exploring.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "productive-weekend",
   "metadata": {},
   "source": [
    "<div align=\"center\">\n",
    "    <img src=\"images/logo.png\" width=\"250\" height=\"200\">\n",
    "</div>\n",
    "\n",
    "<div align=\"center\">\n",
    "    To download the previously cleaned dataset click <a href=\"https://drive.google.com/file/d/1mYJws7uPjbPqPszUQHpf4PfrHSEjAVIu/view?usp=sharing\" target=\"__blank\">here</a>.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "surrounded-storage",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import packages\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# set max rows displayed in output to 25\n",
    "pd.set_option(\"display.max_rows\", 25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "obvious-margin",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape:  (1057135, 16)\n"
     ]
    },
    {
     "data": {
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       "    }\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>Date received</th>\n",
       "      <th>Product</th>\n",
       "      <th>Sub-product</th>\n",
       "      <th>Issue</th>\n",
       "      <th>Sub-issue</th>\n",
       "      <th>Consumer complaint narrative</th>\n",
       "      <th>Company public response</th>\n",
       "      <th>Company</th>\n",
       "      <th>State</th>\n",
       "      <th>ZIP code</th>\n",
       "      <th>Consumer consent provided?</th>\n",
       "      <th>Submitted via</th>\n",
       "      <th>Date sent to company</th>\n",
       "      <th>Company response to consumer</th>\n",
       "      <th>Timely response?</th>\n",
       "      <th>Consumer disputed?</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Complaint ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3379500</th>\n",
       "      <td>2019-09-19</td>\n",
       "      <td>Credit reporting, credit repair services, or o...</td>\n",
       "      <td>Credit reporting</td>\n",
       "      <td>Incorrect information on your report</td>\n",
       "      <td>Information belongs to someone else</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>Company has responded to the consumer and the ...</td>\n",
       "      <td>Experian Information Solutions Inc.</td>\n",
       "      <td>PA</td>\n",
       "      <td>15206</td>\n",
       "      <td>Consent not provided</td>\n",
       "      <td>Web</td>\n",
       "      <td>2019-09-20</td>\n",
       "      <td>Closed with non-monetary relief</td>\n",
       "      <td>Yes</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3255455</th>\n",
       "      <td>2019-05-23</td>\n",
       "      <td>Checking or savings account</td>\n",
       "      <td>Checking account</td>\n",
       "      <td>Managing an account</td>\n",
       "      <td>Deposits and withdrawals</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>Company has responded to the consumer and the ...</td>\n",
       "      <td>MIDFIRST BANK</td>\n",
       "      <td>AZ</td>\n",
       "      <td>85254</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>Referral</td>\n",
       "      <td>2019-05-28</td>\n",
       "      <td>Closed with explanation</td>\n",
       "      <td>Yes</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4267123</th>\n",
       "      <td>2021-04-02</td>\n",
       "      <td>Credit reporting, credit repair services, or o...</td>\n",
       "      <td>Credit reporting</td>\n",
       "      <td>Incorrect information on your report</td>\n",
       "      <td>Information belongs to someone else</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>EQUIFAX, INC.</td>\n",
       "      <td>PA</td>\n",
       "      <td>19403</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>Web</td>\n",
       "      <td>2021-04-02</td>\n",
       "      <td>Closed with explanation</td>\n",
       "      <td>Yes</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Date received                                            Product  \\\n",
       "Complaint ID                                                                    \n",
       "3379500         2019-09-19  Credit reporting, credit repair services, or o...   \n",
       "3255455         2019-05-23                        Checking or savings account   \n",
       "4267123         2021-04-02  Credit reporting, credit repair services, or o...   \n",
       "\n",
       "                   Sub-product                                 Issue  \\\n",
       "Complaint ID                                                           \n",
       "3379500       Credit reporting  Incorrect information on your report   \n",
       "3255455       Checking account                   Managing an account   \n",
       "4267123       Credit reporting  Incorrect information on your report   \n",
       "\n",
       "                                        Sub-issue  \\\n",
       "Complaint ID                                        \n",
       "3379500       Information belongs to someone else   \n",
       "3255455                  Deposits and withdrawals   \n",
       "4267123       Information belongs to someone else   \n",
       "\n",
       "             Consumer complaint narrative  \\\n",
       "Complaint ID                                \n",
       "3379500                              <NA>   \n",
       "3255455                              <NA>   \n",
       "4267123                              <NA>   \n",
       "\n",
       "                                        Company public response  \\\n",
       "Complaint ID                                                      \n",
       "3379500       Company has responded to the consumer and the ...   \n",
       "3255455       Company has responded to the consumer and the ...   \n",
       "4267123                                                    <NA>   \n",
       "\n",
       "                                          Company State ZIP code  \\\n",
