{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"text-align:center\">\n",
    "    <a href=\"https://skills.network\" 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**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estimated time needed: **45** minutes\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this lab, you will focus on data visualization. The dataset will be provided through an RDBMS, and you will need to use SQL queries to extract the required data.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objectives\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After completing this lab, you will be able to:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-   Visualize the distribution of data.\n",
    "\n",
    "-   Visualize the relationship between two features.\n",
    "\n",
    "-   Visualize composition and comparison of data.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to work with database\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download the database file.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2026-02-03 08:05:39--  https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/n01PQ9pSmiRX6520flujwQ/survey-data.csv\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",
      "200 OKequest sent, awaiting response... \n",
      "Length: 159525875 (152M) [text/csv]\n",
      "Saving to: ‘survey-data.csv’\n",
      "\n",
      "survey-data.csv     100%[===================>] 152.13M  55.1MB/s    in 2.8s    \n",
      "\n",
      "2026-02-03 08:05:44 (55.1 MB/s) - ‘survey-data.csv’ saved [159525875/159525875]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/n01PQ9pSmiRX6520flujwQ/survey-data.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Install and Import Necessary Python Libraries**\n",
    "\n",
    "Ensure that you have the required libraries installed to work with SQLite and Pandas:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in /opt/conda/lib/python3.12/site-packages (3.0.0)\n",
      "Requirement already satisfied: numpy>=1.26.0 in /opt/conda/lib/python3.12/site-packages (from pandas) (2.4.2)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in /opt/conda/lib/python3.12/site-packages (from pandas) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.12/site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n",
      "Requirement already satisfied: matplotlib in /opt/conda/lib/python3.12/site-packages (3.10.8)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (1.3.3)\n",
      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (4.61.1)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (1.4.9)\n",
      "Requirement already satisfied: numpy>=1.23 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (2.4.2)\n",
      "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (24.2)\n",
      "Requirement already satisfied: pillow>=8 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (12.1.0)\n",
      "Requirement already satisfied: pyparsing>=3 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (3.3.2)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.12/site-packages (from matplotlib) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib) (1.17.0)\n",
      "Requirement already satisfied: seaborn in /opt/conda/lib/python3.12/site-packages (0.13.2)\n",
      "Requirement already satisfied: numpy!=1.24.0,>=1.20 in /opt/conda/lib/python3.12/site-packages (from seaborn) (2.4.2)\n",
      "Requirement already satisfied: pandas>=1.2 in /opt/conda/lib/python3.12/site-packages (from seaborn) (3.0.0)\n",
      "Requirement already satisfied: matplotlib!=3.6.1,>=3.4 in /opt/conda/lib/python3.12/site-packages (from seaborn) (3.10.8)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.3.3)\n",
      "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (4.61.1)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (1.4.9)\n",
      "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (24.2)\n",
      "Requirement already satisfied: pillow>=8 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (12.1.0)\n",
      "Requirement already satisfied: pyparsing>=3 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (3.3.2)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.12/site-packages (from matplotlib!=3.6.1,>=3.4->seaborn) (2.9.0.post0)\n",
      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.12/site-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.4->seaborn) (1.17.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas \n",
    "!pip install matplotlib\n",
    "!pip install seaborn\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import textwrap\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Read the CSV File into a Pandas DataFrame**\n",
    "\n",
    "Load the Stack Overflow survey data into a Pandas DataFrame:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   ResponseId                      MainBranch                 Age  \\\n",
      "0           1  I am a developer by profession  Under 18 years old   \n",
      "1           2  I am a developer by profession     35-44 years old   \n",
      "2           3  I am a developer by profession     45-54 years old   \n",
      "3           4           I am learning to code     18-24 years old   \n",
      "4           5  I am a developer by profession     18-24 years old   \n",
      "\n",
      "            Employment RemoteWork   Check  \\\n",
      "0  Employed, full-time     Remote  Apples   \n",
      "1  Employed, full-time     Remote  Apples   \n",
      "2  Employed, full-time     Remote  Apples   \n",
      "3   Student, full-time        NaN  Apples   \n",
      "4   Student, full-time        NaN  Apples   \n",
      "\n",
      "                                    CodingActivities  \\\n",
      "0                                              Hobby   \n",
      "1  Hobby;Contribute to open-source projects;Other...   \n",
      "2  Hobby;Contribute to open-source projects;Other...   \n",
      "3                                                NaN   \n",
      "4                                                NaN   \n",
      "\n",
      "                                             EdLevel  \\\n",
      "0                          Primary/elementary school   \n",
      "1       Bachelor’s degree (B.A., B.S., B.Eng., etc.)   \n",
      "2    Master’s degree (M.A., M.S., M.Eng., MBA, etc.)   \n",
      "3  Some college/university study without earning ...   \n",
      "4  Secondary school (e.g. American high school, G...   \n",
      "\n",
      "                                           LearnCode  \\\n",
      "0                             Books / Physical media   \n",
      "1  Books / Physical media;Colleague;On the job tr...   \n",
      "2  Books / Physical media;Colleague;On the job tr...   \n",
      "3  Other online resources (e.g., videos, blogs, f...   \n",
      "4  Other online resources (e.g., videos, blogs, f...   \n",
      "\n",
      "                                     LearnCodeOnline  ... JobSatPoints_6  \\\n",
      "0                                                NaN  ...            NaN   \n",
      "1  Technical documentation;Blogs;Books;Written Tu...  ...            0.0   \n",
      "2  Technical documentation;Blogs;Books;Written Tu...  ...            NaN   \n",
      "3  Stack Overflow;How-to videos;Interactive tutorial  ...            NaN   \n",
      "4  Technical documentation;Blogs;Written Tutorial...  ...            NaN   \n",
      "\n",
      "  JobSatPoints_7 JobSatPoints_8 JobSatPoints_9 JobSatPoints_10  \\\n",
      "0            NaN            NaN            NaN             NaN   \n",
      "1            0.0            0.0            0.0             0.0   \n",
      "2            NaN            NaN            NaN             NaN   \n",
      "3            NaN            NaN            NaN             NaN   \n",
      "4            NaN            NaN            NaN             NaN   \n",
      "\n",
      "  JobSatPoints_11           SurveyLength SurveyEase ConvertedCompYearly JobSat  \n",
      "0             NaN                    NaN        NaN                 NaN    NaN  \n",
      "1             0.0                    NaN        NaN                 NaN    NaN  \n",
      "2             NaN  Appropriate in length       Easy                 NaN    NaN  \n",
      "3             NaN               Too long       Easy                 NaN    NaN  \n",
      "4             NaN              Too short       Easy                 NaN    NaN  \n",
      "\n",
      "[5 rows x 114 columns]\n",
      "Initial dataframe: (65437, 114)\n"
     ]
    }
   ],
   "source": [
    "# Read the CSV file\n",
    "df = pd.read_csv('survey-data.csv')\n",
    "\n",
    "# Display the first few rows of the data\n",
    "print(df.head())\n",
    "print('Initial dataframe:', df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Create a SQLite Database and Insert the Data**\n",
    "\n",
    "Now, let's create a new SQLite database (`survey-data.sqlite`) and insert the data from the DataFrame into a table using the sqlite3 library:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "\n",
    "# Create a connection to the SQLite database\n",
    "conn = sqlite3.connect('survey-data.sqlite')\n",
    "\n",
    "# Write the dataframe to the SQLite database\n",
    "df.to_sql('main', conn, if_exists='replace', index=False)\n",
    "\n",
    "# Close the connection\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Verify the Data in the SQLite Database**\n",
    "Verify that the data has been correctly inserted into the SQLite database by running a simple query:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   ResponseId                      MainBranch                 Age  \\\n",
      "0           1  I am a developer by profession  Under 18 years old   \n",
      "1           2  I am a developer by profession     35-44 years old   \n",
      "2           3  I am a developer by profession     45-54 years old   \n",
      "3           4           I am learning to code     18-24 years old   \n",
      "4           5  I am a developer by profession     18-24 years old   \n",
      "\n",
      "            Employment RemoteWork   Check  \\\n",
      "0  Employed, full-time     Remote  Apples   \n",
      "1  Employed, full-time     Remote  Apples   \n",
      "2  Employed, full-time     Remote  Apples   \n",
      "3   Student, full-time        NaN  Apples   \n",
      "4   Student, full-time        NaN  Apples   \n",
      "\n",
      "                                    CodingActivities  \\\n",
      "0                                              Hobby   \n",
      "1  Hobby;Contribute to open-source projects;Other...   \n",
      "2  Hobby;Contribute to open-source projects;Other...   \n",
      "3                                                NaN   \n",
      "4                                                NaN   \n",
      "\n",
      "                                             EdLevel  \\\n",
      "0                          Primary/elementary school   \n",
      "1       Bachelor’s degree (B.A., B.S., B.Eng., etc.)   \n",
      "2    Master’s degree (M.A., M.S., M.Eng., MBA, etc.)   \n",
      "3  Some college/university study without earning ...   \n",
      "4  Secondary school (e.g. American high school, G...   \n",
      "\n",
      "                                           LearnCode  \\\n",
      "0                             Books / Physical media   \n",
      "1  Books / Physical media;Colleague;On the job tr...   \n",
      "2  Books / Physical media;Colleague;On the job tr...   \n",
      "3  Other online resources (e.g., videos, blogs, f...   \n",
      "4  Other online resources (e.g., videos, blogs, f...   \n",
      "\n",
      "                                     LearnCodeOnline  ... JobSatPoints_6  \\\n",
      "0                                                NaN  ...            NaN   \n",
      "1  Technical documentation;Blogs;Books;Written Tu...  ...            0.0   \n",
      "2  Technical documentation;Blogs;Books;Written Tu...  ...            NaN   \n",
      "3  Stack Overflow;How-to videos;Interactive tutorial  ...            NaN   \n",
      "4  Technical documentation;Blogs;Written Tutorial...  ...            NaN   \n",
      "\n",
      "  JobSatPoints_7 JobSatPoints_8 JobSatPoints_9 JobSatPoints_10  \\\n",
      "0            NaN            NaN            NaN             NaN   \n",
      "1            0.0            0.0            0.0             0.0   \n",
      "2            NaN            NaN            NaN             NaN   \n",
      "3            NaN            NaN            NaN             NaN   \n",
      "4            NaN            NaN            NaN             NaN   \n",
      "\n",
      "  JobSatPoints_11           SurveyLength SurveyEase ConvertedCompYearly JobSat  \n",
      "0             NaN                    NaN        NaN                None   None  \n",
      "1             0.0                    NaN        NaN                None   None  \n",
      "2             NaN  Appropriate in length       Easy                None   None  \n",
      "3             NaN               Too long       Easy                None   None  \n",
      "4             NaN              Too short       Easy                None   None  \n",
      "\n",
      "[5 rows x 114 columns]\n",
      "Initial dataframe: (5, 2)\n"
     ]
    }
   ],
   "source": [
    "# Reconnect to the SQLite database\n",
    "conn = sqlite3.connect('survey-data.sqlite')\n",
    "\n",
    "# Run a simple query to check the data\n",
    "QUERY = \"SELECT * FROM main LIMIT 5\"\n",
    "df_check = pd.read_sql_query(QUERY, conn)\n",
    "\n",
    "# Display the results\n",
    "print(df_check)\n",
    "print('Initial dataframe:', df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: Running an SQL Query\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Count the number of rows in the table named 'main'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>65437</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0     65437"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT COUNT(*)\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: Listing All Tables\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To view the names of all tables in the database:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Table_Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>main</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Table_Name\n",
       "0       main"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT name as Table_Name FROM sqlite_master\n",
    "WHERE type = 'table'\n",
    "\"\"\"\n",
    "pd.read_sql_query(QUERY, conn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: Running a Group By Query\n",
    "    \n",
    "For example, you can group data by a specific column, like Age, to get the count of respondents in each age group:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Age</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>18-24 years old</td>\n",
       "      <td>14098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25-34 years old</td>\n",
       "      <td>23911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>35-44 years old</td>\n",
       "      <td>14942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>45-54 years old</td>\n",
       "      <td>6249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>55-64 years old</td>\n",
       "      <td>2575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>65 years or older</td>\n",
       "      <td>772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Prefer not to say</td>\n",
       "      <td>322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Under 18 years old</td>\n",
       "      <td>2568</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Age  count\n",
       "0     18-24 years old  14098\n",
       "1     25-34 years old  23911\n",
       "2     35-44 years old  14942\n",
       "3     45-54 years old   6249\n",
       "4     55-64 years old   2575\n",
       "5   65 years or older    772\n",
       "6   Prefer not to say    322\n",
       "7  Under 18 years old   2568"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT Age, COUNT(*) as count\n",
    "FROM main\n",
    "GROUP BY Age\n",
    "ORDER BY Age\n",
    "\"\"\"\n",
    "pd.read_sql_query(QUERY, conn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: Describing a table\n",
    "\n",
    "Use this query to get the schema of a specific table, main in this case:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CREATE TABLE \"main\" (\n",
      "\"ResponseId\" INTEGER,\n",
