <td>Internet</td>\n",
       "      <td>Acworth</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>30101</td>\n",
       "      <td>Solved</td>\n",
       "      <td>No</td>\n",
       "      <td>May</td>\n",
       "      <td>[working, service, boot]</td>\n",
       "      <td>[working, service, boot, comcast not, not work...</td>\n",
       "      <td>2</td>\n",
       "      <td>CLOSED</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ticket                                          complaint     dateN  \\\n",
       "0  250635                      comcast cable internet speeds  22-04-15   \n",
       "1  223441       payment disappear - service got disconnected  04-08-15   \n",
       "2  242732                                  speed and service  18-04-15   \n",
       "3  277946  comcast imposed a new usage cap of 300gb that ...  05-07-15   \n",
       "4  307175         comcast not working and no service to boot  26-05-15   \n",
       "\n",
       "       dateT         time            issuedBy      city     state    zip  \\\n",
       "0  22-Apr-15   3:53:50 PM  Customer Care Call  Abingdon  Maryland  21009   \n",
       "1  04-Aug-15  10:22:56 AM            Internet   Acworth   Georgia  30102   \n",
       "2  18-Apr-15   9:55:47 AM            Internet   Acworth   Georgia  30101   \n",
       "3  05-Jul-15  11:59:35 AM            Internet   Acworth   Georgia  30101   \n",
       "4  26-May-15   1:25:26 PM            Internet   Acworth   Georgia  30101   \n",
       "\n",
       "   status behalf month                                            tokens  \\\n",
       "0  Closed     No   Apr                          [cable, internet, speed]   \n",
       "1  Closed     No   Aug  [payment, disappear, service, got, disconnected]   \n",
       "2  Closed    Yes   Apr                                  [speed, service]   \n",
       "3    Open    Yes   Jul   [imposed, new, usage, cap, punishes, streaming]   \n",
       "4  Solved     No   May                          [working, service, boot]   \n",
       "\n",
       "                                              ngrams  cluster updated_status  \n",
       "0  [cable, internet, speeds, comcast cable, cable...        3         CLOSED  \n",
       "1  [payment, disappear, -, service, got, disconne...        3         CLOSED  \n",
       "2  [speed, service, speed and, and service, speed...        2         CLOSED  \n",
       "3  [imposed, new, usage, cap, 300gb, punishes, st...        3           OPEN  \n",
       "4  [working, service, boot, comcast not, not work...        2         CLOSED  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"updated_status\"] = df[\"status\"].apply(change_status)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 6)Provide state wise status of complaints in a stacked bar chart. Use the categorized variable "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state\n",
       "Alabama                  26\n",
       "Arizona                  20\n",
       "Arkansas                  6\n",
       "California              220\n",
       "Colorado                 80\n",
       "Connecticut              12\n",
       "Delaware                 12\n",
       "District Of Columbia     16\n",
       "District of Columbia      1\n",
       "Florida                 240\n",
       "Georgia                 288\n",
       "Illinois                164\n",
       "Indiana                  59\n",
       "Iowa                      1\n",
       "Kansas                    2\n",
       "Kentucky                  7\n",
       "Louisiana                13\n",
       "Maine                     5\n",
       "Maryland                 78\n",
       "Massachusetts            61\n",
       "Michigan                115\n",
       "Minnesota                33\n",
       "Mississippi              39\n",
       "Missouri                  4\n",
       "Montana                   1\n",
       "Nevada                    1\n",
       "New Hampshire            12\n",
       "New Jersey               75\n",
       "New Mexico               15\n",
       "New York                  6\n",
       "North Carolina            3\n",
       "Ohio                      3\n",
       "Oregon                   49\n",
       "Pennsylvania            130\n",
       "Rhode Island              1\n",
       "South Carolina           18\n",
       "Tennessee               143\n",
       "Texas                    71\n",
       "Utah                     22\n",
       "Vermont                   3\n",
       "Virginia                 60\n",
       "Washington               98\n",
       "West Virginia            11\n",
       "Name: ticket, dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_state = (df.groupby(df['state']))[\"ticket\"].count()\n",
    "groupby_state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Alabama', 'Arizona', 'Arkansas', 'California', 'Colorado',\n",
       "       'Connecticut', 'Delaware', 'District Of Columbia',\n",
