M4DataVisualization.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": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2023-01-14 11:38:07--  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’\n",
      "\n",
      "m4_survey_data.sqli 100%[===================>]  34.98M  9.80MB/s    in 3.6s    \n",
      "\n",
      "2023-01-14 11:38:11 (9.80 MB/s) - ‘m4_survey_data.sqlite’ 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": 2,
   "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": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to run an sql query\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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": 5,
     "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": 6,
   "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": 6,
     "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": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .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": 7,
     "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": 8,
   "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": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Histogram of ConvertedComp')"
      ]
     },
     "execution_count": 9,
     "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",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT *\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",
    "\n",
    "df['ConvertedComp'].plot(kind='hist')\n",
    "plt.title('Histogram of ConvertedComp')"
   ]
  },
  {
   "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": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Boxplot of Age')"
      ]
     },
     "execution_count": 10,
     "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",
    "\n",
    "df['Age'].plot(kind='box')\n",
    "plt.title('Boxplot of Age')"
   ]
  },
  {
   "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": 11,
   "metadata": {},
   "outputs": [
    {
     "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",
    "\n",
    "plt.scatter(df['Age'],df['WorkWeekHrs'])\n",
    "plt.title('Scatter plot of age and workweek hours')\n",
    "plt.show()"
   ]
  },
  {
   "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": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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j+6yzs88+u8fldCD+d/bpp5/immuuweuvvw6fz9fnY/vyzDPPYM6cOXC5XFBVFRaLBf/3f//X4zJxl4F8XteuXdvv9+RANDY24nvf+x5KSkoS5SkrKwOARJk6Ojrw0Ucf4etf/zqsVmvisS6Xq9fzvPzyy5AkCZdcckmP9y4/Px+TJ08elpGeA8VOsgdh/PjxvTrJVldX45ZbbsEll1yC9PT0QR9TVVVkZWX12Jafnw8gfsLqa3t/+xYXF/e6v+ta8s0334ybb765zzL0N9xvIM8djUYRCATg8Xh63d9V/oKCgl73FRYWJk76gzVUx+06qS9fvhwVFRWIxWI46aST0NDQgP/+7/9O3DdnzpxEp8oDlaXrC6xLX/t12bp1K9ra2nDVVVehsrKy1/02mw1z5szB8uXLcccdd+DNN9/ELbfcgvnz58MwDLz33nuJE2vXa2lpaYGu67jvvvtw33339fm8Xe9/Q0MDtm/f3usksO9+XdasWYPm5mbceeedfX729mffzzwAaJqGUCgEAGhra4MQot96BXr/fQxUX8c84YQT8MILL+BPf/oTLr30UkQiEUyYMAG33XYbLrzwwkEdv6mpCQD2WyeDeX0tLS37/dvv0vW33hW29iXLvX+XLl++HB6PB62trXjkkUfw7LPP4vrrr8fDDz/c45jnn39+v6+ltbUVTqcTEyZMwIwZM7B06VJcffXVMAwDjz/+OM455xxkZmb2etzkyZMTHXS76y/U9VVXt956K5xOJx5//HE8/PDDUBQFJ5xwAu66664e39X7eu6553DBBRfgG9/4Bn784x8jPz8fqqrioYcewl//+tde+w/k82qa5oDep76YpolFixahtrYWv/jFLzBx4kQ4nU6Yponjjz++199F97DaZd9tDQ0N/e4LACNGjDhguYYLA0qSTJo0Ca+//jq2bt2K4447LvHHFYlEeuzXXwjQdR0tLS09/gC65iHY94+ir/kJ+tu3S9cXwK233orzzjuvz33Gjh3b5/aBPLfVau13LpeuMtXV1fW6r7a2ts8vp4EYquMWFxdjzJgxWL58OcrLyzF9+nSkp6djwYIFuOaaa/Dhhx/igw8+6DEcuntZ9j0h9VWW/c2HMGvWLHzjG9/AlVdeCSDeuXDfk8qCBQvwy1/+EmvWrMGePXuwcOFCuN1uzJgxA8uWLUNtbS3GjBmDkpISAPEWm65f5ddee22fz1tRUQEg/lmx2+19fkF33d/dN7/5TeTn5+O2226DaZr4+c9/3u9rG6yMjAzIstzve9y9PN3/5rqP6ujvb66/9+Ccc87BOeecg0gkgg8++ABLlizBRRddhPLycsyaNWvAZc/JyQGAfls1gcG9vqysrP3+7Xfp2v9f//pX4pf3gXQPCQsXLsQpp5yCRx55BFdeeSVmzJiRuO++++7D8ccf3+cxup8Av/Od7+Caa67BF198gZ07d6Kurg7f+c53BlSWA+nrfVNVFTfddBNuuukmtLe3Y/ny5fjZz36GU045BTU1Nf2OkHv88cdRUVGBp59+usdx9/3eHqiMjAxIkjSg96kvn3/+OT799FM8+uijuOyyyxLbt2/f3ufz7NuJua/nyc7OhiRJeO+99/oc7ZTSI6CG9wrTkWV//RgWLlwoAIidO3cKIYSoq6sTAMTdd9/dY79f/OIXg+6D8t577yW2YT99UEaOHJnY1lcflNGjR/fqrzFQB+qDsmDBgsS2/vqgnH322T2OWVNTIzRN69Gh7qabbhIARDAYPGCZBnPcwfRBEUKIa665RmRnZ4upU6eKn//854ntpaWlYtGiRQKAWLNmTWL75s2bBQDxgx/8oMdx1qxZIwCI2267LbFt3rx5YsKECX0+b/dOss8884ywWCzi4osvFrqu93ncRYsWieLi4sT2X/ziF2Ly5MkiLy+vV3+Yk08+WUyePLnHNeu+/OY3vxEOhyPxWd4fdOske++99wpJksRPf/rTAz5u38d2V1ZWJi677LLEv2fNmiXy8/N7fCYMwxATJ07s0UfjySef7PW+CCHECSec0GcflK56PpD169cLAOKBBx4Y0P7djRw5UowaNWq/Hb0H+voG2gelqqpKqKoq7rrrrgOWr79Oslu3bhWqqopFixYJIeJ9G9LT08X3v//9Ab3utrY2YbPZxC233CLOP/98UVRU1KuPW3/P3aW/TrK/+93vBlSGe++9VwDo0Sl4X+edd54YO3Zsj211dXXC5XL16i8y0M/rofRB+eyzzwQA8eSTT/bY3tVp+Ve/+lVi20D7oKxcuVIAEE8//fR+nzsVsQXlIHz++efQdR1AvNn1ueeew7Jly3DuuecmfoXm5+fj5JNPxpIlS5CRkYGysjK8+eabeO655/o8ptVqxR/+8AcEAgHMmDEDq1atwm9+8xucdtppiX4OXbKzs3HSSSfhF7/4BZxOJx588EFs3rz5gEON//znP+O0007DKaecgssvvxxFRUVobW3FF198gY8//rjH0Nr+KIqChQsX4qabboJpmrjrrrvg8/n2O7laeno6fvGLX+BnP/sZLr30Ulx44YVoaWnBHXfcAZvNlhg+C8SHywLAXXfdhdNOOw2KomDSpEk9rrMezHEHa8GCBXjwwQfR3NyMe++9t8f2pUuXIiMjo8cQ47Fjx+Lqq6/GfffdB1mWcdppp2HXrl34xS9+gZKSEvzwhz8cdBnOP/98OBwOnH/++QiFQnjyyScT9TBt2jRkZGTgjTfe6PHL9OSTT05chuq6vNPlj3/8I+bOnYuvfe1r+P73v4/y8nL4/X5s374dL730Et566y0AwI033ohnn30WJ5xwAn74wx9i0qRJME0Tu3fvxhtvvIEf/ehHmDlzZq/y3nDDDXC5XLj66qsRCATwpz/9KSkzZy5ZsgQLFy7EiSeeiJtvvhlWqxUPPvggPv/8czz55JOJ5zj99NORmZmJK6+8Er/+9a+hqioeffRR1NTUDPi5fvnLX2LPnj1YsGABiouL0d7ejj/+8Y+wWCyYN29eYr/58+djxYoVEELs93gPPPAAzjrrLBx//PH44Q9/iNLSUuzevRuvv/46/vGPfwzq9f385z/Hiy++iJNOOgm//OUv4XA48MADD/Qa+l1eXo5f//rXuO2227Bz587EPE0NDQ1Ys2YNnE7nASdDHD16NK6++mo8+OCDWLlyJebOnYv77rsPl112GVpbW3H++ecjNzcXTU1N+PTTT9HU1ISHHnoo8fj09HSce+65ePTRR9He3o6bb765z0tLyXLWWWcl5qfKyclBdXU17r33XpSVlWH06NH9Pq5rqPk111yD888/HzU1Nfjv//5vFBQUYNu2bQdVlv/+7//GqaeeioULF+JHP/oRDMPAXXfdBafTidbW1v0+dty4cRg5ciR++tOfQgiBzMxMvPTSS31erv71r3+NM844A6eccgpuuOEGGIaB3/3ud3C5XD2eZ86cObj66qvxne98Bx999BFOOOEEOJ1O1NXVYeXKlZg4cSK+//3vH9RrHXLDnZCOJH2N4vF4PGLKlCninnvu6fUrqa6uTpx//vkiMzNTeDwecckll4iPPvqozxYUp9MpPvvsMzF//nxht9tFZmam+P73vy8CgUCPY6IzxT/44INi5MiRwmKxiHHjxol//OMfPfbrbxTRp59+Ki644AKRm5srLBaLyM/PFyeddJJ4+OGH9/vau3693HXXXeKOO+4QxcXFwmq1iqlTp4rXX3+9z3rq/otVCCH+93//V0yaNElYrVbh8XjEOeec0+vXTSQSEf/1X/8lcnJyhCRJfR5nXwM57mBbUNra2oQsy8LpdPYYMfCPf/xDABDnnXder8cYhiHuuusuMWbMGGGxWER2dra45JJLRE1NTY/9BtqC0uXtt98WLpdLnHrqqT1+ZZ977rkCQI/3PhqNCqfTKWRZFm1tbb2OX1VVJa644gpRVFQkLBaLyMnJEbNnzxa/+c1veuwXCATEz3/+czF27NhEvU6cOFH88Ic/7PELHn38qnzyySeFqqriO9/5zn5HhvX12K466P6LVAgh3nvvPXHSSScJp9Mp7Ha7OP7448VLL73U67Fr1qwRs2fPFk6nUxQVFYlf/epX4n//938H3ILy8ssvi9NOO00UFRUJq9UqcnNzxemnn96jFVMIIaZNmyby8/P7fW3drV69Wpx22mnC4/EITdPEyJEjxQ9/+MODen