      "  \"MainBranch\" TEXT,\n",
      "  \"Age\" TEXT,\n",
      "  \"Employment\" TEXT,\n",
      "  \"RemoteWork\" TEXT,\n",
      "  \"Check\" TEXT,\n",
      "  \"CodingActivities\" TEXT,\n",
      "  \"EdLevel\" TEXT,\n",
      "  \"LearnCode\" TEXT,\n",
      "  \"LearnCodeOnline\" TEXT,\n",
      "  \"TechDoc\" TEXT,\n",
      "  \"YearsCode\" TEXT,\n",
      "  \"YearsCodePro\" TEXT,\n",
      "  \"DevType\" TEXT,\n",
      "  \"OrgSize\" TEXT,\n",
      "  \"PurchaseInfluence\" TEXT,\n",
      "  \"BuyNewTool\" TEXT,\n",
      "  \"BuildvsBuy\" TEXT,\n",
      "  \"TechEndorse\" TEXT,\n",
      "  \"Country\" TEXT,\n",
      "  \"Currency\" TEXT,\n",
      "  \"CompTotal\" REAL,\n",
      "  \"LanguageHaveWorkedWith\" TEXT,\n",
      "  \"LanguageWantToWorkWith\" TEXT,\n",
      "  \"LanguageAdmired\" TEXT,\n",
      "  \"DatabaseHaveWorkedWith\" TEXT,\n",
      "  \"DatabaseWantToWorkWith\" TEXT,\n",
      "  \"DatabaseAdmired\" TEXT,\n",
      "  \"PlatformHaveWorkedWith\" TEXT,\n",
      "  \"PlatformWantToWorkWith\" TEXT,\n",
      "  \"PlatformAdmired\" TEXT,\n",
      "  \"WebframeHaveWorkedWith\" TEXT,\n",
      "  \"WebframeWantToWorkWith\" TEXT,\n",
      "  \"WebframeAdmired\" TEXT,\n",
      "  \"EmbeddedHaveWorkedWith\" TEXT,\n",
      "  \"EmbeddedWantToWorkWith\" TEXT,\n",
      "  \"EmbeddedAdmired\" TEXT,\n",
      "  \"MiscTechHaveWorkedWith\" TEXT,\n",
      "  \"MiscTechWantToWorkWith\" TEXT,\n",
      "  \"MiscTechAdmired\" TEXT,\n",
      "  \"ToolsTechHaveWorkedWith\" TEXT,\n",
      "  \"ToolsTechWantToWorkWith\" TEXT,\n",
      "  \"ToolsTechAdmired\" TEXT,\n",
      "  \"NEWCollabToolsHaveWorkedWith\" TEXT,\n",
      "  \"NEWCollabToolsWantToWorkWith\" TEXT,\n",
      "  \"NEWCollabToolsAdmired\" TEXT,\n",
      "  \"OpSysPersonal use\" TEXT,\n",
      "  \"OpSysProfessional use\" TEXT,\n",
      "  \"OfficeStackAsyncHaveWorkedWith\" TEXT,\n",
      "  \"OfficeStackAsyncWantToWorkWith\" TEXT,\n",
      "  \"OfficeStackAsyncAdmired\" TEXT,\n",
      "  \"OfficeStackSyncHaveWorkedWith\" TEXT,\n",
      "  \"OfficeStackSyncWantToWorkWith\" TEXT,\n",
      "  \"OfficeStackSyncAdmired\" TEXT,\n",
      "  \"AISearchDevHaveWorkedWith\" TEXT,\n",
      "  \"AISearchDevWantToWorkWith\" TEXT,\n",
      "  \"AISearchDevAdmired\" TEXT,\n",
      "  \"NEWSOSites\" TEXT,\n",
      "  \"SOVisitFreq\" TEXT,\n",
      "  \"SOAccount\" TEXT,\n",
      "  \"SOPartFreq\" TEXT,\n",
      "  \"SOHow\" TEXT,\n",
      "  \"SOComm\" TEXT,\n",
      "  \"AISelect\" TEXT,\n",
      "  \"AISent\" TEXT,\n",
      "  \"AIBen\" TEXT,\n",
      "  \"AIAcc\" TEXT,\n",
      "  \"AIComplex\" TEXT,\n",
      "  \"AIToolCurrently Using\" TEXT,\n",
      "  \"AIToolInterested in Using\" TEXT,\n",
      "  \"AIToolNot interested in Using\" TEXT,\n",
      "  \"AINextMuch more integrated\" TEXT,\n",
      "  \"AINextNo change\" TEXT,\n",
      "  \"AINextMore integrated\" TEXT,\n",
      "  \"AINextLess integrated\" TEXT,\n",
      "  \"AINextMuch less integrated\" TEXT,\n",
      "  \"AIThreat\" TEXT,\n",
      "  \"AIEthics\" TEXT,\n",
      "  \"AIChallenges\" TEXT,\n",
      "  \"TBranch\" TEXT,\n",
      "  \"ICorPM\" TEXT,\n",
      "  \"WorkExp\" REAL,\n",
      "  \"Knowledge_1\" TEXT,\n",
      "  \"Knowledge_2\" TEXT,\n",
      "  \"Knowledge_3\" TEXT,\n",
      "  \"Knowledge_4\" TEXT,\n",
      "  \"Knowledge_5\" TEXT,\n",
      "  \"Knowledge_6\" TEXT,\n",
      "  \"Knowledge_7\" TEXT,\n",
      "  \"Knowledge_8\" TEXT,\n",
      "  \"Knowledge_9\" TEXT,\n",
      "  \"Frequency_1\" TEXT,\n",
      "  \"Frequency_2\" TEXT,\n",
      "  \"Frequency_3\" TEXT,\n",
      "  \"TimeSearching\" TEXT,\n",
      "  \"TimeAnswering\" TEXT,\n",
      "  \"Frustration\" TEXT,\n",
      "  \"ProfessionalTech\" TEXT,\n",
      "  \"ProfessionalCloud\" TEXT,\n",
      "  \"ProfessionalQuestion\" TEXT,\n",
      "  \"Industry\" TEXT,\n",
      "  \"JobSatPoints_1\" REAL,\n",
      "  \"JobSatPoints_4\" REAL,\n",
      "  \"JobSatPoints_5\" REAL,\n",
      "  \"JobSatPoints_6\" REAL,\n",
      "  \"JobSatPoints_7\" REAL,\n",
      "  \"JobSatPoints_8\" REAL,\n",
      "  \"JobSatPoints_9\" REAL,\n",
      "  \"JobSatPoints_10\" REAL,\n",
      "  \"JobSatPoints_11\" REAL,\n",
      "  \"SurveyLength\" TEXT,\n",
      "  \"SurveyEase\" TEXT,\n",
      "  \"ConvertedCompYearly\" REAL,\n",
      "  \"JobSat\" REAL\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "table_name = 'main'\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 the Distribution of Data\n",
    "\n",
    "**Histograms**\n",
    "\n",
    "Plot a histogram of CompTotal (Total Compensation).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Write your code here\n",
    "QUERY = \"\"\"\n",
    "SELECT CompTotal\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn)\n",
    "\n",
    "df.CompTotal.hist(log=True)\n",
    "plt.xlabel('CompTotal')\n",
    "plt.ylabel('Count')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Box Plots**\n",
    "\n",
    "Plot a box plot of Age.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Write your code here\n",
    "QUERY = \"\"\"\n",
    "SELECT Age, CompTotal\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn)\n",
    "\n",
    "df.plot(kind='box', by='Age', figsize=(5, 6))\n",
    "plt.xticks(rotation=90)\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('CompTotal')\n",
    "plt.title('Age')\n",
    "plt.ylim(-10000, 700000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT Age\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn)\n",
    "df.Age = df.Age.map({'Under 18 years old': 17, '18-24 years old': 21, 'Prefer not to say': float('nan'), \n",
    "        '25-34 years old': 30, '35-44 years old': 40, '45-54 years old': 50,\n",
    "        '55-64 years old': 60, '65 years or older': 66})\n",
    "\n",
    "df.plot(kind='box', figsize=(3, 4))\n",
    "plt.ylabel('Age')\n",
    "plt.title('Age')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing Relationships in Data\n",
    "\n",
    "**Scatter Plots**\n",
    "\n",
    "Create a scatter plot of Age and WorkExp.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Write your code here\n",
    "QUERY = \"\"\"\n",
    "SELECT Age, WorkExp\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn)\n",
    "df.Age = df.Age.map({'Under 18 years old': 17, '18-24 years old': 21, 'Prefer not to say': float('nan'), \n",
    "        '25-34 years old': 30, '35-44 years old': 40, '45-54 years old': 50,\n",
    "        '55-64 years old': 60, '65 years or older': 66})\n",
    "\n",
    "df.plot(kind='scatter', x='Age', y='WorkExp', figsize=(10, 6), color='darkblue')\n",
    "\n",
    "plt.title('Scatter plot of Age and WorkExp')\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('WorkExp')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Bubble Plots**\n",
    "\n",
    "Create a bubble plot of `TimeSearching` and `Frustration` using the Age column as the bubble size.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT Age, TimeSearching, Frustration\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn).dropna()\n",
    "\n",
    "df.Age = df.Age.map({'Under 18 years old': 17, '18-24 years old': 21, 'Prefer not to say': float('nan'), \n",
    "        '25-34 years old': 30, '35-44 years old': 40, '45-54 years old': 50,\n",
    "        '55-64 years old': 60, '65 years or older': 66})\n",
    "norm_age = (df.Age - df.Age.min()) / (df.Age.max() - df.Age.min())\n",
    "df.TimeSearching = df.TimeSearching.map({'30-60 minutes a day': 45, '60-120 minutes a day': 90, \n",
    "        '15-30 minutes a day': 23, 'Less than 15 minutes a day': 14, 'Over 120 minutes a day': 121})\n",
    "df['NFrust'] = df['Frustration'].str.split(';').str.len()  # Transform categorical variable to numerical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Bubble plot')"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FEY12F2rNDjTaXRDFjjo+O4coivjvf//bMqD2vffe6+SMCOnaLhyUCL1agSpz08zgYSo5+iTokBqlRaJBjZ4xYegZ03T3rCAIqDU70Cs2HGN6RkmeG02I14HUqDBcOaoHlm0ugOfknUuCKOLUG4A4rqnFxi0AShmHW8/rifAzJguSSqJBg4XjMvD1rhLkV1vg9AjgwEEURYSr5RifGYOLhyVDo6TZfYl0rE43DpWZsC2/FifqbSe/KxxSIjUY3TMa/ZP00Cq7zuFmzZo1KCwsxMKFC7F69WosW7YMzz77LJTK4HxvCQk1GbHhuGx4Kj7eWoTqRgdidSrIef6sYRSCIOBEvR0RWiVun9QLPC99ewm1yHjh/vOzcMWIVMj45onvAKWcg+rkg0NTS4xawWPRxF5BX28pNUqLu6ZmYfHUTFw0JBkz+8fjshGpWDK9N64fmwY9jY0hEjpWZcbSX/Pw/qYC5FY0QinnEa6WQynnkVvRiPc3FWDpr3k4VmXu7FRbNLfA3HrrrViwYAFqamqwfPnyVrctLy/HjTfeiLi4OGg0GgwZMgTLli3D+vXrwXEcHn/88bP2qaurw8MPP4y+fftCo9HAYDBg2rRpWLNmjZS/FiGSWjQxA1eOTIVHEFFQY0GN2QGnu6m7ye5yo9xoQ1GdDVFhCjxwQTbG9IoOSl5d5xKpC5PJZHh83gCMSI/E/7aX4ECpEQ6XABFNs/lqlDKM7RGB68emY1KfuE7JUS7jkZ2gR3YCTWdOgudYlRkfbi5AncWFjJgwKGSnXxtFapVweQQU1Vrx4eYCLByXgcy48E7KtkllZSW+//579O7dG+PGjYNer8fLL7+Md999F1deeeVp21ZVVWHs2LEoKirCxIkTMW7cOFRUVOCOO+7AjBkzWo1fVFSEyZMno7CwEOeddx4uuOACWCwW/Pjjj7jgggvwzjvv4NZbbw3Gr0oIUzzP4+5pWRicYsBPB8uxs7AeFSY7RFEEz3OI0ioxb3Ac5g9JQma8Lmh5USHjg7mDkjF3UDKOVTZiS34tLA43dGoFJvaOQWpUWGenR0hQWZ1ufLmzBHUWFzJjw9qcwE0h49ErNgzHqy34cmcJlkzP6tRupg8++AAulwsLFy4EAAwYMADDhw/HunXrcOzYMWRmZrZs+/DDD6OoqAgPPPAAXnjhhZbnlyxZglGjRrUa/4YbbkBRURE+//xzXHXVVS3PNzQ0YPLkybj77rsxb948xMdLPwiSEClM6hOHSX3iUFRrQV5lI+wuAeFqOYamRsCgDX73LHUt+SEzXofrxqbj9smZWDAmjYoYck46VGZCSZ0V6dHaDmeh5TgOadFanKiz4lCZKUgZnq15kC/P87j++utbnl+4cCFEUTxt0K/T6cTnn38Og8GAf/zjH6fFGTx48Gn7N9u3bx82bNiASy+99LQiBgAiIiLwxBNPwG6345tvvmH8mxESfGnRYZjeLwFzBydhcp+4TiliAGqRIYT4QRRFbMuvhYznzupOaotCxoPnOWzPr8OItMhOmYL/t99+w/HjxzFz5kwkJye3PH/NNdfgr3/9Kz788EM8/fTTUCgUOHLkCGw2G0aMGAGd7uxm8gkTJuC///3vac9t2bIFAGA0GlsdO1Nd3TRd++HDhxn+VoSc26iQIYT4zOxw40S9DVFhvl2BRWmVKKm3wnyyWzbY3n33XQBo6VZqySsqChdeeCG++eYbfPfdd7jssstgNBoBoM0uoNaer62tBQD88ssv+OWXX9rMw2zuOgOfCQl11LVECPGZ0y203GLtC9nJVeSd7uAvYFpdXY0VK1YAAK6++uqWyfCaH83dPc3Fjl7fNHC+srL1BWBbe95gMAAAXn31VYii2Objgw8+YP3rEXLOohYZQojPlHK+pSjxRXPxo5QH/xpq2bJlcDqdGD58OIYMGdLqNt9//z1+/fVXFBQUIDs7GxqNBvv370djY+NZ3UubNm06a/8xY8YAAH7//XfcfffdzH8HQsjZqEWGEOKzcJUcKZEan1e2rbM6kRqpRbgq+NdQzQN5//Of/+C///1vq4/bbrutZUCwUqnElVdeCaPRiKeffvq0WPv27cNHH3101muMGDEC5513Hr799lu8//77reZx4MABVFVVsf8FCTlHUSFDCPEZx3EY3TMaHkGEy+NdN5HLI0AQRIzqGRX0gb7r16/H0aNHMXDgwDZvmwaAm2++GRzH4YMPPoDb7cbzzz+PHj164MUXX8TkyZPxyCOP4MYbb8S4ceMwe/ZsADhr5tLPPvsMvXr1ws0334whQ4bgtttuw4MPPogFCxZg4MCBGDRoEPLz8yX9fQk5l1AhQwjxS/8kPVKjtCistXa4ppIoiiiqtSIlSov+ScGftLG5NeaWW25pd7v09HRMnz4d5eXl+OGHHxAfH4/Nmzfj+uuvx6FDh/Dvf/8be/bswX/+8x8sWLAAwJ9jaZqlpKRg165deOaZZyCTyfDpp5/itddew+bNm9GjRw+88847GDhwoDS/KCHnIE7sqqu6MWIymWAwGGA0Gs864BByLrDb7SgoKEBGRgbUajXT2M0z+9ZbXEiL1rZ6K3bzzL6RYYouMbMvK3//+9/x7LPPYvXq1Zg5cybz+FL+3QgJBd6ev2mwLyHEb5lx4Vg4LgNf7ixBYY2lZZry5oHAdVYnBEFESpQWV4xIDckipqysDElJSac9d+DAAbz22muIiorCpEmTOikzQghAhQwhJECZceFYMj0Lh8pM2J5fh5J6KzyupruT+iboMapnVJdb/doXI0aMQGZmJgYMGICwsDDk5eVh5cqVEAQB77zzDrWWENLJQvPIQgjpUrRKOUamR2FEWiTMDjecbqFpFWyVvFNm8GXptttuw4oVK/D555+jsbERERERmDlzJu6//35Mnjy5s9Mj5JxHhQwhhBmO4zplxl4pPfbYY3jsscc6Ow1CSBvoriVCCCGEhCwqZAghhBASsqhrqZsQBBGlDTZYnR64PAJUch4GrQJxOhqIKBWj1Ym9JQ1otLshQES4SoH+SXrE6+k9J93X8WozCmssMDvcUMp5RGqUGJJqgDpEB3OT0EefvBBndrhxsNSI7QV1OFbVCLPDA48gQCHjYdAoMCglAsPTItEnQdfqHB/EdzllRvy4rwzrj1SistEJl1uACEAu4xATpsTYXjGYPTAJozIiz5r1tTN18ymjup2u9PdyugWsy63CqoPl2FNSj0abG25BBM8BKjmPHlFhmN4vHrMHJSI1UtvZ6ZIgqTLZUWGyw+7yIFwtR4/IMISrg19WUCETokRRxLaCOqw6UI6Ck1dHNqcHHlEERBEcx6GM51BUa8GmYzXoHR+Oy4anIiMmrLNTD1mNdhee/ekwNh2tRrXZCcfJAuZUDVY3iupKsCanEoNTI/CPuf06/cAuk8kAAC6XCxqNplNzId5zuVwA/vz7dZY9xfV4cXUu8qrMMNvdcHkEeE754HMA6ixO5FaY8NXOEswbnIQ7JmdC3gkLgxLpCYKAzcdrsepgBXYU1sHm9EAURfA8h0itElOy4zB3YCIy43UdB2OEChkfCIKA3cUNWHmgHIfLTXC6BWiUMgxONmDu4CT0SzIEJQ9RFPHr4Uqs2FOKE/U2WBwuVDc6YXa4TzvAKGUc9BoFzA4PahsdMFpduGZ0Gvp1whTxoa7O7MRD3+7D5mM1sDjPLmCaiQCcHhEVJgcajlSjwboPz8wfENQv9ZkUCgVUKhWMRiN0Ol3I3w59LhBFEUajESqVCgpF590FtuFIFZ5fdRgFNdZWC3eg6TPvEgCXwwNrrQXLthShxuzAP+b275RVzol0yhtseOKHQ9hfUodqswuuM5ZZK66zIa/ShO/3luGC/vFYcn6foHwGaIkCL5XUWvHMTznIKTeh0eqAUwAEEZDxIpQ8B71WjWE9IvHInGzEhEs7RmLzsRp8vLUIpfVWlBntqDU72zyxAoCMAxINasToVBiQZMAt5/VEOrXMeM3qdOOhb/ZjbU4lLGd+czuglHEYlRGNl68Y3KljZ0wmE0pLSxEeHg6DwQCFQkEFTRckiiJcLheMRiPMZjOSk5M7bWmV/Sca8PA3+5FXZYbT4/1pQsYBBo0CV41Mxf0z+3Sp7lXiv5J6Kx78aj/2FNfB5u748xCpkWPmgAQ8edFAv4sZWqKAoaJaC/729T7klRthdgpnVaGACIvThnVWO2otDrx8xWDJiplaswPf7ytDWYMNZQ021FhcHe7jEYHSBjs4ADnlJny/rwx3TskEz9OJzBsr9pRh49Ean4sYoKl1ZndRHT74owAPzeorQXbeaT4I1NTUoLS0tNPyIN5RqVSdWsQIgoA31x3D8WqLT0UM0HS8Mdlc+H5fOSb1icPontESZUmCxep04/HvDmF3cS3sbu/2qbe5seZgBeJ1atw7o4+k+XVqIbNx40b861//wq5du1BeXo7ly5dj/vz5LT8XRRGPPfYY3nvvPTQ0NGD8+PF46623kJWVFbQcBUHA0z/mIK/ciHp72ycyh0eEwyZif0kdnl+Vi5cuHyJJPvtLjSiqs8Boc3pVxDQTAZQb7QhTy5FbbkJ+jRmZcZ3X3REqBEHA6kPlaLR7/16fyeYSsD63ErdP6oUIrZJhdr7R6/XQ6/VwuVzweDydlgdpn0wm69TuJADYd8KIQ6VN3ef+cItArcWB1QcrqJDpBn49XIm9JXVeFzHN6mxurD5UgatG9UBihHTj8zq1kLFYLBg8eDBuuukmXHLJJWf9/MUXX8Rrr72GZcuWISMjA48++ihmzpyJnJycoK1vsvl4LXIrGtHo9O4LbXUK2FVUj9xyE7IT2V5NOd0CtubXwurwoKbR6fP+bhEwWl2oNjuwu7iBChkvbD5eiyPlJvh4UXoaEUBZgx0/HajANaN7MMvNXwqFotNPlKRrW7m/DLUWB/wrY5o4PQL+OFaNSpOdpiQIcT8frECD1ccq5qTyBit+OlCOm8/ryTirP3Vq5+WsWbPw9NNP4+KLLz7rZ6IoYunSpfjHP/6Biy66CIMGDcJHH32EsrIyrFixImg5rjpQDrPdCW8vTBweoMFix08HypnncqzKjPwqCxwuD6wu/66o66xO2Jxu7CmqhymAVoZzxbrcKtRbA3+fLC4PfsutZJARIdIy293443gtnJ5AyhjAIwAVJgd+OVTBKDPSGXLKjDhU5v/FXKNDwC+HKyEIgX2e2tNlR2EVFBSgoqIC06dPb3nOYDBg9OjR2LJlS9DyOFhmgsOLgU2ncolNA+VYa7S7YHN54PQIEPz8ULk8ItweEWaHG2Zf2wnPQZUmh9/v9akEAag2OwIPRIjEai0OWB1usDjvuAUBNRbfW49J15FfbYHJ5v+xSwRQ0+jwu0XHG112sG9FRVMVHx8ff9rz8fHxLT9rjcPhgMPx55tuMpn8zkEQBNhdJ+dm8YHoEWF1sh+D4PKIEETR735rABDFk7dLeoSA4pwrbC4P2r0lzAcOlwBBEOguDtKlWZxNk92xIIqATYJjIQkeu8sDd4B/Qo8gwuJwIypcmjGC3e6I+txzz8FgMLQ8UlNT/Y7F8zyUch68j7epcjwHrZL9JFYKGQeea7ql118c1zSBlULGQ0FzPHRIo5ABHJuDukrOUxFDurwwpRxyRnc0chygkeBYSIJHrZAh0FMFz3MIU0nXbtJlj6oJCQkAgMrK08cVVFZWtvysNQ8//DCMRmPLo6SkJKA8+iXpofbxe6jkgX6MB/oCQLhaDrVCBoVcBn8PMwoZB5mMR5hKjnAJP1jdRZxe5XMh2xqeB6IluhohhKWoMCW0SjlY1NxynkdUGH3uQ1mPaC30WpXf+3MAosOU0Eu4dEGXLWQyMjKQkJCAtWvXtjxnMpmwbds2jB07ts39VCpVy22mzY9AzBqQiDC1Et42gih5QK9VY+7gpIBetzWZceHIiAmDWinzu8UnUqNomo041QCDhu5c6cik3rEwaAL/AmoVMkztE8cgI0KkpVMrMKZnNJQBrs0m44F4nQrn943veGPSZQ1I0iM7Qef1OfBM4Uoe5/eLl3TJik4tZMxmM/bu3Yu9e/cCaBrgu3fvXhQXF4PjOCxZsgRPP/00vv/+exw4cADXX389kpKSTptrRmoTesUgM04Hvcq7wiFMxWNwaoQkyxWo5DKM6RkNrUKGGJ3vRYiMAyLDlIgNU2F4WhTz/Lqj8b1ikJ1gQCDHdA5AcoQasweyL24JkcKsgQmIClMGdIJQyniM6Rkt6fwhRHo8z+OCAYmI0Pp3QZcQqcXsQYmMszpdpxYyO3fuxNChQzF06FAAwH333YehQ4fin//8JwDggQcewF133YVFixZh5MiRMJvNWL16ddDmkAEAuZzHP+b0Rc84HSLVsjarUgUPRKp59E+OwiOzpZvBdVBKBHpEaWFQKxEd5n0xwwFIMKihUcrRO0GHXrHhkuXYncjlPM7vH49wpf+tMmoFj/N6x0k20I0Q1kakRSI7QQ+l3L/L8OaLplkDpT2BkeCY3jceA5Ij4OX1fItItQzTs+OQHCHtwrm01pKXjleb8czKHORVmmG2O2F3ixBFEbKTg2/1WhUGJBvwjzn9JL8C2XC0Gp9tK0ZZgxXlXixTwHNAol6NGJ0S/RINuPm8nsiMo0LGW2a7Gw98sw/rcqtg82OtpeFpkXjpisGSf5kJYWlXUT3+/u1+5Nf4tkwBf3KtpUuHpeCR2dk0wL2bKKg248Fv92NfST0cXtxJHaGWYWq/BDw7fwDUfl4Ienv+pkLGBy3Llx8oR25FI+xuARqFDANTDJg7KAlDUw1B+dKKoohVBypa1lyyOpyoMrtgdrhPm/NEzgEGrQIx4SpolHJkJ+hwzegeGJQSIXmO3U2VyY4Hv9mPbfm1sHpZzKhkHAamRODJ+f3RLzE4K6MTwtKvORV4YXUuimutcHrEDmcikPGAXq3AjP7xeCqAxQJJ11RUa8ETPxzCoRMNqLW40NoUayo5kGjQYkp2HB6c2cfvIgagQqYFy0KmKxFFEX8cq8Wqg+UoqrXC4nDB5vRAEEWA48BBBM/z0CpkMGiVyIoLx2XDU5AVT8sS+KvO7MRTKw9hW34tas3OVg/sHAC5jEOERo6BKRF4dE4/ZFA3HglhW4/X4qU1R1BQY4HZ4YLLLUJA02ddPPlfOQ8oFTLEhisxe0Ailpzfh4qYbsrtFrAhrxqrDpZjT3EDHC4PBAAyjoNeLcd5vWMxd1ASBiQHfvFGhcxJ3bWQaWa0uXDghBFbC2qRX2WGxdnUKiPjOURoFOifZMDIjChkJ+igVtB8DoESBAF7Soz46UAZfj9ajapGB9wnm91lfNO4gNE9ozFrQCIm9IqRdKQ+IcFidbqx5lAlVh8sx8FSE8wOFzxC0zwxSjmPlAgNpvSNw5wBiciki6VzRkl90/AGh1uAVilHr9gwpgvjUiFzUncvZJq5PQKK66ywOj1weQQo5TwitEokGdTgGMyDQs5WZbJjb0kDGu0ueERAp5ajX6IeadFhnZ0aIZIQBAE55Y0orLHA4nRDKZPBoFVgVHoUwiWcJ4Scm6iQOelcKWQIIYSQ7sTb8ze1exNCCCEkZFEhQwghhJCQRYUMIYQQQkIWFTKEEEIICVlUyBBCCCEkZFEhQwghhJCQRYUMIYQQQkIWFTKEEEIICVlUyBBCCCEkZFEhQwghhJCQRYUMIYQQQkIWFTKEEEIICVm0XKkPRFFEcZ0Vh8sb0WB1wuH2QKOUI1KrRP8kPRI7aaVpQRBRUGvB0YpGGG0uONweaJVyRIUpMSDZgHi9Oug5EUK6n1qzAwdKjagxO2F1uiHnOeg1CmTF6ZAZFw4ZH/zjHwk+QRCRX2PB0cpGmE4550SHKzEgyYC4IJ9zqJDxgssjYP8JI3YU1iGn1IiKRjs8HhHgAIiAXMYjKUKDgSkGjEyLQr8kfVC+0HaXB/tPGLGtoBa55SZUmxzwiH/mpZTxSIrUYEhqBIanRaFvoq5TCq3u6v1N+Vi+uxSNDjdEiNAoZJjUOxb3n58FhULR2ekRwoQoijhebcbOwnpsL6zFwRNGNNrd8IgieI6DQsYhIyYMQ3tEYXRGFIb0iIBWSaeW7sju8mBfSQO2F9Rhf2kDSmqtcAkiRFEEx3HQKmXIjA3HsLRIjEiPQnZCcM45nCiKouSv0om8XQa8LRaHG1/vOoGNR6tRb3HC5vbA4fLALYgQAfDgIJdxUMl5aBQyxOjUmN43DvOGJEEll7H/hU4y2lz4ckcJNh+vgdHqhM0loMZih9nmhgBAxnGIDlNCr1FCo5QhTq/CBf0TMWtgAhQy6lH0l8vlwv1fH8BvuVVodHha3UYj5zEyIwqvXDEQMTptkDMkhB1BELE2txJf7yzBwTIT6ixNx5ozKWU8wlUyJEdqMKN/Aq4e1QMx4apOyJhIxWh14YudxViXW4Vyow0NVnfTufBkCcEBkMs4aBVyRIYpkRGjxbzBybhgQALkfp5zvD1/U9ncDpvTg0+3FWH9kWoYbS6Y7W54RAFOlwCPKEIUAY4DZDwHh1wGi9MDh1vA9/vKYHd5cNWoHpIUDY12Fz7aUog/8mpgsrtRVGuGxXnmwUWEtcEOrsGOyDAFHG4By/ecgNPjwcVDU6gJ2A9GqwtzX9uIkgZ7u9vZ3AI25tVg+iu/44tFY9An0RCkDAlhRxRFrD5YgU+2FWH/iQaY2yjcAcDpEVBnFVBvdcFkc8Fid2LRpCxEhSmDmDGRisnuwoebC7AmpxJlDTZYHG54BBGeM5pBXB4RTrcTZocLRpsTZocbTo+A+UOSwUt4zqFL8zaIoogVe5taYhpOfjmtThcabS7UW12otbhQZ3WhzuKC0epCo80Jm8MNo82FOosTa3OrsOZQBfO8PIKIr3edwOZjNahttCG3wtRKEXPK7wGgzuJCXqUJNWYHVh0sx4YjVczz6u5cLhfmvLahwyLmVA02Ny5/ZwsqjFYJMyNEGtsL6vDlziLsLalvt4g5lQigqM6GVQer8L/txXC4vduPdF0eQcRXO0rwa04limstaLS74PScXcQATX9/twA43CLqrU7kVZqxYk8pNuZVS5ojFTJtOFFvw9b8WtRbXWi0u2B1umG2u2G0e+AS/vwLigAcHhFGuwdmpxt2lxuNdhdqGx3YmFeNOouTaV751WbsKKiDyeZGfp0Ngpcdg3a3iPwqM6pNTqw/UgWLw800r+7u7i/240SDw+f9THYPbvpwpwQZESIdp1vAuiNV2FtihLWdC6W2lBttWH+kCrnljRJkR4LpWJUZm4/XoLTBBptbgNuLj4MIwOUBTDYX8irN+O1wJaxO6c45VMi0YV9JA8ob7LA5PXC4PbA5PbC5268arE4BVqcAp1uA3eVBSZ0N+080MM1rV1E9qs0OVDTa4PHx+GJxCbDYHSisteJgqZFpXt2Zy+XCxqP+t2IdrWxEaR21ypDQcaSiEXuK62HxsiXmTE6PiMJaC3YU1qGbD8Ps9nYV1aGk3gar0w13a80w7XB5RDTanThS2YhDZSaJMqRCplVmhxvbCmphdwlweQS4PCKsrQxwa43V6YHTI8DuFmB1erA1vxZOb0pYL9SaHdhdXA+b04M6s8uvGOUmJxodLmwrqIPgbXPOOe79P4ra7b7riFsAnlp5mGFGhEhHFEXsKKpD0ck7UvxltLmxu6gepQ02htmRYKpudGBXUT3qLA64/fgsCGgqaitNDmzPl+6cQ4VMK4prrShtsMHp9sDtEeD0oZ9XBOD2CBBEEXaXGyV1VlSavB9X0Z6iOisqjHbYHE74+3GwugTYnAIKayyosfjeVXIuWr63NOAY2wtqGWRCiPSsTg/yKhthtPp3sdTM4RZwrNKMwhpqjQxVxXUWFNVaYXN6fO4BaOYRRBhtLhyrbkSdle1Qi2ZUyLTC7vbA5REhiIBbFH1uUXG4BQhC011NdldTNxOTvFweeAQRjg66uDokinC4PXB42cp0rvO3ef1UNkafAUKkZnd5YHU2zRMTKKfgYXb8I8Fnczb1Sggnpxvxhyg23cZvc7ol+yxQIdMKURQBERAhgmv6X99jnPJ/rFrTTqYFwe+P1J8EARCo79orLN4neqdJqBBEQAz0YukkUaTjTCgTTk4zAgaT2gli0+dBClTItEIll4HnOfAcB57nIPfx/ncFz4PnOHAAFDIeKjmbt1klb4qrDjQex0Gp4KFWSDdhX3fC4n1SyWjeHhIaVAoeKiXPZEZWOc9DRceZkKVWyCDjmya78/fTwHFND41cBpVCmpKDCplWxOvViAtXQn6yiNH4ON22Qs5DxnNQymWI1akQq2Mzw2W8Xo2ocAXUSv+nv1fImgqiOJ0KEVqaRt8bozOiAo6RGadjkAkh0gtXypESFYZwVWAFiELGISlCjQRa6y1kxetVSDSooVLI4O98djwPhKsUSIjUIEIjzQSJVMi0IlanwpAekdAo5ZDLeMg4QOnlFbVa3rT2iFLGQ6PkMTojGmEqNhMop0RqMCDJALVCBp2fB5lEnQpapQxje0VLuoRCd/LgBX29/vu3hueAB2f1YZgRIdLheQ6jMqKRZNAEFEenkmFoj0hkxoUzyowEW48oLQamRCBCo/C5ZwJoasVR8jyiwxUY0zMaSka9E2eiQqYNw9IiER2mhEYhg1ohR7hKjo7+BkoZB41SBqVcBrVChkSDBoNTI5jlxHEcRqZHIVKrQHKk7wcZGQ/otSqkRGoxMJldXt2dQavAwGT/lxlI0CkxKiOGYUaESGtgigGDUvQBtcokGDQY3TOalkMJYRzXVNQm6NVQypsu6n0h5wGtSo6seB0GBXAM7QgVMm3IigvHwJQIhKvl0Ch5aJQy6DUKaJX8WX2FPAeEKWUIV8kRppIjTCmDTi3HkNQIpPhRcLSnb6IefRMNCFcp0CPS+yZbHkDvOB30GgVGpEcx6+46V7xyxRC/DupKGYdnLh0kQUaESCdcJcf4zDj0ignza4xfTJgSYzIiMTCF1hkLdf2T9BiWHolYnerkOE3v9lPwHMLUCqREajGmZzSiJVxElAqZNshlPK4YmYKhPSKgUysQppQjTCmHQa1AVJgCkdpTHhoFDOqmIiZcJYdBo8DontG4eFgK8yXM1QoZrh7dAwOT9YgJVyE9St1hlayUcchO1MGgUWBCZgwuHJzINKdzQVpMGN5fOAJhPgxWU8o4PD6vH6b0iZcwM0KkMa1fHOYPS0FGrNanYiYqTIGpfWOxYGwG9Goahxfq1AoZrhrZAxMyYxCnV0Ej56Hg2x78y6NpLGa4Wo7UCA1mDkjAnIFJkubIid18/mhvlwFvS1mDDZ9uK8KuwnqYnW44XAIcbg8EEeCabtAGzwEahQwqeVNLzJhe0ZIvY19YY8Gn2wqxr8QIq9MDs92JcpMDLnfT/f4cAK2KR3y4EuFqFfQaBSZkxeCqkT1goEG+fjtWZcKty3aiuM7W6qJpQFMLXVy4Es9cPAjT+lERQ0KXxeHG17tOYMWeE8ivscDq8LQ5269GwSM6XIkpvWOxYGw6shN8P96SrqugxoJPthRg8/E61JgdsDrccJ68p7r5nMPzHJQ8D51GjuQILWb0T8AVI1Nh0Ph3zvH2/E2FjBfqLU5sOFqNnYV1KKqzwmxvmixKEETwHAe5jINOLUd6dBjG9IzGeb1jEc5ogG97qhrt2HgyrxN1dlhcLrgFEaIAyDgOMhkHg0aJnjFajO4ZjfOyYqFR0gBfFo6UG/HMT7nYU1wPx8kJExUyDr3jdbjv/N44r3dcJ2dICBtOt4DNx2uwJb8We4rqUVxrhcXlgccjgOOappiI1akwMMWAEWlRmNQnDskRbLvUSddQZbJjw9FqbC+sxbFKM2otDjhdAjwiION5aBQ8EiLU6Buvw7jMWEzIiglo+goqZE5iUci0xLK7cPCEEbuL61FrdsItCCe/xGqMSI9E/yQ9tD7eqs1Cg9WJA6VG7CqqR4PVBY8gQCnnkaBXY3h6FPol6mnOGEJIQJxuAUcqGrGzqA6l9TY43B7wHAe9RoFhPZrGw0jZCk26jnpL0zlnd/Hp55xEgwbD0yLRl9E5hwqZk1gWMqcSRREeQYSM55iPgwlEc15yGQ1/IoRIx+0RutzxjwSflOccb8/fwW8+6Ca4k11KXU1XzYsQ0r3QxRIBusY5hz6JhBBCCAlZVMgQQgghJGRRIUMIIYSQkEWFDCGEEEJCFhUyhBBCCAlZVMgQQgghJGRRIUMIIYSQkEWFDCGEEEJCFhUyhBBCCAlZVMgQQgghJGRRIUMIIYSQkEVrLfnB4fbA5vTA6RGgksmgVcmg6ALrjthdTXm5hK6VV3flcDjw+/F6HK9shEsE0qO0mJgZAz2tAEy6MadbQGWjHRa7Gwo5j+gwJSK0ys5Oi3QCo9WJOosTNrcHOrUCsWFKqJXBLyuokPGSKIo4UW/D3uIG7Cyug8XuhtsjQiFvWsZ+VHoUBqdGIl6vCupqsKIoorDWij3F9dhb3IBGmx0Opwi1kkO0XosxPaMxMMWAOJ06aDl1d4dOGPHAt/twuKwRwhk/4wD0iNbgyXn9MalPfGekR4gkCqrN+GF/OdblVqLGZINbEMFzgEatxKCUCMwekICJveOglNPFU3fmdgv443gNVh0sx57iBljsTng8IuQyDpE6Nab0icOsAYnITmx7tWrWOFEUxaC9Wifwdhnw9pTUWbH6YAX2ltQjv8aCeosTdrcAURTBcxzUChmiw5ToFReOYT0iMWtAAuL00hcOx6vN+PlgBTYfq8KBskY02t0QTvlryjkgOkyJUT0jMaZnLGYNTERUGF05+cvhcGDavzfhRIPdq+31Kh7f3zke6bHB+0ITwlp5gw1L1x7FlrwqlJuccJ1ZvQPgOUCnkaFvggHXjk7D3MFJwU+USO633Cp8sKkAB0vrYbR5zrqQA5rOO/F6JUZmxOCeaVnIiA33+/W8PX9TIdOB3AoTPttahM3Ha1BnccHicMHlwWl/QA6ASgZoVQrE6VWYkBmD68amIy06jNnvcaZ9JQ34cEs+Vu+vgM3d/p+QAxClVeCq0T2wYHQakiI0kuXVXVWbHJj0r99gbe0o3g4ZB3x80yiMy4qVKDNCpHOsshH//O4QdhTWtlrAtCZJr8AtE7Nw04QMaZMjQfXFjmK8sfYoShocXm0v44ChPSLxzwv7YVBKhF+v6e35m9oA21FYY8FHmwux/mg1TtRZUWd1wXFGEQMAIgC7B6izulBUbcba3Cp8tLkQlSbvrtx9daSiEf9dfxw/7CnvsIhpzq/W6sJHmwvx4aZjqLM4Jcmru3I4HJj6ku9FDAB4ROD697fjRH2jBJkRIp3yBhv++d0hbCvwvogBgDKTC2+vP4ovdhRLlxwJqp/2l2PpL7leFzFA07FvV1E9nvwhBwXVZgmzo0KmTQ63B1/uLMGW47WoNNpg93i3n80DVDRY8fuxGny98wQEgW2Dl9nhxmdb8vFzbgW8qGFO0+jw4Ovd5VixtxTdvCGOqRs+3I1Gp+9FTDO3CFz+1naGGREivaVrj2JHYS08fhwqqsxuvLXuKI5WUgEf6sobbFj6y2GUm1w+7ysC2F1cjxd/PgJB8P8Y2pEuXch4PB48+uijyMjIgEajQa9evfDUU08F5SR8uLwR+0oaUGtxwuFlEdPM5m7qith3omlMDUsHS41Yn1cHp485Nau3urAlrwZlRmlai7qjHYV1AccoN9mpVYaEjOPVZmzJq/KpJeZMJxocWLm/jF1SpFP8eKAMBXU2v/cXRGBPYS0OlBoZZnW6Ll3IvPDCC3jrrbfwxhtv4PDhw3jhhRfw4osv4vXXX5f0dUVRxI6COpQb7bA63H7FsDhcKDp5NxErgiBie0Edyo1Wv2OIAHYV12Mvw7y6s3+tPuzXFWlr7vvfATaBCJHYyv3lKDcF1gXtFoB1R6rQaPf9Sp50DU63gF9zquDy88K5WZXFhZ8OlLNJqhVdupDZvHkzLrroIsyZMwfp6em47LLLMGPGDGzfLm0zfZnRjv0nGtBgdfrcfdPMKQB1Fid2FNbBaGXzRS6otWDzsSq/W2OaNdhc2JxXBVuggc4Bn21n18+/m4pHEgLsTjfW5VYG1BrTLL/ajF9zqgIPRDrFxqNVOFzeEHAcQQR+O1yBBqs04zO7dCEzbtw4rF27FkePHgUA7Nu3D5s2bcKsWbMkfd06sxOVjQ64PIF9kx1uAdWNDtQx+uPVWZwoCaCJr5kgAmUmJxpsNOi3I402/1rkWuNvUUxIMFVbnKg2BX6cAQCbS0BJvf8tyKRzFdfZYA1gfOCpTDY3TtSz+VydqUtPiPfQQw/BZDIhOzsbMpkMHo8HzzzzDBYsWNDmPg6HAw7HnyOrTSaTz6/rcHvgEQS4PYG1WIgQ4XB74HCzaflwuAQmV0kA0GhzwcEqWDfGeKw2HA4HVCqa+Zd0XY12FzysBmaKoJbfEGZzecBqSKrN44HZzu7C8FRdukXmyy+/xKefforPPvsMu3fvxrJly/DSSy9h2bJlbe7z3HPPwWAwtDxSU1N9fl0Zz4EHB5lMFkj64MBBxnOQ82xm+pXxHALL6E9KeVNupH2sJ2mmIoZ0dSq5DDyrDz4HKGR0nAlVcp5jdgxUcBwUEs363KULmb/97W946KGHcNVVV2HgwIG47rrrcO+99+K5555rc5+HH34YRqOx5VFSUuLz62qVcmhVgX+ZZRwHnUoOtYJN+aFVNq2fFCgOQJROCa2SVVnUfbEqQgkJFZEaJTRqNjOAN83426Ub/kk79BoFeEbHQI1ChiitgkmsM3XpQsZqtYLnT09RJpO1ez+6SqWCXq8/7eGrtGgtMmPDEa6S+/0GyQDoNXL0SdAj0cBmJt2esWEYlR6BQD9XKjmHwclRtFyBF/omsVteIE5HrTGk64sKV2JQsiHg4wwAxIcrMT4zJvBApFNMyIpBsp7NcatfcgTSorVMYp2pSxcyF154IZ555hmsXLkShYWFWL58OV555RVcfPHFkr6uWiHD2F4xiA5Xwt+FPJVyIE6nxuie0cy6cHRqBcZmxsOgDuwKJyMmDCMzooK6uGWoWnrFIGax7p7ai1ksQqQ0e2AidJrAWmx5DhieEY1+iQZGWZFgS43UYlxWXMBFrVbJY2b/hLMaJljp0oXM66+/jssuuwx33HEH+vbti/vvvx+33XYbnnrqKclfe1CqAb3jddBrlPC1i1fOARFhamQnhGNAMtsv8dAeERiaFgl/P1dyDpiQFYu+iTqmeXVX6bF6Ji0pKhlw7Vhae4aEhom949A3IbBjV7iaxwUDEhllRDrLrAEJiNIGdvGcFafDzP7SfRa6dCGj0+mwdOlSFBUVwWaz4fjx43j66aehVErfJRKnU2Nadjyy4nWI0Cq9fqNkXFPTbN9EPWYMSES4im3/cEqkBnMGJqJnjO9NdDwHjOkVhZn9E6CS0/gYbz15Ub+AY1w3Jj3wRAgJEqWcx7Wj05Co829Mg1IGTMyKw7TseMaZkWAb1ysaU/smwN8hlTFhclw5sgfCA+xJaE+XLmQ624z+8bhwUBL6xIcjRqeEUoY2W0J4NF11x+pU6JtowMVDkzFBgr5hjuMwd3ASrh+XgZ4xWq9bZmQcMCotAgvHZWB4WiTzvLqzCwYkYfHknn7vP6l3DP5xYX+GGREivbmDk3DLxEzEhft2AlLKgHG9YvD4vP5QSnSXCgkenufx6Nx+mJod73MxE6Hmce2YdFw1MkWa5E7ixG6+eqC3y4C3xeURsOpABX4+WIbjNRbUWZww25xwC4AoAhzf1F2j16oQFaZCVnw45g1OwpQ+ccxGe7fG4fbgh31l+HZXCQ6WmdBo96C1P6SMA6K0SoxJj8LVY9Mwtlc0jY3x09I1R7D0t2M+7TNnYALeXDBcoowIkd7n24vxzvqjONHggLud6WV4rqk76bzMODxxUX/EhKuDlySRnNHqxNMrD+OXnDIYbUKr55tmMh5I1Clxw4SeuHl8ht9jY7w9f1Mh4wVRFFFYa8Xe4nrsKKjD0SozbC43PIIIOc8jTClHn4RwjMqIxpAeEUiO0ASlWBAEEfk1FuwprseW41XYXtAAm8sDjyBCxnOIDlNidHoEJvSOx+DUSCQY6MASqL3FdXjg6wPIqzK3+0VOiVDjoQuyMXdIctByI0QqRysbsXJ/GX7LrUJ+tRl2t9C0cBvXVMDEhysxLD0aswYmYlp2PLXEdFNut4ANedVYdbAcW49Xo7LRCY8AQGyac0sh59AjQo2p/RIxd1BSwGNEqZA5iUUhcyqjzYUjFY0wO1xwukWo5Dz0GjmyE/QIYzwexhf1FieOVDbC6nQ35aXgEaFRIDtBDw3NF8Ocw+HAg8tzsOV4LRzuptkvlXIefRJ0+PcVQxHL6JZFQrqSRrsLv+ZUoaTeCpvTA4WMg04tx/isGLo76RxzvNqM9blVMNmbzoVqJY8EvRoz+ycgQstmHCsVMiexLmQIIYQQIj1vz9/U/kcIIYSQkEWFDCGEEEJCFhUyhBBCCAlZVMgQQgghJGRRIUMIIYSQkEWFDCGEEEJCFhUyhBBCCAlZVMgQQgghJGRRIUMIIYSQkEWFDCGEEEJCFhUyhBBCCAlZnbfKIWHO5RFQb3VCEJoWMIzQKMDz0q/CfS6rMdtRYXRAEEVEhyuRqFf7vWQ9IYSEEqvTjcJaC9weEWEqOdIitZB3wsrnVMiEOJvTg5xyI7bl1+FAaQMa7W54BEAp5xCpVWJEWiRGZEQhK04HGRU1TByrbMTyXcX4ek8ZasxOCCeXXeU4QKeS46JBcbh4RDoGpxioqCHdyok6M/75XQ4Ka62wuz2Q802rX18/Nh1XjuzR2emRIKgzO/HTgTKsPliBvGoz7C4PRBGQcUC4WoGhPSIwZ2ASpmTHQRmkooZWv/aRw+HA37/PweHyRtidArQqOUb0iMBDF2RBpVIxyNg7oijiwAkjPt9RjJwyE8pqjai2nb6NDEBqtBbxehVGpkfh6tFpSI7QBC3H7qbR7sKzP+bgmz0n4PS0v62MAyb2jsXzlw5CvF4dnAQJkcjyXSVYuvYYiuusaOuEEabkMb1vAp6Z1x/hYcqg5kekJwgCvt19Am+uP44Kox12l9DqZ0HOc9AoeGQn6vHI7L4Y2iPS79f09vxNhYyX9hbX4W9f7cexakurfzyeA/onGfDK5YOQlRB4wdQejyDih31l+HhLIQ6XNsDawUkVACJVwIiecbh9ci8MT4uSNL/uqKTeioX/tw3Ha6w+7ReplePDG0dhcKr/X2ZCOtPV727Flvxar7fXyDl8cdsYDEql40x3YXe68cSPh/DdnjJYXYLX+8XqlLj//N64clSaX6/r7fmb2r298PKaw5j/ny3Ia6OIAQBBBA6UGjFz6e/437YiyXIRRRE/7ivDexvzsbvYuyIGAOodwKajVVj6ax72n2iQLL/uqMZsx7XvbfG5iAGAeqsb1/13G3LLTRJkRoi0Lnztd5+KGACwuUVc+tYW7C+pkygrEkyCIODJH3Pw7W7fihgAqG504vlVuVixp1Si7JpQIdOBN37Lw+u/5Xu9vQDgoeUHsWJ3iST5HCoz4uOthcgpN7VZVLXF5gF259fg3Y35qDU7JMmvO3rgy70oqrP7vb/J4cFfPtkJp9u3gwAhnekvn+zEgTL/CnCXAFz5zlbUmZ2MsyLBtnx3KVbsKYXDz+NXvc2Nf/2ci4JqM+PM/kSFTDtO1Dfi5TVH/dr3r1/th8PBtlhwuD34YkcJcksbfC5imlk8wMFSI1YdLGeaW3e1Ka8a64/6dkXamoJaG77aJU1xSwhrZosTPx+qDCiGzS3i7yv2M8qIdIYGqxNvbTjuc0vMmSpMDryx7hijrM5GhUw7lvxvv98Fg0cEHlyewzSfw+WNOFhqgtkdWJySWis2Hq1BDbXKdOjz7YVg1Y7ywaZ8uKlVhoSAv39/qOVuvECsz60KPAjpNKsOVqC0wdbxhh3wCCJ+P1qN4xK1ylAh0449xQ0B7f8z41aPXUV1OFHTEHAcD4DiOguN2+hAg9WJtYermcXLr7ZiX6mRWTxCpPLr4QomcWxuEZ9sLmASiwTfmkMVsAfYGtOswebG2hw2n6szUSHThnfW5cET4BWJzS1icx6bE6EgiNhX0oCawItjAEBFvRnHqqTrs+wOcspMsLvZ3dQnADha2cgsHiFS2F9SB4uTXcvhR1ulu/mBSMfudCO3otHvXokzOT0C9kt0IUeFTBv2nGDzhm8vYDNyv9HuhsnmYvahsruAkjrf78I5l5TUs39/yhk00xIipUNlbIvtRkeAfeGkU5Qa7bC72P7timqlOedQIdMGm8vL+5o7YLS5mMTxiCKTPutmgthUIZO2SfH2WO00Lol0bSY72zuNPCwPXCRoXG6B6TkHAFyBdnO0wa9CprKyEtdddx2SkpIgl8shk8lOe3QHkVo2M1MmR7KZSVcp56FgON2znAfC1bRCRXu0Svaf5YhwmlmZdG2Jei3TeMGapp6wpdPIIWe8rE24Wpr6wK8z2cKFC1FcXIxHH30UiYmJ4Ljut4bPFcNTsGJvWcBxLhgYxyAbIEwpQ4JeDSUHOBkUtVoFkBUXHnigbixTgvcnPTqMeUxCWBrV0wAOYNaNnWig4j0UJerV0GsUqLWw6VXgAPRPNDCJdSa/CplNmzbh999/x5AhQxin03WMy4pFuJKHOYBBbwk6NVIidUzy4TgOo9KisCW/FvnVloDjpcQa0DOWTW7dVe94HaLD2H2RlTJgcEoEk1iESCXBEI6kSDVK6/2fBPJUT8zrxyQOCS6e5zEmIxoldTa4GfQxaZQyDJFoqRa/2vxSU1PRzZdoAgBcPjw1oP3/OjOTUSZNhqRFIJnB1U24HOgTr0N2AhUy7VHKeVwzIplZvKl9Y5EazbbZnhAp3DKhJ5M4iXoV+iVFMIlFgm/2oESEMepiT9SrML0fmx6KM/lVyCxduhQPPfQQCgsLGafTtTx0QRa0Cv/6d2PDlbh8hH8LZbWlR5QW5/WOQUyAiymnRIdj9sBEqBXdYzyTlK4YkwE1gz5+ngNuHNeLQUaESO/G8Rl+H/tOtXA822MgCa6xGdEY0iMi4DgqGYfLR6RCp1YEnlQr/PqkXnnllVi/fj169eoFnU6HqKio0x7dhUqlwpr7JsDX77NWwWPtkonM8+E4DpcMS8G4PonQ+zkWOU4DTO+fgHGZMWyT66ZSI7X4+6ysgONcNjQZo3tGM8iIkOB4/pJBCGSsZ/8kHW6bFPh3h3QeuZzHw7P6ItHg/9UzD2BwagQWjktnlteZ/Bojs3TpUsZpdF0pkTqs+9tEzFm6CUZHx+NlEvVqrP/rBKhUKknyiQlX4Y4pmbC7BGw7XgmjD3fzxmmAC4ak4cZx6VDI6E4Cby0Y2xO5VWZ8us2/FVxHpUfi8fkDGGdFiLTmDU1GqdGKf/181OfbcNOjtFh++xhpEiNBlZ2ox99n98UTPxxCtY+LgPIA+iTo8Nylg6BWSneXLCd288EuJpMJBoMBRqMRer0+oFg/7i3F86tzcaLh9EFwHICeMWF46qL+GJcVG9BreOtYVSP++3sBdhTW4UStBe3VWHoFkBytw4z+Cbh+bBqiw6UpsrozQRDw6i+5eHWdb9Otzx6QgBcvG0y3upOQ9f2eUjz4zT7YvJjlmgMwKiMSX9w2TvrESFCtOVSBZ386jBP13g3+Vcl5DE2NwDOXDESvWP/uAPX2/O13IePxeLBixQocPnwYANC/f3/Mmzevy80jw7KQaeZwOFBc70BRnRWZsVqkx7KJ6yuzw43fcirxy+FKFNRYUF5rglsEnB5AJQcMYRpEh6vQN1GPWQMSMKZnNOTUEhOQnYV1eP6nXOw5Ud/mhHk8gMz4MPz1/Gyc3y8OPE/vOQl9b63Pw0ebi1Bhcpx1a7ZKzmFsz2g8Pb8/UqJoWofuqrzBhjfXHcPa3ErUW1ywn7EIrpzjoFLwSIpQ47JhKbhhXHpALTGSFjLHjh3D7NmzUVpaij59+gAAjhw5gtTUVKxcuRK9enWdQY1SFDJdTaPdhaOVjSiosaC4zgqHS4BOLUdGTBjSosPQO15Hk1IxJAgCDpaZsOFwOdYdrUG5yQFRBKK1ckzoE4vzMuMwrlc0FTCkWyqsNmNTXjXKjXaEa+ToGROGmQOSOjstEkSlDVasO1yF/ScaUFBrgdMlQqeRIztRj0EpBkztE8+kFVrSQmb27NkQRRGffvppy+De2tpaXHvtteB5HitXrvQ/c8bOhUKGEEII6W68PX/7VTJt2LABW7duPe0OpejoaDz//PMYP368PyEJIYQQQnzmV9u3SqVCY+PZK6SazWYolWzWKCKEEEII6YhfhczcuXOxaNEibNu2DaIoQhRFbN26FbfffjvmzZvHOkdCCCGEkFb5Vci89tpr6NWrF8aOHQu1Wg21Wo3x48cjMzMTr776KuscCSGEEEJa5dcYmYiICHz33XfIy8tDbm4uAKBv377IzGS7thAhhBBCSHsCuj8qKysLWVk0BTUhhBBCOofXhcx9992Hp556CmFhYbjvvvva3faVV14JODFCCCGEkI54Xcjs2bMHLper5f8JIYQQQjobrbVECCGEkC7H2/O3X3ct3XTTTa3OI2OxWHDTTTf5E5IQQgghxGd+FTLLli2DzWY763mbzYaPPvoo4KQIIYQQQrzh011LJpOpZQK8xsZGqNXqlp95PB789NNPiIuLY54kaZ8oiqg0OVBhsqPO4oBHAJRyHjHhSiRHaBChpdmWWXN5BJTW21BpsqPR7oYIIEwpQ5xehZRILdSKrrUKPCGEsCIIAg6UGpFb0YiyBhtcHhFapQw9orUYnBKBtOiwoObjUyETEREBjuPAcRx69+591s85jsMTTzzBLLmu5miFCa+uzcPW/FpYnR4IIiDjgDCVHBN7x2LJ9EykBnEJe0EQcaDUiGd+PIjtRcZWt5FxwLWje+DGCT2RHhPcD1d3ZHN6sL2wDouWbYfD0/o2PIDnL8zEjKEZVESSbuNEfSPu+98B7C6uh/uUkZUcgDidCvdOz8JVo9M6LT8iPbdbwDd7TuCL7SXIKTfB4RZw6iBbDkC4SoaJWXFYMKYHxmXGBCUvnwb7btiwAaIoYurUqfjmm29OWzRSqVQiLS0NSUldazl3FoN9txfW4snvDyG3ohFuoe3tlDwwKDUSz148AL0TpB1YXG9x4tp3N+NQpcXrfRaOTcHDcwZAJafWAn8crzZj+ssb4Mvo+A+u6YfJA9PBcZxkeREipRP1jbj8re0oN9k73FYlAxaOz8DDs/sFITMSTMerzXjg633YV2KEW+j4KKiWc7h8eAoenNUP4Wr/pqzz9vzt111LRUVFSE1NBc/7NcQmqAItZFbsOYFHVxxEY1uX362I1Cjw6tVDMLG3NN1s1Y0OTH95HYx273NqNi4jAu/fNIa6Pny08UAhrv/0kF/7/m16b9wxLZOKGRJyNudV4/r3t5/WAuONqX1i8f6No6RJigRdTpkRiz7ehRP1Z4+NbQ8HYEJWDP6zYBh0aoXPrytpIdPMarWiuLgYTqfztOcHDRrkb0jmAilk1uZUYPGnu+BHvQC9Wo6PbxqFwT0ifd+5HTanB5Nf/A2VZmfHG7fhkiEJePnKYXRi9VJxrRUT/7UuoBgfXNMPUwZlMMqIEOkVVpsw7ZXf4fHzDDFnYALeXDCcbVIk6GrMdlzx9hbk11j92p8DcOHgBCy9cqjPjR+S3n5dXV2NuXPnQqfToX///hg6dOhpj+7AbHfjr1/t96uIAQCT3Y3bP90Ft9vNNK+X1+QGVMQAwLd7K3CozMQoo+7N4fZg6kuBFTEAcONnOWiwBvZ3IySY5r3xh99FDACsPFCB1QfL2CVEOsXzPx32u4gBABFNn4UfD5SzS+oMfhUyS5YsQUNDA7Zt2waNRoPVq1dj2bJlyMrKwvfff886x07xn/V5aLC5AopRYXTgm93svsg1Zgfe31TIJNZdn+2Cx4t+znPdgRNGn5vV2/Lznnw2gQiR2K85FTA52hkQ6KWnfzzMIBvSWXLKjFh9sDLgOB4BeGvdcbjbG2QaAL8Kmd9++w2vvPIKRowYAZ7nkZaWhmuvvRYvvvginnvuOaYJlpaW4tprr0V0dDQ0Gg0GDhyInTt3Mn2N1vywL/ACRATw8dbCgOM023KkDKw+BgW1NhyvNjOK1j2Jooi7P9vFLN7DPxyHzelnEx8hQfTUyhwmcU402FFtcjCJRYLvh70nYGF0zDpebcbGYzVMYp3Jr0LGYrG0zBcTGRmJ6upqAMDAgQOxe/duZsnV19dj/PjxUCgUWLVqFXJycvDyyy8jMpLtuJMzrc2pQGl9xyP0vZFb0YijFWy6cZ74KY9JnGY/7qVm3/bUW10oM7HrDhIAlDb430RLSDCYzA4U1/o2qLM9f/1qL7NYJLhWHazy6S7N9jg9IjYf70KFTJ8+fXDkyBEAwODBg/HOO++gtLQUb7/9NhITE5kl98ILLyA1NRUffPABRo0ahYyMDMyYMQO9evVi9hqt2ZBXzazlwy0Avx2pCjiO3eVBrSWwrq4zfbu7hGm87qaqkU0xe1pMujolXdzGYzXMTl4AcLicxuOFojqzE9VmtsernYV1TOM186uQueeee1Be3jRw57HHHsOqVavQo0cPvPbaa3j22WeZJff9999jxIgRuPzyyxEXF4ehQ4fivffea3cfh8MBk8l02sNXDVa2A3QbGBQgVqeH6cEFAIw2tr9nd2Px4ZZ7b5VW1zKPSQhLx6rYdjk7JRoXQaRVY3EwH0dZz/hivJlfs9Rce+21Lf8/fPhwFBUVITc3Fz169EBMDLuZ/PLz8/HWW2/hvvvuwyOPPIIdO3bg7rvvhlKpxA033NDqPs8991zAswvLeLa3JbOYbkeKG6VDYBqgTiXF3ekRhgj2QQlhSC5ne2CgWR5IM8an1j/j+rqDy+VCr169cPjwn6PRtVothg0bxrSIAZrWcxg2bBieffZZDB06FIsWLcKtt96Kt99+u819Hn74YRiNxpZHSYnv3ScRGv9mIWxLdJgq4BhhKrl/zWftiArzfYKic4nez9kogx2TEJYy49guZUIziYemRIMacsaVR5w+8HNha3w+NyoUCtjt7McOtCYxMRH9+p0+1XXfvn1RXFzc5j4qlQp6vf60h68uHJwEOaO/n0bBY/bAwMcNKeU80mM0DDL6080TejKN193E6tQdb+SjOD37mISwNCUrmulF09he0QyjkWDRqRVIjdIyjTk6I6rjjfzg1+d18eLFeOGFF5hP9nam8ePHtwwqbnb06FGkpUm7MNmwtCj0jGVzVTI4NQKJEWwKkKfms50x+TyJllDoLvRqOYam6JjFU/JAMqPPAiFSUalU6JPI5nPPAXjhYlp3KVRdOCSJWXeQWsFjQlYsm2Bn8KuQ2bFjB7799lv06NEDM2fOxCWXXHLag5V7770XW7duxbPPPotjx47hs88+w7vvvovFixcze422XD4iNeAYPIBbJ7Cbln5gigGslkgamWZAD8bVdnfDcRyenD+YWbx/ze8NJePxB4RI4aVL2Xzus+LCoVJJ051ApHfhwCTo/VgjqTWDkg0YkSbN1Cl+HVUjIiJw6aWXYubMmUhKSoLBYDjtwcrIkSOxfPlyfP755xgwYACeeuopLF26FAsWLGD2Gm25cVwaEg2BfQEz48MwrV8Co4wAvVqBp+b1ZxLrxcuH0lpLXuiXpIdexab4OH8IrbVEQkP/FAOSDIF1g3IAXrxsIJuESKdIjdbimlGpAd9sopRxWDK9t2QLTQe0aGQoCGTRyJwyI655b5tfSxXE61X4YfEExAV4MDiT2yPgyrc3YVdJo98xHp6Ridum9mGYVfdW3ejAyGd+DSjGr/dNRGYcu24qQqTmcDgw5Km1sPm5RseSqZlYMoOOM6HO6nTjuv9uw67iBr/2l3HAovN64sHZfX3eV9JFI6dOnYqGhoZWX3Tq1Kn+hOyS+iUZsOzGkYgNV/q0X0qEGl8sGsO8iAEAuYzHslvGITvevzE8t0/IwC2TezPOqnuL1amw4W+T/d5/2YJ+VMSQkKNSqbDxgWkIV/p+mlg8uScVMd2EVinHG9cMw6Bkvc8tMzKew2UjUvBXiT8LfrXI8DyPioqKlmUKmlVVVSE5ORkulzST3vgjkBaZZuUNNjzxwyFsPl4Lk73tAc5RWgUm9YnDY3OzEREm7d0pdpcHj367F1/tqfBqexkHvHrlIMwelAJeqpv5u7mqRjumv7TO68X05Bzw618nIz2G7e2shASTw+HAde/vwq7i+g5Xw44NV+Kxuf0wd0hycJIjQVNnduKZlYew8kAF7B1McsgBMGgUuHtqJq4fm+733ETenr99KmT2798PABgyZAh+++03REX9eSuVx+PB6tWr8c4776CwsNCvpKXAopBpZre78fbv+Vh1sAxGmxtOjwCVjEdUmAKXDEvFDWN7QC4P7jwhJXVW/LD/BP79Sx5crUxEG6GW46kLe2NCdjIiw3xrWSJn8wgicspMeOSbvThQ3voMqAl6JV6/ZjgGJhugZjU6m5Au4LmfcvDljhI02t3wiE0TnMl5oG+SAUuvGIT02MCOsaTr23q8Fl/uLMa6I9Uw2V0QhaYFkjmu6YI5Tq/GpcOScfHQFGTEhgf0WpIUMjzPtwwQbW03jUaD119/HTfddJMfKUuDZSHTldldHlSZHKi1OCCIIpQyGWJ0SsSEq6CQ0Z0yrImiCJPdjSqT/WQrnQitUo54vRqRWgUNpCaEdGsNVidyykwoqbfCLYjQKuToFReG3nHhUCvZXNB7e/726dUKCgogiiJ69uyJ7du3Izb2z3vClUol4uLiIJPRFWhnUCtk6BGtRY9ouqU6GDiOg0GjgEFDsyMTQs49EVolxmWync3fXz4VMs0T0QkCLQJGCCGEkM7nV5/DsmXLsHLlypZ/P/DAA4iIiMC4ceNQVFTELDlCCCGEkPb4Vcg8++yz0GiaplrfsmUL3njjDbz44ouIiYnBvffeyzRBQgghhJC2+DUip6SkBJmZmQCAFStW4LLLLsOiRYswfvx4TJ48mWV+hBBCCCFt8qtFJjw8HLW1tQCANWvW4PzzzwcAqNVq2Gw2dtkRQgghhLTDrxaZ888/H7fccguGDh2Ko0ePYvbs2QCAQ4cOIT09nWV+hBBCCCFt8qtF5s0338TYsWNRXV2Nb775BtHR0QCAXbt24eqrr2aaICGEEEJIW2jRSEIIIYR0OZJMiNds48aN7f584sSJ/oQlhBBCCPGJX4VMa3cmnTolu8fTyqI/hBBCCCGM+TVGpr6+/rRHVVUVVq9ejZEjR2LNmjWsc+ySPB4PnM6uV7C53W7Y21mhm7AnCALNdk3OOU6nhy5aCURRhCB07ggVv1pkDAbDWc+df/75UCqVuO+++7Br166AE+tqPB4P1h+txpfbCrGtyAiz3d2y4qdBrcDYnhFYMKYnxgZ57Qm3241Ptxfj4835OFbjOOvnE7NicNP4DEzOjgtqXt2Z1enGr4cr8dKqHBQ3OE/7WYQSeHDuQMwakIAILa02TrqPnHIjPt1ahJX7StFg/7NwV3DAiDQdLhmRgYsGJUGppPX2ujNRFHGi3ob9Jxrwa04lSo02OF0CwlQy9EnQY0p2HAYkGRAZFrzjH9PBvrm5uRgxYgTMZjOrkAFjMdh3W0EtHvxmL4pq7GjvzeIA9E0Kw0uXD0W/xLOLPda+3VWCv321H95cE8VoeHx4y1gMSI6QOq1uSxAEfL+vHEu+2OvV9n8ZE4t7546AUk6rj5PQVWG04d7Pd2BLYWOH2+pUwNPzh+CioclByIwEW7nRho+3FGH1wXKUNdhhd5/dEq1TydAzNgxXj0rDhYOTEKbyfyVsb8/ffhUy+/fvP+3foiiivLwczz//PNxuNzZt2uR7xhIJtJB57dc8LP31KHzpOFDwwD8v7I/rxqb7/HrecLvduPX9zViX3/GB5UyPzumLm8/rKUFW3ZvZ7sZFr23A8Tq7T/upeGDjQ9MQr1dLlBkh0lmXW4lFH+2Ey8ee07n9ovHqgpGQyah1pjsQRRFbj9fgn98fwrEqS7sX9M1Uch7jM6PxxLwBSI3S+vW6khYyPM+D4zicueuYMWPw/vvvIzs72/eMJRJIIbP0lyNYuvaYX6/LA3jiImmKmeve3oDfC/1v9Xpsbl/cOIGKGW/ZnW5MfP5XVFn9Gw/AA9j6yDTEUTFDQsimvGpc93/bvTpptWZqVgTev3k805xI5/gjrwp//WofKkzOjjc+w6j0SLx8xRC/ihlvz99+tXkXFBQgPz8fBQUFKCgoQFFREaxWKzZv3tyliphAbMqrxmt+FjEAIAB48odDyCk3sksKwLLN+QEVMQDwxI+HcbTCxCij7u/W97f6XcQATZ+FGS+vpQHBJGTUm524+UP/ixgA+C2vAW/+eohZTqRzFNda8eh3OX4VMQCwvbAez6zMgd0l3cBwnwsZl8uFm266CU6nE2lpaUhLS0NqairU6u5ztenxePDQ13t96k5qjUsAHvhqL4uUADR1bzz2/WEmsRYt28IkTneXU27E74WBF6MNDuCXnCoGGREivX9+uxsOBuedV34tRJWJ1t8LVW6PgDd/y0N+jSWgOOuPVuPXQxWMsjqbz4WMQqE4a4xMd/Pj/gqcMPpXfZ4pp8yMnQW1TGL9Z30ekzgAUFjvxsHSBmbxuqsP1x5gFuufy/cyi0WIVGrNDvyUw+aY5QGwbEsRk1gk+PKqzNh4rCbgOHaXgE+3F8PikGZqEL+6lq699lr83//9H+tcuoyvdhQwiyUA+GRrPpNYn25hlxcAvLX+ONN43Y3Z7saXB9l1DVZaPMgtpy490rV9sbPYqzshvfX5drbHLRI8m/KqUWs+e1oPf+RWmJAr0ZAGv+6LcrvdeP/99/Hrr79i+PDhCAsLO+3nr7zyCpPkOsuuEt/vBmrPtvyGgGO43W4YHWwnHVpzULqmvu7gSCXbzwEAHC5vRHYirflFuq71RyqZxquzCKg3OxEZTvMqhRJRFPHzoQo4PWzOO/VWN/YW12N4WhSTeKfyqZDJz89Heno6Dh48iGHDhgEAjh49eto2py5VEIrqzU44fL3XsAO11sC7qfaXsq9kXd16udDAFdawnw+pqC6wvmZCpJZXwb6A33uiHlOy45nHJdIx2dyot7iYxjwsUYu0T4VMVlYWysvLsW7dOgDAlVdeiddeew3x8d3nA2p2ugIaqd8aFjer1FvYjNkh3mttsqdAVVTVAOjNPC4hrEjxuTfTsikhx+kR4GZ8p2UjixHkrfBpjMyZ88asWrUKFkv3usLUKuVg3abEMZjYVadVBB6E+EQlYz8jb0JccJewIMRXaglmotaqaGK8UKOQcZDzbD8LYRItXxFQlgxXN+gyosNVUCnY/vEiNYH3DQ9LYb/kgf8TR58b0mPCOt7IR6mRGuYxCWGpV1w485hDUiOZxyTS0qsViGB8Ad0nQcc0XjOfztgcx501BibUx8S0ZlgK2zd7TEbgRYhcLoeO8Vi56f27T5egFLIT2A/K7ZtEA31J1zYlO4FpvAgtj+hwFdOYRHo8z2FG/3hmPRQRGrkkA30BHy/KRVHEwoULoVI1fSjtdjtuv/32s+5a+vbbb9ll2AkuHpGGPwrYzJXDAbh6NJvlAK4enYF3f2d3K+OiibRMQXvC1XLMyTZgZS6bW7CjNTyy46W5IiGElcuHp+Dln31bX649V41IZxSJBNuErFjEbSpAZWPgYzR7x+sku2PTpxaZG264AXFxcTAYDDAYDLj22muRlJTU8u/mR6i7eEgSEvVsmtT6JIRhbCabcRF3TGZXeCQb5BgmUXXcnfzl/IHMYj0xfzB4xn3OhLAWp9dgZjabYwMPYOH4dCaxSPD1jtdhfGZswHHUch4LRvdAeAArYbfHp6gffPCBJEl0NTKZDM9eMhg3f7gzoKsSOQ/867IhrNJCRJgaD83qg+dXHQk41ns3jGGQUfc3INmA4cl67Arw9vdwOTB7INsme0Kk8vRlw/Drs7/6vOr1me6a1AMJBhoXFqoUMh53Ts3EjsJalNTb/Y4zrlc0zu8v3fGPLg/bMCU7HgvHpvq9PwfgoVl9MTAlgllOAHD7pEyMSglsEOoDM/ugX1Lot5wFy8e3jUVkgF38v9w/lVpjSMiIDlfh7euGBxRjfIYed8/oxygj0ll6xobjiXkDEOfnhIZDUyPw2Lz+0Cqlu72Ejqzt+OdFg3DT2FSf3yQZBzw8Kxu3nCfNGJTPbp+Asan+FTP3nZ+FO6ZkMs6oe9Mq5dj48AzEaX2/dVAG4PcHpyAxgq5KSWiZ1jcBby0YBn9umJ2cacAHN46DTEa3XXcHU7Lj8OJlg5AerfV6H6WMw3mZMXjlyiFIi2Z/B+ipOLE73kN9CpPJBIPBAKPRCL3ev4FG63Ir8ffl+1HWwUKSHICesRr867KhGJYm/e2Gyzbn4/HvD3s1gV+4Anj/5jEYlR4teV7dlSAI+M/qPXhpo3dLO1w+NAZPXDxc0isRQqRWWGPGPZ/twL4ya4fbamTAPy8agKtHpQUhMxJsJXVWvP97PtYeqUKlyQFHK5MnapU80qPDcMWIFFwyPBV6tf/jTb09f1Mh4yWPx4Mf91fgm12F2F3cCJvLA1EEOA7QKmUYmx6BK8ekY3Lv2KBehdjtbry/pRCf/HEMZeazZ00clKDGoqnZmDsoOWg5dXeNdhd+PliBZ384gLoz1r9ScsDDc/thzsBExOnVnZQhIeztLqrHf9fnYt2xethOWd+EB9AnQYurR6Xj8hE9oJFo0jPSNQiCiMJaC3YX1WFNTiUqTQ64PQLUShl6xYZjRr84DEqNRJwu8OMfFTInsSpkzmS2OeHwiNAq5V3qi9tgscPmEqFTKxCuppYAqQmCAKtTgAgRYUoZjYMh5wSn04NGpxtyGQcDgwk/SehyewR4RBFynoeMZzuvnLfnbzrT+SlcowT7+S8DFxGmRkRnJ3EO4Xke4WoqXsi5RamUIboLXcCRziOX8Z1eSNARmBBCCCEhiwoZQgghhIQsKmQIIYQQErKokCGEEEJIyKJChhBCCCEhiwoZQgghhIQsKmQIIYQQErKokCGEEEJIyKJChhBCCCEhiwoZQgghhISszp5ZOOS4PQJqzE7UWhxwe0QoZDxidEpEh6mYrzPhiwqjFd/tKcP+MiMcLgE6lRzjs2Iwu28CtFr/Vx8lbVtzsAyfbS9BcV3TqsCx4SrMH5KEi4ckQK2mBSNJ9+N2u7HpWB225tei3uqEQsYjO0GHaX3jkRih6ez0SBC5PAKqGx2oszjhEUQo5TxidSpEaZXgg3wupEUjvVTVaMcfh0vxxE/H0GB3n/XzeJ0Sj87KxPg+yYgMC94iau9tPI5XfsqFrZ1t+ifpcf/M3pjSJz5oeXVXDY12XPv+dhwsb2x3ux5RGry9YBj6JUcEJzFCJJRTZsTLa45gbW51m9vEaYDbpvbFzef1DGJmJNjKGmzYeKQSr687jkqTHW7hz58pZRwGJumxZEYfDE6NgF4d2EU0rX59UqCFjMsj4JMtRXh6ZQ48XrxTKhmHl+YPxJzhKZJWpUU1Fkx/aT1cPuzTPxJYcd8MKBTUQuOP1349gld+PebTPhcOTMDrC4ZLlBEh0nK73fjbp1uw/LDJ633UHLDy3knoFdcVl9Ul/nK4Pfhg03G8/ls+LE5Ph9vH65R4/cpBGNkrDhzn37mQCpmTAilkHG4P7v1sN37KqfL5dW+dkIYHZ/WDXMZ+GNK+knpc9OZmv/ZVAtj7zxnU3eSjuz7dhR8OVPi1b79EHX66ZyLjjAiRltvtxoVLf8PhGl8ul/705e1jMCo9mnFWpDNYHG488NU+rDzo2zGQB/DURf1wzZh0v4oZb8/fNNi3DaIo4tFv9vpVxADAe5uK8Pa644yzAoxWl99FDAA4AYx9ag27hM4B//75sN9FDADklDfiuv9uZZgRIdK74Z2NfhcxAHDF21tR3tBepzcJBW6PgL8vP+BzEQMAAoB/fJeDVQfK2Cd2Cipk2vBHbim+3OP/yQsAXvr1KI5Wtj+WwlcXvBh4EWIUgZd+zmWQTffX0GjHq+vyA47z+7FabMqrZJARIdL7cX8p/igJvAiZu/Q3BtmQzvTz/nKs2Ot/ISICuOd/e1Fy8qYIKVAh0wq7y4MlX+cwiXXv57vgEdj03m05Vo1yO5NQeGPdcbhc/l9tnSuu+r9tzGIt/mwfs1iESOnBL/YyiVNrbyqKSGgy2V148qfDAcdxCcB/1h2FVCNZQqqQef7558FxHJYsWSLp6xwuN6HGwuYkn1NhQX61mUmsl9YcZRKn2Zsb2Hd9dTe5FWz+dgBgtLlwrKKBWTxCpLA2pwKWjsdyeu31VQfYBSNBdeCEEZWNDiaxvt9XgTIjoyvxM4RMIbNjxw688847GDRokOSv9e6GPGaxRAAr97PpH9xV3MAkTrNP1lMh056vdhQzj/n0T0eYxySEpffXsWmNbnak3gO3++wpK0jX99Z6dudCi9ODvUW1zOKdKiQKGbPZjAULFuC9995DZGSkpK8liiLWHalhGvPz7YGfECuM7PsXa+jY0q6vd51gHvNwhfe3sRLSGXYwGBtzpv2l9LkPNQ63B/tKjExjrtgnzaDfkChkFi9ejDlz5mD69OkdbutwOGAymU57+MLuEuDyZsIYHzQ6Am+n3VXUEHgixCdSNIOaW5lMkZCuxClBzJwyKmRCjdnuZn4uLGuQpmupyy9R8L///Q+7d+/Gjh07vNr+ueeewxNPPOH364lgPxiJxQAngdGAYeI9KQamWZxCxxsR0s14RPrchxrx5IMlD+PCqFmXbpEpKSnBPffcg08//dTrtWsefvhhGI3GlkdJSYlPr6mSyyCXsZ2RV6OQBRyjdzzNkhlsERr2kwZG0USEpIuT4qSQEqGVICqRklYpg4Lx7PSxehXTeM26dCGza9cuVFVVYdiwYZDL5ZDL5diwYQNee+01yOVyeDxnd9moVCro9frTHr6Q8Rx6xrD90k3qHfjsln0SDQwyOV3wVoQKTdOyY5nHzIgJYx6TEJYGxLM/MozvGcM8JpGWVilHYgTbxW+nZccxjdesSxcy06ZNw4EDB7B3796Wx4gRI7BgwQLs3bsXMlngLR2t+fucAUzj3TC+F5M4rEuZecOSGUfsXv4yKYN5zNsmso9JCEsXj2RzvGoWqwHU6i4/ioG04u4p7BYAVfIcxmeyvzgEungho9PpMGDAgNMeYWFhiI6OxoABbIuNUw1MNkAtZ9OkFhOmQHaCjkmsBy/uzyROs4dm9WYar7tRq9WI17O9Op0xIIlpPEJYu25MD6bxbp7ch2k8Ejwje8ZBp2LTYDAyPRI9Y6UZItGlC5nOYtAqcP90Nif5F+ZnQ81gjAwAXDM6nUkcoKmJL0ZH/dYdef2qocxi3cPw6oYQqcjlctw5hU2rDAfglvHpTGKR4EswqLFwXFrAcTgAD87uCxnjMTfNQq6QWb9+PZYuXSr561w3IQOZMZqAYozvFYHJ/VMZZdTku8XjmMR5e8EQJnG6u1E9YzC+ZxSTWPfO7MskDiFSu39mNiIYjEv/9JZRkMupWymU3T45C30DvNnk1vPSMTCZ/TjPZiFXyASLSi7DF7ePR7LBv66FvvFhePu6Ucwr0MGpkXhiXr+AYvx8zwQoFHT3jLc+XTQ24Bi5j09jkAkhwfPrg9MCmp/j77OzMU6iMREkeMJUcrx/0yhkRPt3YX/h4ETcNyMbHCdNawxAhUy7osNVWHnPJIxI862SnD0gDl/fMQE6tTTFwg3jMvDS5f4t1fDzPRMkuQOquyt8fg4Gp/j3vuU+Ps3r6QMI6SpiwtXY+o9piPPj/PXCJQNx60S2g4ZJ50k0aPDl7eMxzofWaQXPYcn0XvjXZYOZDa9oCydKtRxlF2EymWAwGGA0Gn2+FbuZIIjYX2rECz8dwtaChlYnCZJxwIx+sbhrWjb6JuokrT6bGa0u3PHpLvxxvOP1KxaM7oFnLh4oeU7d3Yo9JVjyxX6vtv3LpJ54cBZ1J5HQ93+/5+Pl1Ydh7WCS8mnZsXju4kGIM1Dh3h25PQL2lDTgjbV52FpQC4f77LOhXiXDVSOTccWoDGTGBdYl5e35mwoZH4iiiDKjHRVGG0qqGlBh8iDRIEOPuEgkRWgQp1MFpYA5k9XqwtubjmNHYT0OFdTBIQKpsWFIjwnD1OxYpoOESZPt+TV4YfURFNRYUGdtWindoJYjNVKDWyZmYP5QtmOjCOkK1udW4ZecShyrbkRhZQPClTyykmMwpEcErh2djnC6zfqcIAgiTtTbUNloR3mdGQ02D5IitYjVqZAUoUGsjs3Ed1TInMSykCGEEEJIcHh7/qYxMoQQQggJWVTIEEIIISRkUSFDCCGEkJBFhQwhhBBCQhYVMoQQQggJWVTIEEIIISRkUSFDCCGEkJBFhQwhhBBCQhYVMoQQQggJWVTIEEIIISRkUSFDCCGEkJBFK3z5wO7yIK/SjE+3FmDr8ToY7S5EaZWY3jcGFw1LQ2ZcOJTy4NeGX+8swnOrjqDW4jrrZ2nRGrx7/TD0iY8Iel7d2de7SvDQV/vhbuVnfz0/C7dPzIBCoQh6XoRIxe0WsPFYDb7achhrj5jhPPl8kh64a/pATO4di8QITafmSILD6nTjaKUZe4rrcLjMBLPDjVidCsNSI9E32YCeMWGQy4J3LqRFI71gd3mwek8+/rbiKFxC29uFKTm8ND8b0wenQxGEP+LXO4tw/9cHvdo2XCXDT3dNRI8YrcRZdW/LNhfgse9zvNp24bg0PD5vgMQZESItQRDw9e5SPPD1/g63nZSmxLNXj0dyBB1nuiOr0401B8vxzoZ8HKs2t3o+DFfJMDIjEndMzsKwHpGQ8Zzfr0erX58UaCFT2mDDlH/9BqfH+30i1DL88tcpzJYyb82813/H/lKTz/v9ZWIGHpzdT4KMujeXy4U+j65BO3Vsm3b+fQpidHRgJ6Gn0mTH5OfXwubjB/+ta4dh1oBEaZIinSK/2oy7P9+DQ2UmeFM0yDngkmHJ+Puc/jBo/WudptWvGSips2L8874VMQDQYPdg3HO/oqrRLkleM15e71cRAwBvbSzACz9516JAmrhcLmT5WcQAwIhn1qGm0co0J0KkVmWyY/SzvhcxAPCXT3ZjxZ5S9kmRTpFX2Yhr/7sVB70sYgDALQJf7irF3Z/vgtF69rAHlqiQaYPZ4cbUf63ze3+XAEx/aR0cbh+roA489cNBHK22BBTjrY0FOFLZwCahc8CYR9cEHGPEM/5/lggJNkEQMOm5tQHFWPLFXuwrqWeUEeksdRYn/vLxLpQZHX7tvzGvFk/9cBAeQbrOHypk2vCPb/fDFeD7bnII+N+2fDYJAbBarfi/P4qYxJr57z+YxOnuthyrRi2jWP9Zd4xRJEKk9fXuUtgYnHcuenMznG5/2zJJZxNFEa+vPYpjNf5fPIsAlu8tw+a8SnaJnYEKmVZUNdqxYl85k1hP/HAUFkdr97b47saP9zCJ02xzXjXTeN3R0z/lMov14s9HmMUiRCpOt+DVwF5vrcutYhaLBFdxnRUr9pYFHMcjAm+uz5esqKVCphWbD59gFksAcKjMv/EsZ9pW0MAkTrN7/se2MOpujFYXs79ds3VHpLsqIYSFTcdqmMZ76oddTOOR4NlyvAYNjMa37C1pwNHKRiaxzkSFTCse+eEo23jfsru6Yam6lXlnyJ9+2M9+sOL3ewK/uiFESv/3+yGm8U4YQd1LIUgURSzbUuT14N6O2N0ithew6qg/HRUyZ3B7BFgDHRxzhsIA+hebfba1gEEmxBdb8tl/6Y5WmZnHJISlHcfZ32F3rFqaK3EiHbPDjWqTfwN827JVgmMqQIXMWZwe9lcObgZ10dFKOgEGW6ONzdimU7HuqiKENWfHm/hMiu8SkZbdJcDF+E6jOqsUny4qZM7Cc/7PQthmTAYxNAoZgyjEF4HMSNmWzNgw5jEJ6eqCOV09YUPGc2B9CFTLpDmP0afrDCo5D9anLxWDJXeuHpUeeBDik97x4cxjJtFaNKSLi2P/sUdaNH3uQ41eLYdGwbZE6CnRhRwVMmfgOA6z+scxjXnXlN4Bx6A1koJv9kD2U6yPTI9kHpMQlu6dMZB5zJhwNfOYRFpyGY9JfWKZxeM5YFo2u3inxZYkaoi7c1ofpvEuHJLMJE6kn+tVtOWiIQlM43U3g1PZFx03j81gHpMQlib3ZnuyeeiCbKbxSPBcNjwVSkZVQqJehf4p0lzIUSHTit7x4TCo2bw1AxLDkRLJpln15csGMYnT7NWrhjON1x0tHJfGLNbYnlHQMi5GCWEtMUKD83oomcWbM5gWjwxV/RINyE7wfbHl1lw7Jh0x4dIspEyFTCvkMh5f/WUCk1jv3DAKHKMBxFP7sWtBuWRoErNY3dnfZ7FrnXv96sHMYhEipeevGc8kzoX99UiNpG7xUKVRyvDPudkIdKhMkkGFK0amskmqFVTItKF3vA53Tw6sG+CtK/oimfHgzpx/TmES55UrhzKJ090pFAp8edvogOM8Pb8/YnR0QCehITlCi7euHRZQDIMCePlqNgUR6TzDM2Lwt/N7Q+bn9Xi4ksdrVw5GtEStMQAVMu1aMqMvbh6b4te+z87PxgVD2Y+H0Gq1+PnewA4Ohc/PYZTNuWFURgzevMb/wm/J9F64dkw6u4QICYJZAxLx7yuG+LWvQQFsfPh8KOV0igl1HMfhxom98Nfzs3xumYkOU+Dd64ZhRE9pBvk240RRlG5t7S7AZDLBYDDAaDRCr/e9r08URWw+XILrPzoAjxfbq+TAp9cPxoje/hVA3rJarej35Dqf9hmaYsDyO9l0mZ2LjpQbMfPVTT7t88GNIzClT7xEGREivX0l9bjozc1eb39hfz1evno8FTHdjCCI2Hy8Gk/9eBj51Wa42pk7ViPnMK5XDB6bNwA9ov1vifb2/E2FjJdsTg8OlRnxt6/2oqDWdtbPh6bo8fhFA5GdqINKHrzJ65b9cRwv/pwHi7PtMitOp8L71w3BgB4xQcurO/tkayH+saL99WjumNQT907PhEJBg3tJ6HO6BazLrcJTP+zCCWPr2zx0QTbmDE6kMTHdnNnhxoETRny2rRBbjtfC4RYgiE0T6OnUMswfkoxZA5PQJ0EHRYATIVIhcxKrQuZUDrcHdRYn3B4RChmPqDBll7j6WH2gFP/bfgIWpxsxOhWWnJ+JPvERnZ1Wt+VyubApvw77SuoBAL1idLigfxwVL6Rbc7oFHKtuRKPNDbmMR1q0huaJOUfZXU3nQo8gQiVvOheynMWZCpmTpChkCCGEECItb8/fnd+MQAghhBDiJypkCCGEEBKyqJAhhBBCSMiiQoYQQgghIYsKGUIIIYSELCpkCCGEEBKyqJAhhBBCSMiiQoYQQgghIYsKGUIIIYSELCpkCCGEEBKy5J2dQChqsNix5Xg9bC43DBoFRveMQbi689/KCqMVv+VWwe4SEBuuwrTecdBqad0fKe0rqcfekgZ4BBFZceEYkxFJay2Rbk0URRhtLthdAngOMGgVQV0ol5Azdf7ZN0SUN9jwyq9H8c3OE2ht9XIlB1w9tgfumpoV1AXUDpUa8dyqXGw6VtPmNpcNS8ajc/vDQEUNEyt2l+CJr/ajvo1VymQAHrigD24an0ZFDekWBEFEQa0FH67Pw8e7ys76eUK4AkuvGY4ByQaEq+i0ci64ddlW/Hq4FqceBuUc8MSF2VgwrldQc6FFIzvgdrvxyJfb8eX+eq/3eWhWH9w+KdPn1/KFy+XC+Y+vQaHH+30emNkHd0yRNq/urKjGgkkvrfdpny9vG41RGTHSJERIEFQ12nHJ65twwuTocFsewL8u74eLh6aD5znpkyNBVV9fj0lLt8Hk6PjEMyQ5HCvumhTQ69Hq1ycFUsjY7W7M+PdaFBvdPr/umFQtPrntPMjl7K9OjFYXBj+5xq99kwBsfn4O24TOAeuOVOLGD3b6te/fZ2fj1onBvUIhhIXD5SbMevV3n/ebkhWNd24YBaWchmF2F8t35OPebw77vN+eB8chMjLSr9ek1a8ZmLn0N7+KGADYWmLFjf/dxDijppYYf4sYACgDsOijHewSOgfsK6n3u4gBgGd+ysUX24oZZkSI9I5VNfpVxADAurxa3LZsOwShW18nnzP8LWIAYOgLmxlnczYqZNrw2tqjKGpwBRTj90ILvtrJ9gQ2K4AiptmanCqs2F3CIJtzw0VvBv5FfHD5ARitgX2eCAkWs8ON6a9sDCjGurxafLSlgFFGpLPU19f7XcQ06/nQSkbZtI4KmVY0WOx45Zc8JrEe+PoA3G7/WnXOVFRjwTFG58IlX+5nE6ibe+6nHGaxFn+2m1ksQqT0v63HmMR5/IfDMNmpgA9lU17bHnAMAcDq/dJdPHfpQua5557DyJEjodPpEBcXh/nz5+PIkSOSv+5/1ucziyUC+N+OE0xiPfkju5MqAHy9i1plOvLORnZXlJuO1cBKrTKkizM73Hhm1XFm8Q6eMDKLRYKvwcbmQnzx59JdPHfpQmbDhg1YvHgxtm7dil9++QUulwszZsyAxWKR9HU/Zdwc+tFmNlc3a3OrmMRp9tRX1CrTniPl7A/AH24rYh6TEJbyKhvBcmTLXZ/5P76MdK57P9vFLJZHbOqmkkKXLmRWr16NhQsXon///hg8eDA+/PBDFBcXY9cudm/umdxuNyxsCtAWR6s7vm2xI1JcydN1Uvu+23v2fBmB2lZQxzwmISy9u55Nt3qzWqsHNqcP80SQLmPF/gqm8e76KrCxNm0JqZmLjMamU29UVFSb2zgcDjgcfxYOJpPJp9coN9n9S05iWwrpBBhshysamccsa7Ayj0kIS7uL2F/i1FmdSFZqmMcl0mJ9z9nxaml6U7p0i8ypBEHAkiVLMH78eAwYMKDN7Z577jkYDIaWR2pqqk+vY3O2Nm9v57M6GTcTkQ55JLh1tLxK2m5RQgJl97BvPaHbsAkA2NzSnF9DppBZvHgxDh48iP/973/tbvfwww/DaDS2PEpKfBvQGhWuDCRNycQbVJ2dwjknTIKp1nsk6pjHJISlSC37Y6CKJsYjACI00nQChcSn684778SPP/6IdevWISUlpd1tVSoV9Hr9aQ9fBHOdJF8MTTF0dgrnnDE92+7C9FdWXDjzmISwdMngROYxo8K65gUiaZ+S8Vqgcway/2wBXbyQEUURd955J5YvX47ffvsNGRkZQXndvrFsWz9m9IsPOIYUiw9Oy45jHrM7mT+k/aLZH/MGJzOPSQhLsxh/7qf2joFc1qVPNaQN7y8cwTTe32b1YxqvWZf+dC1evBiffPIJPvvsM+h0OlRUVKCiogI2m03S171tajbTeIsns1ln545JPZnEafbw7D5M43U3Bq0CUYy/IdMYFLWESKlnbDgiNOwuxe+/oC+zWCS4JmSxO17FhrG/GG/WpQuZt956C0ajEZMnT0ZiYmLL44svvpD0decPTYGK0cKtKXo5Bvfwb8GsM907nd3K1eEAMuN8Xw38XPPyDeyuSO6eSgtHkq5PxnP4v4WjmMQyqHn0jqfu1FB2ft9oJnHW3DmSSZzWdOlCRhTFVh8LFy6U/LU/vm0MkzifLBrPJA7Q1L300uWDmMT69eEpTOJ0d1P6xKMXo7tG75vBtqWPEKkMTY1EWmTgH/yV90yibqUQ994NYyAL8MK+X2K43ytge4M+YW0YlR6NB2YG1vXyyuWDkB7D9mrksuGpuGxYYOMsll4xCAkGLaOMur/Vj8wIOMZWKhxJCOF5Dj/ccx70Kv9PER9c0x8pkXSc6Q6OPzfH731jwxT46Z5JDLM5GxUy7bhjSiYeneNf/+7SKwfjkuG+zWHjrZeuGIIFo3v4te/SKwZh/jBp8uquFAoF8p6agXA/vy1/PDCFCkcScvRqBTY9PN2vlpkf75qAKYPS2SdFOk3h83Og8HHoVL/EcOx4NPALwY5woih265mKTCYTDAYDjEajz7diNzteZcYtH/yBgvqOJ6UbFKfEf28+D3EG6W/j3l5Qgyve2ebVtgYAa/8+BTE6OqEG4vW1R/GylyujXzE8Bc/M7yfJHWeEBIsgiNhVXI8b398Ks7P908W1w5Nw/5z+iJBgLhrSNezKr8c1/7cZjnbmTUw2qPDj7cMD7k7y9vxNhYwPcsqMeO/3Avy0rxSOUyYo1Ck4zB2SjDum9EJqVPAHtm05Vo031+dj07Gas342Z1ACHrmgL5KjqIBhxeVy4eNtJXhn1WFUnvFlVgFYODED95+fRQUM6VbcHgHHqs347I98rM6pQqPDBYWMR0qEFo9dNAB9EnRUwJxjHvxqN3YXN8Bs9yAyXImLhyTi1km9mcWnQuYkloUMIYQQQoLD2/M3jZEhhBBCSMiiQoYQQgghIYsKGUIIIYSELCpkCCGEEBKyqJAhhBBCSMiiQoYQQgghIYsKGUIIIYSELCpkCCGEEBKyqJAhhBBCSMiiQoYQQgghIYsKGUIIIYSELHlnJxBKbDYbHvvxCP44VoM6qwseQYSM5xAdrsKsfnH4+4UDOiUvu92OJ348gs35dai1OCCKIuQ8j8QINS4ZmoxFkzI7Ja/ubPnOQjy84hDsZyyILueAm8al4JELB3dOYoRIyGR3obTehupGBxxuATwHRGiVSDCokahXg+e5zk6RBIHH48H6o9XYXdyAkjorXB4RWqUMveLCcF5mLAamRAQ1H1o00gs2mw2z3tiCwlpbh9v2T9Lh61tHQqPR+PVavmhotGP+21tQWGvtcNvJvWPw4U2jJc+pu/vnt3vx0fZSr7YdnBSO7+6eJHFGhEivtMGGR77bhg2HLW1uIwPwxe1jMSQ1AnIZNfZ3R06nB6+uy8OnWwrRYPe0uV1mjAaLp/bGxcNSAno9Wv36pEALmQ9+P44nVub6vN/bC4bigoFJPu/nrTd+O4qX1uT5vN+Kv4zDkLRICTLq/rIeWQmX4Pt+O+8fjZiYGPYJESIxt0fAvf/bgh8ONPi03/ZHpiFOr5YmKdIpdhfV44b/24pGp/cHwcFJ4fjwprGIDFf69Zq0+jUDr/5yxK8iBgBu/3QPfthbwjijJs/8eMivIgYA5r+1Gdvzaxhn1P2lP+RfEQMAI17ahpoaes9JaHF7BIx/drXPRQwAjHp2LU7Ud9xSTELDprxqXP72Zp+KGADYV2bG+f9ej1qzQ6LMmlAh04Z9xXX499pjAcW463/7UWfquDvKF+sOV+C9TYUBxbji3W2w2+1sEjoH9H30p4BjjHhpG4NMCAmem95fj0qL/w32E15YB6PNxTAj0hlK6iy48YPt8Pj5UaixuHDlW5vg8bTdFRUoKmTacNF/tjCJM+zZ35jEaXbjsl1M4sz9D51YvfHOb7mwudj0vl702gYmcQiR2vFqMzYeD/wibMKza9DNRy90e7d+uN3v1uhmx2rteOf3fDYJtYIKmVZ88PtxpvH2FdcxifPCqsNM4gDAsSozKhqoVaYjz61h91nYV2ZmFosQqYiiiIsZFd2NLqCkjm2rNAmeTXnVyK1i00X4xto8OJ3StMpQIdOKf6/1b/xJW+74dDeTOG9tYFvR/uXTnUzjdTdSjGv557d7mcckhKUyox0mhj1CL/28h10wElQfbGR3LrS6RHy1+wSzeKeiQqYVpnZuK/NHqVHagU7+2lNi7OwUurQFyw4wj/nZDu9u3Saks3y95SDTeN/vb6DupRC14Vg903gr90tz/KNC5gylXbQZlO40Cr68avZ3XbjpeE66uHc3VTGPWW+lQb+hprTexvx4tVeii2cqZM6wu7hrFgxb82s7O4VzToDj2wgJSRYJhjFYHO6ONyJdyokG9hdyDrc0R1UqZM6gkMk6O4VW0dTfhJBQxdHhiwCQ6mNAhcwZJmV2zVlvp/aJ6+wUzjlyOviSc5Dev0lY26VTK9gHJZLKjA1nHlOrlKahgAqZMwRjjSR/9EuO6OwUzjnD0/xbm6s9SvrGkS7u4UnxzGPq1bQ+caiJDldBJWN7NTe2lzQNBXRYbUVMGNtLkt7xbCrbKC3bq5ppfWKZxutu3rysL/OYj87pzTwmISxNHzWQabyHJ0SBo76lkHTR0GSm8S4cEtgikm2hQqYVL142gGm8D24YxSTO32awPQm+efUgpvG6GykWerxufBbzmISwFKtToVcMuxaU+ROHMotFgmvh2HRmsaI0Mszqn8As3qmokGnF1L6JzGJlxmiRHMWmu+rqMelM4gDAeZnRUKtpddqOfLZwNLNYVwyT5ktMCGuf3jqJSZzMGAXiaRXskNUv2YDJvaOZxHr0wgGQSXQzDRUybdj9yFQmcX5YPIZJnGbr/3Yekzgf38I2r+5qXHYMUiNUAceRc8CLVwxnkBEh0kswqPHMtMBvMPjxnmkMsiGd6dWrh0GvCqwAmZIVhYuHSdOtBFAh06YovQbv3zAsoBir7xrLfPBwerQeS68MrEto60N0cPHF7w9NR6BjFY89N4dNMoQEyTXTR+DSEf5fje959HyoFV1zOgviPYNGiW/vGI8whX/jnAYmhuOd69gMr2gLFTLtmNo3Ed/dMdavff94YCqyk6MYZ9Rk/tBUfHLzCL/23fv3aUiIoKZeX+U+PQdJBt8HgavlQOHzVMSQ0MNxHF66dDSWzvatqz1MBhx8YiYiGd80QTpPZrwOa+6bgqxY3y7MrxqRiG/+MgFKiW67bsaJ3XwRDJPJBIPBAKPRCL3e/9tp//LRTqzKqexwuwWjUvHMJcEbRHvbRzvwc07HU4rfPyMLd06lO2YCtTm3Btd8uM2rbe+ZnIZ7L2A7cJyQzmCyu7C3uAHXv7+9zW1Gp6vw7KVj0DMmjO5S6sa+21OKdzfk4VCFpdWf8xwwIzsKt0/JxpAegd1u7e35mwoZH+3Ir8Ub6/NwpMIMt0eEQs5hYJIBi6f0wuAe0rTAeGNTXiWWbS7GkcpGeDwiNEo5hqUasGhiOjITIjotr+6qpqYGi78+jF1Fppb1SHgAWbFafHrDQEnueCKks3kEEbVmB6oaHXC4PeA4DpFaJeL1KmiVNFfMuaTCaMOW47U4Vm2GyyMiXCnHwBQ9RqZFIlzDpjWOCpmTWBcyhBBCCJGet+dvGiNDCCGEkJBFhQwhhBBCQhYVMoQQQggJWVTIEEIIISRkdfth5s1jmU0mUydnQgghhBBvNZ+3O7onqdsXMo2NjQCA1NTUTs6EEEIIIb5qbGyEwWBo8+fd/vZrQRBQVlYGnU4XkpM0mUwmpKamoqSkhG4fZ4DeT7bo/WSP3lO26P1kK5jvpyiKaGxsRFJSEni+7ZEw3b5Fhud5pKRIt1hVsOj1evoSMkTvJ1v0frJH7ylb9H6yFaz3s72WmGY02JcQQgghIYsKGUIIIYSELCpkujiVSoXHHnsMKpWqs1PpFuj9ZIveT/boPWWL3k+2uuL72e0H+xJCCCGk+6IWGUIIIYSELCpkCCGEEBKyqJAhhBBCSMiiQoYQQgghIYsKmS7gueeew8iRI6HT6RAXF4f58+fjyJEjp21jt9uxePFiREdHIzw8HJdeeikqKys7KePQ8vzzz4PjOCxZsqTlOXo/fVNaWoprr70W0dHR0Gg0GDhwIHbu3Nnyc1EU8c9//hOJiYnQaDSYPn068vLyOjHjrs3j8eDRRx9FRkYGNBoNevXqhaeeeuq0NWXoPW3bxo0bceGFFyIpKQkcx2HFihWn/dyb966urg4LFiyAXq9HREQEbr75ZpjN5iD+Fl1Le++py+XCgw8+iIEDByIsLAxJSUm4/vrrUVZWdlqMznpPqZDpAjZs2IDFixdj69at+OWXX+ByuTBjxgxYLJaWbe6991788MMP+Oqrr7BhwwaUlZXhkksu6cSsQ8OOHTvwzjvvYNCgQac9T++n9+rr6zF+/HgoFAqsWrUKOTk5ePnllxEZGdmyzYsvvojXXnsNb7/9NrZt24awsDDMnDkTdru9EzPvul544QW89dZbeOONN3D48GG88MILePHFF/H666+3bEPvadssFgsGDx6MN998s9Wfe/PeLViwAIcOHcIvv/yCH3/8ERs3bsSiRYuC9St0Oe29p1arFbt378ajjz6K3bt349tvv8WRI0cwb96807brtPdUJF1OVVWVCEDcsGGDKIqi2NDQICoUCvGrr75q2ebw4cMiAHHLli2dlWaX19jYKGZlZYm//PKLOGnSJPGee+4RRZHeT189+OCD4oQJE9r8uSAIYkJCgvivf