       "Complaint ID                                                       \n",
       "3379500       Experian Information Solutions Inc.    PA    15206   \n",
       "3255455                             MIDFIRST BANK    AZ    85254   \n",
       "4267123                             EQUIFAX, INC.    PA    19403   \n",
       "\n",
       "             Consumer consent provided? Submitted via Date sent to company  \\\n",
       "Complaint ID                                                                 \n",
       "3379500            Consent not provided           Web           2019-09-20   \n",
       "3255455                            <NA>      Referral           2019-05-28   \n",
       "4267123                            <NA>           Web           2021-04-02   \n",
       "\n",
       "                 Company response to consumer Timely response?  \\\n",
       "Complaint ID                                                     \n",
       "3379500       Closed with non-monetary relief              Yes   \n",
       "3255455               Closed with explanation              Yes   \n",
       "4267123               Closed with explanation              Yes   \n",
       "\n",
       "             Consumer disputed?  \n",
       "Complaint ID                     \n",
       "3379500                    <NA>  \n",
       "3255455                    <NA>  \n",
       "4267123                    <NA>  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read the data\n",
    "df = pd.read_pickle('clean_complaints.pkl')\n",
    "print(\"Shape: \", df.shape)\n",
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "indoor-latter",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(100, 16)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# copy a small part of the dataset\n",
    "# we'll use it to write useful functions\n",
    "df2 = df[0:100]\n",
    "df2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "settled-basic",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Experian Information Solutions Inc.', 'MIDFIRST BANK', 'EQUIFAX, INC.', 'PENTAGON FEDERAL CREDIT UNION', 'Square Inc.', ..., 'ALLY FINANCIAL INC.', 'Alliance Data Card Services', 'SLM CORPORATION', 'Quick Bridge Funding, LLC', 'BBVA FINANCIAL CORPORATION']\n",
       "Length: 46\n",
       "Categories (46, object): ['Experian Information Solutions Inc.', 'MIDFIRST BANK', 'EQUIFAX, INC.', 'PENTAGON FEDERAL CREDIT UNION', ..., 'Alliance Data Card Services', 'SLM CORPORATION', 'Quick Bridge Funding, LLC', 'BBVA FINANCIAL CORPORATION']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# there are 46 unique companies among those 100 entries\n",
    "df2.Company.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "subject-committee",
   "metadata": {},
   "outputs": [],
   "source": [
    "# takes a dataframe and creates a new dataframe with the number of complaints for each company\n",
    "def complaints_per_company(passed_df):\n",
    "    complaints = pd.DataFrame({'Company Name': [], 'Number of Complaints': []})\n",
    "    \n",
    "    # iterate all unique companies \n",
    "    for company in passed_df.Company.unique():\n",
    "        company_name = str(company)\n",
    "        number_of_complaints = passed_df[passed_df['Company'] == company].shape[0]\n",
    "        \n",
    "        new_row = {'Company Name': company_name, 'Number of Complaints': number_of_complaints}\n",
    "        complaints = complaints.append(new_row, ignore_index=True)\n",
    "        \n",
    "    return complaints"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "eligible-command",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Number of Complaints</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Experian Information Solutions Inc.</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>MIDFIRST BANK</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EQUIFAX, INC.</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PENTAGON FEDERAL CREDIT UNION</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Square Inc.</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Company Name  Number of Complaints\n",
       "0  Experian Information Solutions Inc.                  13.0\n",
       "1                        MIDFIRST BANK                   1.0\n",
       "2                        EQUIFAX, INC.                   9.0\n",
       "3        PENTAGON FEDERAL CREDIT UNION                   1.0\n",
       "4                          Square Inc.                   1.0"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# checking first 100 entries\n",
    "complaints = complaints_per_company(df2)\n",
    "complaints.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "diverse-cyprus",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Complaints</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Company Name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Experian Information Solutions Inc.</th>\n",
       "      <td>121215.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIDFIRST BANK</th>\n",
       "      <td>262.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EQUIFAX, INC.</th>\n",
       "      <td>131461.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PENTAGON FEDERAL CREDIT UNION</th>\n",
       "      <td>1100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Square Inc.</th>\n",
       "      <td>685.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Number of Complaints\n",
       "Company Name                                             \n",
       "Experian Information Solutions Inc.              121215.0\n",
       "MIDFIRST BANK                                       262.0\n",
       "EQUIFAX, INC.                                    131461.0\n",
       "PENTAGON FEDERAL CREDIT UNION                      1100.0\n",
       "Square Inc.                                         685.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# now we apply it to the whole dataset\n",
    "complaints = complaints_per_company(df)\n",