3vv/++OP7444WmaSI/P1/8+Mc/Fo888kiffycvvPCCOPHEE0VaWprQNE2UlZWJ888/v8eosP21YjQ0NAiXy9VjZNiKFSvEGWecITIzM4XFYhFFRUXijDPO6DHFQZc33ngj8T3ZNeS/u2S2oPzhD38Qs2fPFtnZ2YkpG6688kqxa9euPo/d3W9/+1tRXl4uNE0T48ePF3/5y1/6HBE2mM/riy++mPhOKi0tFb/97W/7HWW2r02bNomFCxcKt9stMjIyxDe+8Q2xe/fuXi0oQgjx/PPPi4kTJ/Z4nh/84AciIyOj13H/+te/ipkzZyY+YyNHjhSXXnqp+Oijjw5YpuEiCXGAnwBEiE+SVFFRgd/97nf9drIlOhr4/X5kZmbi3nvv7bc/D9FwiMVimDJlCoqKivDGG28Md3EOGS/xEBENwrvvvouioiJcddVVw10UOspdeeWVWLhwIQoKClBfX4+HH34YX3zxxQFn0D1SMKAQEQ3CGWec0WupAaLh4Pf7cfPNN6OpqQkWiwXHHnssXnnllV79z45UvMRDREREKYczyRIREVHKYUAhIiKilMOAQkRERCnniOwka5omamtr4Xa7kzIRFBEREQ09IQT8fj8KCwsPOHnfERlQamtrE2uMEBER0ZGlpqbmgIuLHpEBpWu565qaGqSlpQ1zaYiIiGggfD4fSkpKEufx/TkiA0rXZZ20tDQGFCIioiPMQLpnsJMsERERpRwGFCIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilDPogPLuu+/irLPOQmFhISRJwgsvvNDjfiEEbr/9dhQWFsJut2P+/PnYuHFjj30ikQiuv/56ZGdnw+l04uyzz8aePXsO6YUQERHRV8egA0pHRwcmT56M+++/v8/77777btxzzz24//77sXbtWuTn52PhwoXw+/2JfW688UY8//zzeOqpp7By5UoEAgGceeaZMAzj4F8JERERfWVIQghx0A+WJDz//PP4+te/DiDeelJYWIgbb7wRP/nJTwDEW0vy8vJw11134bvf/S68Xi9ycnLw97//Hd/85jcBfDl1/SuvvIJTTjnlgM/r8/ng8Xjg9Xo5URsREdERYjDn76T2QamqqkJ9fT0WLVqU2KZpGubNm4dVq1YBANatW4dYLNZjn8LCQlRWVib22VckEoHP5+txGypCCOxpC+KdLY1484sGbKn3wzAPOsMRERHRQUjqVPf19fUAgLy8vB7b8/LyUF1dndjHarUiIyOj1z5dj9/XkiVLcMcddySzqH0yTYFXP6/D21ua4A/HIAGwqjKmlKTjmzNK4dSOyJUBiIiIjjhDMopn3zn2hRAHnHd/f/vceuut8Hq9iVtNTU3Sytrdp3va8drGBlgVGWPz3Bibn4Zctw0fVLVi2aaGIXlOIiIi6i2pASU/Px8AerWENDY2JlpV8vPzEY1G0dbW1u8++9I0LbEw4FAuELh2VyuEKZDj1hJhyampyHRY8VF1KwIRfUiel4iIiHpKakCpqKhAfn4+li1bltgWjUaxYsUKzJ49GwAwbdo0WCyWHvvU1dXh888/T+wzXJr8ETg0pdd2l6YiGDUQCDOgEBERHQ6D7lQRCASwffv2xL+rqqqwfv16ZGZmorS0FDfeeCMWL16M0aNHY/To0Vi8eDEcDgcuuugiAIDH48GVV16JH/3oR8jKykJmZiZuvvlmTJw4ESeffHLyXtlByEuzYW97uNd2f1iHS1PhtrEPChER0eEw6DPuRx99hBNPPDHx75tuugkAcNlll+HRRx/FLbfcglAohGuuuQZtbW2YOXMm3njjDbjd7sRj/ud//geqquKCCy5AKBTCggUL8Oijj0JRerdeHE7HVWRiw14vGnxh5HZe5vGFYmgPRXHm6EJ2kiUiIjpMDmkelOEyVPOgCCGw/IsGLN/UAG8oBkgSbKqMY8sy8I1pJbBbhzdAERERHckGc/5mk0A3kiRh4TH5mFycjm2NAeimQEmGHeVZTsjy/kchERERUfIwoPQhN82G3DTbcBeDiIjoqMXVjImIiCjlMKAQERFRymFAISIiopTDgEJEREQphwGFiIiIUg4DChEREaUcBhQiIiJKOQwoRERElHIYUIiIiCjlMKAQERFRymFAISIiopTDgEJEREQphwGFiIiIUg4DChEREaUcBhQiIiJKOQwoRERElHIYUIiIiCjlMKAQERFRymFAISIiopTDgEJEREQpRx3uAqQ6IQQafBFEdRNZLiucGquMiIhoqPFsux+7mjvw6ud12NEYQMwUSLdbMGtkFk4alwerysYnIiKiocKA0o89bUEsfb8KDb4ICjw2WFUZbcEoXlhfC39Yx/nTiiFJ0nAXk4iI6CuJzQD9WL2jBfXeMMbkuZBmt8BmUVDgsSPXpeHDnS2o9YaHu4hERERfWQwofTBMgc/3epHusPZqJUl3WBCIGNjV3DFMpSMiIvrqY0DphwCwvys4Qhy2ohARER11GFD6oMgSjilIQ1swCrFPEvGGYnBqCsqyHMNUOiIioq8+BpR+zB6ZjRy3hu2NAQQiOqK6iUZfGPW+CKaVZaA4wz7cRSQiIvrKYkDpR2mWA5fPLse4gjS0dkSxpy0IWZZw+sR8nHcsR/AQERENJQ4z3o9RuW5cd6ILe9tDiOgmctwaPHbLcBeLiIjoK48B5QBkWUJJJvubEBERHU68xENEREQphwGFiIiIUg4DChEREaUcBhQiIiJKOQwoRERElHIYUIiIiCjlMKAQERFRymFAISIiopTDgEJEREQphwGFiIiIUg4DChEREaUcBhQiIiJKOQwoRERElHIYUIiIiCjlMKAQERFRymFAISIiopTDgEJEREQphwGFiIiIUg4DChEREaUcBhQiIiJKOQwoRERElHIYUIiIiCjlMKAQERFRymFAISIiopST9ICi6zp+/vOfo6KiAna7HSNGjMCvf/1rmKaZ2EcIgdtvvx2FhYWw2+2YP38+Nm7cmOyiEBER0REq6QHlrrvuwsMPP4z7778fX3zxBe6++2787ne/w3333ZfY5+6778Y999yD+++/H2vXrkV+fj4WLlwIv9+f7OIQERHRESjpAWX16tU455xzcMYZZ6C8vBznn38+Fi1ahI8++ghAvPXk3nvvxW233YbzzjsPlZWVeOyxxxAMBvHEE08kuzhERER0BEp6QJk7dy7efPNNbN26FQDw6aefYuXKlTj99NMBAFVVVaivr8eiRYsSj9E0DfPmzcOqVav6PGYkEoHP5+txIyIioq8uNdkH/MlPfgKv14tx48ZBURQYhoE777wTF154IQCgvr4eAJCXl9fjcXl5eaiuru7zmEuWLMEdd9yR7KISERFRikp6C8rTTz+Nxx9/HE888QQ+/vhjPPbYY/j973+Pxx57rMd+kiT1+LcQote2Lrfeeiu8Xm/iVlNTk+xiExERUQpJegvKj3/8Y/z0pz/Ft771LQDAxIkTUV1djSVLluCyyy5Dfn4+gHhLSkFBQeJxjY2NvVpVumiaBk3Tkl1UIiIiSlFJb0EJBoOQ5Z6HVRQlMcy4oqIC+fn5WLZsWeL+aDSKFStWYPbs2ckuDhERER2Bkt6CctZZZ+HOO+9EaWkpJkyYgE8++QT33HMPrrjiCgDxSzs33ngjFi9ejNGjR2P06NFYvHgxHA4HLrroomQXh4iIiI5ASQ8o9913H37xi1/gmmuuQWNjIwoLC/Hd734Xv/zlLxP73HLLLQiFQrjmmmvQ1taGmTNn4o033oDb7U52cYiIiOgIJAkhxHAXYrB8Ph88Hg+8Xi/S0tKGuzhEREQ0AIM5f3MtHiIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilMOAQkRERCmHAYWIiIhSDgMKERERpRwGFCIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilMOAQkRERCmHAYWIiIhSDgMKERERpRwGFCIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilMOAQkRERCmHAYWIiIhSDgMKERERpRwGFCIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilMOAQkRERCmHAYWIiIhSDgMKERERpRwGFCIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilMOAQkRERCmHAYWIiIhSDgMKERERpRwGFCIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilMOAQkRERCmHAYWIiIhSDgMKERERpRwGFCIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilMOAQkRERCmHAYWIiIhSjjrcBfgqEUKgwRdBKGbApanIdlkhSdJwF4uIiOiIw4CSJBtrvVixtQk7GgOIGSZsFgXHFKRh/thclGc7h7t4RERER5QhucSzd+9eXHLJJcjKyoLD4cCUKVOwbt26xP1CCNx+++0oLCyE3W7H/PnzsXHjxqEoymGxdlcrlq6swud7vUizWVCYbofNouCDnS343/d2YmuDf7iLSEREdERJekBpa2vDnDlzYLFY8Oqrr2LTpk34wx/+gPT09MQ+d999N+655x7cf//9WLt2LfLz87Fw4UL4/UfeidwbiuGl9bUwBDA61400uwWaqiDDYcWYPDfagjH8e/1exAxzuItKRER0xEj6JZ677roLJSUlWLp0aWJbeXl54r+FELj33ntx22234bzzzgMAPPbYY8jLy8MTTzyB7373u8ku0pDauNeLRn8Eo3Jdve6TJAnFGXZUtwSxrSGAYwrThqGERERER56kt6C8+OKLmD59Or7xjW8gNzcXU6dOxV/+8pfE/VVVVaivr8eiRYsS2zRNw7x587Bq1ao+jxmJRODz+XrcUkWTPwJAQJH77gxrsygwTIHmQOTwFoyIiOgIlvSAsnPnTjz00EMYPXo0Xn/9dXzve9/DD37wA/ztb38DANTX1wMA8vLyejwuLy8vcd++lixZAo/Hk7iVlJQku9gHTVEkiP3cL4SAEOg3wBAREVFvSQ8opmni2GOPxeLFizF16lR897vfxVVXXYWHHnqox377Dr8VQvQ7JPfWW2+F1+tN3GpqapJd7INWnuWERZERiRl93u8L63BqCsqyHIe5ZEREREeupAeUgoICHHPMMT22jR8/Hrt37wYA5OfnA0Cv1pLGxsZerSpdNE1DWlpaj1uqGJPnxogcJ3a1BKHv0xE2ohuobQ+hssiDonT7MJWQiIjoyJP0gDJnzhxs2bKlx7atW7eirKwMAFBRUYH8/HwsW7YscX80GsWKFSswe/bsZBdnyFlVGRceV4oROU5sb+rArpYO1HvD2NkcQHVLEJOK03He1GJO2EZERDQISR/F88Mf/hCzZ8/G4sWLccEFF2DNmjV45JFH8MgjjwCIX9q58cYbsXjxYowePRqjR4/G4sWL4XA4cNFFFyW7OIdFgceO784biU9r2vHx7jb4wzGUZjkwvSwDk4rTYbcqw11EIiKiI4okhNhfH8+D8vLLL+PWW2/Ftm3bUFFRgZtuuglXXXVV4n4hBO644w78+c9/RltbG2bOnIkHHngAlZWVAzq+z+eDx+OB1+tNqcs9RERE1L/BnL+HJKAMNQYUIiKiI89gzt9czZiIiIhSDgMKERERpRwGFCIiIko5DChERESUchhQiIiIKOUwoBAREVHKYUAhIiKilMOAQkRERCkn6VPdf1U0+sOoaQ0BECjOcCAvzTbcRSIiIjpqMKDsIxQ18NKntVhX3QpvWIcEwG1TMbU0HWdPLoJTY5URERENNZ5tuzFNgX+tq8HK7c3IcWkYneuCBKAtGMPbm5sQipm4bFY5FJkrExMREQ0l9kHppro1iI93t6HQY0eWS4MsSZAkCZlOK0oyHPh0dzt2NgWGu5hERERfeQwo3WxvDCAUNeC29W5YctlUhHUT2xsZUIiIiIYaA0o3umECna0mfZEAxMwjbvFnIiKiIw4DSjc5bg0ygJhh9rpPN+Pbct3aYS4VERHR0YcBpZsJhR4UZzqwqyUIU3zZUmIKgeqWIIrS7ZhQmDaMJSQiIjo6cBRPN3argguml+AfH1Zja4MfNlUBpPjQ4wKPDRfMKIHbZhnuYhIREX3lMaDsY1SuC9edOArra9qxud4PABid68LU0gzk8PIOERHRYcGA0ocsl4YF4/OwYHzecBeFiIjoqMQ+KERERJRyGFCIiIgo5TCgEBERUcphH5QBEJ3DjD/f64U3FIPHbsHEYg9KMx09JnUzTYGatiAa/WFUNwfhj+hIs1swe0QWCtLtfR5bN0xsbwqgzhuGRZYxKteFfA9XTiYioqMbA8oBmKbAa5/X483NDQiEdaiKDN008faWRiw8Jg+nTMiHJEmo84bw3Lq9WLurFZ/vbUcwakCRZTg1BblpNlw8sxQXTC/pEWhaO6J4cs1ubKn3IarH511Js6uYOyoHZ0wq4KKERER01GJAOYD1e9rx6sZ6pNlUFKXbIUkShBBoDkTx6uf1KPDYMTLXhb+vrsYXdT5sbfAjFDOhWWQIE4AQaAlE8Jf3qlCUYcfcUTkA4sHn6bW78WlNO8qyHHBYVQgh0NIRxWsb65HhtOBro3OG98UTERENE/ZB2Q8hBD7Y2QIhBLJdWqL1Q5Ik5Lg16IbAh1Ut+GxPO3Y2dUCVJfjDMTisChxWFTargqghkO6wIBCO4cVPaiE6Z6jd2dyBzfV+lGbGw0nXcbNdGjRVxvvbm/uccp+IiOhowICyH1HDxN62EDz2vmeP9dgt2N0aRE1rCADQFozCBGBR4kFGkSUIALohYFFk7GrpQDgWDx2NvjAiugmn1rsRK8NhQbM/grZgdEheFxERUapjQNkPRZJgUeR+WzJihgmrIsNmkWGKeAiBALpW8elazkeSJJgCsKpyol+JRZUhATD6WB05ZgioigyrwreHiIiOTjwD7oeqyJhSko72YAzmPkHCMAV8oRiOLc3AMQVpcFgVeBxWWBQZoagJIQSihglVliBBwDBNzB6ZBasar/JROS5kOCxo9Id7HNcUAo3+MMblu/ttuSEiIvqqY0A5gNkjs1CSacfWRj+8oRh0w4Q3FMO2Rj9KsxyYOSILI3NcmDcmB4oEZDqtiOoGWjtiCMd0AEBbMIZxBW6cd2xx4rgZTisWHpOHcMzEzqYA2oNRNAci2NrgR36aDSeNy+sx4oeIiOhoIomuXptHEJ/PB4/HA6/Xi7S0tCF/vj1tQbyyoQ5b6v0Ix0zYLTLG5qfh9EkFKOqc38QwBdbXtOPDnc1YvaMFte1hCAAZTguOK8/CJceXoSij51woQgh8vLsNK7c1o7Y9BEWWcEyhB/PG5KAk0zHkr4uIiOhwGsz5mwFlgIQQqPOG0RHR4bKpyE+z7beFIxwz4A3FYFMVeBz7v1RjmgL+sA5VkfrsNEtERPRVMJjzN8+GAyRJEgr7mQ22LzaLAptFGdC+siwdMMQQEREdTdgHhYiIiFIOAwoRERGlHAYUIiIiSjkMKERERJRyGFCIiIgo5TCgEBERUcrhMOMk6porJRDRke6wINdtG+4iERERHZEYUJKkyR/BC5/sxeZ6H8IxE05NweSSdJw9uRBuG+c4ISIiGgxe4kmCcMzA3z/YhY+qW+G2WVCe5YCmKlixpQnPfFTTa6FBIiIi2j+2oCTBxloftjcEMCLblVitONNphUWR8NkeL3a1dGBEjmuYS0lERHTkYAtKEjT4wjCBRDjp4rZZENZN1PvCw1MwIiKiIxQDShJoqgxhCuy77qJumpAAaOrA1uQhIiKiOAaUJBhXkAaPw4JGfySxTQiBvW0h5Lo1jMnj5R0iIqLBYEBJgkKPDadMyEdUN7GlwY9dzR3YUu+HZlFw9pQijuIhIiIaJHaSTQJJknDSuFyUZDqwfnc72oJR5HtsmFqSgdIsx3AXj4iI6IjDgJIkkiRhTJ4bY/Lcw10UIiKiIx4v8RAREVHKYUAhIiKilMOAQkRERCmHAYWIiIhSDgMKERERpRwGFCIiIko5HGacZOGYgUjMhN2qQJUlSFJ8CDIRERENHAPKPoQQ2NMWQnMggnDMQKZTQ65bQ4bTut/HNXhDeOHTWrz1RQOa/BEYQiDTYcX4Ag9OGpeL6eUZSHfs/xj9lWdLgx/rdrWhujUIm0XGlJJ0HFt6cMcjIiI6Egx5QFmyZAl+9rOf4YYbbsC9994LIH7SveOOO/DII4+gra0NM2fOxAMPPIAJEyYMdXH2yxeO4dl1e/BxdRt2NHXAF47BpsoYnefGiWNzccakAji13lVW0xrEbc9vwPqaNoSiJgxTwASwuyWELfV+rKtuxdzROfjuvBHIddsGXB4hBJZ/0YBXNtQhHDPh0lTEDBNb6v1YU9WKy2dXIN8z8OMREREdKYa0D8ratWvxyCOPYNKkST2233333bjnnntw//33Y+3atcjPz8fChQvh9/uHsjj7JYTAvz6qwartzahtDyMcM5BmV2EKYEdTAP/ZUIt/rdvTa8ViIQQeXrEdn9S0I6oLdN0rd17VCesmGn1hrNjaiOc/3tvr8fuzoymAVzfUw25RMSbPjcJ0O8qynBiV60JVcwee/6R3eYiIiL4KhiygBAIBXHzxxfjLX/6CjIyMxHYhBO69917cdtttOO+881BZWYnHHnsMwWAQTzzxxFAV54B2twaxYa8PTpsKfyQGj90Ct2ZBtssK3RCQJeDTmnbsbg32eFxNaxAf7GyFYRiQ5fjrk2VAlSUoMiAEEDUEorqJNVWtqPOGB1ymj6vbEYwayHFrPbarsoyidDu2NQR6lYeIiOirYMgCyrXXXoszzjgDJ598co/tVVVVqK+vx6JFixLbNE3DvHnzsGrVqj6PFYlE4PP5etySrdEfQSimAwIwTQGrGq8aSZKgKhKiuolQzECDL9LjcQ3+MHwhHbIkwTTj2yRIiccCQMwwIYRAWzCK1o7ogMu0pz0Ih1Xp8z6XpiIYM9AyiOMREREdKYakD8pTTz2Fjz/+GGvXru11X319PQAgLy+vx/a8vDxUV1f3ebwlS5bgjjvuSH5Bu9FUGXJitI0EU4jEv01TQJVlSBJgs/TMdDZVhaoAAqL3aB0BSEDncSRYVTkRfAbCYY33OemLbsbLZ1U4UpyIiL56kn52q6mpwQ033IDHH38cNlv/HTj3PZkL0ccJvtOtt94Kr9ebuNXU1CS1zAAwOteNAo8dYd2Aw6rAF4pBCIFIzAAAmBAo9NgxOrfnasWjcl0YleuGgAypM6QYpoAQgNnZP8SqylAkCaNzXSjLcgy4TJOKPYh1Xh7aV4MvjLw0DSNzXIfwqomIiFJT0gPKunXr0NjYiGnTpkFVVaiqihUrVuBPf/oTVFVNtJx0taR0aWxs7NWq0kXTNKSlpfW4JZvdquCcKYXIsFthtyqI6CaqW4Jo8IWhWRSUZjpx3rHFsO9zycVuVXDB9BJkOq0wISHelgLETAFDxDvLOqwKSjIdOGNSITS170s2fZlcnI7xBW7saAqgLRiFEPGwUtMaRMwQWDAur1d5iIiIvgqSfolnwYIF2LBhQ49t3/nOdzBu3Dj85Cc/wYgRI5Cfn49ly5Zh6tSpAIBoNIoVK1bgrrvuSnZxBmVScToyHFasq27Dxlov/BEd2U4Nk4o9mFKa3u8Q4TMmFiBmmPjHB7uxszmAYNSAKQQ0VUZhuh3Hlqbj7ClFmFmROajyODUVl84qx0uf1eLzvV5s9UegyhLy02w4aVwuZo3MSsbLJiIiSjlJDyhutxuVlZU9tjmdTmRlZSW233jjjVi8eDFGjx6N0aNHY/HixXA4HLjooouSXZxBK8l0oCTTga9PLRrwY2RZwnnHFuOkcbn4eHcb2oJRGIZAUYYDHrsFI3NcB93SkeG04tJZ5WjwhdHkj8CiyCjLcsBmYcsJERF9dQ3LTLK33HILQqEQrrnmmsREbW+88QbcbveBH5zC0h1WnDSu78tUhyovzYa8NE7KRkRERwdJHIEzffl8Png8Hni93iHpj0JERETJN5jzN8eoEhERUcphQBkCR2CjFBERUUrhasZJEtENrNvVhjW7WtHWEUW+x47jKjIxtSQdstz3/C5ERETUNwaUJIgZJp5eW4MPdrRAVWQ4rAo21nqxqdaLvcfk46zJBf1OQkdERES9MaAkwYa9XqzZ2YqCdDtcWrxK8wC0dkTxzpZGVBalYUS3GV+juomoYcJuUaCwdYWIiKgXBpQk+GxPOwTiKxhXN3cgGDPg1hTkptnQ6A9jS70fI3JcaPSFsWpHCz7Z3YaobsLjsGDmiCzMrMiEw8q3goiIqAvPikkQCOvwhqLYsNeL9lAUwoxP3pbtsqLAY0MoamBPWxCPvr8Lu1uDyHBYoVlkNPgieHpNDbbU+3HprDKGFCIiok48IyaBw6Lg870+xAwjftnGIkPXTdR7w/CFYnBYFby4vhZ72oIYk+dOXNbJcFgRjhn4ZHcbRuW4cPIxQzPJGxER0ZGGw4yTwBuOIaobUGUJVlWJ/79FgSQBId1ATXsI2xoDKEy39+pzYrMocGkqPqxq6XPVYiIioqMRA0oSNPojsFsVaBYVoZiBYNRAOGbAaVVhUxXUtAYRihqJDrT7SrNZ4A3FEIjoh7nkREREqYmXeJIgw2GFVZWR57YhopswhIAqS5ABtAZjSLdb0BKIIGYIWNXeo3YiutnZ+sK8SEREBLAFJSlOHJsLh1VFezAKp6Yiw2GF3aKgPaQjy2XFaZX5yPfY0OAL93qsEAItHRFUFnn6bWEhIiI62jCgJMGU0nScPbkQsixjb1sQe9uCqG0Pw6kpuPC4UowrSMNJ4/KgmwJ72oLQjXhfk1DMwPamDuS6bZg7KmeYXwUREVHq4E/2JLAoMr4/fxSmlKTjtY31aA5EUZJhx2mVBZhWlgFJkjB7ZBaEAJZ/0YCdLR2AiM+bMiLHiXMmF6I0yzHcL4OIiChlSOIIXNluMMs1p5qOiI7tjQFEdBMeuwUjc5xQFTZkERHRV99gzt9sQTnMnJqKySXpw10MIiKilMaf7kRERJRyGFCIiIgo5TCgEBERUcphQCEiIqKUw4BCREREKYejeA5R91Hajf4IAhEdDquC/DQbJKn3tPbJYpoCTYEIYoaJDIcVTs5CS0REXyE8q/Whtj2Ed7c2YVtTAIokYWyuC5NL0zEyx5UIHdsbA1hT1YIt9X4EIjpCUQPVrQHUeyPQDRNOmwUzyzOQm2ZDOGbCbbNg5ohMzBmZBVk+cMOVbpjY2hBAVXMHDCFQnGHHMQVp0FQZn+3x4t1tTahu7oBuCqTZLZhRlol543KQZrMktS4afGF8tKsVG2t9MIXA2Pw0TC/LQEkmJ5YjIqKhw4naujFNgf98VovHP6xGdUsQQgCqIsFtUzE6z43TKwtwamU+1u5qwzMf1cAf0SEB2Fzvxd62EGLGl8fqqlRZAqyKDM0iw62pOG5EFn59diVctv6zYTCq46k1u/HJ7nZEDRMSJEgyMCbXjXF5brzxRQNihokctwaLLMMbiqEtGMXEIg8un1MOd5JCyvZGP/6+uhp13jDcNhUSJPjDMWS6rLjwuFJMKk5PyvMQEdHRgRO1HaQ1u1rx5Noa1HkjyHFrcFhVRHQDvpCORl8Yr22sh9uu4pXP6mGYAqNznFhb3Ya2QAwxIx5KJMRDidGZUMzOkKNKElRFwsptzXh4xXbcfMq4fsuxbGMDPqxqRUmGI3HpJqIb+GxPO97d2oQR2U6MzHEl9rdbFWQ6rdhQ68WqHS04ZUL+IddFRDfwr3V70BSIYmy+G3Jny5EQNuxqCeLZj/egLMsJjz25LTZEREQAO8kmmKbAqu3NaAtGoakyHNZ4MNBUBU5NQSCsIxDW8eqGerR0RFGUYYc3rKMlEEGos+lEkeIhZd82qXDMhAkAQoLdIuOdLU3wh2N9lsMfjmHtrlZk7tOvRFMVaKqCel8YdqvS63FWVUaaZsHaqlZEdfOQ62NLvR81rSGUZtoT4QQAJElCaaYDDd4INtZ6D/l5iIiI+sKA0ikUM9DoC8MwBTS1Z7XYLAqihglVlrC3PdTZSiIhEjMQMwR0ISAB6DqP73vNzDQFFElCRDfg1FT4wzHUtAX7LEdbRwz+iI60PlomJAiYQiBq9B1AXDYVvnAMwag+yFffRzmCMZhCQFN7hyFFliBJ8bISERENBQaUTlZVhs2qQAKgmz0jhm4IKLIE3RRwaypEZwRRZBmyFK9Egd7BpIskAaaIHyOqm1AVGRl2a5/72iwyrIqMcPcOLd2PBUDpZ3RQVDehyjKs6qG/rV0hzTB7vyoh4kHJZuHHh4iIhgbPMJ0siowZ5ZmJfiddJ2YhBPzhGFyaCosiYd6YHDisCryhGDKcFqTZLbBZFEACTPPLPijdaaoMAXQ+TsfkknQUpNv7LEeOW8PYfDfqfWGY3cKBEAJRQ8Bts0DZ9wk672/piGBSsSdxeepQjM1zI8NhQaM/3Ou+Bn8EiiQhP812yM9DRETUF3aS7eZrY3Kwud6PVzfUo6YtCE2JBwvNIsNmia9CfFplAXRT4J0tTUizqyhKt6PZF0YwasBAPPHt2+hginiAaA3GUJbpwNVfG9FvGSRJwikT8lHnDWFLgx8euwWyLMEbjCHHbcW4fDe2NwUgSRIyHBZInZeOalpDyHFrmDMqOyl1keG04uTxeXj+k72obulAtktDzDCxqc6HBl8EeW4Nj63ehQmFHpw4NhelWRx2TEREycNhxvsIRnWs3NaM/2yoQ3VLEA6rjNJMJ+aPzcHc0TlwaSqiuom3Njdg9Y4WtASiaPCH0egLoz0URTDcGVQkIM1mQV6ahqgh4LFbMHtkNr4xvRhlWc4DlqPRF8bqnS1YX9MO0xQYm+/GrJHZKPDY8O/1tVhX3QpfKAZJkiB3dlw999gijMlzJ60uTFPgw6pWvLetCbtbg9jeGEAoaqA824FRuS5EdYFGfxj5aTZcMbdiQK+LiIiOXoM5fzOg7Ec4ZiAUNeDQlD47