       "       'District of Columbia', 'Florida', 'Georgia', 'Illinois', 'Indiana',\n",
       "       'Iowa', 'Kansas', 'Kentucky', 'Louisiana', 'Maine', 'Maryland',\n",
       "       'Massachusetts', 'Michigan', 'Minnesota', 'Mississippi', 'Missouri',\n",
       "       'Montana', 'Nevada', 'New Hampshire', 'New Jersey', 'New Mexico',\n",
       "       'New York', 'North Carolina', 'Ohio', 'Oregon', 'Pennsylvania',\n",
       "       'Rhode Island', 'South Carolina', 'Tennessee', 'Texas', 'Utah',\n",
       "       'Vermont', 'Virginia', 'Washington', 'West Virginia'],\n",
       "      dtype='object', name='state')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_state.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(num=None, figsize=(20, 10), dpi=80)\n",
    "plt.bar(x=groupby_state.index,height = groupby_state.values)\n",
    "plt.xticks(groupby_state.index, groupby_state.index, rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state                 updated_status\n",
       "Alabama               CLOSED             17\n",
       "                      OPEN                9\n",
       "Arizona               CLOSED             14\n",
       "                      OPEN                6\n",
       "Arkansas              CLOSED              6\n",
       "California            CLOSED            159\n",
       "                      OPEN               61\n",
       "Colorado              CLOSED             58\n",
       "                      OPEN               22\n",
       "Connecticut           CLOSED              9\n",
       "                      OPEN                3\n",
       "Delaware              CLOSED              8\n",
       "                      OPEN                4\n",
       "District Of Columbia  CLOSED             14\n",
       "                      OPEN                2\n",
       "District of Columbia  CLOSED              1\n",
       "Florida               CLOSED            201\n",
       "                      OPEN               39\n",
       "Georgia               CLOSED            208\n",
       "                      OPEN               80\n",
       "Illinois              CLOSED            135\n",
       "                      OPEN               29\n",
       "Indiana               CLOSED             50\n",
       "                      OPEN                9\n",
       "Iowa                  CLOSED              1\n",
       "Kansas                CLOSED              1\n",
       "                      OPEN                1\n",
       "Kentucky              CLOSED              4\n",
       "                      OPEN                3\n",
       "Louisiana             CLOSED             12\n",
       "                      OPEN                1\n",
       "Maine                 CLOSED              3\n",
       "                      OPEN                2\n",
       "Maryland              CLOSED             63\n",
       "                      OPEN               15\n",
       "Massachusetts         CLOSED             50\n",
       "                      OPEN               11\n",
       "Michigan              CLOSED             92\n",
       "                      OPEN               23\n",
       "Minnesota             CLOSED             29\n",
       "                      OPEN                4\n",
       "Mississippi           CLOSED             23\n",
       "                      OPEN               16\n",
       "Missouri              CLOSED              3\n",
       "                      OPEN                1\n",
       "Montana               CLOSED              1\n",
       "Nevada                CLOSED              1\n",
       "New Hampshire         CLOSED              8\n",
       "                      OPEN                4\n",
       "New Jersey            CLOSED             56\n",
       "                      OPEN               19\n",
       "New Mexico            CLOSED             11\n",
       "                      OPEN                4\n",
       "New York              CLOSED              6\n",
       "North Carolina        CLOSED              3\n",
       "Ohio                  CLOSED              3\n",
       "Oregon                CLOSED             36\n",
       "                      OPEN               13\n",
       "Pennsylvania          CLOSED            110\n",
       "                      OPEN               20\n",
       "Rhode Island          CLOSED              1\n",
       "South Carolina        CLOSED             15\n",
       "                      OPEN                3\n",
       "Tennessee             CLOSED             96\n",
       "                      OPEN               47\n",
       "Texas                 CLOSED             49\n",
       "                      OPEN               22\n",
       "Utah                  CLOSED             16\n",
       "                      OPEN                6\n",
       "Vermont               CLOSED              2\n",
       "                      OPEN                1\n",
