4_analysis_visualization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Notebook 4/4: Analysis and visualization \n",
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Table of contents\n",
    "1. [Purpose of this notebook](#1)\n",
    "2. [Data preparation](#2)\n",
    "    1. [Import libraries](#2A)\n",
    "    2. [Load data](#2B)\n",
    "        1. [Number of daily checkins per ticket type (metro_nb) and distribution of hourly checkins per day category (metro_hp](#2Ba)\n",
    "        2. [Geographical data (geo)](#2Bb)\n",
    "    3. [Wrangling](#2C)\n",
    "3. [Analysis & visualisation](#3)\n",
    "    1. [What is the station with the most traffic, and what is the most common ticket type?](#3A)\n",
    "        1. [Map of # checkins per station and most frequent ticket type](#3Aa)\n",
    "        2. [How many tickets were checked-in to the Parisian metro network in 2018?](#3Ab)\n",
    "        3. [What was the metro station with the most traffic in Paris, in 2018?](#3Ac)\n",
    "            1. [What was the metro station with the least traffic in Paris, in 2018?](#3Aca)\n",
    "        4. [What was the most frequent ticket type?](#3Ad)\n",
    "    2. [What are the proportions of each ticket type?](#3B)\n",
    "        1. [Proportions of each ticket type in 2018 (bar plot)](#3Ba)\n",
    "        2. [Number of checkins per ticket type, per month (bar plot)](#3Bb)\n",
    "        3. [Percentage of checkins per ticket type, per month (bar plot)](#3Bc)\n",
    "    3. [How does traffic fluctuate along the year?](#3C)\n",
    "        1. [Calendar map of traffic in 2018](#3Ca)\n",
    "        2. [What was the day with the most traffic, in 2018?](#3Cb)\n",
    "            1. [What was the day with the least traffic, in 2018?](#3Cba)\n",
    "    4. [Which stations have the highest proportion of IMAGINE R & NAVIGO checkins?](#3D)\n",
    "        1. [Heatmap of IMAGINE R traffic (% of total traffic)](#3Da)\n",
    "        2. [Stations with the highest proportion of IMAGINE R traffic (% of total) (bar plot)](#3Db)\n",
    "        3. [Stations with the highest proportion of NAVIGO traffic (% of total) (bar plot)](#3Dc)\n",
    "        4. [Plot of yearly traffic: ESPLANADE DE LA DEFENSE vs. NOTRE-DAME-DES-CHAMPS](#3Dd)\n",
    "    5. [How does traffic fluctuate along the day?](#3E)\n",
    "        1. [Hourly traffic at NOTRE-DAME-DES-CHAMPS](#3Ea)\n",
    "            1. [What are the busiest hours of the *morning/afternoon* of a *working day outside school holidays* at NOTRE-DAME-DES-CHAMPS?](#3EAa)\n",
    "        2. [Hourly traffic at ESPLANADE DE LA DEFENSE](#3Eb)\n",
    "            1. [What are the busiest hours of the *morning/afternoon* of a *working day outside school holidays* at ESPLANADE DE LA DEFENSE?](#3Eba)\n",
    "    6. [How many people checked in the station SAINT-LAZARE between 8H-9H on 2018-01-01?](#3F)\n",
    "    7. [Visualization of hourly traffic with kepler.gl](#3G)\n",
    "        1. [Prepare data & export to csv](#3Ga)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Purpose of this notebook <a name=\"1\"></a>\n",
    "\n",
    "This final notebook analyzes the traffic data of Parisian metro stations for the year 2018. \n",
    "\n",
    "For more information about the data, please refer to notebook 1/4. The data cleaning process was performed in notebooks 2/4 and 3/4.\n",
    "\n",
    "We will explore some questions about the data, and answer them with visualizations.\n",
    "\n",
    "Please note that iPyLeaflet maps do not display on Github. I have inserted images for better readability."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Data preparation <a name=\"2\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.A. Import libraries <a name=\"2A\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pandas & Numpy\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Matplotlib\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "% matplotlib inline\n",
    "\n",
    "# Ipyleaflet\n",
    "from ipywidgets import *\n",
    "from ipyleaflet import Map, basemaps, basemap_to_tiles, CircleMarker, Icon, Popup, Heatmap\n",
    "\n",
    "# Calmap\n",
    "import calmap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.B. Load data <a name=\"2B\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.B.a. Number of daily checkins per ticket type (metro_nb) and distribution of hourly checkins per day category (metro_hp) <a name=\"2Ba\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "metro_nb = pd.read_csv('../../datasets/metro_nb.csv')\n",
    "metro_hp = pd.read_csv('../../datasets/metro_hp.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DAY</th>\n",
       "      <th>STOP_NAME</th>\n",
       "      <th>ID_REFA_LDA</th>\n",
       "      <th>TICKET_TYPE</th>\n",
       "      <th>NB_CHECKINS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-05-09</td>\n",
       "      <td>OLYMPIADES</td>\n",
       "      <td>71557.0</td>\n",
       "      <td>AMETHYSTE</td>\n",
       "      <td>462.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-05-09</td>\n",
       "      <td>OLYMPIADES</td>\n",
       "      <td>71557.0</td>\n",
       "      <td>NAVIGO</td>\n",
       "      <td>10764.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-05-09</td>\n",
       "      <td>LES AGNETTES-ASNIERES-GENNEVILLIERS</td>\n",
       "      <td>72240.0</td>\n",
       "      <td>NAVIGO</td>\n",
       "      <td>3972.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-05-09</td>\n",
       "      <td>LES COURTILLES</td>\n",
       "      <td>72286.0</td>\n",
       "      <td>TST</td>\n",
       "      <td>813.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-05-09</td>\n",
       "      <td>BOURSE</td>\n",
       "      <td>73635.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          DAY                            STOP_NAME  ID_REFA_LDA TICKET_TYPE  \\\n",
       "0  2018-05-09                           OLYMPIADES      71557.0   AMETHYSTE   \n",
       "1  2018-05-09                           OLYMPIADES      71557.0      NAVIGO   \n",
       "2  2018-05-09  LES AGNETTES-ASNIERES-GENNEVILLIERS      72240.0      NAVIGO   \n",
       "3  2018-05-09                       LES COURTILLES      72286.0         TST   \n",
       "4  2018-05-09                               BOURSE      73635.0         NaN   \n",
       "\n",
       "   NB_CHECKINS  \n",
       "0        462.0  \n",
       "1      10764.0  \n",
       "2       3972.0  \n",
       "3        813.0  \n",
       "4          4.0  "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metro_nb.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STOP_NAME</th>\n",
       "      <th>ID_REFA_LDA</th>\n",
       "      <th>CAT_DAY</th>\n",
       "      <th>HOUR</th>\n",
       "      <th>PCT_CHECKINS_s1</th>\n",
       "      <th>PCT_CHECKINS_s2</th>\n",
       "      <th>PCT_CHECKINS_mean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>QUAI DE LA GARE</td>\n",
       "      <td>71597.0</td>\n",
       "      <td>DIJFP</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.83</td>\n",
       "      <td>3.87</td>\n",
       "      <td>3.850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QUAI DE LA GARE</td>\n",
       "      <td>71597.0</td>\n",
       "      <td>DIJFP</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.33</td>\n",
       "      <td>5.38</td>\n",
       "      <td>5.355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>QUAI DE LA GARE</td>\n",
       "      <td>71597.0</td>\n",
       "      <td>DIJFP</td>\n",
       "      <td>14.0</td>\n",
       "      <td>6.44</td>\n",
       "      <td>6.59</td>\n",
       "      <td>6.515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>QUAI DE LA GARE</td>\n",
       "      <td>71597.0</td>\n",
       "      <td>DIJFP</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.90</td>\n",
       "      <td>7.74</td>\n",
       "      <td>7.820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>QUAI DE LA GARE</td>\n",
       "      <td>71597.0</td>\n",
       "      <td>DIJFP</td>\n",
       "      <td>18.0</td>\n",
       "      <td>11.28</td>\n",
       "      <td>9.68</td>\n",
       "      <td>10.480</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         STOP_NAME  ID_REFA_LDA CAT_DAY  HOUR  PCT_CHECKINS_s1  \\\n",
       "0  QUAI DE LA GARE      71597.0   DIJFP  11.0             3.83   \n",
       "1  QUAI DE LA GARE      71597.0   DIJFP  13.0             5.33   \n",
       "2  QUAI DE LA GARE      71597.0   DIJFP  14.0             6.44   \n",
       "3  QUAI DE LA GARE      71597.0   DIJFP  15.0             7.90   \n",
       "4  QUAI DE LA GARE      71597.0   DIJFP  18.0            11.28   \n",
       "\n",
       "   PCT_CHECKINS_s2  PCT_CHECKINS_mean  \n",
       "0             3.87              3.850  \n",
       "1             5.38              5.355  \n",
       "2             6.59              6.515  \n",
       "3             7.74              7.820  \n",
       "4             9.68             10.480  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metro_hp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 744502 entries, 0 to 744501\n",
      "Data columns (total 5 columns):\n",
      "DAY            744502 non-null object\n",
      "STOP_NAME      744502 non-null object\n",
      "ID_REFA_LDA    744502 non-null float64\n",
      "TICKET_TYPE    647521 non-null object\n",
      "NB_CHECKINS    744502 non-null float64\n",
      "dtypes: float64(2), object(3)\n",
      "memory usage: 28.4+ MB\n"
     ]
    }
   ],
   "source": [
    "metro_nb.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 35603 entries, 0 to 35602\n",
      "Data columns (total 7 columns):\n",
      "STOP_NAME            35603 non-null object\n",
      "ID_REFA_LDA          35603 non-null float64\n",
      "CAT_DAY              35603 non-null object\n",
      "HOUR                 35592 non-null float64\n",
      "PCT_CHECKINS_s1      35237 non-null float64\n",