    "complaints.set_index('Company Name', inplace=True)\n",
    "complaints.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "comfortable-testing",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 Companies with Most Complaints\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number of Complaints</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Company Name</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>EQUIFAX, INC.</th>\n",
       "      <td>131461.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRANSUNION INTERMEDIATE HOLDINGS, INC.</th>\n",
       "      <td>129492.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Experian Information Solutions Inc.</th>\n",
       "      <td>121215.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BANK OF AMERICA, NATIONAL ASSOCIATION</th>\n",
       "      <td>62194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WELLS FARGO &amp; COMPANY</th>\n",
       "      <td>51174.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPMORGAN CHASE &amp; CO.</th>\n",
       "      <td>44698.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CITIBANK, N.A.</th>\n",
       "      <td>34284.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAPITAL ONE FINANCIAL CORPORATION</th>\n",
       "      <td>26390.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ocwen Financial Corporation</th>\n",
       "      <td>18767.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SYNCHRONY FINANCIAL</th>\n",
       "      <td>15248.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        Number of Complaints\n",
       "Company Name                                                \n",
       "EQUIFAX, INC.                                       131461.0\n",
       "TRANSUNION INTERMEDIATE HOLDINGS, INC.              129492.0\n",
       "Experian Information Solutions Inc.                 121215.0\n",
       "BANK OF AMERICA, NATIONAL ASSOCIATION                62194.0\n",
       "WELLS FARGO & COMPANY                                51174.0\n",
       "JPMORGAN CHASE & CO.                                 44698.0\n",
       "CITIBANK, N.A.                                       34284.0\n",
       "CAPITAL ONE FINANCIAL CORPORATION                    26390.0\n",
       "Ocwen Financial Corporation                          18767.0\n",
       "SYNCHRONY FINANCIAL                                  15248.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's find top 10 companies with most complaints\n",
    "complaints.sort_values(by=['Number of Complaints'], inplace=True, ascending=False)\n",
    "print(\"Top 10 Companies with Most Complaints\")\n",
    "complaints.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "magnetic-glucose",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0cTzw1dLjM4BPStqmdIyPS3prqw2mcdGHAQdKWoniCvDSkg5M7Q0FTgHOi4h/1+17HUUBulk/MvRLRPwT+CVFcY2kIcDHgE0jYmREjAT2pPFwjeOB8gweFwHbSfpQbYGk9zcYijIeeH+p/S3xOOs++RdTHpy5++WWF5y5XVxYW9WWBc6XdL+k+4CNgeNa3TmNX55ZevwsRcF3cppu7wHg3cBL/elURDxDMZb4ixERwN7AxyQ9AjwMvAZ8vcnuxwNr9Od4C+EUoDY7yA7AUxHxVGn9TcDGklYr7xQR04B7So9fpZiV5dA0leD9wATgH7VtJI0E3gH8ubTfDOCl0huYYyU9WbtVE9HMzKy7qagxzMwWzrTRaw3KHyKjpszo9z49PT0AjBgxouruLLacOQ+5Zc4tLzhzxdRsha9Ym5mZmZlVwIW1mZmZmVkF8prQ0MxsAIYPH97pLrSdM+cht8y55QVnbhcX1mZmLZKaDqvrWs6ch9wy55YXnLldPBTEzKxFnq4qD87c/XLLC87cLi6szcxa5F9MeXDm7pdbXnDmdnFhbWZmZmZWARfWZmZmZmYVcGFtZmZmZlYBF9ZmZmZmZhXwdHtmZi3yPLB5cObul1tecOZ2cWFtZtYizwObB2fufrnlBWduFw8FMTNrkaeryoMzd7/c8oIzt4sLazOzFvkXUx6cufvllhecuV1cWJuZmZmZVcCFtZmZmZlZBVxYm5mZmZlVwLOCmNmArHf3Q4wYMaLT3TAzM+s4RUSn+2Bmg1hERC7TONV+XuaSF5w5F7llzi0vOHPFmjbowtrMBso/RMzMLCdNC2uPsTazAclp+iZPV5UHZ+5+ueUFZ24XF9ZmNiA5/aD2L6Y8OHP3yy0vOHO7uLA2MzMzM6uAC2szMzMzswq4sDYzMzMzq4DnsTazAXlkyw063YVFbtSUGZ3ugpmZDQIurM3MWpTjH8Jx5jzkljm3vODM7eKhIGZmZmZmFXBhbWbWotmzZzN79uxOd6OtnDkPuWXOLS84c7t4KIiZWYvmzp3b6S60nTPnIbfMueUFZ24XX7E2MzMzM6uAC2szMzMzswq4sDYzMzMzq4DHWJuZtUhSp7vQds6ch9wy55YXnLldXFibmbVo+PDhne5C2zlzHnLLnFtecOZ28VAQMzMzM7MKuLA2M2uR54HNgzN3v9zygjO3i4eCmJm1yPPA5sGZu19uecGZ28VXrM3MzMzMKuDC2szMzMysAi6szczMzMwq4DHWZmYt8jyweXDm7pdbXnDmdnFhbWbWIs8Dmwdn7n655QVnbhcPBcmMpDUk/VrSI5KmS/qBpBEd7tMcSZNKt5GSbmvj8c+RtHEf20yUNLbB8uGSTkznc6qkOyR9YNH1tnWSxkj6YOnxHpKO7mSfzMzMupkL64yo+EzkCuCqiFgPWB9YFji+ox2DVyNiTOn2eERs166DR8RnIuL+hdz9W8BqwCYRsQnwYWC5VneWNHQhj1vbv7dPncYA8wrriLg6Ik4cyPFy53lg8+DM3S+3vODM7eLCOi/vAV6LiJ8DRMQc4HDgU5KWljRU0smSpki6T9KhkraWdAWApD0lvSpphKQlJT2Wlq8j6XeS7pZ0s6QN0/LzJJ0u6TZJj0nap9WOSno5/btTulp8uaQHJV2Y3iAg6RuS7kxXis8uLZ8o6bvp6vHDkt6dli+Qr7T92HT/R5LukjRN0n/30celgc8Ch0bE6+mcPhsRv0zrx6djTZX03XI2Sd+U9BfgnZIeL/X3Dknrpu3WlHR96uv1kt5ROq+nSroR+G56jm6TdG/6d4P0KcQ3gXHpU4BxkiZIOqOFthfqOcvB3Llzs5sL1pnzkFvm3PKCM7eLC+u8jALuLi+IiJeAJ4B1gYOBtYDNI2JT4ELgHmDztPm7ganAVsA2wF/S8rMpisstgSOAs0qHWA3YHtgdaHa1dKnSMJArG6zfHDgM2BhYG3hXWn5GRGyVrhQvlY5RMywitk77/Vda1ihfvWMiYiywKbCjpE2b9BmKc/ZEOofzkfQ24LsUb2bGAFtJ2iutXgaYGhHbRMQtadlLqb9nAN+v5QMuKPX19NIh1gd2jYivAA8CO0TE5sA3gO9ERE+6f2n6FODSui721nYrz5mZmZnVcWGdFwHRy/JdgR9HxGyAiPhnuv+opI2ArYFTgR0oiuybJS0LbAdcJmkS8BOKwqzmqoiYm4ZavKVJv8pDQfZusP6OiHgyIuYCk4CRafnOkv4iaQpFATuqtM8V6d+7S9svkK/BsfaVdA9wb2qv17HXvdgKmBgRM9PxLqQ4bwBzgF/VbX9x6d93pvvvBC5K939BUezWXJY+cQBYgeL8TwVOY/7z0Exvbff5nEk6OF3Zv6uFY5mZmXWN8u/AdDu4ts6zguRlGvDR8gJJywNvB6bTvPC+GfgAMAv4I3AeMJTi6vQQ4IWIGNPkmK+XD7eQ/S63MQcYJmlJiivjYyPib5KOA5ZssM8c3nidN8tXrJTWosi0VUT8n6Tz6tqs9yjwDknLRcS/6pvrZb/XSkVxTTS532ybV0r3vwXcGBF7SxoJTOzl2M2U2+7zOYuIsyk+qWDa6LWanlMzM7NuU/4dWM9XrPNyPbC0pANh3hfnTgHOi4h/A9cBn699IU7SSmm/myiGVNweETOBNwMbAtPSMIgZkj6W9pGkzdqQpVbwPpeumrcyFrhZvprlKQrWFyW9heLNRFPpnJ0LnJ7GNCNpNUkfpxgms6OkldN5Hg/8qZfmxpX+vT3dvw3YL90/ALilfqdkBeCpdH9Cafm/aP5FylbbthJJ2c0F68x5yC1zbnnBmdvFhXVGIiKAvYGPSXoEeBh4Dfh62uQcivHW90maDOyflv+FYkjATenxfcB9qT0oCrNPp32mAXu2IcsLwE+BKcBVwJ0t7NYsX63NyRRDQKYBPwNubaHNY4GZwP1pKMZVwMyIeAb4GnAjMBm4JyJ+3Us7S6QvM36Z4gulAF8CDpJ0H/CJtK6R7wEnSLqV4pOEmhuBjWtfXqzbp9W2rWT48OHZzQXrzHnILXNuecGZ20Vv1EZm1gmSHqcY0vJcp/uyMHIYCjJqyoxOd8HMzBYfTS+D+4q1mVmLPA9sHpy5++WWF5y5XfzlRbMOi4iRne6DtSa3OWDBmXORW+bc8oIzt4uvWJuZmZmZVcCFtZmZmZlZBVxYm5mZmZlVwGOszcxalNscsODMucgtc255wZnbxYW1mVmLcpsDFpw5F7llzi0vOHO7eCiImZmZmVkFXFibmbVo1qxZzJo1q9PdaCtnzkNumXPLC87cLh4KYmbWohz/Uq0z5yG3zLnlBWduF1+xNjMzMzOrgAtrMzMzM7MKuLA2MzMzM6uAx1ibmbVoyJD8rkU4cx5yy5xbXnDmdnFhbWbWomHD8vuR6cx5yC1zbnnBmdslv7cvZmZmZmaLgAtrM7MWeR7YPDhz98stLzhzu+T3uYCZVWq9ux9ixIgRne5GW3ge2Dw4c/fLLS84c7v4irWZmZmZWQVcWJuZmZmZVcCFtZmZmZlZBTzG2swGJKe5UXPKWuPMecgtc255wZnbRTkOZjezSvmHiJmZ5UTNVuT39sXMzMzMbBFwYW1mA5LTvKieBzYPztz9cssLztwuHmNtZgPy8Bbrd7oLg9qoKTM63YVe5Thc0Jm7X255wZnbxVeszczMzMwq4MLazMzMzKwCLqzNzMzMzCrgMdZmZtaU577NQ26Zc8sLztwuLqzNzKypYcPy+zXhzN0vt7zgzO2S39sXMzMzM7NFwIW1mZk15blv85Bb5tzygjO3S36fC5iZWcs8920ecsucW15w5nbxFWszMzMzswq4sDYzMzMzq4ALazMzMzOzCniMtZmZNeW5b/OQW+bc8oIzt4sLazMza8pz3+Yht8y55QVnbpf83r6YmZmZmS0CLqzNzKypnp4eenp6Ot2NtnLm7pdbXnDmdnFhbWZmZmZWARfWZmZmZmYVcGFtZmZmZlYBF9a9kPRWSZdImi7pfknXSlq/tP5wSa9JWqG0bCdJL0q6V9IDkv6rtPwaSQdJmpRuPZKmpPsn9tHmNX30VZKOlfSIpIcl3ShpVGn945J+VXq8j6Tz0v0JkmaW+jVJ0sYNjjGnbpuR5b6lduZK2rS0z1RJI0uPN5cUkt5X13ZIOqX0+AhJx5UeH5jampaeiyPS8vMk7VPabhVJsyR9rq79xyWt3Mc53FrSTZIekvSgpHMkLZ3W7SXpvrR8iqS9SvudJ2lGOieTJe1SWjcxtTdZ0q2SNkjLR0j6fnptPSLp15LWaHCup0r6jaQ31fV1sqSL0/2mr6n0nJxR2u/glOFBSXdI2r6ur3eVHo+VNLG3c2ZmZmZvcGHdhCQBVwITI2KdiNgY+DrwltJm44E7gb3rdr85IjYHxgIfl7RlbUVE/DwixkTEGOBpYOf0+Og+2uzLF4HtgM0iYn3gBOBqSUuWthlbLrbrXFrrV7rd32CbV+u2ebzBNk8Cx/TSz/HALenfsteBjzQqfiV9ADgM2C0iRgFbAC82af9jwJ8btN8rSW8BLgOOiogNgI2A3wHLSdoMOBnYMyI2BPYATi6/gQCOTM/pYcCP65o/ICI2A84HTkrLvgMsB6wfEesBVwFXpNcdvHGuNwH+SfH81vq6EcX/3R0kLdPCa6q23+7A54DtU47PAxdJemtps1XT+TYDYOjQoQwdOrTT3WgrZ+5+ueUFZ24XF9bN7QzMioh5RVJETIqImwEkrQMsCxxLkyIuIl4B7gbWaeWArbTZi6OAQyPi3+nY1wG3AQeUtjmZ4s3BonQNMKp2ZbYsFY37ABOA3eqK/tnA2cDhDdr8GnBERDwNEBGvRcRPmxx/PPAVYA1Jq/ej318Ezo+I29MxIiIuj4hngSOA70TEjLRuBsUblyMbtHM70Oy4NwHrpqvgBwGHR8Sc1ObPKd5cvKeFNvcHfgFcR1Hkt+ooijcAz6Vj3kNR7H+xtM1JFK8/M8C/jHORW+bc8oIzt4sL6+Y2oSiKmxkPXAzcDGwgadX6DSS9GdgWmNbiMftssxFJywPLRMT0ulV3AeUr1L8EtpC0boNmxtUN81iqwTZLldZf2aQ7c4Hv0biAfxcwI/VzIvDBuvVnAgeoNAwm6eu5AEDS24G3RsQdFFnH9bVPi8cY1WBd/bmteT/F1edGPgxMAdYFnoiIl/pqU9JQYBfg6tLiccClFK+V/rwBayXH7cDrknbuR7vWxSKCiOh0N9rKmbtfbnnBmdvFhfXC2w+4JCLmAldQDEGoebekeymuKJ4YEa0W1r21uTAElF9RcyiuSH6twbb1Q0FebbBNeShIb0NVLgK2lbRW3fLxwCXp/iXUFYWp0LwA+FIvbfdmP4qCumH7A1B/HhstO0nSY8D/UAzzKLtQ0iSKNxZHNGmvvs2l0j7PAysBfwCQtBUwMyL+ClxP8UZpxYWL1TAHwLfp46p1Gqt9V3lMtnWnWbNmMWvWrE53o62cufvllhecuUrl34HpdnBtnQvr5qYBWzZakcbWrgf8QdLjFAVduYi7OSI2j4gty0NJetNCm02lgvQVSWvXrdoCqB8r/QtgB+AdrbS9MCJiNnAKxdADYN6V148C30j5fgh8QNJydbt/H/g0sExpWdPnos54YEJq/2pgM0nrtdjt3o4xjWK8fFn9uT2S4kr0sRTDK8oOSG9G9oqIvwGPAms2yF5u89U0ZnpNYARvDNcYD2yYMk4Hlqc4r624nwUzLvAaiYgbgCUpPm1pKCLOjoixEVF/XszMzLpa+Xdgup1dW+fCurkbgCUkfba2QNJWknakKG6Oi4iR6fY2YHVJaw7geANt8yTg9NoQDkm7AttTXD2eJyJmAadRfMluUToP2BVYJT3eFZgcEW9P+dYEfgXsVde/f1Jcdf50afEJwPdqX7KTtISk+a5qpzHdy0TE6rVzmPbbr8X+ngF8UtI2pTY/no55MvA1pdlN0r9fp3jzUO77XOAHwBDVzXpSt90rFMX3qekNB5IOBJameN2Vt32R4gr+EZKWoPgUY9NSxj1p/cr894DvpiFKSBpDMd79rAbbHg98tcV2zczMDBfWTUUxKGdv4L1pSrRpwHEUsy7sRzFjSNmVtF7ENdJXm7tIerJ0e2fdtj+kmE1kiqSHgP+kmMWi0ZCOc4Fhdcvqx1hvN4AsREQPcDpQGyc+ngXz/Yrii3j1TgHmzQ4SEddSjL/+Y3oe7m7Q/2btl4vO+0rn79S6/j5Lca5PVjE93gPAu4GXImISxdX330h6EPgN8NW0vD53UAyl6Kso/RrwGvCwpEcoCua9o8FgsIi4F5gM7As8FRFPlVbfBGwsabU+jkdEXA38DLgt5fgp8PGIeKbBttcCM/tq08zMzN6g3Aaym1m1po1eyz9EBmDUlBmd7kKvenp6ABgxYkSHe9I+ztz9cssLzlwxNVtRf9XPzMxsntym5wJnzkFuecGZ28WFtZmZNeVfxnnILXNuecGZ28VjrM3MrCnPfZuH3DLnlhecuV1cWJuZWVOe+zYPuWXOLS84c7u4sDYzMzMzq4ALazMzMzOzCriwNjMzMzOrgAtrMzMzM7MKeLo9MzNrylN05SG3zLnlBWduFxfWZmbWlH8Z5yG3zLnlBWduFw8FMTOzpjz3bR5yy5xbXnDmdnFhbWZmTXnu2zzkljm3vODM7eLC2szMzMysAi6szczMzMwq4MLazMzMzKwCLqzNzMzMzCrg6fbMzKwpT9GVh9wy55YXnLldlNvUK2ZWOf8QMTOznKjZCg8FMbMBmTt3bqe70DZz587NKi84cy5yy5xbXnDmdnFhbWYDMnv27E53oW1mz56dVV5w5lzkljm3vODM7eLC2szMzMysAi6szczMzMwq4MLazMzMzKwCLqzNzMzMzCrgeazNbECGDcvnx0hOWWucOQ+5Zc4tLzhzu3geazMbkGmj1/IPkcXYqCkzOt0FM7Nu43mszcys/zz3bR5yy5xbXnDmdnFhbWZmTXnu2zzkljm3vODM7eLC2szMzMysAi6szczMzMwq4MLazMzMzKwCLqzNzMzMzCqQ36SGZmbWMs99m4fcMueWF5y5bcds+xHNzGzQGDIkvw82nbn75ZYXnLltx2z7Ec3MbNDw3Ld5yC1zbnnBmdvFhbWZmTXluW/zkFvm3PKCM7eLC2szMzMzswq4sDYzMzMzq4ALazMzMzOzCriwNjMzMzOrgKfbMzOzpjz3bR5yy5xbXnDmth2z7Uc0M7NBw3Pf5iG3zLnlBWdu2zHbfkQzMxs0PPdtHnLLnFtecOZ2cWFt2ZP0VkmXSJou6X5J10paX9JISVMlvU/SpHR7WdJD6f4FknaSdE1qZ4KkmWndNEmXS1q67liTJV1ct+w8SU9JWiI9XlnS4+n+SElTS9t+VtI9klbsJc8ESXMlbVpaNlXSyCbbD5P0nKQT+n/2rNt57ts85JY5t7zgzO3iwtqyJknAlcDEiFgnIjYGvg68pbZNRPw+IsZExBjgLuCA9PjABk1emtaNAnqAcaVjbUTxf24HScvU7TcH+FQfff0EcCiwW0T8Xx/RngSO6WObmt2Ah4B90/kwMzOzheDC2nK3MzArIn5cWxARkyLi5oE0KmkYsAxQLoD3B34BXAfsUbfL94HD036N2tsXOJqiqH6uhS5cA4yStEEL244HfgA8AWzbwvZmZmbWgAtry90mwN0VtjdO0iTgKWAl4DfldcClwMUUxWzZE8AtwCcatLkmcAZFUf33FvsxF/gexdX3piQtBexCUYg36peZmZm1yIW1WbUuTUNG3gpMAY4EkLQVMDMi/gpcD2zRYJz0d9L29f8vZ1IU3vv2sy8XAdtKWquXbXYHboyIfwO/AvaWNLSvhiUdLOkuSXf1s09mZmaDWvl3YLodXFvnwtpyNw3YsupGIyIorlbvkBaNBzZMX0qcDiwPfLRun0eBSSxYQP8b+ADweUkH9KMPs4FTgKN62Ww8sGvq193AmymGx/TV9tkRMTYixrbaHxuchg0blt38t87c/XLLC85cpfLvwHQ7u7bOhbXl7gZgCUmfrS2QtJWkHStoe3tguqQhwMeATSNiZESMBPak8bCL44Ej6hdGxEzg/cB3JL0v9fMQSYf00YfzgF2BVepXSFo+9fEdpX59sUm/LFNDhgzJbv5bZ+5+ueUFZ27bMdt6NLPFTLqyvDfw3jTd3jTgOODphWxyXJpu7z5gc+BbFFetn4qIp0rb3QRsLGm1uv5MA+5p0tcZFF96/JmkbYANged760xE9ACnA6vWlkk6R9JY4CPADRHxemmXXwN7SFqitJ1lbM6cOcyZM6fT3WgrZ+5+ueUFZ24XFXWFmQ02af7sj6TiuWOmjV7LP0QWY6OmzBjQ/j09xctrxIgRVXRnUHDm7pdbXnDmijWdmjavwTZmXSQidu90H8zMzOwNHgpiZmZmZlYBF9ZmZmZmZhVwYW1mZmZmVgGPsTYzs6aGDx/e6S60nTN3v9zygjO3iwtrMzNrSmr65feu5czdL7e84Mzt4qEgZmbWlOe+zUNumXPLC87cLi6szcysKf8yzkNumXPLC87cLi6szczMzMwq4MLazMzMzKwCLqzNzMzMzCrgwtrMzMzMrAKebs/MzJry3Ld5yC1zbnnBmdvFhbWZmTXluW/zkFvm3PKCM7eLh4KYmVlTnqIrD7llzi0vOHO7uLA2M7Om/Ms4D7llzi0vOHO7uLA2MzMzM6uAC2szMzMzswr4y4tmNiDr3f0QI0aM6HQ32qKnpwcgm7xmZtY/vmJtZmZmZlYBRUSn+2Bmg1hERC7TONV+XuaSF5w5F7llzi0vOHPFmjbowtrMBso/RMzMLCdNC2sPBTGzAclp+iZPV5UHZ+5+ueUFZ24XF9ZmNiA5/aD2L6Y8OHP3yy0vOHO7uLA2MzMzM6uAp9szswF5ZMsNOt0FW0yNmjKj010wM2srX7E2MzMzM6uAC2szMzMzswp4KIiZmVlJjn9ZM7fMueUFZ24XX7E2MzMzM6uAC2szM7OS2bNnM3v27E53o61yy5xbXnDmdvFQEDMzs5K5c+d2ugttl1vm3PKCM7eLr1ibmZmZmVXAhbWZmZmZWQVcWJuZmZmZVcBjrM3MzEokdboLbZdb5tzygjO3iwtrMzOzkuHDh3e6C22XW+bc8oIzt4uHgpiZmZmZVcCFtZmZWYnn++1+ueUFZ26XlgtrSdtJ+oQKO0j6g6RfSnrHouygmZlZO82dOze7OX9zy5xbXnDmdunPGOuTgeUi4heS/gdYAwhgCWDPRdE5MzMzM7PBoj9DQTYA7pG0FkVR/WXgVuBdi6JjZmZmZmaDSX8K66WA14GNKa5U/xKYAiyzCPplZmZmZjao9GcoyAxgPPB+4OmIeFbS24BnF0nPzMzMOsDz/Xa/3PKCM7dLf65YH08xnvptwH9LGgHsDPxlUXTMBgdJL0saKelVSZMk3S/px5KGpOUh6Vul7VeWNEvSGaVlB0t6MN3ukLR9ad1ESQ9JmizpTkljSuuWlfQjSdMl3Svpbkmfrevf4ZJek7RCadlOqV8fLi27RtJOTTIekfo2NfXjwFLfxpa2Gylpat2+P5D0lKQhpWVvScebnM7XtaX9a+exdjuwQX8k6ey07xRJ72zy9CBpuKQTJT2S+n+HpA+kdStIuiCdv+np/grN2jLLxfDhw7Ob8ze3zLnlBWdul5YL64i4CFgeWCEizomInoh4U0SMW3Tds0FkekSMATalGC60V1r+GLB7abuPAdNqDyTtDnwO2D4iNgQ+D1wk6a2lfQ6IiM2As4CTSsvPAf4PWC8iNqf4NGWlun6NB+4E9q5b/iRwTF+hJH0eeC+wdURsAuwAtPQWOBXTewN/S/vVfBP4Q0RsFhEbA0eX1k2PiDGl2wUNmt4eWA8YBWxDcY6b+RawGrBJ6v+HgeXSunOBxyJinYhYh+JTqXNayWZmZmYL6u881m8HjpF0qaRVJR0oaf1F0TEbnCJiNnAbsG5a9CrwQOnK7jiK8fk1RwFHRsRzaf97gPOBLzZo/nZgdQBJ6wBbA8dGxNy078yI+G5t47TNssCxFAV22WTgRUnv7SPS14EvRMRL6RgvRsT5fexTszMwFfhR3fFXoyjsSW3e12J7NT3AW4DhEfHviGg4HEvS0sBngUMj4vV0rGcj4peS1gW2pCi8a74JjE3nzSxbnu+3++WWF5y5Xfozj/X2wCSKq2v7AC8B36coWsyAecXcLhRfbK25BNhP0hrAHODp0rpRwN11zdyVltd7P3BVab/JtaK6ifHAxcDNwAaSVq1b/216ef1KWo5iisnpvRzjwtqwDeDaJse/EthdUu3zqDOBcyXdKOmY9F2FmnXqhoK8u8Exn6X49Og89T6AbF3gidqbgjobA5MiYk5tQbo/icbn3iwbnu+3++WWF5y5XfpzxfpEiqLoXoCIeA24CWj0i9/ys04qLm8FfhsR/1ta9zuK4RTjgUtbaEsUM8/UXCjpSYqr2z9suENRoE6SVC7a9wMuScX3FRTDUOaJiJvTvs1ew/X9aOSA2rAN4IOl/oxIj69Khe1fgN3ScX8PrA38FNgQuFfSKmnX+qEgNzc45uUUb17+DZyWjneWpA/10ddWsrWSuTYu/i5Jd/XjmGZmZoNe+Xdguh1cW9efwnpT4NcUxXTNMxQfSZvVCsLNI+K48oqI6KG4Kv0V4Fd1+91PMSShbIu0vOYAYC3gIoqrvbX9Nqt9KTAijk/F7fIAkjalGIf8B0mPUxTZ9cNBoPhSbsOx1qkgfkXS2o0j9+r9wArAlHT87cvHj4h/RsRFEfEJijHgOzRspU666r5yRDxEMTZ9pKT/AsYCE+s2fxR4R7ryXm8asHndlyqHAJsBD/TVj4g4OyLGRsTYvrY1MzPrJuXfgel2dm1dfwrr5ynGWAPFbAPAdsDfq+uqdbFTgKMi4vm65d8DvivpzQBp1o8JFF9UnCciZlEM29hW0kYR8SjFkJFvSxqa9l2SN75YOB44LiJGptvbgNUlrVnX7nXAihQFZSMnAGdKqhXsy5ffmfZiPPCZ2vEp3hjsJmlpSe9JQ2Zqw03WAZ5ooU2AmcVu2jkN3TiY4o813RMRr9Rl+zfFFxRPT1fQkbSapI+n83cv8w+FOTa182iLfTEzM7OS/hTW11FcVTsoPX4M2AT436Z7WFeTNIzijwb1KSKmNfrSX0RcDfwMuE3SgxTDIz4eEc802PZVigL9iLToM8CbgUcl3Q38kWK4CBRXqK+sa+LKtLze8RR/TbSRHwE3AnemqfT+RDEEo6lUNL8P+G2p768At1DMyrElcJek+yi+kHlORNyZNq0fY/2lctsREcBHgePT0JurgEMo3nDs06A7x1IU4/en/l+VHgN8Glhf0qOSpgPrp2VI2kPSN3vLadatJGU3529umXPLC87ctmMWv6db2FBaCbia4ip1ze3AHg2uQloGJG0G/DQitu50X6xzpo1eq7UfIpadUVNmdLoLZmaLQtNqveW/vBgR/0xf8toSGAk8DtwdrVbm1lXS/M5fAg7rcFfMzMzMFgu9XrGW9A7gpYh4Id1vKCJaHR9qZl3GV6ytmcF6xbo27+2wYS1fexr0csucW15w5oot9BXrGRRzVX+F4gp1o1+g0UI7ZmZmg0Juc/1CfplzywvO3C59FcRi/qq8UYWe10h4MzMzM7MGei2sI2JIo/tmZmZmZjY/F8tmZmZmZhVoubCWtKmkP0l6SdKc0m32ouygmZlZO3m+3+6XW15w5nbpz5cOfwGMbrA8r2fJzMy62vDhwzvdhbbLLXNuecGZ26U/hfW6wDTgUOAFGs8QYmZmZmaWpf4U1tcDsyJi4iLqi5mZWcfNmjULyOsKX26Zc8sLztwu/SmsnwIOlnQ1MAmYN7Y6Ir5Zcb/MzMw6Isc/KJxb5tzygjO3S38K68+lf3cHPpTui2JIiAtrMzMzM8tafwrrC/C4ajMzMzOzhlourCNiwiLsh5mZmZnZoNafK9ZIegewHbAKb0yzFxHxw6o7ZmZm1glDhuT3t9Nyy5xbXnDmdmm5sJb0UYq5rJdosNqFtZmZdYVhw/p1zakr5JY5t7zgzO3Sn1L+P4HhwLMUV6sfoJgZ5E+LoF9mZmZmZoOKWp2KRNJrwFXA08CXI2KopD8Ad0XE1xZdF81scTZr1qzIZV5UzwObB2fufrnlBWeuWNO/Ot6fK9azgZnAywCS1gL+DXx+QF0zs0Etp7lRIyKrvODMucgtc255wZnbpT+DT54GVgPuoKjUHwKGUgwNMTMzMzPLWn+uWP8E+DvwK2AaRVHuPw5jZmZmZkb/5rE+pXZf0hbAxsBzEfHUouiYmZmZmdlg0t95rDcBPgGsATwJ/A/gwtosYznNjZpT1hpnzkNumXPLC87cLv2ZFWR/ij9rrnSLdDswIi5aZD00s8VdXt+GMTOz3DWdFaQ/hfV0YC2KKfceBDYE9gJmRMQ6A+6imQ1WLqzNzCwnTQvr/gwFWRm4PCL2ndeqdBmw6wA6ZmaD3LTRa3W6C5aJUVNmtOU4nu+3++WWF5y5Xfoz+OQ8YHVJQwAkDQXeBvx0EfTLzMysIzzfb/fLLS84c7v054r15sA2wFNpWMg6FFexZ0m6IW0TEbFLxX00MzMzM1vs9aew3j79+5Z0q9mhdD+vt0JmZmZmZkl/CuuDFlkvzMzMzMwGuf78gZjzF2VHzMzMFgee77f75ZYXnLldWi6sJQ2n+OMwmwPLlFZFRHy66o6ZmZl1wrBh/frbaV0ht8y55QVnbtsx+7Ht+cA4Fpy7LwAX1mZmZmaWtf4U1rsDz1P89cV/LZrumJmZdZbn++1+ueUFZ26X/hTWjwD3R8QRi6ozZmZmnZbbXL+QX+bc8oIzt0t/CuuPA7dIuhh4GJiTlkdEfKvynpmZmZmZDSL9KawPBlYE9i0tE8UYaxfWZmZmZpa1/hTWnwFmAbcBLyyS3piZmZmZDVL9Kaz/CtwZEf5DMWZm1rU832/3yy0vOHO79Kewvhw4XNLDwIO8McaaiLi66o6ZmZl1guf77X655QVnbtsx+7HtNyjGU3+7bnn0sx0zMzMzs67Tn4L4CYoi2szMrGv19PQAMGLEiA73pH1yy5xbXnDmdmm5sI6IkYuwH2ZmZmZmg1q/RnVLWkHSZyR9S9KnJb1pEfXLOkTSaZIOKz3+vaRzSo9PkfT/JI2U9KqkSaXbgWmbxyWtXNfuBElnNDjepyRNkXSfpKmS9mywzXGSniod58S0fJik5ySdULf9REkPSZos6U5JY0rrlpX0I0nTJd0r6W5Jny2tHyXpBkkPS3pE0n9KUpNztW06xhRJ5/dxXreWdFPq14OSzpG0dFq3V8r/YGprr9J+50n6t6TlSst+IClq51jSnHRepkq6rNRub+fnrtLjsWnZqpJmSHprad1Zko7uLZuZmZkVWi6sJa0P3A/8BPg6cDYwTdIGi6hv1hm3AdsBSBoCrAyMKq3fDrg13Z8eEWNKtwv6cyBJawDHANtHxKbAtsB9TTY/rXScWqG3G/AQsG+D4veAiNgMOAs4qbT8HOD/gPUiYnPg/cBKqT9LAVcDJ0bE+sBmKe8XmvTpeOCwiBgNHNdLzrcAlwFHRcQGwEbA74DlJG0GnAzsGREbAnsAJ0vatNTEo8Ceqa0hwM7AU6X1r6bzsgnQA3y+hfOzqqQPlBdExD+A76b+IGkLYHvglGbZzMzM7A39uWJ9MrAaMBm4FJiUHn+v+m5ZB91KKqwpCuqpwL8krShpCYqi8N6KjrUq8C/gZYCIeDkiZvRj//HADyjG/2/bZJvbgdUBJK0DbA0cGxFz0zFnRsR307b7A7dGxHVp3b+BQ4BmV2x7gDXStr31+4vA+RFxe9o2IuLyiHgWOAL4Tm3/9O8JwJGl/S8GxqX7O1E8R7ObHOtmYN10v7fzcxJwbIP9zwbWkbQzcAZwSETM6iWbmZmZJf0prLcFrouILSJi/4jYEvg98M5F0zXrhIh4Gpgt6R0UBfbtwF8onuexwH0R0ZM2X6duKMi7+3m4ycCzwAxJP5f04V62Pbx0nPelq8u7ANdQFJ7jm+z3fuCqdH8UMLlWVDcwCri7vCAipgPLSlq+wfbTgRMkje2l3wCb1Lfb2zGBu5j/U4JHgFUkrUiR85JGDUkaBnwAmNLC+bkdeD0V0POkc/MfwK+AhyPipt6jmXWfoUOHMnTo0E53o61yy5xbXnDmdulPYS2KK3RlPWm5dZfaVetaYX176fFtpe3qh4Lc3J+DRMQcisJ3H+Bh4DRJxzXZvDwU5PfA7sCN6aryr4C9JZX/91wo6UngKOCHjRqUdEwq1J+uLaL5zDfzLU9jwVegKGQvkrSepFUk3dlH7AW60eCYjZZdAewHbENxVbpsKUmTKAryJ4Bz6fv8QDF15gJXrSNiEsUnFWc17bR0sKS7ymO1zbqFC5Dul1tecOYqlX8HptvBtXX9KazvBj4k6XpJZ0j6I8Uvb/9i7T61cdajKQqsP1NcsS6Pr65EGhZxR0ScQFE4frTFXccDu0p6nOK1+WaKscc1BwBrARcBZ6Zl9wObpXHKRMTxETEGqF2NnkZxVX4eSWsDL0fEv+qO/z7g+oiYAnwa+DXFsJFLG/R1GrBlkxwLHBPYIvW17BLgW8AfGlxxf7X0puPQ9IlCX+eHiLgBWJLGw2jmpltDEXF2RIyNiL6u1psNOhFBRF6zy+aWObe84MwVtzvvd2C6nV1b15/C+qvASxS/nP8DeE967BkDus+tFG+a/hkRcyLin8CbKIrr26s6iKS3pS/I1YwB/trCfstTfKnuHRExMk0F+UXqhjukscHHAttK2igiHqV4I/jt2tVbSUvyxqcuFwLbS9o1rVsKOJ3G3yO4Fxgnacl0pf5Kii9iXtxg2zOAT0rappTh42n2jZOBr0kamZaPpPhy8HxfGIyIJ1L7Ta8i9/f8JMdT/N82s2TWrFnMmpXXVwtyy5xbXnDmdulzHus0bnNpiitoGwGfAEZSFEAXAM8twv5ZZ0yhmA3korply0ZE+fleJw1BqPlZRJye7t8nqXbF85cUs31MKE8lB7yLYgaMtwGvATN5Y0aL3nwEuCEiXi8t+zXwvfQFy3ki4lVJp1B8SfDTwGcovrj3qKR/Aq9SDBepbbsn8ENJZwJDgV9QFMb1zgXWAyZJejnlOwK4XNIuaQhGrQ/PStovZV2V4krwTcAVEfF3SUcBv5E0HJgFfDUNx5hPRPykhXPT3/NzraSZLbZrZmZmvVBfl8glnQ58DtiwPPNB+nLbQ8DZEfHlRdpLM1tsTRu9Vl6fLVrHjJrSn0mDFp7/Ql33yy0vOHPFmn6/sJWhIB8EJtZPJ5Y+mr4+rTczMzMzy1orhfXqwONN1j1FmsfXzMzMzCxnfY6xBl4BtqpfmP6S29ZpvZmZWVfIbUoyyC9zbnnBmdullSvWt1NMUXZemqt3hKT1gPOATalwlggzM7NO83y/3S+3vODM7dLKFesTKf6IxyfSrWwu8N0F9jAzMxukal/qLz6YzUNumXPLC87cLn1esY6IWykK6v+j+BZk7fYC8MmIuGVRdtDMzKydPN9v98stLzhzu7RyxZqIuETSrynmHV4V+AdwW3muXjMzMzOznLVUWEPxxzOAPy7CvpiZmZmZDVr9+ZPmZmZmZmbWhAtrMzMzM7MKtDwUxMzMLAe5TUkG+WXOLS84c7u4sDYzMytxAdL9cssLztwuHgpiZmZWEhHz5r/NRW6Zc8sLztwuLqzNzMxKPN9v98stLzhzu7iwNjMzMzOrgAtrMzMzM7MKuLA2MzMzM6uAC2szMzMzswoot2+Imlm15syZE7lM4zRnzhwgr2mrnDkPuWXOLS84c8XUdIULazMbIP8QMTOznDQtrD0UxMwGZO7cuZ3uQtvMnTs3q7zgzLnILXNuecGZ28WFtZkNyOzZszvdhbaZPXt2VnnBmXORW+bc8oIzt4sLazMzMzOzCriwNjMzMzOrgAtrMzMzM7MKDOt0B8xscHtkyw063QWzthk1ZUanu2BmizEX1mZmZpkbNiyvciC3vODMbTtm249oZmZmi5UhQ/IaGZpbXnDmth2z7Uc0MzOzxUpucxznlhecuV1cWJuZmWUutzmOc8sLztwuLqzNzMzMzCrgwtrMzMzMrAIurM3MzMzMKuDC2szMzMysAp5uz8zMLHO5zXGcW15w5rYds+1HNDMzs8VKbnMc55YXnLltx2z7Ec3MzGyxktscx7nlBWduFxfWZmZmmcttjuPc8oIzt4sLazMzMzOzCriwNjMzMzOrgAtrMzMzM7MKuLA2MzMzM6uAp9szMzPLXG5zHOeWF5y5bcds+xHNzMxssZLbHMe55QVnbtsx237ECkmaI2mSpMmS7pG0Xd36wyW9JmmF0rKdJIWkD5eWXSNpp3R/oqSx6f5ISY9Iel+DY4+SdIOkh9M2/ylJad0ESTNT3yZJuqCXDJMlXVy37DxJ/5a0XGnZD1K/V67LXrsdXer/Q6ndOyWNKbXxeGn/t0q6RNJ0SfdLulbS+r2du96kvp1SenyEpOOaZZV0UKnvPZKmpPsnpvN3Rmm/gyU9mG53SNq+tG6ipLtKj8dKmlh33B9IekrSkNKy+Y7RS65VJM2S9Lm65Z9Kfb5P0lRJe6bl20r6S8ryQPkcSNorbf9g2nevujaPSOumpnN1YCnj2NJ2m6fz/b70+Mp0vEclvVg6r9vVvZ5XkHRBes6np/srpHUjU5uHlo5zhqQJfZ0jMxv8cpvjOLe84MztMqgLa+DViBgTEZsBXwNOqFs/HrgT2Ltu+ZPAMb01LGkN4PfAVyLi93XrlgKuBk6MiPWBzYDtgC+UNrs09W1MRBzY5BgbUTwHO0hapm71o0CtWBsC7Aw8VVr/aqn9MRFxYmndAemcnAWc1OC4Aq4EJkbEOhGxMfB14C2lzZqdu2ZeBz5SK9z7yhoRP6/1HXga2Dk9Prpuv92BzwHbR8SGwOeBiyS9tbTZqpI+0OS4Q1KGvwE7tJil7GPAnynOR63NNSheP9tHxKbAtsB9afX5wMEp1ybAL9M+mwEnA3umHHsAJ0vaNK3/PPBeYOuI2CT1VU36NB64pdaniNg7He8zwM2l18RtdfudCzyWnvN1gBnAOaX1/wC+LGlEP86PmXWB3OY4zi0vOHO7DPbCumx54P9qDyStAywLHEupKEomAy9Kem+Ttt4KXAccGxFXN1i/P3BrRFwHEBH/Bg4Bjm6wbW/2B36RjrVH3bqLgXHp/k7ArUB/Xx23A6s3WL4zMCsiflxbEBGTIuJm6PPcNTMbOBs4vMn63rL25ijgyIh4LvXzHori9YulbU5KfW1kZ2Aq8CNaz1I2HvgKsIak2rlcFfgX8HLq08sRMaO07pm0fE5E3J+WHwF8p7Zd+vcE4Mi0/uvAFyLipbT+xYg4v74z6U3RPsAEYDdJS7YSQtK6wJbAt0qLvwmMTc83wEzgeuCTrbRpZmZm8xvshfVS6SPvBymuvJWLhvEUxenNwAaSVq3b99s0L8YuAM6IiMuarB8F3F1eEBHTgWUlLZ8WjSt9JH9Qk3bGAZemftYXfY8Aq0haMa27pG79Upp/KMg4FvR+4KoGyzep73+dvs5dM2cCBzQZPtJb1t4scK6Bu9LymtuB1yXt3GD/WpYrgd0lDW/1wJLeDrw1Iu6guPJcO8eTgWeBGZJ+rtKwIuA04KE0PONzpcK3aQ4VQ36WS6+hvrwLmJG2nQh8sMU4GwOTImJObUG6P4n5z+WJwFckDW2xXTMzM0sGe2FdGw6xIUUReUG6ogewH3BJRMwFrqD4SH+e0tXZdzdo94/AJyQt3eS4AqLJutry8lCQny/QgLQVMDMi/kpxlXCLVESXXZFybENR5JbVDwW5tLTuQklPUlzt/WGTfvam13PXTLraegHwpfLyFrP2R6Pzv8AbpTSk4YPAValvfwF268dx9iMN5aB4Y1MbejGH4vW2D/AwcFptLHVEfBMYS3Flfn/gd730ubast9dTvfKbrHl9akGzY8y3PF1Jv4Oi780bK8a931Ue325mZpaD8u/AdDu4tm6wF9bzRMTtwMoUV3k3BdYD/iDpcYoCqVEBcjyNx1p/j6IIu0xSo5lTplEUT/NIWht4OSL+1WKXxwMbpv5NpxjK8tG6bS6huAr/h1TktuoAYC3gIoqryPWmUQwLWEA/zl0z3wc+DZTHjLeStZn7G/R1i7R8noi4AViSYrxzzfuBFYAp6djb078s44EJad+rgc0krZeOFxFxR0ScQHGO5uWJiOkR8SNgl7TPm2nwmqnlSEX/K+k11FS6ivxR4BupTz8EPqDSl1x7MQ3YXPN/gXMIxfcDHqjb9jsUb8qa/nyIiLMjYmxE1GcyMzPrauXfgel2dm1d1xTWkjYEhgLPUxREx0XEyHR7G7C6pDXL+6Qx0itSFBf1DgdeAs4tXQWvuRDYXtKu6dhLAadTFOSt9HUIxVXgTWt9pPii4nxFX0Q8QVH4n9VKu3X7zqK4grtt+uJg2Q3AEpI+W+rTVpJ2pJdzJ2l1Sdf3cdx/Ulzl/XR/svbie8B3U3GKillOJtD4nBwPfLX0eDzwmdJx16IYl9zsk4h5JG0ALBMRq5f2PwHYT9LbJG1R2nwM8Ne034dKr5f1gDnACxRfXPyapJFpu5EU46prM6mcAJxZG0okafnyO+BkV2ByRLw99WlN4FfAXn3liYhHgXuZ/6r+scA9aV152wcp3rjs3le7ZtYdhg0bltU8x7nlBWdul8FeWM8bZ0wxfveT6WP6/SjG1JZdmZbXOx5Yo35hRATFl7hWo65gjohXKYrDYyU9BEyhmEGjz+nbkh2ApyKiPMvHTcDGklarO9ZPmoy9rR9jfWL9Bqmfp1B8ca4+297Ae1VMuzYNOI5ido7ezt1qtPYFylMoPj3oV9ZG0pdHfwbclsbS/xT4eEQ802Dbaym+gEcqnt8H/La0/hWK2TRqY6InSHqydCu/Dsaz4Hn4VVo+nGJGjwfTa28c8OW0zScoxlhPoviy5gHpS4yTKK4C/ybl+A3w1bQcii9X3gjcKWkq8Cfg33XHb9anXodtlHwaWF/FtHzTgfXTskYa/r8ws+40ZMiQrOY5zi0vOHO7qKixzPom6RDgiSYzpVimpo1eyz9ELBujpszoe6NBaM6c4nvNQ4fm8b3l3PKCM1es2XS4/suL1rqIaPWKvJmZDSK5FV255QVnbpe8PhMwMzMzM1tEXFibmZmZmVXAhbWZmZmZWQVcWJuZmZmZVcBfXjQzM8vc8OHDO92FtsotLzhzu7iwNjMzy9yCfwetu+WWF5y5XTwUxMzMLHNz5syZNzVZDnLLC87cLi6szczMMpdb0ZVbXnDmdnFhbWZmZmZWARfWZmZmZmYVcGFtZmZmZlYBF9ZmZmZmZhXwdHtmZmaZy22O49zygjO3iwtrMzOzzOU2x3FuecGZ28VDQczMzDKX21RsueUFZ24XF9ZmZmaZy63oyi0vOHO7eCiImQ3Ienc/xIgRIzrdjbbo6ekByCYvOLOZWX/4irWZmZmZWQVcWJuZmZmZVcCFtZmZmZlZBRQRne6DmQ1iERG5TONU+3mZS15w5lzkljm3vODMFWvaoAtrMxso/xAxM7OcNC2sPRTEzAYkp+mbPF1VHpy5++WWF5y5XVxYm9mA5PSD2r+Y8uDM3S+3vODM7eJ5rM1sQB7ZcoNOd8HMzBbCqCkzOt2FruMr1mZmZmZmFXBhbWZmZmZWARfWZmZmZmYV8BhrMzMzM+s6I0aMaPsxfcXazMzMzKwCLqzNzMzMrOvMnj2b2bNnt/WYHgpiZmZmZl1n7ty5bT+mr1ibmZmZmVXAhbWZmZmZWQVcWJuZmZmZVcBjrM3MzMys60hq+zFdWJuZmZlZ1xk+fHjbj+mhIGZmZmZmFXBhbWZmZmZdx/NYm5mZmZlVwPNYm5mZmZkNUi6szczMzMwq4MK6zSTNkTSpdDt6ER9vj6qOIelxSSv3sc2GKde9ktap4rgt9GuMpA+WHleZ+RhJ0yTdl3Jt08f2EyWN7WObvSRtXHr8TUm7VtHfJsd7eVG1bWZmZm/wGOv2ezUixrTjQJKGRcTVwNXtOF6yF/DriPivVjZWMcmkImIgA6HGAGOBawGqyizpncDuwBYR8Xp6UzFioO1SnKNrgPsBIuIbFbRpZmZmJZ2Yx9pXrBcDklaQ9JCkDdLjiyV9Nt1/WdIpku6RdL2kVdLydST9TtLdkm6WtGFafp6kUyXdCHxX0gRJZ6R1H5b0l3Q1+Y+S3pKWHyfpZ+lq62OSvtRHf0dKekDST9PV3OskLZWuGh8GfCYdH0n/T9LUdDusbv+zgHuAd0t6UNI5absLJe0q6VZJj0jaOu23taTbUv9vk7SBpBHAN4Fx6YryuLrMa6bzdl/69x2l83R6aucxSfs0iLoa8FxEvA4QEc9FxNNp/11SP6akc7dEg/P0cun+PumY2wF7ACel/q6Tlu/TW7vp04L/Tq+DKaXne0e98enHvZKW6+V52yk9x5en831hemODpK3SuZgs6Y7e2jEzMxsMhg8f3va5rF1Yt99Smn8oyLiIeBE4BDhP0n7AihHx07T9MsA9EbEF8CegdiX4bODQiNgSOAI4q3SM9YFdI+Irdce+Bdg2IjYHLgG+Wlq3IfA+YGvgvyT19UpcDzgzIkYBLwAfjYhrgR8Dp0XEzpK2BA4CtgG2BT4rafO0/wbABakvfwXWBX4AbJr6sj+wfcr29bTPg8AOaZ9vAN+JiJ50/9KIGBMRl9b184x0nE2BC4HTS+tWS8fYHTixQcbrgLdLeljSWZJ2BJC0JHAeMC4iRlN88vMffZwvACLiNoqr6Uem/k6vrWuh3efS6+BH6byQ/v1i+hTk3cCrfXRhc4o3PxsDawPvSm9OLgW+HBGbAbu20I6ZmZnVcWHdfq+mgmpMuRCMiD8AU4Azgc+Utp9LUfQA/A+wvaRlge2AyyRNAn5CUSTWXBYRcxocew3g95KmAEcCo0rrfhsRr0fEc8A/gLf0kWNGRExK9+8GRjbYZnvgyoh4JSJeBq6gKP4A/hoRf65rb0oaEjINuD4iguKc1NpeIWWeCpxW1/9m3glclO7/IvWp5qqImBsR99Mgb+rzlsDBwEzgUkkTKN4UzIiIh9Om5wM7tNCXvvTV7hXp3/L5vhU4NX3K8KaI6GvCzjsi4sl0nieldjYAnomIOwEi4qW+2pF0sKS7JN3VUjIzM7M2W1TzWJd/B6bbwbV1LqwXE5KGABtRXClcqZdNg+J5e6GuQN+otM0rTfb9IXBGuhr6OWDJ0rrXS/fn0Pf4+1a2721wU30fy+3NLT2eW2r7W8CNEbEJ8GHm73+roskxG/Y1IuZExMQ0ZvwQ4KPNtu3jWK30ta92a/2dd74j4kSKN2JLAX+uDRFpoY1yO6rra58i4uyIGBsRvX5R08zMrFPmzp27SOayLv8OTLeza+tcWC8+DgceAMYDPysNxRgC1Mb/7g/cEhEvATMkfQyKLwBK2qyFY6wAPJXuf7Kynjd3E7CXpKUlLQPsDdw8gPbK/Z9QWv4voNmY4NuA/dL9AyiGw7QkjeFer7RoDMWwlQeBkZLWTcs/QTFMp96zkjZKb5r2bqG/rbZb7uM66Ur/d4G7KIbR9NeDwNskbZXaXE6Sv9hsZmbWTy6s269+jPWJktanuOr4lYi4maIgPTZt/wowStLdwHsovqgHRZH4aUmTKYZO7NnCsY+jGEpxM/BcdZEai4h7KMYM3wH8BTgnIu4dQJPfA06QdCswtLT8RmDj2pj1un2+BBwk6T6KQvXL/TjessD5ku5P+28MHBcRr1GMHb8sDauZSzG2vN7RFLN/3AA8U1p+CXCk6qYk7Ee7ZYep+MLnZIpPO/63H/lqx+0BxgE/TO38AVhS0tskXdvf9szMzHKlYhirLa4kvRwRy3a6H2bNTBu9ln+ImJkNQqOmzOh0Fxapnp4eAEaMqGKm3Pk0Hbrpj3vNzMzMrOuoA/NYu7BezPlqtZmZmVn/tXsOa/AYazMzMzOzSriwNjMzM7Ous6jmse6Nh4KYmZmZWddZFHNY98VXrM3MzMzMKuDC2szMzMysAi6szczMzMwq4DHWZmZmZtZ1PI+1mZmZmVkFPI+1mZmZmdkg5cLazMzMzLrOrFmzmDVrVluP6aEgZmZmZtZ1IqLtx/QVazMzMzOzCriwNjMzMzOrgAtrMzMzM7MKeIy1mZmZmXWdIUPaf/3YhbWZmZmZdZ1hw9pf5qoT35g0s67iHyJmZpaTpn/S0WOszWxA2j1HaCd1Yk7UTnPmPOSWObe84Mzt4qEgZjYgOX3qlVPWGmfOQ26Zc8sLztwuvmJtZmZmZlYBF9ZmZmZmZhVwYW1mZmZmVgGPsTazAenEPKGdklPWGmfOQ26Zc8sLztwunm7PzAbKP0TMzCwnTafb8xVrMxuQaaPX6nQXzMxsMTVqyoxOd6Gt8vtcwMzMzMy6nuexNjMzMzOrgOexNjMzMzMbpFxYm5mZmZlVwIW1mZmZmVkFPMbazMzMzLpOJ+axdmFtZmZmZl1n2LD2l7keCmJmZmZmVgEX1mZmZmbWdTyPtZmZmZlZBTyPtZmZmZnZIOXC2szMzMysAi6szczMzMwq4DHWZmZmZtZ1PI+1mZmZmVkFPI+1mZmZmdkg5cLazMzMzLpOT08PPT09bT3mYl9YS3qzpEnp9ndJT5UeR/p3qqTfSHpT3b6TJV1ct+y81MYS6fHKkh5P94dIOj21N0XSnZLWSutermtngqQz0v3jJP1b0qql9S83uT9K0g2SHpb0iKT/lKRSm3MlbVrafqqkkQ3Oy0RJY9P9xyX9qrRun5TzoNK56kmZJkk6MR1rZmn9JEkbSxop6dX0+H5JF0gantrdKZ3zT5eOtXladkTp/M4otXlbKdtMSfem3L+XtF3d87JP6fEqkmZJ+lx6fGapT6+W2t+n2THrztdOkq5p8FrYJ90fIen7kqan/v1a0hqNnsPSsuNKr8dHJF0haeP+PEelx++XdIekB1N7l0p6R1q3raS/pOUPSDquvi91/RopaWrdc/bh0vprJO2U7g9Pr4dH0mvtDkkf6K19MzMza2yxL6wj4vmIGBMRY4AfA6eVHr+S7m8C/BP4Ym0/SRtR5NtB0jJ1zc4BPtXgcOOAtwGbRsRoYG/ghRa7+hzwld42kLQUcDVwYkSsD2wGbAd8obTZk8AxLR6zbKykUeUFEfHz0rl6Gtg5PT46bXJpbX263Z+WT0/7jAbWAPYtNTuF4jzV7AdMruvLkaU2tystvzQiNo+I9YATgSvS89TIx4A/A+NTli+mPn2w1r90u7yPY7bqO8BywPqpf1el/qmP/Wqvx/WAS4EbJK3SZNsFniMASZsAPwQ+GREbppwXAiPTJucDB6flmwC/7E8wen9NfQtYDdgk/T/6MMV5MDMzs35a7AvrfrgdWL30eH/gF8B1wB51234fOFxS/aj21YBnImIuQEQ8GRH/1+LxfwaMk7RSL9vsD9waEdel9v8NHAIcXdrmGmCUpA1aPG7NycDX+7lPryJiDnAH85/XJ4AlJb0lFZ3vB/53Idq+ETgbOLjJJuMp3qisIWn1JttUQtLSwEHA4SkzEfFz4HXgPa22ExGXUrze9m+ySbPn6CjgOxHxQKmtqyPipvRwVeCZtHxO6Q1QqyYDL0p6b3lhyv1Z4NCIeD21/2xE9LdwNzMzM7qksJY0FNiF4mpwzTiKK4gXk656ljwB3AJ8om75L4EPp4/cT5G0eT+68TJFcf3lXrYZBdxdXhAR04FlJS2fFs0Fvkf/i+RfAltIWrcf+4yrGwqyVHmlpCWBbYDf1e13OcUV5e2AeygK0LKTSm1e2Mvx7wE2rF8o6e3AWyPijpRrXP02DbRyzHeX8/LGG651gSci4qW67e+ieM76o2GmpNlzNCrt18xpwEOSrpT0ufS89Ne3gWPrljXLbWZmZgthsBfWS6UC6XlgJeAPAJK2AmZGxF+B6ymKmRXr9v0OcCSlcxARTwIbAF+jKHCvl7RLL8ev/yP0pwOfLBXJ9dRgn0ZtXQRsqzS+u0VzgJMo+t6q+qEgr6bl65TO6xMRcV/dfr+kKKzHU7xxqVcelnFAL8dvNsxiP94Y7nAJC74xaqSVY95czssbb8SaPS+9PV/N9DZ0pM/nSG98p+BhpXHrEfFNYCxvXA2vf6PTp4i4ObX/7v7u26SfB0u6S9JdVbRnZmZWtaFDhzJ06NDK2y3/Dky3eZ++D/bC+tVUIK0JjOCNMdbjgQ1VfClxOrA88NHyjhHxKDCJ+ccPExGvR8T/RsSRFMX3XrVjSRpR2nQlinHV5X1foCiKy2Omy6ZRFEjzSFobeDki/lVqZzZwCsUQgf74BbAD8I5+7levNsZ6XYoCf76hNBHxd2AW8F6KNy4La3PggQbLxwMT0vN3NbCZpPUGcJy+PAqsKal+bPEWQH+HXTTLVNPoOZqWjjXvOwUUw2SWrW0QEdMj4kcUn8xsJunN/ewXwPHMP9b6UeAdDXL3KSLOjoixETG2763NzMzab1EV1uXfgel2dm3dYC+sAYiIF4EvAUeomO3jYxRfQBwZESOBPWl81fN44IjaA0lbSHpbuj8E2BT4a1r9J+Djad1SFAX5jQ3aPBX4HI3/+M6FwPaSdi21czrF0I965wG7As2+CLeAiJhFMWzgsFb36aO9ZyjGfze6wvoN4KjamOT+krQjxfjqn9Yt3wBYJiJWLz1/J1BcxV4kIuIVii8InpqGFSHpQGBp4IZW25H0UWA3Gl/Frx2r0XP0PeCYui9yLl1q90OlL1GuR3Hl+wVJW0u6oNX+pbH9K1J8abY2xv9c4PTam0ZJq0n6eKttmpmZLa4igoj+fvA8MF1RWANExL0UX9LaF3gqIp4qrb4J2FjSanX7TGP+sa2rAr9JU5XdB8wGzkjrvgx8JA2R+DNwWenLZeU2nwOuBJZosO5ViiL/WEkPUcywcWfpGOVteyiK7lXr1/XhXFr/i5r1Y6wbzaZxFbB0/RCCiLgtIq5q0u5Jde3WrvTXjvcwxRjyj5a/sJeMpzh/Zb+i7+EgzY7Zqq8BrwEPS3qE4s3Z3vHG/8ilJT1Zuv2/tPzwdLxHKN54vSciZvZxrPmeo4iYQvH6ukDFdHu3AhtRfPoBxXcBHkqvvV8AB6Q3NO8AXqV/jqeY6aXmWGAmcH963V+VHiPpHKXpAs3MzAabWbNmMWvWrLYeU+2u5M2sGpJOAn7RYAx8W00bvZZ/iJiZWUOjpszo2LFrfxxmxIj+XmvrU9PvU7X/j6ibWSXS9wDMzMxsMdE1Q0HMzMzMzDrJhbWZmZmZWQU8FMTMzMzMus6imGqvLy6szczMzKzrdKKw9lAQMzMzM+s6nsfazMzMzKwCnZjH2oW1mZmZmVkFXFibmZmZmVXAhbWZmZmZWQVcWJuZmZmZVcDT7ZmZmZlZ1/E81mZmZmZmFfA81mZmZmZmFfA81mZmZmZmFfA81mZmZmZmg5QLazMzMzOzCqjdY0/MrLv09PTEiBEjOt2Ntujp6QEgl7zgzLnILXNuecGZK6ZmK3zF2szMzMysAp5uz8wGpBPTGXVKTllrnDkPuWXOLS84c7t4KIiZDZR/iJiZWU48FMTMFo25c+d2ugttM3fu3KzygjPnIrfMueUFZ24XF9ZmNiCzZ8/udBfaZvbs2VnlBWfORW6Zc8sLztwuLqzNzMzMzCrgwtrMzMzMrAKeFcTMBuSRLTfodBfMzGyQGTVlRqe7sEj4irWZmZmZWQV8xdrMzMzMus6wYe0vc11Ym5mZmVnXGTKk/QMzPBTEzMzMzLqO57E2MzMzM6uA57E2MzMzMxukXFibmZmZmVXAhbWZmZmZWQVcWJuZmZmZVcDT7ZmZmZlZ1/E81mZmZmZmFfA81mZmZmZmFfA81mZmZmZmFfA81mZmZmZmg5QLazMzMzOzCriwNjMzMzOrgAtrMzMzM7MKuLA2qyNpjqRJpdvRafkISd+XNF3So5KukfSOtG6kpKl17Rwn6Yh0/zxJ+6T7EyU9VGq/tnxzSSHpfaU23i5phqSV0uMV0+M1+8jwuKSV0/2QdEpp3RGSjis9PlDSVEnTJN1f67OZmdlgNmzYsLbPZe15rM0W9GpEjGmw/DvAcsD6ETFH0kHAryVtuRDHOCAi7qpbNh64Jf37e4CI+JukHwEnAgenf8+OiL/241ivAx+RdEJEPFdeIekDwGHAbhHxtKQlgU8sRB4zM7PFiuexNltMSVoaOAg4PCLmAETEz4GXgV0raF/APsAEYLdU4NacBmwr6TBge+CUBRro3WzgbODwBuu+BhwREU8DRMRrEfHTfrZvZma22OnEPNa+Ym22oKUkTSo9PgF4AHgiIl6q2/YuYGPg4X4e40JJr6b7uwAbATMiYrqkicAHgSsAImKWpCOB31FcWe7p57EAzgTuk/S9uuWbAHcvRHtmZmaLtdoc1iNGjGjbMX3F2mxBr0bEmNLtUkBANNhW6d9G63pbfkCp/ecphn9cktZdkh6XfQB4hqIQ7rf0huAC4EsLs389SQdLuktS/XAWMzOzrlb+HZhuB9fWubA2a82jwJqSlqtbvgXFVevngRXr1q0EPEcfJA0FPgp8Q9LjwA+BD9SOJWkM8F5gW+BwSastZIbvA58Gliktmwb0e4x4RJwdEWMjYuxC9sXMzGxQKv8OTLeza+tcWJu1ICJeAc4HTk2FMJIOBF4Dbo2Il4FnJO2S1q0EvJ/iy4h92RWYHBFvj4iREbEm8CtgrzT2+kfAYRHxBHAScHJtR0kP9iPDP4FfUhTXNScA35P01tTeEpIquaptZmaWG4+xNltQ/Rjr30XE0RRf9DsJeEjSUsBM4J0RURvucSBwZmlqu/+OiOktHG88cGXdsl8B/wEsRTG2+w9p+VnABEk7UlxtFv1zCnBI7UFEXCvpLcAfUxEfwM8AJH0+bfPjfh7DzMwsS3qjJjCzVqUrvL8Dzip/BNTmPuwOrB0Rp3fi+DXTRq/lHyJmZtYvo6bMWOTHqM0Isgim3Wt6UctXrM0WQkT8HRjT4T5c08njm5mZLc48j7WZmZmZWQXmzJnDnDlz2npMF9ZmZmZm1nVcWJuZmZmZDVIurM3MzMzMKuDC2szMzMysAi6szczMzMwq4On2zMzMzKzrDB8+vO3HdGFtZmZmZl2n+IPC7eWhIGZmZmbWdTzdnpmZmZlZBVxYm5mZmZkNUi6szczMzMwq4MLazMzMzKwCLqzNzMzMzCrg6fbMzMzMrOt4HmszMzMzswp4HmszMzMzswp0Yro9RURbD2hm3aWnpydGjBjR6W60RU9PDwC55AVnzkVumXPLC85csaaXwn3F2szMzMysAi6szczMzMwq4MLazMzMzKwCLqzNzMzMzCrgLy+a2YBERHRiSqNOqP28zCUvOHMucsucW15w5oo1bdCFtZkNlH+ImJlZTjwriJktGu2eI7STOjEnaqc5cx5yy5xbXnDmdnFhbWYDktMPav9iyoMzd7/c8oIzt4sLazMzMzOzCriwNjMzMzOrgAtrMzMzM7MKuLA2MzMzM6uAC2szG5AllljicxRTD3X9bcSIEcoprzN3vi/O7LzOvFhmbsqFtZkN1MGd7kCb5ZYXnDkXuWXOLS848yLnwtrMzMzMrAIurM3MzMzMKuDC2swG6uxOd6DNcssLzpyL3DLnlheceZFTRLTzeGZmZmZmXclXrM3MzMzMKuDC2swWiqT3S3pI0qOSju50f1ol6e2SbpT0gKRpkr6clq8k6Q+SHkn/rthk/0+mbR6R9MnS8rUk/SUtv1TSiLRckk5P5+k+SVu0J+kC/R4q6V5J16TH3Z73TZIul/Rgeq7fmUHmw9NreqqkiyUt2W2ZJf1M0j8kTS0ta5pR0tdSHx+S9L4mbfY7o9r0869J3pPS6/o+SVdKelO35E3HWiBzad0RkkLSyqVli1fmiPDNN99869cNGApMB9YGRgCTgY073a8W+74asEW6vxzwMLAx8D3g6LT8aOC7DfZdCXgs/btiur9iWvdLYL90/8fAf6T7HwT+l2Lu022Bv3Qo9/8DLgKuSY+7Pe/5wGfS/RHAm7o5M7A6MANYqtTXCd2WGdgB2AKYWlrWMGP6fz0ZWAJYi+Jn1tAGbfYrI238+dck727AsHT/u92Ut1nmtPztwO+BvwIrL66Z2/of3zfffOuOG/BO4Pelx18Dvtbpfi1kll8D7wUeAlZLy1YDHmqw7XjgJ6XHP0nLBDxX+mU37/zUtintM+84bcy4BnA98B7eKKy7Oe/yFEWm6pZ3c+bVgb9RFMfDgGsoCrCuywyMZP5Cs2HG+p9LFEXZO+va6ndG2vzzrz5v3bq9gQu7KW+zzMDlwGbA47xRWC92mT0UxMwWRu2XeM2TadmgImkksDnwF+AtEfEMQPp31Qa7NMv9ZuCFiJhdt7y3fdrp+8BXgbmlZd2cd21gJvBzFcNfzpG0DF2cOSKeAk4GngCeAV6MiOvo4swlzTK20seFybg4Zf8UxRVX6OK8kvYAnoqIyXWrFrvMLqzNbGE0+pOug2qKIUnLAr8CDouIl1rdrcGy6GV5b/u0haTdgX9ExN0Ls3uDZYt13mQYxUfJP4qIzYFXKIYItGJQZk7jivek+Dj8bcAykj7e6u4Nli32mVvQSh8XJuNikV3SMcBs4MLaogabDfq8kpYGjgG+0Wh1g2UdzezC2swWxpMU491q1gCe7lBf+k3ScIqi+sKIuCItflbSamn9asA/GuzaLPdzwJskDatb3ts+7fIuYA9JjwOXAO+R9D90b95aH56MiL+kx5dTFNrdnHlXYEZEzIyIWcAVwHZ0d+aaZhlb6ePCZOx4dhVfMN0dOCDSWIUW+zUY865D8YZxcvo5tgZwj6S3tti3tmZ2YW1mC+NOYL30TesRwH7A1R3uU0skCTgXeCAiTi2tuhr4ZLr/SYqx10haXdL1afnvgd0krZiuEO5GMQ4vgBuBfer3T+0emL59vi3FR/TPLKJ4C4iIr0XEGhExkuJ5uiEiPk6X5gWIiL8Df5O0QVq0C3A/XZyZYgjItpKWTq/xXYAH6O7MNQ0zpuX7SVpC0lrAesAdAJIukLT1Qmbs6M8/Se8HjgL2iIh/l1Z1Zd6ImBIRq0bEyPRz7EmKL6D/ncUx86IcfO6bb751743i29QPU3xz+phO96cf/d6e4iO9+4BJ6fZBinF41wOPpH9XStuPZf4vsXwKeDTdDiotXzv9QH8UuAxYIi0XcGY6T1OAsR3MvhNvfHmxq/MCY4C70vN8FcVsF92e+b+BB4GpwC8oZkroqszAxRRjyGdRFFifbpYxbX9M6uNDwAdKyycBb1/YjLTp51+TvI9SjP+dlG4/7pa8zTLXrX+c9OXFxTGz//KimVkvJB0CPBERg+KK/EDllhecudN9aTdJywPnRsTHOt2XdsgtL3Q2swtrMzMzM7MKeIy1mZmZmVkFXFibmZmZmVXAhbWZmZmZWQVcWJuZmZmZVcCFtZmZmZlZBVxYm5mZmZlVwIW1mZmZmVkFXFibmZmZmVXAhbWZmZmZWQVcWJuZmZmZVcCFtZmZmZlZBVxYm5mZmZlVwIW1mZmZmVkFXFibmZmZmVXAhbWZmZmZWQVcWJuZmZmZVcCFtZmZmZlZBVxYm5mZmZlVwIW1mZmZmVkFXFibmZmZmVXAhbWZmRkg6XFJIWmnxaAvQyWdJ+mF1KeTO92nVkkamfoc/dhnsTn3ZgPhwtrMzBYbpQLraUlLpWVj+luodYGPAp8EZgM/BG5qtFEqwA+XdK+kf0t6UdKfJY1rZ2cr8DPgB8CTre5Qe01IGrnIemXWT8M63QEzM7MGVgP+Azi10x0ZCEnDI2LWQuy6fvr32oj4UpO2hwBXAh+mKMCvBf4JbAOMBy5diON2RER8s9N9MKuCr1ibmdniKICjJC3daGX91UpJx6XH56XHE9LjyZJOlfSypPslbS7pW+nK7mOSdmvQ/BaSJkn6l6QrJb25dNztJU2U9H/pqvrPauvLQyAkfV7S08B1Tfo/UtJlkp5Jbd0oaZtaFuBbadNPpPYmNGhmX4qiGmD3iNgzIg6KiI2Bo1NbknSwpCmSXpH0qKRvS1oyrd8ptf+CpK+mvvxV0m6SviBpZsp5YKnvE9M+35F0W2r3xt6uHEu6SNKTkl5P5/UGSaNL6+cbClI6xgmSbkpX42+VtGZaX/70YkZtX0lbSLpZ0kvpOZ8q6T+a9cusai6szcxscXQZsCrwxQG2M5riCu4DwEbAjcA+wJ+BtSiGINQ7DrgHeA7YCzgbQNImwPXAlsDvgIeBg4DLJKmujeOB/wVuq29c0jLADakfD6f7OwE3SFon9e0vafMHKIZI3N+gn7Wi+s8R8fvyioh4MN39D+AnwNsprmAPA45JbZYtD3w85X4Hxfk/mmIIymrAjyStULfPEcB04LHU/8sb9LFmTeBPwDnpGDsDv+xl+5qvAn+jeC62A76dlpf7/3PeGEZyOrA9xRuai4H/o3i+zNrChbWZmS2OLqUoJo8Elh1AO68Au6Z2AFagGL+8T3q8uqRV6vb5z4j4FEVRDfARSctSFKkjgGnAs8Ak4HWKInGDujY+FhGfjohjGvTpQxRF/WPAThHxUeAqYGng0xHxO4rCHeCOiDgsIu5o0M6q6d+/No4OwCHp3y+nTHumx5+pXbVOBHwQ+HR6vDzw+dS351Pf1md+Z0bEJyjyzwa2lDSqST/2pXjD8C/gvrRsQ0lv66XvAD+OiAOA/0qPNweIiMNK23wznaNHgeFp2bUUxfZ7gM/1cQyzyniMtZmZLY7mAv9NUWAf0se2AEObLH88Il6V9EJp2UMRMad0kXkZYGZp/QPp3wdLy1YHRqb726Rb2brA1NLjW3vpa62dhyKiNqShdqw1e9mv3j9a2Kd2rPpMQyiuYte8HBFPSnpTadlDtXXAmynOU9kDABHxnKTngLcCa5T2A0DSehRXqRu9QVoFeLqX/t+b/n0h/dvXm6z/B5xFcWVcqe/fAE7rYz+zSviKtZmZLa4uA6ZQXO2s9+/07/Lp302atDGnfkFELLCszkbp3w1Ly54CHk/3T40I1W7A2hFxTd0xXu+l/Vo765eGkNSuePd29ble7Zjb1o8VT8Vs+Vi1LLXjzKUYYlHT6Jy0dJ4krQysnJY1mtXjQxQF8RTgTcBbyl3t4xiz07+NZoSZm/4t1zJ3RcRmwIoUw1OGAydK8oVEawu/0MzMbLEUESHpv2k8dvde4F3AGZIe4o0hDlX4lqTNKIY4AFwZES9LOhv4LPBlSWtTjPvdiGLsb38uVP2WouBdB7gxXe3dG3iVxmO+m7mUYlz0B4HfSrqW4sr7lhQF+l7AmcAZwA8k7UgxNALg3Ih4bcGh4f3yhVRUj6GoJ+6hGL5TfwX92fTvehTDM8YM5KAlf0vHOkPSwxRjx6+UNJRi7PcKwBIUQ1n6epNgVglfsTYzs8XZFRRjmesdSnEFdAzF8IOfV3jM44AtKIYpXA0cDBARkynGa98E7ADsBywHnNifxiPiFWAX4FcUV5J3pfhi3y5pnHCr7cyleENxBMW4790oru73AJekzc4CvkBxxX08xVXeE4Av96fPTZxIMdRkndT/j5WGtpT9EjgXmEWR9YQKjg1wFMUV8vdT5FkKmAi8DTiA4kr5ncC4Jv0yq5z8WjMzM7NWSZoI7AgcFBHndbY3ZosXX7E2MzMzM6uAC2szMzMzswp4KIiZmZmZWQV8xdrMzMzMrAIurM3MzMzMKuDC2szMzMysAi6szczMzMwq4MLazMzMzKwCLqzNzMzMzCrw/wFVnodkXZWuzAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# build a horizontal bar chart for top companies with most complaints\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import StrMethodFormatter\n",
    "\n",
    "ax = complaints.head(10).plot(kind='barh', figsize=(8, 10), color='#d42c20', zorder=2, width=0.85)\n",
    "\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.spines['left'].set_visible(False)\n",
    "ax.spines['bottom'].set_visible(False)\n",
    "\n",
    "# Switch off ticks\n",
    "ax.tick_params(axis=\"both\", which=\"both\", bottom=\"off\", top=\"off\", labelbottom=\"on\", left=\"off\", right=\"off\", labelleft=\"on\")\n",
    "\n",
    "# Draw vertical axis lines\n",
    "vals = ax.get_xticks()\n",
    "for tick in vals:\n",
    "  ax.axvline(x=tick, linestyle='dashed', alpha=0.4, color='#eeeeee', zorder=1)\n",
    "\n",
    "# Set x-axis label\n",
    "ax.set_xlabel(\"Number of Complaints\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "# Set y-axis label\n",
    "ax.set_ylabel(\"Companies\", labelpad=20, weight='bold', size=12)\n",
    "\n",
    "# Format y-axis label\n",
    "ax.xaxis.set_major_formatter(StrMethodFormatter('{x:,g}'))\n",
    "\n",
    "ax.figure.savefig('worst_companies_complaints.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "described-hearing",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}