i3ZEdNR5w5CkeEfaqqYA6rxhCAhMLcnA6CSEBSEEhADkfS7r1HvD2NEUQMwwkeWMXxZKRt+TvsQME89/vAcvfVaHcfnuHpeQhBDY2uDHtLJM/NfXKoZ09lwiIjqycR6UJLFZlHj/kn44NRWjcr+cj6Son34lh0KSJPR1zs/32JDvOTx9QFRZws7mDuS4tF79WyRJQr7Hji0NfjT4IoetTERE9NXGTrJ0QDFDIBDW+w1rdouCSMxIyvBmIiIigAGFBsCiSEh3WtHRTwDpiOiwW5WkTbFPRETEgEIHJEkSZlZkIqKbiVlzuximQL0vjAmFHuS4tWEqIRERfdWwDwoNyIzyTGyu82NddRscVgVum4qwbqKtI4rybEdS1v8hIiLqwoBCA2KzKLjk+DKMynVh9c4W+EIxaKqM0ycWYPaoLOS62TmWiIiShwGlD7phoqYtiJaOKNI0C0bmOKEoh+9qmBACrR1RRA0THrslKTPDJoPdquDEcbn42uhsBGMGrIq831FOREREBys1znwpQgiBj3e34ak1u/H5Xh/8ER2qLKE8y4lvzCjGaRMKEvOR+MMxbNjjxY6mAGRJwohsB17fWId/fVyLcMyAIknIcVmhKDJkSUJZlgOnVuYjN82Gz2q88IZiKMq049QJ+SjO+HIW1q0Nfry7tQlbG/zQDQGXTcWMskycMDYHnj4WEBwOqiIj7TAGNiIiOvpworZu3t/ehD+9uQ172kLQVBlOq4qoacIbjMFuVXDF3ApcMrMM9b4w/r66GjubOiDLgBDA8k0NiPWxsF4XRQJURYIiSbBZFVg6T/A5Lg03njwGJx+Th8/2tOMfH1TDF9aR49ZgVWT4wzraglFMKEzDd+ZWII0jZYiI6AjFidoOgj8cw7Pr9qLeG0aGwwqnFq8aBwCPzYJabxj/+mgPZo/Ixisb6rCzqQMjc5xQFRkvfLJnv+EEiK/HE9EFJAi4NBWlmQ6YpkCtN4x7l2/FyFwHXvq0FsGYgdG5rsSMrE5NRabTio21Pqze3oxTKguGuiqIiIiGHdvpO22q9WFnUwCyLMFh7dmvomthvuZABP/+dC+2NwVQnGGH2tkKUt0aOuDxRbf/D0R1hGMGVEVGoceGpkAEj3+wG7XtYRSnO3pNF29VZaTZLfiwqhUR3eh1bCIioq8aBpRO3lAMUUNAleU+15PRVAVCANUtQUR1M9HC8mX0GBgJgGHGZ2cFkAg5e9pCMIXodz0dt6YiENHREWFAISKirz4GlE42iwJFBsx+uuQYnZdwMhwWyJKEqG523jO4xfEE4isdK50hyDBNCBFf+Vh0e559RXQTFkWGzcK3jIiIvvp4tus0Nt+NAo8duiG6hY8vtYeicNlUnDWpEIXpNuxpD6Krf3GGfXBdeewWBXarAiEEmv1RuDQV504tRKbDgiZ/pNf+phBo7ohgckl6ygw5JiIiGkoMKJ3y0mxYeEweHJqCpkAEHZEYhBAwDBMN3hAiMRNfG52NSSXpOGtyIRxWFVsb/Gj0hTF3VPaAn6ervaXJH0F1axAmBM47tgizRmZj/thcBCI6attD0M14SApGdWxvDKDQY8ecQTwPERHRkYw/x7s5Z0oRTFPg2Y/3oLY9jKZAFEB8FM/pk/Jw7YmjYFFkTCpOh1NTsXpHC7bU+5Du1PDjhaPx+JrdqPP2bAGRASgy4LCqyHBaYLcoyHFp6IgaKM504PTKAiw8Jg+SJGHB+DwosoQVW5tQ1dQBgfhCfWPy3DhnSiGK0u2Hv1KIiIiGAedB6UOjL4x11W2o9YbgtKqYMyobJZmOPveNGSYkfNnZ1TQF/rZ6F97f1oTReW7EDIFwzISqAHvbQzhhTC4uOb5sv8/vD8ewo6kDUd1EhsOCETkuKPLg+roQERGlGs6Dcohy02w4beLA5huxdJtRtSOiY3O9Hy5NhdWiYFtjALlp8TVqar0R5HvsOGF0zgGP6bZZMKUk/aDKTkRE9FXAgJIkn9a044X18YneACAc06EbAr5QDG5bvBVm3pgclGb13RJDREREX2JASYLdLUE8uWY3glEDI7Ljs8tGdRPVrR1Id1jw/XmjUJjB/iNEREQDxVE8SbB2VwvaglGUZzkSfVGsqoyR2S40+iPY2ujf7+MNU6CtIwp/OHY4iktERJTy2IKSBDubO+CyqmgKRFDvDSMYNeC2qSj02KHKMna3Bvt8nBACH1W3YeW2ZtR5Q1BkCeML0jB/TC4vBRER0VGNASUJrIqE3a1B+MIxGGZ8WHFzIILa9hDcNgtsFgXtwSjqfWGYJpDhtCA/zYa3NjfihfW1AASynBp0w8T725uxozGAK+ZWoCzLOdwvjYiIaFgwoOwjHDOwud6PnU0BxAwTOW4NlUUe5Lpt/T6mKMOJ6pbdiOoG2sNfrpVjVyUoEmCVgRc+roGsSAhFDHREDbhsKvxhHSOyXRiT5048JtNpxZYGP97a3IjLZ5f3uS7Q4SaEQCCiQwBwdc5kGzVMqLKUuKRFRESUTAwo3exuCeLptbuxs7kDrR1RRGImLKqEsiwHFo7Pw8Jj8iHvMx9JMKrjs92taOyc1K27kB6fYua9Ha09tssAJAkwBbC3LYRmfxgzR2RB6VyoMNdtw+Z6P7yhGNId1iF7vQcihMAnu9vxwid7sbneB9MUcGoqrBYZEiS4bCpOHJuDOaNykOkcvnISEdFXT9IDypIlS/Dcc89h8+bNsNvtmD17Nu666y6MHTs2sY8QAnfccQceeeQRtLW1YebMmXjggQcwYcKEZBdnwJr8Efxt9S5sbwpgd0sHWgJRGEJAAlDTGkKDNwKrKuPEcXkAgDpvCMs2NWD1jma8+nnDoJ7LBCCL+MKB4ZiBjXV+SJKEWSPjU9lbFAmhqImo0XtNoMNp+aYG/M/ybWjtiMKiAP6wjkDEACDgtlng0lSs392OD3e24gcnj95vKxMREdFgJL19fsWKFbj22mvxwQcfYNmyZdB1HYsWLUJHR0din7vvvhv33HMP7r//fqxduxb5+flYuHAh/P79j3YZSmt3taC6tQN7WjtQ74tAVSS4NRWaRYEvHMPmeh/e2FiPQERHezCKpe9XYeW2Zqzf3X5Qz9cVPYSIB7btjQF4Q/FWmNaOKLLdGjKGsfWkJRDBX97bifZgFEXpNjitKqK6gCwJSJAQiRlIs6kABFZub8ZL62uHraxERPTVk/SA8tprr+Hyyy/HhAkTMHnyZCxduhS7d+/GunXrAMRPxvfeey9uu+02nHfeeaisrMRjjz2GYDCIJ554ItnFGZCobmLtrjbohkCTPwq7RYbNokCWJWiqDJemIBjVsanOjy31PnxS047qliAqsp2o8/VefXigJACGAIQpENZN7GgKoMkfQcwQmDsqp8cstYfb6h0t2NseQqbTCkWW0BaKQTdNWBQFVlVGzIz3S8lyajBNgfe3N6M5cPB1QURE1N2QnwG9Xi8AIDMzEwBQVVWF+vp6LFq0KLGPpmmYN28eVq1a1ecxIpEIfD5fj1syhWIGglEDMcOEYQpY1Z7VosoyAAmhmIFAxEC9NwRFkmCYh3YJRpLiIcUEoBsm9raFoZsmTqvMx6yRWYd07ENV7wvDMAVsFgUC8RAHdJa5sxtORDchyxIUWYIvHIMvxHlciIgoOYY0oAghcNNNN2Hu3LmorKwEANTX1wMA8vLyeuybl5eXuG9fS5YsgcfjSdxKSkqSWk5NlWHpPNFKsgTd6Ll+oikEhBCwdLaoZDisMEwBOQkjbBQJcFgU2K0qZpRn4OZFY3Hm5MJhXxzQY7dAliTEdCO+GGJneeKXpACI+AKJQggYIh5k7FZlWMtMRERfHUMaUK677jp89tlnePLJJ3vdt+/wWSFEv0Nqb731Vni93sStpqYmqeW0WRRMKkmHRZHhsakIRo1ESDE6L2XYLDJG5bowOteFScXpyHZrqPWGkW47tJOyqsiwWmRkOCy4dFZ5YnHB4Xb8iExkuaxoDcYgAKQ7OgOLEW9pUmQJHpuKtmAUEMCxZRnIT5GyExHRkW/IAsr111+PF198EW+//TaKi4sT2/Pz8wGgV2tJY2Njr1aVLpqmIS0trcct2Y4rz0S2S8OIHBfsFhltwSgafBG0dkQhS0BppgsnjM1FlktDYbodF80sRXGGHeMLPAf1fDIARZIgywLBqIE0mwVrd7Xio12tiOjGAR8/1IozHDhvajFUWcLethDMzlYSw5RgmAKaKsEf0RHRTUwo8uCcKUUpMWcLERF9NSR9mLEQAtdffz2ef/55vPPOO6ioqOhxf0VFBfLz87Fs2TJMnToVABCNRrFixQrcddddyS7OgJVnO3HB9BL8cflWKLIMh1WJX84AYLcqqMhx4NQJ+Yn9JxR6MDrXjT1tQTyyYjue+mjvgJ+rax4UCAHDlOF2qChMt2Ptrlas2dWKqSUZuOT4smG9ZCJJEr49qwwZDgte/LQWu1uDSHdYkOW0wKoqcGkq7FYF08szcOakQozIcQ1bWYmI6Ksn6QHl2muvxRNPPIF///vfcLvdiZYSj8cDu90OSZJw4403YvHixRg9ejRGjx6NxYsXw+Fw4KKLLkp2cQYlx63BbbdgdK4LUSPetyJNU+GyqYh2jrKZVJye2N+qyhiR48JxFdl4fWM9fGED+3RfAQDkuSywqRLsmgW6AfijenwWVllCpsuKWRVZsKjxMBKKGvioug0jc504aVzfLUqHi6rI+PqxxTilsgC13hCEEMj32GEYAu2hKOwWBTlujS0nRESUdEkPKA899BAAYP78+T22L126FJdffjkA4JZbbkEoFMI111yTmKjtjTfegNvtxnDaVOdDVDdxbFlGr5Pu1gY/Ptvj7RFQury9tRGaRcXkHBf8YR26Hu+joaky6v0RnDmlCN+aUYo6bximEMhwWGFVZTy8YgdyXFoinADx1hqnVcEHO1sxf0xur5lrh4PdqmDkPi0kHodlmEpDRERHgyG5xHMgkiTh9ttvx+23357spz8kHWE9PpKnjxYBTY33S+lLa0cUhimwty2MsG4gqpuIGfGRP6YAXv+8HtNKM3DS+DzYLPEw8vleLyK6CUcfl3HsVgUdER0x04Qmc2QMEREdfbjSWzeZLitMIWD2EbJCMRMFnr5HqaTbLfCHdcQMEzHdRMwwYZoi0YelPRTF0lW78OzHexIBLsNphdOqwBfWex3PF4ohL80GKxfiIyKioxTPgN1MLPIgz21DdUsHTDMeJIQQ2NseQppNxbGlGX0+Lh5cBLyhGIIxE7oZn3ytaxo3h9WCjoiOtVWt2NMWgj8cQygag9tmwYY97djZHEAkZkAIgeZABALA8SOy2LeDiIiOWlzNuJssl4YLZhTjkXer8ObmBkR0ExZFRkmmHZfNKu93pEogHENMF+hvcHCLPwKLDNR5w1j8ny+wqd6Hto745SKLImNPewhWRUaOW8OIHCdOnZCP6WV9hyEiIqKjAQPKPnxhHaaI9w1xaSqEACRIaA/G+pxMLhCO4eXP6voNJwBgAKj1RuAN65AQv+wTH2UsEDJM5Hs0FHjs0E1g3phcnDGpgK0nRER0VOMlnm68wRhe2VAHTVUwZ1QOZo3MxuxR2chxa3h7SyN2twZ77B8zTCxdWYVA9MBr8ggAgYgBYRoIRQ2EYwZ0Mz7VfZM/itw0Gwo8Nnxe60Wsr7HKRERERxEGlG62NfrRHIiiwGPvsT3LaUUgrGNrQwBAfGG/d7Y04sf/XI//Wb5tUM8RiMVXMI6ZQFg34Y+a8EcMbNjTjiyXhvr2MPa0BQ98ICIioq8wXuLpJmbEV8Lbd+oRSYoPPdY7R+c8/VEN/rZqF7Y1BnBo6xl/qaoliLw6H9LsFhgmW1CIiOjoxhaUbgrTbXBY1V5Df8MxA4osoTDdjh1NATy7bg8afGEkM0cYJrClwYdQVEeum4vuERHR0Y0BpZvSTAemlqajtj2ImpYOtHRE0OQPo6q5A+ML0jCuwI3VO1vQ6I8g0Mf8JYeqI2JAliW4bGzYIiKioxvPhN1IkoTjKrKwblcbPt3jRdQwkWa34GujsnHxzBJoqoK69viaNEPRj9WiSMhyaojoBhxWvjVERHT04lmwmz1tQTzxYTXCuoEZFRkwDMAXiaHBH8a2xg4cV6Ehy6lBAiBLSHpIyXBY4bFbOIMsEREd9Xgm7GbVjhbU+cIYk+dGXpodhRl2jMtPgymANzc3IKqbOH5kFtKdVtjU5M5ToshAttOKGRWZUBlQiIjoKMczYSfTFNi414sMu7XXJGm5bg0N3jDqvWGMzXfj1Mp8OLXkrubr1lR8bWwuZo/MSupxiYiIjkQMKN1IkgSB3tdthAAkKX6zKDL+a+4InDaxAFYlOa0omQ4Lfnb6eFw5twJuW3KDDxER0ZGIAaWTLEuYVOxBezDWuRKxiK9ObJio94ZQlO5IrGZssyi4fsEoFKXbYVMlDDSmSJ03ID6DrEWWMK3Ug+U3nYALZpQynBAREXViJ9lu5ozKxgc7mvHvT/ciENZhmAKyLKHAY8P8sblQus3glu2yYUJhGva2h/poc+lb1xo8qgQoigyHVcH500qQ6Rr4vCe6YWJLgx+ban0IRHTkujVMLklHcYZjUK+ViIgolTGgdArHDLy6oRbLNjWgPaQnQociAYYp8NJndUizW7DwmLz4pSAhUJhuQ3SQQ3kEAF0AMAV008T/rtwJQwhcPLPsgAsERnQDz3y0Bx/ubIFuCqiyhKhuYsXWJpwzpQhzRmUf1GsnIiJKNbzE0+k/G+rw5xU74Q3rsCoSnFYZNlWGRZEQM0x8UevFKxvqUNXcAQD4qLoN//p470E/35hcF8bmuRHVBZau3IWPqtsO+Jj3tjZh5bZm5Lg1jMlzY0SOC2Pz3RACeOGTvYmyERERHekYUAC0BCJ4e3MD2oIxyJIEiyJBliSoSrzXiCpL6Ijq2NXcgU9r2mGYAm990Yj2jtjBP2cwAkWWUeCxwR/R8cqG2v3uH9ENfLCzFS5N7dFXRZLiU/D7wjo+rm496PIQERGlEgYUAA2+CBq8EZhCQJGRuNQiIT5yJ77mTvxyyp72ELyhGGraOg5pocBgxIg/hyTBosjY0bj/1g9vMIa2YBQeR98daZ1WBbtbQ4dQIiIiotTBgAJAs8jQOideE/uMyenq2ArE/8NuUWBVZWhJmEwtZpgA4qOFDNPEtgY/AhEdQgj4wzG0dUQRjsWDjEWRocpS52P6PpbdqhxymYiIiFIBO8kCKMt0oLI4HZ/u8aIjakASUqKTrAAgy4BVleFxWOC2qXh/ezOsFgWqDOgH2YzijxjYUNMORQZiJhCJGbj0/z6Ezaog22mFU1Pg1CzIcFpxfEUWppdnYGxBGtbsbIUiSWjwhdHkj8AQAnaLAsMUGF/gTlaV9EsIgb3tIfhCOjSLjNJMByyc+faIJoQ4YAdtIqLDjQEFgKrIWDA+D698Vgt/xEBkn5E5MUNAN0xsrffht6/4ETVNmKY46HCSOK4AOhtI4A3r8HaukFzVHAQAaIoEj92CNTtakJduR1G6HdWtAXy8uxWaRYHdokA3TOyNGPDYLfh8jxdTSzOQlsT5VLzBGD6uacOmWh9aOyJoD8YQjhkwBWBVZBRn2nHSuDwcW5rOk9wQiBkmNtf5sa3Rj6huojTLgQyHFdsaAmjwh5Fut6CyyIOxeW7I8sDrPxwz8NGuNqzd1YrWjiiyXFYcV5GJaWUZ0FS2xBHR8GNAARCM6nhvWxNCXWmhD1ETaO2IB4ghWMi4TxFDoDUYRVswhj3tIWx3WKAbAhHdhBACmiLDYVUxIseF4nQ7Pt3jhX3dHnxndnlSwkK9N4xHV1WhqrkDhimws6kDgUgMWS4N08syYLeoqGkN4fEPqqEbJmaO4DT9yRSKGnhq7W6sq26DbghIEtAciMAf1pGXZoPHbkHMMLFyWzPmj83B2VOKeszV059wzMDfV1fj491tsCoyHJqCnU0d2Frvx9Z6Py6cWcqQQkTDjm3zADbs8WLV9mY0BfY/Kkfg8IWTLoYZn4fFMAUCYR2qImNkjgMOq4qSTAfmjMrGhEIPPA4rijPs2LCnHbtagof8vEIIvLA+PnR5VK4LMSPeO6cs04GYbmJzvR+aRUZFthMA8NrGegSj+iE/L33p3a2N+GBnC/LTbBib70a+x4ZAWIcvFEMkZqA8y4ExeW54HBa8tbkRn+5pH9BxP9jZgnW7W1GS4UB5thO5bhsqsp0oTLfjw6pWfLTrwEPeiYiGGgMKgI93t2NPe+qOgJElwBQC4ZgJwzBgVVU4rCq8oRis6pdvoUtTEYwa2FznO+Tn3NsewtYGPwo9dkR1E03+MJyaClmW4bFb0B6MobUjCgAo8NjQ4AtjS73/kJ+X4iK6gQ+rWpFms8CpxRs6G31hRAwTuW4NbcEovKF4oM5wWGEK4KNdBx5mbpoCa6paYbeovTpVOzUVFkXGmqpWCHG4ozgRUU8MKABaOyKIRPu/vDPspK7WG9E5tFnAqsqIxAzEunWEkSQJiiQhEDn0lgxfSEcoasClqYjqJnRTwNI50klVZAgRv9QExEcYCYGkPC/FdUQMBCI6XNqXV2FDMQOKJEGzKNBNkRjhBQBOTUGTP3LA40YNE+3BGJz9jPhyaSpaOyIwTAYUIhpeDCgAPHYLNEsKV0XnuULq/B8QH25sUeXOyeS+ZAgBh/XQuxa5NBU2i4Jg1EgMcdY7Ow/rpglJkhKrOeuGCUlCUp6X4hzWeCfoYLfgbFMVmEIgqhtQZQnWbv1EglEDmU7tgMe1KDJcNqXf/lbBqI40u2VAfVmIiIZSCp+VD59jSzNQmG4f7mL0yxSALEnQLPFAohsmwrqJonQ7FPnLt7AjosNmUTA239XncYQQiUsx1S0dff5KNk2BXc0daO2IIN1uQU1bEErn/C+tHVHEdANtHVFoqtzZkVKgwRdBtkvD2PyhH+Z8tLBZFMwoz0RbMD4XjhAC2W4NFkVGkz+CdIcVGZ2T9vnDMQgBTC/POOBxFVnCzIosBCI6InrPkBKOGQjrBo6ryOKILCIadvzJC2BSSTpmlGdh/W7vIc0OOxQSEUIIuKwqIIAGXxilWU6UZjkT+0V0A7tbgzi2LAMjsnsHlEZ/GK98VoeNtT4EozosioyyLCcWHpOHyiIPAGBXcwde+qwWOxoDCOsmIjEDVc2BROdLfyiGem8YqiIhx2XFqu3NUFUZeWkazp5S0eNyBB26+eNy8UW9D+9va0Z7KAYh4p2lTREPo+9ta4IkxYein3xMHqaUpA/ouDNHZGFznR+f7W2HS4v3Z+qI6OiI6phamoHjyjOH9oUREQ0AzyiIX864aGYpHnl353AXpZeu6fYtqoxstxWj8lxo64jBqshoCUSgyjL84RhipsDEIg++Ob2k13wYbR1RPPr+LmxvDCDfY0NumoZIzMSOpgDqVodw2exypDusWPp+FRr8ERSl2+G0Kvi81otgND6kOd1ugW6YMMI6hEB8QjtJAgwTBZINxRmp2wJ1pPKFYghGDVhVGRkOKwAgrBvwhmKJEV2KLCHdbkFRun3AE+a5NBWXzSnHqu3NWLurFYGIjmy3hjNHFOD4EVmckZiIUgIDSqdtdb4BDSEekWVHVUvosAw3dlpl2C0qLKoEp1VFtsuG2SOyMaMiCx9Xt2LDXh8M08ToPDdmlGdicomnz34ga3a1YntjAKNzXVA7T2KqJmNEthM7mgJ484tG5Lg01PnC8Qm/JAmBsI56bxi5bg0R3YDc+Uu9PNuJjrCBYExHZVE6yjLt2NkcxFubG1GR7eSlgSRatqkBe9tCOK4iC4osQTdNrNreDK8APA4L5ozKhipLqPOG8cqGOozOc6NogJcqXZqKRRPycdK4XEQNE5qqsN8JEaUUBpROD767Y0D7BaPmkIUTqxLvAhvr7BuS7rAi32ODIklo7YhCkoH1NV6cPqkQ/29aCc47Nt7kr+7nl7MQAuuq2+C2qb32kyQJ+R47tjX4saMxgGynBrkzYLR0RBDRTWQ5rbAoMna3dsBjt0CVZXgcMqKBeMuKRVWQm6Zha4MfLR1RZLsO3FGTDqytI4pNdT7kpdkSwaE1EEUgEp+kzR/W0dIRRX6aDQUeG7Y0+PFFrW/AAaWLqsj7/fwQEQ0XfjN1ag4ceIgmALQFo0NWBt0UiBkConNGOAmAKsuJVglFkhA1zMTwUkmSDnhyMQUQiur9zgyqqTIiuomIbkDrNqeKbor4mCFJ6vz1LhLhBYh/cLqClKbKiBlmYtgxHbqwHh9C3v09iXX2P4nPfRNffgGIfw4kSAjuZyZkIqIjDQNKp7JMx4D2G8x6J4OlylK3OU+QCBWGKQBJQswQyHJaB7XWjiJLKPDY4Q/3PUuuLxRDmt2CHLcGX7d97Jb4CB3TFIjoBmwWBUbn5F1CxOdjcVji5fOFdbhtFnjsyVsD6GiXbrcizW7p8Z44rApUWUIgEoMsS4nLeV1BJYetV0T0FcKA0smhDezkKg9h7xNZArpP4Gl0znnR1hGFRZZgtyiYOzq7x+yxAzGjIhOmiIeR7mKGiUZ/BFNL0zF/bC46IkZifoxslwa3zYK2UBT+cAw5Li0+GVs4Bl9Yh8OidHa2jZdvWlkGR/Ekkd2qYGZFJryhGHyhKDoiOhRJQrrDiiZ/FC5NhceuIhjVsaMpgLIsByqL0oa72EREScMzSqe9bQNbv6YjNnQBJax/eWxJig8nbg5E4LFbUVnkwWkT8zF7ZPagjzu1JB07Rmdj5fZmNAUicGkqIrqJYFTHuAI3TqssgN2iYEdTAJ/sboemynBqKjKdFuxpCyJmmIjpJkKxeKCxW2RUFnlQ7w1DNwWmlqZjwfi8ZFYFAThxXC4+r/XizS8a4QvFIBBfQTo3TUNemobtjR3QVBnjCtLw/44thjuJq1gTEQ03BhTEJ6hqCQxd35LBkhBv2nLbVKTbrchL03DaxAKcWpl/UMdTFRnnTyvG6DwX1u5qQ117CFkuK6aXZWJaeUbiktGls8oxLr8VH1a1oD0Yg82ioMBjAwCYADJEfBZZ3RTQVBnjC9IwtTQDU0rSOTR1CFQ1d6DRH0GOW0OBxwYJ8T5FmkXGnFHZmFScDodVRUW2kyNwiOgrhwEFwBd1PkSN1OngKUuAzSJDkWRYZCDbZcP725sxZ1TWQf9KVhUZ08oyMa0sE0KIRMdbIQS8wRgMIeCxW3DCmBx8bXQ2fKEY/vjmVmiqgpJMR2LxOEmSUNsegm6a+PrUQhSmD6zvDg2OaQq89UUj2jqiyHRY0RyIwBQCaTYVHWEdT3xQjbV5bchxazhhTA6O5SU2IkqS1o4omgMRKLKE4gx7v4Mshhq/0QBUNQUQ1Q/HzCYDYwggEDURiIZR5wN2t4eQ67Li1y8ZqMh2YlJxOqaWpidWuR2srnDyRZ0PK7c1Y3tTAEII5KfZMGtkNo6ryESDP4JGfxTF6XY0+ELY2xZG1DDQ3hFFnTeMYMzAO5ubMH9sDq4/eRRGZHOa+2Rq7ohg3e427GwMoKlzMcuuT6gQ8U7UO5uDUBUZL35ai2ll6fjpaeNR1m12YSKiwWgPRvHa5/VYX9MOfziWGGRxwpgczBqRNaSDRPrCgAKgI6ojFE3dlXj9YQP+cAiZzgAiuonP9rbjkxoPLp1VftAjZz7a1Yqn1tYgGNGR7dIgyxKqW4LY0VSNBl8YY/Jc0A0TH+xswa6WDkRiBkL7hDhvKIYXP63F2l2t+L/vzMDYPHbSTJZdTUF8vrcdzYFoouP0vhFalgCrEp/2fuW2FvzG2Ijff2MqPA72RSGiwfGHY3hs1S5srPUhx62hPMsJ3RRo9Efw1Jrd6IjoWDTh4LoZHCyO4gHQ5I8ihRpQ+lXvDaMi24nyLCc27PHi7c2NB3WcjoiOlz+rhW7EZ6HNcFoTs8RmOq1YsbUJUcNES0cUWxoCEJ2LFXYnId4XQpaAOm8YS175InEZiA7dhtp2tHfEOheKjN/2ZQgBm0WF26ZCCIFParxYtbP58BeWiI54H+1qw6Y6H0bmuJDt0qAqMmwWBaWZDjg1FW9tbkSTf2DzhSXLUR9QwjED9e2h4S7GgOxtD+ODHc1o8EXgtqlYV92GjsjgW3421/vQ2Lnmzr4yHBa0BKJ4d0sTmv1h6IaBmGGiI9azj44AENVNSJIEIYCPd7ej0Rc+2JdG3XhDMby/rRndp13rY+Fp6IZAzDChyBKsqoxQ1MAbG+sPWzmJ6KtBCIEPq1rgsKp9TmOR49bQFozhizrfYS3XUX+JJxQ1EEjhyzvdmQCaAhE0d8TnwShKt6Mjog+6L0ogYkAI9JqFNhjVsbnOj6rmAOrag6jzhmGK+HwpfTEEYBjxM2c4aqA1GEOeh4sGDlQ4ZuDDqlasq25DKKpjbL4bs0dmQ5El+CI6hCmgSPFw0lfbVNeEfkD8vYzoJto6oj06QRMRHUjMEPCHdTj6GY0pSxJkCQf1g/hQHPUBxW79cobUI0GmwwJJklHb2Vphswy+d7VLUyBJ8RlIu0KKbpj4bI8XzYEIZFmCx2HBnnYJQgioipSY1r4/phDQFJ4UB0o3TDy9tgard7ZAU2VYFRnLNjVg414fvjGjBGmdodMUgCKh30uQXTVudIbIDIeV4YSIBsWiSHDbVDT4+r6EYwoBUwg4DvNIwaP+Eo9FkWEeQUuY6J2/ppXONXLqD+Kyytj8NOS4NdR6v3xsUyCClkAUNosCmyohqgu4NBWKLCFiHDjAWRUZDYf5+uSRbHO9Hx/takVRuh3lWU4UptsxJs+NWm8IH1e34biKTCiyFG8hkeIhZV+qHF+LKb4cgQm7VcHCCZwwj4gGR5IkHFeRiWBU77PFvNkfQbrDivEFh3e05lHfgtLaEUXEOHISSksgAquqoNBjg1NTUecNY0ze4D40Lk3FmZMK8dSa3djWGEC2y4p6bxiBSAzBqARVltDk74CJ+Iy25gCmiNFUCY39pG/qbXdrEFHD7DF3iSxJyHRasbneh7mjspHe2R+ovzUYFVlCJKYjqscv6Uwu9hzUTMPJtqctiLW72rC90Q9NlTG5JAPTyzIOelg8EQ296eWZ+LTGiy/qfMh1a/A4LDCM+CieqGHirEmFyHXbDmuZjvpvjHgHwyNjFlQZgMduweg8N/LSbNjVEuxzdMdAzCjPhMOq4L1tzdjZFEA4Fu8Ma1UV2Cwy/OF4/xxTCKgyYJh994OQEB9hYlGVwz5G/kjW38yvpglYFQnlWU6MyXNjk+lFe1DvVfdds8pGjXiz65QSD249fTzSHdYhL/v+bK734fHV1WjyR+CyqdANgU21PmzY48Vls8s4HT9RikqzWXD57HK8+nkdPt3jxa7mDsiShHyPDSeMycGcYfjxc9QHlAyHBdPKMrD8i4Mbsns4SIiHA4/DgjmjcmCzKPCGYnBaFZQfwsRcEwo9OKYgDe3BGF76rBYPvbMDWU4rnJqKtlAMImrAqsqI6iYsioRo56UeGfEOu4oUv3YZ1QUcVhWlA1wRmoDRuS44rSqaAxFkd65CHDNMtAWjOG1iAcqznZBlCR1R88sPAOL/KQFw2RQcPyIThelOnDAmGzPKM4f95B8zTLy4vhZtwSjG5rsTfWEiuoHP9rZj1Q4XTjnM8ygQ0cBlOK24aGYZFk2IoDkQgSpLKM5wHFRfx2Q46gOKJEk4rbIAf3h9S8rOhSIAKADG5rtgsygIRHTUtocwZ1Q2ijMObdSMJEnIcFoR003YLTJaO6IIxwwYhgkhBKK6gGkC3X/Dd11xMAQg9Hgn2myXhnGH+frkkawi24mTxuVi+RcNaOmIJkLf+II0zB+Tg46Ijm0NfkT13sO7BYBwzMR3Zo/ArFHDf0mny67mDtS0BlGc4ejRUVdTFbg1FR/tasXC8XlsaSNKcdkuLfHDaTgd9QEFAMqznVAVQE/h0cY2C+C0qthc74dNlXFcRSbOO7YoKSM2ttT78camBgQ7p1NvDsRDigQgdoD+J5oqIS/NhvEF7mFbr+FIJEkSTp9YgFF5LnxR60MoZqA8y4lJJelwaSqe+LC63x71QPzSzuMfVuP4kVkpM2onHDMRM0xofcyjoKkKQlEDuilgZUAhogFgQEG8CTqVp0KRAEBSUJRux6yR2RiV68KIHFdSVrBt9IXxjw+rEdUN2C0qctxWRHQTu1o64A3tv1I0VUKmS0NOmobKovRDLsvRRpYljMtPw7j8nksECCHw2uf1ffb56e797U1oCUSR7R7+XzpAfDInt82C9lAMGfv0hfGGYqgsSoOFQ9GJaICO+mHGALCp1ofUWcu4b6GYgfe2N6Mg3Y7Ree6khJPWjij+vnoXVu9ogRDxWUlbAlFoqgx7H7+C9+XuHJUR0wVmlGcccnkorikQwed72w+4X3vIwCc1bUNfoAHKS9MwuSQd9d4wfOEYhBAwTYHa9hBURcKskdkp09pDRKmPLSiID4tMZQLxFWxbO6J4dt0elGU6kOE8tNEaWxv8ePLD3Vi1owXBqA5ZUmEKgZaOCIIxA5H+xrZ2E46Z8NitKMl0YESO65DKQ1/yhXSED3RtrdPfV+9CSyCKhcfkIWuYrxlLkoSvTy1C1DCxYY8Xde3xeXYynRacMbEIk4s9w1o+IjqyMKAAOFImkhWGiUZ/GJvqfJhzCJ0j24NRPLlmN5r8ERRn2LGrxUS6I75gYHswimDMhFtT0XaASzx5HhvG5LkZTpLMqshwWBUEBxBSVFnBW5sbUdsewn+dMAJpwzySx6Wp+M7scuxqCaKuPQSLKmNUjuuQAzURHX14iQfxdQiOBEKSEI4ah7wewqd7vKhtD6Ei24m8NBsUWUIoZnSO6NGgKRKkAXwySjLsEAI4toyXd5KpMN2GuaOyDrif2yqhPNuBUbkubGnw45Pd7UNfuAGQJAkV2U7MHhUf/sxwQkQHgwEFwM7mjuEuwoAYQiAUM5HlOrQv/C31PlgVGbIsIdtlRUWWE+GYgZZAFO3BKCK6QEQXyHNb0V+PAbtFRnMgijH5LkwtTT+k8lBPqiLjnKnFfU5v392ovDS4NBUWRYamKvh8r/fwFJCI6DAY1oDy4IMPoqKiAjabDdOmTcN77703LOUwBjKX+zBSJcRnczUEctM0HFNwaNfyhYhPqw7Ef+2OzXdjWlkGSjPtyHZpKMtyoDTTgcqidBxfkQGnVUoEFUUCPHYV6Q4LxuS5cdms8mG/rPBVNKM8E8eWZsDSz19omk3GqNwvJ0OTJUBP8c8xEdFgDFsflKeffho33ngjHnzwQcyZMwd//vOfcdppp2HTpk0oLS09rGUZl58GmwKEU3BJHlUC5M6p5tPsKr41owT2fpbEHqjyLAfWVbdBiPgaLpIkIddtS6yzsL0xgNw0DU3+CEblujCpJAMtgQgMIRKLFDb6I/jmjJJh75j5VeXUVCyakA9FkRDTDdS0BhHWDRgGkO6wIMP55URKpikQjBoYN8g1mYiIUtmwtaDcc889uPLKK/Ff//VfGD9+PO69916UlJTgoYce6rVvJBKBz+frcUum4yoyMaEo7cA7HmY2VYbLpkKWZNitCs6cUohZSVgPYXJJBrJcVuxpC0Hs00O4LRiFLAOnVeZjVK4Lu1ri6zEUZThQmhnvs+IL6xiT50ZlEUdlDBVJkjB/bA7KMh0o8Dhw2sQCnDu1BGXZTugmkOvWoCoSOiI6tjcFUJxhx7FlmcNdbCKipBmWgBKNRrFu3TosWrSox/ZFixZh1apVvfZfsmQJPB5P4lZSUpLU8hSm23H72ROhptAUDbIUX0k4agjYLDK+Njob3z6+PCnzn+R7bDh3ajFURcKWBj/qfWE0+SPY1hhAezCGBeNyMb0sExceV4oxeW5Ut3RgS4MfWxv82NHUgeIMOy6aWcrVaYfY6Dw3vj2rHOU5TnhDOtqCUUwuTseJ43KR4bRie2MAzYEIxhek4bLZ5chJkQnbiIiSQRL7/oQ+DGpra1FUVIT3338fs2fPTmxfvHgxHnvsMWzZsqXH/pFIBJHIl9N++3w+lJSUwOv1Ii0teS0f//feTvz21S/6nN6923ptQ0IC4LDKUBUZhR4bZFmCbgpkOKw4+Zg8nHJMPkqSvBjfzqYA1lS1YmOtDwICZZlOzKjIxKQiT2K9lFDUwMZaL6qaO2AKgZJMByYWeYZ9YbqjiW6YqG0PQzdN5HtssFsU1PvCaO2Iwtm5SCPXtyGiI4HP54PH4xnQ+XtYfwLvO6tkV5+IfWmaBk0b+l+HV8ytQIbTgj+v2Ik9bUFEYiYgSZAlAbemQlFkhKImOiJ6YtG2Q2WRAJtVxaRiDyyKhJJMB245dRxaO6KIGSbS7JZE35BkG5ETnzLfMAVMIWBRejeo2a0KppdnYno5Lx8MF1WRUZrVM5wWeOwo8BzaQpFERKlsWAJKdnY2FEVBfX19j+2NjY3Iy8sbjiIBiAem844twdmTi7C53o+q5gDWVbfhk93taO6IQhICRbl2WBQJ9d4IGv1hhAexBPK+rTCaKiPLaUV5lgPpDgs0VcHZU4rgtlkOawuFIktQ+h1QTEREdPgNS0CxWq2YNm0ali1bhnPPPTexfdmyZTjnnHOGo0g9qIqMyiIPKos8OGVCAaqaO1DvC8GiyCjLcsJhkfGfDfX4uLoVn+1px/am/U+Vn2VXoCgK/BEdpilgtchwWFQ4NRWZTisynFaUZzuxYHweppakH54XSURElMKG7RLPTTfdhG9/+9uYPn06Zs2ahUceeQS7d+/G9773veEqUp+sqoyx+W6Mze85hPOS48uw8Jg81LQGUdXcgVc21OKDHc3omh3eogDlmQ4cW5YJj8OCmC7gcVgwKseFYwrcyHFraOmIIRDRYbMoKMty9HmJhYiI6Gg0bAHlm9/8JlpaWvDrX/8adXV1qKysxCuvvIKysrLhKtKg5aXZkJdmw/TyTHxjegkiMQN72uN9V9JsFhSm2/fbedFt5xTgREREfRmWUTyHajC9gImIiCg1DOb8zWsKRERElHIYUIiIiCjlMKAQERFRymFAISIiopTDgEJEREQphwGFiIiIUg4DChEREaUcBhQiIiJKOcO6mvHB6ppbzufzDXNJiIiIaKC6ztsDmSP2iAwofr8fAFBSUjLMJSEiIqLB8vv98Hg8+93niJzq3jRN1NbWwu12Q5L6X+tmsHw+H0pKSlBTU8Mp9IcI63josY4PD9bz0GMdD73DXcdCCPj9fhQWFkKW99/L5IhsQZFlGcXFxUN2/LS0NP4xDDHW8dBjHR8erOehxzoeeoezjg/UctKFnWSJiIgo5TCgEBERUcphQOlG0zT86le/gqZpw12UryzW8dBjHR8erOehxzoeeqlcx0dkJ1kiIiL6amMLChEREaUcBhQiIiJKOQwoRERElHIYUIiIiCjlMKAQERFRymFA6fTggw+ioqICNpsN06ZNw3vvvTfcRTpiLFmyBDNmzIDb7UZubi6+/vWvY8uWLT32EULg9ttvR2FhIex2O+bPn4+NGzf22CcSieD6669HdnY2nE4nzj77bOzZs+dwvpQjxpIlSyBJEm688cbENtbxodu7dy8uueQSZGVlweFwYMqUKVi3bl3iftbxodN1HT//+c9RUVEBu92OESNG4Ne//jVM00zsw3oenHfffRdnnXUWCgsLIUkSXnjhhR73J6s+29ra8O1vfxsejwcejwff/va30d7ePnQvTJB46qmnhMViEX/5y1/Epk2bxA033CCcTqeorq4e7qIdEU455RSxdOlS8fnnn4v169eLM844Q5SWlopAIJDY57e//a1wu93i2WefFRs2bBDf/OY3RUFBgfD5fIl9vve974mioiKxbNky8fHHH4sTTzxRTJ48Wei6PhwvK2WtWbNGlJeXi0mTJokbbrghsZ11fGhaW1tFWVmZuPzyy8WHH34oqqqqxPLly8X27dsT+7COD91vfvMbkZWVJV5++WVRVVUlnnnmGeFyucS9996b2If1PDivvPKKuO2228Szzz4rAIjnn3++x/3Jqs9TTz1VVFZWilWrVolVq1aJyspKceaZZw7Z62JAEUIcd9xx4nvf+16PbePGjRM//elPh6lER7bGxkYBQKxYsUIIIYRpmiI/P1/89re/TewTDoeFx+MRDz/8sBBCiPb2dmGxWMRTTz2V2Gfv3r1ClmXx2muvHd4XkML8fr8YPXq0WLZsmZg3b14ioLCOD91PfvITMXfu3H7vZx0nxxlnnCGuuOKKHtvOO+88cckllwghWM+Hat+Akqz63LRpkwAgPvjgg8Q+q1evFgDE5s2bh+S1HPWXeKLRKNatW4dFixb12L5o0SKsWrVqmEp1ZPN6vQCAzMxMAEBVVRXq6+t71LGmaZg3b16ijtetW4dYLNZjn8LCQlRWVvJ96Obaa6/FGWecgZNPPrnHdtbxoXvxxRcxffp0fOMb30Bubi6mTp2Kv/zlL4n7WcfJMXfuXLz55pvYunUrAODTTz/FypUrcfrppwNgPSdbsupz9erV8Hg8mDlzZmKf448/Hh6PZ8jq/IhczTiZmpubYRgG8vLyemzPy8tDfX39MJXqyCWEwE033YS5c+eisrISABL12FcdV1dXJ/axWq3IyMjotQ/fh7innnoKH3/8MdauXdvrPtbxodu5cyceeugh3HTTTfjZz36GNWvW4Ac/+AE0TcOll17KOk6Sn/zkJ/B6vRg3bhwURYFhGLjzzjtx4YUXAuBnOdmSVZ/19fXIzc3tdfzc3Nwhq/OjPqB0kSSpx7+FEL220YFdd911+Oyzz7By5cpe9x1MHfN9iKupqcENN9yAN954Azabrd/9WMcHzzRNTJ8+HYsXLwYATJ06FRs3bsRDDz2ESy+9NLEf6/jQPP3003j88cfxxBNPYMKECVi/fj1uvPFGFBYW4rLLLkvsx3pOrmTUZ1/7D2WdH/WXeLKzs6EoSq8E2NjY2Ctx0v5df/31ePHFF/H222+juLg4sT0/Px8A9lvH+fn5iEajaGtr63efo9m6devQ2NiIadOmQVVVqKqKFStW4E9/+hNUVU3UEev44BUUFOCYY47psW38+PHYvXs3AH6Ok+XHP/4xfvrTn+Jb3/oWJk6ciG9/+9v44Q9/iCVLlgBgPSdbsuozPz8fDQ0NvY7f1NQ0ZHV+1AcUq9WKadOmYdmyZT22L1u2DLNnzx6mUh1ZhBC47rrr8Nxzz+Gtt95CRUVFj/srKiqQn5/fo46j0ShWrFiRqONp06bBYrH02Keurg6ff/453wcACxYswIYNG7B+/frEbfr06bj44ouxfv16jBgxgnV8iObMmdNrePzWrVtRVlYGgJ/jZAkGg5DlnqceRVESw4xZz8mVrPqcNWsWvF4v1qxZk9jnww8/hNfrHbo6H5Kut0eYrmHG//d//yc2bdokbrzxRuF0OsWuXbuGu2hHhO9///vC4/GId955R9TV1SVuwWAwsc9vf/tb4fF4xHPPPSc2bNggLrzwwj6HuRUXF4vly5eLjz/+WJx00klH7bDBgeg+ikcI1vGhWrNmjVBVVdx5551i27Zt4h//+IdwOBzi8ccfT+zDOj50l112mSgqKkoMM37uuedEdna2uOWWWxL7sJ4Hx+/3i08++UR88sknAoC45557xCeffJKYKiNZ9XnqqaeKSZMmidWrV4vVq1eLiRMncpjx4fDAAw+IsrIyYbVaxbHHHpsYIksHBqDP29KlSxP7mKYpfvWrX4n8/HyhaZo44YQTxIYNG3ocJxQKieuuu05kZmYKu90uzjzzTLF79+7D/GqOHPsGFNbxoXvppZdEZWWl0DRNjBs3TjzyyCM97mcdHzqfzyduuOEGUVpaKmw2mxgxYoS47bbbRCQSSezDeh6ct99+u8/v4Msuu0wIkbz6bGlpERdffLFwu93C7XaLiy++WLS1tQ3Z65KEEGJo2maIiIiIDs5R3weFiIiIUg8DChEREaUcBhQiIiJKOQwoRERElHIYUIiIiCjlMKAQERFRymFAISIiopTDgEJEREQphwGFiIiIUg4DChEREaUcBhQiIiJKOf8fdUdJl5YdCb0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "#bubble_size=df['Age']\n",
