M5-DataVisualization-lab.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"text-align:center\">\n",
    "    <a href=\"https://skills.network/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDA0321ENSkillsNetwork21426264-2022-01-01\" target=\"_blank\">\n",
    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/assets/logos/SN_web_lightmode.png\" width=\"200\" alt=\"Skills Network Logo\"  />\n",
    "    </a>\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Data Visualization Lab**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estimated time needed: **45 to 60** minutes\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this assignment you will be focusing on the visualization of data.\n",
    "\n",
    "The data set will be presented to you in the form of a RDBMS.\n",
    "\n",
    "You will have to use SQL queries to extract the data.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objectives\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this lab you will perform the following:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*   Visualize the distribution of data.\n",
    "\n",
    "*   Visualize the relationship between two features.\n",
    "\n",
    "*   Visualize composition of data.\n",
    "\n",
    "*   Visualize comparison of data.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to work with database\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download database file.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2022-09-08 12:54:35--  https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DA0321EN-SkillsNetwork/LargeData/m4_survey_data.sqlite\n",
      "Resolving cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud (cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud)... 169.63.118.104\n",
      "Connecting to cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud (cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud)|169.63.118.104|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 36679680 (35M) [application/octet-stream]\n",
      "Saving to: ‘m4_survey_data.sqlite.1’\n",
      "\n",
      "m4_survey_data.sqli 100%[===================>]  34.98M  30.3MB/s    in 1.2s    \n",
      "\n",
      "2022-09-08 12:54:37 (30.3 MB/s) - ‘m4_survey_data.sqlite.1’ saved [36679680/36679680]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DA0321EN-SkillsNetwork/LargeData/m4_survey_data.sqlite"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Connect to the database.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "conn = sqlite3.connect(\"m4_survey_data.sqlite\") # open a database connection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import pandas module.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Demo: How to run an sql query\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "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>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11398</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0     11398"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print how many rows are there in the table named 'master'\n",
    "QUERY = \"\"\"\n",
    "SELECT COUNT(*)\n",
    "FROM master\n",
    "\"\"\"\n",
    "\n",
    "# the read_sql_query runs the sql query and returns the data as a dataframe\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to list all tables\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\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>Table_Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EduOther</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DevType</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LastInt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>JobFactors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>WorkPlan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>WorkChallenge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>LanguageWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>LanguageDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DatabaseWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>DatabaseDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PlatformWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PlatformDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>WebFrameWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>WebFrameDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>MiscTechWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>MiscTechDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>DevEnviron</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Containers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>SOVisitTo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>SONewContent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Gender</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sexuality</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Ethnicity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>master</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Table_Name\n",
       "0                 EduOther\n",
       "1                  DevType\n",
       "2                  LastInt\n",
       "3               JobFactors\n",
       "4                 WorkPlan\n",
       "5            WorkChallenge\n",
       "6       LanguageWorkedWith\n",
       "7   LanguageDesireNextYear\n",
       "8       DatabaseWorkedWith\n",
       "9   DatabaseDesireNextYear\n",
       "10      PlatformWorkedWith\n",
       "11  PlatformDesireNextYear\n",
       "12      WebFrameWorkedWith\n",
       "13  WebFrameDesireNextYear\n",
       "14      MiscTechWorkedWith\n",
       "15  MiscTechDesireNextYear\n",
       "16              DevEnviron\n",
       "17              Containers\n",
       "18               SOVisitTo\n",
       "19            SONewContent\n",
       "20                  Gender\n",
       "21               Sexuality\n",
       "22               Ethnicity\n",
       "23                  master"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print all the tables names in the database\n",
    "QUERY = \"\"\"\n",
    "SELECT name as Table_Name FROM\n",
    "sqlite_master WHERE\n",
    "type = 'table'\n",
    "\"\"\"\n",
    "# the read_sql_query runs the sql query and returns the data as a dataframe\n",
    "pd.read_sql_query(QUERY,conn)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to run a group by query\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>287</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18.0</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19.0</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20.0</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>21.0</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>22.0</td>\n",
       "      <td>406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>23.0</td>\n",
       "      <td>581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>24.0</td>\n",
       "      <td>679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>25.0</td>\n",
       "      <td>738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>26.0</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>27.0</td>\n",
       "      <td>724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>28.0</td>\n",
       "      <td>787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>29.0</td>\n",
       "      <td>697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>30.0</td>\n",
       "      <td>651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>31.0</td>\n",
       "      <td>531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>32.0</td>\n",
       "      <td>489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>33.0</td>\n",
       "      <td>483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>34.0</td>\n",
       "      <td>395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>35.0</td>\n",
       "      <td>393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>36.0</td>\n",
       "      <td>308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>37.0</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>38.0</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>39.0</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>40.0</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>41.0</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>42.0</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>43.0</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>44.0</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>45.0</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>46.0</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>47.0</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>48.0</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>49.0</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>50.0</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>51.0</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>52.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>53.0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>54.0</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>55.0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>56.0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>57.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>58.0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>59.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>60.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>61.0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>62.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>63.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>65.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>66.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>67.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>69.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>71.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>72.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>99.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age  count\n",
       "0    NaN    287\n",
       "1   16.0      3\n",
       "2   17.0      6\n",
       "3   18.0     29\n",
       "4   19.0     78\n",
       "5   20.0    109\n",
       "6   21.0    203\n",
       "7   22.0    406\n",
       "8   23.0    581\n",
       "9   24.0    679\n",
       "10  25.0    738\n",
       "11  26.0    720\n",
       "12  27.0    724\n",
       "13  28.0    787\n",
       "14  29.0    697\n",
       "15  30.0    651\n",
       "16  31.0    531\n",
       "17  32.0    489\n",
       "18  33.0    483\n",
       "19  34.0    395\n",
       "20  35.0    393\n",
       "21  36.0    308\n",
       "22  37.0    280\n",
       "23  38.0    279\n",
       "24  39.0    232\n",
       "25  40.0    187\n",
       "26  41.0    136\n",
       "27  42.0    162\n",
       "28  43.0    100\n",
       "29  44.0     95\n",
       "30  45.0     85\n",
       "31  46.0     66\n",
       "32  47.0     68\n",
       "33  48.0     64\n",
       "34  49.0     66\n",
       "35  50.0     57\n",
       "36  51.0     29\n",
       "37  52.0     41\n",
       "38  53.0     32\n",
       "39  54.0     26\n",
       "40  55.0     13\n",
       "41  56.0     16\n",
       "42  57.0     11\n",
       "43  58.0     12\n",
       "44  59.0     11\n",
       "45  60.0      2\n",
       "46  61.0     10\n",
       "47  62.0      5\n",
       "48  63.0      7\n",
       "49  65.0      2\n",
       "50  66.0      1\n",
       "51  67.0      1\n",
       "52  69.0      1\n",
       "53  71.0      2\n",
       "54  72.0      1\n",
       "55  99.0      1"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT Age,COUNT(*) as count\n",
    "FROM master\n",
    "group by age\n",
    "order by age\n",
    "\"\"\"\n",
    "pd.read_sql_query(QUERY,conn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to describe a table\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CREATE TABLE \"master\" (\n",
      "\"index\" INTEGER,\n",
      "  \"Respondent\" INTEGER,\n",
      "  \"MainBranch\" TEXT,\n",
      "  \"Hobbyist\" TEXT,\n",
      "  \"OpenSourcer\" TEXT,\n",
      "  \"OpenSource\" TEXT,\n",
      "  \"Employment\" TEXT,\n",
      "  \"Country\" TEXT,\n",
      "  \"Student\" TEXT,\n",
      "  \"EdLevel\" TEXT,\n",
      "  \"UndergradMajor\" TEXT,\n",
      "  \"OrgSize\" TEXT,\n",
      "  \"YearsCode\" TEXT,\n",
      "  \"Age1stCode\" TEXT,\n",
      "  \"YearsCodePro\" TEXT,\n",
      "  \"CareerSat\" TEXT,\n",
      "  \"JobSat\" TEXT,\n",
      "  \"MgrIdiot\" TEXT,\n",
      "  \"MgrMoney\" TEXT,\n",
      "  \"MgrWant\" TEXT,\n",
      "  \"JobSeek\" TEXT,\n",
      "  \"LastHireDate\" TEXT,\n",
      "  \"FizzBuzz\" TEXT,\n",
      "  \"ResumeUpdate\" TEXT,\n",
      "  \"CurrencySymbol\" TEXT,\n",
      "  \"CurrencyDesc\" TEXT,\n",
      "  \"CompTotal\" REAL,\n",
      "  \"CompFreq\" TEXT,\n",
      "  \"ConvertedComp\" REAL,\n",
      "  \"WorkWeekHrs\" REAL,\n",
      "  \"WorkRemote\" TEXT,\n",
      "  \"WorkLoc\" TEXT,\n",
      "  \"ImpSyn\" TEXT,\n",
      "  \"CodeRev\" TEXT,\n",
      "  \"CodeRevHrs\" REAL,\n",
      "  \"UnitTests\" TEXT,\n",
      "  \"PurchaseHow\" TEXT,\n",
      "  \"PurchaseWhat\" TEXT,\n",
      "  \"OpSys\" TEXT,\n",
      "  \"BlockchainOrg\" TEXT,\n",
      "  \"BlockchainIs\" TEXT,\n",
      "  \"BetterLife\" TEXT,\n",
      "  \"ITperson\" TEXT,\n",
      "  \"OffOn\" TEXT,\n",
      "  \"SocialMedia\" TEXT,\n",
      "  \"Extraversion\" TEXT,\n",
      "  \"ScreenName\" TEXT,\n",
      "  \"SOVisit1st\" TEXT,\n",
      "  \"SOVisitFreq\" TEXT,\n",
      "  \"SOFindAnswer\" TEXT,\n",
      "  \"SOTimeSaved\" TEXT,\n",
      "  \"SOHowMuchTime\" TEXT,\n",
      "  \"SOAccount\" TEXT,\n",
      "  \"SOPartFreq\" TEXT,\n",
      "  \"SOJobs\" TEXT,\n",
      "  \"EntTeams\" TEXT,\n",
      "  \"SOComm\" TEXT,\n",
      "  \"WelcomeChange\" TEXT,\n",
      "  \"Age\" REAL,\n",
      "  \"Trans\" TEXT,\n",
      "  \"Dependents\" TEXT,\n",
      "  \"SurveyLength\" TEXT,\n",
      "  \"SurveyEase\" TEXT\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "table_name = 'master'  # the table you wish to describe\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT sql FROM sqlite_master\n",
    "WHERE name= '{}'\n",
    "\"\"\".format(table_name)\n",
    "\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "print(df.iat[0,0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hands-on Lab\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing distribution of data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histograms\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot a histogram of `ConvertedComp.`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'ConvertedComp'}>]], dtype=object)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GOiFHkq666iqFhoZq7dq1io+P17p169SrVy8n5EhSamqqqqurtWnTJg0ZMsRjfdXV1aqurnZuHzx4UNIPibO2ttabu8KZz9vzNhf05/ts75H+fJ/tPdren9R0PTZmPq8GnfLycklSZGSk23hkZKR27Njh1AQGBqpdu3YeNfWPLy8vV0REhMf8ERERbjUnb6ddu3YKDAx0ak72+OOPKzc312O8uLhYISEhDWmx0UpKSppk3uaC/nyf7T3Sn++zvUfb+5O83+PRo0cbXNskV12d/JqZMeasr6OdXHOq+nOp+VdTp05Vdna2c7v+zUwpKSlN8h6dkpISJScnW/naK/35Ptt7pD/fZ3uPtvcnNV2P9a/INIRXg05UVJSkH862dOjQwRmvqKhwzr5ERUWppqZGlZWVbmd1KioqNGDAAKdmz549HvPv3bvXbZ4NGza43V9ZWana2lqPMz31goKCFBQU5DEeEBDQZL9kTTl3c0B/vs/2HunP99neo+39Sd7vsTFzefWTkWNjYxUVFeV2iqqmpkarV692QkxCQoICAgLcasrKyrRlyxanJjExUVVVVfrwww+dmg0bNqiqqsqtZsuWLSorK3NqiouLFRQUpISEBG+2BQAAfFSjz+gcPnxYX3zxhXP766+/VmlpqcLCwtSxY0dlZWUpLy9PcXFxiouLU15enkJCQpSRkSFJCg0N1dixY/XAAw8oPDxcYWFhmjRpknr37u1chdW9e3cNGzZM48aN04IFCyT9cHl5Wlqa4uPjJUkpKSnq0aOHMjMzNXPmTO3fv1+TJk3SuHHjuOIKAABIOoeg89FHH7ld0VT/npdRo0apoKBAkydP1rFjxzRhwgTnAwOLi4vdPtRn9uzZ8vf318iRI50PDCwoKHA+Q0eSXnjhBU2cONG5Ois9PV1z58517vfz89Nf/vIXTZgwQQMHDnT7wEAAAADpHILO4MGDZYw57f0ul0s5OTnKyck5bU1wcLDy8/PP+MF+YWFhWrZs2RnX0rFjR73xxhtnXTMAAPhp4tvLAQCAtQg6AADAWgQdAABgLYIOAACwFkEHAABYq0m+AgL/p1fO26o+cfavkW8uvnni+gu9BAAAvIYzOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtbwedI4fP66HHnpIsbGxatmypS677DI98sgjqqurc2qMMcrJyVF0dLRatmypwYMHa+vWrW7zVFdX67777lP79u3VqlUrpaena9euXW41lZWVyszMVGhoqEJDQ5WZmakDBw54uyUAAOCjvB50pk+frvnz52vu3Lnatm2bZsyYoZkzZyo/P9+pmTFjhmbNmqW5c+dq48aNioqKUnJysg4dOuTUZGVlacWKFVq+fLnWrFmjw4cPKy0tTSdOnHBqMjIyVFpaqqKiIhUVFam0tFSZmZnebgkAAPgof29PuG7dOt144426/vrrJUmdO3fWiy++qI8++kjSD2dz5syZo2nTpummm26SJC1dulSRkZEqLCzU+PHjVVVVpcWLF+v555/X0KFDJUnLli1TTEyM3nnnHaWmpmrbtm0qKirS+vXr1b9/f0nSokWLlJiYqO3btys+Pt7brQEAAB/j9aBz9dVXa/78+fr888/VtWtXffLJJ1qzZo3mzJkjSfr6669VXl6ulJQU5zFBQUG65pprtHbtWo0fP16bNm1SbW2tW010dLR69eqltWvXKjU1VevWrVNoaKgTciTpqquuUmhoqNauXXvKoFNdXa3q6mrn9sGDByVJtbW1qq2t9ep+qJ8vqIXx6rxNraH7ob7O2/utubC9P8n+HunP99neo+39SU3XY2Pm83rQ+c///E9VVVWpW7du8vPz04kTJ/TYY4/pP/7jPyRJ5eXlkqTIyEi3x0VGRmrHjh1OTWBgoNq1a+dRU//48vJyRUREeGw/IiLCqTnZ448/rtzcXI/x4uJihYSENLLThvmvK+rOXtSMvPnmm42qLykpaaKVNA+29yfZ3yP9+T7be7S9P8n7PR49erTBtV4POi+99JKWLVumwsJC9ezZU6WlpcrKylJ0dLRGjRrl1LlcLrfHGWM8xk52cs2p6s80z9SpU5Wdne3cPnjwoGJiYpSSkqI2bdo0qL+Gqq2tVUlJiR7+qIWq687cV3OyJSe1QXX1/SUnJysgIKCJV3X+2d6fZH+P9Of7bO/R9v6kpuux/hWZhvB60HnwwQc1ZcoU/epXv5Ik9e7dWzt27NDjjz+uUaNGKSoqStIPZ2Q6dOjgPK6iosI5yxMVFaWamhpVVla6ndWpqKjQgAEDnJo9e/Z4bH/v3r0eZ4vqBQUFKSgoyGM8ICCgyX7Jqutcqj7hO0GnsfuhKfddc2B7f5L9PdKf77O9R9v7k7zfY2Pm8vpVV0ePHlWLFu7T+vn5OZeXx8bGKioqyu00Vk1NjVavXu2EmISEBAUEBLjVlJWVacuWLU5NYmKiqqqq9OGHHzo1GzZsUFVVlVMDAAB+2rx+RueGG27QY489po4dO6pnz57avHmzZs2apTvuuEPSDy83ZWVlKS8vT3FxcYqLi1NeXp5CQkKUkZEhSQoNDdXYsWP1wAMPKDw8XGFhYZo0aZJ69+7tXIXVvXt3DRs2TOPGjdOCBQskSXfddZfS0tK44goAAEhqgqCTn5+vhx9+WBMmTFBFRYWio6M1fvx4/e53v3NqJk+erGPHjmnChAmqrKxU//79VVxcrNatWzs1s2fPlr+/v0aOHKljx44pKSlJBQUF8vPzc2peeOEFTZw40bk6Kz09XXPnzvV2SwAAwEd5Pei0bt1ac+bMcS4nPxWXy6WcnBzl5OSctiY4OFj5+fluHzR4srCwMC1btuxHrBYAANiM77oCAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsFaTBJ1//vOfuu222xQeHq6QkBD97Gc/06ZNm5z7jTHKyclRdHS0WrZsqcGDB2vr1q1uc1RXV+u+++5T+/bt1apVK6Wnp2vXrl1uNZWVlcrMzFRoaKhCQ0OVmZmpAwcONEVLAADAB3k96FRWVmrgwIEKCAjQW2+9pc8++0xPPfWU2rZt69TMmDFDs2bN0ty5c7Vx40ZFRUUpOTlZhw4dcmqysrK0YsUKLV++XGvWrNHhw4eVlpamEydOODUZGRkqLS1VUVGRioqKVFpaqszMTG+3BAAAfJS/tyecPn26YmJitGTJEmesc+fOzn8bYzRnzhxNmzZNN910kyRp6dKlioyMVGFhocaPH6+qqiotXrxYzz//vIYOHSpJWrZsmWJiYvTOO+8oNTVV27ZtU1FRkdavX6/+/ftLkhYtWqTExERt375d8fHxHmurrq5WdXW1c/vgwYOSpNraWtXW1np1P9TPF9TCeHXeptbQ/VBf5+391lzY3p9kf4/05/ts79H2/qSm67Ex87mMMV79S9yjRw+lpqZq165dWr16tS655BJNmDBB48aNkyR99dVX6tKliz7++GP169fPedyNN96otm3baunSpVq1apWSkpK0f/9+tWvXzqnp27evRowYodzcXD377LPKzs72eKmqbdu2mj17tsaMGeOxtpycHOXm5nqMFxYWKiQkxEt7AAAANKWjR48qIyNDVVVVatOmzRlrvX5G56uvvtK8efOUnZ2t3/72t/rwww81ceJEBQUF6fbbb1d5ebkkKTIy0u1xkZGR2rFjhySpvLxcgYGBbiGnvqb+8eXl5YqIiPDYfkREhFNzsqlTpyo7O9u5ffDgQcXExCglJeWsO6qxamtrVVJSooc/aqHqOpdX525KW3JSG1RX319ycrICAgKaeFXnn+39Sfb3SH++z/Yebe9Paroe61+RaQivB526ujpdccUVysvLkyT169dPW7du1bx583T77bc7dS6X+x9/Y4zH2MlOrjlV/ZnmCQoKUlBQkMd4QEBAk/2SVde5VH3Cd4JOY/dDU+675sD2/iT7e6Q/32d7j7b3J3m/x8bM5fU3I3fo0EE9evRwG+vevbu+/fZbSVJUVJQkeZx1qaiocM7yREVFqaamRpWVlWes2bNnj8f29+7d63G2CAAA/DR5PegMHDhQ27dvdxv7/PPP1alTJ0lSbGysoqKiVFJS4txfU1Oj1atXa8CAAZKkhIQEBQQEuNWUlZVpy5YtTk1iYqKqqqr04YcfOjUbNmxQVVWVUwMAAH7avP7S1f33368BAwYoLy9PI0eO1IcffqiFCxdq4cKFkn54uSkrK0t5eXmKi4tTXFyc8vLyFBISooyMDElSaGioxo4dqwceeEDh4eEKCwvTpEmT1Lt3b+cqrO7du2vYsGEaN26cFixYIEm66667lJaWdsorrgAAwE+P14POlVdeqRUrVmjq1Kl65JFHFBsbqzlz5ujWW291aiZPnqxjx45pwoQJqqysVP/+/VVcXKzWrVs7NbNnz5a/v79GjhypY8eOKSkpSQUFBfLz83NqXnjhBU2cOFEpKSmSpPT0dM2dO9fbLQEAAB/l9aAjSWlpaUpLSzvt/S6XSzk5OcrJyTltTXBwsPLz85Wfn3/amrCwMC1btuzHLBUAAFiM77oCAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsFaTB53HH39cLpdLWVlZzpgxRjk5OYqOjlbLli01ePBgbd261e1x1dXVuu+++9S+fXu1atVK6enp2rVrl1tNZWWlMjMzFRoaqtDQUGVmZurAgQNN3RIAAPARTRp0Nm7cqIULF6pPnz5u4zNmzNCsWbM0d+5cbdy4UVFRUUpOTtahQ4ecmqysLK1YsULLly/XmjVrdPjwYaWlpenEiRNOTUZGhkpLS1VUVKSioiKVlpYqMzOzKVsCAAA+xL+pJj58+LBuvfVWLVq0SI8++qgzbozRnDlzNG3aNN10002SpKVLlyoyMlKFhYUaP368qqqqtHjxYj3//PMaOnSoJGnZsmWKiYnRO++8o9TUVG3btk1FRUVav369+vfvL0latGiREhMTtX37dsXHx3usqbq6WtXV1c7tgwcPSpJqa2tVW1vr1f7r5wtqYbw6b1Nr6H6or/P2fmsubO9Psr9H+vN9tvdoe39S0/XYmPlcxpgm+Us8atQohYWFafbs2Ro8eLB+9rOfac6cOfrqq6/UpUsXffzxx+rXr59Tf+ONN6pt27ZaunSpVq1apaSkJO3fv1/t2rVzavr27asRI0YoNzdXzz77rLKzsz1eqmrbtq1mz56tMWPGeKwpJydHubm5HuOFhYUKCQnxXvMAAKDJHD16VBkZGaqqqlKbNm3OWNskZ3SWL1+ujz/+WBs3bvS4r7y8XJIUGRnpNh4ZGakdO3Y4NYGBgW4hp76m/vHl5eWKiIjwmD8iIsKpOdnUqVOVnZ3t3D548KBiYmKUkpJy1h3VWLW1tSopKdHDH7VQdZ3Lq3M3pS05qQ2qq+8vOTlZAQEBTbyq88/2/iT7e6Q/32d7j7b3JzVdj/WvyDSE14POzp079Zvf/EbFxcUKDg4+bZ3L5f7H3xjjMXayk2tOVX+meYKCghQUFOQxHhAQ0GS/ZNV1LlWf8J2g09j90JT7rjmwvT/J/h7pz/fZ3qPt/Une77Exc3n9zcibNm1SRUWFEhIS5O/vL39/f61evVp/+MMf5O/v75zJOfmsS0VFhXNfVFSUampqVFlZecaaPXv2eGx/7969HmeLAADAT5PXg05SUpL+9re/qbS01Pm54oordOutt6q0tFSXXXaZoqKiVFJS4jympqZGq1ev1oABAyRJCQkJCggIcKspKyvTli1bnJrExERVVVXpww8/dGo2bNigqqoqpwYAAPy0ef2lq9atW6tXr15uY61atVJ4eLgznpWVpby8PMXFxSkuLk55eXkKCQlRRkaGJCk0NFRjx47VAw88oPDwcIWFhWnSpEnq3bu3cxVW9+7dNWzYMI0bN04LFiyQJN11111KS0s75RVXAADgp6fJLi8/k8mTJ+vYsWOaMGGCKisr1b9/fxUXF6t169ZOzezZs+Xv76+RI0fq2LFjSkpKUkFBgfz8/JyaF154QRMnTlRKSookKT09XXPnzj3v/QAAgObpvASd9957z+22y+VSTk6OcnJyTvuY4OBg5efnKz8//7Q1YWFhWrZsmZdWCQAAbMN3XQEAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYy+tB5/HHH9eVV16p1q1bKyIiQiNGjND27dvdaowxysnJUXR0tFq2bKnBgwdr69atbjXV1dW677771L59e7Vq1Urp6enatWuXW01lZaUyMzMVGhqq0NBQZWZm6sCBA95uCQAA+CivB53Vq1frnnvu0fr161VSUqLjx48rJSVFR44ccWpmzJihWbNmae7cudq4caOioqKUnJysQ4cOOTVZWVlasWKFli9frjVr1ujw4cNKS0vTiRMnnJqMjAyVlpaqqKhIRUVFKi0tVWZmprdbAgAAPsrf2xMWFRW53V6yZIkiIiK0adMm/du//ZuMMZozZ46mTZumm266SZK0dOlSRUZGqrCwUOPHj1dVVZUWL16s559/XkOHDpUkLVu2TDExMXrnnXeUmpqqbdu2qaioSOvXr1f//v0lSYsWLVJiYqK2b9+u+Ph4j7VVV1erurrauX3w4EFJUm1trWpra726H+rnC2phvDpvU2vofqiv8/Z+ay5s70+yv0f6832292h7f1LT9diY+VzGmCb9S/zFF18oLi5Of/vb39SrVy999dVX6tKliz7++GP169fPqbvxxhvVtm1bLV26VKtWrVJSUpL279+vdu3aOTV9+/bViBEjlJubq2effVbZ2dkeL1W1bdtWs2fP1pgxYzzWkpOTo9zcXI/xwsJChYSEeK9pAADQZI4ePaqMjAxVVVWpTZs2Z6z1+hmdf2WMUXZ2tq6++mr16tVLklReXi5JioyMdKuNjIzUjh07nJrAwEC3kFNfU//48vJyRUREeGwzIiLCqTnZ1KlTlZ2d7dw+ePCgYmJilJKSctYd1Vi1tbUqKSnRwx+1UHWdy6tzN6UtOakNqqvvLzk5WQEBAU28qvPP9v4k+3ukP99ne4+29yc1XY/1r8g0RJMGnXvvvVeffvqp1qxZ43Gfy+X+x98Y4zF2spNrTlV/pnmCgoIUFBTkMR4QENBkv2TVdS5Vn/CdoNPY/dCU+645sL0/yf4e6c/32d6j7f1J3u+xMXM12eXl9913n15//XW9++67uvTSS53xqKgoSfI461JRUeGc5YmKilJNTY0qKyvPWLNnzx6P7e7du9fjbBEAAPhp8nrQMcbo3nvv1auvvqpVq1YpNjbW7f7Y2FhFRUWppKTEGaupqdHq1as1YMAASVJCQoICAgLcasrKyrRlyxanJjExUVVVVfrwww+dmg0bNqiqqsqpAQAAP21ef+nqnnvuUWFhof785z+rdevWzpmb0NBQtWzZUi6XS1lZWcrLy1NcXJzi4uKUl5enkJAQZWRkOLVjx47VAw88oPDwcIWFhWnSpEnq3bu3cxVW9+7dNWzYMI0bN04LFiyQJN11111KS0s75RVXAADgp8frQWfevHmSpMGDB7uNL1myRKNHj5YkTZ48WceOHdOECRNUWVmp/v37q7i4WK1bt3bqZ8+eLX9/f40cOVLHjh1TUlKSCgoK5Ofn59S88MILmjhxolJSUiRJ6enpmjt3rrdbAgAAPsrrQachV6u7XC7l5OQoJyfntDXBwcHKz89Xfn7+aWvCwsK0bNmyc1kmAAD4CeC7rgAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdAAAgLUIOgAAwFoEHQAAYC2CDgAAsBZBBwAAWIugAwAArEXQAQAA1iLoAAAAa/lf6AWgeek85S8NqgvyM5rxc6lXztuqPuFq4lWd2TdPXH9Btw8AaL44owMAAKxF0AEAANYi6AAAAGvxHh0AVmsO7yNrDN5zhtNp6Hsom5P693NeSD4fdJ555hnNnDlTZWVl6tmzp+bMmaNBgwZd6GXhPGqKg785vdm6qTS2R/4AA/BFPh10XnrpJWVlZemZZ57RwIEDtWDBAg0fPlyfffaZOnbseKGXB1jF1/412Rz+JQngwvPp9+jMmjVLY8eO1Z133qnu3btrzpw5iomJ0bx58y700gAAQDPgs2d0ampqtGnTJk2ZMsVtPCUlRWvXrj3lY6qrq1VdXe3crqqqkiTt379ftbW1Xl1fbW2tjh49Kv/aFjpRZ99LH/51RkeP1tGfD7O9R1/t7/+b9McG1QW1MHqoX51+Nu1VVV/g/jZMTWqSeev/P/rdd98pICCgSbZxITW2P//jR87Dqryr/jj09nN46NAhSZIx5uxr8NpWz7N9+/bpxIkTioyMdBuPjIxUeXn5KR/z+OOPKzc312M8Nja2SdZou4wLvYAmZnt/kv090t/50f6pC70CNGdN+Xt66NAhhYaGnrHGZ4NOPZfL/V8yxhiPsXpTp05Vdna2c7uurk779+9XeHj4aR9zrg4ePKiYmBjt3LlTbdq08erczQH9+T7be6Q/32d7j7b3JzVdj8YYHTp0SNHR0Wet9dmg0759e/n5+XmcvamoqPA4y1MvKChIQUFBbmNt27ZtqiVKktq0aWPtL7BEfzawvUf6832292h7f1LT9Hi2Mzn1fPbNyIGBgUpISFBJSYnbeElJiQYMGHCBVgUAAJoTnz2jI0nZ2dnKzMzUFVdcocTERC1cuFDffvutfv3rX1/opQEAgGbAp4POLbfcou+++06PPPKIysrK1KtXL7355pvq1KnThV6agoKC9Pvf/97jpTJb0J/vs71H+vN9tvdoe39S8+jRZRpybRYAAIAP8tn36AAAAJwNQQcAAFiLoAMAAKxF0AEAANYi6AAAAGsRdBromWeeUWxsrIKDg5WQkKD//d//PWP96tWrlZCQoODgYF122WWaP3++R80rr7yiHj16KCgoSD169NCKFSuaavln1Zj+Xn31VSUnJ+viiy9WmzZtlJiYqLffftutpqCgQC6Xy+Pn+++/b+pWTqsxPb733nunXP/f//53tzpffQ5Hjx59yv569uzp1DSn5/D999/XDTfcoOjoaLlcLr322mtnfYyvHYON7dHXjsPG9udrx2Bj+/O1Y/Dxxx/XlVdeqdatWysiIkIjRozQ9u3bz/q45nAcEnQa4KWXXlJWVpamTZumzZs3a9CgQRo+fLi+/fbbU9Z//fXXuu666zRo0CBt3rxZv/3tbzVx4kS98sorTs26det0yy23KDMzU5988okyMzM1cuRIbdiw4Xy15Whsf++//76Sk5P15ptvatOmTRoyZIhuuOEGbd682a2uTZs2Kisrc/sJDg4+Hy15aGyP9bZv3+62/ri4OOc+X34O//u//9utr507dyosLEw333yzW11zeQ6PHDmivn37au7cuQ2q97VjUGp8j752HDa2v3q+cgw2tj9fOwZXr16te+65R+vXr1dJSYmOHz+ulJQUHTly+m9UbzbHocFZ/fznPze//vWv3ca6detmpkyZcsr6yZMnm27durmNjR8/3lx11VXO7ZEjR5phw4a51aSmpppf/epXXlp1wzW2v1Pp0aOHyc3NdW4vWbLEhIaGemuJP1pje3z33XeNJFNZWXnaOW16DlesWGFcLpf55ptvnLHm9hzWk2RWrFhxxhpfOwZP1pAeT6W5H4f1GtKfrx2D/+pcnj9fOgaNMaaiosJIMqtXrz5tTXM5DjmjcxY1NTXatGmTUlJS3MZTUlK0du3aUz5m3bp1HvWpqan66KOPVFtbe8aa083ZVM6lv5PV1dXp0KFDCgsLcxs/fPiwOnXqpEsvvVRpaWke/9I8X35Mj/369VOHDh2UlJSkd9991+0+m57DxYsXa+jQoR6fKt5cnsPG8qVj0Fua+3F4rnzhGPQGXzsGq6qqJMnj9+1fNZfjkKBzFvv27dOJEyc8vhE9MjLS45vT65WXl5+y/vjx49q3b98Za043Z1M5l/5O9tRTT+nIkSMaOXKkM9atWzcVFBTo9ddf14svvqjg4GANHDhQ//jHP7y6/oY4lx47dOighQsX6pVXXtGrr76q+Ph4JSUl6f3333dqbHkOy8rK9NZbb+nOO+90G29Oz2Fj+dIx6C3N/ThsLF86Bn8sXzsGjTHKzs7W1VdfrV69ep22rrkchz79XVfnk8vlcrttjPEYO1v9yeONnbMpnetaXnzxReXk5OjPf/6zIiIinPGrrrpKV111lXN74MCBuvzyy5Wfn68//OEP3lt4IzSmx/j4eMXHxzu3ExMTtXPnTj355JP6t3/7t3Oas6md61oKCgrUtm1bjRgxwm28OT6HjeFrx+CP4UvHYUP54jF4rnztGLz33nv16aefas2aNWetbQ7HIWd0zqJ9+/by8/PzSJcVFRUeKbReVFTUKev9/f0VHh5+xprTzdlUzqW/ei+99JLGjh2rP/7xjxo6dOgZa1u0aKErr7zygvxL5Mf0+K+uuuoqt/Xb8BwaY/Tss88qMzNTgYGBZ6y9kM9hY/nSMfhj+cpx6A3N9Rj8MXztGLzvvvv0+uuv691339Wll156xtrmchwSdM4iMDBQCQkJKikpcRsvKSnRgAEDTvmYxMREj/ri4mJdccUVCggIOGPN6eZsKufSn/TDvyBHjx6twsJCXX/99WfdjjFGpaWl6tChw49ec2Oda48n27x5s9v6ff05lH64kuKLL77Q2LFjz7qdC/kcNpYvHYM/hi8dh97QXI/BH8NXjkFjjO699169+uqrWrVqlWJjY8/6mGZzHHrtbc0WW758uQkICDCLFy82n332mcnKyjKtWrVy3h0/ZcoUk5mZ6dR/9dVXJiQkxNx///3ms88+M4sXLzYBAQHmT3/6k1PzwQcfGD8/P/PEE0+Ybdu2mSeeeML4+/ub9evXN/v+CgsLjb+/v3n66adNWVmZ83PgwAGnJicnxxQVFZkvv/zSbN682YwZM8b4+/ubDRs2nPf+jGl8j7NnzzYrVqwwn3/+udmyZYuZMmWKkWReeeUVp8aXn8N6t912m+nfv/8p52xOz+GhQ4fM5s2bzebNm40kM2vWLLN582azY8cOY4zvH4PGNL5HXzsOG9ufrx2Dje2vnq8cg3fffbcJDQ017733ntvv29GjR52a5nocEnQa6OmnnzadOnUygYGB5vLLL3e7pG7UqFHmmmuucat/7733TL9+/UxgYKDp3LmzmTdvnsecL7/8somPjzcBAQGmW7dubgfw+daY/q655hojyeNn1KhRTk1WVpbp2LGjCQwMNBdffLFJSUkxa9euPY8deWpMj9OnTzddunQxwcHBpl27dubqq682f/nLXzzm9NXn0BhjDhw4YFq2bGkWLlx4yvma03NYf6nx6X7nbDgGG9ujrx2Hje3P147Bc/kd9aVj8FS9STJLlixxaprrcej6/xsAAACwDu/RAQAA1iLoAAAAaxF0AACAtQg6AADAWgQdAABgLYIOAACwFkEHAABYi6ADAAC86v3339cNN9yg6OhouVwuvfbaa42ewxijJ598Ul27dlVQUJBiYmKUl5fX6Hn49nIAAOBVR44cUd++fTVmzBj98pe/PKc5fvOb36i4uFhPPvmkevfuraqqKu3bt6/R8/DJyAAAoMm4XC6tWLFCI0aMcMZqamr00EMP6YUXXtCBAwfUq1cvTZ8+XYMHD5Ykbdu2TX369NGWLVsUHx//o7bPS1cAAOC8GjNmjD744AMtX75cn376qW6++WYNGzZM//jHPyRJK1eu1GWXXaY33nhDsbGx6ty5s+68807t37+/0dsi6AAAgPPmyy+/1IsvvqiXX35ZgwYNUpcuXTRp0iRdffXVWrJkiSTpq6++0o4dO/Tyyy/rueeeU0FBgTZt2qR///d/b/T2eI8OAAA4bz7++GMZY9S1a1e38erqaoWHh0uS6urqVF1dreeee86pW7x4sRISErR9+/ZGvZxF0AEAAOdNXV2d/Pz8tGnTJvn5+bndd9FFF0mSOnToIH9/f7cw1L17d0nSt99+S9ABAADNU79+/XTixAlVVFRo0KBBp6wZOHCgjh8/ri+//FJdunSRJH3++eeSpE6dOjVqe1x1BQAAvOrw4cP64osvJP0QbGbNmqUhQ4YoLCxMHTt21G233aYPPvhATz31lPr166d9+/Zp1apV6t27t6677jrV1dXpyiuv1EUXXaQ5c+aorq5O99xzj9q0aaPi4uJGrYWgAwAAvOq9997TkCFDPMZHjRqlgoIC1dbW6tFHH9Vzzz2nf/7znwoPD1diYqJyc3PVu3dvSdLu3bt13333qbi4WK1atdLw4cP11FNPKSwsrFFrIegAAABrcXk5AACwFkEHAABYi6ADAACsRdABAADWIugAAABrEXQAAIC1CDoAAMBaBB0AAGAtgg4AALAWQQcAAFiLoAMAAKz1/wCmILf3GcDJ2wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "QUERY = \"\"\"\n",
    "SELECT * FROM master\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "df.hist(column='ConvertedComp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#or\n",
    "QUERY = \"\"\"\n",
    "SELECT Respondent, ConvertedComp\n",
    "FROM master\n",
    "\"\"\"\n",
    "df_ConvertedComp = pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "# plot histogram\n",
    "df_ConvertedComp['ConvertedComp'].plot(kind='hist', figsize=(10, 5))\n",
    "# add a title to the histogram\n",
    "plt.title('Histogram of Converted Compensation')\n",
    "# add y-label\n",
    "plt.ylabel('Number of Respondents')\n",
    "# add x-label\n",
    "plt.xlabel('Annual USD')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Box Plots\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot a box plot of `Age.`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "QUERY = \"\"\"\n",
    "SELECT * FROM master\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "df.boxplot(column='ConvertedComp')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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f//pXDRgwwPpr3Pz589WoUSMtWLBA4eHhCgsL0913361jx445OHMA9pSSkiJJ1kKlb9++ysrKKjGUeM6cOdbtRcaOHau9e/cqISFBs2fP1tdff63XX3+9zOf++OOPbdbXrVunPXv2WH/kKU3R+T/66COb9vj4eJ08edImP09Pz4v2WNSoUUO33HKLxo0bp2PHjl1wVr++ffvqt99+048//mjTPmfOHFksFvXp0+eC5yqPpk2b6rHHHtMvv/yiuXPnSpJuuOEGHT16VPn5+dYeyOJLaT+Eubq6qmvXrtbZ5M7NPSEhQdnZ2db1zMxMzZ8/X5GRkXJ1dZWPj4+6du2qhIQEm/eyoKBAH330kRo0aKBmzZqV69qKPt9zP//PPvvMZgbAomvevHmzGjduXOo1X0pxdam9WYGBgRo9erT+/ve/a9u2bdaZF0sze/ZsVa9eXcuXL9fKlSttlldffVU5OTnW67/uuuskyfo5F/n0009t1qtVq6Y+ffpo06ZNatu2banvx7k9dwBQZg6946uKkWS+/PJL6/qOHTuMxWIx+/fvt4nr27eviYmJMcacvYnY09PTdO3a1axevdqsXLnStG/fvsSMTwCufEUTDXz44YfW2dEWLFhg7rrrrhITSxTNFli9enXz2muvmaVLl5pnnnnGuLu728wW+N5771mPWeSBBx4w7u7uJSZ8OF8+ISEhZsyYMWbx4sXmvffeM3Xr1jX169c3R48etcaeb7ZAd3d38+yzz5qlS5eaqVOnGl9fX5vZAov29fT0NJ9++qlZv369+fnnn40xZye0eOKJJ8wXX3xhVq1aZebMmWPCwsJMaGioOXPmzHnzLpotMCgoyMyaNcssWbLE/POf/zQWi6XEJA7lndCitNjMzEwTGBhomjdvbvLy8kxeXp4ZOHCgCQgIMJMmTTKLFi0yy5YtM7GxsWbUqFEmISHBGGPMO++8Y/7617+a2NhYs2LFCrNw4ULrDHlLliwxxpScLTAhIcF88cUXpnPnzsbNzc2sXbvWmkfRbIFdu3Y1n3/+ufnqq69M//79zztb4IYNG2yuY+XKlUaSWblypbXt9ttvNxaLxTz22GPW2QLr1atXYrbAAwcOmNDQUHPNNdeYGTNmmOXLl5tvvvnGvP3222bw4MFm3759Ntfz6quvlngfdc6kEEV5PvPMM+a7774zGzZsMDk5OaV+Nl26dDHPPfecmTdvnlm1apWZOXOmqVWrlunevft5Pk1jfvnlF5sZJM915swZExQUZJ1UJT8/3/To0cN4e3ub//znP2bp0qXmueeeM02aNDGSzKRJk6z7/vrrr6ZmzZqmS5cu5sMPPzQrV640X3/9tXnttdf4fgZwWSiuyuHc4uqzzz4zkoyPj4/N4ubmZkaMGGGMMeYf//iHkWQz+9UPP/xgJJmtW7dW9iUAuAylzRbo7+9v2rdvb1577bUS01AfPXrUjB071gQHBxs3NzcTGhpqYmJirHE///yz8fb2tvlHsDHGZGdnm44dO5qwsDCb6dTPl09iYqKJjo42NWrUMN7e3mbQoEFm+/btNrHnFlfGnC0AH3/8cRMaGmrc3d1NcHCwue+++0qcc/fu3SYqKspUr17dSLIeZ+rUqSYiIsLUrl3beHh4mIYNG5oxY8aY3bt3X/S93LNnj7n11ltNrVq1jLu7u2nevLl59dVXTX5+vk2cPYorY4x5++23jSTz3//+1xhzdor2KVOmmHbt2hkvLy/j6+trrrnmGnPvvfda37vk5GRz0003mdDQUOPp6Wlq1aplrrvuOvP1119bj1tUjLz88stm0qRJpkGDBsbDw8N06NDBWoAVt2bNGvOXv/zF+Pj4GG9vb9OtWzczf/58m5jyFFc5OTnmX//6l6lbt67x8vIy3bp1M8nJySY0NLTE39Xhw4fNP//5TxMeHm7c3d1NQECA6dixo/n3v/9tsrKybK6nLMVVTk6Oufvuu02dOnWMxWIxksyuXbtKff+feOIJ06lTJ1OzZk3j6elpGjVqZMaPH2+OHDlSarwxxjz88MMXna2xaObJH374wRhjzLFjx8ydd95patSoYapVq2b69etnvvvuOyPJTJ8+3WbfXbt2mbvuusvUr1/fuLu7mzp16piIiAibWTYBoLwsxhhT0b1jVwuLxaIvv/xSw4YNk3R26MFtt92mX3/91WZWJUny9fVVUFCQnnnmGb300kvKzc21bjt9+rSqVaumxMTEcs0IBgDFxcbG6s4779SGDRus9xmhcu3evVvh4eF69dVX9cgjjzg6HZTik08+0W233aZvv/1WERERjk4HwFWOCS0uQ4cOHZSfn69Dhw4pMjKy1JgePXooLy9PO3fuVOPGjSVJv//+uyQpNDS00nIFAOBqFxcXp/3796tNmzZycXHRd999p1dffVW9evWisAJQKSiuLiIrK0s7duywru/atUspKSkKCAhQs2bNdNttt+mOO+7Q1KlT1aFDBx05ckQrVqxQmzZtNGjQIF1//fW69tprddddd2natGkqKCjQuHHj1K9fv3LfvAwAAM6vevXq+vTTT/XCCy/o5MmTCg4O1ujRo/XCCy84OjUAToJhgReRlJRU6sxVo0aNUmxsrHJzc/XCCy9ozpw52r9/v2rVqqXu3btr0qRJatOmjaSz0+w++OCDSkxMlI+PjwYOHKipU6eWeBYHAAAAgKqL4goAAAAA7IDnXAEAAACAHVBcAQAAAIAdMKFFKQoKCnTgwAFVr15dFovF0ekAAAAAcBBjjDIzM1WvXj25uFy4b4riqhQHDhxQSEiIo9MAAAAAcIXYt2+fGjRocMEYiqtSVK9eXdLZN9DPz8/B2QAAAABwlIyMDIWEhFhrhAuhuCpF0VBAPz8/iisAAAAAZbpdiAktAAAAAMAOKK4AAAAAwA4orgAAAADADiiuAAAAAMAOKK4AAAAAwA4orgAAAADADiiuAAAAAMAOKK4AAAAAwA4orgAAAADADiiuAAAAAMAOHFpcTZ48WZ07d1b16tVVt25dDRs2TNu2bbvofqtWrVLHjh3l5eWlRo0aaebMmSVi4uPj1bJlS3l6eqply5b68ssvK+ISAABXqYCAAFksFusSEBDg6JQAAFc4hxZXq1at0rhx4/Tdd99p6dKlysvLU1RUlE6ePHnefXbt2qVBgwYpMjJSmzZt0sSJE/XPf/5T8fHx1pjk5GSNHDlS0dHR+umnnxQdHa0RI0bo+++/r4zLAgBUcRaLRcePH7dpO378uCwWi4MyAgBUBRZjjHF0EkUOHz6sunXratWqVerVq1epMY8//ri+/vprbdmyxdo2duxY/fTTT0pOTpYkjRw5UhkZGVq0aJE1ZsCAAapZs6bi4uIumkdGRob8/f2Vnp4uPz+/y7wqAEBVUpYC6gr66gQAVLDy1AZX1D1X6enpknTBoRfJycmKioqyaevfv782btyo3NzcC8asW7fOzhkDAK4mxb9/OnXqpJUrV+qTTz7RypUr1alTp1LjAAAo4uboBIoYYzRhwgT17NlTrVu3Pm9cWlqaAgMDbdoCAwOVl5enI0eOKDg4+LwxaWlppR4zJydHOTk51vWMjIzLuBIAQFVVfCjgkSNH1KdPH+t6WFhYqXEAABS5YnquHnjgAf38889lGrZ37pCNouEZxdtLiznfUI/JkyfL39/fuoSEhJQ3fQDAVaZNmzZKTk5WZmamkpOT1aZNG0enBAC4wl0RxdWDDz6or7/+WitXrlSDBg0uGBsUFFSiB+rQoUNyc3NTrVq1Lhhzbm9WkZiYGKWnp1uXffv2XcbVAACuBvPmzVO3bt3k6+urbt26ad68eY5OCQBwhXNocWWM0QMPPKCEhAStWLFC4eHhF92ne/fuWrp0qU1bYmKiOnXqJHd39wvGRERElHpMT09P+fn52SwAAOfj4vL/X4vdunWz2VZ8vXgcAABFHPrtMG7cOH300Uf65JNPVL16daWlpSktLU2nT5+2xsTExOiOO+6wro8dO1Z79uzRhAkTtGXLFn3wwQeaPXu2HnnkEWvMQw89pMTERL388svaunWrXn75ZS1btkwPP/xwZV4eAKCK+eijj6yvN2zYYPOcqw0bNpQaBwBAEYcWV++8847S09PVu3dvBQcHW5e5c+daY1JTU7V3717renh4uBYuXKikpCS1b99ezz//vN544w3dfPPN1piIiAh9+umn+vDDD9W2bVvFxsZq7ty56tq1a6VeHwCgagkODrZrHADAuVxRz7m6UvCcKwBwTvn5+WrSpInatGmjtWvX2swKWLNmTfXs2VObN2/W9u3b5erq6sBMAQCVpco+5woAAEdydXXV1KlTtWDBAvXs2VPr1q1TRkaG1q1bp549e2rBggWaMmUKhRUAoFRXzHOuAAC4EgwfPlxffPGF/vWvf9lMhBQeHq4vvvhCw4cPd2B2AIArGcMCS8GwQABAfn6+1qxZo9TUVAUHBysyMpIeKwBwQuWpDei5AgCgFK6ururdu7ej0wAAVCHccwUAAAAAdkBxBQAAAAB2QHEFAAAAAHZAcQUAAAAAdkBxBQAAAAB2QHEFAAAAAHZAcQUAAAAAdkBxBQAAAAB2QHEFAAAAAHbg5ugEAAC4EuXn52vNmjVKTU1VcHCwIiMj5erq6ui0AABXMHquAAA4R0JCgpo0aaI+ffro1ltvVZ8+fdSkSRMlJCQ4OjUAwBWMnisAAIpJSEjQLbfcooEDB6pjx446fvy4atasqdOnT+uWW27RF198oeHDhzs6TQDAFchijDGOTuJKk5GRIX9/f6Wnp8vPz8/R6QAAKkl+fr6aNGmi06dP6+DBgyW2BwYGqlq1atq+fTtDBAHASZSnNmBYIAAAhdasWaPdu3eXWlhJ0sGDB7Vr1y6tWbOmkjMDAFQFFFcAABTas2eP9bWnp6fNtuLrxeMAAChCcQUAQKHiE1b069dPycnJyszMVHJysvr161dqHAAARSiuAAAo9Oeff0qS/P399cUXXyg7O1vz589Xdna2vvjiC/n7+9vEAQBQHLMFAgBQyGKxSJLS09OtMwQW8fb2tq4XxQEAUBw9VwAAFOrbt6/19bmT6RZfLx4HAEARiisAAAoVL5oKCgr0t7/9TVOmTNHf/vY3FRQUlBoHAEARhgUCAFCo+LOrzpw5o08//VSffvrpBeMAAChCzxUAAIUOHTpk1zgAgHOhuAIAoFBwcLBd4wAAzoVhgQAAFGrbtq319YkTJ7Rp0yalpqYqODhYHTp0UI0aNUrEAQBQhJ4rAAAK3XjjjdbX0dHR8vT01A033CBPT09FR0eXGgcAQBGKKwAACu3du1eS9NJLL+mXX35RRESE/Pz8FBERoc2bN+v555+3iQMAoDiGBQIAUKhhw4bat2+fVq9erR07dmjNmjXWYYGRkZEaNGiQNQ4AgHNZzLlPSYQyMjLk7++v9PR0+fn5OTodAEAlSU9Pt95XdfLkSVWrVs267dSpU/Lx8ZF09n4sf39/R6QIAKhk5akNGBYIAEAhf39/NW7cWJLk4+Ojzp076+mnn1bnzp2thVXjxo0prAAApXJocbV69WoNGTJE9erVk8Vi0bx58y4YP3r0aFkslhJLq1atrDGxsbGlxmRnZ1fw1QAArgY7duxQYGCgJGnjxo16/vnntXHjRklSYGCgduzY4cj0AABXMIcWVydPnlS7du301ltvlSl++vTpSk1NtS779u1TQECA/vrXv9rE+fn52cSlpqbKy8urIi4BAHCVSUhI0MGDB0vddvDgQSUkJFRyRgCAqsKhE1oMHDhQAwcOLHO8v7+/zVCMefPm6fjx47rzzjtt4iwWi4KCguyWJwDAOeTn5+uuu+6SJLm4uKigoMC6rWj9rrvu0tChQ+Xq6uqoNAEAV6gqfc/V7Nmzdf311ys0NNSmPSsrS6GhoWrQoIFuuOEGbdq0yUEZAgCqkhUrVig9PV2SNGjQICUnJyszM1PJycnWmQLT09O1YsUKR6YJALhCVdniKjU1VYsWLdLdd99t037NNdcoNjZWX3/9teLi4uTl5aUePXpo+/bt5z1WTk6OMjIybBYAgPP573//K0lq3bq1EhISlJ2drfnz5ys7O1sJCQlq3bq1TRwAAMVV2edcxcbGqkaNGho2bJhNe7du3dStWzfreo8ePXTttdfqzTff1BtvvFHqsSZPnqxJkyZVZLoAgCpg9+7dkqRrr71WzZo1s65LUlhYmCIjI7V582abdgAAilTJnitjjD744ANFR0fLw8PjgrEuLi7q3LnzBXuuYmJilJ6ebl327dtn75QBAFVAWFiYJGnOnDlq3bq1zbDA1q1b63//+59NHAAAxVXJ4mrVqlXasWOHxowZc9FYY4xSUlIUHBx83hhPT0/5+fnZLAAA5xMdHW19bYwpsZQWBwBAEYcOC8zKyrJ5XsiuXbuUkpKigIAANWzYUDExMdq/f7/mzJljs9/s2bPVtWtX69j34iZNmqRu3bqpadOmysjI0BtvvKGUlBS9/fbbFX49AICqzc3t/78WFy5cqG+++ca67uLiUmocAABFHPrtsHHjRvXp08e6PmHCBEnSqFGjFBsbq9TUVO3du9dmn/T0dMXHx2v69OmlHvPEiRO65557lJaWJn9/f3Xo0EGrV69Wly5dKu5CAABXhUOHDllfF++pkmQzLXvxOAAAiljMud8eUEZGhvz9/ZWens4QQQBwIklJSerTp48mT56smTNnas+ePdZtYWFhuueeezRx4kStXLlSvXv3dlyiAIBKU57agHENAAAUioyMVFhYmNatW6ft27fr22+/VWpqqoKDg9WjRw/dfPPNCg8PV2RkpKNTBQBcgSiuAAAo5OrqqqlTp+qWW27RjTfeqP379+vYsWMKCAhQ/fr1tWTJEn3xxRdydXV1dKoAgCsQwwJLwbBAAHBuQUFBOnjwYIn2wMBApaWlOSAjAICjlKc2qJJTsQMAUFGaNGliLay6dOmiZ5991jop0sGDB9WkSRNHpgcAuILRc1UKeq4AwDmlp6erRo0akqSTJ0+qWrVq1m2nTp2Sj4+PpLMz0/r7+zsiRQBAJaPnCgCASzB48GBJ0oABA+Tp6amkpCTFxcUpKSlJnp6eioqKsokDAKA4JrQAAKBQ0bMVe/XqpSZNmmj37t3WbWFhYRozZowSExNLPIMRAACJnisAAKwaNmwoSZo4caLatGmj5ORkZWZmKjk5WW3atNFTTz1lEwcAQHHcc1UK7rkCAOd07Ngx1apVS5KUmZkpX19f67asrCxVr15dknT06FEFBAQ4JEcAQOXinisAAC7Bzz//bH1dvXp19e/fX2vWrFH//v2thdW5cQAAFKG4AgCgUGpqqiQpPDxckpSYmKhevXopMTHRpr0oDgCA4iiuAAAoFBwcLEn65JNPlJqaqsDAQHl6eiowMFCpqan6+OOPbeIAACiOe65KwT1XAOCc8vPz1aRJE50+fdr6IOHiAgMDVa1aNW3fvl2urq4OyBAAUNm45woAgEvg6uqqOnXq6ODBg7JYLIqOjlZKSoqio6NlsVh08OBB1a5dm8IKAFAqeq5KQc8VADin06dPq1q1anJzc1P9+vW1Z88e67awsDD9+eefysvL06lTp+Tt7e3ATAEAlYWeKwAALsGjjz4qSXrkkUf0+++/6/XXX9cDDzyg119/Xdu2bdOECRNs4gAAKM7N0QkAAHCl2L59uyQpJCREzZs31+7du63bpk+frn/96182cQAAFEfPFQAAhZo2bSpJGjdunNq0aaPk5GRlZmYqOTlZbdq00YMPPmgTBwBAcdxzVQruuQIA55SVlaXq1avLYrHo1KlT8vLysm7Lzs5WtWrVZIxRZmamfH19HZgpAKCycM8VAACXYOPGjZIkY4z8/f31+OOP6/fff9fjjz8uf39/Ff0eWRQHAEBxFFcAABRKTU2VJA0ePFhnzpzRK6+8oubNm+uVV17RmTNnNGjQIJs4AACKo7gCAKBQcHCwJOnJJ5/UqVOnNG7cOEVFRWncuHE6deqUnnzySZs4AACKo7gCAKBQZGSkwsLC9NJLLyk7O1spKSnasmWLUlJSlJ2drcmTJys8PFyRkZGOThUAcAViKnYAAAq5urpq6tSpuvnmmxUQEGBt37dvn3U9Pj5erq6ujkoRAHAFo+cKAIBiHnvsscvaDgBwXvRcAQBQKD09XTt37pR0durdH374QampqQoODlbHjh3l5+ennTt3Kj09Xf7+/g7OFgBwpaG4AgCg0ODBgyVJAwYMUPXq1dW7d2+b7VFRUUpMTNTgwYO1du1aB2QIALiSMSwQAIBCe/fulSQ988wzpW4vmi2wKA4AgOIorgAAKNSwYUNJ0qRJk0rd/sILL9jEAQBQnMUUPW4eVhkZGfL391d6err8/PwcnQ4AoJKkp6erRo0akqSTJ0+qWrVq1m2nTp2Sj4+PJOnEiRPccwUATqI8tQE9VwAAFPL391fjxo0lST4+Purfv7/WrFmj/v37Wwurxo0bU1gBAEpFz1Up6LkCAOfWpEkT66yBxTVu3Fg7duxwQEYAAEeh5woAgMuwY8cOHT16VK1bt1ZAQIBat26to0ePUlgBAC7IocXV6tWrNWTIENWrV08Wi0Xz5s27YHxSUpIsFkuJZevWrTZx8fHxatmypTw9PdWyZUt9+eWXFXgVAICrTUJCgjp27KjNmzfr2LFj2rx5szp27KiEhARHpwYAuII5tLg6efKk2rVrp7feeqtc+23btk2pqanWpWnTptZtycnJGjlypKKjo/XTTz8pOjpaI0aM0Pfff2/v9AEAV6GEhATdcsstatOmjZKTk5WZmank5GS1adNGt9xyCwUWAOC8rph7riwWi7788ksNGzbsvDFJSUnq06ePjh8/bp3N6VwjR45URkaGFi1aZG0bMGCAatasqbi4uDLlwj1XAOCc8vPz1aRJE7Vp00bz5s2Ti8v//wZZUFCgYcOGafPmzdq+fbtcXV0dmCkAoLJc9fdcdejQQcHBwerbt69Wrlxpsy05OVlRUVE2bf3799e6devOe7ycnBxlZGTYLAAA57NmzRrt3r1bEydOtCmsJMnFxUUxMTHatWuX1qxZ46AMAQBXsipVXAUHB2vWrFmKj49XQkKCmjdvrr59+2r16tXWmLS0NAUGBtrsFxgYqLS0tPMed/LkyfL397cuISEhFXYNAIArV2pqqiSpdevWpW4vai+KAwCgODdHJ1AezZs3V/Pmza3r3bt31759+zRlyhT16tXL2m6xWGz2M8aUaCsuJiZGEyZMsK5nZGRQYAGAEwoODpYkbd68Wd26dSuxffPmzTZxAAAUV6V6rkrTrVs3bd++3boeFBRUopfq0KFDJXqzivP09JSfn5/NAgBwPpGRkQoLC9NLL72k3NxcJSUlKS4uTklJScrNzdXkyZMVHh6uyMhIR6cKALgCVameq9Js2rTJ5hfE7t27a+nSpRo/fry1LTExUREREY5IDwBQhbi6umrq1Km65ZZb5O/vr9OnT1u3eXt7Kzs7W1988QWTWQAASuXQ4iorK8vmgYy7du1SSkqKAgIC1LBhQ8XExGj//v2aM2eOJGnatGkKCwtTq1atdObMGX300UeKj49XfHy89RgPPfSQevXqpZdffllDhw7VV199pWXLlmnt2rWVfn0AgKqptIl0LRZLqe0AABRx6FTsRVOrn2vUqFGKjY3V6NGjtXv3biUlJUmSXnnlFc2aNUv79++Xt7e3WrVqpZiYGA0aNMhm/y+++EJPPvmk/vjjDzVu3Fgvvviihg8fXua8mIodAJxT8anY4+Pj9e233yo1NVXBwcHq0aOHbr75ZqZiBwAnU57a4Ip5ztWVhOIKAJxT0Y9+ycnJaty4sbp06aLDhw+rTp06Wr9+vXbs2KGIiAitXLlSvXv3dnS6AIBKUJ7aoMrfcwUAgL0UTbHev39/m2cenjx5UnXr1rV+qTIVOwCgNFV+tkAAAOylaIKkosKqVatWWrBggVq1amXTzlTsAIDS0HMFAECha665xvr6+PHjqlGjhiRp8ODBOnHihGrWrFkiDgCAIvRcAQBQqHv37tbXd9xxh5KTk5WZmank5GTdcccdpcYBAFCE4goAgEKHDx+WJMXExOiXX35RRESE/Pz8FBERoc2bN+vRRx+1iQMAoDiGBQIAUKhOnTo6efKkvv76a+3YsUNr1qyxTsUeGRmpNm3aWOMAADgXPVcAABRav369JOnXX3+1mS1QOjuZxZYtW2ziAAAojp4rAAAK1alTx/osk4CAgFJj/P396bkCAJSKnisAAIr54IMPLms7AMB5UVwBAFAoPz9fY8eOlSRFRUUpODhYPj4+Cg4OVlRUlCTpvvvuU35+viPTBABcoRgWCABAoaSkJB0+fFg9e/bUokWL5OLy/79BFhQU6LrrrtPatWuVlJSkvn37OjBTAMCViJ4rAAAKJSUlSZImTZokY4ySkpIUFxenpKQkGWP0zDPP2MQBAFAcPVcAAJxjzZo1uuuuu7Rnzx5rW2hoqEaPHu24pAAAVzyLMcY4OokrTUZGhnW2KD8/P0enAwCoJMuXL9f1118vSfL29tbp06et24qvL1u2jGGBAOAkylMbMCwQAIBCkZGRslgskqScnBybbUXrFotFkZGRlZ4bAODKR3EFAEChNWvWqGhAx/kGdhhjtGbNmspMCwBQRVBcAQBQaMWKFZKkZs2aqWHDhjbbGjZsqGbNmtnEAQBQHMUVAACF9u3bJ0l68MEHtXPnTq1cuVKffPKJVq5cqR07dmjcuHE2cQAAFMdsgQAAFAoJCZEkffzxx7r//vvVu3dv67aCggLFxcXZxAEAUBw9VwAAFPrLX/4iSfruu+80dOhQJScnKzMzU8nJyRo6dKi+++47mzgAAIpjKvZSMBU7ADin/Px8BQcH6/Dhw+eNqVu3rg4cOCBXV9dKzAwA4ChMxQ4AwCVwdXXVzJkzLxjzzjvvUFgBAEpFz1Up6LkCAOdV9JyrC+GrEwCcR3lqAya0AACg0G+//WZ9vXv3bu3atUupqakKDg5WeHi4wsLCrHEtW7Z0UJYAgCsVPVeloOcKAJyTq6urCgoK5O7urjNnzpTY7uHhodzcXLm4uCg/P98BGQIAKhv3XAEAcAkKCgokSU888USp28ePH28TBwBAcfRclYKeKwBwTvRcAQDORc8VAACX4JdffpEk5ebm6s8//7TZ9ueffyo3N9cmDgCA4iiuAAAoVHySipCQEHl4eOjxxx+Xh4eHQkJCSo0DAKAIwwJLwbBAAHBuF5qOna9NAHAuDAsEAOAyGGP0/fff27R9//33FFYAgAuiuAIA4BxdunRR165dbdq6du2qLl26OCgjAEBVQHEFAEAxXbp00YYNGyRJ/fr103/+8x/169dPkrRhwwYKLADAeTm0uFq9erWGDBmievXqyWKxaN68eReMT0hIUL9+/VSnTh35+fmpe/fuWrJkiU1MbGysLBZLiSU7O7sCrwQAcDXIysqyFlahoaFaunSpnnjiCS1dulShoaGSzhZYWVlZjkwTAHCFcmhxdfLkSbVr105vvfVWmeJXr16tfv36aeHChfrhhx/Up08fDRkyRJs2bbKJ8/PzU2pqqs3i5eVVEZcAALiKREdHW1+3bdtWycnJyszMVHJystq2bVtqHAAARdwcefKBAwdq4MCBZY6fNm2azfpLL72kr776SvPnz1eHDh2s7RaLRUFBQfZKEwDgJHbs2CFJuu666zRv3jy5uJz9DbJbt26aN2+e+vTpo9WrV1vjAAAorkrfc1VQUKDMzEwFBATYtGdlZSk0NFQNGjTQDTfcUKJn61w5OTnKyMiwWQAAzsff31+S5O3tbS2siri4uFhHQRTFAQBQXJUurqZOnaqTJ09qxIgR1rZrrrlGsbGx+vrrrxUXFycvLy/16NFD27dvP+9xJk+eLH9/f+tS/EGRAADnMWbMGEnS4sWLlZGRoWnTpunBBx/UtGnTlJGRocTERJs4AACKu2IeImyxWPTll19q2LBhZYqPi4vT3Xffra+++krXX3/9eeMKCgp07bXXqlevXnrjjTdKjcnJyVFOTo51PSMjQyEhITxEGACcTFJSkvr06XPRuJUrV6p3794VnxAAwOHK8xBhh95zdanmzp2rMWPG6PPPP79gYSWdHcbRuXPnC/ZceXp6ytPT095pAgCqmMjISPn5+V1weLifn58iIyMrMSsAQFVxScMC16xZo9tvv13du3fX/v37JUn/+9//tHbtWrsmV5q4uDiNHj1an3zyiQYPHnzReGOMUlJSFBwcXOG5AQCqtvz8fOs06wMGDFCvXr3UsmVL9erVSwMGDJB09r7e/Px8R6YJALhClbu4io+PV//+/eXt7a1NmzZZh9NlZmbqpZdeKtexsrKylJKSopSUFEnSrl27lJKSor1790qSYmJidMcdd1jj4+LidMcdd2jq1Knq1q2b0tLSlJaWpvT0dGvMpEmTtGTJEv3xxx9KSUnRmDFjlJKSorFjx5b3UgEATmbGjBkqKCjQfffdp82bN2v16tX67bfftHr1am3evFljx45VQUGBZsyY4ehUAQBXoHIXVy+88IJmzpyp9957T+7u7tb2iIgI/fjjj+U61saNG9WhQwfrNOoTJkxQhw4d9PTTT0uSUlNTrYWWJL377rvKy8vTuHHjFBwcbF0eeugha8yJEyd0zz33qEWLFoqKitL+/fu1evVqdenSpbyXCgBwMjt37pQkvf/++/rzzz9ttv3555+aPXu2TRwAAMWV+56rbdu2qVevXiXa/fz8dOLEiXIdq3fv3rrQfBqxsbE260lJSRc95uuvv67XX3+9XHkAACBJjRs3liTl5uZKkoKDg/Xyyy/r8ccfV2pqqrW9KA4AgOLK3XMVHBxc6sMT165dq0aNGtklKQAAHGHo0KHW1wcPHtSBAwcUHR2tAwcO6ODBg6XGAQBQpNw9V/fee68eeughffDBB7JYLDpw4ICSk5P1yCOPWIfzAQBQFXXs2NH6uk2bNmrRooWMMbJYLNqyZYtN3LFjxxyRIgDgClbu4uqxxx5Tenq6+vTpo+zsbPXq1Uuenp565JFH9MADD1REjgAAVIrMzExJUp06dXTo0CEdOnTIZnvt2rV15MgRaxwAAMVd8kOET506pd9++00FBQVq2bKlfH197Z2bw5TnQWEAgKtHQECAjh8/LklydXVVjRo1lJ+fL1dXV504ccI6BXvNmjXpuQIAJ1EpDxGuVq2aOnXqdKm7AwBwxVm/fr2aNm0q6ewzr44ePXreOAAAzlXu4uqmm26SxWIp0W6xWOTl5aUmTZro1ltvVfPmze2SIAAAlWXatGk26+7u7rrhhhu0YMEC60yBRXFvvfVWJWcHALjSlXu2QH9/f61YsUI//vijtcjatGmTVqxYoby8PM2dO1ft2rXTt99+a/dkAQCoSL/99pvNem5urr788kubwqq0OAAApEsoroKCgnTrrbfqjz/+UHx8vBISErRz507dfvvtaty4sbZs2aJRo0bp8ccfr4h8AQCoMLt27bK+7tOnj9zczg7wcHNzU58+fUqNAwCgSLkntKhTp46+/fZbNWvWzKb9999/V0REhI4cOaJffvlFkZGR5X6o8JWCCS0AwDm1atWqTL1SLVu21K+//loJGQEAHK08tUG5e67y8vK0devWEu1bt261zqLk5eVV6n1ZAABcyWrWrGmz3rVrVyUmJqpr164XjAMAQLqECS2io6M1ZswYTZw4UZ07d5bFYtH69ev10ksv6Y477pAkrVq1Sq1atbJ7sgAAVKTo6Gibe4a///57RUVFlRoHAMC5yl1cvf766woMDNQrr7yigwcPSpICAwM1fvx4631WUVFRGjBggH0zBQCggi1evLjMcffee28FZwMAqGrKXVy5urrq3//+t/79738rIyNDkkqMPWzYsKF9sgMAoBKdPHnSrnEAAOdS7nuuivPz85Ofn5+OHz+uN998U+3bt7dTWgAAVL7GjRtbXw8YMECRkZFq2bKlIiMjbUZkFI8DAKBIuXuuilu2bJlmz56tefPmqXbt2ho+fLi98gIAoNLdeOONmjlzplxdXfXLL79o//791m0NGjSQq6ur8vPzdeONNzowSwDAlarcxdXevXv14Ycf6sMPP1RWVpaOHz+uzz77TDfffHNF5AcAQKUpeoRIfn6+TWElSX/++WeJOAAAiivzsMDPPvtMUVFRatGihTZv3qzp06frwIEDcnFxUYsWLSoyRwAAKkVwcLBd4wAAzqXMxdWtt96qTp06KS0tTZ9//rmGDh0qDw+PiswNAIBK1alTJ0mSxWLRsWPHNG7cOEVFRWncuHE6duyY9RmORXEAABRX5uLqrrvu0owZMzRgwADNnDlTx48fr8i8AACodE888YQkyRijv//971q0aJE2bNigRYsW6e9//7uMMTZxAAAUV+biatasWUpNTdU999yjuLg4BQcHa+jQoTLGqKCgoCJzBACgUmzfvl2SVL16dS1ZskR//PGHjh8/rj/++ENLliyRr6+vTRwAAMWVayp2b29vjRo1SqtWrdIvv/yili1bKjAwUD169NCtt96qhISEisoTAIAK17RpU0lSZmampLPPbRw6dKj1+Y1ZWVk2cQAAFGcxRWMcLlFBQYG++eYbzZ49W4sWLVJOTo69cnOYjIwM+fv7Kz09vcQDkgEAV6/9+/erQYMGkqT69evbzBhYfP3PP/9U/fr1HZIjAKBylac2uKyHCEuSi4uLhgwZonnz5mnfvn2XezgAABym+IOCDxw4oNtvv10//vijbr/9dh04cKDUOAAAilx2z9XViJ4rAHBOtWrV0rFjx1SjRo1Sn2VV1B4QEKCjR49WfoIAgEpXqT1XAABcLYq+NF1cXOTiYvsVWbyNH94AAKWhuAIAoNDEiRMlSceOHVPNmjX13nvvKTU1Ve+9955q1qypY8eO2cQBAFCcm6MTAADgShEaGmp9ffToUb333nsKCQnRe++9ZzMMsHgcAABF6LkCAKDQL7/8Iklyczv72+P69es1YMAArV+/XpLk6upqEwcAQHFl6rmqWbOmLBZLmQ5YNGQCAICqZvfu3ZKkvLw8RUVF6ZdfflFGRob8/PzUpk0bJSYm2sQBAFBcmYqradOmVXAaAAA4XuPGjSVJ/fv31/Lly5WXlydJOnnypA4fPqyoqCglJiZa4wAAKI6p2EvBVOwA4JzOnDkjb29vFRQUaNCgQWratKlOnz4tb29vbd++XQsXLpSLi4tOnz4tDw8PR6cLAKgE5akNLmtCi9OnTys3N9emjWIEAFBVubq6qnr16kpPT9fixYu1cOFC67aiadirV69uvfcKAIDiyj2hxcmTJ/XAAw+obt268vX1Vc2aNW2W8li9erWGDBmievXqyWKxaN68eRfdZ9WqVerYsaO8vLzUqFEjzZw5s0RMfHy8WrZsKU9PT7Vs2VJffvllufICADinNWvWKD09XZJUUFBgs61oPT09XWvWrKn03AAAV75yF1ePPfaYVqxYoRkzZsjT01Pvv/++Jk2apHr16mnOnDnlOtbJkyfVrl07vfXWW2WK37VrlwYNGqTIyEht2rRJEydO1D//+U/Fx8dbY5KTkzVy5EhFR0frp59+UnR0tEaMGKHvv/++XLkBAJzP/v377RoHAHAu5R4WOH/+fM2ZM0e9e/fWXXfdpcjISDVp0kShoaH6+OOPddttt5X5WAMHDtTAgQPLHD9z5kw1bNjQOsFGixYttHHjRk2ZMkU333yzpLOTb/Tr108xMTGSpJiYGK1atUrTpk1TXFxc2S8UAOB0Dh8+bNc4AIBzKXfP1bFjxxQeHi7p7P1VRVOv9+zZU6tXr7ZvdudITk5WVFSUTVv//v21ceNG671f54tZt25dheYGAKj6XnzxRZv1kJAQde7cWSEhIReMAwBAuoTiqlGjRtbne7Rs2VKfffaZpLM9WjVq1LBnbiWkpaUpMDDQpi0wMFB5eXk6cuTIBWPS0tLOe9ycnBxlZGTYLAAA51P0XVJk37592rBhg/bt23fBOAAApEsoru6880799NNPks4OuSu692r8+PF69NFH7Z7guc59mHHRTPLF20uLudBDkCdPnix/f3/rcu4vlAAAAABwMeW+52r8+PHW13369NHWrVu1ceNGNW7cWO3atbNrcucKCgoq0QN16NAhubm5qVatWheMObc3q7iYmBhNmDDBup6RkUGBBQBOztXVVQUFBdYf6FxcXJSfn+/otAAAV7By91wVDQks0rBhQw0fPrzCCytJ6t69u5YuXWrTlpiYqE6dOsnd3f2CMREREec9rqenp/z8/GwWAIBzy8/Pt46OMMZQWAEALuqS7rnq2bOn3n33XetkFpcqKytLKSkpSklJkXR2qvWUlBTt3btX0tkepTvuuMMaP3bsWO3Zs0cTJkzQli1b9MEHH2j27Nl65JFHrDEPPfSQEhMT9fLLL2vr1q16+eWXtWzZMj388MOXlSsA4OrXuHFju8YBAJxLuYurjRs3qnv37nrhhRdUr149DR06VJ9//rlycnLKffKNGzeqQ4cO6tChgyRpwoQJ6tChg55++mlJUmpqqrXQkqTw8HAtXLhQSUlJat++vZ5//nm98cYb1mnYJSkiIkKffvqpPvzwQ7Vt21axsbGaO3euunbtWu78AADOxcWlbF+LZY0DADgXiyka81BOxhglJSXpk08+UXx8vPLz83XzzTfrgw8+sHeOlS4jI0P+/v5KT09niCAAOJELTX50rkv8+gQAVDHlqQ0uubgq7scff9SYMWP0888/XxVj0imuAMA5UVwBAM5Vntrgksc17Nu3T6+88orat2+vzp07y8fHR2+99dalHg4AAAAAqrRyT8U+a9Ysffzxx/r222/VvHlz3XbbbZo3b57CwsIqID0AACqPu7u7cnNzyxQHAMC5yl1cPf/88/rb3/6m6dOnq3379hWQEgAAjuHh4VGm4srDw6MSsgEAVDXlKq7y8vJ055136h//+AcP2QUAXHVOnTpl1zgAgHMp1z1Xbm5uev3116+KSSsAADhXWSe0KM/EFwAA51HuCS369u2rpKSkCkgFAADHqlOnjvW1p6enzbbi68XjAAAoUu57rgYOHKiYmBht3rxZHTt2lI+Pj832G2+80W7JAQBQmXx9fXXw4EFJUk5Ojnx9fRUWFqbdu3crKyvLJg4AgHOVu7i67777JEmvvfZaiW0Wi4UhgwCAKsvf399mPSsrS5s3b75oHAAA0iUMCywoKDjvQmEFAKjKrr/+ervGAQCcyyU/RFiSsrOz7ZUHAAAO95e//MWucQAA51Lu4io/P1/PP/+86tevL19fX/3xxx+SpKeeekqzZ8+2e4IAAFSWlJQUu8YBAJxLuYurF198UbGxsXrllVdsHqLYpk0bvf/++3ZNDgCAyjR//ny7xgEAnEu5i6s5c+Zo1qxZuu222+Tq6mptb9u2rbZu3WrX5AAAqEwFBQV2jQMAOJdyF1f79+9XkyZNSrQXFBQoNzfXLkkBAOAIAQEBdo0DADiXchdXrVq10po1a0q0f/755+rQoYNdkgIAwBGMMXaNAwA4l3I/5+qZZ55RdHS09u/fr4KCAiUkJGjbtm2aM2eOFixYUBE5AgBQKbZs2WLXOACAcyl3z9WQIUM0d+5cLVy4UBaLRU8//bS2bNmi+fPnq1+/fhWRIwAAlWLPnj12jQMAOBeLYWxDCRkZGfL391d6err8/PwcnQ4AoJJYLJYyx/L1CQDOoTy1Qbl7rho1aqSjR4+WaD9x4oQaNWpU3sMBAAAAwFWh3MXV7t27lZ+fX6I9JydH+/fvt0tSAAA4gru7u13jAADOpcwTWnz99dfW10uWLJG/v791PT8/X8uXL1dYWJhdkwMAAACAqqLMxdWwYcMknR2PPmrUKJtt7u7uCgsL09SpU+2aHAAAlam0kRmXEwcAcC5lLq6KnkYfHh6uDRs2qHbt2hWWFAAAjlD0XWevOACAcyn3c6527dpVEXkAAAAAQJVW7uJKkpYvX67ly5fr0KFDJX69++CDD+ySGAAAlc3FxaVMvVIuLuWeDwoA4ATK/e0wadIkRUVFafny5Tpy5IiOHz9uswAAUFWFh4fbNQ4A4FzK3XM1c+ZMxcbGKjo6uiLyAQDAYfLy8uwaBwBwLuXuuTpz5owiIiIqIhcAABzKGGPXOACAcyl3cXX33Xfrk08+qYhcAABwKKZiBwBcjnIPC8zOztasWbO0bNkytW3btsRT6l977TW7JQcAQGU6cuSIXeMAAM6l3MXVzz//rPbt20uSNm/ebLPNYrHYJSkAABwhJyfHrnEAAOdS7uJq5cqVFZEHAAAAAFRpDn9Qx4wZMxQeHi4vLy917NhRa9asOW/s6NGjZbFYSiytWrWyxsTGxpYak52dXRmXAwCowqpVq2bXOACAcylzz9Xw4cPLFJeQkFDmk8+dO1cPP/ywZsyYoR49eujdd9/VwIED9dtvv6lhw4Yl4qdPn67//Oc/1vW8vDy1a9dOf/3rX23i/Pz8tG3bNps2Ly+vMucFAHBONWrU0KlTp8oUBwDAucpcXPn7+9v95K+99prGjBmju+++W5I0bdo0LVmyRO+8844mT55cag7F85g3b56OHz+uO++80ybOYrEoKCjI7vkCAK5uBw8etGscAMC5lLm4+vDDD+164jNnzuiHH37QE088YdMeFRWldevWlekYs2fP1vXXX6/Q0FCb9qysLIWGhio/P1/t27fX888/rw4dOtgtdwDA1Ymp2AEAl6PcE1rYy5EjR5Sfn6/AwECb9sDAQKWlpV10/9TUVC1atKjEM7euueYaxcbGqk2bNsrIyND06dPVo0cP/fTTT2ratGmpx8rJybGZ+SkjI+MSrggAUNW5uLiooKCgTHEAAJzL4d8O507fbowp05TusbGxqlGjhoYNG2bT3q1bN91+++1q166dIiMj9dlnn6lZs2Z68803z3usyZMnW4cc+vv7KyQk5JKuBQBQtdWtW9eucQAA5+Kw4qp27dpydXUt0Ut16NChEr1Z5zLG6IMPPlB0dLQ8PDwuGOvi4qLOnTtr+/bt542JiYlRenq6ddm3b1/ZLwQAcNU4d5j55cYBAJyLw4orDw8PdezYUUuXLrVpX7p0qSIiIi6476pVq7Rjxw6NGTPmoucxxiglJUXBwcHnjfH09JSfn5/NAgBwPrm5uXaNAwA4F4fdcyVJEyZMUHR0tDp16qTu3btr1qxZ2rt3r8aOHSvpbI/S/v37NWfOHJv9Zs+era5du6p169Yljjlp0iR169ZNTZs2VUZGht544w2lpKTo7bffrpRrAgBUXWW9l4p7rgAApXFocTVy5EgdPXpUzz33nFJTU9W6dWstXLjQOtwiNTVVe/futdknPT1d8fHxmj59eqnHPHHihO655x6lpaXJ399fHTp00OrVq9WlS5cKvx4AQNW2a9cuu8YBAJyLxRhjHJ3ElSYjI0P+/v5KT09niCAAOJFq1arp9OnTF43z9vYu08OGAQBVX3lqA8Y1AABQqCyFVXniAADOheIKAAAAAOyA4goAgEJlec5ieeIAAM6F4goAgEJlvQ2Z25UBAKWhuAIAAAAAO6C4AgCgkJtb2Z5QUtY4AIBzobgCAKDQiBEj7BoHAHAuFFcAABRydXW1axwAwLnwEOFS8BBhAHBOHh4eys3NvWicu7u7zpw5UwkZAQAcjYcIAwBwCcpSWJUnDgDgXCiuAAAAAMAOKK4AACjEPVcAgMtBcQUAQCGLxWLXOACAc6G4AgCgkItL2b4WyxoHAHAufDsAAFCorDMAMlMgAKA0FFcAAAAAYAcUVwAAAABgBxRXAAAAAGAHFFcAAAAAYAcUVwAAAABgBxRXAAAAAGAHFFcAAAAAYAcUVwAAFKpXr55d4wAAzoXiCgCAQsePH7drHADAuVBcAQBQ6MyZM3aNAwA4F4orAAAKubq62jUOAOBcKK4AACgUGBho1zgAgHOhuAIAoJCnp6dd4wAAzoXiCgCAQn/88Ydd4wAAzoXiCgCAQgUFBXaNAwA4F4orAAAAALADiisAAApxzxUA4HJQXAEAUIjiCgBwORxeXM2YMUPh4eHy8vJSx44dtWbNmvPGJiUlyWKxlFi2bt1qExcfH6+WLVvK09NTLVu21JdfflnRlwEAuAo0atTIrnEAAOfi0OJq7ty5evjhh/Xvf/9bmzZtUmRkpAYOHKi9e/decL9t27YpNTXVujRt2tS6LTk5WSNHjlR0dLR++uknRUdHa8SIEfr+++8r+nIAAFVcSEiIXeMAAM7FocXVa6+9pjFjxujuu+9WixYtNG3aNIWEhOidd9654H5169ZVUFCQdXF1dbVumzZtmvr166eYmBhdc801iomJUd++fTVt2rQKvhoAQFU3cOBAu8YBAJyLw4qrM2fO6IcfflBUVJRNe1RUlNatW3fBfTt06KDg4GD17dtXK1eutNmWnJxc4pj9+/e/4DFzcnKUkZFhswAAnM+bb75p1zgAgHNxWHF15MgR5efnKzAw0KY9MDBQaWlppe4THBysWbNmKT4+XgkJCWrevLn69u2r1atXW2PS0tLKdUxJmjx5svz9/a0Lwz0AwDnt2rXLrnEAAOfi5ugELBaLzboxpkRbkebNm6t58+bW9e7du2vfvn2aMmWKevXqdUnHlKSYmBhNmDDBup6RkUGBBQBO6ELfFZcSBwBwLg7ruapdu7ZcXV1L9CgdOnSoRM/ThXTr1k3bt2+3rgcFBZX7mJ6envLz87NZAADOp27dunaNAwA4F4cVVx4eHurYsaOWLl1q07506VJFRESU+TibNm1ScHCwdb179+4ljpmYmFiuYwIAnNOff/5p1zgAgHNx6LDACRMmKDo6Wp06dVL37t01a9Ys7d27V2PHjpV0drje/v37NWfOHElnZwIMCwtTq1atdObMGX300UeKj49XfHy89ZgPPfSQevXqpZdffllDhw7VV199pWXLlmnt2rUOuUYAQNWRn59v1zgAgHNxaHE1cuRIHT16VM8995xSU1PVunVrLVy4UKGhoZKk1NRUm2denTlzRo888oj2798vb29vtWrVSt98840GDRpkjYmIiNCnn36qJ598Uk899ZQaN26suXPnqmvXrpV+fQAAAACch8UYYxydxJUmIyND/v7+Sk9P5/4rAHAi1atXV1ZW1kXjfH19lZmZWQkZAQAcrTy1gUMfIgwAwJXk1KlTdo0DADgXiisAAAoVFBTYNQ4A4FworgAAKOTq6mrXOACAc6G4AgCgUFBQkF3jAADOheIKAIBCeXl5do0DADgXiisAAAq5u7vbNQ4A4FworgAAKHT06FG7xgEAnAvFFQAAhRgWCAC4HBRXAAAUys3NtWscAMC5UFwBAAAAgB1QXAEAAACAHVBcAQAAAIAdUFwBAAAAgB1QXAEAAACAHVBcAQAAAIAdUFwBAAAAgB1QXAEAAACAHVBcAQBQyMvLy65xAADnQnEFAEChwMBAu8YBAJwLxRUAAIXS09PtGgcAcC4UVwAAFMrIyLBrHADAuVBcAQBQqKCgwK5xAADnQnEFAEAhF5eyfS2WNQ4A4Fz4dgAAoJC3t7dd4wAAzoXiCgCAQjk5OXaNAwA4F4orAAAKubq62jUOAOBcKK4AACh05swZu8YBAJwLxRUAAIWMMXaNAwA4F4orAAAAALADiisAAAAAsAOKKwAACoWEhNg1DgDgXCiuAAAodPr0abvGAQCcC8UVAACFMjMz7RoHAHAuDi+uZsyYofDwcHl5ealjx45as2bNeWMTEhLUr18/1alTR35+furevbuWLFliExMbGyuLxVJiyc7OruhLAQBUcTxEGABwORxaXM2dO1cPP/yw/v3vf2vTpk2KjIzUwIEDtXfv3lLjV69erX79+mnhwoX64Ycf1KdPHw0ZMkSbNm2yifPz81NqaqrN4uXlVRmXBAAAAMBJWYwDH9bRtWtXXXvttXrnnXesbS1atNCwYcM0efLkMh2jVatWGjlypJ5++mlJZ3uuHn74YZ04ceKS88rIyJC/v7/S09Pl5+d3yccBAFQtFoulzLE86woAnEN5agOH9VydOXNGP/zwg6Kiomzao6KitG7dujIdo6CgQJmZmQoICLBpz8rKUmhoqBo0aKAbbrihRM/WuXJycpSRkWGzAAAAAEB5OKy4OnLkiPLz8xUYGGjTHhgYqLS0tDIdY+rUqTp58qRGjBhhbbvmmmsUGxurr7/+WnFxcfLy8lKPHj20ffv28x5n8uTJ8vf3ty5MsQsAAACgvBw+ocW5QzCMMWUalhEXF6dnn31Wc+fOVd26da3t3bp10+2336527dopMjJSn332mZo1a6Y333zzvMeKiYlRenq6ddm3b9+lXxAAAAAAp+TmqBPXrl1brq6uJXqpDh06VKI361xz587VmDFj9Pnnn+v666+/YKyLi4s6d+58wZ4rT09PeXp6lj15AAAAADiHw3quPDw81LFjRy1dutSmfenSpYqIiDjvfnFxcRo9erQ++eQTDR48+KLnMcYoJSVFwcHBl50zAAAAAJyPw3quJGnChAmKjo5Wp06d1L17d82aNUt79+7V2LFjJZ0drrd//37NmTNH0tnC6o477tD06dPVrVs3a6+Xt7e3/P39JUmTJk1St27d1LRpU2VkZOiNN95QSkqK3n77bcdcJAAAAACn4NDiauTIkTp69Kiee+45paamqnXr1lq4cKFCQ0MlSampqTbPvHr33XeVl5encePGady4cdb2UaNGKTY2VpJ04sQJ3XPPPUpLS5O/v786dOig1atXq0uXLpV6bQAAAACci0Ofc3Wl4jlXAHDlOX0mXzsPZ1XoOdo0qFHm2F/+PFFheUhS4zq+8vZwrdBzAAAurjy1gUN7rgAAKKudh7N0w5trHZ2GVUXnsuDBnmpd379CzwEAsC96rkpBzxUAXHkqpecqpKZUlq9Fi0W/7DteobnQcwUAVwZ6rgAAVx1vD9cK78n5dfNmtWrVqkxxLelVAgCcw+EPEQYA4ErRsmVLu8YBAJwLxRUAAMVcbLQ8o+kBAOdDcQUAwDmMMfr111/l4nL2a9LFxUW//vorhRUA4IIorgAAKEXLli31095jCn18gX7ae4yhgACAi6K4AgAAAAA7oLgCAAAAADuguAIAAAAAO6C4AgAAAAA7oLgCAAAAADuguAIAAAAAO6C4AgAAAAA7oLgCAAAAADuguAIAAAAAO6C4AgAAAAA7oLgCAAAAADtwc3QCAICqadeRkzqZk+foNCrUjkNZNv+9mvl4uim8to+j0wCAKo3iCgBQbruOnFSfKUmOTqPSPDw3xdEpVIqVj/SmwAKAy0BxBQAot6Ieq2kj26tJXV8HZ1NxsnPz9efx02pQ01te7q6OTqfC7DiUpYfnplz1PZEAUNEorgAAl6xJXV+1ru/v6DQqVKcwR2cAAKgqmNACAAAAAOyA4goAAAAA7IDiCgAAAADsgOIKAAAAAOyACS0AAOWWk58tF6/92pWxTS5eV+9sgc5iV0aWXLz2Kyc/W9LVPUEJAFQkiisAQLkdOLlHPuFvauJ6R2cCe/EJlw6cbK+OCnR0KgBQZVFcAQDKrZ5PqE7uelDTR7ZX46v4OVfOYuehLD00N0X1+oQ6OhUAqNIorgAA5ebp6qWC7PoK92uulrUYRlbVFWSnqyD7sDxdvRydCgBUaUxoAQAAAAB2QM8VAKDcTufmS5I27093cCYVKzs3X38eP60GNb3l5e7q6HQqzI5DWY5OAQCuCg4vrmbMmKFXX31VqampatWqlaZNm6bIyMjzxq9atUoTJkzQr7/+qnr16umxxx7T2LFjbWLi4+P11FNPaefOnWrcuLFefPFF3XTTTRV9KQDgNHYW/mP8iYRfHJwJ7MnH0+H/LACAKs2h/xedO3euHn74Yc2YMUM9evTQu+++q4EDB+q3335Tw4YNS8Tv2rVLgwYN0j/+8Q999NFH+vbbb3X//ferTp06uvnmmyVJycnJGjlypJ5//nnddNNN+vLLLzVixAitXbtWXbt2rexLBICrUlSrIElS47q+8r7Ke3QenpuiaSPbq8lVPnGHj6ebwmv7ODoNAKjSLMYY46iTd+3aVddee63eeecda1uLFi00bNgwTZ48uUT8448/rq+//lpbtmyxto0dO1Y//fSTkpOTJUkjR45URkaGFi1aZI0ZMGCAatasqbi4uDLllZGRIX9/f6Wnp8vPz+9SLw8AUMVt3p+uG95cqwUP9lTr+kzcAQDOqDy1gcMmtDhz5ox++OEHRUVF2bRHRUVp3bp1pe6TnJxcIr5///7auHGjcnNzLxhzvmMCAAAAgD04bFjgkSNHlJ+fr8BA24cVBgYGKi0trdR90tLSSo3Py8vTkSNHFBwcfN6Y8x1TknJycpSTk2Ndz8jIKO/lAAAq2Okz+dp5uHInXiia6MEREz40ruMrb4+rd8glAFyNHH7nqsVisVk3xpRou1j8ue3lPebkyZM1adKkMucMAKh8Ow9n6YY31zrk3A/PTan0czIUEQCqHocVV7Vr15arq2uJHqVDhw6V6HkqEhQUVGq8m5ubatWqdcGY8x1TkmJiYjRhwgTrekZGhkJCQsp1PQCAitW4jq8WPNizUs/pyKnYG9e5uifQAICrkcOKKw8PD3Xs2FFLly61mSZ96dKlGjp0aKn7dO/eXfPnz7dpS0xMVKdOneTu7m6NWbp0qcaPH28TExERcd5cPD095enpeTmXAwCoYN4erg7pyekUVumnBABUUQ4dFjhhwgRFR0erU6dO6t69u2bNmqW9e/dan1sVExOj/fv3a86cOZLOzgz41ltvacKECfrHP/6h5ORkzZ4922YWwIceeki9evXSyy+/rKFDh+qrr77SsmXLtHatY4aSAAAAAHAODi2uRo4cqaNHj+q5555TamqqWrdurYULFyo0NFSSlJqaqr1791rjw8PDtXDhQo0fP15vv/226tWrpzfeeMP6jCtJioiI0Keffqonn3xSTz31lBo3bqy5c+fyjCsAAAAAFcqhz7m6UvGcKwAAAABSFXnOFQAAAABcTSiuAAAAAMAOKK4AAAAAwA4orgAAAADADiiuAAAAAMAOKK4AAAAAwA4orgAAAADADiiuAAAAAMAOKK4AAAAAwA4orgAAAADADtwcncCVyBgjScrIyHBwJgAAAAAcqagmKKoRLoTiqhSZmZmSpJCQEAdnAgAAAOBKkJmZKX9//wvGWExZSjAnU1BQoAMHDqh69eqyWCyOTgcA4CAZGRkKCQnRvn375Ofn5+h0AAAOYIxRZmam6tWrJxeXC99VRXEFAMB5ZGRkyN/fX+np6RRXAICLYkILAAAAALADiisAAAAAsAOKKwAAzsPT01PPPPOMPD09HZ0KAKAK4J4rAAAAALADeq4AAAAAwA4orgAAAADADiiuAAAAAMAOKK4AALCjpKQkWSwWnThxwtGpAAAqGcUVAMAu0tLS9OCDD6pRo0by9PRUSEiIhgwZouXLlzs6tYuq6ILIGKNZs2apa9eu8vX1VY0aNdSpUydNmzZNp06dqpBzAgAqn5ujEwAAVH27d+9Wjx49VKNGDb3yyitq27atcnNztWTJEo0bN05bt251dIrnlZubW+HniI6OVkJCgp588km99dZbqlOnjn766SdNmzZNYWFhGjZsWIXnAACoePRcAQAu2/333y+LxaL169frlltuUbNmzdSqVStNmDBB3333nSRp7969Gjp0qHx9feXn56cRI0bo4MGD1mM8++yzat++vf73v/8pLCxM/v7++tvf/qbMzExJ0rvvvqv69euroKDA5tw33nijRo0aZV2fP3++OnbsKC8vLzVq1EiTJk1SXl6edbvFYtHMmTM1dOhQ+fj46O6771afPn0kSTVr1pTFYtHo0aMlne1xeuWVV9SoUSN5e3urXbt2+uKLL2zOv3DhQjVr1kze3t7q06ePdu/ebbP9s88+08cff6y4uDhNnDhRnTt3VlhYmIYOHaoVK1ZYz11QUKDnnntODRo0kKenp9q3b6/Fixdbj7N7925ZLBZ99tlnioyMlLe3tzp37qzff/9dGzZsUKdOneTr66sBAwbo8OHD1v1Gjx6tYcOGadKkSapbt678/Px077336syZM+X6jAEAZWAAALgMR48eNRaLxbz00kvnjSkoKDAdOnQwPXv2NBs3bjTfffedufbaa811111njXnmmWeMr6+vGT58uPnll1/M6tWrTVBQkJk4caL1PB4eHmbZsmXWfY4dO2Y8PDzMkiVLjDHGLF682Pj5+ZnY2Fizc+dOk5iYaMLCwsyzzz5r3UeSqVu3rpk9e7bZuXOn2b17t4mPjzeSzLZt20xqaqo5ceKEMcaYiRMnmmuuucYsXrzY7Ny503z44YfG09PTJCUlGWOM2bt3r/H09DQPPfSQ2bp1q/noo49MYGCgkWSOHz9ujDHmxhtvNM2bN7/o+/jaa68ZPz8/ExcXZ7Zu3Woee+wx4+7ubn7//XdjjDG7du0ykqz5/Pbbb6Zbt27m2muvNb179zZr1641P/74o2nSpIkZO3as9bijRo0yvr6+ZuTIkWbz5s1mwYIFpk6dOtb3FQBgPxRXAIDL8v333xtJJiEh4bwxiYmJxtXV1ezdu9fa9uuvvxpJZv369caYs8VVtWrVTEZGhjXm0UcfNV27drWu33jjjeauu+6yrr/77rsmKCjI5OXlGWOMiYyMLFHk/e9//zPBwcHWdUnm4YcftolZuXKlTUFkjDFZWVnGy8vLrFu3ziZ2zJgx5u9//7sxxpiYmBjTokULU1BQYN3++OOP2xyrRYsW5sYbbzzve1OkXr165sUXX7Rp69y5s7n//vuNMf9fXL3//vvW7XFxcUaSWb58ubVt8uTJNsXcqFGjTEBAgDl58qS17Z133jG+vr4mPz//onkBAMqOYYEAgMtijJF0drjd+WzZskUhISEKCQmxtrVs2VI1atTQli1brG1hYWGqXr26dT04OFiHDh2yrt92222Kj49XTk6OJOnjjz/W3/72N7m6ukqSfvjhBz333HPy9fW1Lv/4xz+UmppqM3FEp06dLnpdv/32m7Kzs9WvXz+b482ZM0c7d+60Xle3bt1srr179+4l3p8LvTeSlJGRoQMHDqhHjx427T169LB5fySpbdu21teBgYGSpDZt2ti0FX/PJKldu3aqVq2aTY5ZWVnat2/fBfMCAJQPE1oAAC5L06ZNZbFYtGXLlvNOzHC+AuPcdnd3d5vtFovF5h6rIUOGqKCgQN988406d+6sNWvW6LXXXrNuLygo0KRJkzR8+PAS5/Ly8rK+9vHxueh1FZ33m2++Uf369W22eXp6WvO/mGbNmpUokM7n3PeotPet+HtUtO3ctnPvSyvr+QAAl4eeKwDAZQkICFD//v319ttv6+TJkyW2nzhxQi1bttTevXttekp+++03paenq0WLFmU+l7e3t4YPH26dIKJZs2bq2LGjdfu1116rbdu2qUmTJiUWF5fzf+V5eHhIkvLz861tLVu2lKenp/bu3VviWEU9cC1btrRO2FHk3PVbb71Vv//+u7766qsS5zXGKD09XX5+fqpXr57Wrl1rs33dunXlen/O56efftLp06dtcvT19VWDBg0u+9gAgP9HcQUAuGwzZsxQfn6+unTpovj4eG3fvl1btmzRG2+8oe7du+v6669X27Ztddttt+nHH3/U+vXrdccdd+i6664r0xC94m677TZ98803+uCDD3T77bfbbHv66ac1Z84cPfvss/r111+1ZcsWzZ07V08++eQFjxkaGiqLxaIFCxbo8OHDysrKUvXq1fXII49o/Pjx+u9//6udO3dq06ZNevvtt/Xf//5XkjR27Fjt3LlTEyZM0LZt2/TJJ58oNjbW5tgjRozQyJEj9fe//12TJ0/Wxo0btWfPHi1YsEDXX3+9Vq5cKUl69NFH9fLLL2vu3Lnatm2bnnjiCaWkpOihhx4q1/tTmjNnzmjMmDH67bfftGjRIj3zzDN64IEHLlhwAgAugQPv9wIAXEUOHDhgxo0bZ0JDQ42Hh4epX7++ufHGG83KlSuNMcbs2bPH3HjjjcbHx8dUr17d/PWvfzVpaWnW/Z955hnTrl07m2O+/vrrJjQ01KYtLy/PBAcHG0lm586dJfJYvHixiYiIMN7e3sbPz8906dLFzJo1y7pdkvnyyy9L7Pfcc8+ZoKAgY7FYzKhRo4wxZ2c5nD59umnevLlxd3c3derUMf379zerVq2y7jd//nzTpEkT4+npaSIjI80HH3xQYnKM/Px8884775jOnTubatWqGT8/P9OxY0czffp0c+rUKWvMpEmTTP369Y27u7tp166dWbRokfUYRRNabNq0ydpW2kQcH374ofH397eujxo1ygwdOtQ8/fTTplatWsbX19fcfffdJjs7u8R7AAC4PBZjyjBgHAAAVEmjR4/WiRMnNG/ePEenAgBXPcYDAAAAAIAdUFwBAAAAgB0wLBAAAAAA7ICeKwAAAACwA4orAAAAALADiisAAAAAsAOKKwAAAACwA4orAAAAALADiisAAAAAsAOKKwAAAACwA4orAAAAALADiisAAAAAsIP/A+ndis2z5CuFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#or\n",
    "QUERY = \"\"\"\n",
    "SELECT Respondent, ConvertedComp\n",
    "FROM master\n",
    "\"\"\"\n",
    "df_ConvertedComp = pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "# plot histogram\n",
    "df_ConvertedComp['ConvertedComp'].plot(kind='box', figsize=(10, 5))\n",
    "plt.title(\"Box plots of Respondent's Age\")\n",
    "plt.ylabel('Interval Age')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing relationships in data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scatter Plots\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a scatter plot of `Age` and `WorkWeekHrs.`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT * FROM master\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "df.plot(kind='scatter', x='Age', y='WorkWeekHrs', figsize=(10,6), color='darkblue')\n",
    "\n",
    "plt.title('Relation Between Age and Work Week Hours of Respondents')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Work Week Hours')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#or\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT * FROM master\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "plot = sns.scatterplot(x='Age', y='WorkWeekHrs', data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bubble Plots\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a bubble plot of `WorkWeekHrs` and `CodeRevHrs`, use `Age` column as bubble size.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#or\n",
    "QUERY = \"\"\"\n",
    "SELECT WorkWeekHrs, CodeRevHrs, Age FROM master\n",
    "\"\"\"\n",
    "df=pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "sns.scatterplot(data=df, x='WorkWeekHrs', y='CodeRevHrs', size='Age', hue='Age', alpha=0.5, sizes=(10, 500)) \n",
    "\n",
    "plt.title('WorkWeekHrs and CodeRevHrs By Age', size=14) \n",
    "plt.xlabel('WorkWeekHrs', size=10) \n",
    "plt.ylabel('CodeRevHrs', size=10)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing composition of data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pie Charts\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a pie chart of the top 5 databases that respondents wish to learn next year. Label the pie chart with database names. Display percentages of each database on the pie chart.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "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>Respondent</th>\n",
       "      <th>DatabaseDesireNextYear</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>MySQL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>SQLite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>PostgreSQL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9</td>\n",
       "      <td>Redis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>SQLite</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Respondent DatabaseDesireNextYear\n",
       "0           4                  MySQL\n",
       "1           4                 SQLite\n",
       "2           9             PostgreSQL\n",
       "3           9                  Redis\n",
       "4           9                 SQLite"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT * \n",
    "FROM DatabaseDesireNextYear\n",
    "\"\"\"\n",
    "df_db = pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "df_db.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>Respondent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DatabaseDesireNextYear</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PostgreSQL</th>\n",
       "      <td>4328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MongoDB</th>\n",
       "      <td>3649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Redis</th>\n",
       "      <td>3331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MySQL</th>\n",
       "      <td>3281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Elasticsearch</th>\n",
       "      <td>2856</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Respondent\n",
       "DatabaseDesireNextYear            \n",
       "PostgreSQL                    4328\n",
       "MongoDB                       3649\n",
       "Redis                         3331\n",
       "MySQL                         3281\n",
       "Elasticsearch                 2856"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_groupby = df_db.groupby('DatabaseDesireNextYear', axis=0).count()\n",
    "\n",
    "df_groupby.sort_values([\"Respondent\"], ascending=False, inplace=True)\n",
    "df_pie = df_groupby.head()\n",