      "PCT_CHECKINS_s2      35175 non-null float64\n",
      "PCT_CHECKINS_mean    35603 non-null float64\n",
      "dtypes: float64(5), object(2)\n",
      "memory usage: 1.9+ MB\n"
     ]
    }
   ],
   "source": [
    "metro_hp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert the DAY column back to datetime\n",
    "\n",
    "metro_nb[\"DAY\"] = pd.to_datetime(metro_nb[\"DAY\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.B.b. Geographical data (geo) <a name=\"2Bb\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "geo = pd.read_csv('../../datasets/geo_metro.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LAT_LONG</th>\n",
       "      <th>ID_ZDL</th>\n",
       "      <th>STOP_NAME</th>\n",
       "      <th>LINES</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LONG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>48.8463569889, 2.41947990037</td>\n",
       "      <td>47247</td>\n",
       "      <td>SAINT-MANDE-TOURELLE</td>\n",
       "      <td>M1</td>\n",
       "      <td>48.846357</td>\n",
       "      <td>2.419480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>48.8662858046, 2.32294341224</td>\n",
       "      <td>45676</td>\n",
       "      <td>CONCORDE</td>\n",
       "      <td>M1 / M8 / M12</td>\n",
       "      <td>48.866286</td>\n",
       "      <td>2.322943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>48.8828686476, 2.34413063372</td>\n",
       "      <td>42210</td>\n",
       "      <td>ANVERS</td>\n",
       "      <td>M2</td>\n",
       "      <td>48.882869</td>\n",
       "      <td>2.344131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>48.8822269008, 2.32127492677</td>\n",
       "      <td>44662</td>\n",
       "      <td>ROME</td>\n",
       "      <td>M2</td>\n",
       "      <td>48.882227</td>\n",
       "      <td>2.321275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48.8804494561, 2.30945116799</td>\n",
       "      <td>44146</td>\n",
       "      <td>MONCEAU</td>\n",
       "      <td>M2</td>\n",
       "      <td>48.880449</td>\n",
       "      <td>2.309451</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       LAT_LONG  ID_ZDL             STOP_NAME          LINES  \\\n",
       "0  48.8463569889, 2.41947990037   47247  SAINT-MANDE-TOURELLE             M1   \n",
       "1  48.8662858046, 2.32294341224   45676              CONCORDE  M1 / M8 / M12   \n",
       "2  48.8828686476, 2.34413063372   42210                ANVERS             M2   \n",
       "3  48.8822269008, 2.32127492677   44662                  ROME             M2   \n",
       "4  48.8804494561, 2.30945116799   44146               MONCEAU             M2   \n",
       "\n",
       "         LAT      LONG  \n",
       "0  48.846357  2.419480  \n",
       "1  48.866286  2.322943  \n",
       "2  48.882869  2.344131  \n",
       "3  48.882227  2.321275  \n",
       "4  48.880449  2.309451  "
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 302 entries, 0 to 301\n",
      "Data columns (total 6 columns):\n",
      "LAT_LONG     302 non-null object\n",
      "ID_ZDL       302 non-null int64\n",
      "STOP_NAME    302 non-null object\n",
      "LINES        302 non-null object\n",
      "LAT          302 non-null float64\n",
      "LONG         302 non-null float64\n",
      "dtypes: float64(2), int64(1), object(3)\n",
      "memory usage: 14.2+ KB\n"
     ]
    }
   ],
   "source": [
    "geo.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2.C. Wrangling <a name=\"2C\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set STOP_NAME column as index\n",
    "\n",
    "geo.set_index('STOP_NAME', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add LAT and LONG (latitude and longitude) columns to metro_nb & metro_hp\n",
    "\n",
    "# metro_nb\n",
    "\n",
    "metro_nb['LAT'] = metro_nb['STOP_NAME'].map(geo.LAT)\n",
    "metro_nb['LONG'] = metro_nb['STOP_NAME'].map(geo.LONG)\n",
    "\n",
    "# metro_hp\n",
    "\n",
    "metro_hp['LAT'] = metro_hp['STOP_NAME'].map(geo.LAT)\n",
    "metro_hp['LONG'] = metro_hp['STOP_NAME'].map(geo.LONG)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Analysis and visualization <a name=\"3\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.A. What is the station with the most traffic, and what is the most common ticket type? <a name=\"3A\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.A.a Map of # checkins per station and most frequent ticket type <a name=\"3Aa\"></a>\n",
    "\n",
    "#### Legend:\n",
    "> - **#Checkins**: Size of marker's stroke\n",
    "> - **Ticket type (most frequent)**:\n",
    ">> - Navigo: Blue\n",
    ">> - IMAGINE R: Red\n",
    ">> - Other tickets: Yellow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Prepare data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "# DataFrame of aggregated NB_CHECKINS per STOP_NAME\n",
    "\n",
    "# Group by STOP_NAME and aggregate NB_CHECKINS\n",
    "gp_stop = metro_nb.groupby('STOP_NAME').sum()['NB_CHECKINS']\n",
    "\n",
    "# DataFrame\n",
    "gp_stop = pd.DataFrame(gp_stop)\n",
    "gp_stop.reset_index(inplace=True)\n",
    "\n",
    "# Add coordinates\n",
    "gp_stop['LAT'] = gp_stop['STOP_NAME'].map(geo.LAT)\n",
    "gp_stop['LONG'] = gp_stop['STOP_NAME'].map(geo.LONG)\n",
    "\n",
    "\n",
    "# DataFrame of most frequent TICKET_TYPE per STOP_NAME\n",
    "\n",
    "# Total NB_CHECKINS grouped by STOP_NAME and TICKET_TYPE\n",
    "gbo_stop_tt = metro_nb.groupby(['STOP_NAME', 'TICKET_TYPE'])\n",
    "gp_stop_tt = gbo_stop_tt.sum()['NB_CHECKINS']\n",
    "\n",
    "# DataFrame of most frequent TICKET_TYPE per STOP_NAME\n",
    "stop_max_tt = gp_stop_tt.reset_index()\n",
    "stop_max_tt = stop_max_tt.sort_values('NB_CHECKINS', ascending=False).drop_duplicates(subset='STOP_NAME').sort_index()\n",
    "stop_max_tt = stop_max_tt.loc[:,['STOP_NAME', 'TICKET_TYPE']]\n",
    "stop_max_tt.set_index('STOP_NAME', inplace=True)\n",
    "\n",
    "\n",
    "# Map gp_stop (aggregated NB_CHECKINS per STOP_NAME) \n",
    "# & stop_max_tt (most frequent TICKET_TYPE per STOP_NAME)\n",
    "\n",
    "gp_stop['MAX_TICKET_TYPE'] = gp_stop['STOP_NAME'].map(stop_max_tt['TICKET_TYPE'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
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location=[48.858511129899995, 2.3231548558400004], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='SOLFERINO'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.883995220500005, 2.36891270331], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='STALINGRAD'), radius=3, weight=7), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.869294007700006, 2.35428087908], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='STRASBOURG-SAINT-DENIS'), radius=3, weight=8), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8512376071, 2.3619852263900003], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='SULLY-MORLAND'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8754744576, 2.39886759934], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='TELEGRAPHE'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.86668268020001, 2.3615415320700004], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='TEMPLE'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.877972701400004, 2.29831037512], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='TERNES'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8264260109, 2.35724565076], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='TOLBIAC'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.87631796229999, 2.3325430273], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value=\"TRINITE-D'ESTIENNE D'ORVES\"), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.863073782200004, 2.2871668755], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='TROCADERO'), radius=3, weight=6), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8643437787, 2.33012987711], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='TUILERIES'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8488163725, 2.3212578629099996], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VANEAU'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8568713792, 2.31505663732], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VARENNE'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8395165854, 2.30110751488], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VAUGIRARD (ADOLPHE CHERIOU)'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.842218413599994, 2.32900892624], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VAVIN'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.869798556499994, 2.28533509469], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VICTOR HUGO'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8046881209, 2.3639531966], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VILLEJUIF-LEO LAGRANGE'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.7875627921, 2.36780410698], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VILLEJUIF-LOUIS ARAGON'), radius=3, weight=7), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.7964830846, 2.36826954005], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VILLEJUIF-PAUL VAILLANT-COUTURIER'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8811500285, 2.31517662622], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VILLIERS'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8415055224, 2.3079486793400004], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VOLONTAIRES'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.85745372270001, 2.38071878586], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VOLTAIRE (LEON BLUM)'), radius=3), CircleMarker(color='#2F80ED', fill_color='#000951', fill_opacity=1.0, location=[48.8838092012, 2.30467444053], opacity=0.5, options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='WAGRAM'), radius=3), TileLayer(attribution='&copy; <a href=\"http://www.openstreetmap.org/copyright\">OpenStreetMap</a> &copy; <a href=\"http://cartodb.com/attributions\">CartoDB</a>', max_zoom=20, min_zoom=1, name='CartoDB.Positron', options=['attribution', 'detect_retina', 'max_zoom', 'min_zoom', 'tile_size'], url='http://c.basemaps.cartocdn.com/light_all/{z}/{x}/{y}.png')), options=['attribution_control', 'basemap', 'bounce_at_zoom_limits', 'box_zoom', 'center', 'close_popup_on_click', 'double_click_zoom', 'dragging', 'inertia', 'inertia_deceleration', 'inertia_max_speed', 'interpolation', 'keyboard', 'keyboard_pan_offset', 'keyboard_zoom_offset', 'max_zoom', 'min_zoom', 'scroll_wheel_zoom', 'tap', 'tap_tolerance', 'touch_zoom', 'world_copy_jump', 'zoom', 'zoom_animation_threshold', 'zoom_control', 'zoom_start'])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Map\n",