    "plt.scatter(df['WorkWeekHrs'],df['CodeRevHrs'],s=df['Age'],alpha=0.5)\n",
    "plt.title('Bubble plot of workweek hours, codeRevHrs and age')\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": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT *\n",
    "FROM DatabaseDesireNextYear\n",
    "\"\"\"\n",
    "\n",
    "# the read_sql_query runs the sql query and returns the data as a dataframe\n",
    "df_db = pd.read_sql_query(QUERY,conn)\n",
    "df_count=df_db['DatabaseDesireNextYear'].value_counts().rename_axis('DatabaseName').reset_index(name='Counts')\n",
    "df_top5=df_count[:5].copy()\n",
    "\n",
    "plt.pie(df_top5['Counts'],labels=df_top5['DatabaseName'],autopct='%.2f')\n",
    "plt.title('Top 5 databases to learn')\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": 14,
   "metadata": {},
   "outputs": [
    {
     "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",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT Age,WorkWeekHrs,CodeRevHrs\n",
    "FROM master\n",
    "WHERE Age BETWEEN 30 AND 35\n",
    "\"\"\"\n",
    "df_wk = pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "df_g=df_wk.groupby('Age').median()\n",
    "\n",
    "df_g.plot(kind='bar',stacked=True)\n",
    "plt.title('Median workweek hrs and CodeRevHrs in 30-35 age group')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Hours')\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": 15,
   "metadata": {},
   "outputs": [
    {
     "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",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT Age,ConvertedComp\n",
    "FROM master\n",
    "WHERE Age BETWEEN 45 AND 60\n",
    "\"\"\"\n",
    "df_ac = pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "df_gr=df_ac.groupby('Age').median()\n",
    "\n",
    "df_gr.plot(kind='line')\n",
    "plt.title('Median salary in 45-60 age group')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Salary')\n",
    "plt.show()"
   ]
  },
  {
   "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": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhYAAAGxCAYAAAA+tv8YAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAfpUlEQVR4nO3dfZDV1X348c9lWRZBdgkgz6sigVFEbAQ1GBV8qKhIaoytsUawmrZGQYGMRmsaDKmFOinjpEGYOEBaNZpa1EmMVfHZKAKCRPAhigWWGB4UdSEiLLDn90eH++u6iO5ydhfI6zWzM97vPfeec8867tvvfSqklFIAAGTQqqUXAAAcOIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBexjfvazn0WhUIhCoRBPP/10vetTSvHFL34xCoVCDB8+vMH3P3z48EbdLiLi5ptvLq6tUChEq1atokePHnHuuefG888/36j7bE671v/ee++19FLggNW6pRcA7F6HDh1i1qxZ9SLgmWeeibfffjs6dOjQqPu9/fbb93ptjzzySFRUVERtbW1UVVXFrbfeGsOHD48FCxbEcccdt9f3D+y/hAXsoy666KK4++67Y/r06VFeXl48PmvWrBg6dGhs2rSpUfc7YMCAvV7b4MGDo0uXLhERcdJJJ8UJJ5wQffv2jf/6r//aY1hs3749CoVCtG7tPz1woPJUCOyjLr744oiIuOeee4rHqqurY+7cuXH55ZfXG/+DH/wgTjzxxOjUqVOUl5fHcccdF7NmzYpPfs/gJ58KWbVqVRQKhfjRj34U06ZNiz59+sTBBx8cQ4cOjRdffPFzrbWioiIiIkpLS4vHnn766SgUCnHnnXfGd77znejVq1eUlZXFihUr4t13342rrroqBgwYEAcffHB07do1Tj/99Hjuuefq3G9D17ZgwYIYNWpUdO7cOdq2bRt9+/aN8ePH1xu3fv36uPjii6OioiK6desWl19+eVRXV3+uxwrsmbCAfVR5eXlceOGFMXv27OKxe+65J1q1ahUXXXRRvfGrVq2Kv//7v4///M//jPvvvz8uuOCCGDduXPzwhz/8XPNNnz495s2bF7fddlvcfffd8dFHH8W555672z+4O3fujB07dkRNTU2sWLEirr766igrK4sLL7yw3tgbb7wxqqqqYubMmfGrX/0qunbtGu+//35EREyaNCl+/etfx5w5c+KII46I4cOH7/Z1JZ9nbY8++miccsopUVVVFdOmTYv//u//ju9973uxfv36evf39a9/Pfr37x9z586NG264IX7+85/HhAkTPtc+AZ8hAfuUOXPmpIhIixYtSk899VSKiLR8+fKUUkrHH398uuyyy1JKKR199NFp2LBhu72PnTt3pu3bt6fJkyenzp07p9ra2uJ1w4YNq3O7lStXpohIxxxzTNqxY0fx+MKFC1NEpHvuuad4bNKkSSki6v2Ul5en+++/v84adq391FNP/czHvGPHjrR9+/Z0xhlnpK997WuNWlvfvn1T375908cff/yp8+xa/6233lrn+FVXXZXatm1bZ5+AxnHGAvZhw4YNi759+8bs2bNj2bJlsWjRot0+DRIR8eSTT8aZZ54ZFRUVUVJSEqWlpfH9738/Nm7cGBs2bPjMuUaOHBklJSXFy4MGDYqIiNWrV9cb+/jjj8eiRYti4cKF8dBDD8WZZ54Z3/jGN+KBBx6oN/brX//6buebOXNmHHfccdG2bdto3bp1lJaWxhNPPBGvv/56g9f25ptvxttvvx1XXHFFtG3b9jMf61e/+tU6lwcNGhRbt279XPsE7JmwgH1YoVCIv/mbv4m77rorZs6cGf37949TTjml3riFCxfGWWedFRERd9xxRzz//POxaNGiuOmmmyIi4uOPP/7MuTp37lzncllZ2afe9thjj40hQ4bE8ccfHyNHjoz77rsvvvjFL8bVV19db2yPHj3qHZs2bVp8+9vfjhNPPDHmzp0bL774YixatCjOPvvs3c73WWt79913IyKid+/en/k4P8/9AY3npdmwj7vsssvi+9//fsycOTNuueWW3Y659957o7S0NB566KE6/8f+4IMPNssaW7VqFUcffXTcd999sWHDhujatWvxukKhUG/8XXfdFcOHD48ZM2bUOb558+ZGzX/IIYdERMTvf//7Rt0eyMcZC9jH9erVK6677roYNWpUjBkzZrdjdr2F8/8+XfDxxx/HnXfe2Sxr3LlzZyxbtizKysrqvDX20xQKheJZgl1eeeWVmD9/fqPm79+/f/Epo23btjXqPoA8nLGA/cDUqVP3eP3IkSNj2rRp8dd//dfxd3/3d7Fx48b40Y9+VO+Pdy6LFy8uvsV0/fr1MXv27HjjjTdiwoQJn+s1Duedd1788Ic/jEmTJsWwYcPid7/7XUyePDn69OkTO3bsaNSapk+fHqNGjYovf/nLMWHChDj00EOjqqoqHn300bj77rsbdZ9AwwkLOACcfvrpMXv27PiXf/mXGDVqVPTq1Sv+9m//Nrp27RpXXHFF9vnOPvvs4j936tQp+vXrF7Nnz/7UMyqfdNNNN8WWLVti1qxZceutt8aAAQNi5syZ8cADD+z27aafx4gRI+LZZ5+NyZMnxzXXXBNbt26N3r1713uhJtC0Cil94tNzAAAayWssAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANk0++dY1NbWxh/+8Ifo0KHDbj/qFwDY96SUYvPmzdGzZ89o1erTz0s0e1j84Q9/iMrKyuaeFgDIYM2aNXv8wr9mD4sOHTpExP8u7PN8pwAA0PI2bdoUlZWVxb/jn6bZw2LX0x/l5eXCAgD2M5/1MgYv3gQAshEWAEA2wgIAyMbXpgOwT0gpxY4dO2Lnzp0tvZQ/SSUlJdG6deu9/igIYQFAi6upqYm1a9fGli1bWnopf9LatWsXPXr0iDZt2jT6PoQFAC2qtrY2Vq5cGSUlJdGzZ89o06aND1BsZimlqKmpiXfffTdWrlwZ/fr12+OHYO2JsACgRdXU1ERtbW1UVlZGu3btWno5f7IOOuigKC0tjdWrV0dNTU20bdu2UffjxZsA7BMa+3/I5JPjd+C3CABkIywAgGy8xgKAfdbhN/y6WedbNXVks853IHLGAgD2wrp162LcuHFxxBFHRFlZWVRWVsaoUaPiiSeeaNZ1FAqFePDBB5t1zt1xxgIAGmnVqlXxla98JTp27Bi33nprDBo0KLZv3x6PPvpoXH311fHGG2+09BKbnTMWANBIV111VRQKhVi4cGFceOGF0b9//zj66KNj4sSJ8eKLL0ZERFVVVfzFX/xFHHzwwVFeXh5/9Vd/FevXry/ex2WXXRbnn39+nfsdP358DB8+vHh5+PDhcc0118T1118fnTp1iu7du8fNN99cvP7www+PiIivfe1rUSgUipd/+9vfxmmnnRYdOnSI8vLyGDx4cLz00ktNsRVFwgIAGuH999+PRx55JK6++upo3759ves7duwYKaU4//zz4/33349nnnkm5s2bF2+//XZcdNFFDZ7v3//936N9+/axYMGCuPXWW2Py5Mkxb968iIhYtGhRRETMmTMn1q5dW7x8ySWXRO/evWPRokWxePHiuOGGG6K0tHQvHvVn81QIADTCihUrIqUURx555KeOefzxx+OVV16JlStXRmVlZURE3HnnnXH00UfHokWL4vjjj//c8w0aNCgmTZoUERH9+vWLn/zkJ/HEE0/En//5n8chhxwSEf8bM927dy/epqqqKq677rriGvv169fgx9lQzlgAQCOklCIi9vjx46+//npUVlYWoyIiYsCAAdGxY8d4/fXXGzTfoEGD6lzu0aNHbNiwYY+3mThxYnzrW9+KM888M6ZOnRpvv/12g+ZsDGEBAI3Qr1+/KBQKewyElNJuw+P/Hm/VqlUxUnbZvn17vdt88imMQqEQtbW1e1zjzTffHK+++mqMHDkynnzyyRgwYEA88MADe7zN3hIWANAInTp1ihEjRsT06dPjo48+qnf9hx9+GAMGDIiqqqpYs2ZN8fhrr70W1dXVcdRRR0VExCGHHBJr166tc9ulS5c2eD2lpaW7/cr