    "df_pie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2RGJiorlqt7RjvSh/f380atTIYlutWrWKNHOsXLkSTZs2hUqlMr8O8+bNe+bX4Wl+//13iMViSCQSREZGYuvWrVi2bBnq169vLrNp0ybUqFEDderUsbhO0dHRFtWFDRs2BAD06tUL//77L+7fv1/ieUt7ra9evYqEhAT07dsXAsGjP1mVSoUePXrg6NGjyM/PtzjmG2+8YfF7rVq1oNFokJKSAgDmYz98zR+P5XEajQa7d+9G9+7doVAoirw3NBoNjh49Wuq5ARR5LYvTqFEjqNVqvPvuu1i/fv1z9cZv1aoV8vLycOLECXP/gIdNQi1atEBqaiouXboErVaLo0ePWjQLlBTLuXPnMGTIEGzfvh3Z2dklli3tej+v5/08fV6HDx9GRkYG+vXrZ/GamkwmtG/fHidOnDA3dT3vZ1ePHj2KPSfHcejSpYvFtuL+xkvTpk0btGvXDl988UWxPfOBwr/TVq1aITAw0OL5Pez3tX//fnPZpk2b4uuvv8bMmTMxePBgvPfee/jggw+eK6aSDB48GAEBAWjTpg2aN28OgJ9rXxqrJQLp6enw9/cv0oHD19cXIpEI6enpFtv9/f2LHOPhtifLPov33nsPAIp8KL2I+Ph4SKVSc4eOGTNmYPDgwWjcuDFWr16No0eP4sSJE2jfvv0zfxGOGjUKEydORLdu3bBx40YcO3YMJ06cQO3atYs9RknX5/Fr07t3b/z6668YOHAgtm/fjuPHj+PEiRPw8fGxOOYvv/yC8ePHY926dWjVqhU8PT3RrVs3XL9+HQDMbeBjxoyBWCy2+BkyZAgAmD+QSzvWi/Ly8iqyTSqVWjyPNWvWoFevXggKCsLSpUtx5MgRnDhxAgMGDIBGo3mp8wOFX9onTpzA4cOHMWfOHLi4uOCdd96xeG7Jyck4f/58kevk4uICxpj5OjVv3hzr1q2DwWDA+++/j+DgYNSoUaPYvhSlvdYP/w0ICChSLjAwECaTCZmZmRbbn7yeUqkUAMzXMz09HSKRqEi5J2NJT0+HwWDArFmzijznh22dT35Zl3bup+nbty/mz5+P+Ph49OjRA76+vmjcuDF27txZ6mMffrHv3bsXZ86cgVqtRosWLQAA1apVg4+PD/bt24ejR48W6R9QnAkTJuCHH37A0aNH0aFDB3h5eaFNmzY4efJkkbIv85yL87yfp8/r4d98z549i7yu06dPB2MMGRkZAJ7/s6u49ykAKBQKyGQyi21SqfSF/nanT5+OtLS0EocMJicnY+PGjUWeW/Xq1QEUfc/26dMHEokEWq3W3B/AWiQSCSQSiUVsgG2vfWlevivnA15eXjh27BgYYxZv3pSUFBgMBnh7e1uUT0pKKnKMh9uK+1IozcO7+MfvmF7E/fv3cerUKbRo0cLc23Lp0qVo2bIlZs+ebVG2pGy0OEuXLsX777+PadOmWWxPS0uDu7t7kfIlXZ+H1yYrKwubNm3C5MmT8emnn5rLaLVa85voIaVSialTp2Lq1KlITk4239F36dIFsbGx5tdmwoQJePPNN4uNPyoq6pmOVZaWLl2K8PBwrFixwuI9Zq3OUz4+PmjQoAGAwlEDVatWRYsWLTBy5Ehs2rQJAODt7Q25XI758+cXe4zH3+ddu3ZF165dzXeg33zzDXr37o2wsDC8+uqr5nKlvdYP/01MTCxSLiEhAQKBAB4eHs/1XL28vGAwGJCenm7x9/ZkLB4eHhAKhejbty+GDh1a7LHCw8Of69yl6d+/P/r374+8vDz8999/mDx5Mjp37oxr164hNDS0xMfVqFHD/GUvlUrh5+eHKlWqmPc3b94ce/fuNX+JlpYIiEQijBo1CqNGjYJarcauXbvwf//3f4iOjsbdu3ehUCis84SL8byfp8/r4eNnzZpV4uirhzW2z/vZZYve/HXq1MG7776LGTNmmBPSx3l7e6NWrVr4+uuvi318YGCg+f9GoxF9+vSBh4cHpFIpPvjgAxw6dMjiy9ua7PHaW61GoE2bNsjNzS0ydnvx4sXm/Y/bvXu3RW9so9GIFStWoFKlSggODn7u8z88z8sMKSwoKMDAgQPNQ1Qe4jjOnOE/dP78+SI9tp92F1DcMTZv3lxilfGyZcssmiji4+Nx+PBhc1Unx3FgjBU55l9//QWj0Vjic/Tz80NMTAzeffddXL16Ffn5+YiKikLlypVx7tw5NGjQoNgfFxeXZzpWSV72DgkofM4SicTizZ6UlFRk1MDD871ss0WzZs3w/vvvY/PmzebXunPnzrh58ya8vLyKvU5hYWHFxtKiRQtMnz4dAIo0X5X2WkdFRSEoKAj//POPRbm8vDysXr3aPJLgeTz8Evz7778ttj85Z4JCoUCrVq1w5swZ1KpVq9jn/CKJ+7O8PkqlEh06dMBnn30GnU5X6mRfHMehRYsWOHz4MHbu3GmuDXioRYsW2L9/P/bu3YvAwEBERkY+c7zu7u7o2bMnhg4dioyMDKvNh1HSdXjez9Pn1bRpU7i7u+Py5csl/s0//CJ83s8uW/nqq6+g0+kwderUIvs6d+6MixcvolKlSsU+t8cTgcmTJ+PAgQP4+++/sWLFCpw7d65IrYA1Pr8essdrb7Uagffffx+//fYb+vXrh7i4ONSsWRMHDx7EtGnT0LFjR7Rt29aivLe3N1q3bo2JEydCqVTi999/R2xsbKlDCP/55x+sWbMGnTp1QmhoKNRqNVauXInly5cjJiYGtWvXfqZ479y5g6NHj8JkMiErKwtnzpwxV0n++OOPaNeunbls586d8eWXX2Ly5Mlo0aIFrl69ii+++ALh4eEWE5i4uLggNDQU69evR5s2beDp6Qlvb2+EhYWhc+fOWLhwIapUqYJatWrh1KlT+P7770tMelJSUtC9e3cMGjQIWVlZmDx5MmQyGSZMmAAAcHV1RfPmzfH999+bz7F//37MmzevSKbYuHFjdO7cGbVq1YKHhweuXLmCJUuWWHyBzJkzBx06dEB0dDRiYmIQFBSEjIwMXLlyBadPn8bKlSuf+VjFeThz4J9//gkXFxfIZDKEh4c/15dI586dsWbNGgwZMgQ9e/bE3bt38eWXXyIgIKBI00TNmjWxb98+bNy4EQEBAXBxcTHXajyPL7/8EitWrMDEiROxa9cujBgxAqtXr0bz5s0xcuRI1KpVCyaTCXfu3MGOHTswevRoNG7cGJMmTcK9e/fQpk0bBAcHQ61W4+eff4ZYLC7yBVXaay0QCPDdd9+hT58+6Ny5Mz788ENotVp8//33UKvV+Pbbb5/7ebVr1w7NmzfHuHHjkJeXhwYNGuDQoUNYsmRJkbI///wzXnvtNTRr1gyDBw82z5p248YNbNy48YUmeKlZsybWrFmD2bNno379+hAIBGjQoAEGDRoEuVyOpk2bIiAgAElJSfjmm2/g5uZm7nfxNK1atcKqVauwY8cO/Prrrxb7WrRogfT0dPz333/PNC9Ely5dUKNGDTRo0AA+Pj6Ij4/HzJkzERoaisqVKz/3cy5OSdfheT9Pi2M0GoudofRhgjVr1iz069cPGRkZ6NmzJ3x9fZGamopz584hNTXVXAP6vJ9dthIeHo7BgwcXO5zziy++wM6dO9GkSRMMHz4cUVFR0Gg0iIuLw5YtW/DHH38gODgYO3fuxDfffIOJEyeak6tvvvkGY8aMQcuWLdG9e3cAME869fPPP6Nfv34Qi8WIiooq9gapNCqVyv6u/Qt1MWTF90pNT09nH330EQsICGAikYiFhoayCRMmMI1GY1EOD4Zq/f7776xSpUpMLBazKlWqsL///rvU8x45coS1adOG+fv7M7FYzBQKBWvYsCH7/fffLXpUl+RhD9OHP0KhkHl4eLD69euzESNGFDvMTKvVsjFjxrCgoCAmk8lYvXr12Lp161i/fv2K9PjdtWsXq1u3LpNKpQyAuRdyZmYm++CDD5ivry9TKBTstddeYwcOHGAtWrRgLVq0MD/+Ye/PJUuWsOHDhzMfHx8mlUpZs2bNLHqvM8bYvXv3WI8ePZiHhwdzcXFh7du3ZxcvXizS+/nTTz9lDRo0YB4eHkwqlbKKFSuykSNHsrS0NIvjnTt3jvXq1Yv5+voysVjM/P39WevWrdkff/zx3McqzsyZM1l4eDgTCoUWwxIf7xH8uOKu77fffsvCwsKYVCplVatWZXPnzjX33H7c2bNnWdOmTZlCoWAALK5xcR6+J4szduxYBsDc6zc3N5d9/vnnLCoqikkkEvPQupEjR5pHwmzatIl16NCBBQUFMYlEwnx9fVnHjh0thvo9z2vNGGPr1q1jjRs3ZjKZjCmVStamTRt26NAhizIPr8Xjw0cZY2zBggVFej2r1Wo2YMAA5u7uzhQKBXv99ddZbGxssSNfbt++zQYMGMCCgoKYWCxmPj4+rEmTJuyrr74q8nyeHAL88G/u8WGoGRkZrGfPnszd3Z1xHGd+/RYtWsRatWrF/Pz8mEQiYYGBgaxXr17moVyluXz5svlv++LFixb7TCYT8/T0ZADY3Llzizz2yb+bH3/8kTVp0oR5e3sziUTCKlSowD744AMWFxdnLvM817s4JV0Hxp7987Q4D3vpF/fz+N/U/v37WadOnZinpycTi8UsKCiIderUyeI1fN7PruKGgJc0iqG4v93ilPQZkZqaylxdXYsdCZaamsqGDx/OwsPDmVgsZp6enqx+/frss88+Y7m5uSwhIYH5+vqy1q1bW3x3mEwm1qVLF+bu7m7x+k2YMIEFBgYygUBQ4gio4oSGhrJOnToV2W6ra/8sOMaK6SJfxjiOw9ChQ4tk7IQ4k3379qFVq1ZYuXJlkd7hhBBiK7T6ICGEEOLEKBEghBBCnBgvTQOEEEIIsQ9UI0AIIYQ4MUoECCGEECdGiQAhhBDixCgRIIQQQpwYJQKEEEKIE6NEgBBCCHFilAgQQgghTowSAUIIIcSJUSJACCGEODFKBAghhBAnRokAIYQQ4sQoESCEEEKcGCUChBBCiBOjRIAQQghxYpQIEEIIIU6MEgFCCCHEiVEiQAghhDgxSgQIIYQQJ0aJACGEEOLEKBEghBBCnBglAoQQQogTo0SAEEIIcWKUCBBCCCFOjBIBQgghxIlRIkAIIYQ4MUoECCGEECdGiQAhhBDixCgRIIQQQpwYJQKEEEKIE6NEgBBCCHFilAgQQgghTowSAUIIIcSJUSJACCGEODFKBAghhBAnRokAIYQQ4sQoESCEEEKcGCUChBBCiBOjRIAQQghxYpQIEEIIIU6MEgFCCCHEiVEiQAghhDgxSgQIIYQQJ0aJACGEEOLEKBEghBBCnBglAoQQQogTo0SAEEIIcWKUCBBCCCFOjBIBQgghxIlRIkAIIYQ4MUoECCGEECdGiQAhhBDixCgRIIQQQpwYJQKEEEKIE6NEgBBCCHFilAgQQgghTowSAUIIIcSJUSJACCGEODFKBAghhBAnJuI7AELIy8nXGZCSrUVqrhbZBXrkag3I1xmRpzUgT2tEns7w4P8GaPQmGBkDYwwmBrRUKuGVogc4DgIBB04AcAIOIpEAErkIUoUIUoUYUoUIErkIMqUIErn4wXYRJDL6CCHE0dFfMSF2TKM3Ij49H7fTcnEvswDJ2RokZ2uRkqNBSo4WKdla5GoNL3z8aoG+yLmc88KPFwg4SJUiuHjK4Oojh6uXHK7eMrh6yeHiLYOLlwxCIVU8vgyO47B27Vp069atzM4RFhaGESNGYMSIEWV2jrJmi+tUXlEiQIgduJuRjxupubidmofbaY9+ErMKYGJ8R1cyk4mhIEePghw9UuKLJhQcByjdpXD1fpAgeMvhFaSCb6gLVB4yHiK2PzExMVi0aFGR7dHR0di2bZtVz7Vw4UKMGDECarXaYvuJEyegVCqtei7iOCgRIMTG7qTn48L9LFy4n4WL97NwMSEL6nw932GVCcaA3EwtcjO1SLhuuU/uIoZPiAu8K7jAJ8QFPhVc4OYj5ydQnrVv3x4LFiyw2CaVSm12fh8fH5ud60Xo9XqIxWK+wyi3qM6OkDKUrdFj1+VkfLP1CnrPPYpaU7aj+fd7MfSf0/hj/00cvJHGaxKQk53L27kLcvS4czkDp7fFY/vci1g68Qj+GvUf1v10GodWXcf1E8nIy9LyFp8tSaVS+Pv7W/x4eHgUW3b8+PGIjIyEQqFAxYoVMXHiROj1j95D586dQ6tWreDi4gJXV1fUr18fJ0+exL59+9C/f39kZWWB4zhwHIcpU6YAKGwamDlzpvkYarUa//vf/+Dn5weZTIYaNWpg06ZNAID4+Hh06dIFHh4eUCqVqF69OrZs2WJ+7OXLl9GxY0eoVCr4+fmhb9++SEtLM+/ftm0bXnvtNbi7u8PLywudO3fGzZs3zfvj4uLAcRz+/fdftGzZEjKZDEuXLgUAzJ8/H9WrV4dUKkVAQAA+/vhji2uTlpaG7t27Q6FQoHLlytiwYcOLvSBOhmoECLGirAI9jt/OwNFb6Th2Ox2XE7Ltumo/OSkVvvDmOwwzbb4B96+qcf+q2rzNw1+B4KqeCI7yQFCUB6Ry5/7YcnFxwcKFCxEYGIgLFy5g0KBBcHFxwbhx4wAAffr0Qd26dTF79mwIhUKcPXsWYrEYTZo0wcyZMzFp0iRcvXoVAKBSqYoc32QyoUOHDsjJycHSpUtRqVIlXL58GUKhEAAwdOhQ6HQ6/Pfff1Aqlbh8+bL5OImJiWjRogUGDRqEGTNmoKCgAOPHj0evXr2wZ88eAEBeXh5GjRqFmjVrIi8vD5MmTUL37t1x9uxZCASP7k3Hjx+PH3/8EQsWLIBUKsXs2bMxatQofPvtt+jQoQOysrJw6NAhi9inTp2K7777Dt9//z1mzZqFPn36ID4+Hp6entZ/IcoR5/6LIuQl6QwmHLmVjv+upeLorXRcSbTvL/4nKRQyIJvvKJ4uMykfmUn5uLD3HjgBB99QFwRHeSC4igcCKrlDKHb8is1NmzYV+VIeP348Jk6cWKTs559/bv5/WFgYRo8ejRUrVpgTgTt37mDs2LGoUqUKAKBy5crm8m5ubuA4Dv7+/iXGsmvXLhw/fhxXrlxBZGQkAKBixYrm/Xfu3EGPHj1Qs2bNIvtmz56NevXqYdq0aeZt8+fPR0hICK5du4bIyEj06NHD4nzz5s2Dr68vLl++jBo1api3jxgxAm+++ab596+++gqjR4/GJ598Yt7WsGFDi2PFxMTg3XffBQBMmzYNs2bNwvHjx9G+ffsSny+hRICQ55aRp8Oe2BTsupyMA9dTkacz8h2S02AmhuTb2Ui+nY1T2+IhEgvgX8kNIdU8UamuD9x8FHyH+EJatWqF2bNnW2wr6S521apVmDlzJm7cuIHc3FwYDAa4urqa948aNQoDBw7EkiVL0LZtW7z11luoVKnSM8dy9uxZBAcHm5OAJw0fPhyDBw/Gjh070LZtW/To0QO1atUCAJw6dQp79+4ttqbh5s2biIyMxM2bNzFx4kQcPXoUaWlpMJlMAAoTjMcTgQYNGpj/n5KSgoSEBLRp0+apsT+MAwCUSiVcXFyQkpLyzM/dWVEiQMgzuJ6cg51XkrH7SgrO3Ml0qLv+8sygN+FebCbuxWbiyJqb8A5RIaK+LyLq+zpUUqBUKhEREVFquaNHj+Kdd97B1KlTER0dDTc3Nyxfvhw//vijucyUKVPQu3dvbN68GVu3bsXkyZOxfPlydO/e/Zlikcuf3mFz4MCBiI6OxubNm7Fjxw588803+PHHHzFs2DCYTCZ06dIF06dPL/K4gIAAAECXLl0QEhKCuXPnIjAwECaTCTVq1IBOp7Mo//gohtJieujJDoUcx5kTDVIySgQIKcGd9HysP3sf687ex83UPL7DIc8g7W4u0u7m4ui6Ww6bFDzNoUOHEBoais8++8y8LT4+vki5yMhIREZGYuTIkXj33XexYMECdO/eHRKJBEbj02uwatWqhXv37pmr8osTEhKCjz76CB999BEmTJiAuXPnYtiwYahXrx5Wr16NsLAwiERFv17S09Nx5coVzJkzB82aNQMAHDx4sNTn7eLigrCwMOzevRutWrUqtTx5PpQIEPKY9FwtNl9IxLoz93H6jprvcMhLcKSkQKvVIikpyWKbSCSCt7dlR86IiAjcuXMHy5cvR8OGDbF582asXbvWvL+goABjx45Fz549ER4ejnv37uHEiRPmdvmwsDDk5uZi9+7dqF27NhQKBRQKy+vRokULNG/eHD169MCMGTMQERGB2NhYcByH9u3bY8SIEejQoQMiIyORmZmJPXv2oGrVqgAKOxLOnTsX7777LsaOHQtvb2/cuHEDy5cvx9y5c+Hh4QEvLy/8+eefCAgIwJ07d/Dpp58+0zWaMmUKPvroI/j6+po7Mx46dAjDhg177utNLFEiQJxegc6I7ZeSsP7sfRy4ngYD1fuXO48nBX7hrqjeLBCVG/hBJBHyHRqAwiF1D6vOH4qKikJsbKzFtq5du2LkyJH4+OOPodVq0alTJ0ycONE8DFAoFCI9PR3vv/8+kpOT4e3tjTfffBNTp04FADRp0gQfffQR3n77baSnp2Py5Mnmxz5u9erVGDNmDN59913k5eUhIiIC3377LQDAaDRi6NChuHfvHlxdXdG+fXv89NNPAIDAwEAcOnQI48ePR3R0NLRaLUJDQ9G+fXsIBAJwHIfly5dj+PDhqFGjBqKiovDLL7+gZcuWpV6jfv36QaPR4KeffsKYMWPg7e2Nnj17PueVJsXhGGP0qUec0o2UXPx9LB6rT91DtubFp+l1ZG+ajKiUXbRjlzOQKkSIauyP6s2D4BlAs+oR50WJAHEqeqMJOy4lY+nReBy5lc53OLxz5kTgcQERbqjRPAiV6vlCKHL84YiEPA9KBIhTSFAXYNnxO1h+4i5Sc5xjtrpnQYmAJbmLGFVeCUD15oF22ZeAkLJAiQAp1y4lZGH2vpvYejEJRmr7L4ISgRJwQIWqnqgbHYrgqOKn+iWkvKBEgJRLh2+m4Y/9t/DftVS+Q7FrlAiULqCSG+p3CENoDS++QyGkTFAiQMoNxhi2X0rGH/tv4uxdNd/hOARKBJ6dTwUX1O8Qiop1fMBxHN/hEGI1lAgQh2c0Maw9cx9/7L+JGyn8rabniCgReH6egUrUiw5F5YZ+EAgoISCOjxIB4tC2XkjEDzuu0sx/L4gSgRfn5iNHvfahiHrFH0IhjTQgjosSAeKQDl5Pw/fbY3HuXhbfoTg0SgRenspTisZdKiKqsT84qiEgDogSAeJQzt5V47ttsTh8k+YAsAZKBKzHO0SFJt0jEFKt+FUDCbFXlAgQh3ArNRfTt8Vi+6VkvkMpVygRsL4K1TzRpEcEvILouhLHQIkAsWt5WgN+2XMdCw7GQWek5UStjRKBssEJOFRrGoDGXStCrpLwHQ4hT0WJALFb68/exzdbYpGUreE7lHKLEoGyJVWI0LBTOGq2DIKAOhQSO0WJALE7sUnZmLz+Eo7dzuA7lHKPEgHb8PBX4LVelVGhGk1KROwPJQLEbmQV6PHTzmtYciQeRnpb2gQlArYV1dgfr/WqDJlSzHcohJhRIkDswvZLSfh83UVaEMjGKBGwPbmrBC3eiUSler58h0IIAEoECM8y8nSYvOESNp5L4DsUp0SJAH8q1fVB83ejoHClzoSEX5QIEN5suZCIz9ddQEaenu9QnBYlAvySKkVo9lZlRL0SwHcoxIlRIkBsLi1Xi8/XXsA2mhOAd5QI2IcK1b3Qsk8UXDxlfIdCnBAlAsSmNp5LwOdrLyBLY+A7FAJKBOyJRCbEq29GoHqzQFrdkNgUJQLEJvJ1BkxcewGrz1BfAHtCiYD9CavphTYx1WhkAbEZh5rhIiYmBhzHgeM4iMViVKxYEWPGjEFe3sutPBcXFweO43D27FnrBPoMUlJS8OGHH6JChQqQSqXw9/dHdHQ0jhw5YlHu8OHD6NixIzw8PCCTyVCzZk38+OOPMBqNFuU4jsO6detsFv/zuJyQjQ4/7ackgJBnEHchHSu+Oo6kW7SgFrENEd8BPK/27dtjwYIF0Ov1OHDgAAYOHIi8vDzMnj2b79AAADqdDhJJ6b2Ae/ToAb1ej0WLFqFixYpITk7G7t27kZHxaBKdtWvXolevXujfvz/27t0Ld3d37Nq1C+PGjcPRo0fx77//2n0V4vwDNzFtaywMNDswIc8sN1OLtT+cRuOuFVG3XQW7/zsnjs2hagQAmO+eQ0JC0Lt3b/Tp0wfr1q2DVqvF8OHD4evrC5lMhtdeew0nTpwwPy4zMxN9+vSBj48P5HI5KleujAULFgAAwsPDAQB169YFx3Fo2bIlAMBgMGD48OFwd3eHl5cXxo8fj379+qFbt27m47Zs2RIff/wxRo0aBW9vb7z++usAgMuXL6Njx45QqVTw8/ND3759kZaWBgBQq9U4ePAgpk+fjlatWiE0NBSNGjXChAkT0KlTJwBAXl4eBg0ahDfeeAN//vkn6tSpg7CwMAwcOBCLFi3CqlWr8O+//5b15X5h6nwd+v55EF9spiSAkBdhMjEcWXsTm38/D00ujawhZcfhEoEnyeVy6PV6jBs3DqtXr8aiRYtw+vRpREREIDo62nyHPXHiRFy+fBlbt27FlStXMHv2bHh7ewMAjh8/DgDYtWsXEhMTsWbNGgDA9OnT8ffff2PBggU4dOgQsrOzi61+X7RoEUQiEQ4dOoQ5c+YgMTERLVq0QJ06dXDy5Els27YNycnJ6NWrFwBApVJBpVKZE5ji7NixA+np6RgzZkyRfV26dEFkZCSWLVv20tevLBy/nY7W3+/GAaraJOSlxV9Ix4qvjyPxJv09kbLhcE0Djzt+/Dj++ecftGrVCrNnz8bChQvRoUMHAMDcuXOxc+dOzJs3D2PHjsWdO3dQt25dNGjQAAAQFhZmPo6Pjw8AwMvLC/7+/ubts2bNwoQJE9C9e3cAwK+//ootW7YUiSMiIgLfffed+fdJkyahXr16mDZtmnnb/PnzERISgmvXriEyMhILFy7EoEGD8Mcff6BevXpo0aIF3nnnHdSqVQsAcO3aNQBA1apVi33uVapUMZexJ3P3XcU326/DxKgqkxBryc3UYt2P1FRAyobD1Qhs2rQJKpUKMpkMr776Kpo3b45hw4ZBr9ejadOm5nJisRiNGjXClStXAACDBw/G8uXLUadOHYwbNw6HDx9+6nmysrKQnJyMRo0ambcJhULUr1+/SNmHycVDp06dwt69e813/iqVClWqVAEA3Lx5E0BhH4GEhARs2LAB0dHR2LdvH+rVq4eFCxdaHKukQR2MsWfqi2AreqMJQxYewtfbblASQEgZMDcV/HYeGpqEi1iRwyUCrVq1wtmzZ3H16lVoNBqsWbMGbm5uAFAkS2aMmbd16NAB8fHxGDFiBBISEtCmTZtiq92fVNwxn6RUKi1+N5lM6NKlC86ePWvxc/36dTRv3txcTiaT4fXXX8ekSZNw+PBhxMTEYPLkyQCAypUrA4A5kXlSbGwsIiMjS43fFpIy89D++x3YEqvmOxRCyr34i+lY/d0pZKXm8x0KKSccLhFQKpWIiIhAaGgoxOLCcbYRERGQSCQ4ePCguZxer8fJkyctqtZ9fHwQExODpUuXYubMmfjzzz8BwHxn/fiQPDc3N/j5+Zn7Dzzcf+bMmVJjrFevHi5duoSwsDBERERY/DyZNDyuWrVq5qGQ0dHR8PT0xI8//lik3IYNG3D9+nXExMSUGktZ++/SXbz+4x7cVBtLL0wIsQp1cj5WfXsKCTfUfIdCygGHSwSKo1QqMXjwYIwdOxbbtm3D5cuXMWjQIOTn5+ODDz4AUNhuv379ety4cQOXLl3Cpk2bzEmCr68v5HK5uVNfVlZhp5xhw4bhm2++wfr163H16lV88sknyMzMLLV9bujQocjIyMC7776L48eP49atW9ixYwcGDBgAo9GI9PR0tG7dGkuXLsX58+dx+/ZtrFy5Et999x26du1qfk5z5szB+vXr8b///Q/nz59HXFwc5s2bh5iYGAwcOBAdO3a0OO/t27eL1ELk5uZa+3Kb/bb1DPovOYscQ7l4GxHiUDR5emyYeRZXjyXxHQpxcA7dWfBx3377LUwmE/r27YucnBw0aNAA27dvh4eHB4DCu/4JEyYgLi4OcrkczZo1w/LlywEAIpEIv/zyC7744gtMmjQJzZo1w759+zB+/HgkJSXh/fffh1AoxP/+9z9ER0dDKBQ+NZbAwEAcOnQI48ePR3R0NLRaLUJDQ9G+fXsIBAKoVCo0btwYP/30E27evAm9Xo+QkBAMGjQI//d//2c+Ts+ePbF37158/fXXaNasGbKzs83Pdfz48UXOO2rUqCLb9u7dax4OaS2MMYxYuB/rr+ahnOSShDgko8GEXQsuIyu1AI06h/MdDnFQNMXwczCZTKhatSp69eqFL7/80ubn12g06Nq1K+7evYv9+/ebRzvYUl6BBv1+342TqTY/NSkDNMVw+RHZ2A+t+1aFUETJOXk+9I55ivj4eMydOxfXrl3DhQsXMHjwYNy+fRu9e/fmJR6ZTIb169fj/fffx3///Wfz899LyUDn77dSEkCIHbp2LBnrZ56hyYfIc6Magae4e/cu3nnnHVy8eBGMMdSoUQPffvutRc9/Z3Eq9hY+XHoWaQYp36EQK6IagfLHzUeOzh/Xhrufgu9QiIOgRIA8FWMMmw6dxaebbiEPtFZ6eUOJQPkkU4nxxid14BPiwncoxAFQ0wApEWMM8zcfxOiNcZQEEOJANLl6rP/pDFLis/kOhTgASgRIsQwGA35asRPfHMiAjrOfGQwJIc9Gm2/A+plnaTljUipKBEgRGq0WXy/egt/OFMDAlZsRpoQ4HV2BARt+PouE62q+QyF2jBIBYiEnNw+T/tqARVcBIyUBhDg8vdaIjbPO4l5sBt+hEDtFiQAxS03PxGd/rsWqO1KYuKdPmkQIcRwGnQmbfzuPO5fS+Q6F2CFKBAgAICE5FZ/PXYtNya6UBBBSDhn0JmyZfQFx59P4DoXYGUoECO4lJmPKvPXYmelNSQAh5ZjRYMLWORdw80wK36EQO0KJgJO7cz8RX81fh11ZPpQEEOIETEaGHX9dwt3L1GeAFKJEwInF30vA9IVrsSvbDybqGEiI0zAZGbbOuUDzDBAAlAg4rfh7Cfhx0RrszPKDgRPzHQ4hxMb0WiM2/XoO6uR8vkMhPKNEwAnduZ+Inxevxk61L3QCmjGQEGdVkKPHxllnkZel5TsUwiNKBJzMvcRk/Lp4FXZkeqNAqOQ7HEIIz7LTNNj06znoCgx8h0J4QomAE0lJz8Ccv9dge7o7coWufIdDCLETaXdzseWP8zDqTXyHQnhAiYCTUGfnYN6ytdiaIEGWyJPvcAghdub+VTV2LrgEZqIFaZ0NJQJOIC+/AAtWrMOW6/lIk/jzHQ4hxE7dPJ2KAyuu8R0GsTFKBMo5rVaHJas3YuuFBNyTh/MdDiHEzl3Yfx9ndt7hOwxiQ5QIlGMGgwHLN2zDluNXcEtRDQwc3yERQhzAkbU3aZEiJ0KJQDnFGMO67Xux+b8TuKGqDQO91ISQZ8RMDNv/uoScDA3foRAboG+HcmrfkZNYt/M/3FDVQj6jCYMIIc9Hk6vH1j8uwKA38h0KKWOUCJRDF2Kv49+N23FbFoEMpuA7HEKIg0q9k4P9f1/lOwxSxigRKGfuJSZjyepNuK5zxX148x0OIcTBxR5NwoV99/gOg5QhSgTKkaycXCxcuQFXknJwW1yR73AIIeXEwZXXkXBDzXcYpIxQIlBO6HR6/L12C87F3kK8ay0YaYQAIcRKTEaG7X9eRJ6a1iQojygRKAcYY1i/Yy8OHD+NZK/ayDZS50BCiHXlZ+uw7c8LMBpoGuLyhhKBcuDQibPYtPsA8t0jcEfvwnc4hJByKulWNo6uv8V3GMTKKBFwcHF3E/Dvpu3QiF1w0UDTBxNCyta5XXeQcD2T7zCIFVEi4MBy8/KxdO1mJGdk44o4ivoFEELKHGPArgVXaNnicoQSAQdlMpmwZutuXIy9jgzvWsg2ivgOiRDiJHIyNLQ4UTlCiYCDOnTiLHYdPAahT0Vc11C/AEKIbcUeTcKtM6l8h0GsgBIBBxR3NwErN++AQCLDWX0g3+EQQpzU3r9jkZ+t4zsM8pIoEXAwD/sFpKarcU8ZhTyTkO+QCCFOSpOrx54lV/gOg7wkalh2IA9XFLwQex2KoKq4kUPrCBDHdiPhPHadW4E7adeRnZ+OQe2monb4axZlkjLjse7YXNxIPA/GTAjwCMOAthPh6eJX6vFP3tiDhbu/Rq2wJvhf9Jfm7Seu78L6Y39BZ9Dg1agO6P7qh+Z96TlJ+HXzOIx7czbkEqX1nmw5FX8hHZcO3Ef1ZkF8h0JeECUCDuTMpVjsOXQc3n4B2JPnxXc4hLw0raEAQV6V8EpUe/y1c0qR/alZCZix/hM0qdIBnRr0g1yiRFLmHYhFklKPnZGTjHVH56CSf02L7bkFWfhn/494r+U4eLsGYPbWz1A5sDZqhL4CAFhxYCa6NhpEScBzOLjqBoKreMDNh25OHBElAg5CnZ2DVZt3wmgy4QoLQQE1CZByoHqFxqheoXGJ+zeemIfqFRqj2yuP7ti9XUvvF2MyGbFwzzR0bNAPNxMvoECXa96XlpMImUSJ+hGtAACRgXWQlBmPGqGv4MT13RAKxKhTsdlLPCvnY9AasXvRFXQfXQ8cR8OYHQ31EXAAjDGs3boHN+PuQexXCbc0cr5DIqTMmZgJl+4cg69bMH7dPB6fLuqB79cOxbnbB0t97NZTS6CSuaFJlY5F9vm6BUFv0OJu2nXkabIRn3oVgV4VkafJxuaTC9HrtWFl8XTKvcQbWbhyOJHvMMgLoETAAZw4dwn7j55EYEAAjud48B0OITaRW6CGVl+AnWeXo1pIQ3zcaTpqh72Gv3ZMwfWEcyU+7mbSRRy5uhW9m48udr9C6oK+rcZj8d7p+H7tUDSKfB3VQhpi7dE5aFGjG9Kzk/Dtqg/x9b8f4Myt/WX19MqlI2tuoiCXRhE4GmoasHPpmVlYvWUXOAGHOEEATRxEnIaJFS5uUzOsCVrX6gkACPaOwK3kSzh4eSMqB9Yu8hiNLh+L93yDd5uPgkruVuKxa4e/ZtEp8VrCWSRk3EavpsMwZfn76N/mM7gqPPH92qGICKgFFzkl4M9Ck6fH4VU30CamGt+hkOdA3yp2rHD2wF2Iv5eAoPBI/Jeu4jskQmxGJXODQCBEgEeoxXZ/9wq4lXSx2MekZScgPScJc7Z9bt7GGAMADP/zdUx8exF83Cz7GOiNOvx74Gf0az0Bqdn3YTIZzUmGr1sw4pKvoGZYE2s+tXIt9mgSqjQJQFAkJU+OghIBO3bi3CUcOH4GIUEBOJLrQWsJEKciEooR6hOFZPVdi+0pWffgUcLQQT/3Cvi/t/6y2LbpxHxodAXo2XQoPFQ+RR6z7dRSVKvQCCE+kbibdh0mZjTvM5oM5poJ8mwCAgTI+eU7sJlfghPRV4wjoFfJTmXn5GL9jr0QCgXIEHnjXo6M75AIsTqtvgCpWffNv6fnJOFe2g0opC7wdPFD29pvY/6uLxERUAuRgXVw+e4JXIw/gk+6zDA/ZvGeb+Gm9EbXxgMhFkkQ6BlucQ65pLAm7cntAJCYEYfTN/fh055zABQmEhzH4XDsFrjKPZGsvoNQ36iyeOrljtJVhKoFR+G6bAEYgMx/qsHz/b58h0WeASUCdmrHf0dwM/4eIipWxLqMkts6CXFk8alX8cvGR5361hyZDQBoHNkOfVuNR+3w1/BOsxHYcWYZVh36Fb7uIRjYbgoqBTyaGyAjN+WFhqwxxrDsvxl4s8lgSMWFI3EkIineazkO/x78BQajHr2aDoO7smgtAnlEIOQQ6Z0J/83fQ5CrNm9P/fVXuHbpDJEHNRHYO449bEAjduNW/D1898dCSMQi3JGE4WwuLSpEysabJiMqZVPfE/JijPokNIpfC7d7xffZcH/rLQR8+YWNoyLPi4YP2hmDwYB1O/YiKycXCndvXMyj2c0IIXZGoEdw+ja8fujLEpMAAFCvXo2CS5dsGBh5EZQI2Jmjpy/g9IUrCAsJxJlcVxgYvUSEEHvB4GK4iiaHP0fkhY2lFzeZkPz1tLIPi7wU6iNgRzKzsrFh5z5IJRLoRC64lknzdhNC7INIqEaVS0vgmxT7XI8rOH0aOfv2waVly7IJjLw0ut20I9v2HcKd+4moEOSPEzkuYDRckBDCN4EegRk70Hz3Z8+dBDyU9utvVg6KWBPVCNiJ+HsJ2H/0FHx9vJBqkOMOrSdACOEVg8pwHTVPzodck/NSR9JcvIicPXvh0rqVlWIj1kQ1AnaAMYZt+w4hKzsHPp4eOJ7tyndIhBAnJhRmofq12Wh08OeXTgIeSv11FmiQmn2iGgE7cOXGbRw7cxFBAX6I18iRoi99rfXyJuvIv8i/dgT6jHvgRBJIg6rCo0UMxF7BxZZP3/Yrcs9tg0frQXBt2PWpx84+sR45Z7fAmJ0KgdwViqim8GjRD9yDNe1zL+2Fev8iML0Gqlrt4NFqgPmxhqxkJK+YiIB+MyGQUp8NUs4JDAhI34eoc2utfpeovXwFubt3w6VtWysfmbwsSgR4ZjQasXXvQWh1Ori7umBvqnOO6dbcvQiXep0g8a8MMCPU/y1B8r8TEfjBbAgklrMq5l87Am3iVQhVnqUeN/fSXmTuXwjvjp9AGlQV+oz7SN8yEwDg2WYQjPlZyNg2C14dR0Dk7o+UVVMhrVATikoNAQDp23+HR4sYSgJIOcegNN5ErWPzIC/ILrOzpP76G1Rt2rzQBFCk7FDTAM9OXbiCs5euokJQAO5qpEh3wtoAAPDr9QVUNdtC4hMKiW9FeHUcAWN2KnTJNyzKGXLSkLHzD3h3HgMISs9jdQmxkAVXhbJaS4jc/CAPrwdF1ebQJV0vPJ46CZxUAWXV5pAGREJWoRb0aXcAAHmX94ETiqCIogVnSPklFGaj+vU5aHzgpzJNAgBAGxuLnB07y/Qc5PlRIsAjrVaHrXsPguM4KBVynMmhGQQfMmnzAAAC2aMaEsZMSNs0A66N34TEJ7Skh1qQBlWDNukmtAlXAQB6dRIKbp6E/MEdv8gzCEyvhS75JowFOdAlXoPEJwzGghyoD/wNz9c/svIzI8ROCAwIUO9Bs90T4Hf/gs1Om/bbb9RXwM5Q0wCPjpw+j6u34lApNAQJWolT9g0oDmMMmXv+gjS4GiQ+Yebt2UdXgRMI4VL/jWc+lrJaCxgLspH093gADDAZoarbEW6vvAUAEMpU8O40EmmbZoAZdFDWaA15xfpI2zITLvU7w5CVjJTVXwImA9ya9oayymtPPyEhdo9BabqNmsfmQVGgtvnZtdeuIWf7dri2b2/zc5PiUSLAk/wCDXbsPwy5VAapRIKzaVQb8FDGzj+gS4mDf5/vzNu0STeQfWoDAvr9/Fzti5o755F1ZAU82w2GNDAKhswEZOyaC7VyGdybvgsAUEQ2gSKyicVj9Knx8Hz9IyT8+T94dxkLodIDiYtHQRZSA0Klu9WeKyG2JBTmIPLqcgTcO8trHGm//QaXdu3ACahS2h5QIsCTE+cuIu5eAiLCKyBFJ0aCTsp3SHYhY+cfKLhxDH69v4XI1du8XXv3Ekx5Wbg/u/+jwsyEzL3zkH1yPYIHzy/2eOoDS6Gq3houtaMBABKfMJj0WmRs+xVuTd4Gx1l+EDGDHhk7ZsOr82gYMhPBTEbIKhSudCf2DII28SoUEY2t/KwJKWMCA/wzD6HKmX/toj1Ye/0GsrduhVunTnyHQkCJAC80Wi12HTgGmVQKiViMM+lUG8AYQ+auP5B/7Qj83v0GYnd/i/3KGq0gC6ttsS3l30lQVm8NVc2ShyMxvRZ4ogah8MufAYzhyckb1YeXQ1axPqT+EdAl3wRMxkfHMhkAk+nFniAhvGBQmOJQ88Q8KPMy+Q7GQvofcygRsBOUCPDg1PnLuHXnHiqGBiNTL8Jdraz0B5VzGTtnI+/yfvi++TkEEgWMuYUfWpxUAYFYCqHcFUL5ExMtCUQQKj0s5hpI2/QjhC5e8GgRAwCQRzRC9ol1kPhWhCQwCobMRKgPLIU8ojE4gdDicLrUeOTH/oeAmFkAAJFnMMAJkHNuB4QqD+jT70ESULnsLgIhViQQ5iLq2nIE3D3DdyjF0l6/jrzjx6Fs1IjvUJweJQI2ptPpsevgMYhFIkglEpxU0zLDAJB7ZgsAIHnZBIvtXh1HPPWO/0mG7FTgsep+tybvAOCgPrAUxtx0CORukEc0gkfzvhaPY4whY/uv8Gg9yDxvgUAshVfHEcjYORvMqIfn6x9B5OINQuyawAA/9WFUPbMSAmbfNViZy5ZRImAHOEbjOGzq2JkLmLVgGcJCAiEQy/BPsh8tNUx486bJiErZzjmJVfnDoGDxqHlqPpS56XwH82zEYlTesxsiHx++I3Fq9A1kQwaDAbsOHINAIIBMKsW1fAUlAYSQlyYQ5iLq9kK8sv97x0kCAECvR+a///IdhdOjbyEbOnflOmJv3kZwgB8YAy7nUbMAIeQlCIzwzTmI5nsmICj+JN/RvBD1vyvBDAa+w3Bq1EfARhhj+O/oKTCTCQq5DHc1UmQb6fITQl4Eg5zdRa3j86DMTeM7mJdiSE5Gzu49cI1ux3coTou+iWwk7m4CLl27CX+/wrawS1QbQAh5AQJhHirfXImguBN8h2I1mcuWUSLAI0oEbOTYmfPIzc9HaHAAsgxC3NPSBEKEkOfAGeGTcxzVTv0DoZ2PBnhe+UePQnvrFqQVK/IdilOiPgI2kJmVjSOnz8PLwx0cx+FavgJFZrIhhJASyHAXDU9+hZonl5a7JOChzH+W8R2C06JEwAZOnb+MlLQM+Hp5gjHgRj6tbU8IKZ1AmI/I+CVosu9buOSk8B1Omcpavx6m/Hy+w3BKlAiUMb3egP+On4ZcLoNQKECCToI8k7D0BxJCnBdnhHfeUby2ZwKCbx/lOxqbMOXkIGvDRr7DcEqUCJSxi9du4Pad+wjwLewkeJ1qAwghTyHDfTQ8PQ21TiyBiDnXsDr16tV8h+CUqLNgGTt84iyYiUEuk0Jv4hCnoXUFCCFFccJ8VLq9BhVuHeE7FN5oLlyA7t59SIKD+A7FqVCNQBlKSk3Hxas34OPtCQC4rZHRTIKEEEucEV75x9FszwSnTgIeytm+ne8QnA59K5WhC7HXkZmVAw+3wmWGqVmAEPI4KZeA+me+Re3ji5yuGaAk2ZQI2Bw1DZQRk8mEI6fOQS6XQiAQINcoQKJOwndYhBA7wAkLUCluHSrcPMh3KHZHc/489PfvQxxEzQO2QjUCZeRm/D3E3U2An7cXAOB2gRw0dwAhTo4zwTP/JJrt+5SSgKfI3r6D7xCcCiUCZeTc5avI12igVMgBAPHUSZAQpyblElH/zLeoc3wBREZqBnia7O3b+A7BqVDTQBko0Ghw/OxFuLu6gOM4FBgFSKZmAUKcEifUoOKd9Qi9/h/foTgMzbnz0CckQBwYyHcoToFqBMrAlRu3kZCcCh8vDwDAHY0MjJoFCHEunAmeBafRbN+nlAS8AGoesB1KBMrAmQuxMJlMkEoKawFo7gBCnIuES0a9c9NR59g8iIx6vsNxSDnbqHnAVqhpwMpy8/JxPvYaPD3cAAB6E4cEWmmQEKfACTUIu7sR4df28R2Kwys4fx76xESIAwL4DqXcoxoBK7t2Ox5pGWp4ubsDAO5ppTBSswAh5RtngofmLF7b93+UBFgLYzSngI1QImBlV67fgokxiMWFlS3ULEBI+SYRpKDu+e9R9+hciI1avsMpV3J27uI7BKdATQNWpNXqcObiVbi7Fs4kyFhhjQAhpPzhhFqE3tuMild38x1KuVVw/jxM+fkQKGhW1rJEiYAV3Yi/i5T0DFQI8gcApBtE0NKSw4SUL5wJ7pqLqHliIcQGqgEoU3o98k+fgeq1pnxHUq5RImBFV2/GQa/XQyYtrAWgToKElC9iQSqqn1sIz/Q4vkNxGvnHj1MiUMYoEbASg8GAUxcuQ6VSmrdRIkBI+cAJtaiQsBWVruzkOxSnk3/sGN8hlHuUCFhJ/P1EJCanwdencMlhIwOSaDZBQhwbZ4Kb9hJqnlgEib6A72icUsGlSzDl5UGgVJZemLwQSgSs5Nad+4VrC8gL1xZI0UlgYDQogxBHJRakofqFRfBMvcV3KM7NYED+6dNQNWvGdyTlFiUCVhJ7/RbEIhE4rnDOAGoWIMRBCXWokLgNEZdpDLu9yD9+nBKBMkSJgBXk5Rfgetwd87BBALhPiQAhDsYEN90V1Di5AFIdNQPYk7zjx/kOoVyjRMAK4u4lQJ2dg9DgwpWyDAxI04t5jooQ8qxEggxUu7gI3ik3+A6FFENz6TKMuXkQqqifQFmgRMAK4u4mQK83mhcZSteLYaJphQmxf0IdQpJ2ovKlLXxHQp7GYEDB6VNQNW/OdyTlEiUCVnDp2k1IpY9GCKTSaAFC7ByDqz4WNQ8vgFSXx3cw5BnkHTtGiUAZoUTgJamzcxB/L8Gif0AqNQsQYrdEwkxUu7gY3snX+A6FPIf84yf4DqHccpjxbXfu3AFjrMh2xhju3LnDQ0SFbt+9D3V2DtxdVeZtVCNAiB0S6BGcthXNd39OSYAD0sTGgun1fIdRLjlMjUB4eDgSExPh6+trsT0jIwPh4eEwGo28xHUvMRkmxiASFV5KjYlDttFhLishToDBxXAVtY7Pp2YAR6bXQ3vrNmRRkXxHUu44zDcWY8w8Rv9xubm5kMn4W+r3Vvw9SMSPmgKoNoAQ+yESqlHl0hL4JsXyHQqxAu3165QIlAG7TwRGjRoFAOA4DhMnToTiseUojUYjjh07hjp16vASm1arQ9zd+3BRPYqJ+gcQYgcEegSl7kHUhQ18R0KsSHvtGoBOfIdR7th9InDmzBkAhTUCFy5cgETy6I5bIpGgdu3aGDNmDC+xJaWmITs3D77eXuZtaVQjQAiPGFSG66h5cj7kmhy+gyFWVpgIEGuz+0Rg7969AID+/fvj559/hqurK88RPZKQnIp8jRYK+aOmiUyD3V9SQsoloTALVa4shV/CZb5DIWWEEoGy4TDfWgsWLOA7hCLuJ6UAgLnvgoEBuUYhnyER4nwEegSm7UOV8+v4joSUMX1iIs0wWAYcJhHIy8vDt99+i927dyMlJQUmk8li/61btl8h7NrtO1DIHq0pkGUQgdGMgoTYCIPKeAM1j82HvCCb72CILTAG7fVrUNSty3ck5YrDJAIDBw7E/v370bdvXwQEBBQ7gsCWcnLzkJCUAtVjmamamgUIsQmhMAtVYv+B3/2LfIdCbEx77TolAlbmMN9cW7duxebNm9G0aVO+QwEAJKelIzcvH8GBfuZtahoxQEjZEhgQkL4fUefWOM5saMSqqJ+A9TlMIuDh4QFPT0++wzBLy1BDq9ebFxoCqEaAkLLDoDTeQq1j8yAvyOI7GMIjSgSsz2GS6i+//BKTJk1Cfn4+36EAAFIzMsEBFk0UlAgQYn1CYTaq3fgTjQ/MoCSAQHv9Ot8hlDsO8831448/4ubNm/Dz80NYWBjEYstq+NOnT9s0nsTkVAgEj/IoEwOyKREgxHoEBvhnHkCVM6sc546FlDmjWg1DaipEPj58h1JuOMw3V7du3fgOwYwxhrsJSVDI5eZt+UYhjDRigBArYFCY4lDzxDwo8zL5DobYIX1iIiUCVuQwicDkyZP5DsEsNy8fmVk5UMgfDR3MM9E9CyEvSyDMQdS15Qi4e5bvUIgdM6Sm8h1CueIwiQAAqNVqrFq1Cjdv3sTYsWPh6emJ06dPw8/PD0FBQTaLIz0zC/kFGvj7epu30URChLwEgQF+6sOoemYlBMxUenni1AwpKXyHUK44TCJw/vx5tG3bFm5uboiLi8OgQYPg6emJtWvXIj4+HosXL7ZZLKkZmdBotJBJH40YyKNEgJAXwKBg8ah5bB6UeRl8B0MchJ4SAatymPrsUaNGISYmBtevX7dYdrhDhw7477//bBpLeqYaACw6C+ZTIkDIcxEIc1Hl9gK