    "center=(48.855115,2.352448)\n",
    "\n",
    "m = Map(\n",
    "    center=center,\n",
    "    zoom=12\n",
    ")\n",
    "\n",
    "# Colors\n",
    "c_dict = {\n",
    "        'NAVIGO': '#2F80ED', #Turquoise stroke for NAVIGO\n",
    "        'IMAGINE R' : '#EA3546' #Red stroke for IMAGINE R\n",
    "    }\n",
    "\n",
    "# Markers\n",
    "for x in gp_stop.iterrows():\n",
    "    lat = x[1].LAT\n",
    "    long = x[1].LONG\n",
    "    \n",
    "    nb_checkins = x[1].NB_CHECKINS\n",
    "    \n",
    "    r = int(nb_checkins/800000)\n",
    "    \n",
    "    n = x[1].STOP_NAME\n",
    "    \n",
    "        \n",
    "    max_tt = x[1].MAX_TICKET_TYPE\n",
    "    \n",
    "    c = c_dict.get(max_tt, '#FDE74C') #Yellow stroke for other tickets\n",
    "    \n",
    "    message = HTML()\n",
    "    \n",
    "    message.value = n\n",
    "    \n",
    "    circle_marker = CircleMarker(location=(lat, long), draggable=False)\n",
    "    circle_marker.radius = 3\n",
    "    circle_marker.stroke = True\n",
    "    circle_marker.color = c\n",
    "    circle_marker.opacity = 0.5\n",
    "    circle_marker.weight = max(r,5)\n",
    "    circle_marker.fill_color = '#000951'\n",
    "    circle_marker.fill_opacity = 1\n",
    "    m.add_layer(circle_marker);\n",
    "    \n",
    "    circle_marker.popup = message\n",
    "    \n",
    "# TileLayer    \n",
    "positron_layer = basemap_to_tiles(basemaps.CartoDB.Positron)\n",
    "m.add_layer(positron_layer)  \n",
    "    \n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img width=\"1000\" height=\"700\" controls src=\"img/map1.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> The Paris metro is very dense. It comprises a total of 302 stations over an area of 105 square kilometres (size of Paris). This map is missing one metro station: CLUNY-LA-SORBONNE. For some reason, this station is missing from the daily traffic and hourly profiles datasets (see notebook 3/4).\n",
    "\n",
    "> A few stations largely dominate the network: Saint-Lazare, Montparnasse, Gare de l'Est. Although our analysis focuses on the metro network, it is important to note that these stations are also rail stations, and therefore allow transfers to trains that serve stations outside of Paris, and connections to a large number of metro, bus and tram lines.\n",
    "\n",
    "> The network is entirely 'blue' except for one red dot: The most frequent ticket type across all metro stations is Navigo, except for NOTRE-DAME-DES-CHAMPS, where IMAGINE R is the most common rate plan used."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.A.b. How many tickets were checked-in to the Parisian metro network in 2018? <a name=\"3Ab\"></a>\n",
    "\n",
    "> Answer: 971,366,669"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'971,366,669'"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Total number of checkins in Paris metro in 2018\n",
    "total_metro_checkins = int(metro_nb['NB_CHECKINS'].sum())\n",
    "\n",
    "\"{:,}\".format(total_metro_checkins)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.A.c. What was the metro station with the most traffic in Paris, in 2018? <a name=\"3Ac\"></a>\n",
    "\n",
    "> Answer: SAINT-LAZARE, with 11,288 passengers per day on average. In 2018, a total of 26,617,781 passengers checked-in to SAINT-LAZARE, representing 2.74% of the total traffic."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "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>STOP_NAME</th>\n",
       "      <th>NB_CHECKINS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>SAINT-LAZARE</td>\n",
       "      <td>11288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>MONTPARNASSE</td>\n",
       "      <td>7161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>GARE DE L'EST</td>\n",
       "      <td>5464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>REPUBLIQUE</td>\n",
       "      <td>5086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>LES HALLES</td>\n",
       "      <td>4352</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         STOP_NAME  NB_CHECKINS\n",
       "263   SAINT-LAZARE        11288\n",
       "176   MONTPARNASSE         7161\n",
       "103  GARE DE L'EST         5464\n",
       "244     REPUBLIQUE         5086\n",
       "140     LES HALLES         4352"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Daily average of checkins per metro station\n",
    "pvt_stations = metro_nb.pivot_table(values = 'NB_CHECKINS', index = 'STOP_NAME', aggfunc = np.mean)\n",
    "pvt_stations.reset_index(inplace=True)\n",
    "pvt_stations['NB_CHECKINS'] = pvt_stations['NB_CHECKINS'].astype(int)\n",
    "pvt_stations.nlargest(n=5, columns='NB_CHECKINS')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26617781"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Total number of passengers at station SAINT-LAZARE in 2018\n",
    "metro_nb.groupby('STOP_NAME')['NB_CHECKINS'].sum()['SAINT-LAZARE'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.74"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Percentage of total checkins\n",
    "round((metro_nb.groupby('STOP_NAME')['NB_CHECKINS'].sum()['SAINT-LAZARE']/total_metro_checkins)*100,2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### What was the metro station with the least traffic in Paris, in 2018? <a name=\"3Aca\"></a>\n",
    "\n",
    "> Answer: EGLISE D'AUTEUIL, with 62 passengers per day on average."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "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>STOP_NAME</th>\n",
       "      <th>NB_CHECKINS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>EGLISE D'AUTEUIL</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>PELLEPORT</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>PRE SAINT-GERVAIS</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>BUTTES-CHAUMONT</td>\n",
       "      <td>182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>PORTE D'AUTEUIL</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             STOP_NAME  NB_CHECKINS\n",
       "86    EGLISE D'AUTEUIL           62\n",
       "191          PELLEPORT          127\n",
       "233  PRE SAINT-GERVAIS          140\n",
       "37     BUTTES-CHAUMONT          182\n",
       "210    PORTE D'AUTEUIL          187"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pvt_stations.nsmallest(n=5, columns='NB_CHECKINS')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.A.d. What was the most frequent ticket type? <a name=\"3Ad\"></a>\n",
    "\n",
    "> Answer: NAVIGO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NAVIGO       300\n",
       "IMAGINE R      1\n",
       "Name: TICKET_TYPE, dtype: int64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stop_max_tt.TICKET_TYPE.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> As seen on the map, Navigo is the most common ticket type accross the Parisian metro network, apart from 1 station (NOTRE-DAME-DES-CHAMPS) where the most frequent ticket type is IMAGINE R. \n",
    "\n",
    "> IMAGINE R is a special rate plan for students only, whereas NAVIGO tickets are mostly used by people who **are not** eligible to special discounts (such as AMETHYSTE, TST, FGT). Therefore, people who use IMAGINE R are very likely to be students, and those who use NAVIGO to be working people. \n",
    "\n",
    "> Looking at the proportions of each ticket type can give us information on the population."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.B. What are the proportions of each ticket type? <a name=\"3B\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.B.a. Proportions of each ticket type in 2018 (bar plot) <a name=\"3Ba\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 480x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "gbo_tt = metro_nb.groupby('TICKET_TYPE')\n",
    "gp_tt = gbo_tt.sum()['NB_CHECKINS'].sort_values(ascending=False)\n",
    "gp_tt_prop = round((gp_tt/total_metro_checkins)*100,2)\n",
    "\n",
    "# Figure\n",
    "plt.figure(figsize=(6,6), dpi= 80)\n",
    "\n",
    "# Data\n",
    "tickets = gp_tt_prop.index.tolist()\n",
    "n_tickets = len(tickets)\n",
    "y_pos = np.arange(n_tickets)\n",
    "percentage = gp_tt_prop.values.tolist()\n",
    "\n",
    "# Colors\n",
    "colors=['#2F80ED', '#EA3546', '#D9D7D8','#A09D9E', '#7A7677', '#2E282A']\n",
    "\n",
    "plt.barh(y_pos, percentage, align='center', color=colors)\n",
    "\n",
    "\n",
    "# Style\n",
    "\n",
    "# Title\n",
    "plt.title('Proportions of each Ticket Type', fontsize=15)\n",
    "# Labels\n",
    "plt.xlabel(\"Percentage\")\n",
    "plt.ylabel(\"Ticket Type (rate plan)\")\n",
    "plt.yticks(ticks=range(n_tickets), labels=tickets)\n",
    "# Spines \n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)\n",
    "# Invert y axis\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TICKET_TYPE\n",
       "NAVIGO         71.40\n",
       "IMAGINE R      16.18\n",
       "TST             4.63\n",
       "FGT             3.59\n",
       "AMETHYSTE       2.87\n",
       "AUTRE TITRE     1.27\n",