       "Virginia              CLOSED             49\n",
       "                      OPEN               11\n",
       "Washington            CLOSED             75\n",
       "                      OPEN               23\n",
       "West Virginia         CLOSED              8\n",
       "                      OPEN                3\n",
       "Name: ticket, dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_state_ustatus = df.groupby(['state','updated_status'])[\"ticket\"].count()\n",
    "groupby_state_ustatus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>updated_status</th>\n",
       "      <th>CLOSED</th>\n",
       "      <th>OPEN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>17.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>14.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>159.0</td>\n",
       "      <td>61.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>58.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District Of Columbia</th>\n",
       "      <td>14.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>201.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>208.0</td>\n",
       "      <td>80.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>135.0</td>\n",
       "      <td>29.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>50.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>63.0</td>\n",
       "      <td>15.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>50.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>92.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>29.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>23.0</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>8.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>56.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>11.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>36.0</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>110.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>15.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>96.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>49.0</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>16.0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>49.0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>75.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>8.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "updated_status        CLOSED  OPEN\n",
       "state                             \n",
       "Alabama                 17.0   9.0\n",
       "Arizona                 14.0   6.0\n",
       "Arkansas                 6.0   0.0\n",
       "California             159.0  61.0\n",
       "Colorado                58.0  22.0\n",
       "Connecticut              9.0   3.0\n",
       "Delaware                 8.0   4.0\n",
       "District Of Columbia    14.0   2.0\n",
       "District of Columbia     1.0   0.0\n",
       "Florida                201.0  39.0\n",
       "Georgia                208.0  80.0\n",
       "Illinois               135.0  29.0\n",
       "Indiana                 50.0   9.0\n",
       "Iowa                     1.0   0.0\n",
       "Kansas                   1.0   1.0\n",
       "Kentucky                 4.0   3.0\n",
       "Louisiana               12.0   1.0\n",
       "Maine                    3.0   2.0\n",
       "Maryland                63.0  15.0\n",
       "Massachusetts           50.0  11.0\n",
       "Michigan                92.0  23.0\n",
       "Minnesota               29.0   4.0\n",
       "Mississippi             23.0  16.0\n",
       "Missouri                 3.0   1.0\n",
       "Montana                  1.0   0.0\n",
       "Nevada                   1.0   0.0\n",
       "New Hampshire            8.0   4.0\n",
       "New Jersey              56.0  19.0\n",
       "New Mexico              11.0   4.0\n",
       "New York                 6.0   0.0\n",
       "North Carolina           3.0   0.0\n",
       "Ohio                     3.0   0.0\n",
       "Oregon                  36.0  13.0\n",
       "Pennsylvania           110.0  20.0\n",
       "Rhode Island             1.0   0.0\n",
       "South Carolina          15.0   3.0\n",
       "Tennessee               96.0  47.0\n",
       "Texas                   49.0  22.0\n",
       "Utah                    16.0   6.0\n",
       "Vermont                  2.0   1.0\n",
       "Virginia                49.0  11.0\n",
       "Washington              75.0  23.0\n",
       "West Virginia            8.0   3.0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group_values = groupby_state_ustatus.unstack().fillna(0)\n",
    "group_values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "closedTickets = group_values[\"CLOSED\"]\n",
    "openTickets = group_values[\"OPEN\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure(num=None, figsize=(20, 10), dpi=80)\n",
    "p1 = plt.bar(groupby_state.index, closedTickets, 0.35)\n",
    "p2 = plt.bar(groupby_state.index, openTickets, 0.35,bottom=closedTickets)\n",