8sv97SgLIc6GmAetymBqBEydOYM6cOUW2BwUFISkpyaaxqLOy8WS/QGoaIOQZCYzwzTqMaqf/pWYA8kKoacC6HCYRkMlkyM4uOp/41atX4WPj3qOpGeoiwxepaYCQ0jDI2R3UOj4fytw0voMhDsyQSu8fa3KYpoGuXbviiy++gF6vB1A4kc+dO3fw6aefokePHjaNJS0jE1IJJQKEPCuBMA9RcQvx6v7vKAkgL41qBKzLYRKBH374AampqfD19UVBQQFatGiBiIgIuLi44Ouvv7ZZHHq9AersXIuphRkDCmj4ICFFcUb45BxCsz2fIijuJN/RkHLCmJEBZjDwHUa54TBNA66urjh48CD27NmD06dPw2QyoV69emjbtq1N48jJy4NOp4NSoTBv0zGOlh8mxAKDHPdQ48Q8uORSxy5iZYzBkJYGsb8/35GUCw6TCDzUunVrtG7dmrfz5+TmQavTw8P9UdOAjmoDCDETCPMQcWs1gm8f4zsUUo4ZUlIoEbASu04Efvnll2cuO3z48DKM5JGsnFxodTqLpgEdo9oAQsAZ4Z1zAtVP/Q0hjQYgZYyGEFqPXScCP/30k8XvqampyM/Ph7u7O4DCmQYVCgV8fX1tlgjk5OaBMQah8FEtANUIEGcnwz3UPDUfLtnJfIdCnASNHLAeu04Ebt++bf7/P//8g99//x3z5s1DVFQUgMKhg4MGDcKHH35os5hy8wuKbKNEgDgrgTAflW6vQcitI3yHQpwM02r4DqHcsOtE4HETJ07EqlWrzEkAAERFReGnn35Cz5490adPH5vEodHqimyjpgHidDgjvPJOovqJfyBi1Hub2B57MJScvDyHSQQSExPNcwg8zmg0IjnZdtWRGq0W7IltWqoRIE5Eyt1HzdML4JqVyHcoxImZdEVvysiLcZhvsDZt2mDQoEE4efIkGCv8Kj558iQ+/PBDmw4hzM3Lh1BgedmoRoA4A05YgIi7/6Dp3mmUBBDeUY2A9ThMjcD8+fPRr18/NGrUyDy9r8FgQHR0NP766y+bxZGblw+RyPKyGSgRIOUZZ4RX3mlUP7UUIiM1AxD7wKhGwGocJhHw8fHBli1bcO3aNcTGxoIxhqpVqyIyMtKmceTmF0AktJxO2ESJACmnpFwiapxZADf1fb5DIcQC1QhYj8MkAg9FRkba/Mv/cQUFGohETyQCPMVCSFnhhAWoGL8eoTcO8B0KIcWiGgHrcZhEwGg0YuHChdi9ezdSUlJgMll+/e7Zs6fMY2CMIV+joRoBUn5xJnjmn0H1k0sgNtIdF7FfVCNgPQ6TCHzyySdYuHAhOnXqhBo1aoDjbP/lq9XpoNcbIHwiEXhfvBsVFLdh5DgYmRAmCGCCAMYHPyZwMEEIIziYIIDhsf0mCGBkj8oaIXzwb+GxjBAU/8Ms/2+AAAYIzdsNEMDw+OPNZR7sf7DvYTnzPiaE/sH/HagvKbECKZeEGmcXwC3zHt+hEFIqSgSsx2ESgeXLl+Pff/9Fx44deYtBrzfAZDIV6SxYFbdQ13TctsFwJfzfihg4mMCBPUhYTODAOMET2x774QoTHWZOfp4s8+Q2DkZOCBN7kBBx3GP/Fzz6/4PHmROnJxIt44MkywgBTOyx/0MIw2OPfTLhMhSz/fHkycCKJl8PEyYDEz1IpDiLpMrIHh1Xb/G7/S5TzQk1CLu7EeHX9vEdCiHPjOkoEbAWh0kEJBIJIiIieI3BxBgYYxAInvzmLZ9NAxwYhGCw6AXx5CQKj3vaPntmg6QKQDEJ1MPE6snkioOJE1j+Xlzi9USCZHri8YWJ0aNkKj09C3KFClK5wlwTdUkTjCYHDkKqKzpjJnkxJ/PzMT8jHZc0WqQaDfglMAhtXVzM+/NMJvyUmoLdublQG40IEovxnrsH3vHweOpxF2dkYLlajUSDHh5CIdq5uGCktw+kD4Yzb8zOwk+pqcg3mdDDzR1jfX3Nj72v12Hg3btYGRoGldB+k9LnQTUC1uMwicDo0aPx888/49dff+WlWQAo7KfAGOPt/MSxCcCAB/UXZiUlT2WRVD38nnksr5sRWBWHOjGM2CiEt8FY7MPI88k3mRAllaG7mzs+SSg62mJ6SjKO5edjekAAgsRiHMrLx5fJSfARidDmsYThcRuzszAjLRVf+fujrlyOOJ0e/5dYOJfDp75+yDQYMCkpCdP8AxAsFmPw/XtopFCghUoFAJianIxRPr7lJgkAqLOgNTlMInDw4EHs3bsXW7duRfXq1c1zCTy0Zs2aMo/BaDRBl5WM7IRcZEglhQkBxyHHNR1QlPnpCbGqTJMIico8sCrA+AoifL7JE+E3aUW3l9VcpULzB1/AxTlbUIBurm5opFACAHq5S/CvOhOXtJoSE4FzBQWoK5ejs6sbACBILEFHVxdc0BTOt39Xr4dKIEAHV1cAQCOFAjd0WrSACpuysyDmOLxewrEdFs1pYTUOkwi4u7uje/fuvMbAGTSQZlyDNiMVOo4rnOGQAYZKKZQIEIezzuQO9uAGMUdhxPhemXj/mB867E+D0Ei1A2WlnlyBvXm5eNPNDb4iEY4X5CNOp8eEB4lBSY/ZmJ2N8wUFqCWX465OhwN5eej6IDEIlUigYQyXNRoEisW4qNHgTTc3qI1GzEpLw8KQCrZ6ejbDiSWlFyLPxGESgQULFvAdAkQiIaLCQ6CsXRMKlat5e4XcHYD2Ao+REfL8zvkFAMiy2La4cTrOhqgwYp0RqqxcfgIr5/7Pzw+TkxLR6tZNiABwHIcv/fxRX1Hy3URHV1dkGA147048AMAA4B13dwzy8gIAuAmF+MY/ABMSE6FhJrzh6orXlCp8lpiI9zw8cF+vx9D792BgDEO9vRHt4lriuRwFJ5db7VgxMTFYtGgRPvzwQ/zxxx8W+4YMGYLZs2ejX79+WLhwYanHMhqN+O6777Bo0SLEx8dDLpcjMjISH374Ifr3728ud/fuXUyZMgVbt25FWloaAgIC0K1bN0yaNAleD15XAGjZsiXq1KmDmTNnWuvpFuEwicBDqampuHr1KjiOQ2RkJHx8fPgOCYyG2REHdE5efGer84F5GD5AiAmbfVH5WoqNoyr/lmZm4FyBBr8FBSFQJMbJggJ8kZwMb5EITZTF1wocz8/DnPR0TPLzRy25DHd0ekxLSYaPMA2Dvb0BAG1dXCw6JR7Pz8N1nRaf+/mh/a1b+CEwEN4iId6Oj0cDuQJeIof7+LcgkEqteryQkBAsX74cP/30E+QPkgyNRoNly5ahQoVnr1GZMmUK/vzzT/z6669o0KABsrOzcfLkSWRmZprL3Lp1C6+++ioiIyOxbNkyhIeH49KlSxg7diy2bt2Ko0ePwtPT06rP72kc5p2Ql5eHYcOGYfHixebJhIRCId5//33MmjULiqdk09b2cNGjh/QcVVERxxLLFEgT55e4P1dmxGc9MtD7pB+67E2H0EDtsdagMZkwMzUVs4KCzR35omQyxGo1WJiRUWIi8EtaGt5wdUNPd3cAQKRUhnyTCVOSk/ChlxcET3Rg1plM+CI5Gd8FBOKOTgcjGBo++IwMk0hwXlOAVirH7jPAyWRWPV69evVw69YtrFmzxrys/Zo1axASEoKKFSsCABYvXoyRI0ciISEB0scSkR49ekCpVGLx4sXYuHEjhgwZgrfeesu8v3bt2hbnGjp0KCQSCXbs2GFOOipUqIC6deuiUqVK+OyzzzB79myrPr+ncZhb2VGjRmH//v3YuHEj1Go11Go11q9fj/3792P06NE2iaGk0QJagXXfkISUtX8Nz1at+k+DdHzZV4lsD8f+0rAXBsZgQNFRqgJwMD1lqIjGZMKTo5aFHAeG4geYzE5PRzOlEtVkMhgfnPchPWMwOupQ38cIZNatEQCA/v37WzRDz58/HwMGDDD//tZbb8FoNGLDhg3mbWlpadi0aZO52t/f3x979uxBamrxHW8zMjKwfft2DBkyxJwEPOTv748+ffpgxYoVRW44y5LDJAKrV6/GvHnz0KFDB7i6usLV1RUdO3bE3LlzsWrVKl5j03GUCBDHctbfq/RCD1z2z8Ow/lrEVvEtvTBBnsmEKxoNrjzo0X9fr8cVjQYJej1UQiEayuX4ITUFx/PzcE+nw9osNTZkZ6HtY3fonyYmYEbqo2aZlioVlqvV2JKdjXs6HQ7n5eGXtFS0UqkgfOIG5bpWi6052RjmXdhsWlEigYDjsFqtxv7cXNzW6VDTynfTfOCk1n8Offv2xcGDBxEXF4f4+HgcOnQI7733nnm/XC5H7969LZKFv//+G8HBwWjZsiUAYMaMGUhNTYW/vz9q1aqFjz76CFu3bjWXv379unnRvOJUrVoVmZmZJSYSZcFhmgby8/Ph5+dXZLuvry/y80uu4rQFSgSII9GDQ7zL840KKJCaMKl7Bt4644vuuzMg0lNTQUkuaQoQc/eu+ffpD77Qu7m6YlpAIH4IDMJPqakYl5iILKMRgWIxPvH2wdsPqv0BIFGvt7hL+8jLGxw4/JyWihSDAR5CIVqpVPjE27KPFGMMU5KS8KmvHxQPJhqSCQSY5h+AL5OToGMMn/v6we+J4deOSFBCM8rL8Pb2RqdOnbBo0SIwxtCpUyd4P+iD8dCgQYPQsGFD3L9/H0FBQViwYAFiYmLMNcbVqlXDxYsXcerUKRw8eBD//fcfunTpgpiYGPz111+lxvCwJkAisV2Ts8MkAq+++iomT56MxYsXQ/Ygmy0oKMDUqVPx6quv2iQGjhMUvthPVNlQ0wBxJPuVAdBxLzYr28q6GTgfrMDotYB7eraVIysfGimUuBxVpcT9PiIRpgUEPPUYiyqEWvwu4jgM9fbG0Ce+lJ7EcRz+Dg0tsr2lSoWWKn5nZrU2gUvJczW8jAEDBuDjjz8GAPz2229F9tetWxe1a9fG4sWLER0djQsXLmDjxo2WsQkEaNiwIRo2bIiRI0di6dKl6Nu3Lz777DNERESA4zhcvnwZ3bp1K3L82NhY+Pj4wP2xxLCsOUzTwM8//4zDhw8jODgYbdq0Qdu2bRESEoLDhw/j559/tkkMEqkMQqEIxicmsqAaAeJIditerjfyVZ98DOtfgIs1itbQEWIrwjIaAtm+fXvodDrodDpER0cXW2bgwIFYsGAB5s+fb/4ueppq1aoBKOz07uXlhddffx2///47Cgosp/ZOSkrC33//jZiYGKs8l2flMDUCNWrUwPXr17F06VLExsaCMYZ33nkHffr0KdLhoqyIpTIIRSIYn+hBreVsc35CrOG0FfJWrZjhiy7p6Bbqi147MiGied+JjQldy6YDq1AoxJUrV8z/L06fPn0wZswYzJ07F4sXL7bY17NnTzRt2hRNmjSBv78/bt++jQkTJiAyMhJVqhTWFP36669o0qQJoqOj8dVXX1kMH4yMjMSkSZMsjpmamoqzZ89abPP394e/v79VnrPDJAJAYUeNQYMG8XZ+oVAIqVyJHHWGxXYdNQ0QB5EmkCFRmGO1462rlYELgXKMW6uAR1pW6Q8gxEoEZThlsqvr02sbXF1d0aNHD2zevLlI9X50dDSWLVuGb775BllZWfD390fr1q0xZcoU88q1lStXxokTJzBlyhT06tULKSkpYIzhzTffxJIlS4oMh//nn3/wzz//WGybPHkypkyZ8tLPFQA4ZssxCi/p6tWrmDVrFq5cuQKO41ClShV8/PHH5izLFpb/9jUS79yAX3C4xfZe6T9DBOpARezbYrdK+N7T+nfvYgOHsds9Ued8stWPTUhxKm7cAGnlyryd//XXX0fVqlXxyy+/WOV4kydPxowZM7Bjxw6b9Xt7yGH6CKxatQo1atTAqVOnULt2bdSqVQunT59GzZo1sXLlSpvFoVC5FGkaAAAdZ/0xrYRY239Pmc/+ZehFDNM6pWPRGz7QS2mCLVL2BG5uvJw3IyMDy5cvx549ezB06FCrHXfq1Kn45ZdfcOzYMfOkebbiME0D48aNw4QJE/DFF19YbJ88eTLGjx9vMYtTWZIrXWE0FL2j0glkUBjzbBIDIS/qskRbpsffXD0TFwJkmLBWAa8UdZmeizgvTiyGiKfp5evVq4fMzExMnz4dUVFRVj3242sR2JLD1AgkJSXh/fffL7L9vffeQ1JSks3ikCtVMJmKtqbQyAFi785LPZEjKCi94Eu646nBsJhcnKzr/5S58gh5caKAgBJnei1rcXFxyMrKwpgxY3g5f1lwmESgZcuWOHDgQJHtBw8eRLNmzWwWh1QmR3HvPy0lAsTObVXZbrifQQh81z4N87p7Q1cGU8ES5yYOCuQ7hHLFYZoG3njjDYwfPx6nTp3CK6+8AgA4evQoVq5cialTp1rM/fzGG2+UWRwSmbzIhEIAjRwg9u+4zPZ/7juqqHHZX4oJaxXwScos/QGEPANxUBDfIZQrDjNqQCB4tsoLjuNgND7f9KnP48rpw1i3YCZCI2tYbK+Zfxg1C46U2XkJeRkaCNAkLAx6jp+RLQIjMGKPNxqfSgbnGB85xI55Dx8GnyFD+A6j3HCYpgGTyfRMP2WZBAAPagQexPO4bKFHmZ6XkJexWxnEWxIAACYhMOP1NMx50xNaOdWekZcjoRoBq3KYRKA4arXa5ueUSuUQisQwPTHNcLbw5aZtJaQs7VHyM9TqSXsiszB2gABJQfT3Ql4cNQ1Yl8MkAtOnT8eKFSvMv7/11lvw9PREUFAQzp07Z7M4JDI5RMVMM5wt9KQe0sRunZPZz7szyVWHEe9l4+ArfmA89fwmjk0cSJ0FrclhEoE5c+aYF3bYuXMndu3ahW3btqFDhw4YO3aszeKQyAprBAxPzCVg5MTIF5TNaliEvIwEoQIpgly+w7BgEgC/tErHr295QqOgtTrIcxCJICpmSXry4hxm1EBiYqI5Edi0aRN69eqFdu3aISwsDI0bN7ZZHEoXN4glUui1GsDFsro1R+gJpcm+PnAJ2ewSBMaV7URCL+pApSzEDpDg/9Z7IehuOt/hEAcg9vMDV8JiQOTFOEyNgIeHB+7evQsA2LZtG9q2bQsAYIyVeQfBx4klUrh5+UKrKToxS7aA2j2J/Tlko9U5X1Sqiw4je6uxr4kfTNRUQEpB/QOsz2ESgTfffBO9e/fG66+/jvT0dHTo0AEAcPbsWURERNg0Fp+AEOiKSwRo5ACxQ7ESDd8hlE7A4fcW6Zj5jjsKVIrSyxOnRYmA9TlMIvDTTz/h448/RrVq1bBz506oVIXt8YmJiRhi4/GkHt5+MJmK1kLQyAFib47LfZAncIBE4IGjYTkY+QHD3VBvvkMhdkpSIYTvEModh+kjIBaLi53becSIETaPxcXDC0Bhs8Tj811TIkDszXalDwDH6reSodBjdG81Bh30Q5tDqRDYeCU2Yt9k1arxHUK54zA1AgCwZMkSvPbaawgMDER8fDwAYObMmVi/fr1N43D18C7sMKiz7ICVL3CBwXFyK+IETsgct1PV3NfS8UNvN+S7lM3SycQxyapX5zuEcsdhEoHZs2dj1KhR6NChA9RqtbmDoLu7O2bOnGnTWFzdvSCVK6AtyLfcwXHUT4DYjVxOhDsix6oNeNLJkBx88oERcRX5WXKW2BeRnx9E3tRsZG0OkwjMmjULc+fOxWeffQbhY0NHGjRogAsXLtg0FoWLG+RKF2g1+UX25VDzALETO1RBMHK2G1FTVrLkBox7OxNbW/rBSMPGnJqsRo3SC5Hn5jCJwO3bt1G3bt0i26VSKfLy8mwai0AggLd/UAkjBygRIPZhn8KV7xCsasGr6Zje2wW5rtRU4Kxk1al/QFlwmEQgPDwcZ8+eLbJ969atqFq1qs3j8fYPhl6nK7I9U0hVmMQ+nJc6fm3Ak84G52L4BwbcjKC/M2ckp/4BZcJheraNHTsWQ4cOhUajAWMMx48fx7JlyzBt2jTMmzfP5vG4uHuDK2Z1gVQxjXEl/LstdkG60LH7B5QkV2bEhLcy8d5xP3TanwahofwlPKR41FGwbDhMItC/f38YDAaMGzcO+fn56N27N4KCgjBr1iw0a9bM5vG4eniBEwhgNBogFD66jFqBAlkCD7iZMm0eEyEPbVYFAHCc+QNexNJG6TgbosLIdSa4qHP4DoeUMeooWHYcpmkAAAYNGoT4+HikpKQgKSkJx48fx5kzZ2w+syBQOIRQKlNAV1C0n0CqONjm8RDyuMNyGd8h2MTFgDwMG6DF1ShfvkMhZYxqA8qO3ScCarUaffr0gY+PDwIDA/HLL7/A09MTv/32GyIiInD06FHMnz/f5nG5ejwYQljMyIEUSgQIj0wArkuKvi/Lq3ypCRPfzMDqaD8YRA5TyUmeE3UULDt2/1fzf//3f/jvv//Qr18/bNu2DSNHjsS2bdug0WiwZcsWtGjRgpe4xBIpvHwDcfdWLNy9LZfETBVRPwHCn4Nyf2i4oh1Zy7sV9dJxLkiB0esAt4xsvsMhVkY1AmXH7msENm/ejAULFuCHH37Ahg0bwBhDZGQk9uzZw1sS8FBI5WrQaYu2w+YJ3ZAnUPEQESHATpUX3yHwJtYvH8MHaHC5GjUVlDc0YqDs2H0ikJCQgGoP5pauWLEiZDIZBg4cyHNUhXwCQsBxHIxGQ5F9qSJqHiD8OC117qV8C8QmTOmageUdfGEQi/kOh1iBuEIFiHxoyGhZsftEwGQyQfzYH7NQKIRSaR8TivgGhkLh4ob8nKLVkCk0jJDwIFMgxT0Hn1bYWtbUycDkfjKovd34DoW8JNVrTfkOoVyz+z4CjDHExMRAKpUCADQaDT766KMiycCaNWtsHpuLhxc8fQKQmngHLu6WMwpSjQDhwzZVIEzlYFpha7nuU4CP+3MYt80PtS4k8x0OeUHK117jO4Ryze4TgX79+ln8/t577/EUSVEcx6FCRDXcvXmlyL4soRe0nAxSVr7HchP7sl/hAkDNdxh2RSdi+KpzOrqE+uCdHVkQFzMjKLFjYjEUjRrzHUW5ZveJwIIFC/gO4al8g0PBcRxMJhMEgsdaWjgOqaIgBOtv8hcccTqXpPQlV5KNNTNxIVCOT9cq4Jmq5jsc8owUdepAqLKP5uDyyu77CNg738BQyJUuKMgrOrMZ9RMgtnRF4g61wHnmD3gRcV4F+Lh/Lk7X8StmgnBij6hZoOxRIvCS3L394ObpjbycrCL7qJ8AsaWtKn++Q3AIBiHwbYd0LOjmA92DvkfEfimpo2CZo0TgJQkEAoREVIcmr2hP7QyRH7Scc0z1Svh3VC7hOwSHsq1qJj4dIEKqvwffoZASCL28IKtGMwqWNUoErMA/JByMmcCYZWUj4wS4J6nEU1TEmejB4aY4j+8wHM49dy2GvZ+D4/X9wTjnnn/BHimbNAFHr0uZo0TACnwCQiCTK6HJL1orcFcSyUNExNnsUwZAx+n5DsMhmYTAD+3SMLe7F3QyaiqwJzR/gG1QImAFXn5BULl5FDuxUJI4FDqOPlxI2dql9Cy9EHmqXVFqjB0gRHIgXUu7wHFQNqVEwBYoEbACoUiEChHVkJ9btMOgiRPivpiaB0jZOku5plUkuunwSd9sHG7kR00FPJNWqQKRtzffYTgFSgSsJCg8EiaTCSaTqci+O9LKPEREnEWKUIZEYdHhq+TFmATAzDbp+L2nJzQK6uzLF1Xz5nyH4DQoEbCSkIiqULq6Izcrs8i+RHEY9Bz16CZlY4sqCIyjUfHWtj8iC2MGCJAY7LyrOfLJrXMnvkNwGpQIWImbpw+CK0YhJzOtyD4TJ8J9cUUeoiLO4ICCZl0rKykuOnzSR439r/rBRE0FNiOtUgXSylSTaiuUCFhRpWr1YNDrim8eoNEDpIxckWj5DqF8E3D4rWU6ZvXyQIFSznc0TsGtSxe+Q3AqlAhYUYUHzQN52eoi+xIlYdCD1kYn1nVW6oUcQQHfYTiFQxWzMeoD4F4F6sBWpgQCuHbuzHcUToUSASty9/ZDYFhlZGemFtln5MRIlITzEBW/vjmgRcO5uXD5Jhu+3+eg2/J8XE2zXCaXMYYp+zQI/DEH8q+z0XJhHi6lPH0pXb2R4Yv9WlT6JQeyr7JR+49cbLthsCjz93k9Qn7Kgef0bIzdYbkKZJzahMhZucjWOnbb+jaVL98hOJV0pR6j+qix5zU/mAT08VkWFI0bQexH72tboneyFXEch4ga9WHQ6YrMMggAdyTO1+a1P96AoQ0lOPqBEjv7KmAwAe2W5iNP9+j6fHdIhxlHdPi1owwnBinhr+Lw+pJ85DzlS/rzPVrMOaXDrA4yXB6qwkf1Jei+Ih9nEgsTiLR8EwZuLMAPr8uw/T0lFp3TY/O1RxPuDN5cgG/bSuEqdex23+Myu19AtFz6o1k6ZrzjjnyVgu9Qyh23ztQsYGuUCFhZSKWqULi4Fds8kCCpCIP9r/xsVdveUyKmjgTVfYWo7S/Egq4y3MliOPXgC5sxhpnHdPismRRvVhWjhq8Qi7rJka9n+OdCyTPlLTmvx/+9JkXHymJU9BBgcEMJoiuJ8OORwmV4b2UyuEk5vF1DjIZBQrQKF+JyamHfjX8u6CERcnizqmM31RRAiNviorNZEts4HpqNEQNNiA+npgJr4WQyuES34zsMp0OJgJV5+gYgoEIlZBczesDASZAoCbN9UHYk60G/Nk954Z34bTVDUi5Du0qPEiSpiEOLMBEO3yu5eUBrBJ68GZaLgYN3CpsHKnsKkK9nOJNoREYBw4n7RtTyEyKjgGHSXg1+7eD448N3qYJg4J7ehELKllpuwNh31NjegpoKrEHVqiWEKhXfYTgdeudaGcdxqFyzAfRaTbHNAzelNXmIyj4wxjBquwavVRCihq8QAJCUW3iX7qeyrKL3U3LmfcWJriTEjKM6XE83wsQYdt40YH2sAYm5hdfcQ85hUTc53l9XgEZzc/F+bTGiI0QYs0ODYY0kuK02oe6cXNT4PRerLjvmHP17lG58h0AemNckHd/1dkWeCw3lfBk0WoAfzlVPbSMhEVUhV7kiPycLSld3i30J4nDkCNzhYlLzEhufPt6iwflkIw4OKPph+WRLPWNFtz3u5/YyDNqoQZXf8sABqOQpQP86Yiw4++hLvXtVMbo/Vv2/L86ACylG/NpRhohfcrGshxz+Kg6N/spD81AhfJWOlRefl1JtgD05HZKLTz4Q4rONPgi/WbTDMHk6obs7VM2a8R2GU3KsTz4H4eUXBP+QcGQV0zwAjsN1WW3bB8WzYVsKsOGaAXv7KRHs+uht568q/H9SrmXtSUo+g5+q5Lenj1KAde8okPd/LogfoULsUCVUEg7hHsU/RmtgGLJZgzmd5biRYYLBBLQIEyHKW4hILwGOPaUZwh7dEymRIqD+AfYmW27E+F6Z2NTaD0ahkO9wHIpLh/bgxI7db8dRUSJQBgqbBxpCp8kvoXmghtN0GmSM4eMtBVgTa8Ce9xVFvqjD3Tn4qzjsvPVo6J/OyLA/zoAmwaV/kMpEHIJcBTCYgNVX9OgaVfx1/fI/LTpEiFAvQAijCTCYHr0ueiNgdLBRhJtVgU+vMiG8Wtw4Hd+8p0KuG7V3Pyv3rl35DsFpUSJQRipEVIVC6Yq8nKIrEuoFMsRJq/IQle0N3aLB0vN6/POmHC7Swnb/pFwTCvSF37wcx2FEYwmmHdBi7RU9LqYYEbOuAAoxh941H90dvL+2ABN2PZoL4Ng9A9Zc0eNWpgkH4g1o/3c+TAwY17ToMnyXUoxYccmAL1oV7qviLYCA4zDvtA6br+kRm2ZCw0DHuns7rKAZ7uzd+cA8DB+gx/VIH75DsXuymjUhr1OH7zCclnPclvLAOyAEFSpXw42Lp6F6op8AAFyT1UGE9oLtA7Ox2ScL2+xbLsq32L6gqwwxdQoXYhrXVIICA8OQLRpkFjA0DhZiR18FXB4b438nywQB9yhv1RgK5xK4lWmCSsKhY2URlnSXw11meZvMGMP/NmnwU7QUSknhPrmYw8JuMgzdooHWAPzaUYYgV8fKiWPFNJugI8iVGfFZj0y8e9IXb+zNgNBgKP1BTsizXz++Q3BqHCuu7ppYxdVzx7Bu/k/wr1AJYknRO9W2Wcvha7jPQ2TEkR2V+2KQv+MPf3Q21ZKUGLXOBNdMWjL6cSJ/f0Ts2glORPelfHGs2yAHE16lNnwCKyAjJbHY/ddkdWwbECkXtitpAhtHdNk/D8P6a3GlKk2f+zjP9/pQEsAzSgTKkEQqQ81GLVCQm13sioR3JZWRz9G4Y/J8Tsocqz8DeaRAasLkbhlY2d4XBjF9+XEKBdx79eI7DKdHiUAZq1yrIVw9vIqdaZBxQtyU1eIhKuKocjgR7oqoatnRraybgan9FFB7ufIdCq/cu3eH0NW5r4E9oESgjLl7+aJyrUbISk8pdv91WS0Y6WUgz2i7KghGruQZF4njuOqTj2H9C3Cxhh/fofBDIIBnv/f5joKAEgGbqFrvVUgkMhTkFZ0ARiNQ4Z4TrkpIXsx+Jd09lSdaMcMXXdLxTydfGJxsMh1V61aQVKjAdxgElAjYRHDFKgiqGInM1IRi91OnQfKszkto+Fl5tK5WBibGyJDh4zzrR3jRkEG7QYmADQgEAtRo1AIGvQ4GQ9EFblLFwUgRBfEQGXEkN8UuyBDm8R0GKSM3vQswLCYfZ2uX/6YCWfXqUDRsyHcY5AFKBGykUrW68PQJhDo1udj95xSv2Tgi4mg2uwTwHQIpY3oRw7SO6Vj0hg/0Ugnf4ZQZzxiqDbAnlAjYiFypQrWGzZCblVHs+gOp4mAkikN5iIw4iqMymkTIWWyunokJMRKk+7rzHYrViYOC4Nq+Pd9hkMdQImBDUbUbQenqjtysjGL3U60AKYkBHK5J8ksvSMqNO54aDIvJxcm6/ihP07/6DB9GqwzaGUoEbMjbPxiVqtVBZmpSsfszRP64K4mwcVTEERyU+0PL6fgOg9iYQQh81z4N87p7QycrOk25o5FGRsK1Sxe+wyBPoETAhjiOQ83GLSGWSItdlRAAzsubwkTry5In7FR58R0C4dGOKmp82l+EVH8PvkN5KT6jRoIT0NeOvaFXxMYqVK6OyjUaIC3xbrF9BbJE3oiXVOEhMmLPzlD3AKd3z12LYe/n4GgDPzDO8W4W5A3qw6VlS77DIMWgRMDGOI5DvebRkMmVyMtWF1vmgqIJzTZIzDIEUtwXFp2MijgfkxCY8Xo65rzpBa3csbJD39Gj+Q6BlIC+bXgQFB6JqDqNkZZ0r9hagVyhO25Ja/AQGbFHW1VBMNG0wuQxeyLVGDNAgKQgT75DeSaqNm2gqFuX7zBICSgR4AHHcajXrB2ULm7IUacXW+ai/BUYQKuTEeA/hYrvEIgdSnbVYcR72Tj4ip03FQiF8B01ku8oyFNQIsAT/5CKqFqvCTKSE4qtFSgQuuCGrDYPkRF7c0lKowVI8UwC4JdW6fj1LU9oFHK+wymWW7eukFaqxHcY5CkoEeBRvWbtoHL3LHFlwkvyRtCDxts6s0sSd2QJaP4A8nQHKmVh9AAO90Psa3QJJ5XCZ9gwvsMgpaBEgEfe/sGo2bA51GnJMJmKtgFrBQrEyuvzEBmxF1tV/nyHQBxEqosOI3ursa+JH0x20lTg0acPxP70HrZ3lAjwrE7TtnD19IY6rfg1CC7LGyFX4DwrkhFLx+Tld755UgYEHH5vkY6Z77ijQKXgNxRXV3j/bxCvMZBnQ4kAzzx8/FGnSVtkZaQUWytg5MQ4oWzLQ2SEb1oIcFNMqw2S53c0LAcjP2C4E+bNWwy+o0ZB6O7O2/nJs6NEwA7UeqUVPH0DkZGSUOz+REkY4miSIaezVxkAPVd02WpCnkWGQo8x76qxs7kfTDaezU9evz7c3+5l03OSF0eJgB1w9fBC3aZtkavOgNFoLLbMKWUraDnHmkCEvJw9SseeTpbYh7lN0/FDbzfkuyhtcj5OLEbAF1PB2Uk/BVI6SgTsRI1GLeAdEIK0xDvF7tcKFDijaG7jqAifzkrL05pzhE8nQ3LwyQdGxFX0KfNzef3vfzRc0MFQImAnVK7uaNzmDeg0BdAUFN8ufEtWE8miYBtHRviQLJQjiaYVJlaUJTdg3NuZ2NrSD0ahsEzOIalYEd4f/q9Mjk3KDseKm82G8MJoMGD9wpm4eu44KlSuXmzVmosxAx3ViyFE8U0IpHyY7xaBnzztdyKhvKt5SNuShoL4AhjUBlQYVgGu9V3N+w1ZBiT9m4TcS7kw5huhjFQi4L0ASP1LXkpXc1+DlDUpKIgrgD5dD/93/eEdbdnZTX1YjaRVSWBaBo9mHvB/59HQNF2qDnE/xKHSlEoQysvmi668qHNPheHr9VBlW7EzKschdMliKBo0sN4xiU1QjYAdEYpEaBLdAypXd2SmJhVbJkfoiUvyxjaOjNjaQQW/Q79KY9KaIKsgQ8B7AUX2McYQ/0s8dKk6VBheARFTIyD2FiPu+ziYtCWvmWDSmiDxkcDvLT+I3IpOr23IMeD+gvsIeDsAoaNDkXkoEzlnc8z7ExYnwO8tP0oCnsHZ4FwM/8CAG5Wt11Tg/tZblAQ4KEoE7Ix/SDgatOyI7Mw06HXF3xFeljdCltAxFhshL+aKRMt3CE/lUssFfj384Nag6BwXumQdCm4WILBfIBQVFZAGSBH4fiBMGhPUR9UlHlNRUQH/d/zh/oo7OFHR2jBdqg5CuRBujd2gqKiAsqoSmgQNAEB9RA1OxBUbDylersyI/+uZifVtfWEUvVzyJPT2hu/YMVaKjNgaJQJ2qN5r7VAhohqS794qdr+JE+K48nVQm075dFrqhVxBAd9hvDCmL3xncuJHX+acgAMn4pB/7cWnS5b6SWHSmQqbI3INKLhdAFmIDIZcA1LWphRbO0FK93fDDHz9nhI57i4vfAz/zz+D0OXFH0/4RYmAHZLKFWjavgdEYkmJqxOmioNxU1rTxpERW9im8uU7hJciDZBC7CVG8spkGPOMMBlMSN2UCkOWAYYswwsfV6gUInhQMO7NvYdbX9yCexN3uNR0QdKKJHi29YQ+TY8bk27g+mfXkXUiy4rPqPy7GJCPYQO0uFrl+d97qlat4Nq+fRlERWyF1rm1U2FRNVHrlVY4vmcjFC7uEBbTy/eMojmCdLcgZzT7XHlyQu7Yf5aciEOFYRVwf959XBl6BRAAqmoqqGq9/HLKrvVdLTol5l7JhfaeFoHvBeLa+GsI+SgEIjcRbn5xE8ooJUSujn0tbSlfasLE7hl4+7Qfuu5Oh8hQetLGKRTwnzTRBtGRskQ1AnaK4zg0btMFvsFhSLkfV2wZvUCGY6p21ERQjhRAiDiR4w8blIfJEfFlBKr+XhVVZlZB2JgwGHONkHhbb+0Ek96ExCWJCOwXCF2KDszIoKyihDRACqm/FPk3adXGF7GiXjq+eF+BLE/XUssGTJ0CcQA1yTg6SgTsmIu7J5q83g1GvQ4FeTnFlkmQVESsjFYoLC92qIJg4MrP0FChQgiRqwjaJC0KbhfApZ712pFTN6RCVVMFeZgczMSAxwYkMIPl7+T5xPrlY/gADS5XK7mpwOWNLnDr0sWGUZGyQomAnYuq+yqq1HkVKffiUNKUD+cUzZAu9LNxZKQs7FU6Rq93o8aIgvgCFMQXdmrUpelQEF8AXXrhSJes41nIvZILXYoO2aezEfd9HFzrucKlxqNE4N6f95C08tEwWZPBZD4mMzIYMg0oiC+ANrnoCArNfQ2yjmfB783C9700QApwQMb+DOSczYE2UQt5RXlZXoJyr0BswpSuGVjewRcGsdhinyAoCAGTJvMUGbE2mlDIAaQl3cOK2dNgNBjg7V/8zIIqYyY6ZC2FmNnvJDSkdK0rVEOqA8womHslF3HT44psd2/qjuBBwUjfmY7UrakwZhkhchfBvYk7fLr6QCB6dO9x65tbkHhLEDyo8D2tS9Xh2thrRY6piFKg4oSK5t8ZY7j99W14d/aGa51H1dfZZ7ORuCQRTM/g28MXni1oiK21VEqTY+waDp7p2WBCIcKXL4e8Zg2+wyJWQomAgzi5fyt2rl4I/5CKkMqKv9MJ015Bk9wtNo6MWMtdkRIdg70AWquF2CGxHhi/wxst27wDvw8/5DscYkXUNOAgar/aGpVr1EdS/E2YTMU3fsZJq+KWtLqNIyPWssklkJIAYrf0YmBH3zD4/o/WEihvKBFwEGKJFK269oGnXwBS7sWVWO6Esg3UQu8S9xP7dVhObdrEfnkJPTCj3UxaXrgcokTAgXj5BaF5p7dhMhqQo84otoyRE+OASxfoOOsN0yJlzwTgqthxZxMk5ZuQCTDz9V/gJnWMzqzk+VAi4GCq1H0VdZtFIz3pXolrEeQIPXFUSTN9OZKjcl8UCOx7fQHivIbV/Bh1/OrwHQYpI5QIOBiO49CkXXeEVamFxLjrJQ4pvCetjMsyWgnMUexQWW8VOEKsqanHK/ig/iC+wyBliBIBByRXqtC623tw8fBCasKdEsudUzRDsqj44YbEvpyS0p8isT++nDd+7DCT7zBIGbPLT5+YmBhwHIePPvqoyL4hQ4aA4zjExMTYPrBScBxn/lEqlahcuTJiYmJw6tQpi3L79u2zKCuXy1G9enX8+eefz3wu/5CKaNaxF/RaDXKzMostwzgBDrl0Rp7g5ed4J2UnSyDGHVHxM0cSwhcllFjUdQmUYiXfoZAyZpeJAACEhIRg+fLlKCh41IFKo9Fg2bJlqFChAo+RPd2CBQuQmJiIS5cu4bfffkNubi4aN26MxYsXFyl79epVJCYm4vLly/jwww8xePBg7N69+5nPVaNRc9R9rR1SE+9Cryu+fVkjUGKfSw/oOOkLPydStrYrg2DiaD5cYj9ETISfW/6MYDeqUXQGdpsI1KtXDxUqVMCaNWvM29asWYOQkBDUrVvXvE2r1WL48OHw9fWFTCbDa6+9hhMnTpj3P7z73r17Nxo0aACFQoEmTZrg6tWrFuf76quv4OvrCxcXFwwcOBCffvop6tSpY95vMpnwxRdfIDg4GFKpFHXq1MG2bduKxO3u7g5/f3+EhYWhXbt2WLVqFfr06YOPP/4YmZmWd+6+vr7w9/dHeHg4hg8fjrCwMJw+ffqZr5FAIECzjm+hco16SLh9rcT5BbJE3vjPpSuMKLqCIeHffiWt407sB8c4jKsxDo1DG/MdCrERu00EAKB///5YsGCB+ff58+djwIABFmXGjRuH1atXY9GiRTh9+jQiIiIQHR2NjAzL4XWfffYZfvzxR5w8eRIikcjiOH///Te+/vprTJ8+HadOnUKFChUwe/Zsi8f//PPP+PHHH/HDDz/g/PnziI6OxhtvvIHr16+X+jxGjhyJnJwc7Ny5s9j9jDFs27YNd+/eRePGz/fHJ5Ur0ObNfvDyC0Ly3VsllksRh+CwqgNMNGON3bkgKX25V0JspadvT7zb4F2+wyA2ZNeJQN++fXHw4EHExcUhPj4ehw4dwnvvvWfen5eXh9mzZ+P7779Hhw4dUK1aNcydOxdyuRzz5s2zONbXX3+NFi1aoFq1avj0009x+PBhaDQaAMCsWbPwwQcfoH///oiMjMSkSZNQs2ZNi8f/8MMPGD9+PN555x1ERUVh+vTpqFOnDmbOnFnq86hSpQoAIC4uzmJ7cHAwVCoVJBIJOnXqhMmTJ6N58+bPfZ28/ILQqmsfcAIB1GnJJZa7K43CaUXL5z4+KTs3xK7IFObxHQYhAIAGogb4LPozvsMgNmbXiYC3tzc6deqERYsWYcGCBejUqRO8vR/Nmnfz5k3o9Xo0bdrUvE0sFqNRo0a4cuWKxbFq1apl/n/Ag/WzU1JSABS21Tdq1Mii/OO/Z2dnIyEhweI8ANC0adMi5ynOwyF+T87IdeDAAZw9exZnz57FX3/9hWnTphWpiXhWETUb4JU2XZGdmYa8nKwSy12T16NhhXZkswut5U7sQ7gpHLO6z4JQSE2IzkbEdwClGTBgAD7++GMAwG+//Waxr6QvWMZYkW3ix5bRfLjv8Tb14o7xpGc5T3EeJgvh4eEW28PDw+Hu7g4AqF69Oo4dO4avv/4agwcPLvWYxcXWuE0X5KjTceq/bRCFRkAqVxRb9qyiORSmXITpYp/7PMS6jsqkAGhGQcIvL4MX5nSbA5WCRhg5I7uuEQCA9u3bQ6fTQafTITo62mJfREQEJBIJDh48aN6m1+tx8uRJVK1a9ZnPERUVhePHj1tsO3nypPn/rq6uCAwMtDgPABw+fPiZzjNz5ky4urqibdu2Ty0nFAotRkk8L6FIhJZd+6Bag9eQGH+jxJEE4DgcVbVHkth+R184AwM4XJdQswDhl9KgxK9tfkWAF9VOOSu7rxEQCoXmO+onq6yUSiUGDx6MsWPHwtPTExUqVMB3332H/Px8fPDBB898jmHDhmHQoEFo0KABmjRpghUrVuD8+fOoWPHRGuhjx47F5MmTUalSJdSpUwcLFizA2bNn8ffff1scS61WIykpCVqtFteuXcOcOXOwbt06LF682Hz3/1BKSgo0Gg20Wi2OHz+OJUuWoGfPns95hSxJZXK83rM/NPl5uHX5LEIqV4VQWPRlNnFC/Kd6A69nr4CHMfWlzklezH+KAGg5Pd9hECcmNooxrdE01AirwXcohEd2nwgAhXfkJfn2229hMpnQt29f5OTkoEGDBti+fTs8PDye+fh9+vTBrVu3MGbMGGg0GvTq1QsxMTEWtQTDhw9HdnY2Ro8ejZSUFFSrVg0bNmxA5cqVLY7Vv39/AIBMJkNQUBBee+01HD9+HPXq1Sty3qioKACASCRCSEgIPvzwQ0yZMuWZ4y6J0sUN0W8PxIZFv+D+zasIjqgKgaBo5Y9BIMVe1zfRLmsZVKbslz4veT67lB4AaCIhwg+hUYixUWPRumZrvkMhPONYSZPVO7nXX38d/v7+WLJkCd+hvLDke3FYv/BnZKWlILBiZIn9GVyN6Xg9azmkTGPjCJ1bh5AauCeiBIzYntAgxJDgIRjUbhAtK0zsv4+ALeTn52PGjBm4dOkSYmNjMXnyZOzatQv9+vXjO7SX4hcchvZvD4TcxQXJ926XWC5b6IV9Lm/S7IM2lCGQ4r6QagOI7QkNQrzv8T4+aPsBJQEEACUCAAp73G/ZsgXNmjVD/fr1sXHjRqxevbrUzn2OoELl6mjbIwYcJ0B60v0Sy6WLA7Db9S1oOLkNo3Nem12CwDiqjCO2JTQI0V3aHUM7D6VhgsSMmgacxJmDO7Fr9SKo3D3g5lnykreuhnS0zl4FBcu1YXTO538BtXBEpuY7DOJEhAYhok3R+Ozdz+CqKrnfFXE+VCPgJOo0bYtX23VDVnoK8rLVJZbLFnlhl9vbyBXQB0VZuiTR8R0CcSJCgxCtNK0wqvsoSgJIEZQIOAmO4/Dq691Qr1k0UhPvQpNf8h1/rtAdO13fQbbg2UdekGd3UeqBbEE+32EQJyE0CNFa0xrje42Hn7cf3+EQO0SJgBMRikRo+UZv1GzUHMl3b6Mgt+TOagVCF+xyexuZQu8Sy5AXs1Xpz3cIxEmI9CK00bbBuF7j4O9D7ztSPEoEnIxEKkO7XgNR69XWSL4f99R1CTQCJXa79kK6kD5ArOmY3CGm7yAOTqQXoY2OkgBSOkoEnJBUJke7twagfvP2SEu8i9yszBLL6gRy7HZ7C8miYBtGWH5pIcAtMU0rTMqWWCdGW11bjHt7HDUHkFJRIuCkxBIp2nR/H41ad0FGSgKyM9NKLGvgJNjn+iYSxGG2C7Cc2qMMhJ4z8B0GKcfkeXJ0NHTEuHfGwdfLl+9wiAOgRMCJicRitOzyLl5t1x1Z6alQp6eUWNbIifGfSzfclUTYMMLyZ4/Sne8QSDnmpnZDJ64TPnn7E/g8ZZgwIY+jRMDJCUUiNOvYC8069kJeVib+v717D5KqvvM+/u7LdPd0z6XnfulhbgxzYYYBBAwigrgooGbdVXe13M2jT4ybEBOSMn9tkS2TypZVSUxqK0kllcInkn3MprKVuEnUaFxEFpFwk4vCcJOBucFcmJmee9/OOfvHyCgqMwPMlf68qK5upvuc/h6K6fPp3znn++vuuHDF15o2B7uSPssp96KpK/AGc9itth0yObLas9jg3sCTDz2pECBXRQ2FBADLstj/5ivsfOU3uD1eMnIDo76+NPQeywbewIExRRXOfhcciaybk62OgjKhbJaNQHOAVZmr+KeH/omMtIzpLklmGY0ICDDcZ2DZmnv4q7/9P0SjYdrPN476+nrPAt5I+XsGbb4pqnD2+5PaCssESzATKD5TzOqs1QoBcs0UBGSEzWZj0a1ruevBz4Nl0dp0ltEGjC4m5PNn/z9y0Zk3hVXOXrsSvdNdgtxAvDEvJadLWF+5no2PbFQIkGumQwPyqY4f3M1//24rkdAQeUVlo85SZrdiLBt4g7nho1NY4eyzvKicAbumepbrlxpKpfhcMfesuIf7192P26WZQ+XaKQjIFb1/9B22/W4rwYvt5JeU40xIGPX15UOHuGlwB3bMKapw9jjgzuT/5mtEQK5fRm8G89rn8Xfr/o61K9Zit2tgV66PWpzJFZXVLCEpNZ1tv9tKw+lj5BWW4vEmXfH1pxIXE3RmsrLvJTzW0BRWOvP9OTkb0IyOcu0cloO8C3lUmpU88vePsGzBsukuSW4QGhGQMfX3Bnnz9/+fo/vfwp+ZM+o0xgBeo5dVfX8g3bhyX4J4c1/BAuoTrtzOWWQ0yUYyuWdymZ85n8fuf4yyIvXzkImjICDjEotG2bPtD+zd9kdsDgc5BcWjnjfgsKJ8pv91iiMnprDKmWkQByuKCzFsutRSrl5hqJDkU8ncVHUTj/3tY+oWKBNOQUDGzbIsjh/czY4//ge93Z0ESspxOEc/ujQvdJhFAztJIDpFVc48v08u5F80iaNcpQQrgapgFbZmG7ctvY1HPvsIyb7k6S5LbkAKAnLVzje8z7bfPk9z/Unyispwj3FZXJLRzfL+18iOnZ+iCmeWr+UsYLtXhwVk/DKMDEpaSmAA