       "Name: NB_CHECKINS, dtype: float64"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gp_tt_prop"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> NAVIGO tickets represent more than 71% of all checkins, followed by IMAGINE R with only 16% of all checkins. Other ticket types represent less than 5% of all checkins.\n",
    "\n",
    "> We will focus the remaining of our analysis on IMAGINE R and NAVIGO ticket types."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.B.b. Number of checkins per ticket type, per month (bar plot)  <a name=\"3Bb\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "gbo_month_tt = metro_nb.groupby([metro_nb['DAY'].dt.month, 'TICKET_TYPE'])\n",
    "gp_month_tt = gbo_month_tt.sum()['NB_CHECKINS']\n",
    "\n",
    "df_month_tt = pd.DataFrame(gp_month_tt).reset_index()\n",
    "\n",
    "to_rename = {'DAY': 'MONTH'}\n",
    "df_month_tt.rename(columns=to_rename, inplace=True)\n",
    "\n",
    "df_month = pd.DataFrame(df_month_tt.groupby('MONTH').sum()['NB_CHECKINS'])\n",
    "df_month_tt['TOTAL'] = df_month_tt['MONTH'].map(df_month['NB_CHECKINS'])\n",
    "\n",
    "df_month_tt.sort_values('MONTH', inplace=True)\n",
    "\n",
    "df = df_month_tt\n",
    "\n",
    "tickets = gp_tt_prop.index.tolist()\n",
    "months = df['MONTH'].unique()\n",
    "\n",
    "list_checkins = []\n",
    "\n",
    "for t in tickets:\n",
    "    l = df[df['TICKET_TYPE'] == t]['NB_CHECKINS'].tolist()\n",
    "    list_checkins.append(l)\n",
    "\n",
    "Y = np.array(list_checkins)\n",
    "\n",
    "X = np.arange(Y.shape[1])\n",
    "\n",
    "# Colors\n",
    "colors = ['#2F80ED', '#EA3546', '#D9D7D8','#A09D9E', '#7A7677', '#2E282A']\n",
    "\n",
    "# Figure\n",
    "plt.figure(figsize=(12,6), dpi= 80)\n",
    "\n",
    "# Plot\n",
    "for y in range(Y.shape[0]):\n",
    "    plt.bar(X, \n",
    "            Y[y], \n",
    "            bottom = np.sum(Y[:y], axis = 0), \n",
    "            color = colors[y % len(colors)], \n",
    "            ec='white')\n",
    "\n",
    "# Style    \n",
    "plt.title(\"# Checkins per Ticket Category, per Month\", fontsize=15)\n",
    "# Labels & ticks\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"# Checkins\")\n",
    "plt.xticks(ticks=range(12), labels=months)\n",
    "plt.tick_params(axis='y', which='both', left=False, labelleft=False)\n",
    "# Legend\n",
    "plt.legend({group:col for group, col in zip(tickets, colors[:len(tickets)])})\n",
    "# Spines\n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Accross the year, NAVIGO tickets remain the most frequently used tickets. The traffic with both NAVIGO and IMAGINE R tickets decreases dramatically in August and February. The proportions seem to remain stable but the traffic changes make them hard to compare on this plot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.B.c. Percentage of checkins per ticket type, per month (bar plot)  <a name=\"3Bc\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "df_month_tt['PERC_CHECKINS'] = (df_month_tt['NB_CHECKINS']/df_month_tt['TOTAL'])*100\n",
    "\n",
    "tickets = gp_tt_prop.index.tolist()\n",
    "\n",
    "Y=[]\n",
    "\n",
    "for t in tickets:\n",
    "    l = df_month_tt.loc[df_month_tt['TICKET_TYPE'] == t, 'PERC_CHECKINS'].tolist()\n",
    "    Y.append(l)\n",
    "\n",
    "Y = np.array(Y)    \n",
    "X = np.arange(Y.shape[1])\n",
    "\n",
    "months = df_month_tt['MONTH'].unique()\n",
    "n_months = df_month_tt['MONTH'].nunique()\n",
    "\n",
    "# Figure\n",
    "plt.figure(figsize=(12,6), dpi= 80)\n",
    "\n",
    "# Colors\n",
    "colors = ['#2F80ED', '#EA3546', '#D9D7D8','#A09D9E', '#7A7677', '#2E282A']\n",
    "\n",
    "# Plot\n",
    "for y in range(Y.shape[0]):\n",
    "    plt.bar(X, \n",
    "            Y[y], \n",
    "            bottom = np.sum(Y[:y], axis = 0), \n",
    "            color = colors[y % len(colors)], \n",
    "            ec='white')\n",
    "\n",
    "# Style\n",
    "\n",
    "# Title\n",
    "plt.title('% Checkins per Ticket Category', fontsize=15)\n",
    "# Legend\n",
    "plt.legend({group:col for group, col in zip(tickets, colors)})\n",
    "# Labels\n",
    "plt.xlabel(\"Month\")\n",
    "plt.ylabel(\"% Checkins\")\n",
    "plt.xticks(ticks=range(n_months), labels=months)\n",
    "# Spines \n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> We can now compare the variations of the proportions of each ticket more easily. Although traffic diminishes *for all ticket types* during summer, the proportions of each ticket type remain roughly the same."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.C. How does traffic fluctuate along the year? <a name=\"3C\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.C.a. Calendar map of traffic in 2018 <a name=\"3Ca\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1280x800 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "pvt_days = metro_nb.pivot_table(values = 'NB_CHECKINS', index = 'DAY', aggfunc = np.sum)\n",
    "df = pvt_days\n",
    "\n",
    "# Plot\n",
    "plt.figure(figsize=(16,10), dpi= 80)\n",
    "calmap.calendarplot(df['NB_CHECKINS'], \n",
    "                    fig_kws={'figsize': (16,10)}, \n",
    "                    yearlabel_kws={'color':'black', 'fontsize':14}, \n",
    "                    subplot_kws={'title':'# Checkins in 2018'})\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Traffic drops during week-ends and national holidays (May). The decline in traffic is less significant during school holidays, apart from summer holidays (August)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.C.b. What was the day with the most traffic, in 2018? <a name=\"3Cb\"></a>\n",
    "\n",
    "> Answer: February 06, 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'February 06, 2018'"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "busiest_day = pvt_days.nlargest(n=1, columns='NB_CHECKINS').index[0]\n",
    "busiest_day.strftime(\"%B %d, %Y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### What was the day with the least traffic, in 2018? <a name=\"3Cba\"></a>\n",
    "\n",
    "> Answer: January 01, 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'January 01, 2018'"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "quiet_day = pvt_days.nsmallest(n=1, columns='NB_CHECKINS').index[0]\n",
    "quiet_day.strftime(\"%B %d, %Y\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.D. Which stations have the highest proportion of IMAGINE R & NAVIGO checkins? <a name=\"3D\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.D.a. Heatmap of IMAGINE R traffic (% of total traffic) <a name=\"3Da\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "728d95a5ac0740718633b9444b14ca4f",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>Map</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
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CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.892828853400005, 2.3274284585], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='GUY MOQUET'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.9458456578, 2.36454176212], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='SAINT-DENIS-UNIVERSITE'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.8684401633, 2.4015617127400004], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='PELLEPORT'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.8819319996, 2.3934454523900004], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='DANUBE'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.8450615799, 2.4012890198299996], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='PICPUS'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.841338247299994, 2.4009185368], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='BEL-AIR'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', 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location=[48.8046881209, 2.3639531966], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='VILLEJUIF-LEO LAGRANGE'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.8410940563, 2.2879457665], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='BOUCICAUT'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.826054999200004, 2.40674222317], options=['class_name', 'color', 'dash_array', 'fill', 'fill_color', 'fill_opacity', 'line_cap', 'line_join', 'opacity', 'pointer_events', 'radius', 'stroke', 'weight'], popup=HTML(value='LIBERTE'), radius=3, stroke=False), CircleMarker(fill_color='#ffffff', fill_opacity=0.7, location=[48.814803006999995, 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'bounce_at_zoom_limits', 'box_zoom', 'center', 'close_popup_on_click', 'double_click_zoom', 'dragging', 'inertia', 'inertia_deceleration', 'inertia_max_speed', 'interpolation', 'keyboard', 'keyboard_pan_offset', 'keyboard_zoom_offset', 'max_zoom', 'min_zoom', 'scroll_wheel_zoom', 'tap', 'tap_tolerance', 'touch_zoom', 'world_copy_jump', 'zoom', 'zoom_animation_threshold', 'zoom_control', 'zoom_start'])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "d1 = metro_nb.groupby('STOP_NAME')['NB_CHECKINS'].sum()\n",
    "d1 = pd.DataFrame(d1).reset_index()\n",
    "cols = {'NB_CHECKINS':'TOTAL'}\n",
    "d1.rename(columns=cols, inplace=True)\n",
    "\n",
    "d2 = metro_nb.pivot_table(values='NB_CHECKINS', index='STOP_NAME', columns=['TICKET_TYPE'], aggfunc=np.sum).reset_index()\n",
    "\n",
    "d3 = d1.merge(d2, how='inner', on='STOP_NAME')\n",
    "d3['PCT_IMAGINER'] = round(d3['IMAGINE R']/d3['TOTAL'],2)\n",
    "d3['LAT'] = d3['STOP_NAME'].map(geo.LAT)\n",
    "d3['LONG'] = d3['STOP_NAME'].map(geo.LONG)\n",
    "\n",
    "# Heatmap of PCT_IMAGINER\n",
    "\n",
    "center=(48.855115,2.352448)\n",
    "\n",
    "m = Map(\n",
    "    center=center,\n",
    "    zoom=12\n",
    ")\n",
    "\n",
    "# Heatmap layer\n",
    "locations = []\n",
    "\n",
    "for x in d3.iterrows():\n",
    "    lat = x[1].LAT\n",
    "    long = x[1].LONG\n",
    "    p = x[1].PCT_IMAGINER\n",
    "    \n",
    "    loc = [lat, long, p]\n",
    "    \n",
    "    locations.append(loc)\n",