    "plt.xticks(groupby_state.index, groupby_state.index, rotation='vertical')\n",
    "plt.legend((p1[0], p2[0]), ('CLOSED', 'OPEN'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  7)Which state has the maximum complaints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "updated_status\n",
       "CLOSED    Georgia\n",
       "OPEN      Georgia\n",
       "dtype: object"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maxTickets = group_values.idxmax()\n",
    "maxTickets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clearly Georgia has the maximum number of tickets"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 8)Which state has the highest percentage of unresolved complaints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "state\n",
       "Kansas                  0.500000\n",
       "Kentucky                0.428571\n",
       "Mississippi             0.410256\n",
       "Maine                   0.400000\n",
       "Alabama                 0.346154\n",
       "New Hampshire           0.333333\n",
       "Vermont                 0.333333\n",
       "Delaware                0.333333\n",
       "Tennessee               0.328671\n",
       "Texas                   0.309859\n",
       "Arizona                 0.300000\n",
       "Georgia                 0.277778\n",
       "California              0.277273\n",
       "Colorado                0.275000\n",
       "West Virginia           0.272727\n",
       "Utah                    0.272727\n",
       "New Mexico              0.266667\n",
       "Oregon                  0.265306\n",
       "New Jersey              0.253333\n",
       "Connecticut             0.250000\n",
       "Missouri                0.250000\n",
       "Washington              0.234694\n",
       "Michigan                0.200000\n",
       "Maryland                0.192308\n",
       "Virginia                0.183333\n",
       "Massachusetts           0.180328\n",
       "Illinois                0.176829\n",
       "South Carolina          0.166667\n",
       "Florida                 0.162500\n",
       "Pennsylvania            0.153846\n",
       "Indiana                 0.152542\n",
       "District Of Columbia    0.125000\n",
       "Minnesota               0.121212\n",
       "Louisiana               0.076923\n",
       "Ohio                    0.000000\n",
       "District of Columbia    0.000000\n",
       "Rhode Island            0.000000\n",
       "North Carolina          0.000000\n",
       "New York                0.000000\n",
       "Montana                 0.000000\n",
       "Arkansas                0.000000\n",
       "Nevada                  0.000000\n",
       "Iowa                    0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "totalTickets = np.add(openTickets,closedTickets)\n",
    "percentOpen = np.divide(openTickets,totalTickets)\n",
    "percentOpen.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Kansas have maximum percentage of unresolved tickets amongst the states"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 9)Provide the percentage of complaints resolved till date, which were received through the Internet and customer care calls."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>updated_status</th>\n",
       "      <th>CLOSED</th>\n",
       "      <th>OPEN</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>issuedBy</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Customer Care Call</th>\n",
       "      <td>864</td>\n",
       "      <td>255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Internet</th>\n",
       "      <td>843</td>\n",
       "      <td>262</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "updated_status      CLOSED  OPEN\n",
       "issuedBy                        \n",
       "Customer Care Call     864   255\n",
       "Internet               843   262"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groupby_resolved_internet_calls = df.groupby([\"issuedBy\",\"updated_status\"])[\"ticket\"].count()\n",
    "issuedby = groupby_resolved_internet_calls.unstack()\n",
    "issuedby"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Customer Care Call - Resolved %  :  77.21179624664879\n",
      "Internet - Resolved %  :  76.289592760181\n"
     ]
    }
   ],
   "source": [
    "closedCCC = issuedby.loc[\"Customer Care Call\",\"CLOSED\"]\n",
    "totalCCC = issuedby.loc[\"Customer Care Call\",\"CLOSED\"]+issuedby.loc[\"Customer Care Call\",\"OPEN\"]\n",
    "closedIN = issuedby.loc[\"Internet\",\"CLOSED\"]\n",
    "totalIN = issuedby.loc[\"Internet\",\"CLOSED\"]+issuedby.loc[\"Internet\",\"OPEN\"]\n",
    "\n",
    "resolvedCCC = (closedCCC / totalCCC)*100\n",
    "resolvedIN = (closedIN / totalIN)*100\n",
    "\n",
    "print(\"Customer Care Call - Resolved %  : \",resolvedCCC)\n",
    "print(\"Internet - Resolved %  : \",resolvedIN)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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