7l59N/etvQ9Xgmu6y5IblIKAXJPe7k62/9e/U3dwN+nZeaSkjfGV17KoCh2gdvDtuOtGuKZwPhcdOlFQxsGC8kg5nlMesvxZ3L/ufm5betuoh+FErpeCgFyzaCTM239+kf1vvkKCy01WfuGYH1gpsU5u6X+VDKNtiqqcXg3OJO4tSAd9jssYPJaH6q5qIs0RaitqefjehykOFE93WRIHFATkuliWxbH9b7Hjj/9Bf1+Q/KJ5Y/YbsFkm1UN7qB7ai+MG7znw07RyfuZXEyEZXV4sj7yGPJxRJ3feeief/avP4ktU+26ZGgoCMiGaz5xg+x9+RfOZ46TnBEgZR7vTtFgbt/S/it/onIIKp8c/5tdyxB2c7jJkhvJYHmoGagifCVOQU8CDGx5k2YJlOhQgU0pBQCbMYH8fe7b9nkO7tmGaBrmFpTgco19VYLdi1A7upjJ0ADs31n9FE1heNI8he3i6S5EZxmbZKDPKyGvLo6ezh6ULlvLwPQ+Tm5U73aVJHFIQkAllWRb1dYfY+cpvON/wPln5hSSlpI25XGa0hVv6XyPZDE5+kVNkV2IOG3PVA14u5zf93BS6id6GXtwuNxtWbWD9qvWaL0CmjYKATIr+3iBvv/Y73tvzJtjt5BaUYHc4Rl3GYUWpGdpDxdBBnMSmqNLJ83RWNS8m9U13GTJDOC0nNbEaAj0BGlsaKZ1TysP3PExNec10lyZxTkFAJo1lWZw8spddr/6W9uZzZAWK8CWnjrmc1+hl8eBOiiInp6DKyXNvwQIa1FZYgIARYFFoEV3nuwhHwqxYvIIHNzxIhl9TB8v0UxCQSdfbdZFdr/2Wo/vfwpmQQHageFwzpmVGW7hpcAeZsdYpqHJi9dgTWFUYwLTd2FdFyOi8ppcl0SV4u720tLVQlFfEvWvuZfmi5TjH6MopMlUUBGRKmKbJ8YO7efvV33KxrYWcgmISx9Mu1bIojpxg4eBb+MzZM8z+m5Ri/jVDISBe2S0782LzqBisoLm5GbfLzW1Lb+Pu2+/WKIDMOAoCMqW6L7ax60//Sd07u3F5EsnKmzPmuQMwfP5A1dABqob2z4p5C76cW8tbicHpLkOmmM2yUWKUUB2tpre9l+6ebubPnc/f3Pk3zC+br8sCZUZSEJApZxgGR/ftZO+2P9DR2kRaZi6pGdnj+pBMNPupHdxFafjYjG7Wt6qwim7HwHSXIVPFgkKjkAWxBdgH7DS0NJDhz2D9betZs3wNiZ7E6a5Q5IoUBGTa9AW7OLjrdY7sfoP+3iBZ+YXjOpkQhpsR3TSwg5xY8yRXefVOJqTyYMH4tkNmv3wjn9poLSmxFBrONxCLxVi2YBn3rb2PgtyC6S5PZEwKAjLt2prPsf/NlzlxeC+mYZBdUIzL7RnXsoHI+1QP7Z1RJxT+W3oF/y91aLrLkEmWbWSzMLaQDCODrmAXFzouUBQo4q/v+Gturr0ZxzgOeYnMBAoCMiOYpsnZE0fY+8ZLNJ4+hsvjJSt/zpidCS/JjjYxf2g/+dGzk1zp2B4O1HLMFZzuMmSSpJvp1EZryTPz6OnroaW1hSRfEquXrWb96vWkjaOBlshMoiAgM0o0EqHunbfZv+MV2pvPkZKeRVpW7rhPskqNdTB/aD9FkZPYp2FCoxg2PlNcSsQ2809olKuTZqZRHa1mjjmH/oF+mi404XF7WFKzhLUr1jK3cK5OBpRZSUFAZqSBvh4Ovb2Nw7v+m95gJ5l5BeNqVXyJ1+ilMvQOc0PvTelVBm/48vl6tq4Pv1HYLBsFZgHlsXKyzWwGhwZputCEw+FgYeVC1q1cR0VphQKAzGoKAjKjXWxtZt/2lzlxaA+RcIis/EISfUnjXt5lDlEeOkx56BAea/KP2/9zVg0vJ/VO+vvI5HJZLubG5jLPmIfP8hEKh2i60IRlWdSU13DXyruomVczrsZYIjOdgoDMeJZl0Xj6GPu2v0zD6WPEolHSc/LwJfvH/U3MYUUpCR+jaugAyebktf1dP6eGFqeCwGyVaqZSEaugyCjCiZNwJExzazPRaJTKuZXctfIuFlUuUldAuaEoCMisYRgGjaeP8d6eHZypO0RocAB/Vg4paZnjDgQ2y6Qg8j6l4aPkRRsm9DyCi3YPdxTmYNn0KzWb2CwbATNAeaycHDMHgGg0SktbC0OhIcqKyrhr5V0sqVmCK8E1zdWKTDwFAZl1LMviQuMZju7byYnDe+gPdpGSlok/K/eqhmo95gBF4ROUhI+RbnRcd13/njqX76frJMHZwmW5KI2VMs+YR5I1fLhpYGiAC+0XiEQjFAeKufPWO/nMws/gGeflrCKzkYKAzGqdbS0cO/A2R/f/D8GONrwpftKz83A6E65qPamxi5SEj1EcPoHX6r+mWr6QV8teT/CalpWpYbfsBMwARbEi8s18HDiwLIuuni7aO9tJcCZQXlTOyqUrWVy9GF+ib7pLFpl0CgJyQ+jt7uTk4T0c+ct2Oi404XInkpEbGHdjohGWRW60gZJwHQWR96/qioMVRRX02dVIaMaxINvMptgoZo4xBxfDw/uxWIy2i21093aTlpLG4vmLuWXxLVSWVqoZkMQVBQG5oQwN9HPq3X0c2f0GFxrPYLc7SMvOI9GXfNWXeDmtCHPCpykJ15Eda8LOlX9V3nWn8w/547+aQSaZBZlmJoVGIXOMOXjxjjw1ODTI+fbzRKIR8rPyuXXJrSyrXUZ+dv40FiwyfRQE5IYUjYQ5c+wg7+55k5azpxka7MOblIo/M+fqRwmARKOPwsgp8qP1ZEdbcGBc9vx3M6p4IUWTDE0nm2Ub2fkXGAWX7fwty6K7t5u2i204HU7KCstYdfMqFlUtInk802GL3MAUBOSGZpom7S3nqD9+hOMH/0JnWzOmYZDsTyclPWvcLYw/ymaEOHngP1mZ7+TmpH5SzD4eCNRySm2Fp5zX9JJj5pBj5pBr5JLI5bP8DQ4N0t7VTv9gP/4kPwsrF7LiphVUza3SJYAiH1AQkLgRjURorj/O+0cPcfroAXo727E7nKRmZJGUmj7uQwfn28/zx3feZvHNq8jJDZAdbecvnk4aHa102DswbMbYK5Fr4rJcwzt+Y3jnn2KlfOI1kWiEjq4Ogr1B3C43BbkFLF+4nNrKWgI5AXUBFPkYBQGJS4P9vZw78S4n391P0/t19PcGcXu8+DNzxuxcuPe9AxxsbWTd+gc/cbmigUGnvZM2exut9lY67Z3qK3AdHJaDLDOLXDOXHCOHNCsNG5/ckUejUTqDnXT1dGG328nNzGVpzVJqK2opKyrTt3+RUSgISFyzLIvujlbOnniXE4f+QmvTWSKhQbzJqSSnZeD2eD/xDfL3//Mn+jyJ3LbyzjHXHyNG0B6ky9ZFt72bLnsXvbZeTNvUT4g0G/hMH37LT5qZRo6ZQ4aZgYNPP4M/Eo3QFeyiu7cbGzYy0zJZULGAhZULqZpbRaIn8VOXE5HLKQiIfMAwDFobz1B//Ain3t1H8GI7kdAgCW4PSanpJKX4icSivPDmS8wpr6GiYsG1vQ8GPbYeuuwfhoMeW09cHVJwWA78lh+/OXxLs9Lwm34SuHL/B8uyGBgcINgXpLe/F7vdTlZaFgsrF1JdXk1FSQVJXl25IXK1FAREPkUsGqX9fAPnz53m7PEjtDbVM9DXQ2tPNwc6LrBk+e1kX8X0yGMxMemx9dBt7yZoDzJgG2DQNsiAbYCwLTwh7zEd7JadRCvxsp2+3/KTbCV/6hD/R1mWRSgcItgXpKe3B8M08CX6yEzLpHpeNfPL5lNeUq6mPyLXSUFAZAyWZdHX3cn5htMcObyPVw/txpmcTCgUwuF0kJqcij/ZP2ltaGPERkLBpfuPPh6yDU3LoYYEKwGv5SXRSiTRSsRreT/xdzfuMXf4HxWOhOnp6yHYGyQWi+F2u0lPTaeytJJ5xfMoChQRyA7omL/IBFIQELlK0WiUptYmGloaOHn2JKfPnaa7p5tINILdYSfJmzRym4odloVFiBAxW4wYsZF7A+MTP/v483bsOC79sYbv7dhHHn/0OTt2nDjxWB68lhcn17dtlmURjoTpH+ynp6+HUDiEy+kiNSWVsqIyKksrKQoUUZhXiNvlnqB/LRH5OAUBkes0FBqi8XwjDecbaDzfSH1zPT29PfQP9mMYBna7HZ/XR5I3CZ/XF5cz2BmGwcDQAINDg/QP9hOJRgBwJ7jxeX0U5hdSXVZNUaCIokDRrB/uP3fuHCUlJRw6dIhFixaxY8cO1qxZQ3d3N36/f7rLE7mMxtdErlOiJ5GK0goqSiuA4SZGXcEuWi+20nqxlebWZs40nqGrp4uOrg5iRgybzYYv0YfP68Pj9uB2uXFeQ3OjmebSt/yBoQEGBod3/KZlYrfZ8SZ6SfYlM7dwLsWBYrIzsslKzyInM2dau/s99thj/PKXvwTA4XCQn5/PPffcwzPPPENaWtqEvMeKFSu4cOECqampE7I+kYk0+z95RGYYu91OZnommemZ1JTXAJe3uG3taKWlrYUzTWe42HWRvv4+wpEwpvnhcX6Xy4Xb5b7s5kpwTWszHMuyiMaihCNhItEIkUhk5HEsNhxuLCxcCS58iT5yMnMonVNKXlYeOZk5ZKcP7/hn4vH99evX8/zzzxOLxairq+Pzn/88wWCQX//61xOyfpfLRW5u7oSsS2SizbzfSJEbkM1mIz01nfTUdKrmVgEfnIQ40EdPXw+9/b309vfS099DT28PbZ1tdHR1jDwfDoeJxCLYsGFZFtiGA4fD7hi5dzgcl//M4bjsecuyMC0T0zQ/vP/gsWVal//8g/toNIppmSMn/DmdzpFQkuhJJJATIDMtk3R/Osm+ZJJ9yWSkZZCdnk1KUsqs6eLndrtHdtQFBQU89NBDbN26deT5559/nu9973ucPXuW4uJiNm3axJe//OWR5/ft28cXv/hFjh8/Tk1NDZs3b75s/R8/NNDQ0MBXvvIVdu3aRSQSobi4mO9///vcfffdU7K9Ih+lICAyTWw2GylJKaQkfbJN7iWhcOjDgPBBYLg0ghAKhxgKDxEKh0b+HoqEiEQiGKZBNBolbIYxTAPTNLHZbNhtdmz24Xu7ffiWYE/A6XbiSnCR4Ez48N7lwp/sx5/iH97JJyWT7E0eeexL9M2aHf3VqK+v57XXXiMhYbinwZYtW3j66af5yU9+wuLFizl06BBPPPEEPp+PRx99lIGBAe69917uuOMOXnjhBc6ePcvXvva1Ud/jySefJBKJsHPnTnw+H3V1dSQlqQeCTA8FAZEZzOP24HF7yM7IHvcyl4bwo7HoyLB9NBbFbrPjdDhxOB04Hc6R26WRhHj28ssvk5SUhGEYhEIhAH74wx8C8J3vfIcf/OAH3H///QCUlJRQV1fHz3/+cx599FF+9atfYRgGv/jFL/B6vVRXV9Pc3MzGjRuv+H6NjY088MADLFgw3JSqtLR0krdQ5MoUBERuMDabDVeCa+RYvYxtzZo1/OxnP2NwcJDnnnuOU6dO8dWvfpWOjg6ampp4/PHHeeKJJ0ZeH4vFRk78O378OAsXLsTr/XDa41tuuWXU99u0aRMbN27k9ddfZ+3atTzwwAPU1tZOzsaJjCG+vwaIiAA+n4+ysjJqa2v50Y9+RDgc5tvf/vbICZxbtmzh8OHDI7ejR4+yZ88eYHgE5mp94QtfoL6+ns997nO89957LF26lB//+McTuk0i46UgICLyMU8//TTPPvsshmEQCASor6+nrKzssltJSQkA8+fP58iRIwwNDY0sfykkjGbOnDl86Utf4sUXX+Qb3/gGW7ZsmbTtERmNDg2IiHzM7bffTnV1Nc888wzf+ta32LRpEykpKWzYsIFwOMyBAwfo7u7mqaee4pFHHmHz5s08/vjjfPOb3+TcuXM8++yzo67/61//Ohs2bKC8vJzu7m62b99OVVXVFG2dyOU0IiAi8imeeuoptmzZwrp163juuefYunUrCxYsYPXq1WzdunVkRCApKYmXXnqJuro6Fi9ezObNm/nud7876roNw+DJJ5+kqqqK9evXU1FRwU9/+tOp2CyRT1CLYRERkTimEQEREZE4piAgIiISxxQERERE4piCgIiISBxTEBAREYljCgIiIiJxTEFAREQkjikIiIiIxDEFARERkTimICAiIhLHFARERETimIKAiIhIHFMQEBERiWMKAiIiInFMQUBERCSOKQiIiIjEMQUBERGROKYgICIiEscUBEREROKYgoCIiEgcUxAQERGJYwoCIiIicUxBQEREJI4pCIiIiMQxBQEREZE4piAgIiISxxQERERE4piCgIiISBxTEBAREYljCgIiIiJxTEFAREQkjikIiIiIxDEFARERkTimICAiIhLHFARERETimIKAiIhIHFMQEBERiWMKAiIiInFMQUBERCSOKQiIiIjEMQUBERGROKYgICIiEscUBEREROKYgoCIiEgcUxAQERGJYwoCIiIicUxBQEREJI4pCIiIiMQxBQEREZE4piAgIiISxxQERERE4piCgIiISBxTEBAREYljCgIiIiJxTEFAREQkjv0vM+e4wWM82v0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create pie chart\n",
    "df_pie['Respondent'].plot(kind='pie',\n",
    "                          figsize=(5, 6),\n",
    "                          autopct='%1.1f%%', # add in percentages\n",
    "                          startangle=90,     # start angle 90°\n",
    "                          shadow=True,       # add shadow      \n",
    "                          )\n",
    "\n",
    "plt.title('Top 5 Databases that Respondents Wish to Learn Next Year')\n",
    "plt.axis('equal') # Sets the pie chart to look like a circle.\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>Respondent</th>\n",
       "      <th>LanguageDesireNextYear</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "      <td>C#</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4</td>\n",
       "      <td>JavaScript</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>SQL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9</td>\n",
       "      <td>Bash/Shell/PowerShell</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Respondent LanguageDesireNextYear\n",
       "0           4                      C\n",
       "1           4                     C#\n",
       "2           4             JavaScript\n",
       "3           4                    SQL\n",
       "4           9  Bash/Shell/PowerShell"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# your code goes here\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT * \n",
    "FROM LanguageDesireNextYear\n",
    "\"\"\"\n",
    "df_lg = pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "df_lg.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "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>Respondent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LanguageDesireNextYear</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>JavaScript</th>\n",
       "      <td>6630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HTML/CSS</th>\n",
       "      <td>5328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Python</th>\n",
       "      <td>5239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SQL</th>\n",
       "      <td>5012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TypeScript</th>\n",
       "      <td>4088</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Respondent\n",
       "LanguageDesireNextYear            \n",
       "JavaScript                    6630\n",
       "HTML/CSS                      5328\n",
       "Python                        5239\n",
       "SQL                           5012\n",
       "TypeScript                    4088"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group respondents by language and apply count() function \n",
    "df_lg = df_lg.groupby('LanguageDesireNextYear', axis=0).count()\n",
    "\n",
    "df_lg.sort_values([\"Respondent\"], ascending=False, inplace=True)\n",
    "df_pie = df_lg.head()\n",
    "df_pie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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x22+/4cKFCxbHBsqqr+53bK1Wi507d+L555+HQqGAwWAw//Xs2RNardZc5duqVSucOnUK48ePx7///ov8/Pwneh7lOI7Ds88+a7Hs3nMJlL3funbtCg8PD/PrM23aNKjVamRmZj5RDJs3b4ZYLIZYLEZ4eDh+/fVXzJ07F7169TKX2bhxIzw9PfHss89anKcmTZogMDDQXGXdpEkTSCQS/N///R+WLFmC69evV3rcfv36QSaTmR+7ubnh2WefxZ49e2A0GlFUVITDhw/jhRdesBiNIRQKMXToUNy8eROXLl2y2GefPn0sHjdq1AgAzOezvCpx8ODBFuUGDBgAkciyi9HGjRvRuXNnBAcHWzzn8vb48vdZuV69ekEoFFZ67Pspb1oaMGAAVq1ahVu3bj1wm3Ll1f/lr0FCQoK5CaBDhw4AgD179pjXtWjRAm5ubpXur1WrVtBoNBg4cCDWrVt33x77Dzrfj2rXrl0AYNWE+OKLL0KpVFbYpPQorl69iosXL5pf/3s/82lpaRbvqZ9//hnNmjWDTCYzf9/s3LnT4vumXJ8+fSAWiys8bkXnSavVPtJnNzo6GqNHj8YPP/yA1NTUCsts3LgRMTExaNKkicVz6969u1XTUq1atfDrr79i7dq16N27N2JjY2028qNHjx5o06YNateujSFDhgDg79zfj80SArVajcDAQHAcZ7Hc398fIpEIarXaYnlgYKDVPsqX3Vv2YZSf5LvbKB9XamoqYmNjzW1Ue/fuxdGjR83tfCUlJRblfXx8rPYhlUotyqnVaosEqFxFyx7WmjVrMGDAAISEhGDp0qU4ePAgjh49ilGjRkGr1VocWyQSwdvb+77HVqvVMBgMmDt3rvmCWP7Xs2dPADB/Gb733nuYPXs2Dh06hB49esDHxwddunR57GFX5RQKhcVFESg7l3c/nyNHjuDpp58GAPz666/Yv38/jh49ig8++ACA9evzqDp06ICjR4/i0KFD+OOPPxAREYGJEydi37595jIZGRnQaDSQSCRW5yo9Pd18nmrWrIkdO3bA398fEyZMQM2aNVGzZs0K2z4r+0zodDoUFhYiNzcXjDEEBQVZlQsODgZg/dm5971Z3rGo/ByVl7/32CKRyGrbjIwMbNiwwer5NmjQAACsLpQPOvb9dOzYEWvXroXBYMCwYcMQGhqKmJgYLF++/IHbxsXFQSAQID4+Hmq1GmfPnkVcXByAsiSradOmSEhIQGpqKpKSkiz6D1Rk6NChWLhwIVJSUtC/f3/4+/ujdevW2L59u1XZJ3nOFSn/7Pr5+Vks5zgOgYGBj/VdebfyfjGTJ0+2el3Hjx8P4M7r+s033+DVV19F69at8ffff+PQoUM4evQonnnmmQqfX0Xv03K2Ok8ff/wxhEIhpk6dWunzO336tNVzc3NzA2PM6j3bq1cvBAQEQKvV4s0337RIaJ+UVCqFRCKxiA2w/7m/n4ceZfAgPj4+OHz4MBhjFklBZmYmDAYDfH19LcrfOyzo7mUVXWAfhP3XmcwWQzjWrl2LoqIirFmzBuHh4eblTzJUzsfHx6pTGlDxeZDJZFad6ICyN8fd53Hp0qWIjIzEypUrLc75vdv6+PjAYDAgJyfHIim499heXl7mX5sTJkyo8HlERkYCKLtgvPnmm3jzzTeh0WiwY8cOvP/+++jevTtu3LgBhUJR4fa2sGLFCojFYmzcuNEieVi7dq1N9u/h4YEWLVoAAFq3bo3WrVujcePGGD9+PBITEyEQCMydxrZu3VrhPu7+xRkbG4vY2FgYjUYcO3YMc+fOxaRJkxAQEGDRE76yz4REIjHXAAkEAqSlpVmVK++4du/n7EHKP2vp6ekICQkxLzcYDFYXG19fXzRq1AiffvpphfsqT0pspW/fvujbty9KS0tx6NAhzJo1C4MGDUJERESF8wmU8/DwMF/0y4cUtm/f3rw+Li4O8fHxaNiwIQA8MCEAyjrBjhw5EkVFRdizZw8++ugj9O7dG5cvX7b4jrC18s9uVlaWRVLAGEN6erq5JuVxlb9f3nvvPfTr16/CMtHR0QDKvm86deqEn376yWL9vcM4y93747AqBAUFYdKkSfj888/x1ltvWa339fWFXC7HwoULK9z+3s/LuHHjUFBQgAYNGuD1119HbGwsvLy8qiR2Rzz3Nqsh6NKlCwoLC62+lH///Xfz+rvt3LnT4gJpNBqxcuVK1KxZE6GhoY98/PLj2GIoYvnJvHuYBmMMv/7662PvMy4uDmfPnsX58+ctllc0siIiIgKnT5+2WHb58mWr6mCO4yCRSCxe/PT0dKtRBuW/jlauXHnfYysUCnTu3BknT55Eo0aN0KJFC6u/ipI1T09PvPDCC5gwYQJycnLuO0b3SX8xAWXPWyQSWWTvJSUl+OOPPyo83pPWGNSuXRtvv/02zpw5Yz6HvXv3hlqthtForPA8lX+Q7yYUCtG6dWtzTdOJEycs1q9Zs8aiJqSgoAAbNmxAbGwshEIhlEolWrdujTVr1lg8J5PJhKVLlyI0NBR16tR5pOdWXpW+bNkyi+WrVq2yGDlQ/pzPnj2LmjVrVvicHycheJj3g1QqRVxcHL744gsAeKhmwc6dO+PKlSv4888/0bx5c4sELS4uDomJiVi7di3EYrFFsvAgSqUSPXr0wAcffACdTodz58499Lb3U9l5KP/eXLp0qcXyv//+G0VFRVbfq48qOjoatWvXxqlTpyp8Te9uTuE4zmro2unTp3Hw4MEniuFJvfPOO/D29sa7775rta537964du0afHx8Knxud486WrBgAZYuXYoffvgB69evh0ajwciRIy32Z4vvr3KOeO5tVkMwbNgw/Pjjjxg+fDiSk5PRsGFD7Nu3D5999hl69uyJrl27WpT39fXFU089halTp0KpVGLevHm4ePHiA4ce/vnnn1izZg169eqF8PBwaDQarF69GitWrMCIESPQuHHjh4r3zJkz+Ouvv6yWt2zZEt26dYNEIsHAgQPx9ttvQ6vV4qeffkJubu7Dn5B7TJo0CQsXLkSPHj0wY8YMBAQE4M8//8TFixcBWNZsDB06FEOGDMH48ePRv39/pKSk4Msvv7SqNuzduzfWrFmD8ePH44UXXsCNGzcwc+ZMBAUF4cqVK+ZyzzzzDNq3b4+33noL+fn5aN68OQ4ePGhOou4+9pw5c9ChQwfExsbi1VdfRUREBAoKCnD16lVs2LDB3Kb57LPPIiYmBi1atICfnx9SUlLw3XffITw8HLVr1670PNSsWRNyuRzLli1DvXr1oFKpEBwc/EgXk169euGbb77BoEGD8H//939Qq9WYPXt2heNsGzZsiBUrVmDlypWIioqCTCYz/zJ8FJMnT8bPP/+M6dOnm4cSLVu2DD179sT//vc/tGrVCmKxGDdv3kR8fDz69u2L559/Hj///DN27dqFXr16ISwsDFqt1vxr5d7PhFAoRLdu3fDmm2/CZDLhiy++QH5+vsWENbNmzUK3bt3QuXNnTJ48GRKJBPPmzcPZs2exfPnyR/5lUK9ePQwZMgTfffcdxGIxunbtirNnz2L27Nlwd3e3KDtjxgxs374d7dq1w+uvv47o6GhotVokJydj8+bN+Pnnnx85mS9/Lb744gv06NEDQqEQjRo1wieffIKbN2+iS5cuCA0NhUajwZw5cyAWi80J7v107twZs2fPxj///IPJkydbrIuNjQUArFu3Du3atYNSqbzvvsaOHQu5XI727dsjKCgI6enpmDVrFjw8PJ74F3q5ys5Dt27d0L17d7zzzjvIz89H+/btcfr0aXz00Udo2rQphg4d+lD737BhQ4X9JF544QXMnz8fPXr0QPfu3TFixAiEhIQgJycHFy5cwIkTJ7B69WoAZd83M2fOxEcffYS4uDhcunQJM2bMQGRkpFXyaE/u7u744IMP8MYbb1itmzRpEv7++2907NgRb7zxBho1agSTyYTU1FRs27YNb731Flq3bo0zZ87g9ddfx/Dhw81JwG+//YYXXngB3333HSZNmgSgbCZMAPjll1/g5uYGmUyGyMjIx6rVBuB45/6RuyH+595RBoyVDa8YN24cCwoKYiKRiIWHh7P33nvPamgM/usJOm/ePFazZk0mFotZ3bp12bJlyx543IMHD7IuXbqwwMBAJhaLmUKhYC1btmTz5s2rtEfm3cp7YVb2V977fcOGDaxx48ZMJpOxkJAQNmXKFLZlyxarHqZxcXGsQYMGFZ6f8PBwi2Vnz55lXbt2ZTKZjHl7e7PRo0ebhz2dOnXKXM5kMrEvv/ySRUVFMZlMxlq0aMF27dpV4SiDzz//nEVERDCpVMrq1avHfv31V3NP3rvl5OSwkSNHMk9PT6ZQKFi3bt3YoUOHGAA2Z84cq3M0atQoFhISwsRiMfPz82Pt2rVjn3zyibnM119/zdq1a8d8fX2ZRCJhYWFhbPTo0Sw5OfmBr8Hy5ctZ3bp1mVgsthjlUNF7ijFW4fNZuHAhi46OZlKplEVFRbFZs2ax3377jQGwGGKTnJzMnn76aebm5sYAWL0m96po2GG5H3/80WI4qV6vZ7Nnzza/T1QqFatbty575ZVX2JUrVxhjZe/X559/noWHhzOpVMp8fHxYXFwcW79+vXm/5e/JL774gk2fPp2FhoYyiUTCmjZtyv7991+rOPbu3cueeuopplQqmVwuZ23atGEbNmywKFPe6/3e3tXx8fFW7+HS0lL21ltvMX9/fyaTyVibNm3YwYMHKxztkpWVxV5//XUWGRnJxGIx8/b2Zs2bN2cffPABKywstHg+FY3kufv1Lj/2mDFjmJ+fH+M4zvz6bdy4kfXo0YOFhIQwiUTC/P39Wc+ePdnevXsrfG3ulZ+fz0QiEQNgMTqkXJMmTRgA9sEHH1itu/dztmTJEta5c2cWEBDAJBIJCw4OZgMGDGCnT582l3mU812Rys4DY2VD4t555x0WHh7OxGIxCwoKYq+++qp5eNz9lH92Kvsrd+rUKTZgwADm7+/PxGIxCwwMZE899RT7+eefLWKcPHkyCwkJYTKZjDVr1oytXbvW6rvufq9/ZaMeys/fg4bHVfYdUVpayiIjI61GGTDGWGFhIfvwww9ZdHQ0k0gk5mHVb7zxBktPT2eFhYWsbt26rH79+qyoqMhi2wkTJjCxWGwxiuy7775jkZGRTCgUVjpiqiKVXSvsde4fBseY/Sdo5zgOEyZMwA8//GDvQzuc//u//8Py5cuhVqstOpzYw59//onBgwdj//79aNeunV2PTe5ITk5GZGQkvvrqK6tfs4QQYi82azIgDzZjxgwEBwcjKioKhYWF2LhxIxYsWIAPP/ywypOB5cuX49atW2jYsCEEAgEOHTqEr776Ch07dqRkgBBCCCUE9iQWi/HVV1/h5s2bMBgMqF27Nr755hv873//q/Jju7m5YcWKFfjkk09QVFSEoKAgjBgxAp988kmVH5sQQojj46XJgBBCCCGOxXHuu0gIIYQQ3lBCQAghhBBKCAghhBBCCQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEEJACQEhhBBCQAkBIYQQQkAJASGEEBv5+OOP0aRJE77DII+JY4wxvoMghNiGVm9ETpEORaUGFJYaUKwzorDUgKJSA4p0RhSVGlBcakCp0QTGAJOJwcSATpBCUGqCgOPACQCO48AJOUikIkgVIkjkIkjlIkgU//0rL1suFNFvikfFcdx91w8fPhyLFy+u0hiKioowY8YMrF69Grdv34abmxsaNGiAyZMno3fv3o+938LCQpSWlsLHx+eht+nUqROaNGmC77777rGPS2xDxHcAhJCHk1mgRaq6GGl5WmQWlCIz/79/C7TIyC97nK81PNa+w6XeKMwoeeTthGIBpHIRZCox3LxlcPOR3fnXRwZ3HzkU7pLHislVpaWlmf+/cuVKTJs2DZcuXTIvk8vlVR7DuHHjcOTIEfzwww+oX78+1Go1Dhw4ALVa/Vj7Y4zBaDRCpVJBpVLZOFpiL1RDQIgDKdYZcD2rCNezi5CUVYTr2YVIyi5CUnYRCh7zYv8wpj9mQvAwRGIBVHclCV4BCviGquBbww0ypbhKjuksFi9ejEmTJkGj0YAxhtq1a2PcuHGYPHmyuczZs2fRqFEjXLlyBTVr1gTHcZg3bx7Wr1+PhIQEBAYG4ssvv8SLL75o3ubWrVt48803sW3bNggEAnTo0AFz5sxBREQEAMDT0xNz5szB8OHDK42ttLQUU6dOxfLly5GZmYmwsDC8++67GD16NBISEtC5c2ds3boVH3zwAU6fPo1///0Xu3fvxtq1a5GYmAgAGDFiBDQaDZo2bYoff/wRWq0WAwcOxNy5cyGRSDBixAgsWbLE4rhJSUnmOIl9UQ0BITzJLdLhzK28sr+bZf/e0lTNRZlPBr0JmoxiaDKKrdapvKTwDVXBJ1QF31A3+Iaq4OEvf2C1uiviOA6jRo3CokWLLBKChQsXIjY2FjVr1jQvmzp1Kj7//HPMmTMHf/zxBwYOHIiYmBjUq1cPxcXF6Ny5M2JjY7Fnzx6IRCJ88skneOaZZ3D69GlIJBIEBgZi8+bN6NevH9zc3CqMZ9iwYTh48CC+//57NG7cGElJScjOzrYo8/bbb2P27NmIioqCp6cndu/ebbWfnTt3QiaTIT4+HsnJyRg5ciR8fX3x6aefYs6cObh8+TJiYmIwY8YMAICfn58tTid5DJQQEGIHxToDTqRocPqWxnzxv5nrOBd/nV7Py3ELc0tRmFuK5DN3qqrFUiF8QpTwq+GGoNqeCKnjVW2aHUaOHIlp06bhyJEjaNWqFfR6PZYuXYqvvvrKotyLL76IMWPGAABmzpyJ7du3Y+7cuZg3bx5WrFgBgUCABQsWmBOrRYsWwdPTEwkJCXj66afxyy+/YPDgwfDx8UHjxo3RoUMHvPDCC2jfvj0A4PLly1i1ahW2b9+Orl27AgCioqKs4p0xYwa6det23+ckkUiwcOFCKBQKNGjQADNmzMCUKVMwc+ZMeHh4QCKRQKFQIDAw8InPH3kylBAQUgVKdEYcS8nBoetqHLymxumbeTCYHLd1TpObBwWUfIcBANCXGpF+PR/p1/NxZvctAIBngAIhdcqSg+A6nlB6SHmOsmoEBQWhV69eWLhwIVq1aoWNGzdCq9VaNAcAQNu2ba0el1fTHz9+HFevXrX65a/VanHt2jUAQMeOHXH9+nUcOnQI+/fvx65duzBnzhxMnz4dU6dORWJiIoRCIeLi4u4bb4sWLR74nBo3bgyFQmERa2FhIW7cuIHw8PAHbk/shxICQmyg1GDE8eRcHLyuxqHrapy6kQed0cR3WA9NLBIB/FQSPJTyJodze28DuJMgBP+XJLhSgjBmzBgMHToU3377LRYtWoSXXnrJ4oJamfLaAJPJhObNm2PZsmVWZe6ujheLxYiNjUVsbCzeffddfPLJJ5gxYwbeeeedh+7YqFQ+fhJZHZuFHB0lBIQ8ppwiHXZeyMCOCxnYeyUbxToj3yE9Pif7cr43QfCtoUJUEz9ENvaDb6hz93Lv2bMnlEolfvrpJ2zZsgV79uyxKnPo0CEMGzbM4nHTpk0BAM2aNcPKlSvh7+8Pd3f3hz5u/fr1YTAYoNVq0bBhQ5hMJuzevdvcZPC4Tp06hZKSEnOScejQIahUKoSGhgIoa1IwGp34s+NCKCEg5BFczyrE9vNlScCJVA2MDtwMUJ1k3yhE9o1CHNmQBHc/OaIa+yKyiR+CojzACZwr2REKhRgxYgTee+891KpVy6p5AABWr16NFi1aoEOHDli2bBmOHDmC3377DQAwePBgfPXVV+jbty9mzJiB0NBQpKamYs2aNZgyZQpCQ0PRqVMnDBw4EC1atICPjw/Onz+P999/H507d4a7uzvc3d0xfPhwjBo1ytypMCUlBZmZmRgwYMAjPR+dTofRo0fjww8/REpKCj766CNMnDgRAkHZHBYRERE4fPgwkpOToVKp4O3tbV5H7IsSAkIe4HJGAf45eQv/nkvH9awivsMhD5CfVYLEHTeQuOMG5O4SRDbyRWRjX9So6w2h2DkuNKNHj8Znn32GUaNGVbh++vTpWLFiBcaPH4/AwEAsW7YM9evXBwAoFArs2bMH77zzDvr164eCggKEhISgS5cu5hqD7t27Y8mSJXj//fdRXFyM4OBg9O7dG9OmTTMf46effsL777+P8ePHQ61WIywsDO+///4jP5cuXbqgdu3a6NixI0pLS/Hyyy/j448/Nq+fPHkyhg8fjvr166OkpISGHfKI5iEgpAKZ+VqsS7yNNSdv4UJaPt/hVLlJxUKIda7dk18sEyKqsR/qtQtCcB1Ph27D3r9/Pzp16oSbN28iICDAYh3Hcfjnn3/w3HPP8RPcIyifh2Dt2rV8h0IeAtUQEPKfolIDtp5Nx9rEW9h/NRvUGuBa9FojLh1Ox6XD6XD3k6Ne20DUbRsElZeM79DMSktLcePGDUydOhUDBgywSgYIqUqUEJBq7/B1NVYcvYGtZ9NRoqfOTdVBflYJDq9PwpENSahRzxt12wUhqokf7/dmWL58OUaPHo0mTZrgjz/+4DUWUv1QkwGplvK1evx9/Cb+PJyKK5mFfIfDu+rQZPAgMqUYtVsFoH77IPiGVjx7HyGujBICUq1czijA4gPJWHvylnMPE7QxSggsBUa5o0m3MEQ19nO6UQqEPC5KCIjLY4xhx4VMLNqfhAPXHu9ubq6OEoKKefjJ0aRrDdRtGwSRRMh3OIRUKUoIiMsyGE1Yf+o2fkq4Rs0CD0AJwf3J3cSI6RiChp1DIVfReSKuiRIC4nJKDUasOnYTv+y5hhs5jnMDIUdGCcHDEYkFiG4bhCZda8DT/8HTCRPiTCghIC6jqNSAZYdTsGBvEjILSvkOx6lQQvBoOA6IbOKHFj0i4BdGHRCJa6CEgDi9olIDftuXhIX7k6ApduA79DgwSggeEwfUbOKHVs9GwTvYMe4WScjjooSAOC290YQ/D6di7q4ryC7U8R2OU6OE4MlwHFCnVSBa9o6Eh9/D3SmQEEdDCQFxOowxbDydhtnbLiFFXcx3OC6BEgLbEAg5NOgQjJa9IyF3o/NJnAslBMSpHLiajc+3XsTpm3l8h+JSKCGwLbFMiKbdwtCkaxjEUhquSJwDJQTEKVxKL8Cnmy9gz+UsvkNxSZQQVA2FhwStn41CvfZBDn0zJUIASgiIgyssNeDb7Zex5EAyDHS3oSpDCUHVCoh0R6fB0TQlMnFolBAQh7X+1G18uuk8MvJpCGFVo4Sg6nECDo06haJVn0hIZHRfOeJ4KCEgDudqZiE+Wn8W+6/SNMP2QgmB/Sg9pejwYm3Uau7PdyiEWKCEgDiMEp0R3++6ggV7r0NvpLelPVFCYH9h9b3RcWAdePjRjIfEMVBCQBzCgavZePvv07iZS1MN84ESAn4IxQI06x6O5t3DIRQL+A6HVHOUEBBeFesMmLX5IpYeSgG9EflDCQG/PAMU6DqiPgIi3fkOhVRjlBAQ3hxJysFbqxJxg2oFeEcJAf8EAg4tekWgeY8ICAQ0RJHYHyUExO60eiO+2noRiw4kg0YSOgZKCBxHQKQ7uo6sT3dTJHZHCQGxq5OpuZi04iRS6LbEDoUSAscikgrR4YVaaBAbwncopBqhhIDYBWMMP+y6gm93XKFaAQdECYFjimjki6eG1qX7IhC7oG6tDio5ORkcxyExMZHvUJ6YurAUA+cfwNfbKRkg5FEkn87G8hmHkXw6m+9QSDXgcgnBiBEj8Nxzz9n1mH///Tdat24NDw8PuLm5oUGDBnjrrbeeaJ81atRAWloaYmJiHnqbxYsXw9PT84mOa2uHrqvR9et4HErW8B0KIU6ppECPTfNOY8/ySzAaTXyHQ1wYzZ/5hHbs2IGXX34Zn332Gfr06QOO43D+/Hns3Lnzsfep0+kgkUgQGBhow0jtizGG2VvOYd6eZDBQj2lCntSZ3beQfbMQ3f8vBkoPKd/hEBfkcjUEd9u6dSs6dOgAT09P+Pj4oHfv3rh27Zp5fdu2bfHuu+9abJOVlQWxWIz4+HgAwNKlS9GiRQu4ubkhMDAQgwYNQmZmprn8xo0b0aFDB0yZMgXR0dGoU6cOnnvuOcydO9div+vXr0eLFi0gk8ng6+uLfv36mddFRETgk08+wYgRI+Dh4YGxY8daNRkkJCSA4zhs2rQJjRs3hkwmQ+vWrXHmzBnz+pEjRyIvLw8cx4HjOHz88ce2PJ0PTV1Yiue/T8CPe1IoGSDEhtKu5WHVZ0eRdo1u/01sz6UTgqKiIrz55ps4evQodu7cCYFAgOeffx4mU1m12+DBg7F8+XLc3a9y5cqVCAgIQFxcHICyX+szZ87EqVOnsHbtWiQlJWHEiBHm8oGBgTh37hzOnj1baRybNm1Cv3790KtXL5w8eRI7d+5EixYtLMp89dVXiImJwfHjxzF16tRK9zVlyhTMnj0bR48ehb+/P/r06QO9Xo927drhu+++g7u7O9LS0pCWlobJkyc/zml7IseSsvHUVzuRmFZs92MTUh0U5+mw9tsTOLvnFt+hEBfjcqMMRowYAY1Gg7Vr11qty8rKgr+/P86cOYOYmBhkZWUhODgYu3btQmxsLACgXbt26NChA7788ssK93/06FG0atUKBQUFUKlUKCoqwoABA7B582aEh4ejTZs2ePrppzF48GBIpVLzPqOiorB06dIK9xkREYGmTZvin3/+MS9LTk5GZGQkTp48iSZNmiAhIQGdO3fGihUr8NJLLwEAcnJyEBoaisWLF2PAgAFYvHgxJk2aBI1G8wRn8PH9se8yPt50GUZGtQLOhkYZOKd67YMQ93I0TXtMbMKl30XXrl3DoEGDEBUVBXd3d0RGRgIAUlNTAQB+fn7o1q0bli1bBgBISkrCwYMHMXjwYPM+Tp48ib59+yI8PBxubm7o1KmTxT6USiU2bdqEq1ev4sMPP4RKpcJbb72FVq1aobi47FdyYmIiunTpct9Y760xqEzbtm3N//f29kZ0dDQuXLjwUNtWFcYYpiw7gKkbr1AyQIgdXdifhjVfn0BhrpbvUIgLcOmE4Nlnn4Varcavv/6Kw4cP4/DhwwDKmgHKDR48GH/99Rf0ej3+/PNPNGjQAI0bNwZQ1uTw9NNPQ6VSYenSpTh69Kj5V/zd+wCAmjVrYsyYMViwYAFOnDiB8+fPY+XKlQAAuVz+wFiVSuVjP0+O4+8irCksQd9v/sXqM7m8xUBIdZaZnI9Vnx3F7Sv0GSRPxmUTArVajQsXLuDDDz9Ely5dUK9ePeTmWn9gnnvuOWi1WmzduhV//