    "\n",
    "heatmap = Heatmap(\n",
    "    locations=locations,\n",
    "    radius = 20,\n",
    "    blur = 15,\n",
    "    max = 0.007\n",
    ")\n",
    "\n",
    "m.add_layer(heatmap);\n",
    "\n",
    "# Stops layer\n",
    "for x in geo.iterrows():\n",
    "    lat = x[1].LAT\n",
    "    long = x[1].LONG\n",
    "    \n",
    "    n = x[0]\n",
    "    \n",
    "    message = HTML()\n",
    "    \n",
    "    message.value = n\n",
    "    \n",
    "    circle_marker = CircleMarker(location=(lat, long), draggable=False)\n",
    "    circle_marker.radius = 3\n",
    "    circle_marker.stroke = False\n",
    "    #circle_marker.color = '#000951'\n",
    "    #circle_marker.opacity = 0.7\n",
    "    circle_marker.fill_color = '#ffffff'\n",
    "    circle_marker.fill_opacity = 0.7\n",
    "    m.add_layer(circle_marker);\n",
    "    \n",
    "    circle_marker.popup = message\n",
    "\n",
    "# Add a layer with the basemaps dictionary to change style of the map    \n",
    "dark_matter_layer = basemap_to_tiles(basemaps.CartoDB.DarkMatter)\n",
    "m.add_layer(dark_matter_layer)    \n",
    "    \n",
    "m\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img width=\"1000\" height=\"700\" controls src=\"img/map2.png\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> This map produces a quite different result from the [map of # checkins per station](#3Aa). Indeed, the Rive Gauche (southern bank of La Seine) has more traffic, due to the prominence of universities in that area, and hence the higher proportion of checkins performed with IMAGINE R tickets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.D.b. Stations with the highest proportion of IMAGINE R traffic (% of total) (bar plot) <a name=\"3Db\"></a>\n",
    "\n",
    "> Answer: NOTRE-DAME-DES-CHAMPS, JUSSIEU, CENSIER-DAUBENTON, CRETEIL-UNIVERSITE, RASPAIL."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 480x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "df = d3.nlargest(10, 'PCT_IMAGINER')[['STOP_NAME', 'PCT_IMAGINER']]\n",
    "\n",
    "# Figure\n",
    "plt.figure(figsize=(6,6), dpi= 80)\n",
    "\n",
    "# Data\n",
    "stops = df.STOP_NAME.tolist()\n",
    "n_stops = len(stops)\n",
    "y_pos = np.arange(n_stops)\n",
    "percentage = df['PCT_IMAGINER'].tolist()\n",
    "\n",
    "# Colors\n",
    "colors=['#ea3546', '#ed2d62', '#e92f7f', '#df3b9a', '#ce4ab3', '#ce4ab3', '#b65ac9', '#9769da', '#6f75e7', '#2f80ed']\n",
    "\n",
    "plt.barh(y_pos, percentage, align='center', color=colors)\n",
    "\n",
    "\n",
    "# Style\n",
    "\n",
    "# Title\n",
    "plt.title('Stations with the highest proportion of IMAGINE R checkins', fontsize=15)\n",
    "# Labels\n",
    "plt.xlabel(\"Percentage\")\n",
    "plt.ylabel(\"Station\")\n",
    "plt.yticks(ticks=range(n_stops), labels=stops)\n",
    "# Spines \n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)\n",
    "# Invert y axis\n",
    "plt.gca().invert_yaxis()\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Unsurprisingly, the stations with the highest proportion of IMAGINE R checkins are those close to universities."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.D.c. Stations with the highest proportion of NAVIGO traffic (% of total) (bar plot) <a name=\"3Dc\"></a>\n",
    "\n",
    "> Answer: ESPLANADE DE LA DEFENSE, QUATRE SEPTEMBRE, SAINT-PHILIPPE-DU-ROULE, KLEBER, SAINT-AUGUSTIN."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RNCdp7tNB+dEKb9K947tUnccrrJT/7Wpj/cdJz9Era/T+X7G4kIfBViAHooXyK5MmcxetXKe+Rto9FsXtla1CmlvW8LEdHeip/WrH4aTrxI/LGZKWI/Wu/w64tpQ9G2mIdGcKz/+LiDcknQd8NT/SaEdgTJ1e6HouIQ3vbkt6v7bjUmB3SetGxC119mFjUg/e71vU8wgwuBwcdlNtKPftNj6rjwBt9VSRhpavIc1FfYV0o06PyUPUpwKn5mkvN5DmUo5utp6HOK0jkjbOF/Oy2hyR4tDB/6j/sM73mPpX7vdJQUtR7YLczgM/LyNN0BxaaOvsud7XmPoi2JTS0/Y/Wkp+hPRFPlcbVVxPug3903wYoI3L6x9I6gW5s0Udnex/J2q/dqel3r+RzteIcoak2dVLT9HPwyT/Is3FWaqwzRVIw9HdrfNcYId6Qw953kvt74VL675NupNLpOEq6N55m51092NtO3Pm5edp/T6B9P7/dH4Yaa2OeUm/1rtyG4u+nr8oanYk/biqzeO7gxQM7yXpg/e70pPuP0H68m7H/2hj2kJE/If0+dit+N7J52PzvH89oaf2q6X84+500nksT42o9Z4dHRH/KL3+RrpeNRrmnJM0t3AhWgxvFvye9F76TYO5UPWu6UeTfgydLGmhKQqneV9/IF1bf9Vi2+eS7jL+9lQbrf9d0lB+n9wAfLsw16xY36KFxXOBtSV9sU65qbYbEaeS7mr+nqQjyvndVeea8Srpu6Tl94h70KxTvwXmkXQ+qdt8TtIvwaGkL4LTCmXvBDaVtD/pDrnHIuJW0q+5XSW9TPriWI/UG/NfplR7TMCPJS1Amq92dUQ8V6ddtUc9jJa0dm7LjsAGpLuZWk12LVsJuErS33Ib3yXdebk4aSi2letJF9ggD3lGxHuSbiINl46N1g/b7WT/25Z/id8PDM1D0y+S7jBr+4aFiLhW0omkId/BwD9Jd5+tSOoh3Ic08bw3jCR9ad8o6QRSoPg90nyTwd2s80DSjQ23SjqZdM4XIt0csGn+G+Cfkp4hDUs9S/pS/x7p0Qi191gtoDpC0tmk43Jxix6gf5PO8wDS3LOheV/2jNZPr4f0iJOvApdLOp50TncDliM9+6o8/PgicIOk00jv6X1Jc9BOhnSDjaQfkz7P10o6K5fbh/TZOq6NNkE6FkMlHUuaDvFavUnb2QGkAPFmSaeQ5hp+nzQFYmSb22uqB/erXUeQHjmyMumRDzW7AOMi4skG610E/FbSWhFxVyH9KtLNHF8iBb8XtNOIiHhB0pdJN8KMz+/L20nXtY/z4U0JTxTWmShpd1Jv3r35nHSR3lPfIM2zGhqtH1J7GukYHC9pXdJnZ17SZ3gUnQfF3yZdXyfkz+pjpHO4Qf63dkPPUaQpCOfltt9N+hxvR3ps0lTXu4j4Tb7W/kzSyxFxdIdtq+dBSWNIn4WXSD/atyPte3Pt3Orpl1+1F2nezSmkibuvkoKGh0h3Sy5WKrsy6Zfg6zDFg2r7kbp7a0NLV+SyXZQey0G6EDxCupAErR9UW6v3LdJwzbBSmQE0eHwGhcc5kCZ1/i7v52ukO3FuAXZq8zitmuu7v5R+UE7/eZ11Otn/LuCSOnVMdVwatG89Um/CW6X9Hk36Ei2XH0npERY5/Zu5ntdJQwPjSRfGJVtsv+3tFNtXSNuE9EiOt0iBxXDSL/k36qw71YM0GxzrxfI5f4J0B+9/SL113yyU2ZP0nn6BD5/9dTQwf6mug0mT5t+jxSM3qP+g2i4Kz8jL5YbkunZsUE/tQbUv5TpupfGDav+P9KDaZ/O5uwT4eJ06v5KP85ukH1ANH1TboE3zknp5Xsrb7Sp9Dsufz8+TftC8TgrMLqLxg2oXKaUPa3WsO9yvWn0dPWajwXs9yI/ZIAUQda8BhXWWzWWOrZN3bM47o8G6Uz1mo5C3JOnRHPfnY1x7uOpoYIMG9a1ButP0P6TPxb/z8Vq11XEp1DFPfr89Vqjjb7Vz1ajNpE6kAA4upQ8kBY7P8OEDaC+i8My/XG4RUu/h07ncE6TviAVz/lQPqs3pv87p38rLDR9UW2dfbyDdOV5bHkF6Dt1L+ZjfT/pB2PKZdLVngZiZzdAkXUB6SO+KLQtXiKSxpGCj3fky07KtIaS5NjtFRG/1cJpZD/AcNDOb4Sg/C6qwvCJpHuTYPmmQmVkP8xw0M5sRPSppNOlJ+cuS5qW8TRpuNDOb4TlAM7MZ0RWkSfFLkOaW3Az8NCIearqWmdkMwnPQzMzMzCrGc9DMzMzMKsZDnDZLOfbYY2PQoEF93QwzM5tGm2+++f4R0dPPrqsMB2g2Sxk0aBCbbbZZXzfDzMymXdsP154ReYjTzMzMrGIcoJmZmZlVjAM0MzMzs4pxgGZmZmZWMQ7QzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxiHKCZmZmZVYwDNDMzM7OKcYBmZmZmVjEO0MzMzMwqxgGamZmZWcU4QDMzMzOrmNn7ugFm09Nef32F+W56sa+bYWbWsXGHLtTXTbDpyD1oZmZmZhXjAM3MzMysYhygmZmZmVWMAzQzMzOzinGAZmZmZlYxDtDMzMzMKsYBmpmZmVnFOEAzMzMzqxgHaGZmZmYV06sBmqQuSZMkjSu8BuW87SXdmdMmSrpa0mw5b6ykx3LeJEmHF+oMSf0abE95vatK6QPyeqcU0j4mKTpY/73cnntze0+W1L9QZrSkp0v7unudNvZ0XZObHP/5JL1W3O8G5YrH+2FJYyR9oZA/RNIbpfac3yRv25zX7Px35X2fvbCdOyQNyX8vI+mifIzuzetukvOGSXq5VO/vm+2jmZnZjGR6/FdPQyNiXDFB0pLAScDaEfF4TlsLKAZM+0XEBZIWBO6WdGtEXNxiW58HJgOrS1ouIh4r5L0ObCVp1Yi4vxvrvxoRg3Nb5wQOBm6SNCgiXs5ljomIUS3a2NN1NTMUuBPYXtI+EfFak7L7RcQFuU1DgLMlfScizsv5k2ptrqNZ3lTnv2AuYDhwYp28E4CrIqIW7C0CzFPIvyYitmu8O2ZmZjOuvhriXBx4D/jgP0WMiLsiIsoFI+Il4DZg5TbqHQ6cDJwJ7FHKewc4Mr+6s36xTW9HxCHA08DX2mhXQz1ZVx3DgaOA60jBWrttGguMBH7Sw+0pGwmMkDRPnbz+pGNSa9MLEfFEL7fHzMysEqZHgHZOaShqbmA8cAPwuKTzJR0gael6K+ehv8+SeoIakrQQsCUpuDoFGFYbMi34I7CapA26uX7ZbcAnC8sHlPZ1wxbr91ZdSFoVWAa4krQ/wztZH7i11J6VS+05pkneRwp59c5/zT3ANcB+dbZ/FHCKpBsl/VrS50r5G5fqrVcHkvaX9FTtNfn+Vp2wZmZmfa9PhjizHSStAmwEbAUcJGmdiHg45x8naSSp5+uwiLimxXZ2AS6PiMnAZEnPAlsAl9cKRMQ7kkaQvvy37HT9OlRanpZhyZ6sC1JA9peIeE/SZcCJkj4REQ90sz29McQJMAK4TdIfi4kRcZakK4CNgQ2ACyX9IiJqgWFbQ5wRcSxwbG154NfPnaqX1szMrGr69C7OiJgYESfmL9pbgG0L2ftFxOCI+FREnNBGdcOBTfLk8y5gOer3Gp0FzAt8qZvrF30KmNBG29rRY3VJmgPYFdgt78vDpPlbnfSi9eS+NRQRXaRey4Pr5L0UEedFxA+Ab5P2yczMbKY3PXrQppKHMwdExI15eUFSQPRIN+tbG1gUWCoi3s9p/YAnJS1aLBsRIelA0nBnx+vnvDlJ87P6A2d0p829UVfBtsCjEbFuYTufAMZK+klEvNOiTRuS5od9r4fa08rhwAOk3tJaG7YBro6I1yUJWJNuvj/MzMxmNNMjQDtH0huF5f2AR4FDJC1HurtyduDPEXFhm3XepykfkXERcHYtuAKIiMmSxpB6Xc4rrhwRV0p6FBiQk4a3sf58ksblts4BXA+sX7jrEtK8sWGF5TMKQ3JFPVnX/JKeKiw/CbxEKdiLiAckPQ18kdLxyGpDyvMCjwPfjIhLCvkr5zbXvBoR7cyLm+r8l4erI+IFSccDPy8kbwQcI+ld0nDrJKYMGDcutWdSRLR9I4SZmVmVqc6Nk2YzrYFfPzfmG7hxXzfDzKxj4w5dqK+bUCmSNo+IMX3djt7i/0nAzMzMrGIcoJmZmZlVjAM0MzMzs4pxgGZmZmZWMQ7QzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFdMn/9WTWV/5467zs9lmftijmZlVm3vQzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxifBenzVL+cPKLXDrmmb5uhpn1gVFHL9HXTTBrm3vQzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxiHKCZmZmZVYwDNDMzM7OKcYBmZmZmVjEO0MzMzMwqxgEaIGlOSUdJeljSA5ImSBpeyB8iaVxpnQGSJpfSlpf0vqQRhbS9JI3LrxclPV1Y3ljS6ELaREl/lTRPYf0uSZMK64yTNKjOPvSTdHpu+/j8786F9r9RquP8OnnjJd0gaXVJPy+UfU3SY4XllSWNLaWNk7RFrnOspLclLVbn2FxQOH7vFdadKOngQvmRkp7PeQ9IukjS4oX8hts3MzOb0fm/ekpGA3MBa0TE/yQNAC6XNGdEnNBBPXsAVwO7Szo8kj8CfwSQNBoYFxGjaitI2g04JiJGSZorr/894OhCvUMjYooAsY7DgeeBQRERkuYDiv+vyaSIGNxg3Q/yJO0PnBYRawOH5LSxwKiIuKDQboD9imkl44FdgV/n5T2AO0tlXi1sdwFgkqTzI+K+nH9GROwraTbgbOBQ4DuF9Ztt38zMbIY1y/egSVoR2A7YMyL+BxARXcAPgBFNVi3X8xFgGLA38CqwSadtiYi3gBuAZTtdF+gP/CciItf1akQ81I16rgBW7sZ6ZX8GdgPIAdZQ4Mwm5ecFBLxSzoiI94Fr6N5xMTMzm+HM8gEasCbwUET8t5R+M7BkcVithS2ApyLifuAUYHiL8lPJvUhDgHNLWeeUhvLmrrP6b4AfS7pT0u8kbVPKX7lUxzENmvF/TN3T1chxpToHFvKeBJ6R9Blgc+AO4KXS+vPl9e4FHgNOiognyxvJPYvbAOd0sH0zM7MZloc4W3sDiAZ5xfThwKn57zOAn0taMCLKQUk9B0jaA1gJuJTUW1TUcogzIq6R9HFgI2B94ERJF0TEd3ORZkOcK+vDOXYPknu+2tBqiPFU0nFZEDgJWLqUXxziXAi4StLtEXFRzt9F0hBgIHAv8LcOt18bst2/trza6l9j2QEbNd8rMzOzPuYeNLgbWFHSwqX09YD7IuIV0tyucv4iwHMAkhYFvgCMkNRF6oGaA9ilzTYcExGrkwK0dYC9urEfRMT/IuKyiDgY2IE0B6wdkyJicH59JQ/x9oQLSD2LawBXNSsYES8CY3L5mjNyALcsaY7gzzptQEQcGxH9a68VVi53LJqZmVXPLB+g5XlaFwMn1e6ezDcJHEWahwbwEPCOpK1z/mzAt4B/5vyvAxdExDIRMSAiBgA70uEwZ0Q8AXwfOKTBMGZDkjaXtGAhaW3gkU7q6GkR8SawH7B3nkfWUB7G3ACYVKeeF4FvAN+VtGRvtNXMzKxKZvkALfs6KZi5V9JDwMPAARFxJUBEvAN8GfhBHgqsDQcelP8dThrWLBoDLCVprU4akof3JjLl3YrlOWgb11l1EHBd7TEbwLbA1wr55Tlo13fSrgbKc8Cm6jGMiPMi4ooG69fmoNWO6T1A3btmI+Ju4O/ATzvZvpmZ2YxI+aY/y3Lv2C+BzYDP594bm0l8+SvnhOegmc2aRh29ROtCNsOQtHlEjOnrdvQW3yRQkofiftTX7TAzM7NZl4c4zczMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxiHKCZmZmZVYwDNDMzM7OK8XPQbJbynW8uxGab+WGVZmZWbe5BMzMzM6sYB2hmZmZmFeMAzczMzKxiHKCZmZmZVYwDNDMzM7OKcYBmZmZmVjF+zIbNUi45/mkeOf+hvm6Gmdxo7sgAACAASURBVE0ne/1hxb5uglm3uAfNzMzMrGIcoJmZmZlVjAM0MzMzs4pxgGZmZmZWMQ7QzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxiKhOgSdpe0p2SxkmaKOlqSbPlPEl6TNJVpXUGSJpcWO7K685eSLtD0hBJP891j5P0Wq6vtrxynfbcIOnRQnt+ltNnlxSSPlYq/5Sk1fLfp0v6Xv77G5L+Uaf+FSS9UFp/Yt7e/ZL2KpR7N6ffk/fnc4W6Jxf2Y5yk4xsc31rZuyU9kMuOkPTRdverxTF6UNKvJamQ30/SybnMREm3Sdqy1KZ/lOrcVNId9Y5RnXbVjlfttWq9smZmZjOaSvxXT5KWBE4C1o6Ix3PaWkDkIp8HJgOrS1ouIh5rUt1cwHDgxGJiRBwCHJLrHguMiogLWjRt74i4RNJCwD2SbgHGdLRzndkxIiZIWi5v7zrgbWByRAzObf8K8DdgibzOvyJixzbr/6CspCWAU4Azge2noc21Y9QPGAfcCJyXg+srgFuAFSPivXxOL5H0tYi4ehq2WbNjREzogXrMzMwqpSo9aIsD7wEv1hIi4q6IqAVow4GTScHEHi3qGgmMkDRPTzUuIl4Ebgem6mnrDTkAfRhYqU72FcDiOSCalm08A3wd2LpeD2I36psM3Aksm5M2B5YEfhgR7+UydwG/BA6e1u2ZmZnNzKoSoI0HbgAel3S+pAMkLQ2Qe6+2JAVnpwDDakOfDdwDXAPs11ONk/RxYH3grkLyTcXhNWCxHtzeGsAKpONS9lXg0RwQAWxaGubbu93tRMR/gUeAT/ZAm5cCVgMuy0lrAXdExLulojcDa0/r9rJ/lPZ9zh6q18zMrE9VYogzIt4HdpC0CrARsBVwkKR18t+X54BksqRngS2Ay5tUOQK4TdIfp7Fpx0s6nDTMeEhEXFeY37Z+RLxWKyjpqWncFqSA403gf8BuEfGopBWAfjkIFPAksF1hnU6GOOupzRmLJmWa5R0v6ZfAKsBxETGpg203qrfZ9opaDnFK2h/Yv7b82VWH8ollNmizejMzs75RiQCtJiImAhOBEyVdAWxLGoZbQlJXLjYfacizYYAWEV2SzqTNoTRJWwBH5cWzI+KX+e+9I+KSjnek+xoFHB/MQWuXpFtJ8/Fej4j1G5RZGFgemJDniL0ELAy8lvOVl59rdYwkrQlcK+mfETGG1Nv4LUmzl3rR1uPDnsjnc/1FiwDPdbKvzUTEscCxteV9vji63eDPzMysz1QiQMvDmQMi4sa8vCCwHCkYWxRYKveykedePSlp0RbVHg48ALzTavsRcSVwZff3oHoi4jPN8iUtBvwJuCwiHszJVwLfAn6al3cHHoiI53New2MUEXdLGgkcSbqR4p/As8CvJP2gcJPAT4Bd82o3A6dIGhQR90qaizTH8NKOd9jMzGwmUpU5aLMDh+RHNYwDrgf+TLp54OxacAYfTEYfw4df8nVFxAvA8aSJ6n1t6/xYiNrr6B6suzwH7YwWZe+W9ADpGN4B7FzI3xtYVtL4fB52AoZ20JbfAQtK+lI+Z1uSguyHJU0i3Vk7PCL+BZADv6HASXl7t5NuNPh9oc4FS8fu+kJeeQ7ahh201czMrLL04Y2SZjO/fb44OjwHzWzWsdcfVuzrJlgvkbR5nlIzU6pKD5qZmZmZZQ7QzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxiHKCZmZmZVYwDNDMzM7OKqcR/9WQ2vWyz99JstpkfXGlmZtXmHjQzMzOzinGAZmZmZlYxDtDMzMzMKsYBmpmZmVnFOEAzMzMzqxgHaGZmZmYV48ds2CzltiMn8u7oBfq6GWbWi7Y649N93QSzaeYeNDMzM7OKcYBmZmZmVjEO0MzMzMwqxgGamZmZWcU4QDMzMzOrGAdoZmZmZhXjAM3MzMysYhygmZmZmVWMAzRri6QuSYPz3x+VdKGkv0s6U9K+dcoPk/SypHGF1+/r5N0jabykLxXWHSvpsdK6W9TJmyTpOEl+H5uZ2UzF/5OAdUTSfMBFwEPAXsCpTYpfExHbtcqTtC5wMXBhIX+/iLigwbr7RcQFkuYHxgE3A3/rYDfMzMwqzT0P1omFgauBWyNiz4h4v4fq7Qe81OlKEfEKcDuwbA+1w8zMrBIcoFknzgH+FREHtll+49Iw5X518h4EzgX2L617XGndgeXKJS0JrAFc0p2dMTMzqyoHaNaJS4EdJS3TZvlrImJw4XVcnbyVgM8Af5K0VCF/v9K6jxTyjpM0AXgCuDwiHmjUAEn7S3qq9rrhiavbbLqZmVnfcYBmnTgOOAEYK+njPVVpRNSCrQ3aXGW/iFgNWBvYQ9JWTeo+NiL6116f/fgmPdBiMzOz3uUAzToSEccCvyUFaT0y90tSf2BF4MEO2zIeGAH8QpJ6oi1mZmZV4ADNOhYRo4BRwLWAgJHFYURJO+Wi5Tlo5xSq+SAPuBL4aUTcU8gvz0HbpUFzTgDmBbbv2b00MzPrO37MhrUlIgaUlo8Hjm+x2ugGdY1ulJfzh7SbFxHvACu1aIeZmdkMxT1oZmZmZhXjAM3MzMysYhygmZmZmVWMAzQzMzOzinGAZmZmZlYxDtDMzMzMKsYBmpmZmVnFOEAzMzMzqxgHaGZmZmYV4/9JwGYpn/7JKmy22af7uhlmZmZNuQfNzMzMrGIcoJmZmZlVjAM0MzMzs4pxgGZmZmZWMQ7QzMzMzCrGd3HaLOXhg25hkVFv9XUzzKwXrHnpNn3dBLMe4x40MzMzs4pxgGZmZmZWMQ7QzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxiHKCZmZmZVYwDNDMzM7OKcYDWiyRtL+lOSeMkTZR0taTZcp4kPSbpqtI6AyRNLix35XVnL6TdIWmIpJ/nusdJei3XV1teuUGbZpP0hKQrS+mbSrqjlLaCpBcKy/NLOl7Sw5LGS7pH0l8lLZvzD5f0q1Id35D0j/z3nJJ+L+m+vP79kvaR9JlCu5+QNLmwvF+pjhUkhaQTC9voJ+ndds+LmZlZ1fm/euolkpYETgLWjojHc9paQOQinwcmA6tLWi4iHmtS3VzAcODEYmJEHAIckuseC4yKiAtaNG1z4HlgHUkfj4gn2tyf2YArgLuB1SLiTUkfAXYClgceb6Oa/YFFgDUi4l1JHwWWj4j7gcF5O98AtoyIHQvb/kapnteAbSUdGxGT2mm/mZnZjMQ9aL1nceA94MVaQkTcFRG1AG04cDJwJrBHi7pGAiMkzdMD7aoFemcDu3ew3ubAUsA+EfEmQES8FxFnR8Q1bdbRH3g2It7N67+Zg7NOvQUcDfyiG+uamZlVngO03jMeuAF4XNL5kg6QtDSApIWALUnB2SnAsNrQZwP3ANcA+01LgyQtAmxKCs5OAXaXpDZXXwu4sxZcddNJwA55iPMkSUNzL1x3/AFYS9JnpqE9ZmZmldR2gJbnRp0g6Z95LtXVkq7uzcbNyCLi/YjYAVifNDS4AXCfpBWAXYDLI2JyRIwHngW2aFHlCGAfSQtPQ7N2BS6OiFci4i7SEOumtSY32pV6iZI2znPEHpZ0SDt15H1dHtgbeBI4DDiv892AiHgLOBQ4qlk5SftLeqr2uuqZm7qzOTMzs+mqkx60v5G+0H8H/LrwsiYiYmJEnBgR2wG3ANuShhk3yTcAdAHL5bRm9XSRetwObme7krYoTLQ/MCcPBzYvbHeZwnafB8rB3yLAc/nvu0k9VrPn9lwTEYNJvXHzt1kHEfFWRFwVEYcBm5Dmks1P95wOLAR8oVGBiDg2IvrXXp9fYv1ubsrMzGz66eQmgY9GxE96rSUzmTycOSAibszLC5ICsfmARYGlIuL9nNcPeFLSoi2qPRx4AHin1fYj4krggzs181Dg/MCStXlwuTeuKw+5TkxJ2iIirsxDrt8C/pmruJLU03ecpANq89CAeUlz7QCuAg6U1D8inpK0ALAzqfcPSRsBkyLimVx+bVJQ92qr/Wmwj+9L+gnpR4OZmdlMo5MetAmSPt5rLZn5zA4cIulBSeOA64E/k24eOLsWnAFExGRgDGkIsqGIeAE4HliyG+0ZDpxVuEmBiPgvaW7b1yLibeDLpABrHDAOeJt8l2hu7xaASEO14yXdSOoxOyWXuQ/YF7iwsM+jI+LCvMkBwOX58Rr3AD8Etiu2qVMRcSnQ1p2oZmZmMwq1+90oaQywDnAzUOs9ISK2752mmfW8Ez59WKy76Jp93Qwz6wVrXrpNXzfBpiNJm0fEmL5uR2/pZIjz9PwyMzMzs17UdoAWEX+GNEkpL3d7WMrMzMzMGuvkMRtLSroMeB14XdIl+Wn5ZmZmZtaDOrlJ4CTSg1eXzK8bcpqZmZmZ9aBO5qAtExFfLCz/Mt+pZ2ZmZmY9qJMeNElaorCwBOmRC2ZmZmbWgzrpQfsVcLeky/PylsABPd8kMzMzs1lbJ3dx/lXS3cCQnPTr/GBSMzMzM+tBnfSgERETgAm91BazXrfCEeuy5mab9XUzzMzMmmoZoEk6KyK+mnvPpnr2WUSs1SstMzMzM5tFtdOD9qv877692RAzMzMzS1oGaBFxZ/5zYEScWsyTtAdwbW80zMzMzGxW1cljNr5XJ+27PdUQMzMzM0vamYP2aWA9YFFJexeyFgDm6q2GmZmZmc2q2pmDtiQwGJgHWLOQ/gowrBfaZGZmZjZLa2cO2oXAhZK2iojLW5U3q7KHD7qFRUa91dfNMLMetual2/R1E8x6VCcPqr1c0lLAasBHC+kX9UbDzMzMzGZVbQdoknYHDgUWAh4C1gBuARygmZmZmfWgTu7i3J80B+2RiFgb2AR4sFdaZWZmZjYL6yRAezsiXiL3ukXEdaSbB8zMzMysB3Xyf3G+JUnAg5L2BR4HPtY7zTIzMzObdXUSoB0MzA/8CPgj0A/4Tm80yszMzGxW1kmA9kJEvAy8DGwGIGn1XmmVmZmZ2Syskzloo9tMMzMzM7Np0M5/9bQYsAQwt6RBgHJWP2DeXmybmZmZ2SypnR60rwIXAsuTnnl2IXABcDxwdO81zZqR1CXpOUlzFNI2lhSSRkkaImlcIS8k3SvpHkn35+faFev7hKRLJT2SX5dIWqWQPzLX8eVCmiQ9JmlyqV2TJI0rvAblvO0l3ZnTJkq6WtJsOW+spP9KWqBQ1z8kDct/D5N0Qf57QHGbZmZmM5uWAVpE/CYilgMOz/9uCvwWGBERp/R2A62pJ4BtC8vDgTualN8wItYgBd0nSloSIP8PEdcCZ0TEwIgYCJwBjJW0RGH9O4E9CsufB16os52hETG48Lo3b+skYPuctgrwQyAK670CHNjGfpuZmc3UWgZokv4laXBEHJa/yG8HNgeOlvTjXm+hNXMaOWDKPU/rAle0Wiki7gFeAvrnpO8AYyPizEKZs4DrmPJO3RuAgYWgbQ/g1DbbujjwHvBiYRt3RUQxQDsKGJ7fZ2ZmZrOsdoY4l46I2lDZzsC1EbEVsD6wS6+1zNpxIzAgBzRfBf5OCoKakrQRqefrnpy0FnBznaI3A2uX0k4HdpPUD/gUcGWd9c4pDXHODYwnBXiPSzpf0gGSli6t9wxwIvCzVvvQLkn7S3qq9rrqmZt6qmozM7Ne085jNt4o/L0+cBlARLwk6d1eaZV14q/AMGA7UsDcLGi+PgdLywE7RsTb3djen4ExwGvA34D365QZWgjqi3bI89o2ArYCDpK0TkQ8XChzDDCpOP9tWkTEscCxteUTPn1YNCluZmZWCe30oL0vqb+kj5G+WK8t5M3TO82yDvwF2Bt4MyIealF2w4hYgTRXbbSkxXP6XcB6dcqvl/M+EBFPk/4XiUNJQ6wdiYiJEXFiRGwH3MKUc+iIiFdIQ51Hdlq3mZnZzKKdAO0XwN3AQ8A1EfEggKT1ga7ea5q1IyL+DfwEaHs+YESMBq4CfpqTTgA2lrRzrYykrwJDgD/UqWIEcHCp56spSUtL2qCwvCCpJ++ROsVPIP0/r+XhVTMzs1lCyyHOiDhP0k2kSd7jC1ldwJ691C7rQER03JNFCujulHR0RDwtaQjwK0mHk+6snARsFBH/qbO9O2h+t+g5kopD4/sBjwKHSFoOeJ303vtzRFxYp/63JB1C6h1sZH5JTxWWn4yIer2AZmZmMxxNeROd2czthE8fFusuumZfN8PMetial27T102w6UzS5hExpq/b0Vs6+a+ezMzMzGw6cIBmZmZmVjEO0MzMzMwqxgGamZmZWcU4QDMzMzOrGAdoZmZmZhXjAM3MzMysYhygmZmZmVVMO/9ZutlMY4Uj1mXNzTbr62aYmZk15R40MzMzs4pxgGZmZmZWMQ7QzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFePHbNgs5Zn9LqOrX1dfN8PMetCAG77Z100w63HuQTMzMzOrGAdoZmZmZhXjAM3MzMysYhygmZmZmVWMAzQzMzOzinGAZmZmZlYxDtDMzMzMKsYBmpmZmVnFzPABmqT5JL0m6ZRS+hySjpd0n6R7JN0vaf9C/iGSJuS8iZKOKeSFpHsljSu8Fi7kjStta/ecvm9eHibp5bzePZLGS/pSofxYSdvV2ZeRkp4vbfegVnl16glJ/yqlvSBpQCntWkkPS1JeXqpQ98OS3igsHydpSHHfJS0g6URJj+ZjeLukrQv5Q3JbRhTSVpPUVWpHo3M4xfbq7GPdc2RmZjajmxn+J4GhwJ3A9pL2iYjXcvo+wFLAGhHxrqSPAgMBJO0IbAV8KiLekDQ78MlSvRtGxOQG23xX0toRcWde3gO4o1TmmojYLm9vXeBi4MI29ueMiNi3G3llAyVtERFX1suUtCKwIvASsBEwNiL+DQzO+UOAURExuLDOkMLfAi4D7gZWysd4MHCppGERMSYXfQb4vqQTIuKFBm1tdA5baXaOzMzMZlgzfA8aMBw4CriO9EVf0x94LiLeBYiINyPivkLei8CbOe/diLing22eRgrKkLQSMAdwX5Py/UiB0PR0CPDLWu9YHXsApwN/Ih3DTn0eWBbYv3CMxwFHACMK5Z4F/lpKK2t0Ds3MzGZJM3SAJmlVYBngSuAUpgw0Tga+KOkBSSdL+j9JH8l5ZwPLAY9K+oukPSTNXar++sLQ2TWlvPOArXOv3B6kgK1s47zug8C5wP51ytSzS2nYbmibeWUXA68BO5cz8nHYDTiVFDx9UdICbbavZi3gzoh4u5R+M7B2Ke0I4KuSlqvTlmbnsJVm58jMzGyGNUMHaKQv879ExHuk4bblJH0CIPeWDQS+CzwO/Ay4KOc9AwwCdgHuBb4D3CRpzkLdG0bE4PzauLTdN0gBxU75dVadtl2T110J+AzwJ0lLtbFPZxS2Ozgizmkzr54fA4eV9gtga6ArIibmYcd/USeQ6ykR8SIwCji8TnbDc9iGZucIAEn7S3qq9rr8hbu6tQ9mZmbT0wwboEmaA9gV2C1POn8YmIdCD0xEvB0RV0fE4aR5VltLWijnvRcRN0XEMcAGpB611TpowmnAscBNEfFKs4IRMQF4Im9nuomIm4DxwLdLWcOBlSR15WO3IZ0Pc94FrJ3PQ9F6Oa9sFOkcrFlLaOccTquIODYi+tdeWy2yVk9VbWZm1mtm2AAN2BZ4NCKWjogBETEAWBfYVekOzs9JWrJQfm3SvLPJktaRNLCQtwppHtmT7W48Im4l9Qgd2aqspP6kCfkPtlt/D/op8BNgrtyWxUnzx1YoHLclgaUkrdFBvVeTjtdx+SYL8k0CB1GnpywiXgcOA35eSG56DjvaSzMzs5nIjHwX53DgjGJCRDwg6Wngi6SemFF5ntjbpPlYX4qI9/PjGH4nqR9puPI9YOeIeL5Q3fWS3issD42ISaXt/aZJ+zYuPCJiDuCnpRsR/iTpd4XlnfK/uxTvliQNle7XRl5dEXG/pEvJNzWQ5p79s3j3Yz4mZ5OO6d7N6iutsxVwDPCQpLeBV4G9Gt05Sppjtj85WKT1OXwRWFXSU4UiN0dE7Vi1PEdmZmYzIkVEX7fBbLr562r7xYb9Vu3rZphZDxpwwzf7ugnWByRtXnik00xnRh7iNDMzM5spOUAzMzMzqxgHaGZmZmYV4wDNzMzMrGIcoJmZmZlVjAM0MzMzs4pxgGZmZmZWMQ7QzMzMzCpmRv6fBMw6tsRxWzNgs836uhlmZmZNuQfNzMzMrGIcoJmZmZlVjAM0MzMzs4pxgGZmZmZWMQ7QzMzMzCrGAZqZmZlZxfgxGzZLmbzXX3huvhv7uhlm1oMWGzeyr5tg1uPcg2ZmZmZWMQ7QzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxiHKCZmZmZVYwDNDMzM7OKcYBmZmZmVjEO0BqQ1CVpkqRx+d8Dc/oASZML5WaXdKikiZIm5PInSepXLltYJyT1y3+PlfRYXq/22qKQt12d9UdKGpX/HiLpjdL65+e8YZIuKK07RNK4Bvs8QNJ7uY578z6dLKl/ocxoSU/nMhMl/VXSPIX8OSUdJelhSQ/kenZrtv06x3QBSSdKejRv43ZJW+e8bQv7+Yyk5wvLu9Q/m2ZmZjMW/1dPzQ2NiHGSlgbul3Q18FypzCnAQsB6EfGSJAE75rT329zOfhFxQetiDU2KiMHTsH7Rq7W6JM0JHAzcJGlQRLycyxwTEaMkzQVcDXwPODrnjQbmAtaIiP9JGgBcLmn2iDil1cbz8bsMuBtYKSLelTQYuFTSsIi4CLgolx0J9IuIfXtix83MzKrCPWhtiIingYnAssV0SSsAOwG7R8RLuWxExN8j4tHp39KeFRFvR8QhwNPA1+rkvwXcQD4uklYEtgP2jIj/5TJdwA+AQ9vc7OdzfftHxLu5jnHAEcCIadkfMzOzGYV70NogaRVgYWAsMG8hay3goYh4ocnq8zUaUiw4LvcG1ewQEY900MSVS9sYExEHdLB+K7cBnywnSloAGAL8JCetSToe/y0VvRlYRtKibWxrLeDOiHi7Th3HdNJoMzOzGZUDtObOkfQ+sDJpGPJ5SfO2Wqnk1fLwo6QolemtIc7ydlqlN6LS8gGS9gBWAi4Frumgrp5qU1sk7Q/sX1v++kJrs9F8A3tjU2ZmZj3GQ5zNDY2ITwCbA7+UNKiUfxewoqSFp3/T2vI8qeevaBHyPDpJxxcm2Jf3rehTwITC8jERsTopQFsH2Cun303947Ee8GREPN+qTaRjurakOerUcVeTNtYVEcdGRP/aa5t+n+i0CjMzs+nOAVobIuJfwAnA4aX0h4FzgVMKd2VK0g6Slp/+LZ3KraThz9qk/7mA4cA/ASJi74gYnF/3llfOd2QeCvQHzijnR8QTwPeBQyTNHREPARcDJ9Xu7Mw3CfwaOCyv9hDwTuGuzNmAb9XaRLrp4EnSsO/sucxg4CBKx9/MzGxm5QCtfYcBn2Xq3p89gHuAWyXdB9xP6nF7sYO6jys9JqP4uIg/SXqq8Fqvzvorl9a/HiDPBfsK8Ic8R+124F7g+CZtmS/XMSGXXQZYv3AH5xTyXZUTge/kpK8DjwL3SnoAuITU43ZyLv8O8GXgB7lNtblzB+X894GtSHeCPiRpEvAnYK+IuLJJu83MzGYaiuiVqT9mlfT3gbuG56CZzVwWGzeyr5tgfUDS5hExpq/b0Vvcg2ZmZmZWMQ7QzMzMzCrGAZqZmZlZxThAMzMzM6sYB2hmZmZmFeMAzczMzKxiHKCZmZmZVYwDNDMzM7OK8X+WbrOUfn/8OotttllfN8PMzKwp96CZmZmZVYwDNDMzM7OKcYBmZmZmVjEO0MzMzMwqxgGamZmZWcU4QDMzMzOrGD9mw2Ypr+z5a16c7+y+boaZTaOFxp/S100w61XuQTMzMzOrGAdoZmZmZhXjAM3MzMysYhygmZmZmVWMAzQzMzOzinGAZmZmZlYxDtDMzMzMKsYBmpmZmVnFOEAzMzMzqxgHaNaQpC5JkySNk/SApDMlzZvzPiHpUkmP5NclklYprDta0r6l+kZKGpX/Hibp5Vz3BEnXSFqpUHaQpKsl3ZPzb5e0WqGe5/O6tddB0+eomJmZ9T4HaNbK0IgYDHwSWAAYJmkp4FrgjIgYGBEDgTOAsZKW6KDuayJicESsBtwJjCrknQX8NiLWyPnbA88V8s/I69ZeR0zDPpqZmVWKAzRr15zAPMBLwHeAsRFxZi0zIs4Crst53XEVsGxhuT/wdKH+JyPiuanWMjMzmwk5QLNWzpE0DniG/2/v3oMlKeszjn+fZbkownKPisKiEogXvGEIKhFBkBiRVUBUkAJBy6hVEdCQmMSYaEyIsCYGLxEhWMTLQlAUSgW5yUYJKLAsLLIbjSshAuKFeENL4Jc/pg+Ox3PmzF7OmXfY76eqa6f77e55+q13Z36nu89peAA4F3gGcPUU614NPHNN3yDJPOClQP9TzN8JXJHksiR/m+TpkzY7ctIlziOm2feJSW6fmC78v9VrGk+SpDlngaaZTFzi3A5YDZwy5HY1xPLnd8Xf94D9gA88uFLVacDjgI8A2wBLJxVhky9xLpnyzaoWV9VjJqaDFywcMr4kSaNjgaahVNV9wPnAQcD1wN5TrLZ31wZwN7DtpPbt+PX7yK7oir/HAKvoK9C697yrqj5RVX8EvAs4cl2PQ5KkcWCBpjWxH7AS+CC9s1+vmmhI8kpgX35VZF0MHJ5km679UcAhwBcn77SqfgYcD7xo4lJmkpcm2bh7PR/YA/jm7ByWJEltmT/qAGrekiT30hsr3wZeX1X/m2Rf4NQk76J32XIl8LyqugOgqi5L8j5695FVt86fV9XXpnqTqvpOklOBvwEOpvdbm3+f5BfARsC1wF/1bXJkl2HCFVV1wno7akmSRihV090qJD30nL/LQfX8LXYcdQxJ62ib5WeOG+qShgAAC65JREFUOoJGLMmBVfUbV2UeKrzEKUmS1BgLNEmSpMZYoEmSJDXGAk2SJKkxFmiSJEmNsUCTJElqjAWaJElSYyzQJEmSGuOTBLRB2fLDJ7HNAQeMOoYkSQN5Bk2SJKkxFmiSJEmNsUCTJElqjAWaJElSYyzQJEmSGuNvcWqDcs+b/oy7F5w66hiSOttfe/GoI0hN8gyaJElSYyzQJEmSGmOBJkmS1BgLNEmSpMZYoEmSJDXGAk2SJKkxFmiSJEmNsUCTJElqjAWaJElSYyzQNFCS1UlWJlmW5OtJPp5k8772Y5NUkn0mbXd2kjcP2O9fJ7k/yc6Tll+Z5Fvd+61M8t4k8/raK8lNSZYnWZXkE0meuD6PWZKkUbNA0zCOqKqnAU8CFgDH9LUdB1zW/TuUruA6BrgSOHaKVU7o3u9ZwCHAYZPa96mqPYDdgS8BX06yy7DvL0lS6yzQtCY2AR4O/BAgyW7ALsDRwKIkWw65nwOAu4C3AMf2nyHrV1U/Ar4K7DxN+wNV9SHgYuANa3AckiQ1zQJNw1iSZBlwJ/AAcG63/DjgnKr6DnA58Ioh93cccFZV3QB8H3jBVCsleRTwVOCiGfZ3Db2ze5IkPSRYoGkYE5c4twNWA6ckmU/vzNm/duucxRCXOZNsCxwIfGLAdu9NcjNwG/D5qvr6TLsd8H4nJrl9Yrroh3fOFFGSpJGbP+oAGh9VdV+S84H3AEuBrYCLk0CvSHp0kidX1c0DdvNqeuPuxm67jYBtk2xbVd/v1jmhqi5IsgewNMklVfX5Aft8FjDle1bVYmDxxPx5u+1ZwxyrJEmj5Bk0ran9gJX0znq9uaoWdtPO9Aqhmc6iHQcc1rfdY4ELgaMmr1hVy4G/BN6drprrl2RektcCBwEfXKejkiSpIRZoGsaS7s9e3Az8DnACsD9w3qT1PgYclWSTbv4d/ZcXk5wM7ABcOsV20xV2HwQ2B17Wt2xpkuXArV2O51TVt9b24CRJak2qvOKjDcd5u+1Z+y7YdtQxJHW2v/biUUfQmEpyYFV9cdQ5Zotn0CRJkhpjgSZJktQYCzRJkqTGWKBJkiQ1xgJNkiSpMRZokiRJjbFAkyRJaowFmiRJUmN8Fqc2KFud/ndsf8ABo44hSdJAnkGTJElqjAWaJElSYyzQJEmSGmOBJkmS1BgLNEmSpMZYoEmSJDXGAk2SJKkxFmiSJEmNsUCTJElqjAWaJElSYyzQJEmSGmOBJkmS1BgLNEmSpMZYoEmSJDXGAk2SJKkxFmiSJEmNSVWNOoM0Z5JcALx/1DnWwqHA+aMOsZbGNfu45obxzT6uuWF8s49rboA3VtWiUYeYLRZo2qAkub2qHjPqHGtqXHPD+GYf19wwvtnHNTeMb/ZxzQ3jnX0YXuKUJElqjAWaJElSYyzQtKFZPOoAa2lcc8P4Zh/X3DC+2cc1N4xv9nHNDeOdfUbegyZJktQYz6BJkiQ1xgJNkiSpMRZoGktJdk3ylSSrknw1yZOmWOfYJMv6pu8l+VRf+4uT3Jrkv5J8KsmWw7SNMneSpyS5qst2c5Kzkjysb9tKclPftvusj9zrKfvCJPdPan9837at9vkLJ7V9J8n1fduOus/nJVmc5JYky5NckeQJfe2tjvNpc4/BOB+UveVxPij3OIzzU7vxcGuSM5Ns0tc+5+N81lWVk9PYTcDlwDHd68OArw6xzc3Aod3rRwB3Abt386cD75mprYHcuwJ7dK83ApYA7+hbt4CtGu3zhcA906zXbJ9P0XYRcFIrfQ4sAq4BNu7m/wI4d6Z+HXWfz5C76XE+Q/Zmx/mg3GMwzl/brbcJEOAM4K2jHOezPY08gJPTmk7ADsCPgPndfIA7gScM2GYv4Lt9H0yHA1/oa38icPtMbaPOPUX7W4Cz++Zn5UN0PfX5oC+usehz4NHAvcAOrfQ5cAiwDNiiW+cfgMWtj/NBuVsf5zP0ebPjfNg+b3Scnw68rW/+ZcDyUY3zuZi8xKlx9Fjgjqq6D6B6/+tuA3YasM1xwDlV9ctufifg233tq4FHJZk/Q9uocz8oyebA8cBnJjVdluTG7lLG5uuYecL6yr55dwnj+iRvT7JRt3ws+hw4BvhcVX130vJR9vmFwJX0vtTuAPYH3t61tTzOB+V+UKPjfKbsrY7zofqcNsf5dcBLkmyZZGPg5fSKYRjNOJ91Fmh6yOs+SF4BnDnqLGtiUO7u3oslwCVV9em+pp2r6pnAs4HtgffMRdYp8k2V/Q5gx6p6FvACYB/gpBHEm9YMfR7gNVO0jbrP9wSeDOxI78zHZcCH5jjD2pgxd8PjfFD2lsf5MH3e6jg/G/gC8KVuWgXcN8cZ5pQFmsbR/9D3E1D3gbITvZ+6pnI4sKKqbulbdhuwc9/8Qn71U9ygtlHnpvvpcQm9L4I/7m+rqtu6f38KfIDel8P6sM7Zq+oXEz+RV9UPgLP68jXd553nAZsBF/cvbKDPjwYur6p7quoB4KPA87u2lsf5oNytj/Npszc+zgf2eafJcV4976iqp1fVs4FbgBVd8yjG+ayzQNPY6T78rgeO6hYdSu+egm9Ms8lx/OZPg18AnpFk927+DcAnh2gbae7uQ+yTwA+A13WXAybatk7y8O71POAI4IZ1zb0es+/QfemSZFN695BM5Gu2zye1nV1V908saKTP/xvYr+832l5M75ccoO1xPm3uMRjng7K3PM4HjZUJTY7zJJsl2bp7vR3wp/TuoYMRjPM5sb5uZnNymssJ2A24mt5p7q8BT+mWfwR4yaT1fgxsMcU+XgLcCnwDuABYMEzbKHMDR9K7WfdGejf7LgPe37XtDSzv2lYA5wDbtNLn9L6obu7L98/Apq33ede2APgp8LhJy0fe58Cm9H6j7etdlkv6c7Y6zgflbn2cz5C92XE+xFhpeZz/Vpd7Rffv6yftY87H+WxPPupJkiSpMV7ilCRJaowFmiRJUmMs0CRJkhpjgSZJktQYCzRJkqTGWKBJ0ixIsjrJyiTLktyS5I0NZFqU5PdGnUPSzCzQJGn2HFFVTwP+AHh3kj2G3bDv+Y3r0yLAAk0aAxZokjTLqurbwErgt5O8Osk13YO0r0ryVIAkxyS5Isn5SW4CfjfJjkn+PclNSZYneWe37hZJzkhybbf8wxN/HT7JlUlOTbI0yTeTfKhb/iJ6f7Dzrd1ZveOTPLJ7z+uSrEhyeveX4kmycZIPJFmV5D+TnJbkyoljmu44JK0fzT/NXZLGXZKnALsDdwMnA79fVb9Isg/wceBJ3ap7AU+vqpXddlfQe1D4Yd389t16pwFLq+q13bMLz6D3vMqJB1g/nt4zFjcGbkmyd1V9LslngWVV9Y/d/jYDDq6qn3Rn7D4DvJzeo3BeB+zal+1zfcfzHOCVA45D0jqyQJOk2bMkyb3Az4DXAH8IPBW4pldXAbBNkod1r7/SV5w9Angu8MKJFavq7u7lImDvJCd28w8DHnx2IrCkeg+Dvi/JMnoF29VT5JsHnJLkuUCAHeg9puiTwP7Av1XVL7s8HwWO77Y7ZLrjqKp7h+0cSdOzQJOk2XNEVS2bmEmyF/DRqnrb5BW7QucnQ+43wKFVtWqa9p/3vb6f6T/rT6RXlO1VVT9PshjYbJp1+58LGKY5Dknrh/egSdLc+SxwVJKdAJLMS7LnVCtW1U+Aq4CTJpb1XeK8ADg5yfxu+dZJnjDE+/+I3gOxJ2wN3NkVZ48EDu9ruxx4VXcv2sbA0WtzHJLWjgWaJM2RqloK/Anw6SQ3AiuAVwzY5NXAnt0N/MuAN3XLTwDuBZYlWQ5cBiwcIsI5wMuT3JDkeOCfgL2SrOjaLu1b91+A1cAtwJeBbwL3rOVxSFpDqaqZ15IkbXCSbFFVP+7OoH0MuK6qThl1LmlD4D1okqTpXJpkU3r3pf0H8L4R55E2GJ5BkyRJaoz3oEmSJDXGAk2SJKkxFmiSJEmNsUCTJElqjAWaJElSYyzQJEmSGmOBJkmS1Jj/B/y39hZjOd1nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 480x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "d3['PCT_NAVIGO'] = d3['NAVIGO']/d3['TOTAL']\n",
    "df = d3.nlargest(10, 'PCT_NAVIGO')[['STOP_NAME', 'PCT_NAVIGO']]\n",
    "\n",
    "# Figure\n",
    "plt.figure(figsize=(6,6), dpi= 80)\n",
    "\n",
    "# Data\n",
    "stops = df.STOP_NAME.tolist()\n",
    "n_stops = len(stops)\n",
    "y_pos = np.arange(n_stops)\n",
    "percentage = df['PCT_NAVIGO'].tolist()\n",
    "\n",
    "# Colors\n",
    "colors=['#ea3546', '#ed2d62', '#e92f7f', '#df3b9a', '#ce4ab3', '#ce4ab3', '#b65ac9', '#9769da', '#6f75e7', '#2f80ed']\n",
    "colors.reverse()\n",
    "\n",
    "plt.barh(y_pos, percentage, align='center', color=colors)\n",
    "\n",
    "\n",
    "# Style\n",
    "\n",
    "# Title\n",
    "plt.title('Stations with the highest proportion of NAVIGO checkins', fontsize=15)\n",
    "# Labels\n",
    "plt.xlabel(\"Percentage\")\n",
    "plt.ylabel(\"Station\")\n",
    "plt.yticks(ticks=range(n_stops), labels=stops)\n",
    "# Spines \n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)\n",
    "# Invert y axis\n",
    "plt.gca().invert_yaxis()\n",
    "plt.xlim(0.7, 0.9) \n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Here, we see that the stations where the % of NAVIGO checkins is the highest are those where there is a high concentration of office buildings. \n",
    "\n",
    "> More than 85% of the traffic at ESPLANADE DE LA DEFENSE comes from NAVIGO checkins. We will look into the traffic at ESPLANADE DE LA DEFENSE further, and compare it to that of NOTRE-DAME-DES-CHAMPS."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.D.d. Plot of yearly traffic: ESPLANADE DE LA DEFENSE vs. NOTRE-DAME-DES-CHAMPS <a name=\"3Dd\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Data\n",
    "stations = ['ESPLANADE DE LA DEFENSE', 'NOTRE-DAME-DES-CHAMPS']\n",
    "\n",
    "df = metro_nb.loc[metro_nb['STOP_NAME'].isin(stations), ['DAY','STOP_NAME', 'NB_CHECKINS']]\n",
    "df = df.pivot_table(values='NB_CHECKINS', index=['DAY'], columns = ['STOP_NAME'], aggfunc=np.sum)\n",
    "df.reset_index(inplace=True)\n",
    "\n",
    "# Colors\n",
    "colors = ['#2F80ED', '#EA3546']\n",
    "\n",
    "# Figure\n",
    "fig, ax = plt.subplots(1,1,figsize=(16, 7))   \n",
    "\n",
    "# Plot\n",
    "plt.plot(df.DAY, df['ESPLANADE DE LA DEFENSE'].rolling(7).mean(), color=colors[0], linewidth=1.5)\n",
    "plt.plot(df.DAY, df['NOTRE-DAME-DES-CHAMPS'].rolling(7).mean(), color=colors[1], linewidth=1.5)\n",
    "\n",
    "# Style\n",
    "\n",
    "# Title\n",
    "plt.title('# Checkins per Station (ESPLANADE DE LA DEFENSE vs. NOTRE-DAME-DES-CHAMPS)', fontsize=15)\n",
    "# Grid\n",
    "plt.grid(color='black', alpha=0.3, linestyle=\"--\", lw=0.5)\n",
    "# Spines \n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)  \n",
    "# Labels\n",
    "plt.xlabel(\"Day\")\n",
    "plt.ylabel(\"# Checkins\")\n",
    "plt.legend({group:col for group, col in zip(stations, colors)})\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> We see how dramatically the public holidays of May affected the traffic at Esplanade de la Défense. This station is almost exclusively frequented by people who comute to work (>85%), and therefore more affected by national holidays than other stations. Comparatively, NOTRE-DAME-DES-CHAMPS's traffis is more diverse, as IMAGINE R checkins represent less than half of all checkins."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.E. How does traffic fluctuate along the day? <a name=\"3E\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.E.a. Hourly traffic at NOTRE-DAME-DES-CHAMPS <a name=\"3Ea\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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R85sDPf595EbgWBE5IdxOY8wrwCRsHR8ACrB1eCVMD3sV9hp3i4jsIyK/FZEy7PVuwY7+T+mH7aEEgnwN2LW4H6zF1mU7dq7lQmNMaZh0D9P1+gcHJOnPiG64614C/NMYExjNW4od9fpKN3k8g53TfSr2Wr9sjOnutwrW/TC0Hvd5dQgdnY703SFcPdaHKefwwE5jTKsxZh62c+EnWHf7ucBrIvIfEdjTl99ad7a8EyZtrM//k1i9VWN/w7cDv4fIzkk/+FvI978Ch4pIah+eVwH+Tu8cAbxoOruFh9oQmB7zkIhUYDtEW4A5dL6fLPP+nucdMwn73vBgD+UfjR2Z7DbNAO9lp3j1aQ86X59i32kO89IcDrxtgoLkGWPexMYXCNiQip23+nhI/suwjf2jQ7Z3OvcDeM/p6Vke6W+qBNuwDrzv/R3YzeC7Jod6Co7FNryDA0AtBWaLyKgwx9/i/f2tCTO9waPXZ6PiH9q4VaJNqzHmrdAP9oEdzCiCbuhBbMP2XPeVcHmF437gOBGZ6D0Qj6NnVx2wL/+9NTbBjuwE04x1UQLYB/uiczd7H5ot2N7UdPa6HUda1pnYUYEuLwf9tA+sO9FbWDepMrHzjXpzu8nC1iEcgUbfNOzoxkJjTCBSaAUwQkSyujk2mgReJCJtsIMNfBWq4U3dpP0sjOYDaaux56cvZT+JbcxdiJ3b1yeMnRv1Bj3MvTXG7DbGLDPGfAsbZfIGYBbWFS+YPXTWSDgWY7VzC/Yl9HDsb2rA19YY8zn2Bf8yCb+0VQXWlbA7xmPr0NNLXXcEOjjOxY7IPChByzYFsS3M9S8FO9+dzr/3UPe27hgTyNvL5xDgQOBpERkmdvmNddh7RdgXR2PnZz6BnfYxl94je34cph5bvH0XhtSjt3tmcD1C780N3TwjQu1/zxhzozFmDjDVq2tgaZHu7Kmgb7+17mzpNBVgkM5/oHOhGDsieYUJme7RyznpK9vDfE/Dji5H+rwKEMnzd2RomV5DtyN6tNdJ8RTWRfan2DnLh2PdmbOCjtsNPMbeqNsLse7TPbnPFnh/e3q+Lqb/97JCbOT9lpDPRPaer5FYj65QgrcVYs9x6DkNfA99Pwp37vvznhPuWR7xs9NrzJ+H7UTP8H4jmdhR93O9KTqDReh9Zx62wftc0O/3WWwbaG6Y45tD/oYjkmej4hO6FJDiF5XAvmG2F2F7pWFvSPjQObj70LWHMaKeRWPMq2KXmFmIvdltoeuIZijV2Mb4QKjBc7/C9uiHEniJjLSs72NHk14QkRN66ZGNCK83eaH3gnGEZ+tTIrJfD/nvxLp7heOzcC+tHiuw0VRPJrJe/4HwFrY3+VQGZ45vB8aYFhFZ7ZX9497SBx13l9jgaj8Rka3GmNv7WPRN2JfEI3pLaIwxInILdkSoGNu4DjAMe43D4nVOnAF8zxhzT9D2aHac3obVe7h5uq8CXxGRfBMyN9mz4T+ANcaYXtedDcM6YwOQvSUi72I9HX5C+EBP3bGFoFFJuu8ICmUOsDWokyTQgLqNvXP+ApwqdnmbcNdpKXYUpYW+dYSFspzO9ehpBBLoeNk9CXuNBoQxZpOIPM5eDXRnzwrgIhE52