/2r5bmGhgZRpVKJn3/+eTBSDDlz5swRb7rpptOeu+SSS8QFCxaIokjvqS8AiMuXL2/5tzfvXU5OjghA3LFjR8s2q1atEjmOE0tLS4OWe1d15nvamu3bt4sAxKKiIlEUO/c9pRaZLshoNAIAoqKiAAC7du2Cy+XC9OnTW7bJzs5Gjx49sGXLlk7JMRQsXrwYc+bMOe19A+j99NX333+PESNG4PLLL0dcXByGDh2K9/6/vfsPiqL84wD+PjgBjwvuxLrDjF8qAYIMF8IcNIYgv2oQqCQvhoAZbUAlsCEVGcpyqHQYmn6i0YwyadNP1HJARX4UEIOA3BGNIimIMx1QIAGhEtzz/YNhv62IHZocm5/XzM3c7j777Gc/y9x95tnn2MJCbntHRwe6u7t5+bS1tYW/vz/lcxoBAQEoLy/HhQsXAAA6nQ41NTWIjIwEQDm9G8bkrq6uDjKZDL6+vlybNWvWwMzMDPX19bMesxD98ccfEIlEkMlkAEyb0//8QyOFxmAwICMjA4GBgfD09AQAdHd3w8LCgvuDmaRQKNDd3W2CKOe+zz//HGfPnkVDQ8OUbZTPmbl06RIKCgrw8ssvY+fOnWhoaMBLL70ECwsLJCYmcjlTKBS8/Sif09uxYwcGBwfh5uYGc3NzjI+PIzc3F/Hx8QBAOb0LxuSuu7sbDz30EG+7WCzGggULKL9GuH79OrZv3w6NRsM9ONKUOaVCZo7ZvHkzWltbUVNTY+pQBOvKlStIT09HWVkZrKysTB2O4BkMBvj6+uLNN98EAPj4+KC1tRX79u1DYmKiiaMTpi+//BKHDx/GZ599huXLl0Or1SIjIwOLFi2inJI57a+//kJcXBwYYygoKDB1OABosu+csmXLFhw/fhyVlZVYvHgxt16pVGJ0dBQDAwO89j09PVAqlbMc5dzX1NSE3t5eqFQqiMViiMVifP/993jvvfcgFouhUCgonzNgb28PDw8P3jp3d3d0dXUBAJezm3/1Rfmc3iuvvIIdO3Zg/fr18PLyQkJCArZu3Yq33noLAOX0bhiTO6VSid7eXt72sbEx9Pf3U35vY7KIuXz5MsrKyrjRGMC0OaVCZg5gjGHLli04cuQIKioq4OzszNv+2GOPYd68eSgvL+fWtbW1oaurC2q1erbDnfNCQkLw008/QavVci9fX1/Ex8dz7ymfxgsMDJzy7wAuXLgAR0dHAICzszOUSiUvn4ODg6ivr6d8TmNkZARmZvyPX3NzcxgMBgCU07thTO7UajUGBgbQ1NTEtamoqIDBYIC/v/+sxywEk0VMe3s7Tp8+DTs7O952k+b0nk4lJkZJTU1ltra2rKqqiun1eu41MjLCtUlJSWEODg6soqKCNTY2MrVazdRqtQmjFpa//2qJMcrnTJw5c4aJxWKWm5vL2tvb2eHDh5lEImGHDh3i2rz99ttMJpOxY8eOsZaWFhYdHc2cnZ3ZtWvXTBj53JWYmMgefvhhdvz4cdbR0cGKi4vZwoUL2bZt27g2lNPpDQ0NsebmZtbc3MwAsPz8fNbc3Mz9gsaY3EVERDAfHx9WX1/Pampq2LJly5hGozHVKZnc7XI6OjrK1q5dyxYvXsy0Wi3ve+rGjRtcH6bKKRUycwCAW74OHDjAtbl27RrbtGkTk8vlTCKRsNjYWKbX600XtMDcXMhQPmfmu+++Y56enszS0pK5ubmxjz/+mLfdYDCwnJwcplAomKWlJQsJCWFtbW0minbuGxwcZOnp6czBwYFZWVkxFxcXlp2dzftSoJxOr7Ky8pafmYmJiYwx43LX19fHNBoNk0qlzMbGhiUnJ7OhoSETnM3ccLucdnR0TPs9VVlZyfVhqpyKGPvbv5IkhBBCCBEQmiNDCCGEEMGiQoYQQgghgkWFDCGEEEIEiwoZQgghhAgWFTKEEEIIESwqZAghhBAiWFTIEEIIIUSwqJAh5D8mKSkJMTExpg7DpIKCgpCRkXHbNiKRCEePHp2VeO5WVVUVRCLRlOeDEUKokCFEUEQi0W1fu3btwrvvvouDBw/e81h+++03pKamwsHBAZaWllAqlQgPD0dtbe09P/a/Qa/XIzIy0tRhGCUgIAB6vR62tramDoWQOUds6gAIIcbT6/Xc+y+++AKvvvoq74GOUqkUUql0VmJ55plnMDo6iqKiIri4uKCnpwfl5eXo6+u7p8cdHR2FhYXFXfcjpKccW1hYCCpeQmYTjcgQIiBKpZJ72draQiQS8dZJpdIpt5aCgoKQlpaGjIwMyOVyKBQKFBYW4s8//0RycjIeeOABLF26FKWlpbxjtba2IjIyElKpFAqFAgkJCfj9998BAAMDA6iursaePXuwevVqODo6ws/PD1lZWVi7di3Xx8DAADZs2IAHH3wQNjY2CA4Ohk6n47ZfvHgR0dHRUCgUkEqlWLlyJU6fPs2Lw8nJCbt378YLL7wAGxsbvPjiiwCA2tpaBAUFQSKRQC6XIzw8HFevXuX2MxgM2LZtGxYsWAClUoldu3bx+v37raXOzk6IRCIUFxdj9erVkEgk8Pb2Rl1dHW+fwsJCPPLII5BIJIiNjUV+fj5kMtmMruGdXI+bby0dPHgQMpkMJ0+ehLu7O6RSKSIiIniFLiH3CypkCLkPFBUVYeHChThz5gzS0tKQmpqKdevWISAgAGfPnkVYWBgSEhIwMjICYKIACQ4Oho+PDxobG3HixAn09PQgLi4OwP9Hfo4ePYobN25Me9x169aht7cXpaWlaGpqgkqlQkhICPr7+wEAw8PDePLJJ1FeXo7m5mZEREQgKioKXV1dvH7y8vLg7e2N5uZm5OTkQKvVIiQkBB4eHqirq0NNTQ2ioqIwPj7OO2dra2vU19dj7969eOONN1BWVnbbPGVnZyMzMxNarRaurq7QaDQYGxsDMFE4paSkID09HVqtFqGhocjNzZ35xcDMr8etjIyMIC8vD59++il++OEHdHV1ITMz847iIUTQ7vljKQkh98SBAweYra3tlPWJiYksOjqaW37iiSfY448/zi2PjY0xa2trlpCQwK3T6/UMAKurq2OMMbZ7924WFhbG6/fKlSsMAPcU4a+//prJ5XJmZWXFAgICWFZWFtPpdFz76upqZmNjw65fv87rZ8mSJWz//v3Tntfy5cvZ+++/zy07OjqymJgYXhuNRsMCAwOn7ePmc2aMsZUrV7Lt27dzywDYkSNHGGOMe7rvJ598wm3/+eefGQB27tw5xhhjzz33HHvqqad4fcbHx9/yGtzOnVyPyScTX716lTE2ce0BsF9++YXb58MPP2QKhWJGsRDyX0AjMoTcB1asWMG9Nzc3h52dHby8vLh1CoUCANDb2wsA0Ol0qKys5EZepFIp3NzcAEzcDgIm5sj8+uuv+PbbbxEREYGqqiqoVCpuorFOp8Pw8DDs7Ox4/XR0dHB9DA8PIzMzE+7u7pDJZJBKpTh37tyUERlfX1/e8uSIjLHnDAD29vbc+Rmzj729PS8nbW1t8PPz47W/edlYM70etyKRSLBkyRJevP90foT8F9FkX0LuA/PmzeMti0Qi3jqRSARgYl4JMFFgREVFYc+ePVP6mvyCBwArKyuEhoYiNDQUOTk52LBhA1577TUkJSVheHgY9vb2qKqqmtLH5LySzMxMlJWVIS8vD0uXLsX8+fPx7LPPYnR0lNfe2tqatzx//vw7OufJ8zNmn5tz8m+a6fUwtg/G2L8YJSHCQIUMIWQKlUqFb775Bk5OThCLjf+Y8PDw4CbQqlQqdHd3QywWw8nJ6Zbta2trkZSUhNjYWAATBVRnZ+c/HmfFihUoLy/H66+/bnRsd+vRRx9FQ0MDb93Ny4SQ2Ue3lgghU2zevBn9/f3QaDRoaGjAxYsXcfLkSSQnJ2N8fBx9fX0IDg7GoUOH0NLSgo6ODnz11VfYu3cvoqOjAQBr1qyBWq1GTEwMTp06hc7OTvz444/Izs5GY2MjAGDZsmUoLi6GVquFTqfD888/b9QISFZWFhoaGrBp0ya0tLTg/PnzKCgo4H5VdS+kpaWhpKQE+fn5aG9vx/79+1FaWsqNnhBCTIMKGULIFIsWLUJtbS3Gx8cRFhYGLy8vZGRkQCaTwczMDFKpFP7+/njnnXewatUqeHp6IicnBxs3bsQHH3wAYOJWR0lJCVatWoXk5GS4urpi/fr1uHz5MjcHJD8/H3K5HAEBAYiKikJ4eDhUKtU/xufq6opTp05Bp9PBz88ParUax44dm9Ho0UwFBgZi3759yM/Ph7e3N06cOIGtW7fCysqKazP5M+5b3U4jhNwbIkY3VQkh5I5s3LgR58+fR3V1NQCgsrISTz/9NC5dugS5XG7i6Ai5P9AcGUIIMVJeXh5CQ0NhbW2N0tJSFBUV4aOPPuK2l5SUYOfOnVTEEDKLaESGEEKMFBcXh6qqKgwNDcHFxQVpaWlISUkxdViE3NeokCGEEEKIYNFkX0IIIYQIFhUyhBBCCBEsKmQIIYQQIlhUyBBCCCFEsKiQIYQQQohgUSFDCCGEEMGiQoYQQgghgkWFDCGEEEIEiwoZQgghhAjW/wA2xQkpTAJdQQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Write your code here\n",
    "ax = df.plot(kind='scatter',\n",
    "            x='TimeSearching',\n",
    "            y='NFrust',\n",
    "            alpha=0.5,\n",
    "            s=norm_age * 200 + 1\n",
    "            )\n",
    "\n",
    "ax.set_ylabel('Frustration')\n",
    "ax.set_xlabel('TimeSearching, min')\n",
    "ax.legend(['Age'], loc='upper center', fontsize='x-large')\n",
    "ax.set_title('Bubble plot')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing Composition of Data\n",
    "\n",
    "**Pie Charts**\n",
    "\n",
    "Create a pie chart of the top 5 databases(`DatabaseWantToWorkWith`) that respondents wish to learn next year.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Write your code here\n",
    "QUERY = \"\"\"\n",
    "SELECT DatabaseWantToWorkWith\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn).dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "datab = df.copy()\n",
    "dummiesdatab = datab['DatabaseWantToWorkWith'].str.get_dummies(sep=';')\n",
    "datab = dummiesdatab.agg('sum').T.head()\n",
    "\n",
    "datab.plot(kind='pie',\n",
    "              figsize=(9, 5),\n",
    "              autopct='%1.1f%%', # add in percentages\n",
    "              labels=None,\n",
    "              startangle=0,\n",
    "              pctdistance=1.12,  # the ratio between the center of each pie slice and the start of the text\n",
    "              shadow=False,\n",
    "              colormap='Spectral'\n",
    "              )\n",
    "\n",
    "plt.title('DatabaseWantToWorkWith')\n",
    "plt.axis('equal') # Sets the pie chart to look like a circle\n",
    "plt.legend(labels=datab.index, loc='upper left')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Stacked Charts** \n",
    "\n",
    "Create a stacked bar chart of median `TimeSearching` and `TimeAnswering` for the age group 30 to 35.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Write your code here\n",
    "QUERY = \"\"\"\n",
    "SELECT Age, TimeSearching, TimeAnswering\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.TimeSearching = df.TimeSearching.map({'30-60 minutes a day': 45, '60-120 minutes a day': 90, \n",
    "        '15-30 minutes a day': 23, 'Less than 15 minutes a day': 14, 'Over 120 minutes a day': 121})\n",
    "df.TimeAnswering = df.TimeAnswering.map({'30-60 minutes a day': 45, '60-120 minutes a day': 90, \n",
    "        '15-30 minutes a day': 23, 'Less than 15 minutes a day': 14, 'Over 120 minutes a day': 121})\n",
    "df_time = df.groupby('Age', as_index=False).median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "order = [7, 0, 1, 2, 3, 4, 5]\n",
    "df_time = df_time.reindex(order)\n",
    "\n",
    "ax = df_time.plot(kind='bar', x='Age', figsize=(9, 5), stacked=True)\n",
    "\n",
    "xlabels = [textwrap.fill(label.get_text(), width=10) for label in ax.get_xticklabels()]\n",
    "ax.set(xlabel='Age group', ylabel='Time spent')\n",
    "ax.set_xticklabels(xlabels)\n",
    "plt.title('Median TimeSearching and TimeAnswering for different Age groups')\n",
    "plt.xticks(rotation=0)\n",
    "plt.grid(True, axis='y', linestyle='dashed')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualizing Comparison of Data\n",
    "\n",
    "**Line Chart**\n",
    "\n",
    "Plot the median `CompTotal` for all ages from 45 to 60.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Write your code here\n",
    "QUERY = \"\"\"\n",
    "SELECT Age, CompTotal\n",
    "FROM main\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn).dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_300/3170935809.py:9: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  ax.set_xticklabels(xlabels)\n"
     ]
    },
    {
     "data": {
      "image/png": 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rpnZjbtuHMWHCBERHR+Odd95BcHAwHBwcIAgCRo0aRde+s0A06SKEU9u2bfHnn3+if//+9T5ZWkcQBFy9elU8ugUAly5dAoBar6vl7u4OOzs7pKSkVHssOTkZUqlU/EVbn5NqdRc3re11mzdv3qCjXFu2bIFCocAPP/xQ7ZfbsWPH8MUXXyA9PR2+vr7w8/ODIAhIS0vTm6BdvnxZ73m61XdarbZBl534448/UF5ejt9//13v6AfvR8I18fPzQ2pqarX2mvLk8dxzz2HhwoW4fft2tes/VdW2bVucO3cOw4YNe+D21mV75coVvaNDPPX99ddfuHPnDn799VcMHDhQbE9LS+McDZ/Ro0dDJpPhxx9/rPNk+vp8HxhKTdv30qVL3NfA8/PzQ0JCAgRB0JtE6z6e1X0P1rYd7969i0OHDiE8PBwLFy58YF3EMtA5XYRwmjBhArRaLT766KNqj2k0GuTn53O9ztq1a8X/Z4xh7dq1UCgUGDZsWI39ZTIZRo4cid9++03vI8isrCxs3boVjz76qPgxjW6SxFNLixYtEBwcjM2bN+v1v3DhAg4ePIgxY8Zwjed+W7ZswYABA/Dss8/imWee0fv3zjvvAAB++uknAEBoaCgAYP369Xqv8eWXX+p9LZPJMG7cOPzyyy81LtnPycl5YE26yV/VoxkFBQXYtGlTPUf3P2PGjMGJEydw6tQpvTpqOxJal7Zt22L16tVYunSp3nli95swYQJu3ryJb775ptpjpaWlKCkpAQBx1eAXX3yh12f16tV11lJTXhUVFdW208Py8fHByy+/jIMHD1bb5kDlHym6C47W5/vAUHbv3o2bN2+KX586dQonT5584IrMqsaMGYPMzExs375dbNNoNPjyyy/h4OAgXorFzs4OQPXv25q2A8C3DYl5oiNdxOp8++234gnaVb355psP9bqDBg3Cq6++iqVLlyI+Ph4jR46EQqFAamoqdu7ciTVr1uCZZ5554GvY2Nhg//79mDJlCvr06YN9+/Zh7969eP/99x/48eTHH3+MyMhIPProo3j99dchl8uxYcMGlJeX610PKTg4GDKZDMuWLUNBQQFUKpV4baqarFixAqNHj0ZISAimTZsmXjLC2dm5Qfd+PHnypLg8viYtW7ZEjx49sGXLFsyfPx89e/bEuHHjsHr1aty5c0e8ZITu6F/VIwCffvopoqKi0KdPH7z88svo1KkT8vLycPbsWfz555/Iy8urta6RI0dCqVTi8ccfx6uvvori4mJ888038PDwwO3bt+s9TgCYN28efvjhB4waNQpvvvmmeMkI3dGNhuDZR59//nns2LEDr732GqKiotC/f39otVokJydjx44dOHDgAHr16oXg4GBMmjQJ69evR0FBAfr164dDhw5VO4pYk379+sHV1RVTpkzBrFmzIJFI8MMPPxjlI7jPP/8cV65cwaxZs/Drr7/iscceg6urK9LT07Fz504kJydj4sSJAPi/DwylXbt2ePTRRzF9+nSUl5dj9erVaNasWbUL2dbmlVdewYYNG/Diiy8iNjYWrVu3xs8//4zjx49j9erV4gICW1tbdOrUCdu3b0eHDh3g5uaGzp07o3Pnzhg4cCCWL18OtVqNli1b4uDBgwY/4kgakYlWTRJicLol07X9u3HjRq2XjLC3t6/2erol/ffbuHEj69mzJ7O1tWWOjo6sS5cubN68eezWrVsPrE/3PleuXGEjR45kdnZ2zNPTky1atIhptVq9vqhh+fjZs2dZaGgoc3BwYHZ2dmzIkCEsOjq62vt88803rE2bNkwmk3FdPuLPP/9k/fv3Z7a2tszJyYk9/vjjLCkpSa8P7yUj3njjDQZAb0n//RYvXswAsHPnzjHGGCspKWEzZsxgbm5uzMHBgY0dO5alpKQwAOzTTz/Ve25WVhabMWMG8/HxYQqFgnl5ebFhw4axjRs3PrAuxhj7/fffWdeuXZmNjQ1r3bo1W7ZsGfv222+rLbP38/NjYWFh1Z4/aNAgvcsKMMZYQkICGzRoELOxsWEtW7ZkH330Efu///u/el8y4kFw3yUjGKu87MCyZctYUFAQU6lUzNXVlfXs2ZOFh4ezgoICsV9paSmbNWsWa9asGbO3t2ePP/44u3HjBtclI44fP8769u3LbG1tmbe3N5s3bx47cOBAtX1q0KBBLCgoqFrdU6ZM0bt8woNoNBr23//+lw0YMIA5OzszhULB/Pz82NSpU6tdToLn+6C2y8fUlvn9PwN0PydWrFjBPv/8c+bj48NUKhUbMGCAuN/W5P5LRjBWuc9OnTqVNW/enCmVStalSxe9nz860dHRrGfPnkypVOptn4yMDPbUU08xFxcX5uzszMaPH89u3brFtQ2J+ZEwZqZnDxJiZV588UX8/PPPKC4uNnUpZi8+Ph7du3fHjz/+2KBLMBDyMK5duwZ/f3+sWLECb7/9tqnLIVaEzukihJhUaWlptbbVq1dDKpXqncRNCCGWjs7pIoSY1PLlyxEbG4shQ4ZALpdj37592LdvH1555RWDr0YjhBBTokkXIcSk+vXrh8jISHz00UcoLi6Gr68vFi9ejA8++MDUpRFCiEHROV2EEEIIIY2AzukihBBCCGkEJp10HTlyBI8//ji8vb0hkUiwe/fuWvu+9tprkEgk1S4Kl5eXh8mTJ8PJyQkuLi6YNm1atdVhCQkJGDBgAGxsbODj41Pj9Vx27tyJwMBA2NjYoEuXLtVuaMoYw8KFC9GiRQvY2tpi+PDhdFVgQgghhHAz6TldJSUl6NatG1566SU8/fTTtfbbtWsXTpw4AW9v72qPTZ48Gbdv30ZkZCTUajWmTp2KV155BVu3bgVQeRf7kSNHYvjw4fj6669x/vx5vPTSS3BxcRHv/xYdHY1JkyZh6dKleOyxx7B161aMHTsWZ8+eRefOnQFUnuz7xRdfYPPmzfD398eCBQsQGhqKpKQk2NjYcI1XEATcunULjo6O9bpdCyGEEEJMhzGGoqIieHt713pfVN4XMgsA2K5du6q1Z2RksJYtW7ILFy4wPz8/tmrVKvGxpKSkahfA27dvH5NIJOzmzZuMMcbWr1/PXF1dWXl5udhn/vz5LCAgQPx6woQJ1S6G2KdPH/bqq68yxhgTBIF5eXmxFStWiI/n5+czlUrFfvrpJ+4x6i5KSP/oH/2jf/SP/tE/y/t348YN7t/5NTHr1YuCIOD555/HO++8g6CgoGqPx8TEwMXFBb169RLbhg8fDqlUipMnT+Kpp55CTEwMBg4cCKVSKfYJDQ3FsmXLcPfuXbi6uiImJgZz587Ve+3Q0FDx4860tDRkZmbq3WjX2dkZffr0QUxMjHiLivuVl5ejvLxc/Jr9s2YhLS1NvP2DVCqFTCaDVqvVu2O8rl2j0ejdekMmk0Eqleq1azQanDt3Dr169ap2mw65XC724WlXKBQQBAFarVZsk0gkkMvltbbXVvvDjKlqu1qtNuiYquYllUqtYkxVazfkdlKr1YiPj0dwcDBUKpVVjMlY20mj0eDMmTMIDg4W+1n6mGpqN8SYBEEQ96uqRw0seUzG2k4ajQbx8fHo1auXuJ9Z+pjqqr2hYyovLxf3K4VCYdAx5eXlwd/fX/zd3VBmPelatmwZ5HI5Zs2aVePjmZmZ1e4pJ5fL4ebmhszMTLGPv7+/Xh9PT0/xMVdXV2RmZoptVftUfY2qz6upT02WLl2K8PDwau0xMTHiDU59fX3RvXt3xMXFIT09XewTEBCAwMBAREdH693MNzg4GH5+fjh8+DCKior0XtfR0REHDx7U21GHDBkCW1vbaueojRkzBqWlpTh27JjYJpfLERYWhuzsbMTExOi97tChQ3H9+nXEx8eL7e7u7ujXrx+Sk5ORkpIithtqTCEhIfDw8MDevXsNPibduG7dumU1YzLmdjpx4oTVjQkw7HYqKipCWVkZTpw4YTVjMtZ2atWqFe7du4f09HRkZGRYxZiMvZ0kEgns7OysakzG2k4nTpww+Jj+/vtvcTs8DLO5ZIREIsGuXbswduxYAEBsbCzCwsJw9uxZ8Vyu1q1bY/bs2Zg9ezYA4JNPPsHmzZv1AgUADw8PhIeHY/r06Rg5ciT8/f2xYcMG8fGkpCQEBQUhKSkJHTt2hFKpxObNmzFp0iSxz/r16xEeHo6srCxER0ejf//+uHXrFlq0aCH2mTBhAiQSid4d5Ku6/0hXYWEhfHx8kJubCycnJwCG+UtCrVYjMjISY8aMqVaDNf3FZ6gxVc1LV6elj6lq7YbcThUVFYiMjMSIESNgY2NjFWMy1nZSq9XYt28fRowYAYVCYRVjqqndEGPSarU4cOAAQkNDIZPJrGJMxtpOup9Xo0ePhkKhsIox1VV7Q8dUVlYm/rxSKpUGP9LVrFkzFBQUiL+/G8Jsj3QdPXoU2dnZ8PX1Fdu0Wi3eeustrF69GteuXYOXlxeys7P1nqfRaJCXlwcvLy8AgJeXF7KysvT66L6uq0/Vx3VtVSddWVlZCA4OrnUMKpUKKpWqWrtCoRB/KOvIZDK9Hz46up2Pt/3+121Iu1QqrfFEwdraa6udxmT5Y9L98FEoFOJrWvqYamKIMen+Ar7/+9uSx1RbuyHHVNPrW/qYjLGdJBIJJBKJVY2pIe0PGlPVP3Z0NRh7TPVlttfpev7555GQkID4+Hjxn7e3N9555x0cOHAAQOUhy/z8fMTGxorPO3z4MARBQJ8+fcQ+R44c0ZthR0ZGIiAgAK6urmKfQ4cO6b1/ZGQkQkJCAAD+/v7w8vLS61NYWIiTJ0+KfUxJJpMhODi4xh2IVEd58aOs+FFW/CgrfpQVP4vI6qFOw39IRUVFLC4ujsXFxTEAbOXKlSwuLo5dv369xv73r15kjLFRo0ax7t27s5MnT7Jjx46x9u3bs0mTJomP5+fnM09PT/b888+zCxcusG3btjE7Ozu2YcMGsc/x48eZXC5nn332Gbt48SJbtGgRUygU7Pz582KfTz/9lLm4uLDffvuNJSQksCeffJL5+/uz0tJS7vEWFBQwAKygoID7OYQQQggxLUP9/jbppCsqKqrGJZlTpkypsX9Nk647d+6wSZMmMQcHB+bk5MSmTp3KioqK9PqcO3eOPfroo0ylUrGWLVuyTz/9tNpr79ixg3Xo0IEplUoWFBTE9u7dq/e4IAhswYIFzNPTk6lUKjZs2DCWkpJSr/Eaa9KlVqvZoUOHmFqtNujrWivKix9lxY+y4kdZ8aOs+BkzK0P9/jbpOV2DBw+udomDB7l27Vq1Njc3N/FCqLXp2rUrjh49+sA+48ePx/jx42t9XCKRYMmSJViyZAlXrY2J/XPRtvpk2ZRRXvwoK36UFT/Kih9lxc8SsjLbc7oIIYQQQqwJTboIIYQQQhqB2VynqykoLCyEs7PzQ1/n436CICA3NxfNmzd/uHtCNRGUFz/Kih9lxY+y4kdZ8TNmVob6/U2TrkZkrEkXIYQQQozHUL+/adpsBdRqNfbu3Vvtar+kZpQXP8qKH2XFj7LiR1nxs4SsaNJlJe6/XQJ5MMqLH2XFj7LiR1nxo6z4mXtWNOkihBBCzFCZWouEjAJcKpCgqMy8JxOEj9nee5EQQghpKvLvVSDxViGSbhUi8VYBkm4X4kpOCbQCAyDDVxcPI8jbGY+0dkNvfzc80toVzRyq39uXmDc6kb4RGetEet0F4RwdHcWb7pLaUV78KCt+lBW/ppwVYww380urTLAKcfF2IW7ml9bY381eCRu5BLcKyqs91s7DAb393dDH3w2PtHaDt4utscs3a8bcrwz1+5uOdFkJW9um/c1WX5QXP8qKH2XFrylkpdYKuJJTjMSbhUi6XTnJSrpdiILSmk/09nWzQ6cWTgjydkInbycEeTvDw1EJrVaLnBI1Tl+7i1NpeTh9LQ+XsopxObvy39aT6QCAVq626O3vht7/HA3zb27f5Ca15r5f0ZGuRmSsI11qtRoREREYM2YMFAqFwV7XWlFe/CgrfpQVP2vMqqRcg4u3KydVuklWSlYRKjRCtb4KmQTtPRzRydtJnGR19HaCk031LGrLKq+kAqev5eF0Wh5OXcvDhZsFEO77bd7cQYXe/q7/TMKaIcDLETKp9U7CjLlf0ZEuQgghxARyisqReKug8iPCf45gXbtTgpoOYTio5OjUovLIVeXRKye083CASi57qBrc7JUIDfJCaJAXAKC4XIOz1yuPhJ1Ky0N8Rj5yi8sRcT4TEeczAQCONvIq54S5oUtLZyjltJ6uMdGkixBCCKmBIDBcz7und3J74q1C5BRVP78KADydVAjydtb7iNDH1Q7SRji65KCSY2AHdwzs4A7gfysfT1/Lw8m0PMRey0NRmQaHk7NxODkbAGCjkKKHryseaV15Xlh3X1fYKh9uMkgejCZdhBBCmrxyjRapWcWVk6sqJ7iXVGir9ZVIgDbN7dHJ27lycvXPkazmZrSa0EYhqzy/y98NM4YAGq2Ai7eLcDLtjnhe2N17akRfuYPoK3cAAHKpBF1aOYsn5/f0c4OzrXV8/Gsu6JyuRmTM1YsajQZyubzJnTTZEJQXP8qKH2XFz9RZFdxTV34seLtQnGRdzi6G5v6TogCo5FIEejmik7ez+PFgoJcj7JSNc8zCWFkJAsOVnGKc/GcCdvJqHjILy/T6SCRAoJeTuDryEX9XeDjaGKwGQzPmfkX3XrRAdMkI80B58aOs+FFW/BorK8YYbheUiUeudB8RZtyt+fIMLnYK8chV0D+TrDbN7SGXme68p8bMKuNuqXhO2KlreUjLLanWr01ze/G8sN7+bmjlams2+7slXDKCJl2NiFYvmgfKix9lxY+y4meMrDRaAWm5JeLJ7bojWHfv1Xx5hlautnqTqyBvJ7RwtjGbCYSOKfer7KIynE67i1Npd3Dq2l0kZxZWWyzQwtlGPDG/j78b2nk4mCxDWr1ICCGEGFhphRYXM/93cdGk24VIvl2I8houzyCTStDew6HK5RkqT3R3tqOJcV08HG0Q1rUFwrq2AFD5seyZ65VHwU6l5eF8RgFuF5Tht/hb+C3+FoDKVZW9/Fz/OS+sGTq2cDTpkUJzQ5MuQgghZutOcbm4alC3ijAtt6TaNakAwF4pQ8cW/7s0Q6cWzmjv6QAbBa3IMwRnOwWGdfTEsI6eAIB7FRrEp+fj5D8fScbduIu8kgocTMrCwaQsAJXbpGfr/101v2sr5ya9PWjSZSXkctqU9UF58aOs+FFW/O7PijGGG3mlete/SrxVgKzCmi/P4O6oqnb1dj+3xrk8Q2Mz1/3KTilHv3bN0a9dcwBAhUbA+ZsF4urI0/9cpuLIpRwcuZQDAFDKpQj2cRGvmt/DzxUOKsONz1yz0qFzuhqRsc7pIoQQS6LWCriUVaT38eDFW4UoKtdU6yuRAP7N7NGxytXbO3k7mfUqOlJJKzAkZxaKV80/lZaH3OIKvT4yqQRB3k7iJOyR1m5wtVeaqOLa0Yn0FshYky5BEJCbm4vmzZtDKqXPzutCefGjrPhRVnW7cLMAP8dmYHfcTeTXcP9BpUyKAC/HyslVy8oJVoCXk0GPhFgaa9qvGGNIyy3RWyFZ00rSDp4OVU7ObwYvZ74JtjGzohPpiUir1SImJgZjxoyx+G/KxkB58aOs+FFWNcsrqcDuuJvYGZuBi7cLxXZbGUM3XzcEtXQRJ1lt3R2goJOu9VjTfiWRSNDG3QFt3B0wsbcvAOBmfqnekbDL2cW4lFX578cTlTfy9nGzRe/WzSrPC/N3Q+tmdjWukLSErGjSRQghxKA0WgF/X8rBzjMZOJScBbW28gMVpUyKEUGeeDq4BQovncJjYY/Q5TWauJYutmjZvSXGdm8JoHLhxOlr/9xD8todJN0qxI28UtzIy8AvZzMAVJ7Pp7tq/iOt3RDg6Wgx5/LRpIsQQohBXM4uws4zGfg17qbe/Qm7tHTG+F6t8EQ3b7jYKSuvp5RqwkKJ2WrmoMKozl4Y1bnyRt5FZWrE/nMj79PX8nDuRgFyisqxN+E29ibcBgA42yrwSGtX9PB1hrqo8pxBc53L06TLCkgkEroKdj1QXvwoK35NNavCMjX+OHcLO89kIP5GvtjezF6Jsd1bYnyvVgj00j8Hpqlm1RBNPStHGwUGB3hgcIAHgMobecffyBc/koy9fhcFpWr8eTEbf17MBiCHxj0Nb4UGmrbwWtCJ9I2IVi8SQqyBIDBEX7mDnbE3sP9CpnhRUplUgiEBHhjfqxWGBHhAKTfP82qI9VBrBSTdKsSptDycTMvDmet5WDupBx5t39yg70OrFy2QMVcv3rhxAz4+PmZ78qA5obz4UVb8mkJW6Xfu4efYG/jl7E3czP/fqrMOng4Y39MHY7u3hLujqs7XaQpZGQplxU8QBFxPT0erVj5QyA17AVZavUhEWq0W8fHx8Pb2pm9KDpQXP8qKn7Vmda9Cg4jzmdh55gZOpuWJ7U42cjwR7I3xPX3QtZVzvT7+stasjIGy4qfVapFw7hxatWwJwDyvek+TLkIIIXoYYzhz/S52nrmBvQm3UVKhBVB5odJH2zXH+F4+GNnJs0nfzoWQhqBJFyGEEADA7YJS/Hr2Jn6OzUBabonY3rqZHZ7p2QpP92gFbxdbE1ZIiGWjSZcVkEgkcHd3b7KrW+qL8uJHWfGz1KzK1FpEJmVhZ2wGjqXmiDeStlPKENalBcb38sEjrV0NOi5LzcoUKCt+lpAVnUjfiGj1IiHEHDDGcP5mAXaeycDv526hoMoteXr7u2F8z1YY06UF7Jvw7XcIqYpOpCcirVaL1NRUtG/fHjIZnWNRF8qLH2XFzxKyyi0ur7wlz5kMpGQVie3ezjYY17MVnunZCn7N7I1ehyVkZS4oK36WkBVNuqyAIAhISUlB27ZtzXZHMyeUFz/Kip+5ZqXWCohKzsbO2AxEJWdD88/nh0q5FKOCvDC+Vyv0a9scska8jYq5ZmWOKCt+lpAVTboIIcQKpWQWYeeZG9gdfxO5xRViezcfF4zv2QqPd/OGs62Z3iuFECtFky5CCLESBffU+P3cTeyMzUBCRoHY3txBhad7tMQzPVuhg6ejCSskpGmjSZcVkEql8PX1pQvncaK8+FFW/EyVlVZgOHY5FzvP3MDBpCxU/HNLHrlUgmEdPTC+pw8GBbhDITOfbUj7FT/Kip8lZEWrFxsRrV4khBhKWm4Jfo69gV/P3sTtgjKxPdDLEeN7+WBssDeaOdR9Sx5CSN1o9SIRabVaJCQkoGvXrmZ78qA5obz4UVb8GiOr4nINIhJuY2fsDZy+dldsd7ZVYGywN8b38kGQt5NZX6cIoP2qPigrfpaQFU26rIAgCEhPT0fnzp3NdkczJ5QXP8qKn7GyYozhZFoedp7JwL4Lt3Hvn1vySCXAwA7uGN/TB8M7eUBl4Bv8GhPtV/woK36WkBVNugghxAzdzC/FL7EZ+Dk2A+l598T2Ns3t8UyvVni6eyt4OduYsEJCSH3RpIsQQsxEmVqLA4mZ2HkmA8ev5EJ3xq2DSo7HurbA+F6t0MPXsLfkIYQ0Hpp0WQGpVIqAgACzXrFhTigvfpQVv4ZmxRhD/I187IzNwB/nbqGoTCM+FtKmGcb3aoVRnb1gp7SeH9e0X/GjrPhZQla0erER0epFQohOdlEZdp29iZ9jM5CaXSy2t3SxxTP/3JLHx83OhBUSQnQM9fvbfKeDhJtGo0F0dDQ0Gk3dnQnlVQ+UFT+erCo0AvZfuI1p351GyNLDWLovGanZxbBRSPFU95bY+u8+ODpvCOaM6GDVEy7ar/hRVvwsISuTTrqOHDmCxx9/HN7e3pBIJNi9e7f4mFqtxvz589GlSxfY29vD29sbL7zwAm7duqX3Gnl5eZg8eTKcnJzg4uKCadOmobi4WK9PQkICBgwYABsbG/j4+GD58uXVatm5cycCAwNhY2ODLl26ICIiQu9xxhgWLlyIFi1awNbWFsOHD0dqaqrhwngIjDHk5OSADlryobz4UVb8HpRV0q1ChP+RiL5LD+G1H8/iUHI2tAJDD18XLH26C059MByrng1Gv3bNIW3EeyCaCu1X/CgrfpaQlUknXSUlJejWrRvWrVtX7bF79+7h7NmzWLBgAc6ePYtff/0VKSkpeOKJJ/T6TZ48GYmJiYiMjMSePXtw5MgRvPLKK+LjhYWFGDlyJPz8/BAbG4sVK1Zg8eLF2Lhxo9gnOjoakyZNwrRp0xAXF4exY8di7NixuHDhgthn+fLl+OKLL/D111/j5MmTsLe3R2hoKMrKykAIIfe7W1KB746nIeyLoxjzxVFsOn4NeSUV8HBU4bVBbfHn3EH49fX+mNTbF042dA9EQpoCk56ZOXr0aIwePbrGx5ydnREZGanXtnbtWvTu3Rvp6enw9fXFxYsXsX//fpw+fRq9evUCAHz55ZcYM2YMPvvsM3h7e2PLli2oqKjAt99+C6VSiaCgIMTHx2PlypXi5GzNmjUYNWoU3nnnHQDARx99hMjISKxduxZff/01GGNYvXo1PvzwQzz55JMAgO+//x6enp7YvXs3Jk6caKyICCEWRMuAvy7lYFf8bfyZlI0KbeUteRQyCUZ08sT4nj4Y0L455GZ0Sx5CSOOxqOUwBQUFkEgkcHFxAQDExMTAxcVFnHABwPDhwyGVSnHy5Ek89dRTiImJwcCBA6FUKsU+oaGhWLZsGe7evQtXV1fExMRg7ty5eu8VGhoqftyZlpaGzMxMDB8+XHzc2dkZffr0QUxMTK2TrvLycpSXl4tfFxYWAqj86FStVgOoXG0hk8mg1WohCILYV9eu0Wj0DpXKZDJIpVK9dkEQ0K1bN8hkMvF1deTyyk18/2fctbUrFAoIggCtViu2SSQSyOXyWttrq/1hxlS13dBjEgQBXbp0gUwms5oxVa3dkGPSZSUIAgRBsIoxGWM7aZkE6/+6gi0JNrhzIk5sD/J2wjM9WiKsiydc7f75GcQEAFKzH5MxtxMABAcHA4BePZY8JmNtJ933oFQqBWPMKsZUV+0NHVPVn1cajcbgYzIEi5l0lZWVYf78+Zg0aZK4ciAzMxMeHh56/eRyOdzc3JCZmSn28ff31+vj6ekpPubq6orMzEyxrWqfqq9R9Xk19anJ0qVLER4eXq394MGDsLOrPEnW19cX3bt3R0JCAtLT08U+AQEBCAwMxKlTp5CTkyO2BwcHw8/PD0eOHEFRUZHYHhISAqlUin379untHEOGDIGtrW21c9TGjBmD0tJSREVFiW1yuRxhYWHIzc1FTEyM2O7o6IihQ4fixo0biI+PF9vd3d3Rr18/pKamIiUlRWw35Jg8PDxw8OBBo4ypTZs2uH79ulWNyVjb6fz581Y3JsAw2ynzHrAryxXJmZXPt5cz9GrO0K+FFK8+OwDZ2dmI+etPixpTY22nuLg4qxuTsbZT8+bNrW5MxtpO58+fN/iYjh8/DkMwm0tGSCQS7Nq1C2PHjq32mFqtxrhx45CRkYG//vpLnHR98skn2Lx5s16gAODh4YHw8HBMnz4dI0eOhL+/PzZs2CA+npSUhKCgICQlJaFjx45QKpXYvHkzJk2aJPZZv349wsPDkZWVhejoaPTv3x+3bt1CixYtxD4TJkyARCLB9u3baxxTTUe6fHx8kJubK47BEH9J6FZsDBo0qNoJhNb0F5+hxlQ1L6lUahVjqlq7IbeTWq1GdHQ0+vXrB5VKZRVjMtR2Yoxh25kMfLIvBWVqAW72CjzjD8wY2x92KqVFjomn3RBjEgQBx48fR//+/fWuqWTJYzLWdtL9vBo4cCDkcrlVjKmu2hs6pvLycvHnlUKhMOiY8vLy0KxZM+u/4bVarcaECRNw/fp1HD58WG+wXl5eyM7O1uuv0WiQl5cHLy8vsU9WVpZeH93XdfWp+riureqkKysrSzxEXhOVSgWVSlWtXaFQQKHQP3FWJpPVeK8o3c5XV3txcTEYY9Vet+p78rZLpdIaLy5XW3tttT/smB5UY33b769dl5c1jamu9oaMiTGG4uJiyOVy8TUtfUw1qe+YiisY5v+SgINJlT83BrRvjmVPBeH00UOwUyn1nmcpY2rM7aRWq1FUVASpVFrj61vimOpqf5gx6VbkSyQSqxlTQ9sfNCa5XC7+vNLVYOwx1ZdZn82pm3Clpqbizz//RLNmzfQeDwkJQX5+PmJjY8W2w4cPQxAE9OnTR+xz5MgRvRl2ZGQkAgIC4OrqKvY5dOiQ3mtHRkYiJCQEAODv7w8vLy+9PoWFhTh58qTYhxDSNERfycXoNUdxMCkLCpkEH4Z1xOapveHuWP0PLEIIqcqkR7qKi4tx+fJl8eu0tDTEx8fDzc0NLVq0wDPPPIOzZ89iz5490Gq14vlTbm5uUCqV6NixI0aNGoWXX34ZX3/9NdRqNWbOnImJEyfC29sbAPDcc88hPDwc06ZNw/z583HhwgWsWbMGq1atEt/3zTffxKBBg/D5558jLCwM27Ztw5kzZ8TLSkgkEsyePRsff/wx2rdvD39/fyxYsADe3t41fhxKCLE+aq2AVZGX8NXfV8AY0MbdHl9M7I7OLZ0BAFU+8SCEkJoxE4qKimIAqv2bMmUKS0tLq/ExACwqKkp8jTt37rBJkyYxBwcH5uTkxKZOncqKior03ufcuXPs0UcfZSqVirVs2ZJ9+umn1WrZsWMH69ChA1MqlSwoKIjt3btX73FBENiCBQuYp6cnU6lUbNiwYSwlJaVe4y0oKGAAWEFBQb2eVxetVsuysrKYVqs16OtaK8qLH2VV6VpuMXti7THmN38P85u/h737yzlWUq7W60NZ8aOs+FFW/IyZlaF+f5vNifRNAd17kRDL8+vZDCzYfQElFVo42cjx6biuGNOlRd1PJIRYDbr3IhGp1Wrs3bu32soQUjPKi19TzqqwTI3Z2+Iwd8c5lFRo0dvfDftnD6x1wtWUs6ovyoofZcXPErIy+9WLhI853+DTHFFe/JpiVrHX72L29jjcyCuFTCrB7GHt8fqQdpDVcV/EpphVQ1FW/CgrfuaeFU26CCHkH1qBYX3UZaw+lAqtwNDK1RZrJnZHTz9XU5dGCLECNOkihBAAt/JLMXt7PE6l5QEAngz2xkdjO9PNqAkhBkMn0jciY51IzxhDUVERHB0dIZE8+OMPQnnVR1PJat/525j/SwIKyzSwV8rw0djOeLpHq3q9RlPJyhAoK36UFT9jZmWo3990pMtK2NramroEi0J58bPmrO5VaPDRniT8dOoGAKCbjwu+mBgMv2b2DXo9a87K0CgrfpQVP3PPilYvWgGNRoOIiAizP4HQXFBe/Kw5qws3C/DYl8fw06kbkEiA1we3xc+vhTR4wmXNWRkaZcWPsuJnCVnRkS5CSJMiCAzfHk/Dsv3JUGsZvJxssPLZbujXtrmpSyOEWDmadBFCmozsojK8vTMBRy7lAABGdvLEsnFd4WqvNHFlhJCmgCZdhJAmISo5G2/vPIc7JRWwUUix4LFOeK63L52cTAhpNLR6sREZc/WiRqOBXC6nXyAcKC9+1pBVmVqLZfuTsen4NQBAoJcjvpzUHe09HQ36PtaQVWOhrPhRVvyMmRXdBojoKS0tNXUJFoXy4mfJWaVmFWHsuuPihGtq/9bYPaO/wSdcOpacVWOjrPhRVvzMPSuadFkBjUaDqKgos16xYU4oL36WmhVjDD+euI7HvjyG5MwiNLNXYtOLj2DR40GwUciM8p6WmpUpUFb8KCt+lpAVndNFCLEqd0sqMP+XBBxMygIADOzgjs/Gd4WHo42JKyOENHU06SKEWI3oK7mYsz0eWYXlUMgkmD8qEC/194e0jhtVE0JIY6BJl5WQy2lT1gflxc8SslJrBayKvISv/r4CxoA27vb4YmJ3dG7p3Kh1WEJW5oKy4kdZ8TP3rGj1YiMy1upFQpqya7kleHNbHM5lFAAAJvX2wYLHOsFOad4/fAkhloNWLxKRIAjIzs6GIAimLsUiUF78zDkrxhh+ic1A2BdHcS6jAM62Cnw1uQeWPt3VJBMuc87K3FBW/CgrfpaQFU26rIBWq0VMTAy0Wq2pS7EIlBc/c82qsEyN2dvj8dbOcyip0KKPvxv2vTkAo7u0MFlN5pqVOaKs+FFW/CwhKzr+TgixKLHX7+LNbXHIuFsKmVSCOcPbY/rgdpDRyfKEEDNHky5CiEXQCgzroy5j9aFUaAUGHzdbrJnYHT18XU1dGiGEcKFJlxWQSCRwdHSkW0Rworz4mUtWN/NLMWdbPE5dywMAPBnsjY/GdoaTjcKkdVVlLllZAsqKH2XFzxKyotWLjYhWLxJSfxHnb+PdXxJQWKaBvVKGj5/qjKe6tzJ1WYSQJoRWLxKRIAi4fv26Wa/YMCeUFz9TZnWvQoN3f0nA61vOorBMg24+Loh4c4DZTrhov+JHWfGjrPhZQlY06bICWq0W8fHxZr1iw5xQXvxMldWFmwV47Itj2Hb6BiQSYMaQtvj5tRD4NbNv1Drqg/YrfpQVP8qKnyVkRed0EULMhiAwfHs8Dcv2J0OtZfByssGqZ4MR0raZqUsjhJCHRpMuQohZyC4qw1s7zuFoai4AYGQnTywb1xWu9koTV0YIIYZBky4rIJFI4O7ubtYrNswJ5cWvsbKKSs7G2zvP4U5JBWwUUix8LAiTevtY1Dai/YofZcWPsuJnCVnR6sVGRKsXCdFXptbi033J+C76GgCgYwsnfDkpGO08HE1bGCGEVEGrF4lIq9UiOTnZrE8eNCeUFz9jZpWaVYSx646LE66X+vtj1+v9LHbCRfsVP8qKH2XFzxKyokmXFRAEASkpKWa9TNacUF78jJEVYww/nriOx748huTMIjR3UGLT1Eew8PFOsFHIDPY+jY32K36UFT/Kip8lZEXndBFCGs3dkgrM/yUBB5OyAAADO7jj8/Hd4O6oMnFlhBBifDTpIoQ0iujLuZizIx5ZheVQyqSYPzoQU/u1hpRuVE0IaSJo0mUFpFIpfH19IZXSp8U8KC9+hshKrRWwMvISvv77ChgD2rrbY83E7ujc0tmAlZoe7Vf8KCt+lBU/S8iKVi82Ilq9SJqaa7kleHNbHM5lFAAAJvX2xYLHOsJOSX/vEUIsB61eJCKtVou4uDizXrFhTigvfg3NijGGX2IzEPbFUZzLKICzrQJfTe6BpU93sdoJF+1X/CgrfpQVP0vIiiZdVkAQBKSnp5v1ig1zQnnxa0hWhWVqvLktHm/tPIeSCi36+Lth35sDMLpLCyNWanq0X/GjrPhRVvwsISvr/JOTEGISsdfv4s1tcci4WwqZVII5w9tj+uB2kNHJ8oQQQpMuQsjD0woM66IuY82hVGgFBh83W6yZ2B09fF1NXRohhJgNmnRZAalUioCAALNesWFOKC9+PFndzC/FnG3xOHUtDwAwNtgbH43tDEcbRWOVaRZov+JHWfGjrPhZQla0erER0epFYm0izt/Gu78koLBMAweVHB+NDcJT3VuZuixCCDEoWr1IRBqNBtHR0dBoNKYuxSJQXvxqy+pehQbzf07A61vOorBMg24+Ltg769EmPeGi/YofZcWPsuJnCVnRx4tWgDGGnJwc0EFLPpQXv5qyunCzALN+isPV3BJIJMDrg9ti9vAOUMia9t9wtF/xo6z4UVb8LCErmnQRQrgIAsP/HUvD8gPJUGsZvJxssOrZYIS0bWbq0gghxCLQpIsQUqeconLM33UWR1NzAQChQZ749OmucLVXmrgyQgixHDTpsgIymQzBwcGQyWSmLsUiUF78ZDIZSl3b4vF1MbhTUgEbhRQLHwvCpN4+kEjo2ltV0X7Fj7LiR1nxs4SsTHoSxpEjR/D444/D29sbEokEu3fv1nucMYaFCxeiRYsWsLW1xfDhw5GamqrXJy8vD5MnT4aTkxNcXFwwbdo0FBcX6/VJSEjAgAEDYGNjAx8fHyxfvrxaLTt37kRgYCBsbGzQpUsXRERE1LsWU5FKpfDz8zPrZbLmhPLio9EKWLLnIt6NuI47JRXo2MIJe954FM/18aUJVw1ov+JHWfGjrPhZQlYmraykpATdunXDunXranx8+fLl+OKLL/D111/j5MmTsLe3R2hoKMrKysQ+kydPRmJiIiIjI7Fnzx4cOXIEr7zyivh4YWEhRo4cCT8/P8TGxmLFihVYvHgxNm7cKPaJjo7GpEmTMG3aNMTFxWHs2LEYO3YsLly4UK9aTEWj0eDw4cNmvWLDnFBefNZGXcZ30dcAAC/288Ou1/uhnYejaYsyY7Rf8aOs+FFW/CwiK2YmALBdu3aJXwuCwLy8vNiKFSvEtvz8fKZSqdhPP/3EGGMsKSmJAWCnT58W++zbt49JJBJ28+ZNxhhj69evZ66urqy8vFzsM3/+fBYQECB+PWHCBBYWFqZXT58+fdirr77KXQuPgoICBoAVFBRwP4dHRUUF2717N6uoqDDo61oryqtucel3WZv39jK/+XvYext/o6w40H7Fj7LiR1nxM2ZWhvr9bbbndKWlpSEzMxPDhw8X25ydndGnTx/ExMRg4sSJiImJgYuLC3r16iX2GT58OKRSKU6ePImnnnoKMTExGDhwIJTK/53wGxoaimXLluHu3btwdXVFTEwM5s6dq/f+oaGh4sedPLXUpLy8HOXl5eLXhYWFAAC1Wg21Wg2g8nCoTCaDVqvVu0mnrl2j0egtf5XJZJBKpXrtute6//8BQC6v3MT3z/xra1coFBAEQe8u7RKJBHK5vNb22mp/mDFVbTf0mKq+nrWMqWrtDzumcg3D3O3x0AoMY4I80MfpFtRqtUWPqTG2U03fj5Y+ppraDTEmXZ+qfS19TMbaTrr/MsbAGLOKMdVVe0PHVDUzY4zJEMx20pWZmQkA8PT01Gv39PQUH8vMzISHh4fe43K5HG5ubnp9/P39q72G7jFXV1dkZmbW+T511VKTpUuXIjw8vFr7wYMHYWdnBwDw9fVF9+7dkZCQgPT0dLFPQEAAAgMDcerUKeTk5IjtwcHB8PPzw5EjR1BUVFTja1fdOYYMGQJbW9tq56iNGTMGpaWliIqKEtvkcjnCwsKQm5uLmJgYsd3R0RFDhw7FjRs3EB8fL7a7u7ujX79+SE1NRUpKithuqDGFhITAw8PDKGPSsaYxGWo7/XnXDVdzS+BmI8GjtrcAAJGRkRY9psbYTrpzSSMjI61mTMbaTq1aVV5ENzExERkZGVYxJmNvp+LiYjg6OlrVmIy1nSIjIw0+puPHj8MQzOY2QBKJBLt27cLYsWMBVJ5n1b9/f9y6dQstWrQQ+02YMAESiQTbt2/HJ598gs2bN+sFCgAeHh4IDw/H9OnTMXLkSPj7+2PDhg3i40lJSQgKCkJSUhI6duwIpVKJzZs3Y9KkSWKf9evXIzw8HFlZWVy11KSmI10+Pj7Izc0VbyNgiL8kBEFAfn4+3N3dq/3laE1/8RlqTIIgIC8vT5xEW8OYqtb+MNvpSGoupn1/FgDw3Ys9EeLvijt37qBZs2ZQKBQWOaaq7cbcToIgICsrC82aNRNP5LX0MdXUbogxARA/aajKksdkrO0kCALu3LkDT0/PGo+4WOKY6qr9YY506X5eyWQyg44pLy8PzZo1e+jbAJntkS4vLy8AQFZWlt5EJysrC8HBwWKf7OxsvedpNBrk5eWJz/fy8kJWVpZeH93XdfWp+nhdtdREpVJBpVJVa1coFFAo9G8GLJPJalzmqtv56mrXTSBqW7Vx//s9qF0qldb4OrW111b7w47pQTXWt/3+2qtuR2sZU13tdY3pbkkF3tuVCAB4sV9rDA6s3O+9vb31+lvSmO5nzO0kk8mqZQVY9phqazfEmO7/lKIqSx3Tg9ofZkxV9ytrGVND2x80JpVKVe170Nhjqi+zXVfp7+8PLy8vHDp0SGwrLCzEyZMnERISAqDykGV+fj5iY2PFPocPH4YgCOjTp4/Y58iRI3oz7MjISAQEBIh/ZYWEhOi9j66P7n14ajEltVqNvXv3VvsrgtSM8qqOMYYPd19AdlE52rrbY/6oQACUVX1QVvwoK36UFT9LyMqkk67i4mLEx8eLn8OmpaUhPj4e6enpkEgkmD17Nj7++GP8/vvvOH/+PF544QV4e3uLH0F27NgRo0aNwssvv4xTp07h+PHjmDlzJiZOnCjOdp977jkolUpMmzYNiYmJ2L59O9asWaN34vybb76J/fv34/PPP0dycjIWL16MM2fOYObMmQDAVYupmfUSWTNEeen7Lf4W9p6/DblUglXPBsNW+b+/ACkrfpQVP8qKH2XFz9yzMunHi2fOnMGQIUPEr3UToSlTpuC7777DvHnzUFJSgldeeQX5+fl49NFHsX//ftjY2IjP2bJlC2bOnIlhw4ZBKpVi3Lhx+OKLL8THnZ2dcfDgQcyYMQM9e/ZE8+bNsXDhQr1refXr1w9bt27Fhx9+iPfffx/t27fH7t270blzZ7EPTy2EWKKb+aVY8FvlNeneHNYeXVu5mLYgQgixUiaddA0ePPiBdwOXSCRYsmQJlixZUmsfNzc3bN269YHv07VrVxw9evSBfcaPH4/x48c/VC2EWBpBYHh7xzkUlWnQ3dcF0we3NXVJhBBitbhWL7q6unLf9iMvL++hi7JWhYWFcHZ2fujVD/djjKGoqAiOjo50exYOlNf//PfoVXy89yJsFTJEvDkA/s3t9R6nrPhRVvwoK36UFT9jZmWo399cR7pWr17d4DcgjcPW1tbUJVgUygu4lFWE5QcqL7fy4WMdq024dCgrfpQVP8qKH2XFz9yz4pp0TZkyxdh1kIeg0WgQERGBMWPG1Lr0lvwP5QVUaATM3haPCo2AIQHueK63b439KCt+lBU/yoofZcXPErJ6qHO6ysrKUFFRoddmyI/NCCHGsfrPS0i6XQhXOwWWPdOVPrYghJBGUO9LRpSUlGDmzJnw8PCAvb09XF1d9f4RQszb6Wt5+PrvKwCApU93gYcjrcAlhJDGUO9J17x583D48GF89dVXUKlU+O9//4vw8HB4e3vj+++/N0aNhBADKS7XYO6OeAgMGNejFUZ1blH3kwghhBhEve+96Ovri++//x6DBw+Gk5MTzp49i3bt2uGHH37ATz/9VO3GleR/jLl6UaPRQC6X08dEHJpyXvN/TsD2MzfQ0sUW+2YPgJPNg897aMpZ1RdlxY+y4kdZ8TNmVob6/V3vI115eXlo06YNgMrzt3SXiHj00Udx5MiRBhdCHk5paampS7AoTTGvyKQsbD9zAxIJ8PmEbnVOuHSaYlYNRVnxo6z4UVb8zD2rek+62rRpg7S0NABAYGAgduzYAQD4448/4OLiYtDiCB+NRoOoqCizv/2BuWiKeeUWl+PdXxIAAK8MaIO+bZpxPa8pZtVQlBU/yoofZcXPErKq96Rr6tSpOHfuHADg3Xffxbp162BjY4M5c+bgnXfeMXiBhJCHwxjDu7+cx52SCgR6OWLuyA6mLokQQpqkel8yYs6cOeL/Dx8+HMnJyYiNjUW7du3QtWtXgxZHCHl4O87cwJ8Xs6CUSbHq2WCo5LK6n0QIIcTg6n2k6/vvv0d5ebn4tZ+fH55++mkEBgbS6kUTkstNehtNi9NU8kq/cw9L/kgCALw1sgM6tqj/CaBNJStDoKz4UVb8KCt+5p5VvVcvymQy3L59Gx4eHnrtd+7cgYeHB7RarUELtCbGWr1ISE20AsOzG2Jw5vpd9PZ3w08v94VMSqufCCGkvky2epExVuNSzIyMDDg7Oze4ENJwgiAgOzsbgiCYuhSL0FTy2nDkCs5cvwsHlRyfj+/WoAlXU8nKECgrfpQVP8qKnyVkxT3p6t69O3r06AGJRIJhw4ahR48e4r9u3bphwIABGD58uDFrJbXQarWIiYmho4ycmkJeF24WYFXkJQDAosc7wcfNrkGv0xSyMhTKih9lxY+y4mcJWXF/+Dl27FgAQHx8PEJDQ+Hg4CA+plQq0bp1a4wbN87gBRJC6qdMrcWc7fFQaxlCgzzxTM9Wpi6JEEII6jHpWrRoEQCgdevWePbZZ2FjQ/drI8QcrTiQgtTsYjR3UOGTp7rQVawJIcRM1Ps0/ylTpgAAYmNjcfHiRQBAUFAQunfvbtjKCDeJRAJHR0f65crJmvOKvpyL/ztWefHi5c90QTMH1UO9njVnZWiUFT/Kih9lxc8Ssqr36sXs7GxMnDgRf/31l3gF+vz8fAwZMgTbtm2Du7u7Meq0CrR6kRhTQakao1cfwa2CMjzXxxefPNXF1CURQohVMNnqxTfeeANFRUVITExEXl4e8vLycOHCBRQWFmLWrFkNLoQ0nCAIuH79ulmv2DAn1prX4t8TcaugDH7N7PDBmI4GeU1rzcoYKCt+lBU/yoqfJWRV70nX/v37sX79enTs+L8f6p06dcK6deuwb98+gxZH+Gi1WsTHx5v1ig1zYo157Um4hV1xNyGVACsnBMNeZZgLBFpjVsZCWfGjrPhRVvwsIat6T7oEQYBCoajWrlAozHp2SYi1yioswwe7LgAAZgxph55+riauiBBCSE24J13p6ekQBAFDhw7Fm2++iVu3bomP3bx5E3PmzMGwYcOMUiQhpGaMMbzzcwIKStXo0tIZs4a1N3VJhBBCasE96fL390dubi7Wrl2LwsJCtG7dGm3btkXbtm3h7++PwsJCfPnll8asldRCIpHA3d3drFdsmBNryuvHE9dx5FIOVHIpVj3bDQpZvQ9eP5A1ZWVslBU/yoofZcXPErLiXr0olUqRmZkJDw8PMMbw559/Ijk5GQDQsWNHuho9B1q9SAzpSk4xwr44ijK1gEWPd8LU/v6mLokQQqySSVYv6maPEokEI0aMwBtvvIE33niDJlwmptVqkZycbNYnD5oTa8hLrRUwd3s8ytQCHm3XHFNCWhvlfawhq8ZCWfGjrPhRVvwsIat6LXFasGAB7OwefA+3lStXPlRBpP4EQUBKSgratm0LmUxm6nLMnjXktfbwZZzLKICTjRwrxneFtAE3s+ZhDVk1FsqKH2XFj7LiZwlZ1WvSdf78eSiVylofN+fPUQmxFvE38rE26jIA4OOnuqCFs62JKyKEEMKjXpOuXbt2wcPDw1i1EELqcK9Cgznb46EVGJ7o5o0nunmbuiRCCCGcuM/poqNY5ksqlcLX1xdSqWFXrlkrS85raUQy0nJL4OVkg4+e7Gz097PkrBobZcWPsuJHWfGzhKwatHqRNAytXiQPIyolG1M3nQYA/DCtNwa0p/ucEkJIY2j01YubNm2Cs7Nzg9+IGI9Wq0VcXJxZr9gwJ5aY192SCsz7OQEA8GK/1o024bLErEyFsuJHWfGjrPhZQlbck64pU6ZApVIBAFJSUjBz5kwMGzYMw4YNw8yZM5GSkmK0IsmDCYIg3jGA1M3S8mKM4YPd55FTVI627vZ4d3Rgo723pWVlSpQVP8qKH2XFzxKyqvcHn7/88gs6d+6M2NhYdOvWDd26dcPZs2fRuXNn/PLLL8aokZAmbXf8TUScz4RcKsHqZ7vDRmGeS6EJIYQ8WL1WLwLAvHnz8N5772HJkiV67YsWLcK8efMwbtw4gxVHSFN3M78UC3cnAgDeHNYeXVrRR/yEEGKp6n2k6/bt23jhhReqtf/rX//C7du3DVIUqR+pVIqAgACzXrFhTiwlL0FgeGtHPIrKNeju64Lpg9s2eg2WkpU5oKz4UVb8KCt+lpBVvSsbPHgwjh49Wq392LFjGDBggEGKIvUjk8kQGBhotlfgNTeWkte3x9Nw4moebBUyrJoQDLmBb2bNw1KyMgeUFT/Kih9lxc8Ssqr3T/EnnngC8+fPx8yZM/Hjjz/ixx9/xMyZM/Huu+/iqaeewu+//y7+I41Do9EgOjoaGo3G1KVYBEvIKyWzCMsPVC5OWfBYJ7Rubm+SOiwhK3NBWfGjrPhRVvwsIat6n9P1+uuvAwDWr1+P9evX1/gYUHkxVXNetmlNGGPIyckB5yXXmjxzz6tco8Xs7fGo0AgYGuiBSb19TFaLuWdlTigrfpQVP8qKnyVkVe9JlzkvxSTEGqz+MxUXbxfC1U6BT8d1obtBEEKIlTDfs80IaYJOX8vD139fAQAsfboLPBxtTFwRIYQQQ6n3kS4AOH36NKKiopCdnV3tyNfKlSsNUhjhJ5PJEBwcbNYnD5oTc82ruFyDuTviwRjwTM9WGNW5halLMtuszBFlxY+y4kdZ8bOErLjvvajzySef4MMPP0RAQAA8PT31PvqQSCQ4fPiwwYu0FnTvRfIg839OwPYzN9DSxRb7Zw+Ao43C1CURQgiBCe69qLNmzRp8++23uHjxIv766y9ERUWJ/2jCZRoajQaHDx826xUb5sQc8zqYmIntZ25AIgFWTuhmNhMuc8zKXFFW/CgrfpQVP0vIqt6TLqlUiv79+xujFtJAjDEUFRWZ9YoNc2JueeUUleO9X88DAF4Z0AZ92jQzcUX/Y25ZmTPKih9lxY+y4mcJWdV70jVnzhysW7fOGLUQ0uQwxvDerwm4U1KBQC9HzB3ZwdQlEUIIMZJ6T7refvttpKSkoG3btnj88cfx9NNP6/0zJK1WiwULFsDf3x+2trZo27YtPvroI71ZLGMMCxcuRIsWLWBra4vhw4cjNTVV73Xy8vIwefJkODk5wcXFBdOmTUNxcbFen4SEBAwYMAA2Njbw8fHB8uXLq9Wzc+dOBAYGwsbGBl26dEFERIRBx0uanh1nbuDPi9lQyqRY9WwwVHLzPQGUEELIw6n3pGvWrFmIiopChw4d0KxZMzg7O+v9M6Rly5bhq6++wtq1a3Hx4kUsW7YMy5cvx5dffin2Wb58Ob744gt8/fXXOHnyJOzt7REaGoqysjKxz+TJk5GYmIjIyEjs2bMHR44cwSuvvCI+XlhYiJEjR8LPzw+xsbFYsWIFFi9ejI0bN4p9oqOjMWnSJEybNg1xcXEYO3Ysxo4diwsXLhh0zA0hk8kQEhJi1is2zIm55HX9TgnC/0gCALwd2gEdW5jf4gpzycoSUFb8KCt+lBU/i8iK1ZODgwPbs2dPfZ/WIGFhYeyll17Sa3v66afZ5MmTGWOMCYLAvLy82IoVK8TH8/PzmUqlYj/99BNjjLGkpCQGgJ0+fVrss2/fPiaRSNjNmzcZY4ytX7+eubq6svLycrHP/PnzWUBAgPj1hAkTWFhYmF4tffr0Ya+++ir3eAoKChgAVlBQwP0cYp00WoE9vf4485u/h034OppptIKpSyKEEFILQ/3+rvd1utzc3NC2bVuDT/5q0q9fP2zcuBGXLl1Chw4dcO7cORw7dky8FlhaWhoyMzMxfPhw8TnOzs7o06cPYmJiMHHiRMTExMDFxQW9evUS+wwfPhxSqRQnT57EU089hZiYGAwcOBBKpVLsExoaimXLluHu3btwdXVFTEwM5s6dq1dfaGgodu/eXWv95eXlKC8vF78uLCwEAKjVaqjVagCVCxNkMhm0Wq3eNc907RqNRu/jVJlMBqlUqteuVqtx+PBhhIaGVqtBLq/cxPev5qitXaFQQBAEvVs4SSQSyOXyWttrq/1hxlS1XZeVocZUNS9dnY09pvWHLyH2+l3Yq2RY9nQQpJLKj8rNbTtVVFTg8OHDGDp0KGxsbBp1OxlrTMba99RqNQ4ePIihQ4dCoVBYxZhqajfEmLRaLQ4dOoRhw4bpHZWw5DEZazvpfl6NHDkSCoXCKsZUV+0NHVNZWZn480qpVBp8TIZQ70nX4sWLsWjRImzatAl2dnYGKaI27777LgoLC8W7hmu1WvznP//B5MmTAQCZmZkAAE9PT73neXp6io9lZmbCw8ND73G5XA43Nze9Pv7+/tVeQ/eYq6srMjMzH/g+NVm6dCnCw8OrtR88eFDMztfXF927d0dCQgLS09PFPgEBAQgMDMSpU6eQk5MjtgcHB8PPzw9HjhxBUVFRja9ddecYMmQIbG1tq51/NmbMGJSWliIqKkovl7CwMOTm5iImJkZsd3R0xNChQ3Hjxg3Ex8eL7e7u7ujXrx9SU1ORkpIithtqTCEhIfDw8DDKmHRMMaZstQqrDl0GAIxtVYFz0VFwM/PtFBkZaZLtZEn7XnFxMbRaLSIjI61mTMbaTq1atYJGo0FiYiIyMjKsYkzG3k7FxcVwdHS0qjEZaztFRkYafEzHjx+HIdT74qjdu3fHlStXwBhD69atxb/odM6ePWuQwgBg27ZteOedd7BixQoEBQUhPj4es2fPxsqVKzFlyhRER0ejf//+uHXrFlq0+N/VuydMmACJRILt27fjk08+webNm/VCBwAPDw+Eh4dj+vTpGDlyJPz9/bFhwwbx8aSkJAQFBSEpKQkdO3aEUqnE5s2bMWnSJLHP+vXrER4ejqysrBrrr+lIl4+PD3Jzc8WLqxnqSFdkZCTGjBlTrQZr+ovPUGOqmldjH+nSCMAT66KRml2MkZ08sHZiN/E9H2ZMVWs39JGuyMhIjBgxgo501TEmtVqNffv2YcSIEXSkq44xabVaHDhwQDzabA1jMuaRrsjISIwePZqOdHEc6dL9vDL0ka68vDw0a9bsoS+OWu8jXWPHjm3wm9XXO++8g3fffRcTJ04EAHTp0gXXr1/H0qVLMWXKFHh5eQEAsrKy9CZdWVlZCA4OBgB4eXkhOztb73U1Gg3y8vLE53t5eVWbOOm+rquP7vGaqFQqqFSqau0KhaLaZFUmk9V48p9u5+Ntv/91G9IulUohlVZfY1Fbe22105iqt3+6Jwmp2cVo7qDCp+O66X2kXVvttbU3xph0P3wUCoX4mk1hOz2oxtradXfnuP/725LHVFu7IcdU0+tb+piMsZ0kEgkkEolVjakh7Q8aU9U/dnQ1GHtM9VXvV1m0aJFB3pjHvXv3qoUrk8nE2am/vz+8vLxw6NAhcZJVWFiIkydPYvr06QAqD2vm5+cjNjYWPXv2BAAcPnwYgiCgT58+Yp8PPvgAarVa3GiRkZEICAiAq6ur2OfQoUOYPXu2WEtkZCRCQkKMNn5ecrkcQ4YMMdhOYe1Mldfxy7n4v2NpAIAVz3SFm72yjmeYHu1b/CgrfpQVP8qKnyVk1eDKYmNjcfHiRQBAUFAQunfvbrCidB5//HH85z//ga+vL4KCghAXF4eVK1fipZdeAlA58589ezY+/vhjtG/fHv7+/liwYAG8vb3FI3IdO3bEqFGj8PLLL+Prr7+GWq3GzJkzMXHiRHh7ewMAnnvuOYSHh2PatGmYP38+Lly4gDVr1mDVqlViLW+++SYGDRqEzz//HGFhYdi2bRvOnDmjd1kJU7K1tTV1CRalsfMqKFXj7Z3nAADP9fHFkECPOp5hPmjf4kdZ8aOs+FFW/Mw+q/oud8zKymJDhgxhEomEubq6MldXVyaRSNjQoUNZdnZ2fV/ugQoLC9mbb77JfH19mY2NDWvTpg374IMP9C7tIAgCW7BgAfP09GQqlYoNGzaMpaSk6L3OnTt32KRJk5iDgwNzcnJiU6dOZUVFRXp9zp07xx599FGmUqlYy5Yt2aefflqtnh07drAOHTowpVLJgoKC2N69e+s1HmNdMqKiooLt3r2bVVRUGPR1rZUp8nrzp7PMb/4eNmj5YVZcpm60931YtG/xo6z4UVb8KCt+xszKZJeMeOONN1BUVITExER07NgRQOVJ51OmTMGsWbPw008/GWxC6OjoiNWrV2P16tW19pFIJFiyZAmWLFlSax83Nzds3br1ge/VtWtXHD169IF9xo8fj/Hjxz+wDyH325NwC7vjb0EqAVY+Gwx7lfke+iaEEGI89f7pv3//fvz555/ihAsAOnXqhHXr1mHkyJEGLY4QS5dZUIYPdlXetWDmkHbo4etq4ooIIYSYSr1vAyQIQo0rCnRLOQkhlRhjeOfncygoVaNLS2e8May9qUsihBBiQvW+TteTTz6J/Px8/PTTT+KJ6Ddv3sTkyZPh6uqKXbt2GaVQa1BYWAhnZ+eHvs7H/dg/VzKXy+XisnVSu8bK6/uYa1j4WyJUcin2zhqAdh4ORnsvY6F9ix9lxY+y4kdZ8TNmVob6/V3vI11r165FYWEhWrdujbZt26Jt27bw9/dHYWGh3o2oSeMqLS01dQkWxdh5XckpxicRlat73xsdaJETLh3at/hRVvwoK36UFT9zz6reky4fHx+cPXsWe/fuxezZszF79mxERETg7NmzaNWqlTFqJHXQaDSIiooy2L2hrJ2x81JrBczdHo8ytYAB7ZvjhZDWRnmfxkD7Fj/Kih9lxY+y4mcJWTVoGZVEIsGIESMwYsQIQ9dDiMVbe/gyzmUUwNlWgRXPdINUSh8JEEIIqceRrsOHD6NTp04oLCys9lhBQQGCgoLqvOQCIdYuLv0u1kZV3sz647Gd4eVsY+KKCCGEmAvuSdfq1avx8ssv13gCmbOzM1599VWsXLnSoMURfuZ82wNzZIy87lVoMHfHOWgFhie6eePxbt4Gfw9ToH2LH2XFj7LiR1nxM/esuFcv+vn5Yf/+/XrX56oqOTkZI0eORHp6ukELtCbGWr1IzMOHu8/jxxPp8HKywYHZA+FsV/NNXAkhhFiWRl+9mJWVVeudwIHK2WVOTk6DCyENJwgCsrOz6TppnIyRV1RKNn48UfkHx2fju1nNhIv2LX6UFT/Kih9lxc8SsuKedLVs2RIXLlyo9fGEhAS0aNHCIEWR+tFqtYiJiYFWqzV1KRbB0HndLanAvJ8TAABT+7fGo+2bG+R1zQHtW/woK36UFT/Kip8lZMU96RozZgwWLFiAsrKyao+VlpZi0aJFeOyxxwxaHCHmjjGG93edR05ROdp5OGD+qEBTl0QIIcRMcZ9x9uGHH+LXX39Fhw4dMHPmTAQEBACoPJdr3bp10Gq1+OCDD4xWKCHmaFfcTey7kAm5VILVzwbDRiEzdUmEEELMFPeky9PTE9HR0Zg+fTree+896M6/l0gkCA0Nxbp16+Dp6Wm0QkntJBIJHB0d6RYRnAyV1838Uiz6LREAMHt4e3Ru6WyI8swK7Vv8KCt+lBU/yoqfJWRV73svAsDdu3dx+fJlMMbQvn17uLq6GqM2q0OrF62HIDA8998TOHE1Dz18XbDj1RDIZfW+wQMhhBALYLJ7LwKAq6srHnnkEfTu3ZsmXGZAEARcv37drFdsmBND5PXt8TScuJoHO6UMKycEW+2Ei/YtfpQVP8qKH2XFzxKyss7fFE2MVqtFfHy8Wa/YMCcPm1dKZhGW708BACx4rBNaN7c3ZHlmhfYtfpQVP8qKH2XFzxKyokkXIfVQrtFi9vZ4VGgFDAv0wMRHfExdEiGEEAtBky5C6mFVZCou3i6Em70SS8d1MesTNgkhhJgXmnRZAYlEAnd3d5oAcGpoXqev5WHDkSsAgE+e6gIPR+u/mTXtW/woK36UFT/Kip8lZNWg1YupqamIioqq8XL7CxcuNFhx1oZWL1quojI1Rq85ioy7pRjfsxVWjO9m6pIIIYQ0EkP9/q737bi/+eYbTJ8+Hc2bN4eXl5fejFIikdCkywS0Wi1SU1PRvn17yGR0cc66NCSvj/YkIeNuKVq52mLh452MXKH5oH2LH2XFj7LiR1nxs4Ss6v3x4scff4z//Oc/yMzMRHx8POLi4sR/Z8+eNUaNpA6CICAlJcWsl8mak/rmdSAxEzvOZEAiAVZOCIajjXXczJoH7Vv8KCt+lBU/yoqfJWRV70nX3bt3MX78eGPUQojZySkqx3u/ngcAvDKwDXr7u5m4IkIIIZaq3pOu8ePH4+DBg8aohRCzwhjDe78mIK+kAoFejpg7ooOpSyKEEGLB6n1OV7t27bBgwQKcOHECXbp0gUKh/1HLrFmzDFYc4SOVSuHr6wuplBaj8uDNa/vpG/jzYjaUMilWTwyGSm6e5wgYE+1b/CgrfpQVP8qKnyVkVe/Vi/7+/rW/mESCq1evPnRR1opWL1qO63dKMHrNUdyr0OKDMR3x8sA2pi6JEEKIiZjs3otpaWm1/qMJl2lotVrExcWZ9a0PzEldeWm0AuZsj8e9Ci36+Lth2qO1/6Fh7Wjf4kdZ8aOs+FFW/CwhK/M9Bke4CYKA9PR0s16xYU7qymvDkas4m54PB5Ucn0/oBqnUfC+0Z2y0b/GjrPhRVvwoK36WkFW9z+kCgIyMDPz+++9IT09HRUWF3mMrV640SGGEmMKFmwVYFXkJABD+RBBaudqZuCJCCCHWot6TrkOHDuGJJ55AmzZtkJycjM6dO+PatWtgjKFHjx7GqJGQRlGm1mLO9nhoBIbRnb3wdI+Wpi6JEEKIFan3x4vvvfce3n77bZw/fx42Njb45ZdfcOPGDQwaNIiu32UiUqkUAQEBZr1iw5zUltfy/SlIzS6Gu6MK/3mKbmYN0L5VH5QVP8qKH2XFzxKyqvfqRUdHR8THx6Nt27ZwdXXFsWPHEBQUhHPnzuHJJ5/EtWvXjFSq5aPVi+br+OVcTP7vSQDApqmPYEiAh4krIoQQYi5MtnrR3t5ePI+rRYsWuHLlivhYbm5ugwshDafRaBAdHQ2NRmPqUizC/XkVlKrx9s5zAIDJfXxpwlUF7Vv8KCt+lBU/yoqfJWRV73O6+vbti2PHjqFjx44YM2YM3nrrLZw/fx6//vor+vbta4waSR0YY8jJyUE9D1o2Wffntei3C7hdUIbWzezwQVhHE1dnXmjf4kdZ8aOs+FFW/Cwhq3pPulauXIni4mIAQHh4OIqLi7F9+3a0b9+eVi4Si/PHuVvYHX8LMqkEq54Nhp2yQQt6CSGEkDrV+zdMmzb/uzK3vb09vv76a4MWREhjySwsw4e7LwAAZgxph+6+riauiBBCiDUz31P8CTeZTIbg4GDIZE3v3oANIZPJ0K1bN7y/OwkFpWp0beWMN4a2M3VZZon2LX6UFT/Kih9lxc8SsuI60uXm5oZLly6hefPmcHV1feBS+ry8PIMVR/hIpVL4+fmZugyLIZVKceQ2cDQ1Fyq5FCsnBEMho78/akL7Fj/Kih9lxY+y4mcJWXFNulatWgVHR0cAwOrVq41ZD2kAjUaDI0eOYODAgZDL6ZykuqTczsfHfyQCAN4f0xHtPBxMXJH5on2LH2XFj7LiR1nxs4SsuKqaMmVKjf9PzANjDEVFRWa9YsNcqLUC3v75PCoE4NF2zfB8X/P+q8jUaN/iR1nxo6z4UVb8LCErrklXYWEh9wvSRT+JOfvv0TScv1kIOxnD0qeCmvTNrAkhhDQurkmXi4sL9y1RtFrtQxVEiLFkF5Vh7eFUAMBTrQV4OdmYuCJCCCFNCdekKyoqSvz/a9eu4d1338WLL76IkJAQAEBMTAw2b96MpUuXGqdK8kAymQwhISFmvWLDHHx2IAUlFVp0a+WMN55oT3lxoH2LH2XFj7LiR1nxs4Ss6n3vxWHDhuHf//43Jk2apNe+detWbNy4EX/99Zch67MqdO9F07lwswCPrz0GxoBfX++HHnRNLkIIIZxMdu/FmJgY9OrVq1p7r169cOrUqQYXQhpOrVZj7969UKvVpi7FLDHGEP5HIhgDxgZ7o0sLB8qLE+1b/CgrfpQVP8qKnyVkVe9Jl4+PD7755ptq7f/973/h4+NjkKKqunnzJv71r3+hWbNmsLW1RZcuXXDmzBnxccYYFi5ciBYtWsDW1hbDhw9Hamqq3mvk5eVh8uTJcHJygouLC6ZNmybeykgnISEBAwYMgI2NDXx8fLB8+fJqtezcuROBgYGwsbFBly5dEBERYfDxNpQ53+DT1Paev43T1+7CRiHFvFGBACiv+qCs+FFW/CgrfpQVP3PPqt6TrlWrVuHLL79Ely5d8O9//xv//ve/0bVrV3z55ZdYtWqVQYu7e/cu+vfvD4VCgX379iEpKQmff/45XF3/99HQ8uXL8cUXX+Drr7/GyZMnYW9vj9DQUJSVlYl9Jk+ejMTERERGRmLPnj04cuQIXnnlFfHxwsJCjBw5En5+foiNjcWKFSuwePFibNy4UewTHR2NSZMmYdq0aYiLi8PYsWMxduxYXLhwwaBjJoZVptZiaUQyAOC1QW3h7WJr4ooIIYQ0VfW+etiYMWNw6dIlfPXVV0hOrvxl9vjjj+O1114z+JGuZcuWwcfHB5s2bRLb/P39xf9njGH16tX48MMP8eSTTwIAvv/+e3h6emL37t2YOHEiLl68iP379+P06dPix6JffvklxowZg88++wze3t7YsmULKioq8O2330KpVCIoKAjx8fFYuXKlODlbs2YNRo0ahXfeeQcA8NFHHyEyMhJr166l+0+asW+OXMXN/FJ4O9vg1YFtTV0OIYSQJqzeJ9I3pk6dOiE0NBQZGRn4+++/0bJlS7z++ut4+eWXAQBXr15F27ZtERcXh+DgYPF5gwYNQnBwMNasWYNvv/0Wb731Fu7evSs+rtFoYGNjg507d+Kpp57CCy+8gMLCQuzevVvsExUVhaFDhyIvLw+urq7w9fXF3LlzMXv2bLHPokWLsHv3bpw7d67G+svLy1FeXi5+XVhYCB8fH+Tm5oon4kmlUshkMmi1WgiCIPbVtWs0Gr0LvclkMkilUr12xhju3bsHZ2fnaodWdVfl5W1XKBQQBEHv0h8SiQRyubzW9tpqf5gxVW2///N53jFlFZZhxOpjKFULWP1sN4R19hTzKi4uhqurKxhjFjUmncbaToIgoLi4GA4ODpDL5VYxJmNtJ8YY8vPz4eDgIF5ix9LHVFO7IcYkkUhw79492NnZ6dVoyWMy1nbS/bzSXbrJGsZUV+0NHZNGoxF/XkmlUoOOKS8vD82aNXvoE+kbdJ38o0ePYsOGDbh69Sp27tyJli1b4ocffoC/vz8effTRBhdzv6tXr+Krr77C3Llz8f777+P06dOYNWsWlEolpkyZgszMTACAp6en3vM8PT3FxzIzM+Hh4aH3uFwuh5ubm16fqkfQqr5mZmYmXF1dkZmZ+cD3qcnSpUsRHh5erf3gwYOws7MDAPj6+qJ79+5ISEhAenq62CcgIACBgYE4deoUcnJyxPbg4GD4+fnhyJEjKCoqEtsfeeQRODs74+DBg3o76pAhQ2Bra1vt/LMxY8agtLRU73IgcrkcYWFhyM3NRUxMjNju6OiIoUOH4saNG4iPjxfb3d3d0a9fP6SmpiIlJUVsN9SYQkJC4OHh0eAx/XhZilK1FD39XBHirdDr7+DgYJFjAqxvO1nLmO7du4ejR49a1ZiMuZ06d+6M8+fPW9WYjLmdBg8eDDs7O6sakyVtp+PHj8MQ6n2k65dffsHzzz+PyZMn44cffkBSUhLatGmDtWvXIiIiwqAnlyuVSvTq1QvR0dFi26xZs3D69GnExMQgOjoa/fv3x61bt9CiRQuxz4QJEyCRSLB9+3Z88skn2Lx5s17oAODh4YHw8HBMnz4dI0eOhL+/PzZs2CA+npSUhKCgICQlJaFjx45QKpXYvHmz3qUy1q9fj/DwcGRlZdVYf2Md6VKr1YiMjMSYMWOq1WBNf/HVZ0znMgrwzIaTAIDfZvRHl5ZOYu1V89LVaQljqqqxtlNFRQUiIyMxYsQI2NjYWMWYjLWd1Go19u3bhxEjRkChUFjFmGpqN8SYtFotDhw4gNDQUL1rKlnymIy1nXQ/r0aPHg2FQmEVY6qr9oaOqaysTPx5pVQqreNI18cff4yvv/4aL7zwArZt2ya29+/fHx9//HGDC6lJixYt0KlTJ722jh074pdffgEAeHl5AQCysrL0Jl1ZWVnix41eXl7Izs7Wew2NRoO8vDzx+V5eXtUmTrqv6+qje7wmKpUKKpWqWrtCoRB/KOvIZLIaL+hW2007a2u//3Ub0i6VSiGVVl9jUVt7bbWbakxyuRyf7KucZI/r0QrdfFzE+u9nKWMy1XbS/fBRKBTia1r6mGpiiDFV/Uix6uOWPKba2g05pppe39LHZIztJJFIIJFIrGpMDWl/0Jiq/rGjq8HYY6qveq9eTElJwcCBA6u1Ozs7Iz8/3xA1ifr371/tCNWlS5fg51d5k2J/f394eXnh0KFD4uOFhYU4efKkeLX8kJAQ5OfnIzY2Vuxz+PBhCIKAPn36iH2OHDmiNwuPjIxEQECAuFIyJCRE7310fXTvQ8zH7+du4Wx6PuyUMswbFWDqcgghhBAADZh0eXl54fLly9Xajx07hjZt2hikKJ05c+bgxIkT+OSTT3D58mXxqvczZswAUDnznz17Nj7++GP8/vvvOH/+PF544QV4e3tj7NixACqPjI0aNQovv/wyTp06hePHj2PmzJmYOHEivL29AQDPPfcclEolpk2bhsTERGzfvh1r1qzB3LlzxVrefPNN7N+/H59//jmSk5OxePFinDlzBjNnzjTomMnDuVehwaf7KlfVvj64LTzp/oqEEELMBaunTz75hHXq1ImdOHGCOTo6sqNHj7Iff/yRubu7sy+++KK+L1enP/74g3Xu3JmpVCoWGBjINm7cqPe4IAhswYIFzNPTk6lUKjZs2DCWkpKi1+fOnTts0qRJzMHBgTk5ObGpU6eyoqIivT7nzp1jjz76KFOpVKxly5bs008/rVbLjh07WIcOHZhSqWRBQUFs79699RpLQUEBA8AKCgrq9by6CILAKioqmCAIBn1dS7TyYArzm7+H9Vt6iJVWaGrsQ3nxo6z4UVb8KCt+lBU/Y2ZlqN/f9T6RnjGGTz75BEuXLsW9e/cAVJ679Pbbb+Ojjz4ywrTQehjr3ouMMRQVFcHR0VE8r6QpupVfiqGf/4UytYB1z/VAWNcWNfajvPhRVvwoK36UFT/Kip8xszLZvRclEgk++OAD5OXl4cKFCzhx4gRycnJowmVCGo0GUVFRZn/7A2P7dF8yytQCerd2w5gutS9woLz4UVb8KCt+lBU/yoqfJWTV4NPxlUpltZWFhJhK7PU8/H7uFiQSYOHjnegvQkIIIWaHe9L10ksvcfX79ttvG1wMIQ0hCAxL/kgCAEzo6YPOLZ1NXBEhhBBSHfek67vvvoOfnx+6d++Oep4GRhqBoa4hYol2xd3EuYwCOKjkeDuU7xIRTTmv+qKs+FFW/CgrfpQVP3PPivtE+hkzZuCnn36Cn58fpk6din/9619wc3Mzdn1WxVgn0jdlJeUaDPnsL2QXlePd0YF4bRDd1JoQQohhNfqJ9OvWrcPt27cxb948/PHHH/Dx8cGECRNw4MABOvJlYoIgIDs7W++WBk3FV39dQXZROXzd7DC1f2uu5zTlvOqLsuJHWfGjrPhRVvwsIat6rV5UqVSYNGkSIiMjxXsTvv7662jdujWKi4uNVSOpg1arRUxMjN79qJqCG3n3sPHoVQDA+2M6QiWvfkuHmjTVvBqCsuJHWfGjrPhRVvwsIat6XzJCfKJUColEAsaYWQ+QWK9P9yWjQiMgpE0zhAZ5mrocQggh5IHqNekqLy/HTz/9hBEjRqBDhw44f/481q5di/T0dDg4OBirRkKqOXn1Dvaevw0pXSKCEEKIheA+zf/111/Htm3b4OPjg5deegk//fQTmjdvbszaCCeJRNKkrlasFRiW7Km8RMTE3r7o2KJ+JzU2tbweBmXFj7LiR1nxo6z4WUJW3KsXpVIpfH190b179wcO6NdffzVYcdaGVi8axo7TNzDvlwQ42sjx19uD0cxBZeqSCCGEWLFGX734wgsvYMiQIXBxcYGzs3Ot/0jjEwQB169fN+sVG4ZSVKbG8gMpAIA3h7Vv0ISrKeX1sCgrfpQVP8qKH2XFzxKyqtfFUYl50mq1iI+Ph7e3N6TSBq+NsAjroq4gt7gcbZrb44WQ1g16jaaU18OirPhRVvwoK36UFT9LyMo8qyKkBtfvlODbY2kAgA/COkIpp92XEEKI5aDfWsRifBJxERVaAQPaN8fQQA9Tl0MIIYTUC026rIBEIoG7u7tZr9h4WNFXcnEgMQsyqQQLHnu4S0Q0hbwMhbLiR1nxo6z4UVb8LCEr7tWL5OHR6sWG0QoMYV8cRXJmEV4I8cOSJzubuiRCCCFNSKOvXiTmS6vVIjk52WrvDLDtdDqSM4vgbKvAnOEdHvr1rD0vQ6Ks+FFW/CgrfpQVP0vIiiZdVkAQBKSkpJj1MtmGKixT4/ODlwAAs4e3h6u98qFf05rzMjTKih9lxY+y4kdZ8bOErGjSRczal4dSkVdSgXYeDvhXXz9Tl0MIIYQ0GE26iNlKyy3Bd9HXAAAfhnWEQka7KyGEEMtFv8WsgO4WTeZ6MbiG+s/eJKi1DEMC3DE4wHCXiLDWvIyBsuJHWfGjrPhRVvwsIStavdiIaPUiv6OpOXj+/05BLpVg/+yBaOfhYOqSCCGENFG0epGItFot4uLizHrFRn1otAI+2pMEAHg+xM/gEy5ry8uYKCt+lBU/yoofZcXPErKiSZcVEAQB6enpZr1ioz62nkrHpaxiuNopMHvYw18i4n7WlpcxUVb8KCt+lBU/yoqfJWRFky5iVvLvVWBlZOUlIuaO6ABnO4WJKyKEEEIMgyZdxKysOZSK/HtqBHg6YlJvX1OXQwghhBgMTbqsgFQqRUBAgFmv2OBxObsYP8RcBwAseKwT5Ea6RIS15NUYKCt+lBU/yoofZcXPErKi1YuNiFYvPtiLm07hr5QcDO/oif9O6WXqcgghhBAAtHqRVKHRaBAdHQ2NRmPqUhosKiUbf6XkQCGT4IOwjkZ9L2vIq7FQVvwoK36UFT/Kip8lZEWTLivAGENOTg4s9aClWivg438uETG1vz/8m9sb9f0sPa/GRFnxo6z4UVb8KCt+lpAVTbqIyf0Qcx1XckrQzF6JmUPbmbocQgghxCho0kVMKq+kAqv/rLxExFsjA+BkQ5eIIIQQYp1o0mUFZDIZgoODIZPJTF1Kva2KvITCMg06tnDCs4/4NMp7WnJejY2y4kdZ8aOs+FFW/CwhK1q92Iho9aK+lMwijF5zBAIDfnq5L0LaNjN1SYQQQkg1tHqRiDQaDQ4fPmzWKzbuxxjDR3uSIDBgVJBXo064LDEvU6Gs+FFW/CgrfpQVP0vIiiZdVoAxhqKiIrNesXG/QxezcexyLpQyKd4fY9xLRNzPEvMyFcqKH2XFj7LiR1nxs4SsaNJFGl2FRsB/Ii4CAKYN8IdvMzsTV0QIIYQYH026SKPbHH0NabklcHdUYcYQukQEIYSQpoEmXVZAJpMhJCTErFds6OQWl+OLQ6kAgHdCA+Cgkjd6DZaUl6lRVvwoK36UFT/Kip8lZNX4v/GIwUmlUnh4eJi6DC6fH7yEonINOrd0wjM9WpmkBkvKy9QoK36UFT/Kih9lxc8SsqIjXVZArVZj7969UKvVpi7lgZJuFWL76XQAwMLHgiCVSkxSh6XkZQ4oK36UFT/Kih9lxc8SsqJJl5Uw5yWyQOWqkiV7EiEwIKxrC/T2dzNpPeaelzmhrPhRVvwoK36UFT9zz4omXaRRHEjMwomreVDJpXhvdKCpyyGEEEIaHU26iNGVa7T45J9LRLwysA1audIlIgghhDQ9dBugRmSs2wDpLgjn6OgIicQ050k9yFd/XcGy/cnwdFLh8FuDYW+CFYtVmXte5oSy4kdZ8aOs+FFW/IyZVZO8DdCnn34KiUSC2bNni21lZWWYMWMGmjVrBgcHB4wbNw5ZWVl6z0tPT0dYWBjs7Ozg4eGBd955p9rnvn/99Rd69OgBlUqFdu3a4bvvvqv2/uvWrUPr1q1hY2ODPn364NSpU8YYZoPY2tqauoQaZReVYe3hyktEzB8VaPIJl4655mWOKCt+lBU/yoofZcXP3LOymEnX6dOnsWHDBnTt2lWvfc6cOfjjjz+wc+dO/P3337h16xaefvpp8XGtVouwsDBUVFQgOjoamzdvxnfffYeFCxeKfdLS0hAWFoYhQ4YgPj4es2fPxr///W8cOHBA7LN9+3bMnTsXixYtwtmzZ9GtWzeEhoYiOzvb+IOvg0ajQUREhFmeQPjZgRSUVGjRzccFY4NbmrocAOadl7mhrPhRVvwoK36UFT9LyMoiJl3FxcWYPHkyvvnmG7i6uortBQUF+L//+z+sXLkSQ4cORc+ePbFp0yZER0fjxIkTAICDBw8iKSkJP/74I4KDgzF69Gh89NFHWLduHSoqKgAAX3/9Nfz9/fH555+jY8eOmDlzJp555hmsWrVKfK+VK1fi5ZdfxtSpU9GpUyd8/fXXsLOzw7ffftu4YViQCzcLsDM2AwCw8LFOJrtEBCGEEGIOzOOznjrMmDEDYWFhGD58OD7++GOxPTY2Fmq1GsOHDxfbAgMD4evri5iYGPTt2xcxMTHo0qULPD09xT6hoaGYPn06EhMT0b17d8TExOi9hq6P7mPMiooKxMbG4r333hMfl0qlGD58OGJiYmqtu7y8HOXl5eLXhYWFACqvJaK7johUKoVMJoNWq4UgCHqvL5PJoNFo9G7eKZPJIJVK9dqrXpPk/uuTyOWVm/j+mX9t7QqFAoIgQKvVim0SiQRyubzW9ppql0qlWPx7IhgDHu/qha7eDtBqtdxjqtpu6DFVfb36jOlht5Mxx1S1dkOOSVenWq22mjEZazvV9P1o6WOqqd0QY9L1qdrX0sdkrO2k+y9jDIwxqxhTXbU3dExVMzPGmAzB7Cdd27Ztw9mzZ3H69Olqj2VmZkKpVMLFxUWv3dPTE5mZmWKfqhMu3eO6xx7Up7CwEKWlpbh79y60Wm2NfZKTk2utfenSpQgPD6/WfvDgQdjZVa7g8/X1Rffu3ZGQkID09HSxT0BAAAIDA3Hq1Cnk5OSI7cHBwfDz88ORI0dQVFRU42tX3TmGDBkCW1tbRERE6PUbM2YMSktLERUVJbbJ5XKEhYUhNzdXbzLp6OiIoUOH4saNG4iPjxfb3d3d0a9fP6SmpiIlJUVs9/X1xU2ZJ85cvwuFlKGnPAMRERn1HlNISAg8PDyMMiad+ozJENvJmGNqyHbiHVNkZKTVjQkw7HYqLi4Ws7KWMRlrO7VqVXk3isTERGRkZFjFmIy9nYqLi+Ho6GhVYzLWdoqMjDT4mI4fPw5DMOvVizdu3ECvXr0QGRkpnss1ePBgBAcHY/Xq1di6dSumTp2qdzQJAHr37o0hQ4Zg2bJleOWVV3D9+nW987Pu3bsHe3t7REREYPTo0ejQoQOmTp2qdyQrIiICYWFhuHfvHu7evYuWLVsiOjoaISEhYp958+bh77//xsmTJ2usv6YjXT4+PsjNzRVXPxjiLwndX0BKpZL7LwZj/nVUoWUYufoYbuaXYtaQtnhjaNt6j6lqu6H/OmKMQavVwsbGRvz/usZkaX/xGWpMgiBAo9FALpdDLpdbxZiMeaSrrKwMcrlcXDll6WOqqd0QY5JIJGCMif+1hjEZazvpjm7Z2NhAIpFYxZjqqr2hY9JoNOLPK6lUatAx5eXloVmzZg+9etGsj3TFxsYiOzsbPXr0ENu0Wi2OHDmCtWvX4sCBA6ioqEB+fr7e0a6srCx4eXkBALy8vKqtMtStbqza5/4Vj1lZWXBycoKtrS1kMhlkMlmNfXSvUROVSgWVSlWtXaFQQKFQ6LXp3uN+up3vQe26ZbJKpbLa61Z9T9523ceDvO33177haCpu5pfC29kG04e0h0KhPy6eMTW09traq9au++VoY2PDPaa62k09Jp72hoxJl5Wtra04kbD0MdXEUGPSaDR6WT2odksZkzG2U11L+y1xTHW1N3RMuu9BiUQCiURiFWN6mPYHjUmhUFT7eWXsMdWXWZ9IP2zYMJw/fx7x8fHiv169emHy5Mni/ysUChw6dEh8TkpKCtLT08UjUiEhITh//rzeKsPIyEg4OTmhU6dOYp+qr6Hro3sNpVKJnj176vURBAGHDh3SO/JlKhqNBlFRUWaxYiOrsAzr/7oCAJg/OhC2SvO727s55WXuKCt+lBU/yoofZcXPErIy6yNdjo6O6Ny5s16bvb09mjVrJrZPmzYNc+fOhZubG5ycnPDGG28gJCQEffv2BQCMHDkSnTp1wvPPP4/ly5cjMzMTH374IWbMmCEehXrttdewdu1azJs3Dy+99BIOHz6MHTt2YO/eveL7zp07F1OmTEGvXr3Qu3dvrF69GiUlJZg6dWojpWEZlu1Pxr0KLXr6ueKJbt6mLocQQggxG2Y96eKxatUqSKVSjBs3DuXl5QgNDcX69evFx2UyGfbs2YPp06cjJCQE9vb2mDJlCpYsWSL28ff3x969ezFnzhysWbMGrVq1wn//+1+EhoaKfZ599lnk5ORg4cKFyMzMRHBwMPbv31/t5PqmLP5GPn49exNA5SUi6OrJhBBCyP9Y3KTrr7/+0vvaxsYG69atw7p162p9jp+fX7XVEfcbPHgw4uLiHthn5syZmDlzJnetjclQnzc3FGMMS/5IBAA83aMluvm4mLSeupg6L0tCWfGjrPhRVvwoK37mnpVZr160Nsa696I5+C3+Jt7cFg87pQxRbw+Gp5ONqUsihBBCDKJJ3nuR1EwQBGRnZ+stf21M9yo0+HRf5fXKXh/c1uwnXKbOy5JQVvwoK36UFT/Kip8lZEWTLiug1WoRExNT7erOjWXD31dxu6AMLV1s8e8BbUxSQ32YOi9LQlnxo6z4UVb8KCt+lpAVTbrIQ7mVX4oNRyovEfH+mI6wUZjfJSIIIYQQc0CTLvJQlu1PRplaQO/WbhjTpfYLxRJCCCFNHU26rIBEIqn1ys7GFHv9Ln6LvwWJBFj4uOVcIsJUeVkiyoofZcWPsuJHWfGzhKxo9WIjsqbVi4LA8NT64ziXUYBne/lg2TNdTV0SIYQQYhS0epGIBEHA9evXG3XFxq64mziXUQAHlRxvhwY02vsaginyslSUFT/Kih9lxY+y4mcJWdGkywpotVrEx8c32oqNknINlu2vvETEjCHt4O5Y/abe5qyx87JklBU/yoofZcWPsuJnCVnRpIvU21d/XUF2UTl83ezw0qOtTV0OIYQQYhFo0kXq5UbePWw8ehVA5SUiVHK6RAQhhBDCgyZdVkAikcDd3b1RVmx8ui8ZFRoBIW2aITTIMm/23Zh5WTrKih9lxY+y4kdZ8bOErGj1YiOy9NWLp9LyMGFDDKQSYO+sAejYwvLGQAghhNQXrV4kIq1Wi+TkZKOePCgIDEv2JAIAJvb2tegJV2PkZS0oK36UFT/Kih9lxc8SsqJJlxUQBAEpKSlGXSb7c2wGLtwshKONHG+N6GC092kMjZGXtaCs+FFW/CgrfpQVP0vIiiZdpE5FZWosP5ACAHhzWHs0c7CsS0QQQggh5oAmXaRO66KuILe4HP7N7fFCSGtTl0MIIYRYJJp0WQGpVApfX19IpYbfnNfvlODbY2kAgA/GdIRSbvm7jDHzsjaUFT/Kih9lxY+y4mcJWdHqxUZkiasXX/3hDA4kZmFA++b4/qXeZr0UlxBCCDEGWr1IRFqtFnFxcQZfsRF9JRcHErMgk0qw4LFOVjPhMlZe1oiy4kdZ8aOs+FFW/CwhK5p0WQFBEJCenm7QFRtagWHJH0kAgMl9fNHB09Fgr21qxsjLWlFW/CgrfpQVP8qKnyVkRZMuUqPtp28gObMIzrYKzBlu2ZeIIIQQQswBTbpINYVlanx+sPISEbOHt4ervdLEFRFCCCGWjyZdVkAqlSIgIMBgKza+PJSKOyUVaOfhgH/19TPIa5oTQ+dlzSgrfpQVP8qKH2XFzxKyotWLjcgSVi+m5ZZg5Kq/odYyfDf1EQwO8DB1SYQQQohJ0epFItJoNIiOjoZGo3no1/rP3iSotQyDA9ytdsJlyLysHWXFj7LiR1nxo6z4WUJWNOmyAowx5OTk4GEPWh5NzcGfF7Mhl0rwYVgnA1VnfgyVV1NAWfGjrPhRVvwoK36WkBVNuggAQKMV8NGeyktEPB/ih3YeDiauiBBCCLEuNOkiAICtp9JxKasYrnYKzB5Gl4gghBBCDI0mXVZAJpMhODgYMpmsQc8vuKfGyshLAIC5IzrA2U5hyPLMzsPm1ZRQVvwoK36UFT/Kip8lZEWrFxuRua5eDP8jEZuOX0OApyP2znoUchnNxQkhhBAdWr1IRBqNBocPH27Qio3L2cX4IeY6AGDBY52axITrYfJqaigrfpQVP8qKH2XFzxKysv7fsE0AYwxFRUUNWrHx8d4kaASG4R098Wj75kaozvw8TF5NDWXFj7LiR1nxo6z4WUJWNOlqwqJSsvFXSg4UMgk+COto6nIIIYQQq0aTriZKrRXw8T+XiHixX2v4N7c3cUWEEEKIdaNJlxWQyWQICQmp14qNH2Ku40pOCZrZK/HGsPZGrM78NCSvpoqy4kdZ8aOs+FFW/CwhK7mpCyAPTyqVwsOD/5Y9eSUVWP1n5SUi3hoZACcb675ExP3qm1dTRlnxo6z4UVb8KCt+lpAVHemyAmq1Gnv37oVarebqv/rPSygs06BjCyc8+4iPkaszP/XNqymjrPhRVvwoK36UFT9LyIomXVaCd4nspawibDmZDgBY+FgnyKQSY5Zltsx5SbG5oaz4UVb8KCt+lBU/c8+KJl1NCGMMH+1JglZgGBXkhZC2zUxdEiGEENJk0KSrCTl0MRtHU3OhlEnx/hi6RAQhhBDSmOg2QI3IWLcB0l0QztHRERJJzR8XVmgEhK4+grTcEkwf3BbzRwUa7P0tDU9epBJlxY+y4kdZ8aOs+BkzK7oNENFja2v7wMc3R19DWm4JmjuoMGNIu0aqynzVlRf5H8qKH2XFj7LiR1nxM/esaNJlBTQaDSIiImo9gTC3uBxfHEoFAMwLDYCDqmlfKaSuvMj/UFb8KCt+lBU/yoqfJWRFk64m4PODl1BUrkHnlk54pmcrU5dDCCGENEk06bJySbcKsf207hIRQZA20UtEEEIIIaZm1pOupUuX4pFHHoGjoyM8PDwwduxYpKSk6PUpKyvDjBkz0KxZMzg4OGDcuHHIysrS65Oeno6wsDDY2dnBw8MD77zzTrXDj3/99Rd69OgBlUqFdu3a4bvvvqtWz7p169C6dWvY2NigT58+OHXqlMHHbEiMMSzZkwiBAWFdW6C3v5upSyKEEEKaLmbGQkND2aZNm9iFCxdYfHw8GzNmDPP19WXFxcVin9dee435+PiwQ4cOsTNnzrC+ffuyfv36iY9rNBrWuXNnNnz4cBYXF8ciIiJY8+bN2XvvvSf2uXr1KrOzs2Nz585lSUlJ7Msvv2QymYzt379f7LNt2zamVCrZt99+yxITE9nLL7/MXFxcWFZWFvd4CgoKGABWUFDwkMnoEwSBVVRUMEEQ9Nr3nb/N/ObvYR0+iGA38koM+p6WrLa8SHWUFT/Kih9lxY+y4mfMrAz1+9usJ133y87OZgDY33//zRhjLD8/nykUCrZz506xz8WLFxkAFhMTwxhjLCIigkmlUpaZmSn2+eqrr5iTkxMrLy9njDE2b948FhQUpPdezz77LAsNDRW/7t27N5sxY4b4tVarZd7e3mzp0qXc9Rtz0lVQUKC3o5WpNWzAssPMb/4e9tmBZIO+n6WrKS9SM8qKH2XFj7LiR1nxM2ZWhvr9bVHL2AoKCgAAbm6VH5PFxsZCrVZj+PDhYp/AwED4+voiJiYGffv2RUxMDLp06QJPT0+xT2hoKKZPn47ExER0794dMTExeq+h6zN79mwAQEVFBWJjY/Hee++Jj0ulUgwfPhwxMTG11lteXo7y8nLx68LCQgCV94fS3RtKKpVCJpNBq9VCEAS915fJZNBoNGBVLqUmk8kglUr12tVqNaKiojBmzBix3zdH0pCedw+eTiq8OrBNtXtRyeWVm/7+j1kVCgUEQYBWqxXbJBIJ5HJ5re211f4wY6razls775iq5qWr09LHVLV2Q26niooKREVFYcSIEbCxsbGKMRlrO+n2qxEjRkChUFjFmGpqN8SYtFotoqKiEBoaCplMZhVjMtZ20u1Xo0ePhkKhsIox1VV7Q8dUVlYmfg8qlUqDj8kQLGbSJQgCZs+ejf79+6Nz584AgMzMTCiVSri4uOj19fT0RGZmptin6oRL97jusQf1KSwsRGlpKe7evQutVltjn+Tk5FprXrp0KcLDw6u1Hzx4EHZ2dgAAX19fdO/eHQkJCUhPTxf7BAQEIDAwEKdOnUJOTo7YHhwcDD8/Pxw5cgRFRUU1vnbePQ2+jJMBkOCNQX5QyYCIiAi9fmPGjEFpaSmioqLENrlcjrCwMOTm5upNJh0dHTF06FDcuHED8fHxYru7uzv69euH1NRUvXPtDDWmkJAQeHh44ODBg3o7/JAhQ2Bra/tQY9KxpjEZcztFRkZa3ZgAw26n4uJiMStrGZOxtlOrVpWrqBMTE5GRkWEVYzL2diouLoajo6NVjclY2ykyMtLgYzp+/DgMwWKuSD99+nTs27cPx44dE79ht27diqlTp+odTQKA3r17Y8iQIVi2bBleeeUVXL9+HQcOHBAfv3fvHuzt7REREYHRo0ejQ4cOmDp1qt6RrIiICISFheHevXu4e/cuWrZsiejoaISEhIh95s2bh7///hsnT56sseaajnT5+PggNzdXvKKtoY50RUZGike63tuViJ/P3kTXVk7YNb0/pFIJ/XV035EuXV50pKvuI12RkZF0pItjTGq1Gvv27aMjXZxHug4cOEBHujiPdEVGRtKRLo4xlZWViT+vDH2kKy8vD82aNXvoK9JbxJGumTNnYs+ePThy5Ig44QIALy8vVFRUID8/X+9oV1ZWFry8vMQ+968y1K1urNrn/hWPWVlZcHJygq2tLWQyGWQyWY19dK9RE5VKBZVKVa1doVCIP5R1dO9xP93OV1e77uuU7Hv4Je4mAGDR450hk0nF96xJTe1SqRRSafWFrbW111b7w47pQTXWt/3+2nXvZU1jqqu9IWNijEEul0OhUIivaeljqokhxqT74X//97clj6m2dkOMSS6XQyaT1fj6ljqmB7U/zJjkcjkkEgkkEonVjKmh7Q8ak0KhEL8HdTUYe0z1ZdaXjGCMYebMmdi1axcOHz4Mf39/vcd79uwJhUKBQ4cOiW0pKSlIT08Xj0iFhITg/PnzyM7OFvtERkbCyckJnTp1EvtUfQ1dH91rKJVK9OzZU6+PIAg4dOiQ3pEvU1EoFAgLC4NcLkf4H4lgDHgy2Bs9/VxNXZpZ0uVV2zc6+R/Kih9lxY+y4kdZ8bOErMx60jVjxgz8+OOP2Lp1KxwdHZGZmYnMzEyUlpYCAJydnTFt2jTMnTsXUVFRiI2NxdSpUxESEoK+ffsCAEaOHIlOnTrh+eefx7lz53DgwAF8+OGHmDFjhngU6rXXXsPVq1cxb948JCcnY/369dixYwfmzJkj1jJ37lx888032Lx5My5evIjp06ejpKQEU6dObfxg7iMIArKzs7E34RZOX7sLG4W0Sd/Qui66vKoeWiY1o6z4UVb8KCt+lBU/i8jqodY+GhmAGv9t2rRJ7FNaWspef/115urqyuzs7NhTTz3Fbt++rfc6165dY6NHj2a2trasefPm7K233mJqtVqvT1RUFAsODmZKpZK1adNG7z10vvzyS+br68uUSiXr3bs3O3HiRL3GY6xLRlRUVLAdv+xm/Zb+yfzm72GrIlMM+vrWpqKigu3evZtVVFSYuhSzR1nxo6z4UVb8KCt+xsyqSVwygnGc429jY4N169Zh3bp1tfbx8/OrtjrifoMHD0ZcXNwD+8ycORMzZ86ssyZT+Ou2BDfzy+DtbINXB7Y1dTmEEEIIuY9Zf7xI+GQVliHyZuWmnD86ELbK6icHEkIIIcS0aNJlBT6PvIwKQYLuPi54opu3qcsxexKJBI6OjpBI6ObfdaGs+FFW/CgrfpQVP0vIymKu02UNCgsL4ezs/NDX+bjfzjM3sOJACr55oRe6+bgY7HUJIYQQYrjf33SkywqM69ESWya1RZeWhpvIWTNBEHD9+nXzXuFiJigrfpQVP8qKH2XFzxKyokmXFdBqtUg6n6B3lV5SO61Wi/j4eMqLA2XFj7LiR1nxo6z4WUJWNOkihBBCCGkENOkihBBCCGkENOmyAhKJBO7u7ma9YsOcUF78KCt+lBU/yoofZcXPErKi1YuNyFirFwkhhBBiPLR6kYi0Wi2Sk5PN+uRBc0J58aOs+FFW/CgrfpQVP0vIiiZdVkAQBKSkpJj1MllzQnnxo6z4UVb8KCt+lBU/S8iKJl2EEEIIIY2AJl2EEEIIIY2AJl1WQCqVwtfXF1IpbU4elBc/yoofZcWPsuJHWfGzhKxo9WIjotWLhBBCiOWh1YtEpNVqERcXZ9YrNswJ5cWPsuJHWfGjrPhRVvwsISuadFkBQRCQnp5u1is2zAnlxY+y4kdZ8aOs+FFW/CwhK5p0EUIIIYQ0ArmpC2hKdKfPFRYWGvR11Wo17t27h8LCQigUCoO+tjWivPhRVvwoK36UFT/Kip8xs9L93n7Y0+Bp0tWIioqKAAA+Pj4mroQQQggh9VVUVARnZ+cGP59WLzYiQRBw69YtODo6GvSGnIWFhfDx8cGNGzdoVSQHyosfZcWPsuJHWfGjrPgZMyvGGIqKiuDt7f1Ql6SgI12NSCqVolWrVkZ7fScnJ/qmrAfKix9lxY+y4kdZ8aOs+Bkrq4c5wqVDJ9ITQgghhDQCmnQRQgghhDQCmnRZAZVKhUWLFkGlUpm6FItAefGjrPhRVvwoK36UFT9LyIpOpCeEEEIIaQR0pIsQQgghpBHQpIsQQgghpBHQpIsQQgghpBHQpMuCtG7dGqtXrzZ1GYQQQghpAJp0GdDgwYMxe/bsau3fffcdXFxcGr0eXmVlZXjxxRfRpUsXyOVyjB07tsZ+W7ZsQbdu3WBnZ4cWLVrgpZdewp07dxqtziNH/r+9e4+Lot7/B/5aWNhdQFFBlEUB8YJ3hUQDNEUsLTUp9fjo4Y28kyl28iRmDzNPelJDzeO9DMT7LS95v4EpagoKKCggQiql9lU0gVQur98f/pzjulwWRJR6Px+P/WPm85nPfua1s8OHmdmZn9C7d2/o9XqoVCps27bNoDw7Oxsffvgh6tWrB51Oh+bNm2Pp0qUltpmRkYHhw4ejQYMG0Ol0aNiwIT7//HM8fPiwyPqXLl1CtWrVXurPEwD+85//wMvLC9WqVYODgwMCAgKQnJxsUKdLly5QqVQGrzFjxpTYbnJyMvz8/FCnTh1otVq4ubnhs88+Q15eXpH1169fD5VKVew29TJYsmQJWrdurdxQ0dvbG3v27FHKy5PTk0zZZqpCTkX56quvoFKpDPZ75ckrIyPDaBmVSoWTJ08WWb8q5DVt2jSj9WnatKlSXt7tiiS+/vprNGnSBBqNBk5OTpgxY0aRdaOjo6FWq9G2bduKWq0yy8zMxKBBg2BnZwedTodWrVohJiZGKQ8MDDTKoUePHi+sv8+b3JH+b+Thw4ewtLQ0ml9QUACdTofx48djy5YtRS4bHR2NIUOGYN68eejduzcyMzMxZswYjBw5Ej/88MPz7joAICcnB23atMGwYcPw7rvvGpX/85//xOHDh7F69Wq4urpi//79+OCDD6DX6/H2228X2ebFixdRWFiIZcuWoVGjRjh//jxGjhyJnJwcfP311wZ18/Ly8N5776FTp044fvz4c1nHinLkyBGMHTsWXl5eyM/Px6effoo33ngDSUlJsLa2VuqNHDkS06dPV6atrKxKbNfCwgJDhgyBp6cnatSogfj4eIwcORKFhYWYOXOmQd2MjAxMnDgRnTp1qtiVq2D16tXDV199hcaNG4MkVq5ciT59+uDs2bNo0aIFgLLn9Jgp20xVyelpp0+fxrJly9C6dWujsvLmdfDgQSVzALCzszOqU5XyatGiBQ4ePKhMq9WGf3LLk1NwcDD279+Pr7/+Gq1atcLt27dx+/Zto3p37tzBkCFD4O/vjxs3bjzDWpRfVlYWfH194efnhz179qB27dpITU1FzZo1Der16NEDYWFhyvTLeMuHgoICqFSqZ3oEEACAosJ07tyZwcHBRvPDwsJoa2urTA8dOpR9+vThnDlzWLduXdaqVYsffPABHz58qNS5ceMGe/XqRa1WS1dXV65evZouLi6cN2+eUicrK4vDhw+nvb09q1WrRj8/P8bFxSnln3/+Odu0acNvv/2Wrq6uVKlUpa7D4749bc6cOXRzczOYt2DBAjo5OZXa5vMAgFu3bjWY16JFC06fPt1gnqenJ6dMmVKmtmfPns0GDRoYzf/kk084aNAgo8+zKrh58yYB8MiRI8q84rbXsvroo4/YsWNHg3n5+fn08fHhd999V+w29TKrWbMmv/vuO5LPllNp20xVzenevXts3LgxDxw4YJRPefJKT08nAJ49e7bEelUpr8f73+KUJ6ekpCSq1WpevHix1LoDBgzgZ599Vmo/nqdJkyYZ7RueVtbPceXKlaxVqxbv379vML9Pnz4cNGiQMr1t2zZ6eHhQo9GwQYMGnDZtGvPy8pTy0NBQtmzZklZWVqxXrx6DgoJ47949pfzxd3b79u1s1qwZzc3NmZ6ezsjISHp5edHKyoq2trb08fFhRkaGyf2X04svSGRkJNLS0hAZGYmVK1ciPDwc4eHhSnlgYCCuXr2KyMhIbN68GYsXL8bNmzcN2ujfvz9u3ryJPXv2IDY2Fp6envD39zf4r+fSpUvYsmULfvjhB8TFxZW7v97e3rh69Sp2794Nkrhx4wY2b96Mt956q9xtVjQfHx/s2LEDmZmZIInIyEikpKTgjTfeKFM7d+/eRa1atQzmHT58GJs2bcKiRYsqssuV5u7duwBgtF5r1qyBvb09WrZsicmTJyM3N7dM7V66dAl79+5F586dDeZPnz4dDg4OGD58+LN1vJIVFBRg/fr1yMnJgbe3tzK/PDmZss1U1ZzGjh2Lnj17olu3bkWWl3e7evvtt+Hg4ICOHTtix44dRuVVLa/U1FTo9Xq4ublh4MCBuHLlikF5WXP68ccf4ebmhp07d6JBgwZwdXXFiBEjjI50hYWF4fLly/j8888rfJ3KYseOHWjXrh369+8PBwcHeHh44NtvvzWqFxUVBQcHB7i7uyMoKKjEy1b69++PgoICg+3j5s2b2LVrF4YNGwYAOHr0KIYMGYLg4GAkJSVh2bJlCA8PNzgNa2ZmhgULFiAxMRErV67E4cOH8cknnxi8V25uLmbNmoXvvvsOiYmJqFWrFgICAtC5c2ckJCTgxIkTGDVqFFQqlemhmDw8E6Uqy5EuFxcX5ufnK/P69+/PAQMGkCSTk5MJgKdOnVLKL1y4QADKka6jR4+yevXqRqP9hg0bctmyZSQf/adlYWHBmzdvmrwOJf3XsXHjRtrY2FCtVhMAe/fubXB0rjKhiCNd9+/f55AhQwiAarWalpaWXLlyZZnaTU1NZfXq1bl8+XJl3v/93/+xfv36ylGiqnakq6CggD179qSvr6/B/GXLlnHv3r1MSEjg6tWr6eTkxHfeecekNr29vanRaAiAo0aNYkFBgVJ29OhROjk58ffffydZ9v9kX4SEhARaW1vT3Nyctra23LVrl1JWnpxM2WaqYk4kuW7dOrZs2ZJ//vknSeP9Xnny+v333xkaGsqTJ0/y1KlTnDRpElUqFbdv367UqWp57d69mxs3bmR8fDz37t1Lb29vOjs7848//iBZvpxGjx5NjUbDDh068KeffmJkZCTbtm1LPz8/pU5KSgodHByYnJxMsvQjbs+TRqOhRqPh5MmTeebMGS5btoxarZbh4eFKnXXr1nH79u1MSEjg1q1b2axZM3p5eRn8fXxaUFAQ33zzTWU6NDSUbm5uLCwsJEn6+/tz5syZBsusWrWKjo6Oxba5adMm2tnZKdNhYWEEYHD26NatWwTAqKgo00N4igy6KlBZBl1vvfWWQZ3x48crX5xt27ZRrVYb/CEjyRo1aiiDroULF9LMzIzW1tYGLzMzM37yySckH33ZGjVqVKZ1KG5HlpiYSEdHR86ePVvZibRq1YrDhg0rU/sVpahB15w5c9ikSRPu2LGD8fHx/O9//0sbGxseOHCA5KMd1pNZPe3atWts2LAhhw8fbjD/nXfe4aRJk5TpqjboGjNmDF1cXHj16tUS6x06dIgAeOnSJZJk8+bNlax69OhhUPfKlStMTEzk2rVr6eTkxFmzZpEk//jjD7q6unL37t1K3Zf9jyNJPnjwgKmpqYyJiWFISAjt7e2ZmJhYZF1Tciptm6mqOV25coUODg6Mj49X5pV2mqws29WTBg8erJyaqqp5PSkrK4vVq1dXTls/zZScRo4cSQDKgIokY2NjCYAXL15kfn4+27VrxyVLlijlL3LQZWFhQW9vb4N548aN46uvvlrsMmlpaQTAgwcPFlvnzJkzNDc357Vr10iSrVq1Mri0xN7enlqt1mB/r9VqCYA5OTkkyQMHDrBr167U6/W0sbExKg8LC6OlpaUykHssMDCQGo2GvXr14vz58/nrr7+WKRMZdFWg3r17MzAw0Gj+vHnz6OzsrEwXtbMIDg5m586dSZo26Prqq6/o5OTE1NRUo9fj/wTL82Urbkc2aNAg9uvXz2De0aNHCaDMG11FeHrQlZubSwsLC+7cudOg3vDhw9m9e3eSj66TezKnJ2VmZrJx48YcPHiwUe62trY0NzdXXmZmZgRAc3Nzrlix4vmsYAUZO3Ys69Wrx8uXL5daNzs7mwC4d+9ekmRGRoaS1eOdW1FWrVpFnU7H/Px8nj17Vsnm8UulUlGlUtHc3Fz5g/Ky8/f356hRo4osMyWn0raZqprT1q1bjfoNQOl3UUcnyrtdLVy4kHXr1iXJKpvX09q1a8eQkJAiy0zJaerUqVSr1QbL5ebmEgD379/PrKysInN6PO/QoUPPdwWf4uzsbPRP7OLFi6nX60tczt7enkuXLi2xjqenJ2fOnMmYmBiamZnxypUrSplWq+WsWbOK/PtYUFDA9PR0ajQaTpgwgSdOnGBycjJXrFhBAMzKyiJZ8j/XZ86c4cyZM+nt7U0bGxueOHGi9DD+P/n1YgVyd3fH/v37jeafOXMGTZo0Mbmdpk2bIj8/H7GxsfDy8gLw6Kf6d+7cUep4enri+vXrUKvVcHV1fdaulyo3N9folzfm5uYAHv2E+UXLy8tDXl6e0S9LzM3NUVhYCABwcHCAg4OD0bKZmZnw8/PDK6+8grCwMKM2Tpw4gYKCAmV6+/btmDVrFo4fPw4nJ6fnsDbPjiTGjRuHrVu3IioqCg0aNCh1mcfX/Dk6OgIAXFxcTHqvwsJC5OXlobCwEE2bNsW5c+cMyj/77DPcu3cP33zzDerXr1+2FXlBCgsL8eDBgyLLTMmptG1Gp9NVyZz8/f2N+v3++++jadOmmDRpkrJPeFJ5t6u4uDhlmb/CdpWdnY20tDQMHjy4yHJTcvL19UV+fj7S0tLQsGFDAEBKSopSv3r16kY5LV68GIcPH8bmzZtN2g9UJF9fX6Nb1aSkpJS4DVy7dg23bt1ScijOiBEjMH/+fGRmZqJbt24G24CnpyeSk5PRqFGjIpeNjY1FYWEhQkNDlf39xo0bTV0teHh4wMPDA5MnT4a3tzfWrl2LV1991bSFTR6eiVKlpaVRq9Vy3LhxjI+P58WLFxkaGkq1Ws09e/Yo9Uo70kWSPXr0oIeHB0+ePMmYmBh27NiROp1OOdJVWFjIjh07sk2bNty3bx/T09MZHR3NTz/9lKdPnyZZtiNdiYmJPHv2LHv37s0uXbrw7NmzBr8kCgsLo1qt5uLFi5mWlsZjx46xXbt2bN++fXmiKpd79+4p/QLAuXPn8uzZs/zll19IPjrN0aJFC0ZGRvLy5csMCwujVqvl4sWLi23z2rVrbNSoEf39/Xnt2jX+9ttvyqs4VeH0YlBQEG1tbRkVFWWwTrm5uSTJS5cucfr06YyJiWF6ejq3b99ONzc3vvbaayW2u3r1am7YsIFJSUlMS0vjhg0bqNfrOXDgwGKXedlPA4WEhPDIkSNMT09nQkICQ0JCqFKpuH///nLn9DRTtpmXPafiPHl6sbx5hYeHc+3atbxw4QIvXLjAGTNm0MzMjN9//32xy7zseX388ceMiopS9s3dunWjvb09b968We6cCgoK6Onpyddee41nzpxhTEwMO3TowNdff73YZV7k6cVTp05RrVZzxowZTE1N5Zo1a2hlZcXVq1eTfLRPnzhxIk+cOMH09HQePHiQnp6ebNy4sdH1yk+7c+cOraysaGlpyfXr1xuU7d27l2q1mtOmTeP58+eZlJTEdevWKb9kj4uLIwDOnz+faWlpjIiIoJOTU6lHui5fvsyQkBAeP36cGRkZ3LdvH+3s7Er8G/M0GXRVsFOnTvH1119n7dq1aWtryw4dOhhde2TKoOu3335jz549qdFo6OzszIiICKNbRvzxxx8cN24c9Xo9LSwsWL9+fQ4cOFA5zFqWL5uLiwsBGL2etGDBAjZv3pw6nY6Ojo4cOHBgiacHKlpkZGSRfRw6dCjJR5kFBgZSr9dTq9XS3d2doaGhRufkn/T4YsnS1v3pZV72QVdx6xQWFkby0bU5r732GmvVqkWNRsNGjRrxX//6F+/evVtiu+vXr6enpydtbGxobW3N5s2bc+bMmcpF1UV52f84Dhs2jC4uLrS0tGTt2rXp7+/P/fv3kyx/Tk/7uwy6yptXeHg4mzVrRisrK1avXp3t27fnpk2bSlzmZc9rwIABdHR0pKWlJZ2cnDhgwADlNOizbFeZmZl89913aWNjwzp16jAwMJC3bt0qtv6LHHSR5I8//siWLVtSo9GwadOmBj9Sys3N5RtvvMHatWvTwsKCLi4uHDlyJK9fv25S24MHDy7y9hHko4GXj48PdTqdsk09+d5z586lo6MjdTodu3fvzoiIiFIHXdevX2dAQIDyubq4uHDq1KlGl6SUREW+BOeGhBBCCCHKwN/fHy1atMCCBQtedFdMJoMuIYQQQlQZWVlZiIqKQr9+/ZCUlAR3d/cX3SWTyYX0QgghhKgyPDw8kJWVhVmzZlWpARcgR7qEEEIIISqFPAZICCGEEKISyKBLFCswMBABAQEl1unSpQsmTJhQKf15mUlWppOsTCdZmU6yMt1fPauXef1k0CWEEEIIUQlk0PUXUFBQoNx1XZRMsjKdZGU6ycp0kpXp/s5ZkUR+fv6L7kaxyvvZyKCrAkVERMDOzs7o8SEBAQEGj37Yvn07PD09odVq4ebmhi+++MJg45o7dy5atWoFa2tr1K9fHx988AGys7OV8vDwcNSoUQM7duxA8+bNodFocOXKFURFRaF9+/awtrZGjRo14Ovri19++aXY/p47dw5du3aFTqeDnZ0dRo0aZfA+T8vJycGQIUNgY2MDR0dHhIaGlicmAJJVWUhWppOsTCdZmU6yenYPHjzA+PHj4eDgAK1Wi44dO+L06dNKeVRUFFQqFfbs2YNXXnkFGo0Gx44dq7T1e/DgASZOnAgnJydYW1ujQ4cOiIqKUsqL+2zKzOTbqIpS5ebm0tbWlhs3blTm3bhxg2q1mocPHyZJ/vTTT6xevTrDw8OZlpbG/fv309XVldOmTVOWmTdvHg8fPsz09HQeOnSI7u7uDAoKUsrDwsJoYWFBHx8fRkdH8+LFi7x79y5tbW05ceJEXrp0iUlJSQwPD1cekfO07OxsOjo68t133+W5c+d46NAhNmjQQLm7O2l8x+egoCA6Ozvz4MGDTEhIYK9evVitWjXlbtSSlWQlWUlWktXfO6vijB8/nnq9nrt372ZiYiKHDh3KmjVrKnfTf/zEkdatWyuP4CrqTvvPa/1GjBhBHx8f/vTTT7x06RLnzJlDjUbDlJQUkkV/Njk5OWXOQQZdFSwoKIhvvvmmMh0aGko3NzflUTT+/v6cOXOmwTKrVq2io6NjsW1u2rSJdnZ2yvTjR9fExcUp827dukUAjIqKMqmfy5cvZ82aNZmdna3M27VrF83MzJRHMDy54d67d4+WlpYGO51bt25Rp9OV+4spWZlOsjKdZGU6ycp0klX5ZWdn08LCgmvWrFHmPXz4kHq9nrNnzyb5v0HXtm3bKn39fvnlF5qbmzMzM9Pgvfz9/Tl58mSSRX825SGDrgp25swZmpubK88kbNWqFadPn66U29vbU6vV0traWnlptVoCUEbNBw4cYNeuXanX62ljY2NUHhYWRktLS6NnCgYGBlKj0bBXr16cP38+f/3112L7+dFHH7FLly4G8+7cuUMAPHLkCEnDDffxA0Kf/u+qbdu25f5iSlamk6xMJ1mZTrIynWRVfvHx8QTAjIwMg/kBAQF8//33Sf5v0FXa83yfx/rt3LmTAAw+O2tra6rVav7jH/8gWfxnU1ZyTVcF8/DwQJs2bRAREYHY2FgkJiYiMDBQKc/OzsYXX3yBuLg45XXu3DmkpqZCq9UiIyMDvXr1QuvWrbFlyxbExsZi0aJFAICHDx8q7eh0OqhUKoP3DgsLw4kTJ+Dj44MNGzagSZMmOHnyZKWsd3lIVqaTrEwnWZlOsjKdZFU5rK2tK/09s7OzYW5ujtjYWIPP78KFC/jmm2+UekV9NmUlg67nYMSIEQgPD0dYWBi6deuG+vXrK2Wenp5ITk5Go0aNjF5mZmaIjY1FYWEhQkND8eqrr6JJkyb49ddfTX5vDw8PTJ48GcePH0fLli2xdu3aIus1a9YM8fHxyMnJUeZFR0fDzMysyMcqNGzYEBYWFvj555+VeVlZWUhJSTG5b0WRrEwnWZlOsjKdZGU6yap8GjZsCEtLS0RHRyvz8vLycPr0aTRv3rxMbT2P9fPw8EBBQQFu3rxp9NnVrVu3TP0r1TMdJxNFunPnDq2srGhpacn169cblO3du5dqtZrTpk3j+fPnmZSUxHXr1nHKlCkk/3codP78+UxLS2NERASdnJwIgFlZWSQfHea0tbU1aPfy5csMCQnh8ePHmZGRwX379tHOzo6LFy8uso85OTl0dHRk3759ee7cOR4+fJhubm4lXow4ZswYuri48NChQzx37hzffvtt2tjYPNMhaMlKspKsJCvJ6q+X1dOCg4Op1+u5Z88egwvpb9++TfJ/pxcfZ1Gc57V+AwcOpKurK7ds2cLLly/z559/5syZM7lz506SRX825SGDrudk8ODBrFWrFu/fv29UtnfvXvr4+FCn07F69eps3749ly9frpTPnTuXjo6O1Ol07N69OyMiIkr9Yl6/fp0BAQF0dHSkpaUlXVxcOHXqVBYUFBTbx4SEBPr5+VGr1bJWrVocOXIk7927p5Q/veHeu3ePgwYNopWVFevUqcPZs2ezc+fOz/zFlKxMJ1mZTrIynWRlOsmqfP7880+OGzeO9vb21Gg09PX15alTp5RyUwddz2v9Hj58yKlTp9LV1ZUWFhZ0dHTkO++8w4SEBJIVN+iSB14/J/7+/mjRogUWLFjworvy0pOsTCdZmU6yMp1kZTrJSjwLGXRVsKysLERFRaFfv35ISkoq8hyzeESyMp1kZTrJynSSlekkK1ER1C+6A381Hh4eyMrKwqxZs+RLWQrJynSSlekkK9NJVqaTrERFkCNdQgghhBCVQG4ZIYQQQghRCWTQJYQQQghRCWTQJYQQQghRCWTQJYQQQghRCWTQJYQQQghRCWTQJYT4Szhx4gTMzc3Rs2fPF90VIYQoktwyQgjxlzBixAjY2NhgxYoVSE5Ohl6vf9FdKtLDhw9haWn5orshhHgB5EiXEKLKy87OxoYNGxAUFISePXsiPDzcqM6OHTvQuHFjaLVa+Pn5YeXKlVCpVLhz545S59ixY+jUqRN0Oh3q16+P8ePHIycnp8T3/vLLL+Hg4IBq1aphxIgRCAkJQdu2bZXywMBABAQEYMaMGdDr9cqNNc+dO4euXbtCp9PBzs4Oo0aNQnZ2trJcly5dMGHCBIP3CggIQGBgoDLt6uqKf//733jvvfdgbW0NJycnLFq0yOTchBCVSwZdQogqb+PGjWjatCnc3d0xaNAgfP/993jyIH56ejr69euHgIAAxMfHY/To0ZgyZYpBG2lpaejRowf69u2LhIQEbNiwAceOHcOHH35Y7PuuWbMGM2bMwKxZsxAbGwtnZ2csWbLEqN6hQ4eQnJyMAwcOYOfOncjJyUH37t1Rs2ZNnD59Gps2bcLBgwdLfK/izJkzB23atMHZs2cREhKC4OBgHDhwoMztCCEqwTM/MlsIIV4wHx8fzp8/nySZl5dHe3t7RkZGKuWTJk1iy5YtDZaZMmUKATArK4skOXz4cI4aNcqgztGjR2lmZsY///yzyPft0KEDx44dazDP19eXbdq0UaaHDh3KOnXq8MGDB8q85cuXs2bNmszOzlbm7dq1i2ZmZrx+/TpJsnPnzgwODjZou0+fPhw6dKgy7eLiwh49ehjUGTBgAN98880i+yuEeLHkSJcQokpLTk7GqVOn8N577wEA1Go1BgwYgBUrVhjU8fLyMliuffv2BtPx8fEIDw+HjY2N8urevTsKCwuRnp5e7Hs/3c7T0wDQqlUrg+u4Lly4gDZt2sDa2lqZ5+vri8LCQiQnJ5u45o94e3sbTV+4cKFMbQghKoc88FoIUaWtWLEC+fn5BhfOk4RGo8HChQtha2trUjvZ2dkYPXo0xo8fb1Tm7Oz8TH18cnBlKjMzM4NTpACQl5f3TP0QQrxYcqRLCFFl5efnIyIiAqGhoYiLi1Ne8fHx0Ov1WLduHQDA3d0dMTExBsuePn3aYNrT0xNJSUlo1KiR0au4Xxu6u7sbtfP0dFGaNWuG+Ph4g4v0o6OjYWZmplxoX7t2bfz2229KeUFBAc6fP2/U1smTJ42mmzVrVmofhBCVTwZdQogqa+fOncjKysLw4cPRsmVLg1ffvn2VU4yjR4/GxYsXMWnSJKSkpGDjxo3KLxxVKhUAYNKkSTh+/Dg+/PBDxMXFITU1Fdu3by/x4vZx48ZhxYoVWLlyJVJTU/Hll18iISFBabM4AwcOhFarxdChQ3H+/HlERkZi3LhxGDx4MOrUqQMA6Nq1K3bt2oVdu3bh4sWLCAoKMvil5WPR0dGYPXs2UlJSsGjRImzatAnBwcHlSFMI8bzJoEsIUWWtWLEC3bp1K/IUYt++fRETE4OEhAQ0aNAAmzdvxg8//IDWrVtjyZIlyq8XNRoNAKB169Y4cuQIUlJS0KlTJ3h4eGDq1Kkl3u9r4MCBmDx5MiZOnAhPT0+kp6cjMDAQWq22xH5bWVlh3759uH37Nry8vNCvXz/4+/tj4cKFSp1hw4Zh6NChGDJkCDp37gw3Nzf4+fkZtfXxxx8jJiYGHh4e+PLLLzF37lx0797dpPyEEJVLbo4qhPhbmjFjBpYuXYqrV69WaLuvv/466tati1WrVlVou0VxdXXFhAkTjO7nJYR4OcmF9EKIv4XFixfDy8sLdnZ2iI6Oxpw5c8p1X6wn5ebmYunSpejevTvMzc2xbt06HDx4UO6TJYQokgy6hBB/C4+vubp9+zacnZ3x8ccfY/Lkyc/Upkqlwu7duzFjxgzcv38f7u7u2LJlC7p161ZBvRZC/JXI6UUhhBBCiEogF9ILIYQQQlQCGXQJIYQQQlQCGXQJIYQQQlQCGXQJIYQQQlQCGXQJIYQQQlQCGXQJIYQQQlQCGXQJIYQQQlQCGXQJIYQQQlQCGXQJIYQQQlSC/weHVPQI/J6KkgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = df.groupby('Age', as_index=False).median()\n",
    "\n",
    "order = [7, 0, 1, 2, 3, 4, 5]\n",
    "df_line = df.reindex(order)\n",
    "\n",
    "plt.figsize=(10, 6)\n",
    "ax = sns.lineplot(data=df_line, x='Age', y='CompTotal')\n",
    "xlabels = [textwrap.fill(label.get_text(), width=10) for label in ax.get_xticklabels()]\n",
    "ax.set_xticklabels(xlabels)\n",
    "plt.title('Line plot of Age and Median CompTotal')\n",
    "plt.xlabel('Age group')\n",
    "plt.grid(True, linestyle='dashed')\n",
    "plt.xticks(rotation=0)\n",
    "plt.ylabel('Median CompTotal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Bar Chart**\n",
    "\n",
    "Create a horizontal bar chart using the `MainBranch` column.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Write your code here\n",
    "QUERY = \"\"\"\n",
    "SELECT MainBranch, COUNT(*) as Count\n",
    "FROM main\n",
    "GROUP BY MainBranch\n",
    "ORDER BY Count DESC\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_300/2340173538.py:4: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
      "  ax.set(yticklabels=labels)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))\n",
    "ax = sns.barplot(data=df, y='MainBranch', x='Count')\n",
    "labels = [textwrap.fill(label.get_text(), width=20) for label in ax.get_yticklabels()]\n",
    "ax.set(yticklabels=labels)\n",
    "plt.xticks(rotation=0)\n",
    "plt.xlabel(\"Type of MainBranch\")\n",
    "plt.ylabel(\"Number of Respondents\")\n",
    "plt.grid(True, axis='y', linestyle='dashed')\n",
    "plt.title(\"Distribution of respondents by MainBranch\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Summary\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this lab, you focused on extracting and visualizing data from an RDBMS using SQL queries and SQLite. You applied various visualization techniques, including:\n",
    "\n",
    "- Histograms to display the distribution of CompTotal.\n",
    "- Box plots to show the spread of ages.\n",
    "- Scatter plots and bubble plots to explore relationships between variables like Age, WorkExp, `TimeSearching` and `TimeAnswering`.\n",
    "- Pie charts and stacked charts to visualize the composition of data.\n",
    "- Line charts and bar charts to compare data across categories.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Close the Database Connection\n",
    "\n",
    "Once the lab is complete, ensure to close the database connection:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors:\n",
    "Ayushi Jain\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Other Contributors:\n",
    "- Rav Ahuja\n",
    "- Lakshmi Holla\n",
    "- Malika\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Copyright © IBM Corporation. All rights reserved.\n"
   ]
  }
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