vknhgwZYl538eJFZGdn4/PPP0dsbCzq1q1r0aGwMhEREVAoFCgqKgIANGrU6IlGHdzt0KFD5v/n5ubi8uXLqFu3LgBAIpHAaDTa5DgP40xSOrp9tQ2ns+x3TEKItZICPdZ9l4hLh9P5DoU4MZcddujl5QUfHx/88ssvCAoKQmpqqtWIAqDsl3nfvn0xdepUXLhwAYMGDTKvCwsLg0Qiwdy5czFu3DicPXsWM2fOtNj+448/RnFxMXr27Inw8HBoNBp8//330Ov16NatGwDgo48+QpcuXVCzZk28/PLLMBgM2LJlC95+++1Hfl4zZsyAj48PAgIC8MEHH8DX19c870JERAQKCwuxc+dONG7cGAqFAgpF1cyHvuHwRUxZewla5rJvIUKcisnIsGPxeRTllaLZ0+F8h0OckMvVEJhMJohEIggEAqxYsQLHjx9HTEwM3njjDXz11VcVbjN48GCcOnUKsbGxCAsLMy/38/PD4sWLsXr1atSvXx+ff/45Zs+ebbFtXFwcrl+/jmHDhqFu3bro0aMH0tPTsW3bNkRHRwMAOnXqhNWrV2P9+vVo0qQJnnrqKXPzxaP6/PPP8b///Q/NmzdHWloa1q9fD4mkrDNYu3btMG7cOLz00kvw8/OrtGPkk2CM4edNRzDpnyuUDBDiaBhwcM017Ft9BS7WX5zYgcuNMnjmmWdQq1Yt/PDDD3yHYlPlowxyc3N5m43QaDRi+p/x+ONsCRjncrlktUajDFxP7Rb+6DKiPoQi+qySh+My75Tc3Fxs2rQJCQkJ6Nq1K9/huJyi4hK8Om8Tfj+rpWSAECdw5VgmNv5wCjqtge9QiJNwmW/2UaNG4ZVXXsFbb72Fvn378h2OS8lU52DonI3YdksI8DiigRDyaG5ezMU/X59AUV4p36EQJ+ByTQbEtq6l3MIrC/fgaqk736GQKkRNBq7N3VeGZ19rAs+AqulkTFyDy9QQENs7ffEahv2yl5IBQpxcfrYWa2Yfh/p2Id+hEAdGCQGp0OFT5zF2yRHcMrrxHQohxAbK5yrITS/iOxTioCghIBYYY9h9+AQmLk9EBqOaAUJcSUm+Dmu/PQlNBt18jFijhICYMcawZfdBvPn3BWTBg+9wCCFVoDhPh7XfnIAmk5ICYokSAgKgbI6Bv7fswtRN16AWePIdDiGkChXl6bDu25PIyyrhOxTiQCghIDAajVi1cRtm7boJtdCb73AIIXZQmFuKtd+eQH42JQWkDCUE1Vx5MvDN3nSoRb58h0MIsaPCnFKs++4kCnLo9smEEoJqzWg0YvXGbZiz5yayRP58h0MI4UF+thZrvzmBwlyavKi6o4SgmjIajfhr03b8tPs60sXBfIdDCOFRfrYWG39IhK6EpjmuzighqIZMJhPWbNmJBfEXkCKJ4DscQogDUN8qwpb5Z2A0mvgOhfCEEoJqxmQyYe2/8ViyIxFXpbX5DocQ4kBuXsxFwtKLfIdBeEIJQTXCGMOW+H34/d/DuCCrCwa6UREhxNLFg+k4uimJ7zAIDyghqEb2HjmBPzbtxXlZfRgh5DscQoiDOrIhCRcPpfEdBrEzSgiqiRNnL2DJP//itKQudBDzHQ4hxMHF/3ERNy/m8B0GsSNKCKqBy9dTsHjVepwwRaAYMr7DIYQ4AZORYcv8s3SHxGqEEgIXdzMtAwtXrsXxIi/kCuj+BISQh6crMWDjD6dQlEdzFFQHlBC4sOwcDRas+AfH0g24JQ7hOxxCiBMqzCnF1vlnYaLhiC6PEgIXVVBYhEWr1uLYtUwkyevwHQ4hxImlX8/DgTXX+A6DVDFKCFyQwWDA8nVbcfDMFVx3bwwjvcyEkCd0aucNXD2eyXcYpArRlcLFlM01sB/xh47jhmdTFJtEfIdECHERu/64AE1GMd9hkCpCCYGLOXb6PNZti0e6WzSyjHK+wyGEuBC91oitv5yBXmfkOxRSBSghcCEpN2/jz7WbkcHckWSiWxkTQmxPfasIu/+8xHcYpApQQuAiNPkFWLx6PVKzCnBFUovvcAghLuzSoXSc23uL7zCIjVFC4AL0egOW/bMZ5y5fwy2vxtCaaFpiQkjV2rvyCrJSC/gOg9gQJQROjjGGDTt2Y9/RkygJaIh0Pc1ESAipekaDCVt/OQNdiYHvUIiNUELg5E6eu4hNO/dC6BWMs1pvvsMhhFQj+dla7F11me8wiI1QQuDEstS5WLn+X2iNQKIpnG5nTAixu4sH03E9MYvvMIgNUELgpPR6A1as34qUm7eR5tEAhUaab4AQwo+EZRdRnK/jOwzyhOgq4qR27D2EgydOQRxUB9eLFHyHQ8gju3r7NHacWonU7CvIL1Zj7NPT0Tiyg3n9H/Ff4PDlbRbbRPjXw+Tnf6h0n4cubcXShK+sln87egvEIgkA4OiVHVh3eAF0Bi3aRvfA821fMZdTF6Tjh01v4+1+P0EuUT7pU6w2Sgr02P3nRfQY14jvUMgToITACV28moR12xOgdPPE/hJ/vsMh5LGUGkoQ4lMTbaKfwYLtH1dYpn6NlhjS6W3zY6HgwV9ZMokS015abLGsPBkoLMnDn7u/xpBOb8PXPQg/bfkAtYMbIya8DQBg5d7v0LfVWEoGHpGHtxiBu39BXlA3ePTty3c45DFRQuBk8goKsXzdVhQWFSPDpwmKS2iIIXFODcJao0FY6/uWEQnFcFc8WmdZDqh0m+yCNMgkSjSv1RkAUCe4CdJzUxAT3gZHr+yEUCBGk6jYRzpedcZxQB3/PASt+xQCbREyrh+Dsn17iHxpYjRnRAmBEzGZTPh703ZcupYEVY16uJJHv2KIa7ty+xTeXdIfcqkStYMa49lWo+Am97rvNqX6EkxdNhCMmRDiUxO9W45EDd/aAAB/jxDoDaW4kX0F3qoApGRdQpu6z6BIm49Nxxbjf89+bY+n5RLcvcRocHMN5PFbzcuMeXlInz4DoXO/5zEy8rg4xhjjOwjycA6fPIN5v6+El7cPdmijqCMhsZlJxUKIdRLejj9xfherPgTHr8ZDKpbD2y0A6vw0bDy2GCaTEW/3/wliYcWxJmWcR1beLQT7REGrK0LCmTU4d+MI3nvhF/h7hAIATiXtw8Zji6E3lKJl7a7o1WI4liZ8hRCfKNTwqY2/DvwIo8mAni2GoWlUnF2evzNhYFAarqLVid8gKK54YqKQb7+Be48edo6MPCm6ojiJHE0e/tm6CwKBAJdYCCUDxOWVV+sDQLB3JML8ojHtz0E4l3K40mr9yID6iAyob34cFRiDL/4eh91n1+LF9hMBAI0jO1gkHpdvJ+J2ThIGtH8NH68YhpFdPoC7whtf/TMBtYIaPbBGojrhhKWIurYKEcmH7lsu/ZNPoWjTBiIvOnfOhIYdOgHGGNb9m4Dk1FuQ+UfgQjGNKiDVj4fSB96qAGTl33zobQScAOF+0cjKq3gbvVGHVXvnYGDsJGTl34LJZETt4MYI8KwBf49QJGdcsFX4Tk9hSkLbPR8+MBkAAKNajYxZs+wQFbElSgicwPEzF7D78DGEBAXicIE3QBMQkWqoUJuH3KJMuCt8Hnobxhhuqq9Vus3W40tRP6wVavjVgYmZYGJ3butrNBlgYqYnjtvpCXWIuLECbfbMhkxf/NCb5W/YiJLExKqLi9gc1Ts7OE1+AdZs2QEASBMHIKdYzHNEhNhGqb4EWXl37pinLkjHzeyrUEjdoJS5Y9OxJWgSGQsPpQ/UBenYcOQ3qGQeaBxxp7r/912fw0Ppi76txwAANh/7HREB9eDvEQKtrhgJZ//BTfVVDOjwutXx03KSceJaAt59YT4AIMAzDBzH4cDFzXCXeyNDk4pw/+gqPguOTY5UNN43D4rSx7iJEWNInzULEStWgOPoR4wzoITAgTHGsGH7blxPuYmImrXwT7Y73yERYjMpWZfw/Ya3zI/XHPwJANC6ztN4KXYSbuck4cjl7SjRFcJd4Y06wU0wqutUyCR3msxyCjMtLjYlukIs3/MNCopzIZMoEepbC5Oe/RYR/nUtjs0Yw/I936Bfu1chFcsBABKRFEM6vY1V+76HwajHgPavwVPpV5WnwHEJ9Ai7uQG1Lu98ot1oT51G/saN8Hj2WRsFRqoSjTJwYInnLuH7hX/C08MN5xGGi8U0zJBUDb5HGRDHIeNuodGheVCVaGyyP1FgIGpu2QyBXG6T/ZGqQ30IHFRxiRb/bN0FvdEApvTBJepISAipSgIDQjM2oF38ZzZLBgDAkJ4O9YLfbLY/UnUoIXBQCQeP4vL1ZETWCMGBPA+6kyEhpMpIuAy0PDQddS5sfXDhx6BeuBD69PQq2TexHUoIHFBaZja2JuyHp4c7UvXuyNBJ+Q6JEOKKBAYEZ29Fh/gZcCvOqbLDsJISZH79TZXtn9gGJQQOhjGGzTv3IiM7B/5+vjhW4MZ3SIQQFyQWZKH5kU9R9+wGuxwvf+NGlJw6ZZdjkcdDCYGDOXf5GvYfS0RoUAAulbjRjISEENvijAjM3YHYXR/DozDTfsdlDBmf0WRFjowSAgei0+mxflsCdHo9VG4eSCxU8R0SIcSFiARqNDkxC/VP/cPL8UtOnULeho28HJs8GCUEDmTf0ZM4e/kqImoE42yREloT3dqYEGIDnBH+ebvRcdc0eOel8RpK5jffwKTV8hoDqRglBA4iR5OHzbv2QimXgxPLcIZqBwghNiASatD45FeIObmK71AAAIa0NGhWOUYsxBIlBA5i96HjuJGWgdCgQJwuVEHH6KUhhDwBzgTfwgPosPMD+Ghu8B2NBfXCRWB6Pd9hkHtQjzUHkKnOwa79R+Dr5YlSiHCuqPrNSJh3cBWKLx+EPucmOJEE0pB68IobAbFPqLlM9qZvUXTWcipVSVA0goZ9Xel+CxK3oujcLuizUsrKB9aCZ8dhkAbfmaO+8Fw8NLuXgOm1UDV6Gl6dR5nXGfIykLFyKoKGfweBlCaHIs5BKMxD/cRf4adO4juUChnS05G3bh08X3iB71DIXSghcADx+48gKzsH9aNr4nCBCoZqWDugvXEWbs16QRJYG2BGaPb8gYxVUxE8+icIJDJzOVlkc/j2nHRnQ+H938LaG2egrBcHadd64ERi5B3+GxmrpiF49I8QufnCWJyHnK1z4dNzEkSegcj8azqkYQ2hqNkSAKD+dx684kZQMkCcA2eCd9ExNDzyO4Rw7Fnp1b8ugEe/fuAE1e/7zlFRQsCzW+mZSDh0HP5+3ihlIlysplMUBwyYYfHYp+ck3Jw7GLqMq5DViDEv50RiCFVeD71fv2enWO73mddQfGk/tCmnoIrpAoMmHZxUAWW9jgAAWVgj6LNTgZotUXQ+AZxQBEV0uyd4ZoTYh0BYgHqnf0NA1hW+Q3koupQUFPz7L9x79OA7FPIfSs14tnPfYeRq8uDn443zRUoYq2HtQEVMpUUAAIHMsnOlNvUMbswdjFu//B/UW76HsUjzSPtl+lLAZIRAVjbhk8g7BExfCl3GNRhLCqBLuwyJXwSMJQXQ7F0G727jbPJ8CKk6JniVnECHXR84TTJQLvuXX/kOgdyFagh4lHzjNvYfPYlAfz8YmADnq2HfgYowxpC7awGkofUh8YswL5dHNYeibgeI3P1gyMuAZu9SZKx4H0HD54ATiR9q37m7l0Co8oE8ogkAQChTwbfXG8je+A2YQQdlzFOQRzVH9ubv4Na8Nwx5Gcj8eyZgMsCj/SAo63aogmdMyOMRCIsQfXYRgjIu8B3KYym9cAGFu3dDFRfHdygElBDwhjGGbXsOIr+wCKHBgThXpEAp1Q4AAHK2/wxdZjICB39psby8Wh8AJH4RkATWxq2fRqHk2tGHqtbPO/wXii/sRsDAWeBEd271q6jTDoo6d7bXpp6GPisF3t3G4fYv/wffZ6dAqPRC2u9vQlYjBkKl55M/SUKeCIOH7iwaHfoVYpOR72CeSPb8XyghcBB0BeLJtZQbOJJ4FsGB/mDgcJZqBwCUJQMlVw8jYOBnELn73resSOUNkYcf9Lm3H7jfvMNrkHdwNfwHzITEP7LScsygR862n+DdfQIMuWlgJiNkYQ0h9gmF2DsEpWmXHvk5EWJLnLAE0Vd+QfMDPzt9MgAAJSdOoPjYMb7DIKCEgDd7D59EUXExPN3dcL1EXu3vWcAYQ872n1B8+QACXv4UYs/AB25jLMmHIT/7gZ0M8w7/jbwDKxDw4nRIg2rft6zmwArIoppDGlgLYCbgri9cZjIAJtPDPSFCbI7BTX8B7ePfR8it03wHY1PZ83/hOwQCajLgxc20DBxJPIMAPx9wHIfTNCshcrb/hKLzu+Hf70MIJAoYC3MBAJxUAYFYCpOuBHn7/oQiuh2EKu+yPgS7f4dQ7g5F7bbm/WRv/BpCNx94xY0AUNZMoNm7FL7PToHII+DOfiUyCCRyixh0WSkovrgHQSPmAgBE3qEAJ0DBqW0QqrygV9+E5AEJBSFVgRNqUevyn6hx4zjfoVSJor17oT1/HrL69fkOpVqjhIAHB4+fQk5ePmKia+GmVoocw8N1iHNlhSc3AwAylr9nsdyn5ySoGnYFOAF0WckoPLcLJm0RhCovyMIawbfvOxZzBBjyswDuTsVXwYnNgNGA7LWWd1nzaD8Qnh0Gmx8zxpDz7w/wemqsed4DgVgKn56TkLP9JzCjHt7dxkHkdv9mDEJsi0FluILG++ZDanDt+f+zf/kVod99y3cY1RrHGHPs2StcjDo3D9O//QlGE0OQvy+25XghVSt/8IaEVKFJxUKIdZIHFyR2wwlLEXVtJcKTD/Mdin2IRKgdvwsiPz++I6m2qA+BnR0+eRqZ2TkI8PVGoUGIG1rZgzcihFQjDErTdbTd80H1SQYAwGBA3rp1fEdRrVFCYEeFRcWIP3AM7m5uEAgEuFCsAAPHd1iEEEch1CEydQVa7/kaMn0J39HYnebvNXyHUK1RQmBHR0+dw820dAQF+MLEgMvVdJpiQog1OUtBm70fIvL6Pr5D4Y0uKQnFx12z46QzoE6FdqLXGxB/8CjkMhnEIhGSSmQoMQn5DosQwjeBHuE316Hm5Xi+I3EImtV/QdG8Od9hVEtUQ2An5y5fQ/KN2wgKKOswc4lqBwip9mS4hdb7p1EycJf8f/+FsbCQ7zCqJUoI7OTwydMwGo2Qy6QoMAhxq1TKd0iEEL4IDAhNX4d2CZ9BWZrPdzQOhZWUIH/TZr7DqJYoIbCD2xlZOHnuEvx9vQGU9R2gzoSEVE9SLh0tD01HnYvb+A7FYWn+/pvvEKol6kNgByfOnIcmLx8hgbUAANdKaN4BQqodgQHBGdtQ99wmviNxeNrTp6G9fBmyOnX4DqVaoRqCKlZaqsP+Y6fg5qYCx3HI0omRX83vW0BIdSMRZKL5kU8oGXgEeVRLYHeUEFSxc1eu4ebtdAT6+QCg2gFCqhWBEUE529Fh13R4FGbxHY1TyVu3Hkyn4zuMaoUSgip2NPEsTIxBKpGAMeA6JQSEVAtigRrNjn6KeqfX8h2KUzJqNCjYtYvvMKoVSgiqUKY6B4nnL8PPp6wzYbpOgmKae4AQ18YZ4a9JQOyuafAsyOA7GqeWv4maWOyJGrOr0LlL16DJL0C9WpEAqLmAEFcnEuYi5thP8M67xXcoLqFw/wGYdDoIJHTjLXugGoIqwhjDsdPnIBGLIBAIYGJAMt3IiBDXxJngW7AfHXZ+SMmADbHiYhQfOsR3GNUGJQRV5FZ6Jq4mpcLPu6y54HapFFpqLiDE5QiFeWh06ms0Ov4nfaFWAepHYD/UZFBFzl+5jryCIoQGBwKg2gFCXA5ngk/hUcQc/QNCML6jcVmFCbv5DqHaoISgCphMJhxNPAu5TAqOK5uR8AZNVUyIyxAIC1D/1AL4Z1/lOxSXZ0hPR8m5c5A3aMB3KC6PEoIqkHorHUk3bsPvv6mK1XoRimgyIkJcgAleJSfR6PBiCGHiO5hqo3BXPCUEdkBNXlXg3OVrKCwqhpuy7I6GN6i5gBCnJxAWov6FH9H08EJKBuysMJ7uBmkP9LPVxoxGI44knoVSIafmAkJcAoNH6Rk0OrwAYpOR72CqJe3589BnZEAcEMB3KC6Naghs7FZ6Jm6lZ8LX2xMAoDVxyNTRGFpCnJFAWIy6l+ej+cH5lAzwrJBGG1Q5Sghs7EpSKoqKi6H6r7ngllZGtzomxOkwuOvPo338+wi+fYbvYAiAAmo2qHLUZGBj5y5fg0gkouYCQpwUJyxB7UvLEHrzJN+hkLsUHzoMU3ExBAoF36G4LKohsKG8gkJcvp4Cb08P87KblBAQ4iQYVIZLaLf7A0oGHBDT6VB04ADfYbg0Sghs6GryDeTm5cPLww0AoNGLaHZCQpwAJ9SiZtLvaLXve0gNpXyHQypRfPwE3yG4NGoysKHL15JhYgwiUdlpTafOhIQ4OAal8Toa7/8JMn0J38GQByhJTOQ7BJdGCYGN6PUGnLpwGe4qpXkZJQSEODChDpFJfyHy+n6+IyEPSXvuHJhOB47uflglKCGwkdTbacjIViPQ39e8jBICQhyTgiWj0d55UOiK+A6FPAKm00F7/jzkTZrwHYpLooTARpJSb6FEWwqFrGxWwiKjAIU0XTEhjkWoQ0TKWkRdpRvmOKvixERKCKoIXbFs5GryDYjvGm6YTqMLCHEoMtxA433zoCzN5zsU8gRKTiYCI/iOwjVRQmADOp0el5NSqP8AIY5IoEeNWxtR+9IOviMhNkAdC6sOJQQ2cCs9E5q8AgT4+ZiXUUJACP+k3G00Ovgj3Eo0fIdCbMSQkQF9WhrEQUF8h+JynGoegtTUVDDGrJYzxpCamspDRGVSb6ehRKuFQl7Wf8Bg4qAxUK5FCG8EBoRmbkT7+E8pGXBBJSdp4qiq4FQJQWRkJLKysqyW5+TkIDIykoeIyiSl3gbHceb+AzkGEd2/gBCeSLgMtDg8A3XOb+E7FFJFiqnZoEo41c9Yxpj5onu3wsJCyP7r3W9vRqMRF68lwd1NZV6m1ot5iYWQak1gRFDmDtQ7u57vSEgVK0k8xXcILskpEoI333wTAMBxHKZOnQrFXTe3MBqNOHz4MJrwNAwlLTMb6lwNvO66fwElBITYl1iQjYZH58GzIIPvUIgdaC9cgKm0FAIpjeayJadICE7+117EGMOZM2cguWuWKolEgsaNG2Py5Mm8xHYzLQNFxSWoERxoXpZDCQEh9sEZEZizG/VP/c13JMSe9HqUXrhA8xHYmFMkBPH/3Qd75MiRmDNnDtzd3XmO6I70zGwwMAgEZd0xGCvrQ0AIqVoiQQ5ijv8M77xbfIdCeFCalEwJgY051ZVr0aJFfIdgJfnmbUjFd2os8o1CGJhT9dUkxLlwJvhp9qHByZXO1Sua2JQuJZnvEFyOUyUERUVF+Pzzz7Fz505kZmbCZDJZrL9+/bpd49HrDUi9nQ6l8k6fBuo/QEjVEQo1aHByPnxz+BtmTByDLjmF7xBcjlMlBGPGjMHu3bsxdOhQBAUFVTjiwJ6ycnJRUFgE77s6FOZSQkCI7XEm+BQcRsNjS6lWgAAAdCmUENiaUyUEW7ZswaZNm9C+fXu+QwEAZGSrUVRcgtCgOx0K841CHiMixPUIhfmon/gr/NT2rQEkjo0SAttzqoTAy8sL3t7efIdhlpGlBhggFN75zZJPHQoJsQ3OBO+iE2h4ZAmEMD24PKlWWHEx9BmZEAf48x2Ky3Cq2reZM2di2rRpKC4u5jsUAGVDDgVCy1NINQSEPDmBsBANzs1FkyOLKBkgldIlJ/Mdgktxqp+zX3/9Na5du4aAgABERERALLZsrz9x4oTdYmGMISn1FpQKuXmZzsSh1EQJASGPj8FTm4hGhxdBxIx8B0McnC4lGcrWrfgOw2U4VULw3HPP8R2CWX5hEXLzC6CQ30kIqHaAkMcnEBahzvnFCE47z3coxEnQSAPbcqqE4KOPPuI7BLNcTT602lJ4uruZlxVQ/wFCHgODu+4cGh9aALFJz3cwxIlQx0LbcrormEajwV9//YVr165hypQp8Pb2xokTJxAQEICQkBC7xZGbnw9taSlk0rsmJaKEgJBHwglLUPviHwi9RTerIY+O+hDYllNdwU6fPo2uXbvCw8MDycnJGDt2LLy9vfHPP/8gJSUFv//+u91iydXkgwHmKYsBajIg5OExuOkvofHe+ZAYdXwHQ5yU/sYNMJMJnMCp+sc7LKc6i2+++SZGjBiBK1euWNzuuEePHtizZ49dY9HkFwDMclkRJQSEPBAn1KLW9cVouX8uJQPkiTCdDoYMusOlrThVDcHRo0cxf/58q+UhISFIT0+3ayxpmVkQiy1Pn9bkVPkVIXbGoDReReN9P0Nm0PIdDHERxtxciIOC+A7DJThVQiCTyZCfn2+1/NKlS/Dz87NbHIwxpGdmQy6zvBd3CSUEhFSIE5Yi6voqhCcd4jsU4mKMeXl8h+AynOoK1rdvX8yYMQN6fVlPZI7jkJqainfffRf9+/e3Wxza0lJo8gshk1omBFpqMiDEisKUhLZ7PqRkgFQJSghsx6kSgtmzZyMrKwv+/v4oKSlBXFwcatWqBTc3N3z66ad2iyNHYz3CQGfiYAS/N1sixKEIdYi4sQJt9syGTO8Ys4sS12PUUEJgK07VZODu7o59+/Zh165dOHHiBEwmE5o1a4auXbvaNY6i4hKU6vSQSu4kBNRcQMgdcqSi8b55UJQW8B0KcXFUQ2A7TpUQlHvqqafw1FNP8Xb8opISGAwGi06F1KGQEAACPcJubkCtyzv5joRUE5QQ2I7DJwTff//9Q5d9/fXXqzCSO4qLSwCU9WEoV0L9B0g1J+NuodHBeVCVaPgOhVQjxjwN3yG4DIdPCL799luLx1lZWSguLoanpyeAspkLFQoF/P397ZYQFJVYD5miGgJSbQkMCE3bgjoXtvIdCamGqIbAdhz+KpaUlGT++/TTT9GkSRNcuHABOTk5yMnJwYULF9CsWTPMnDnTbjEVF5fcOycRDIw6FJLqR8JloOWh6ZQMEN6YqFOhzTh8DcHdpk6dir/++gvR0dHmZdHR0fj222/xwgsvYPDgwXaJI7+wCALOMgGghIBUKwIDgjN3oO7ZDXxHQqo5qiGwHadKCNLS0sxzENzNaDQiw47TV+bm5UMsFlsso4SAVBdiQRYaHpkHz8JMvkMhhBICG3L4JoO7denSBWPHjsWxY8fAWFml/bFjx/DKK6/Ydehhbl4BJPdMW2ykhIC4Os6IwNwdiN31MSUDxGFQQmA7TpUQLFy4ECEhIWjVqhVkMhmkUilat26NoKAgLFiwwC4xMMZQUFQEscgyIaAaAuLKRAI1mpyYhfqn/uE7FEIssNJSmEpL+Q7DJThVk4Gfnx82b96My5cv4+LFi2CMoV69eqhTp47dYjAajTAajBa3PQYoISAuijPCX7MPMSdX8R2J0zlWXIyFOWqc05Yiy2jA98Eh6OrmZl6fbTDgm6xM7C8qRoHJiBZyBd4PCEDEXROe3etKaSl+yM7COa0Wtw0GvOvnj2He3hZlNuTn4dusLBSbTOjv4Ykp/v7mdbf0Ooy5cQOrwyOgErrQUGmDAbhnKnny6JyqhqBcnTp10KdPH/Tt29euyQAA6A0GGE0mCISWp46aDIirEQk1aHzyK0oGHlOxyYRoqQwfBgRYrWOM4bVbN3FDr8cPISH4OyICQWIxRt9IRbHJVOk+tSYTQsUSvOnnD98KLui5BgOmpadjip8/fg2tgXX5edhdWGhePz0jA2/6+btWMgCYm5BtJTMzE6+88grCwsIglUoRGBiI7t274+DBg+YyBw4cQM+ePeHl5QWZTIaGDRvi66+/htFotNgXx3FYu3atTeOrKk5VQ2A0GrF48WLs3LkTmZmZMN3zwdm1a1eVx2AwGGEymSCiJgPiqjgTfAsOIebYMuf8xeAgOqpU6KhSVbguRa/HKa0W6yIiUfu/X7bTAgLQ4Wo+Nufn44X/5lm5V0O5HA3lcgDAN1nW/Thu6PVQCQTo4e4OAGilUOCqrhRxUGFjfh7EHIdud9VSuIz7JFGPo3///tDr9ViyZAmioqKQkZGBnTt3IicnBwDwzz//YMCAARg5ciTi4+Ph6emJHTt24O2338ahQ4ewatUqi4nrnIVTJQT/+9//sHjxYvTq1QsxMTG8nHC9wQCTyQThPU0Gtn07EsIPoTAP9RN/hZ86ie9QXJqOlX1jSO/6DhNyHMQchxMlxZUmBA8SLpFAyxjOa7UIFotxVqtFPw8PaIxGzM3OxuIaYbYI3/HYMCHQaDTYt28fEhISEBcXBwAIDw9Hq1atAABFRUUYO3Ys+vTpg19++cW83ZgxYxAQEIA+ffpg1apVeOmll2wWk704VUKwYsUKrFq1Cj179uQthvKE4N4mA0KcmwnexUfQ8MjvEFpNu0VsLVIiRbBIhG+zs/BxQCDkAgGW5OQg22hElsH44B1UwkMoxKzAILyXlgYtM6GPuzs6KFX4IC0NQ7y8cEuvx4RbN2FgDBN8fdHdzd2Gz4o/tmwyUKlUUKlUWLt2Ldq0aQPpPX0Ttm3bBrVajcmTJ1tt++yzz6JOnTpYvnw5JQRVTSKRoFatWrzGYDAYYTQxq4mJSPUlgBFimCDkyv4VwQgRZ4QIprI/i/8bKlwu/O//wv+WC+8qIyxfjjvLhZwRgvL/l6/jTBDCCCHYf/+a/vszQgAGIUzQFRfCUFyMAB8PCLiy9QKYcDjdC42OnKMmAjsRcxzmhITiw/Q0tL16BUIAbRVKxCqVT7zvrm5uFp0XjxQX4YquFB8GBOCZ69cxOzgYviIhXkpJQQu5Aj4ip7oMVMyGNQQikQiLFy/G2LFj8fPPP6NZs2aIi4vDyy+/jEaNGuHy5csAgHr16lW4fd26dc1lnI1TvRPeeustzJkzBz/88ANv7TOG8hqCe5oMXC09uPsiJym/EN11ARNzBoj+u8g87kVOhLsvdmXlyy9gQrCHvMjdvcxUdpFjZeXL/19eTgDTPf+/c0G890/ITOD+Ky/471gCGCFgDNx/25Wv5/j4RV3RIR8mDNl/f+xO+ePwxPzO7jjqIcPEPQyqEhrCZQ8NZDL8ExGJAqMResbgLRLhpZRkxMhkNjuGzmTCjIwMfBkUjFSdDkYwtFQoAAAREglOa0vQWeWCfQqeUP/+/dGrVy/s3bsXBw8exNatW/Hll19aDG+vrFaCMQbJfUaKODKnSgj27duH+Ph4bNmyBQ0aNLCaLXDNmjVVHoPBaKwwIegguggJV3DXr7jyi9mdC1j5xfFJLnJCzggBs7yw3XtRE97zf+6ei9zdF7Pyi1x5eae8yJEnsspY9qv0RDMD3qgnwpQt/qhziSYeshe3/3r8J+t0OKfV4nVfP5vt+ye1GrFKJerLZDiv1cJw10VMzxiMLvL54qqglkMmk6Fbt27o1q0bpk2bhjFjxuCjjz4y33DvwoULaNeundV2Fy9eRJMmTWwejz04VULg6emJ559/ntcYjEYTTMy6yWC4YDPqGs9aFq7sw+YiH0LiGs4HuAEoBgDkyQ34sF8Onj3jh5d25EOipdqCx1VkMiFVpzM/vqXX44JWCw+hEMFiMbYW5MNbKESQSIzLpaWYlZmBLioV2t/VbPBu2m34i0R4069sLgEdY7j23yQ8egZkGAy4oNVCIRAg/J5fpVdKS7GlIB9rIiIBAFESCQQch781GviKREjS6dDQhrURvBJW/aWsfv36WLt2Lbp37w5vb298/fXXVgnB+vXrceXKFXz33XdVHk9VcKqEYNGiRXyHAKDi5gEj51SnkhAAgIaT4IbK+nbeGxrm4ki4BG9v9EWNlGweInN+57QlGHHjhvnxF/8NE3zO3R2fBQUjy2DAl5mZyDYY4CcSoa+HB8b5+FrsI02vt+jXkWXQo39KsvnxotwcLMrNQUu5HEvCws3LGWP4OD0d7/oHQPFfbaZMIMBngUGYmZEOHWP40D8AAffUsjorTmS7eRXUajVefPFFjBo1Co0aNYKbmxuOHTuGL7/8En379oVSqcT8+fPx8ssv4//+7/8wceJEuLu7Y+fOnZgyZQrGjBlj1fE9KSkJiYmJFstq1aoFVSXDUvnCMVvP6GAHWVlZuHTpEjiOQ506deDnZ7sqtge5kpSKT+b8grDQIEjvysifLVyBxrpjdouDEFtYrqyJz/ytbxh2t8FHvdFrdw5EeoOdoiLk0dQ9e8ZmzQalpaX4+OOPsW3bNly7dg16vR41atTAiy++iPfffx/y/+aB2Lt3Lz799FMcPHgQ+fn5AIDPP/8c77zzjsX+KuvvFh8fj06dOtkkZltxqoSgqKgIr732Gn7//XfzpERCoRDDhg3D3Llzofivs0xVupqcihlf/whfL3eIhAIwxsCYCf3Zv2grOF3lxyfEloYpa+LkAxICAIhUyzF5vQh+6bl2iIqQR1Pv4gVej6/VatG3b1/cuHEDu3fvtuuPVFtyqlFGb775Jnbv3o0NGzZAo9FAo9Fg3bp12L17N9566y27xGAqLQZLOYLUA2uQtOcvJO/9Gyn7/4EmPcUuxyfEVowMOKPUPbgggCSfEkwYno9d7QNgEjjV1wZxdQ4wbFImk2HdunUYNmwY9uzZw3c4j82pagh8fX3x119/WVWzxMfHY8CAAcjKyqryGNJvXMeCL96DWCaHWCwFJxBAwHHoIDiB5gJ+s1RCHsVeeSDGBz768KiYNCVe38Dgqc6vgqgIeTRCT0/UOXTwwQXJAzlVql9cXIyACm4U4u/vj+LiYrvEIBSKoJDL4e8fiMDgEAQEBsEvIBBSpWvM+EWqjy0qn8fa7mxQESaMKsGR5gFgNEEX4Znwnrs9ksfnVAlB27Zt8dFHH0GrvdMruqSkBNOnT0fbtm3tEoNAKAQnEFjdWKmUk9vl+ITYyrEnGHGmFzHMflqNb1/2RJH7k8+uR8jjEnp58R2Cy+C/8eURzJkzB8888wxCQ0PRuHFjcByHxMREyGQy/Pvvv3aJQSAUgeM4MGaZEGgFVd+hkRBbuSVUIF1Y+OCCD3AoogCnxwgw5d8ANDiXYYPICHk0Im9KCGzFqRKCmJgYXLlyBUuXLsXFixfBGMPLL7+MwYMHm4eCVDWhQFiWENxTQ1AioF9JxHmscw8F46znH3gcxVITpvdRo1u0L4ZuLYSs2Db7JeRhCD0pIbAVp0oIAEAul2Ps2LG8HV8gFEIgEFjNY63lKCEgzmOvXAbAthfu7dEaHK8hxtsb/RB1reo7+BICUB8CW3K6hODSpUuYO3cuLly4AI7jULduXUycOBF169a1y/EFQlGFfQiohoA4i1IIcFlSVCX7zlHo8e6AXPRP9Ee/XRqISx9uWCMhj0vo5cl3CC7DqToV/vXXX4iJicHx48fRuHFjNGrUCCdOnEDDhg2xevVqu8QglSsgEolhNFh+0ekFMhhhu+kzCakqO5XB0HEPnozoSfzdJAfvjBLjdujjjWQg5GGJqIbAZpyqhuDtt9/Ge++9hxkzZlgs/+ijj/DOO+/gxRdfrPIYhEIhFG4eyMlKt1qnFSigNBVUeQyEPIltKi8AeVV+nJuepZg0tBQjDwbg6X1qCA009TGxPRplYDtOVUOQnp6OYcOGWS0fMmQI0tOtL9BVxc3DCwa9dVUoNRsQZ5Aote+FeVFbNaaNkEPt72nX45LqQehFNQS24lQJQadOnbB3716r5fv27UNsbKzd4lB5eFeYEFDHQuLoLok9oBZWTf+B+7niV4IJIwqxt00gTX1MbEpEfQhsxqmaDPr06YN33nkHx48fR5s2bQAAhw4dwurVqzF9+nSsX7/eomxVUbp5WA07BKiGgDi+9W7BAOyfEACASQjM7ZyNfbXdMWGjEe651LxGnhyNMrAdp7qXgeAhf1lwHAej0VhlcZzYuw3bVi9AWO0Yi+UNi/ejYcmhKjsuIU/q+ZCGuCqp+v4DDyLVc3hjhzeansoE5zxfQcTBcDIZ6iae5DsMl+FUdXcmk+mh/qoyGQAAmUKJir7DqIaAOLICToQk8ZPPTmgLpWKGz3uo8eOLXihR0Syf5PGIg4P5DsGlOFVCUBGNRmP3Y8qVKnCcAKZ7Eg/qQ0Ac2WZVKIxc1SbLj2pPzXy8NsaIS3X9+Q6FOCFJVCTfIbgUp0oIvvjiC6xcudL8+MUXX4S3tzdCQkJw6tQpu8UhU6ggFkusOhZSDQFxZLsc9I6c+XIjpj6fgyV9/FAqk/IdDnEi0sgovkNwKU6VEMyfPx81atQAAGzfvh07duzA1q1b0aNHD0yZMsVuccgUKogkEujvSQjyhdS5hTiuM9JSvkO4r00NcvHmGCFSI3z5DoU4CUkUJQS25FSjDNLS0swJwcaNGzFgwAA8/fTTiIiIQOvWre0Wh1yhgkgstqoh0AtkKBaooDA5RjstIeWOynxRICjhO4wHynLTYfJAHQYe98ez8bkQ6at2RkXi3KTUZGBTTlVD4OXlhRs3bgAAtm7diq5duwIAGGNV3pHwblK5AhKJDIYKvqw0Qvp1QxzPJrcAvkN4JMub5+C9UVJkBFOtG6kc1RDYllMlBP369cOgQYPQrVs3qNVq9OjRAwCQmJiIWrVq2S0OjuOgcPescHIiSgiIIzoi4/gO4ZGleGvx2tA87IgNgFFI9wkhloR+vhC6ufEdhktxqoTg22+/xcSJE1G/fn1s374dKpUKQFlTwvjx4+0ai7unDwx66zbZPBElBMSxZApluCl00kmABBx+6aDGzGEqaHw9+I6GOBDqUGh7TtWHQCwWY/LkyVbLJ02aZPdYfAJDYNRbzwlPNQTE0WxwCwGr4rsbVrXzgUUYPwp4fVcgWh3PgIAmM6r2aMih7TlVDQEA/PHHH+jQoQOCg4ORkpICAPjuu++wbt06u8bh6e0HBoZ7J3rME/rABOerniWua4/CNYbDGoTAN92y8c1ALxR6qPgOh/BMSv0HbM6pEoKffvoJb775Jnr06AGNRmPuSOjp6YnvvvvOrrF4+PhDLJFCr7NsNjBxIhQIPO0aCyGVMQE4Ly7mOwybOhKejwmjdTgTEwCqJ6i+JNRkYHNOlRDMnTsXv/76Kz744AMI7+pk1KJFC5w5c8ausXj6BkAmV0JbbH2jmDyRn11jIaQyCYpgaAXWnV+dXYnUhJnPqvFLPx9oFXK+wyE8oCGHtudUCUFSUhKaNm1qtVwqlaKoyL53cFOo3KHy8IK2xPq41I+AOIqtKtcetrczOg//G8twrRYl4dUJJ5dDRPcxsDmnSggiIyORmJhotXzLli2oV6+eXWPhOA4BoREoraCGgBIC4iiOy1y/Uj1XYcB7L+ZieS9/6KUSvsMhdiCrVw8cR321bM2pRhlMmTIFEyZMgFarBWMMR44cwfLly/HZZ5/ht99+s3s8voGhYMx6QiQaekgcQYpIhUyBkw43fAz/NMrBoXAJ3t7ghpAbar7DIVVI0cy6ppg8OadKCEaOHAmDwYC3334bxcXFGDRoEEJCQjB37lzExsbaPR4PHz+AcTCZTBAI7lS2FAg8YYAIIlgPSyTEXta5hwCc409XbEtpHjq8MUSHYYcD8MweNUQG+gy6Inmz5nyH4JKcqskAAMaOHYuUlBRkZmYiPT0dR44cwcmTJ+06U2E5T58ASGRy6LT3fOlyHDTUsZDwbJ+8+t458PfWakwdKUd2gCffoRBb4ziqIagiTpEQaDQaDB48GH5+fggODsb3338Pb29v/Pjjj6hVqxYOHTqEhQsX2j0uDx9/yBTKCjsWZopC7R4PIeW0EOCquHrfZOuabwkmjijE7raBMAmc4quOPARJzSgIPT35DsMlOcWn5P3338eePXswfPhweHt744033kDv3r2xd+9ebN68GUePHsXAgQPtHpdUJoenj3+FQw8zxGF2j4eQcv+qQqHnqLrcJAB+7JSNWUPdke9F8967AgU1F1QZp0gINm3ahEWLFmH27NlYv349GGOoU6cOdu3ahbi4OF5jC6gRBZ3WeuKXTHEIjM5xeokL2qGief/vdiq4EOPHaHG8aQAY9U53aormzfgOwWU5xRXr9u3bqF+/PgAgKioKMpkMY8aM4TmqMt5+gVbTFwOAkRNDLQriISJCgESJc9+7oCroRAxfPKPG9wO8UOzmGtM5V0fyZpQQVBWnSAhMJhPEYrH5sVAohFLpGB9oT98ACARCGPTWX8AZ4ho8RESquzNSL2iErjVdsS3tj8rHxDEGXKjnz3co5BGJ/P0hqUHfq1XFKYYdMsYwYsQISKVlvaa1Wi3GjRtnlRSsWbPG7rH5h4RD6e6BogINPLwtRxZkiMPQsOSQ3WMi1dtGVRCA6t2h8EEKZUZ89FwOetTxw6BtBZCWaPkOiTwEqh2oWk6REAwfPtzi8ZAhQ3iKxJrSzQOBNaKQfOmMVUKQLQqm+QiI3R2SCx9ciAAAttTPxdEwMd7Z6IvwpGy+wyEPoKCEoEo5RUKwaNEivkO4r/DaDXDl9FGr5SZOiCxxMIL0qTxERaqjPIEEyaLqMzuhLWSr9JjysgYvnfBHn/hciHXU/8JRyalDYZVyij4Eji4gNAJCsdjqVsgAkCGi4YfEfjaqQmHiTHyH4ZRWNsvBu6OkSA9x7RtCOSuBUglZ3bp8h+HSKCGwAf+QCKjcPVGUr7FaRx0LiT3tUqr4DsGp3fDS4vUhedjWMRBGITW9OBJlhw7g6DWpUpQQ2IBMoURwRB0UVpAQ5IgCoePoDmzEPs5JqHPcExNwWNA+G9OHK5HrS/M5OAq3rl34DsHlUUJgIzVq1oNRr7NazjgBsmgaY2IHB+T+KBJQQmArFwOKMWFUEQ60CoSJJjPil1gMFc+T0FUHlBDYSEBoBMQSqfWNjgCk0zTGxA62qOiGWrZmEALfdcnG7MGeKPCk5hi+KFu2hNDdne8wXB4lBDbiHxIOlYdXhc0GtyRR9g+IVDtHZfQrtqocq1GAiWN0ONUoANbzkpKqpqLmArughMBGJFIZatSsh+KCPKt1hUIvqIUBPERFqos0oRy3hTTcsCqViE34tJca8/v7okQp5zuc6oPj4NalK99RVAuUENhQSFQ0DAZ9hfc2SJFG8xARqS7Wu4WCcfTb1R521dHgf2MZrtShJhp7kDVsCHEATTNtD5QQ2FBAaASkMjlKK7j7YaokmqoaSZXZo6BfrPakkRvwQf9cLOvtB91/U6qTquHWhZoL7IUSAhvyDawBd08fFOVprNYVC92RJQq2f1DE5enB4ZKkiO8wqqV1DXMxeYwQN8N8+Q7FZbl1o+YCe6GEwIbEEgki6zVBYX5uhetTpDTLFrG9ncpglHI03S5f0t11eHOwBuu7BMAgdorZ4J2GJDIS0ijqlG0vlBDYWGS9RhAKhRVOY5wqiYYJ1BOc2NZ2JU216wiWtlJj6gg5sgK9+A7FZdBkRPZFCYGN1ahZD56+gcjLybJaVypQ0FTGxOZOyIx8h0D+c823BK8NL0B8u0CYBPT1+qSo/4B90TvWxiRSGeo0allhPwIASJFUv2aDWXtL0fLXQrjNyof/VwV4bkUxLmVbXsQYY/g4QYvgrwsg/zQfnRYX4Vzm/S90ay7o0eKXQnh+ng/lZ/lo8nMh/jhlOVvkstN61Pi2AN5f5GPKNstZ/JI1JtSZW4j8Uuft7nlV7I5sYSHfYZC7mATAT3HZ+HSoG/K8aTKdxyUODoascWO+w6hWKCGoAhHRDSESiyuctfCGpDaMqF436NidYsCElhIcGq3E9qEKGEzA00uLUaS7cyH+cr8O3xzU4YeeMhwdq0SgikO3P4pRcJ+LtbecwwexUhwcrcTpcSqMbCLGyHVa/HvVAADILjZhzIYSzO4mw79DlFhySo9Nl++0tb+6qQSfd5XCXeq8zTjr3aijqqM6E1yECaNLcLRZABhNffzIPF98ARydN7uihKAKhERGwzsguMJmA71AhnRxOA9R8WfrECVGNJGggb8QjQOFWNRXhtQ8huNpZTUAjDF8d1iHD2Kl6FdPjBh/IZY8J0exnuHPM5V3lusUIcLz9cSo5ydETW8B/tdGikYBAuxLLUsIrucyeEg5vBQjRssQITpHCnE+q+zWwH+e0UMi5NCvnrjqT0AV2i+nG2c5Mp2I4avuanz3kheK3JR8h+M8RCJ49OvPdxTVDiUEVUAskSC6cWsUF+RXuD65mo82yPuvv6W3vCz7T9IwpBcyPF3zTg9tqYhDXIQIB24+XPs4Yww7rxtwSW1Cx/Cy/dT2FqBYz3AyzYicEoajt4xoFCBETgnDtHgtfughs+0Ts7NiCHFdTLMTOoODkfl4bYwB5+rTBDsPQxUXR5MR8YDGyFSRiDoxOLRjHbQlRZDJLX8Z3JTUggEiiGDgKTr+MMbw5r9adAgTIsa/rOkkvbDsV3uAyrJ6MEDJISXPdN/95WkZQr4pQKkREHLAvF4ydPsvsfCSc1jynBzD1pagRM8wrLEY3WuJMGpdCV5rJUGSxoQ+K4qhNwIfd5LihfrOVVuw2S0UBo46FDqLQpkR0/vm4OloXwz5txCyYrozZWW8BrzIdwjVEiUEVSQovBZ8A0ORm50BWahlQmDkxEiV1kFU6XmeouPPxM1anM4wYt8o6+rTe1sLGbNedi83KZA4ToVCXVkNwZv/ahHlJUCniLK39vP1xHj+rmaBhGQDzmQa8UNPGWp9X4jl/eUIVHFotaAIHcOF8Fc6T6XZLqUHAA3fYZBHtK2uBsdriPH2Jj9EXrNuVqzuRMFBUMbG8h1GteQ8335ORigSIbpJa5QU5Vd4b4NLsmY8RMWv1zaXYP1lA+KHKxHqfuetF6gq+396oeV5yixmCFDd/y0q4DjU8hagSaAQb7Ur+5U/a5/1HBAAUGpgGL9Ji/m95biaY4LBBMRFiBDtK0QdHwEOP2TzhKM4JdU9uBBxSGqlHu8MyMWqZ/yhl1A/kLt59u8PjoZs8oLOehUKrxMDmVwJbbH1sLBcUQAyRSE8RGV/jDFM3FyCNRcN2DVMgUgvy7ddpCeHQBWH7dfvNKHojAy7