5/v37x4QJE+Kxxx6LCy64IObMmdPg+24IYQEAjXT77bfHzp0744QTToi5c+fGW2+9Fa+//nr8+Mc/jqFDh8aZZ54ZgwYNiksuuSSWLFkSCxcujNGjR8ewYcNiyJAhERFx+umnx0svvRT/8R//EW+99VZMmjQpli9f3uC1HH744fHEE0/EunXr4oMPPoiPP/44xo4dG08//XSsXr06nn/++Vi0aFExaJqKF28CsM/a1z8Js0+fPrFkyZK45ZZb4jvf+U6sXbs2DjnkkBg8eHDMmDGj+KFV48aNi1NPPTVatWoVZ599dvzbv/1b8T5GjBgR//iP/xjXX399bN26NS6//PIYPXp0LFu2rEFr+dd//deYOHFi3HHHHdGrV6948803Y+PGjTF69OhYv359dOnSJS644IL4wQ9+kHsb6iikTz6x08Q2bdoUFRUVUV1dHeXl5c05NQD7oK1bt8bKlSujT58+jf6qbvLY0+/i8/799lQIAJCNsAAAshEWAEA2wgIAyEZYALBPaOb3ErAbOX4HwgKAFrXrEyW3bNnSwith1+9gb76ozOdYANCiSkpKomPHjsXvvWjXrt0ev3+D/FJKsWXLltiwYUN07NgxSkpKGn1fwgKAFrfrGzk/60u1aFqf/HbUxhAWALS4QqEQPXr0iK5du+72C7hoeqWlpXt1pmIXYQHAPqOkpCTLHzdajhdvAgDZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZNNi3xUycNKj0aqsXUtNHxERq6aObNH5AeBA44wFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkE2Dw+LZZ5+NUaNGRc+ePaNQKMSDDz7YBMsCAPZHDQ6Ljz76KI499tj4yU9+0hTrAQD2Y60beoNzzjknzjnnnKZYCwCwn2twWDTUtm3bYtu2bcXLmzZtauopAYAW0uQv3pwyZUpUVFQUfyorK5t6SgCghTR5WNx4441RXV1d/FmzZk1TTwkAtJAmfyqkrKwsysrKmnoaAGAf4HMsAIBsGnzG4o9//GOsWLGieHnlypWxdOnS6NSpUxx66KFZFwcA7F8aHBYvvfRSnHbaacXLEydOjIiIMWPGxM9+9rNsCwMA9j8NDovhw4dHSqkp1gIA7Oe8xgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyad1SEy//wYgoLy9vqekBgCbgjAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMimdUtNPHDSo9GqrF1LTQ8AB5xVU0e29BKcsQAA8hEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyaVRY3H777dGnT59o27ZtDB48OJ577rnc6wIA9kMNDotf/OIXMX78+Ljpppvi5ZdfjlNOOSXOOeecqKqqaor1AQD7kQaHxbRp0+KKK66Ib33rW3HUUUfFbbfdFpWVlTFjxoymWB8AsB9pUFjU1NTE4sWL46yzzqpz/KyzzooXXnhht7fZtm1bbNq0qc4PAHBgalBYvPfee7Fz587o1q1bnePdunWLdevW7fY2U6ZMiYqKiuJPZWVl41cLAOzTGvXizUKhUOdySqnesV1uvPHGqK6uLv6sWbOmMVMCAPuB1g0Z3KVLlygpKal3dmLDhg31zmLsUlZWFmVlZY1fIQCw32jQGYs2bdrE4MGDY968eXWOz5s3L0466aSsCwMA9j8NOmMRETFx4sS49NJLY8iQITF06ND46U9/GlVVVXHllVc2xfoAgP1Ig8Pioosuio0bN8bkyZNj7dq1MXDgwHj44YfjsMMOa4r1AQD7kQaHRUTEVVddFVdddVXutQAA+znfFQIAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZtG6piZf/YESUl5e31PQAQBNwxgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGQjLACAbIQFAJCNsAAAshEWAEA2wgIAyEZYAADZCAsAIBthAQBkIywAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACyERYAQDbCAgDIRlgAANkICwAgG2EBAGTTurknTClFRMSmTZuae2oAoJF2/d3e9Xf80zR7WGzcuDEiIiorK5t7agBgL23evDkqKio+9fpmD4tOnTpFRERVVdUeF0bjbdq0KSorK2PNmjVRXl7e0ss5INnjpmePm549bloH2v6mlGLz5s3Rs2fPPY5r9rBo1ep/X9ZRUVFxQGz0vqy8vNweNzF73PTscdOzx03rQNrfz3NCwIs3AYBshAUAkE2zh0VZWVlMmjQpysrKmnvqPxn2uOnZ46Znj5uePW5af6r7W0if9b4RAIDPyVMhAEA2wgIAyEZYAADZCAsAIBthAQBk06xhcfvtt0efPn2ibdu2MXjw4Hjuueeac/r9xpQpU+L444+PDh06RNeuXeP888+P3/3ud3XGpJTi5ptvjp49e8ZBBx0Uw4cPj1dffbXOmG3btsW4ceOiS5cu0b59+/jqV78av//97+uM+eCDD+LSSy+NioqKqKioiEsvvTQ+/PDDpn6I+5QpU6ZEoVCI8ePHF4/Z3zzeeeed+OY3vxmdO3eOdu3axZ/92Z/F4sWLi9fb572zY8eO+N73vhd9+vSJgw46KI444oiYPHly1NbWFsfY44Z59tlnY9SoUdGzZ88oFArx4IMP1rm+OfezqqoqRo0aFe3bt48uXbrENddcEzU1NU3xsPNKzeTee+9NpaWl6Y477kivvfZauvbaa1P79u3T6tWrm2sJ+40RI0akOXPmpOXLl6elS5emkSNHpkMPPTT98Y9/LI6ZOnVq6tChQ5o7d25atmxZuuiii1KPHj3Spk2bimOuvPLK1KtXrzRv3ry0ZMmSdNppp6Vjjz027dixozjm7LPPTgMHDkwvvPBCeuGFF9LAgQPTeeed16yPtyUtXLgwHX744WnQoEHp2muvLR63v3vv/fffT4cddli67LLL0oIFC9LKlSvT448/nlasWFEcY5/3zj/90z+lzp07p4ceeiitXLky3Xfffenggw9Ot912W3GMPW6Yhx9+ON10001p7ty5KSLSAw88UOf65trPHTt2pIEDB6bTTjstLVmyJM2bNy/17NkzjR07tsn3YG81W1iccMIJ6corr6xz7Mgjj0w33HBDcy1hv7Vhw4YUEemZZ55JKaVUW1ubunfvnqZOnVocs3Xr1lRRUZFmzpyZUkrpww8/TKWlpenee+8tjnnnnXdSq1at0iOPPJJSSum1115LEZFefPHF4pj58+eniEhvvPFGczy0FrV58+bUr1+/NG/evDRs2LBiWNjfPL773e+mk08++VOvt897b+TIkenyyy+vc+yCCy5I3/zmN1NK9nhvfTIsmnM/H3744dSqVav0zjvvFMfcc889qaysLFVXVzfJ482lWZ4KqampicWLF8dZZ51V5/hZZ50VL7zwQnMsYb9WXV0dEf//m2FXrlwZ69atq7OfZWVlMWzYsOJ+Ll68OLZv315nTM+ePWPgwIHFMfPnz4+Kioo48cQTi2O+/OUvR0VFxZ/E7+Xqq6+OkSNHxplnnlnnuP3N45e//GUMGTIk/vIv/zK6du0aX/rSl+KOO+4oXm+f997JJ58cTzzxRLz55psREfHb3/42fvOb38S5554bEfY4t+bcz/nz58fAgQPrfJPoiBEjYtu2bXWeTtwXNcu3m7733nuxc+fO6NatW53j3bp1i3Xr1jXHEvZbKaWYOHFinHzyyTFw4MCIiOKe7W4/V69eXRzTpk2b+MIXvlBvzK7br1u3Lrp27Vpvzq5dux7wv5d77703lixZEosWLap3nf3N43/+539ixowZMXHixPiHf/iHWLhwYVxzzTVRVlYWo0ePts8ZfPe7343q6uo48sgjo6SkJHbu3Bm33HJLXHzxxRHh3+XcmnM/161bV2+eL3zhC9GmTZt9fs+b9WvTC4VCncsppXrHqGvs2LHxyiuvxG9+85t61zVmPz85ZnfjD/Tfy5o1a+Laa6+Nxx57LNq2bfup4+zv3qmtrY0hQ4bEP//zP0dExJe+9KV49dVXY8aMGTF69OjiOPvceL/4xS/irrvuip///Odx9NFHx9KlS2P8+PHRs2fPGDNmTHGcPc6rufZzf93zZnkqpEuXLlFSUlKvsjZs2FCvyPj/xo0bF7/85S/jqaeeit69exePd+/ePSJij/vZvXv3qKmpiQ8++GCPY9avX19v3nffffeA/r0sXrw4NmzYEIMHD47WrVtH69at45lnnokf//jH0bp16+Jjt797p0ePHjFgwIA6x4466qioqqqKCP8e53DdddfFDTfcEN/4xjfimGOOiUsvvTQmTJgQU6ZMiQh7nFtz7mf37t3rzfPBBx/E9u3b9/k9b5awaNOmTQwePDjmzZtX5/i8efPipJNOao4l7FdSSjF27Ni4//7748knn4w+ffrUub5Pnz7RvXv3OvtZU1MTzzzzTHE/Bw8eHKWlpXXGrF27NpYvX14cM3To0Kiuro6FCxcWxyxYsCCqq6sP6N/LGWecEcuWLYulS5cWf4YMGRKXXHJJLF26NI444gj7m8FXvvKVem+TfvPNN+Owww6LCP8e57Bly5Zo1aruf8ZLSkqKbze1x3k1534OHTo0li9fHmvXri2Oeeyxx6KsrCwGDx7cpI9zrzXXq0R3vd101qxZ6bXXXkvjx49P7du3T6tWrWquJew3vv3tb6eKior09NNPp7Vr1xZ/tmzZUhwzderUVFFRke6///60bNmydPHFF+/2LU+9e/dOjz/+eFqyZEk6/fTTd/uWp0GDBqX58+en+fPnp2OOOeaAfAvZZ/m/7wpJyf7msHDhwtS6det0yy23pLfeeivdfffdqV27dumuu+4qjrHPe2fMmDGpV69exbeb3n///alLly7p+uuvL46xxw2zefPm9PLLL6eXX345RUSaNm1aevnll4sfjdBc+7nr7aZnnHFGWrJkSXr88cdT7969vd30k6ZPn54OO+yw1KZNm3TccccV3z5JXRGx2585c+YUx9TW1qZJkyal7t27p7KysnTqqaemZcuW1bmfjz/+OI0dOzZ16tQpHXTQQem8885LVVVVdcZs3LgxXXLJJalDhw6pQ4cO6ZJLLkkffPBBMzzKfcsnw8L+5vGrX/0qDRw4MJWVlaUjjzwy/fSnP61zvX3eO5s2bUrXXnttOvTQQ1Pbtm3TEUcckW666aa0bdu24hh73DBPPfXUbv/7O2bMmJRS8+7n6tWr08iRI9NBBx2UOnXqlMaOHZu2bt3alA8/i0JKKbXMuRIA4EDju0IAgGyEBQCQjbAAALIRFgBANsICAMhGWAAA2QgLACAbYQEAZCMsAIBshAUAkI2wAACy+X9h8zJUf2aU1gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT MainBranch\n",
    "FROM master\n",
    "\"\"\"\n",
    "df_mb = pd.read_sql_query(QUERY,conn)\n",
    "df_cnt=df_mb['MainBranch'].value_counts().rename_axis('MainBranch').reset_index(name='Counts')\n",
    "\n",
    "df_cnt.plot(kind='barh')\n",
    "plt.title('MainBranch')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Close the database connection.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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": [
    "Copyright © 2020 IBM Corporation. This notebook and its source code are released under the terms of the [MIT License](https://cognitiveclass.ai/mit-license?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDA0321ENSkillsNetwork21426264-2022-01-01&cm_mmc=Email_Newsletter-\\_-Developer_Ed%2BTech-\\_-WW_WW-\\_-SkillsNetwork-Courses-IBM-DA0321EN-SkillsNetwork-21426264&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ).\n"
   ]
  }
 ],
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