kw1oF/poIzIYA0oraYmZuacUPWqJ0CxICKMJMJjuJCB6I2B0otGHJ6U+yBdY3zODOJe/mubgndFipIX68B2KYxAK4dmfOhPyhRKCKhQQGgm/4HDkqSuuFqwutQQTNmux9LQef/aTw03KIb3QhPRCE0r0ZVdgjuMwqbUEn+0txT8X9DibacSItSVQiDkManinun/YPyV4b8eddtdZe0ux/ZoB13NNuJhtxDcHS/H7aT2GNLLuC3Au04iV5wyY0bnsRjR1fQUQcBx+O6HDpst6XMw2oWWw8wwH3ehGt9N2FTc9S/G/oXnYGhcAo8h53oNVQRUbC3FgIN9hVFvUh6AKCYVC1G3SGjeunQdjzGpM7U1JLRQK3KEyVTwawVX8dKxs6GCnJZa/aBf1lWFEk7Lq0rfbS1BiYBi/WYvcEobWoUJsG6qA211zBKTmmSDg7uSwRfqy8jfzTZCLgLq+Qix9Xo6XYiwTAsYY/m+jFt92l0IpKdufXMxh8XMyTNisRakB+KGnDCHuzpMfH5ZV7wuHK1rYTo39tZV4Y50A3lkavsPhheeAAXyHUK1xrKIGbmIzWWk38Of30yFTKOHmaV0tWK/kKJoW7+EhMuKssgVSdAkLgom7/wgM4pwERmDibl+0O5oJgan6vMaiwEDU2rkDnJCSXb44z08iJ+UbGIqaDZohNyu9wvVXpQ2hh3MNdyP82ugWSsmACzMJge+fysaXg9xR4OnGdzh249mvHyUDPKOEoIpxHIcGLTpAKBJDW2J9z3q9QIYkaX0eIiPOareCZryrDk7UKMT4MVokNq4GUx+LxfCkuQd4RwmBHYTVboCQyDpQp9+qcP0leTNQuw15GCYA5yTW98ggrqlUzPBZTzXmveCNEpWC73CqjEefZ6kzoQOghMAOhEIhGrXuBKNBD4PBem7+AqE30sQR9g+MOJ298iCUCCqeZ4G4rt218vDaGCMuR7vgdL5CIXxfeYXvKAgoIbCbWjHN4RMQgtzMtArXX5I1t3NExBltVdF49eoqX27Eh/1y8PuzftDJpHyHYzPuvXpCEhbGdxgElBDYjUyhRMPWcSjK18BUQc/hNHE48oTePERGnMkxGTUuVXcbY3Lx5mghUiN8+Q7lyQkE8B03ju8oyH8oIbCj6Mat4eblg4LcbOuVHFdtJioij+eGSIl0Id3dkACZ7jpMHqjB2q4BMIidd5SS29NPQxoVxXcY5D+UENiRl18g6jRqBY06s8L116UNUCSoPsOMyKNZ5xby4Ls9kWrlz5ZqvD9ShswgL75DeXQcB99XqXbAkVBCYGcNmreHRCpHcaH17IQmToQz8rY8REWcwX65jO8QiANK9inBxGH52NkhAEYnGseveuopyKKj+Q6D3IUSAjsLjqyDsNr1kZtRcefCJGkD6ktArJRCgEsS63ksCAEACDjMj1Xjk6EqaHzc+Y7mofi++irfIZB7UEJgZwKBAA1bx8HEjNDrrIePMU6AU/IOPERGHNl2ZQj0nPWQVULudi6oCBNGleBwC8eezEgZGwt5TAO+wyD3oISAB1H1msA/JBzqjNsVrr8prY1sUZCdoyKObLvKk+8QiJPQixi+7qbGtwO9UOjumLNaUu2AY6KEgAcSqQxNOzyNUm0x9DpdhWUSFbF2joo4skSpge8QiJM5FJ6PiWP0OBsT4FAzoSratIGiWVO+wyAVoISAJ/WatUNIeC1k3U6pcH2muAZu0+yFBMAFiSdyhNR/gDy6YqkJM55V49d+vtAq5HyHAwDwe/11vkMglaCEgCdSmRwt4nrAaNCjVFvx3PSJiliHyuwJPza4UfMReTI7ojX431iGa7X8eI3DvXdvqh1wYJQQ8KhO49YIrx2DrFsV1xJoRP5IkdS1c1TE0RyUi/gOgbiAXIUB772Yi+U9/aGXSux+fE6hgP+UyXY/Lnl4lBDwSCQWo0WnHuA4DiVFhRWWOa1oDyO9TNVWASdCkqji9wYhj+OfxjmYMlqM2zXse18M3/8bC3FAgF2PSR4NXWl4FlW/KWo2aFppX4JCoSeuSRvaOSriKDa61YCRM/IdBnExtz1KMWlIHjZ3DoBRVPU1UOIaNeA9alSVH4c8GUoIeCYQCNCiU09IpHIU5msqLHNW0RZ6OO985eTxxStpKmtSdRa3UWPaCDnU/p5VepyAd96GQGL/ZgryaCghcAA1atZDncatoE67AcasuxFqBUqcl7fiITLCtzMS68mrCLGlK34lmDCiEHvaBMAksP0lQdmuHdy6drX5fontUULgADiOQ4u4Z6Bw80B+RXdCBHBe3hIaoQvc7pQ8tCNyPxQKKh6BQogtmYTAD53V+HywO/K9bFgrJRIh4P33bLc/UqUoIXAQgTWi0KBFLHKz0iusJWCcEIeV3WCi291VG5tU/nyHQKqZxNBCTBitxYkmtpn62GvQQEhr1bJBZMQeKCFwIE07dIO7pw802ekVrleLg3FF1sS+QRHeHJFR8kfsr1TM8HkPNX540RvFKsVj70fo7Q2/iRNtGBmpapQQOBCfgGA0btcFGnUmTMaKe5afUnRAkYA6mrm6TKEMt4QFfIdBqrG9NfMwcawRF+s+Xk2V36T/QejuHHdeJGU4VlH9NOFNfq4aK378BIX5GgTWiKywTLDuOjoV/GPnyIg9LfCshTleFd/nwtEUXSpC9uZslKSUwKAxIOy1MLg3v3MhMOQZkL4qHYXnCmEsNkJZR4mgIUGQBkor3SczMGRtykLuvlwYcg2QBkkR8GIA3BrdSYY1BzRI/ysdrJTBK9YLgS8HmtfpsnRInp2Mmh/XhFAurJonXo30POeFgdvyIdU+XCdXWYMGiFi9ClwVdFIkVYdeLQfj7uWDdk8/D32pttLJim5LopBMMxi6tN2Kx6+qtTdTqQmyMBmChlhPscwYQ8r3KdBl6RD2ehhqTa8Fsa8YyV8lw1RqqnSfGWsykBOfg+Ahwaj9WW14dfZC6txUlKSUdbI0FBhwa9EtBL0UhPC3wpG7PxcFiXdqVG7/fhsBLwZQMmAjmxvk4s0xQqREPkTHZrEYQZ99SsmAE6JXzAHVa94e0U1aI/NmUoUdDAHguLIztJzMzpERezCAw0VJMd9hPDS3Rm4I6B8AjxYeVut0GTqUXCtB8PBgKKIUkAZJETwsGCatCZpDmkr3qTmggV9vP7g1doPEXwKfp3ygilEhe2vZKBxdlg5CuRAerT2giFJAWU8J7W1t2bYHNeBEXIXxkMeX5abDlJc1WPO0PwziyudF8Rv/KmTR0XaMjNgKJQQOSCgUokOPF+Du4wd1+q0Ky5QKFDip7GTfwIhdJCiDoOWco7ngQZi+LKHlxHc6SHICDpyIQ/HlypMepmcW2wCAQCIwbyMNkMKkM5U1UxQaUJJUAlkNGQyFBmT+k1lhbQWxjRXNc/DuKCkygr2t1kkbNIDP2LE8REVsgRICB+UbGIo2T/VBcaEGukruhpgkbYA0cbidIyNV7V+l9Rets5IGSSH2ESNjdQaMRUaYDCZkbcyCIc8AQ56h0u1UDVVQ/6tGaXopmImh8Gwh8k/mm7cRKoUIHRuKm7/exPUZ1+HZzhNuDd2QvjId3l29oc/W4+q0q7jywRXkHc2z19OtNlK9tXhtaB62dwyAsbxpQCxGyOezwNlhKmRSNeiVc2CN2nbGtfMncP3CKdSoVR9cBeOCjyi7oadmCcTQ8xAhqQonZJW3rTsbTsQh7LUw3PrtFi5MuAAIAFV9FVSNVPfdLmhQEG4tuoUr710BOEDiL4FXBy/k7ss1l3Fv7m7RebHwQiFKb5YieEgwLr9zGTXG1YDIQ4RrM65BGa2EyJ2+7mxKwOHX9mrE15Di/XgVIl8aAmnt2nxHRZ4AfUIcmFgiRYceLyIt9To06gx4+QZalSkSeuCMoh2aFe/mIUJia0liN2QKXOvuhvIIOWrNrAVjsRHMwCByL7tIyyPklW4jchch/H/hMOlMMBYZIfIUIWN1BiS+Fc+Hb9KbkPZHGkL/LxS6TB2YkUFZVwkAkAZKUXytGO5NaQhcVbgapscPk8KwuNdovkMhT4iaDBxccERtNI/rgbzsTBj0FbcrX5Q1R4Yo1M6Rkaqwzi0YrjoZpVAhhMhdhNL0UpQklcCt2YPn0xBIBBB7iQEjkH8sv9JtstZnQdVQBXmEHMzEgLsqWZjB8jGxLblAjk87fw5OSCM6nB0lBE6gRcdnEFarPtJTr1dcgONwwK0XtFzlv7iIc9gvr3xsvqMyao0oSSkxDwnUZetQklICnbosgc07kofCC4XQZeqQfyIfyV8lw72ZO9xi7lzcb/5yE+mr78zQWXytGHnH8qDL1KHoUhGSv04GYwx+Pfysjq+9pUXekTwE9AsAUNZvARyQszsHBYkFKE0rhTyKPhtV5f227yPUjX6QuAJqMnACMoUS7Xv0xz+/fYsCjRpunj5WZUoEKhxSPYO4gn9c9QemyyuBEFfFztdcUJJUguQvks2P05eXXdg923sidGwoDHkGpK1IgzGvrOrfs50n/PpaXth1ap1FzQjTM2SuyYQuUweBTAC3Rm4I/b9QCJWWv0IZY7i96DYCBwZCIC37fSOQCBAyJgRpf6SB6RmChgaV1TIQm+sa2gXP1XqO7zCIjdBMhU6CMYada37HkV0bUKN2fQiFFedyTYsSUE973M7REVv4xy0M0+iGlsRJ+Ep8sLbfOnhIab4HV0FNBk6C4zi06doHATWikHEjqdJyiYpYZIusOx8Sx7dTSV+sxDlwjMMXnb6kZMDFUELgRFQeXujQoz84cMjPza6wDOOE2K/qDR3nfG3R1d0pKQ0dJc5hfKPxaBXUiu8wiI1RQuBk6jRqheZxzyAn4zZ0pdoKyxQJPXBQ9QyoLch5nJZ6QyNwnumKSfXVMaAjxjUbx3cYpApQQuBkOI5D26efR62YZkhLuVrpvQ5uSWrhnLy1naMjj2uDKoDvEAh5oFBpKL7u+jXfYZAqQgmBE5LK5Ojcdwg8fQOQeSu50nKn5e1pamMncUhOA36IY5NDjl97/AqZiG6q5qooIXBSfsFh6NjrJRj0ehTm5VZciOOwX9ULhQKaoc2R5QqkSBUVPLggITzhGIdZ7WYh1IPmG3BllBA4sfrN26NJu67ITrsBva60wjI6gRz73J6FETSLmKPa6BYCE0dT6RHHNSJyBLrU7sJ3GKSKOVRCMGLECDz33HNWyxMSEsBxHJ577jlwHHffv/L9cByHceOsO76MHz8eHMdhxIgRDzzuvSIjI7F161YAZfMC/PLLL2jdujVUKhU8PT3RokULfPfddyguLuscVlRUhHfeeQdRUVGQyWTw8/NDp06dsHHjRvM+r1+/joEDByI4OBgymQyhoaHo27cvLl++/MB4OI5Dhx4vIKpeE9xOvgKTqeKLSo4oEEdU3R64P8KPBMX9b/RDCJ/aurfFm3Fv8h0GsQOHSggeZM6cOUhLSzP/AcCiRYuslgFAjRo1sGLFCpSU3Ll1sFarxfLlyxEWFvbIxz59+jTUajU6d+4MABg6dCgmTZqEvn37Ij4+HomJiZg6dSrWrVuHbdu2AQDGjRuHtWvX4ocffsDFixexdetW9O/fH2q1GgCg0+nQrVs35OfnY82aNbh06RJWrlyJmJgY5OU93C1b5UoVuvQfDh//YGTcqGRqY5TdKvmUvP0jP29S9c5JKh4tQgjfQoWh+L7393yHQezEqXoyeXh4wNPT02KZp6cnAgOtJ+Jp1qwZrl+/jjVr1mDw4MEAgDVr1qBGjRqIiop65GOvW7cO3bt3h1QqxapVq7Bs2TKsXbsWffv2NZeJiIhAnz59kJ+fDwDYsGED5syZg549e5rXN2/e3Fz+/PnzuH79Onbt2oXw8LLOf+Hh4Wjf/tEu3H5BNdCp7yBs/GMeNNkZ8PStuMf6OUUbyE1FqFOa+Ej7J1VnnzwARQJKCIjjUTIlfu31K2Ri6kRYXThVDcGjGjlyJBYtWmR+vHDhQowaNeqx9rV+/XrzxX/ZsmWIjo62SAbKcRwHD4+y2bsCAwOxefNmFBRU3GHMz88PAoEAf/31F4xG42PFVa52w5Zo3aUP8nKyoC0uqrTcMeVTSJXQPcsdxRaV9c16COGbgAkwu+NshHpRJ8LqxOESgo0bN0KlUln89ejR47H2NXToUOzbtw/JyclISUnB/v37MWTIkEfez61bt3Dq1CnzL/0rV64gOjr6gdv98ssvOHDgAHx8fNCyZUu88cYb2L9/v3l9SEgIvv/+e0ybNg1eXl546qmnMHPmTFy/XnnVf2U4jkPrLs+iQfMOSE+9BqPBUFlBHFD1RKYo5JGPQWzvGP34Io6GAa/XfR0dojrwHQmxM4dLCDp37ozExESLvwULFjzWvnx9fdGrVy8sWbIEixYtQq9eveDr++h3j1m/fj3at28Pb29vAGUdCss7MN5Px44dcf36dezcuRP9+/fHuXPnEBsbi5kzZ5rLTJgwAenp6Vi6dCnatm2L1atXo0GDBti+ffsjxykSi9H5uSEIrVkPN69frLSToYkTYbfbc9AIre+aSOzntlCBNCENNySO5eWglzG6zWi+wyA8cLiEQKlUolatWhZ/ISGP/2t21KhRWLx4MZYsWWKT5gIAqFOnDi5cuPBQ24rFYsTGxuLdd9/Ftm3bMGPGDMycORM6nc5cxs3NDX369MGnn36KU6dOITY2Fp988sljxerm6Y0eL4+FX1AN3L5+qdKZDPUCGRLc+qFIQD3c+bLOPQSMowmmiePoquyK959+n+8wCE8cLiGwtWeeeQY6nQ46nQ7du3d/5O0LCwsRHx+PPn36mJcNGjQIly9fxrp166zKM8buO0Kgfv36MBgM0Gor7kjGcRzq1q2LoqLK+wE8iF9wGJ55aSxUnt5IT71WaVJQLHRHglt/uhEST/bK5XyHQIhZc645Pu/z+UPVfhLX5PIJgVAoxIULF3DhwgUIhZVPzpOXl2fVVJGamoqtW7eidu3aFiMTBgwYgJdeegkDBw7ErFmzcOzYMaSkpGDjxo3o2rUr4uPjAQCdOnXC/Pnzcfz4cSQnJ2Pz5s14//330blzZ7i7uyMxMRF9+/bFX3/9hfPnz+Pq1av47bffsHDhwgo7LD6K0Jp10e2FkRCJJchOv1n58xb5Yo9bX5q4yM704HBJ8vhJHyG2VLu0Nr7u8zWkEvpxUJ051bDDx+Xu/uCpexMSEtC0aVOLZcOHD4fRaLS6OHMchz///BO//PILFi5ciE8++QQikQi1a9fGsGHDzDUR3bt3x5IlS/D++++juLgYwcHB6N27N6ZNmwYACA0NRUREBKZPn47k5GRwHGd+/MYbbzzx867dsAU69RmM7X8tvO9wxExxDRxQ9UT7wo0Q0D0S7WKnMgQ6jm53TPgXWhiKr579Cj6e1KeouuNYZfXJBEajEf7+/tiyZQtatXLOe38zxnB453rs3rACnn4BcPPwrrRsnZKTaFG8y47RVV9vBDTEDsXDTT5FSFUJKAzA112+RuO6jfkOhTiAalFD8LjUajXeeOMNtGzZku9QHhvHcWjZuTeKC/NxeOd6iERiyJVuFZa9LG8KgKF5cTyoFbFqnZQ+2bwThDwp3yJfzIqbRckAMaMagmpCr9Nh2+rfcOrATgRH1IZEVnmHtijtGbQq2k7NB1Xkstgd/UM9+Q6DVGNeRV74rM1n6NCM5hogd7h8p0JSRiyRoMvzw1C3aRvcTr4Cg15XadnrsoY4qOoJE709qsQGt2C+QyDVmFuxG6Y2m0rJALFC3/jViEyhxNMvjkZE3Ua4df3yfadLTpHWxV66bXKV2C+X8B0CqaZUxSq8F/MeurbuyncoxAFRQlDNqDy88MxLYxEYFolb1y7eNym4JamFBLfnYaCuJjZTyIlwXUyzExL788j3wDvR76B3h9401wCpECUE1ZC3fxB6DnoVATUicPPaBRiNldz3AECGJBzx7v2h4+hXrS1sUYXCyFGHQmJfvjm+eCP6DfTp1IeSAVIpSgiqqYDQCDw77DWERNTGzasXYNBXPiY+SxyKXe4vQsvRnXie1E7lg+fEIMSWAjMC8Wr0q3iuy3MQCOgrn1SO3h3VmG9gKJ4d9hrCajfAzesXoddV3tEwRxSIne4voYRT2DFC13NaWsp3CKSa4BiH0JuhGB49HP2e7nffmVoJASghqPa8/ALx7NCJiKrbGLeuX4SutOJ7LABl0xzv8HgZRYKK5zEg93dc6oMCQQnfYZBqQMAECE8Jx4vRL2JAzwEQiagfEHkwSggI3L190XvoBNRu2AK3ky6jVFv5RatA6IXt7i/TrZMfwya3iqeOJsSWRCYRaibVxKBmgzCk7xBIxNT/hzwcmpiImBUX5mPrygW4ePIAAsNqQiZXVlpWxHRoW7AFNfRX7Rihc+sVGoNUcT7fYRAXJjVIUTu1NgbFDULPuJ7UTEAeCSUExIK2uAjbVv2Gc8f2wj80otJpjgEAjKFhyQHElByiqY4fIFsgRZewIJg4E9+hEBclL5UjJi0Gw54ZhrhWcTSagDwyalgiFmQKJbq/PBZCsRinDu6CX3AYlG4eFRfmOJxRtEeu0B9tC7dADLp7X2U2uNWAiau80yYhT0JVpELT3KYY2W8kWjZ03nuvEH5RQkCsSGVyPP3iKIhEYpzYvx3MZILKw6vS8jeltbFN6IWOBWvhZqI7+FUkQaEAQAkBsT2/LD80MzXD6JdHo17NenyHQ5wYNRmQShn0euzeuALHEjZD4eYBb/+g+1ZDSkwl6FC4EYH6VDtG6fhMANqE10aJgIYcEtsRMzGCU4LRzLMZRr84GuHB4XyHRJwcJQTkvoxGIxL3bcfeLath0JciMKzWfSc34ZgJTYt3o672hB2jdGzxiiC8HiDmOwziQjwMHgi8EogWkS0wsv9IBPjSCBby5CghIA/l2vmT2Lnmd6gzbiE4og7EkvsPZYrUnkOrou0QgqbpfdcvBptUNLqA2EYNbQ24X3ZHu8btMOz5YfB08+Q7JOIiKCEgDy0r7Qa2/7UIyRdPIyA0EnLV/Sco8tGnIbZgPRSs0E4ROqauYQ2QIaQbGpEnI2RC1MmtA8ktCTq16oRBzw6CQk4zhxLboYSAPJLiwnzEr1uGM4cT4O7lC88HVFXKTEVoU7gVwfpk+wToYFJF/9/enQVHdZ5pHP/3pm6pu9XdElpaaAWJTUishhCMgTgeIEzi2C47Kc+4ysGelHMzF1Mhy6SSSi6ocZFy5cIXrhpXjD3O4tQkMTNmxvFgTByDjcELEFabHYQ2pG6J3k/3OXMhI0ywLclIaiGeH0V10wedfqWyOU9/5/vez8f66hK0LlNuhM/0UXe2jkAuwPpV61l3xzpcLt2GktGlQCAjlstmefu1l9iz/b+wsKismTbkmufG1AEWxF+/5ZYmPlkyg38PfHo7aJGhVGWqCB4P0lDRwDf//pvMmzVPPQZkTCgQyOdiWRbHD7zNa1t/RX9vN1UNM3A6P/sTiy8XZVnsZcqyF8epyvz7xtRWjhRE812G3IRslo2my014znhY2LyQf/jqP1BZVpnvsmQSUyCQG9J+7iTbf/8sF04epbLus9sdw8AqhNmpfbQk3pr0Ew5T2PlifT2GLZvvUuQmEzSD1FyowZPwsOb2Ndz95bvxuLX9uIwtBQK5YZejvex48T84+t6bBKdUECgpG/JrgtkulsVeJpS7NA4V5sdLvlr+degfhcggu2Vndno2jg8dVJRW8MC6B1g6b6luEci4UCCQUWFk0rz1f1t59y9/ImtkqKydjmOILVftVo7WxG5mpd7BzuT7z/CfK1rYWaTOjTI8U3JTmBOdQ+RChJYZLTz4tQfVbEjGlQKBjBrLsjh97AB/+Z/fcfH0h0wJ13xmy+MryowLfCH2p0nX9viO2tlEHPF8lyETnNNy0mq0UtRWRDKZZPUXVnPfmvvwFfnyXZrcYhQIZNTF+qO8+cofOfjWa9jsdiqqG7APsQ2r08qwIP46TemD41Tl2DpcEOSbU4vzXYZMcJW5SubF59F5tpNAcYD7/u4+Vi5Z+ZndQEXGigKBjIkrqxB2/e9/0tl2lorqeop8Q18gK4xzLIrvJHiTzy14vHQ2vy7W6IB8MpflYkFmAd5OLz3RHpqbmrl/3f001TXluzS5hSkQyJjq6+3mjf/9T468swuX20NZVe2Qn35slklj+iAtid14rJtzDf/d1S2cck2uWyAyOqpz1bTEWrh47iIBX4C1d6zly1/8MoWewnyXJrc4BQIZc7lcjiPv7GL3n35PpLuDitppQy5PBHCZKVqTb9KUOoAdcxwqHR19dhcra6eSs908NcvY85pe5hvzcbQ76OvvY/6c+dz7d/cyrWZavksTARQIZBz1dLbx+rbf8cGBtynyByitmDqs5VTF2R4WJXYSNs6OQ5U37jfFDfxb6eTusSDDV2AV0JxtZurlqZy7cI4poSmsX7WeVUtXUeD67E3CRMaTAoGMq6xhcODNHby1fSuX+3qpqGkY1mgBwNTMSRbEX6fYjIxxlTfmn8Kt7PFE812G5JnDcjAjO4NZmVl0dXSRSCZY3LKYe+66h5pwTb7LE7mOAoHkRcf5U+x6+fecPPw+TpeLsql1Q7Y+hoHeBTNT79Gc3EOBlRmHSkfuC3UziNtvzrkPcuNslo36XD0t2RbMmMm5tnNUllXy1S99ldsX3Y5ziP4cIvmiQCB5k8tmOb5/D2+/9hId507hC5ZSUh4e1m0EjxlnXmIXDenDE6qp0Z7Ccv6pUi1mb1XhXJj5xnz8WT/n2s9hGAZL5y3lnrvu0T4EMuEpEEjeJWKXObjnNd59/U/09V5iSlU1vuKhGxoBBLLdNCf3Ups5PiGCwU/KmnnRdznfZcg4KzFLmG/MpzxXTselDnoiPdSGa/nanV9j6bylOIbowyEyESgQyITR09nG3p3/w9F3d2NkMlRU11MwzKVYvlyUOcm9NKSP5HXTpLU1c2lz9uft/WV8+UwfrdlWarI1RKIR2rvbmRKawuovrGbV0lWEhhlsRSYCBQKZUCzL4uwHh9jz6n9z9oO/4nIXUlZVg8MxvPuuhWaMWcl3aEwdxIUxxtVeq91RyJqaciyb/pea7IJmkFnZWdTl6ojFYlxov4Df6+eLC7/IXcvv0u0BuSkpEMiEZGQyHH3vTfa+9hJdF88SKC0nWFox7F3fCswkM1PvMSO1H/c4NTf692ATT4bS4/JekgcWVJlVzMzOpNKsJJFMcL79PE6nk0VzF7Hm9jVMq5mmnQnlpqVAIBNarD/K+7u2s3/3dmJ9UUoqwvgCJcP+R9dpZWhMHWBW8l2KrLFtJfyPVa0ccEfH9D1k/DksB/W5emZmZxKwAmSMDOfaz5HL5mie0cy6FeuYO2OugoDc9BQI5KbQ1XaWd15/mQ8O7iMR6yc0pYLikrJh/yNst7JMSx9mTnIfvjHYVTGLjWX100nZJuZSSBk5t+WmKdtEU7YJDx6yuSxtnW3EE3Ga6ppYu2Iti+Yu0jJCmTQUCOSmYVkWXW1n+evbr3Pkvd3Eor0ESssIlFYMe3c4m2VSZZxieuoQVcbpUWuJvN1bxb+U68IwGRSbxczKzqI+V48DB9lslo5LHUT7o9SEa1izYg3L5i/T3gMy6SgQyE2pp7ONQ/ve4NDe1+nr6cYXLCFUFh7R8i6PGac+fYRp6cMEcz03VM93y+fyilerC25WNstGpVnJjOwMwmYYGzZS6RRtnW2kM2mqyqu447Y7WLF4BQF/IN/liowJBQK5qUV7ujjy7m7+umcnPZ0XB/dIcIxwGLfUaGda+hB1mWOfqwPil2rn0O2IjfjrJL8CZoD6XD312XqKKAKgP9bPxc6L2Gw2ptdOZ+WSlSyauwhfkS/P1YqMLQUCmRRifRGOvv8WB97cQXf7edyFRZRWVOMqGNnmMQ7LoCbzIdNSh6jInmc4MxROufzcXa315jcLt+WmLldHQ7aBEqsEGLgddSlyia6eLooKi2hubOaO2+6gZUYLLtfQLbVFJgMFAplUkvEYx/bvYf/u7XReOIPD6SJUVkmh1z/iWeDeXB/T0oeYlj6M1/z07oO/KJnJM4HkjZYuY8hluZiam0ptrpawGcbOwJyTbC5L56VOIn0RSgIlLGldwrKFy2isbdSqAbnlKBDIpJROJfnw4D4O7fsLF8+cIJWM4ysOEZxSjnOkW85aFmXZNqZmTlKdOUGxGb3m8P1TWzlWEP3EL5X8cVpOqnJV1OXqCJthHFydX5JKp2jvaieRShAuC7Ni8QqWzluqhkJyS1MgkEnNNE06zp/i5OH3Ofbem/R2t2MBwdJy/MHSEX8KvBS5xL79r3BvcxmLPb2UGp0sr68la8uOzTcgI+I1vVSalYRzYcJmGCdX55Lkcjl6oj30RHuw2+w0VDcMzg8o9hXnsWqRiUGBQG4Z6WSCsx8e4vj+vZw+doBYXwRPkY9gWQWeQu+wzvHekffZc/4Ud625F5fLhcNMcMLVSbu9nQ5HB2mbOhWOJ5flosKsoDJXSaVZid/yX3Pcsiz6Y/109XRhZA1KAiXMnz2fhc0LmdM4h4KRjhaJTGIKBHJLinR3cOrIfg6/u5uutjMYmTT+YCmB0rLP3Dfhv/7yMlFXASvvWHPdMQuLiC1Cu6Oddns7l+yXtK/BKLNbdkrNUirNSipzlZRYJYPzAa6wLItEMkF3pJtYIkaxt5im+iaWtC6huamZkkBJnqoXmdgUCOSWlstmaTt9nBOH3+P4/rfp6+3CbnfiD5XiC4SuCQepdIrnX3uJmhnNzJrVOuS5DQwi9gg99h56bb302HuI28e2ffKkY0GxVTwYAMrNclx88qz/wRAQj1HoKaS6oprbWm6jZWYLNeEaTRIUGYICgchHErF+Th87yIlD73L+5FFifREAvMUhikOlnG47y6vHDnD7qnUUFwc/13ukSNFrHwgHVx51m2GAw3IQsAKEzBBBM0jIGnj8tABgWRaxRIxIX4RYPIa7wE1VRRWL5y5mTtMcplVPG1GjKpFbnQKByCeI9UVoO/MBZz84zOljB+jr7ebg+dOczWZYfvtd+D/HMsZPfS9bbHAEodfeS5+9b9KHBLflJmSGBi7+VpCQGcJv+a8b/v9bqXSKaH+U6OUopmlS5CmivLSchXMW0tzUzLSaaeobIPI5KRCIDCGdStJ+9gS79+zk/fMniWXSXI5fxmF3ECwOEgqEcBe4R/U9DQzitjgxW4y4LU7cfvV5zBab8KsabJaNQquQIquIQgoHnwfMgRGAQoa3D0A2myV6OUq0P0o6k8Zd4CZUHGLW9FnMqJ9BQ3UDUyumaiRAZBQoEIiMgGmaXOy6yKnzpzh++jjHTh6jN9pLJpuhwFWA3+vH5/XhLfSO6T3rNOmrgcEeJ26LkyFD1pbFwLjm8cqvG5rgaIEDB3bsOHDgslwDF/uPLvRXnl/5swcPtmH1ebyWaZpcjl8m0h8hkUhgt9sJ+AM0VDcwp2kODVMbqK2q1cZCImNAgUDkBiRTSc60neH0+dOcOn+KM21n6I/1k0glAPAUePB5ffi9fjxuT94mtllY5MhdFxZy5AYu8tbVi/2VP388AAw1lP95mKZJPBkf+J2Ik06nwQb+Ij+VZZW0zGyhobqBhpoGgv7gqL//ePnpT3/K1q1b2b9/f75LEflM2q9V5AYUegqZPX02s6fPBiBjZOjo7qC9u52LXRc5efYkFzovcLHr4uAFr6iwCH/RwEjCaN9q+DQ2bDg/+sWVjwDj+FHAMAziyTixRIx4Ik7OzGHDRlFhEb4iH3Ob5lJfXU+4LExdVR2VZZV5CU8PP/wwzz33HABOp5Oamhruvfdefvazn+H1Dt2rwmaz8eKLL/L1r399jCsVGX0KBCKjqMBVQG1VLbVVtYOvJZIJ2rvbae9q50LnBU6ePUnHpQ7OtZ0jmxuYC2Cz2/AUePC4PbgL3IOPdvvofzIfK6ZpkjEypDNp0pk0iWSCZCqJhYXT4cRb6CVYHGTBnAVUV1ZTUVpBxZQKykrKJlSDoLVr17JlyxYMw+CNN97g0UcfJR6P89RTT+W7NJExpUAgMsaKCouYXjud6bXTgavd89q72rkUuUT0cpSeaA/tXe30RHtIppJE+iKkM2ksrIH7904HHrdnMDQ4nU4cdgcOhwOH3TGmwcGyLLK5LBkjQyYzcMG/cuE3DAOb3TYw2mADt8tNQUEBbpeb+qn1NNQ0EC4LU15aTkVpBaFAaMKHHLfbTWXlwJ4GDz74IDt37mTr1q1s376dxx57jO9+97uDf/fQoUO0trby4YcfcueddwJwzz33AFBXV8eZM2cG/+7zzz/Pj3/8YyKRCOvWrePpp5/G7x/orJhOp9m4cSMvvPAC/f39LF68mF/84hfcdtttAPz5z39m9erVvPrqq3z/+9/nyJEjzJ8/ny1btjBz5szx+LHILUCBQGSc2Ww2Av4AAX/gumO5XI7+eD/R/ih9l/vou9xHtD9Kd283Hd0d9Pb1EovHMLIGuVyOnDnw2zKtq0PsNhjIEQOvXQkOdrsdy7IwTRPTMrFMa+Dxo2lENmxcMw/wo4u8ZVo4nU4KXAWDF/vyknJKgiWUlZTh9/nxF/nx+/z4inwUe4vx+/zjdjtkrBUWFmIYBhs2bGDLli3XBIJnnnmGFStWMH36dPbt20d5eTlbtmxh7dq116x8OHnyJFu3bmXbtm1EIhEeeOABHn/8cTZt2gTA9773Pf7whz/w3HPPUVdXx+bNm1mzZg0nTpygpORqZ8Uf/ehHPPHEE5SVlfHYY4+xYcMGdu/ePX4/DJnUFAhEJhCHw0GoOESoOPSJxw3DoD/WTzKdJGNkMAyDtJG++jyTvub1VDpFMpUkkUqQzqRxOgYu7C6nC5fLNfjc6XTidHxs1MHhwOkYeM3lclHsKx5cQeEv8t8yy/z27t3Lb37zG+68806+9a1v8ZOf/IS9e/eyZMkSDMPgV7/6FT//+c8BKCsrAyAYDA6OMFxhmibPPvvs4IjAQw89xI4dO9i0adPg7Yhnn32WdevWAfD000+zfft2fvnLX7Jx48bB82zatImVK1cC8IMf/ID169eTSqXweDxj/rOQyU+BQOQm4nK5KA2V5ruMSW3btm34fD6y2SyGYXD33Xfz5JNPUl5ezvr163nmmWdYsmQJ27ZtI5VKcf/99w95zvr6+sEwABAOh+nq6gIGRg8Mw2D58uWDx10uF0uWLOHo0aPXnKe1tfWacwB0dXVRW1uLyI2a2DfzRETG2erVq9m/fz/Hjx8nlUrxxz/+kfLycgAeffRRXnjhBZLJJFu2bOEb3/gGRUVFQ57zb7sn2mw2TNMEuHrL5m9WVViWdd1rHz/PlWNXziNyoxQIREQ+xuv10tjYSF1d3XUX8q985St4vV6eeuopXn75ZTZs2HDNcZfLRS6XG9H7NTY2UlBQwK5duwZfMwyDd955h9mzZ3/+b0RkhHTLQERkmBwOBw8//DA//OEPaWxsZNmyZdccr6+vZ8eOHSxfvhy3200o9MlzQT7O6/Xyne98h40bN1JSUkJtbS2bN28mkUjwyCOPjNW3InIdjRCIiIzAI488QiaTuW50AOCJJ55g+/bt1NTUsGDBgmGf8/HHH+e+++7joYceYuHChZw4cYJXXnllWIFCZLSodbGIyAjs3r2bVatWceHCBSoqKvJdjsioUSAQERmGdDrN+fPn+fa3v004HObXv/51vksSGVW6ZSAiMgy//e1vmTlzJn19fWzevDnf5YiMOo0QiIiIiEYIRERERIFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQEBQIRERFBgUBERERQIBAREREUCERERAQFAhEREUGBQERERFAgEBERERQIREREBAUCERERQYFAREREUCAQERERFAhEREQE+H+eHbyF3KrVnwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create pie chart\n",
    "df_pie['Respondent'].plot(kind='pie',\n",
    "                          figsize=(5, 6),\n",
    "                          autopct='%1.1f%%', # add in percentages\n",
    "                          startangle=90,     # start angle 90°\n",
    "                          shadow=True,       # add shadow      \n",
    "                          )\n",
    "\n",
    "plt.title('Top 5 Languages that Respondents Wish to Learn Next Year')\n",
    "plt.axis('equal') # Sets the pie chart to look like a circle.\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stacked Charts\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a stacked chart of median `WorkWeekHrs` and `CodeRevHrs` for the age group 30 to 35.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 11398 entries, 0 to 11397\n",
      "Data columns (total 3 columns):\n",
      " #   Column       Non-Null Count  Dtype  \n",
      "---  ------       --------------  -----  \n",
      " 0   CodeRevHrs   8972 non-null   float64\n",
      " 1   WorkWeekHrs  11276 non-null  float64\n",
      " 2   Age          11111 non-null  float64\n",
      "dtypes: float64(3)\n",
      "memory usage: 267.3 KB\n"
     ]
    }
   ],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT CodeRevHrs, WorkWeekHrs, Age\n",
    "FROM master\n",
    "\"\"\"\n",
    "df_stacked = pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "df_stacked.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "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>CodeRevHrs</th>\n",
       "      <th>WorkWeekHrs</th>\n",
       "      <th>Age</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>33.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CodeRevHrs  WorkWeekHrs   Age\n",
       "0         3.0          8.0  31.0\n",
       "1         2.0         40.0  34.0\n",
       "2         2.0         40.0  32.0\n",
       "3        15.0         42.0  34.0\n",
       "4         2.0         40.0  33.0"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stacked = df_stacked.loc[(df_stacked['Age'] >= 30) & (df_stacked['Age'] <= 35)].reset_index().drop(columns=['index'])\n",
    "df_stacked.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "df_stacked.groupby(['CodeRevHrs','Age'])['WorkWeekHrs'].median().sort_values(ascending=False).unstack().plot(kind='bar', stacked=True, figsize=(20, 8))\n",
    "plt.title('Stacked Chart of Median WorkWeekHrs and CodeRevHrs For The Age Group 30 to 35', loc='center', color='blue')\n",
    "plt.xlabel('CodeRevHrs')\n",
    "plt.ylabel('WorkWeekHrs')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "QUERY = \"\"\"\n",
    "SELECT WorkWeekHrs, CodeRevHrs, Age FROM master\n",
    "WHERE Age BETWEEN 30 AND 35\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "df1 = df.groupby('Age').median()\n",
    "\n",
    "df1.plot(kind='bar', figsize=(10, 6), stacked=True)\n",
    "\n",
    "plt.title('Stacked Bar Chart of Median WorkWeekHrs and CodeRevHrs for Those Age 30 to 35')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing comparison of data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Line Chart\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the median `ConvertedComp` for all ages from 45 to 60.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "QUERY = \"\"\"\n",
    "SELECT ConvertedComp, Age FROM master\n",
    "WHERE Age BETWEEN 45 AND 60\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "df1 = df.groupby('Age').median()\n",
    "\n",
    "df1.plot(kind='line', figsize=(15, 5), color='green')\n",
    "\n",
    "plt.title('Median ConvertedComp for Those Age 45 to 60', color='red')\n",
    "plt.ylabel('ConvertedComp', color='blue')\n",
    "plt.xlabel('Age', color='blue')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bar Chart\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a horizontal bar chart using column `MainBranch.`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "QUERY = \"\"\"\n",
    "SELECT MainBranch, COUNT(*) as MainBranch\n",
    "from master\n",
    "group by MainBranch\n",
    "\"\"\"\n",
    "\n",
    "df=pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "df.plot(kind='barh', figsize=(10,6), color='green')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Close the database connection.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ramesh Sannareddy\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Other Contributors\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rav Ahuja\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change Log\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Date (YYYY-MM-DD) | Version | Changed By        | Change Description                 |\n",
    "| ----------------- | ------- | ----------------- | ---------------------------------- |\n",
    "| 2020-10-17        | 0.1     | Ramesh Sannareddy | Created initial version of the lab |\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
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