BizbqDlBjEY5//jHu6XXQhzTvpK6PN3X+xIaRX2pT2S51WHORGUtzW0TG+EOLjT6gDsEjOnGWOeC0qXTVf+CKwSkcnYaS9/Cu0MCCHwDBtFGP1G4V4W6Gz+Y5h9gfK2YjslQhkRkraFrtcnEGwzVGddzn0/33O6PMuNMZtF5BPs8ytcvYI5BdswP5vwS9udSjfzsaOJ14g+EetmHyDw+3276xGU0L9lAHt8Nir+oiO3il+8gX0pCI68eDh2/lFgbcBy7++BQWnGYV/AB8ID2J7/SB6IYIOHzB3IKKOx0W5fx87Z6zJSEDRC8jL2vBR1nxtgXX0DUWyfF5Eh/bUtjK3txpjXsW64OfQ8MlaKDTjR1zJWYh80P5cwQY1EZLp3rQeM505+L/BdCROMxevJDXX1iia/xgZ5ujBM2SnSffCnn2LdQm8Vka/1pUBjzHJs0ItODWoRSfd6rUOZ7P0NHQWYgJ1X3R2Z2OdIR6PNu55nhqRr9vb1+TdkjNmODdb2Q/auURjgTmAocE2YQ7+JrVd/1y8OtuHf2Je7hWKDvkV6XHPI77zXQEdio7B/Fc8l1XNNn49d6unEkM/52FGecIFRwL7g/QUbcK5fa7t69ajuxjOhJ34KjMbOr4+YHs7vZDx99mDPn7GjTXeEGykSGyk4NIBRb/b4fv4jOSf9ILQBcjbWZbatD8+rvvAv4Ish5z/UhsDvO/h+Mh7rVdIJYyPcl2Kf5/thR1174jVsFPYu92GPgd7LXsYGkHq7B0+ef2FdvwOeGYgNOtnxvPfeR97Gc7kOYi52GarXeqlngL6+55QCo0UkNIjkr4FzROTE0ANEJEtETvK+lmAbe6G/kRPpOfhatLkOez7v8WycjHWjvzWMXbcBR4rIxH6UM4Gen42Kj+jIreIXt2NHQJ4XkV9ie29vxq4p9hcAY0y5iLwF3CAiDdgHz48YeG/ZQ1hXrjR6nqMT4DrsQ+lVEbkN2wP8BaDahFnepQeuAl4WkXbsS9hu7EP5P4D/McZ8hHUJ/jp2IfKbsJFtD8S69f4qODNjTLX3IrwS6y73JdPPZS7ELoXwPDZi8kfYB/0V2J7m9T0cupquD/9IWYB9YXxLRO7AjowNwTbav4UNMLa5n3mH8mPsKOZqr6zV3vYjsaOCNxP5S0MoE0QkNDKjMXYOOcaY5SJyO3C/2IifT2Jd8Yqx0bc30b073XexvfoPiMgOY8zzfbDr5+ydmxZgKPCRiDyEPfe7sCMJ12AbBaGjS4fRg2u0MWaXiPwL+KmI1GJfvq728g3ucNng/f2BiLwC1Jrw81e74xbsuSrC/hYD5b8tIv+DnSs+BjtS1owdgbkUu/zTk2Hy6w+/wury+9gR3ACjwlx/sMs/9eTWFnxsKtZl8VTsaMuL2GBMYOfYjQf+2xizIjQDEbkG++L4h9B93oh1OLe7cEwVkdARrSbTSyyDkGMzsJ1d84EvYQMF/TMkbW435+tjY+ek/sRzA34Ue+/JxUb0/TI28Fm3GGMaRWQe1uVwtYjchV1OqxAbHXcBe91TI2Wwzn9PRHROxC5V8yCwfwQdEKd5z5h/enl9kc7zhyN5XvWFX2MDKj3t3Q9HY+87wbEsNmA7tW8TkZ9ggxFeR/fLJ92PvTe8ZozZ0E0aAIwxNWKXtrtJ7IoMz2Cfc/8BXGeMqRjgvexa4E3g7yLyAHYEdgz2vC72tPMg9ln0tIhch23MX4d1S24PKuNn2HejB7H3tOnYqSN/MDYKcST09T1nNbajZjrW2ynAXdio9M94v6cXsffYQ7D32OUisgb7+3q0m9/IMqxHRU5/31G6oVhEarD3nYnY3+EXgR8bYwLP+BJsIK5bjTGdOoJEpBQb1Go+4ZeTC4uIDPfKW91bWsUnTBxEtdKPGx/szb2qm32LCYqW7G37AnapiAas2+6jdI1qegDW1awe27P4FcJHS34rTJkLCYluG7RvFbCqD3WbgX0Y7vY+b+AtXk6EUZ29bUdiGzK1Xp0+xDb0hwalGY9tlHzunZt3gfnevgmERCf10n/m5ZsRWu9wx4SeN+xD/g/eOW7APpifBqb3cl4Owz6U9wvZ3hHps5fjR2JH1j7B9ph/jm1knxMmbb+iJQcdn4l9EVzr1bEB21C6HMjq6Vp2pye6j7TaJQIkdnQn0KBsxnYi3EpQVORw5w3rIrgC2yA+IpyNhIm8i+0MWh98zjx9XI11Fd2GfbH8GNvLPTbM77MdmNDLeT0AO2pR7+nwKkLuBVjXuF9h3ePa6SGaMN3/nu8jJKpo0L4ve+dot3dd38TOx5NuyogkWnI4DTyA7dzKDTrv3WlgbHd1DHNsM3aqxrPYJVBSgtL9ztNMd9HaA1FUR9FL9GIvfV+iJX/cSx1Cj23E/pYfAY7r5tp2V9bXvDRHYV/GN7L3XrQG7x4Y4W/9AO9alWNdPHdgO25ODLGli868fSvw7t2DeP57Oiaic4J1Ud4DDOshr9leead6emvwztMlYdL2+Lyih2dsD2W/59m4FjsiW0VQtGSsu/mbnpYCrrVhrxV7o+Z+sw/a+LZXjz3YztvH8FZtYID3MmyH5Z+xHfCBe+u9BN0LsI3CNV75pdhG4UfAr0PsnIft7G/2rs9NQFrQ/l7PPX1/z3kf+EmY7SlYT5jXsc+hJi/tz7Adpud6thzTTb6BiNDzQrYPNFpy6H3nYeDYkLTrgWd6yOsF4P2QbQG3/LC6wjaYPwcy+2q7fgbnI96FUpSkwet1q8A2Iu73255Ex5uP+LAx5pZeEysJg4j8AjjcGNPbOreKosQBnkdGuzFmUQ9pZmM72aYbO6c8YRGRS7ANzdEmzFrXiYCI7I9t3F5sjHkwivn2+T1HRC4HvmGMmRYtO1xERP6GXaHjUr9tUcKjbslK0uDNnzkI+AF2hGeJvxY5w43ALSJyh+lf4B4lzhCRXKwL7lf9tkVRlIg5mu7n/zqD2CjkU7DTlBYnUsPWc2PfApRh3byvwXoW/CVK+Q/kPec+4GoROcXYqPtKCGKjT5/KwGO/KDFEG7dKMnEotse6DPi6ie7cj2Tmz9j5J2Ow53ZQEbsuYHfrwRrTeyANpSv7AdebMPOnFEWJT4wx0VhbOhG4FhvM6590nv+eCBisO+9orGvySuDKKDbQ+/2eY4yp9wIf5kbJlj7jBXDraT3wNuOvy+lorLvyZz7aoPSCuiUripLQiMgmuo/oXGaMmTB41iiKoiiK0h9E5BQ6L+MTyk+MMf1d21lJErRxqyhKQiMi07HBosKxx0Sw/IqiKIqiKP7iuVWHWws4QIUxpnKw7FESE6cat3/84x/NlCl7vXIaGhrIyenTknaKklCoxhWXUX0rrqMaV1xG9a3EihNOOOGb3QVLc2rO7ZQpUzj++OM7vpeWljJ1ak8dQIqS2KjGFZdRfSuuoxpXXEb1rcSQjd3tSBlMKwab4cOH+22CosQU1bjiMqpvxXVU44rLqL4VP3C6cdvaqquSKG6jGldcRvWtuI5qXHEZ1bfiB043bmtrE2bpM0XpF6pxxWVU34rrqMYVl1F9K37g1JzbUMaP7251EEVxA9W44jKqb8V1VOOKy6i+o0dLSwvl5eU0NTX5bcqgkpWVxdixY0lPT4/4GKcbt2VlZTqRXXEa1bjiMqpvxXVU44rLqL6jR3l5Ofn5+UyYMAER8ducQcEYQ3V1NeXl5ey///4RH+e0W3JGRobfJihKTFGNKy6j+lZcRzWuuIzqO3o0NTVRUFCQNA1bABGhoKCgz6PVTjduCwoK/DZBUWKKalxxGdW34jqqccVlVN/RJZkatgH6U2enG7eVlZV+m6AoMUU1rriM6ltxHdW44jKqb8UPnG7cFhYW+m2CosQU1bjiMqpvxXVU44rLqL7dIjU1lZkzZ3LwwQdzyCGHcNttt9He3g7AihUrOOOMMwBYvHgxl156KQDXXnstY8aMYebMmcycOZOrr74agNmzZzN16lQOOeQQZs2aRWlpadTsdDqgVLJFFFOSD9W44jKqb8V1VOOKy6i+3SI7O5u1a9cCsH37ds4//3xqa2u57rrrejzu8ssv58orr+yy/ZFHHuGwww7jvvvu47/+67946qmnomKn0yO3dXV1fpugKDFFNa64jOpbcR3VuOIyqm932Xfffbnvvvu48847McYMKK/jjz+ejz/+OEqWOT5yq+trKa6jGldcRvWtuI5qXHEZ1Xds+NVz9ZRubYtqnlNHpnLVl3L7dMzEiRNpa2tj+/btPaa74447ePjhhwH45S9/yamnntpp//Lly5k+fXrfDO4Bp0duy8rK/DZBUWKKalxxGdW34jqqccVlVN8KWLfktWvXsnbt2k4N2wULFjBz5kxWr17NrbfeGrXynB65zcrK8tsERYkpqnHFZVTfiuuoxhWXUX3Hhr6OsMaKTz75hNTUVPbdd1/Wr1/f5+MDc26jjdMjt8OGDfPbBEWJKapxxWVU372zu7WZ5vbouqcpg4dqXHEZ1be77Nixg+985ztceumlcbf+rtON28fmNfYAACAASURBVK1bt/ptgqLEFNW44jKq796Zs3IpP1n3qt9mKP1ENa64jOrbLRobGzuWAjrllFOYM2cOP/vZz7qka21tJTMz0wcLLU67JY8YMcJvExQlpqjGFZdRffdMWcMuSut2kp3q9KPcaVTjisuovt2ira17L6HZs2cze/ZsANatW8fkyZMBu85tOFasWBFl6/bi9MhtfX293yYoSkxRjSsuo/rumVVV5QB8VLeT9gEuxaD4g2pccRnVd/Jx2mmn8d5777FgwQLfbHC6u7ehocFvExQlpqjGFZdRfffM6mrbuG1oa+Wzhlom5A712SKlr6jGFZdRfScfzz77rN8muD1yq+trKa6jGldcRvXdPcYYVlWXMyYrH4ANu6t9tkjpD6pxxWVU34ofON241fW1FNdRjSsuo/runrKGWsobd7Nogl34Xhu3iYlqXHEZ1bfiB043bnNycvw2QVFiimpccRnVd/es8lySTx85iVFZedq4TVBU44rLqL4VP3C6cZubGx+LHCtKrFCNKy6j+u6e1dXlFGZkMzVvOMX5w7Vxm6CoxhWXUX0rfuB043bHjh1+m6AoMUU1rriM6js8xhhWVZUzq2AsIkJxfgEf1e2kzbT7bZrSR1Tjisuovt0iLy8PsEv9nHTSSUydOpXJkydzww03YLyI/YsXL+bSSy/tdNzs2bN56623WLRoEffee2+nfU888QSnnXZaVO10unE7cuRIv01QlJiiGldcRvUdnrKGWiqadnNs4VgAivMLaGpvo6yh1mfLlL6iGldcRvXtHo2NjZx55plcffXVlJaW8u6777JmzRruvvvuXo8tKSlh6dKlnbYtXbqUkpKSqNrodOO2pqbGbxMUJaaoxhWXUX2HZ2X1ZgCOLRgH2MYtaFCpREQ1rriM6ts9Hn30UWbNmsWcOXMAO6/6zjvv5Oabb+712JNPPpkNGzZQWVkJ2HWQX3rpJc4666yo2uj0OrdNTU1+m6AoMUU1rriM6js8q6vKGZGRw5S8fQCYmjccsI3b00dO8tM0pY+oxhWXUX3Hhrrbf0/rR59ENc+0KRPJ++F3e023bt06Dj300E7bJk2aRF1dHbW11nto2bJlrFq1qmP/xx9/DEBqairnnnsujz32GD/4wQ9Yvnw5s2fPZsiQIVGsieMjt7q+luI6qnHFZVTfXQmsbzurcAwiAsCQ9EzGZOVTununz9YpfUU1rriM6js5mTdvHmvXru34HHbYYR37gl2TY+GSDI6P3JaVlTF16lS/zVCUmKEaV1xG9d2VTQ272NJUx7EFYztt14jJiYlqXHEZ1XdsiGSENVYcdNBBvPrqq522ffLJJ+Tl5UU0AnvMMcdQWVnZMVc3dA5uNHB65DYQ1UtRXEU1rriM6rsrK6vs+raB+bYBivML2KgRkxMO1bjiMqpv91iwYAGrVq3ipZdeAmyAqcsuu4yrrroqouNFhHnz5nHhhRdy2mmnkZWVFXUbnW7cxuKEKUo8oRpXXEb13ZXV1eXsm5nDZG++bYBAxORN9bt8skzpD6pxxWVU3+7Q2tpKZmYm2dnZPPnkk9x4441MnTqV6dOnc/jhh3dZ/qcnSkpKePfdd2PikgyOuyVXVVVRUFDgtxmKEjNU44rLqL470zHf1lvfNpjgiMmTQhq+SvyiGldcRvXtDuvWrWPSJBuwcPr06axYsSJsuoULF7Jw4cJO20LTzpw5s2Nd3Fjg9MjtqFGj/DZBUWKKalxxGdV3Zz5t2EVlmPm2AFPzAxGTNahUIqEaV1xG9e0G99xzDyUlJdx4441+mxIRTjduq6s1uIbiNqpxxWVU351ZWWXXt50VpnGbl5bBuOx8NtTpOUskVOOKy6i+3eA73/kOH374YcfatvGO043b5uZmv01QlJiiGldcRvXdmdXV5RSFmW8boDi/QCMmJxiqccVlVN+KHzjduNX1tRTXUY0rLqP63osxhtXdzLcNYCMmf05ru0ZMThRU44rLqL4VP3C6cVtWVua3CYoSU1TjisuovvfySX0NlU31YefbBijOL6C5vY1PG2oG0TJlIKjGFZdRfSt+4HTjNpLFhBUlkVGNKy6j+t7Lymq7vu2swu4btxpUKvFQjSsuo/pW/MDpxm1amtMrHSmKalxxGtX3XlZXlzMyM5cDcrtf5mdKXqBxq/NuEwXVuOIyqm+3yMvLA+yyQCeddBJTp05l8uTJ3HDDDRhj2LRpE2PHjqU9ZGrMzJkzeeONNygtLWX27NnMnDmTAw88kIsvvjgmdjrduN25U3uvFbdRjSsuo/q2GGNYXVXOrMLu59uCjZi8X/YQbdwmEKpxxWVU3+7R2NjImWeeydVXX01paSnvvvsua9as4e6772bChAnst99+rFy5siP9hg0b2L17N0ceeSSXXXYZl19+OWvXrmX9+vV8//vfj4mNTjdux4wZ47cJihJTVOOKy6i+Lf+ur2HrnvqwSwCFohGTEwvVuOIyqm/3ePTRR5k1a1bHskA5OTnceeed3HzzzQCUlJSwdOnSjvRLly5l/vz5AFRWVjJ27N7n2PTp02Nio9P+Atu2besYQlcUF1GNKy6j+ras8ubb9hRMKkBx/nD+saOMlvY20lNSY22aMkBU44rLqL5jxLZ7oemT6OaZNRGKvt1rsnXr1nHooYd22jZp0iTq6uqora1l7ty5zJw5k9/97nekpaWxbNkyHn/8cQAuv/xyTjrpJI455hjmzJnDokWLGDZsWHTrgeMjt6E+34riGqpxxWVU35ZVVZsZlZXLpNzeXwKK8wtoMe18Ur9rECxTBopqXHEZ1XfyUVRUxLRp03j55ZdZu3YtaWlpTJs2DYBFixaxfv16zjvvPFasWMFRRx3Fnj17om6D0yO36g6huI5qXHEZ1ffe9W2PKxzX43zbAMX5BYANKhWInqzEL6pxxWVU3zEighHWWHHQQQfx6quvdtr2ySefkJeX1xEdO+CaXFRURElJSae0o0eP5qKLLuKiiy5i2rRpfPDBB11GggeK0yO3mzdv9tsERYkpqnHFZVTf8HH952zb0xDRfFuwEZMFjZicKKjGFZdRfbvHggULWLVqFS+99BJgA0xddtllXHXVVR1pzjnnHJ555hmWLVvWMd8W4LnnnqOlpQWArVu3Ul1dHZMOkJg2bkXkARHZLiIfBG27VkQqRGSt9zm9m2O/JCKlIvKxiFzdn/Jj4cetKPGEalxxGdU3rK6KfL4tQE5aOuNzhmrjNkFQjSsuo/p2h9bWVjIzM8nOzubJJ5/kxhtvZOrUqUyfPp3DDz+cSy+9tCPtsGHDOProoykqKmLixIkd21944QWmTZvGIYccwqmnnsott9zCyJEjo25rrN2SFwN3An8K2X6HMebW7g4SkVTgLuCLQDnwLxF5yhjzYawMVRRFUZR4Y2V1OaOycpkYwXzbABoxWVEURYkm69atY9KkSYCNcrxixYoe0z/xxBNdtt1+++3cfvvtsTCvEzEduTXGvAr0Z5GrI4CPjTGfGGOagaXAV/qaSU1NTT+KVpTEQTWuuEyy6zsw3/bYgsjm2wYozh/Ov+traG5vi6F1SjRIdo0rbqP6doN77rmHkpISbrzxRr9NiQi/AkpdKiJfB94CrjDGfB6yfwwQ7KhfDhwZLiMRuRi4GOCSSy6hqKiIUaNGUV1dTWNjI01NTZSVlTFkyBDS0tLYuXMnY8aMYdu2bbS3tzNmzBg2b97c4TpRU1PDuHHjqKioICUlhaKiIioqKhg+fDitra3U1tYyfvx4ysrKyMjIoKCggMrKSgoLC2lqaqKurq5jf1ZWFsOGDWPr1q2MGDGC+vp6GhoaOvbn5OSQm5vLjh07GDlyJDU1NTQ1NXXsz8vLIysri6qqqo46NTc3d+zXOmmdGhsbqa6udqpOLl4nrVP/6jR06FA+/fRTp+rUl+vUOCyX7XsamJ4+hG3btkVcp6F1zbSadt7bVk5+bVNc1cnF6zSQOrW1tVFbW+tUnVy8Tlqn/tUpJyeH0tJSp+rk13VqaWmhtbWV9vZ22tvbycjIoLm5GREhNTWV1tZW0tLSuuxPSUkhJSWlY39bWxvGmLD709PTaW1t7bL/G9/4BgsXLiQ9PZ2mpiYA0tPTaWlpITXVLjnX1tbWsS10vzGmi81paWm0tLSEtTm0Tq2trZSWlna6Tj0hxpgeEwwUEZkAPG2MmeZ9LwKqAAPcAIwyxlwUcsxXgS8ZY77pfb8AONIYcyk98Oqrr5rjjz++4/vGjRuZPHly9CqjKHGGalxxmWTX94Ob3uOK91/hrZMW9skt+b1d25n96qM8cOjpnDV6SgwtVAZKsmtccRvVd/RYv349Bx54oN9m+EK4uovICZ6HcBcGPVqyMWabMabNGNMO/AHrghxKBTAu6PtYb1ufSElxOhi0oqjGFadJdn2vrN7MqKw89s8Z2qfjJucNJwXRebcJQLJrXHEb1bfiB4OuOhEZFfT1bOCDMMn+BUwWkf1FJAOYDzzV17KKior6Z6SiJAiqccVlklnfxhhWV1VwXMHYPs23BchOTWNC7lA27O5PyAtlMElmjSvuo/pW/CDWSwEtAV4DpopIuYh8A/iViLwvIu8BJwKXe2lHi8gzAMaYVuBS4HlgPfCYMWZdX8uvqOjzYK+iJBSqccVlklnfH9V9zo7mBmYVRrYEUCjFecN15DYBSGaNK+6j+lb8INbRkkuMMaOMMenGmLHGmPuNMRcYY6YbY2YYY840xlR6abcYY04POvYZY8wUY8wkY8xN/Sl/+PDh0aqKosQlqnHFZZJZ36urbUzFSNe3DaU4v4BPNGJy3JPMGlfcR/XtFjfddBMHH3wwM2bMYObMmbzxxhsAVFVVkZ6ezj333NMp/YQJE6iqqur4vmLFCs444ww2bdrE2LFjaW9v75Q+OM+B4LQzfGtrq98mKEpMUY0rLpPM+l5VXc7orDwm9HG+bYDi/AJaTTsf14UuRqDEE8msccV9VN/u8Nprr/H000/zzjvv8N577/HSSy8xbpwNj/T4449z1FFHsWTJkojymjBhAvvttx8rV67s2LZhwwZ2797NkUeGXRynTzjduK2trfXbBEWJKapxxWWSVd8d820L+7a+bTDF+QUA6poc5ySrxpXkQPXtDoHllTIzMwEoLCxk9OjRACxZsoTbbruNiooKysvLI8qvpKSEpUuXdnxfunQp8+fPj4qtfq1zOyiMHz/ebxMUJaaoxhWXSVZ9l9bttPNt++mSDHBA3j5exGQNKhXPJKvGI6Xl3XU0PLSM/J9eScqwIX6bo/QR1XdsuOaDFXxQuyOqeU4bMoJfTJvd7f45c+Zw/fXXM2XKFE455RTmzZvHCSecwObNm6msrOSII45g7ty5LFu2jCuuuKLjuBNPPLFjLdy6ujqKi4sBmDt3LjNnzuR3v/sdaWlpLFu2jMcffzwqdXF65LasrMxvExQlpqjGFZdJVn2vrrY93/2dbwuQlZrGxNxhOnIb5ySrxiPBtLWx+5e/o3nVG9Tddrff5ij9QPXtDnl5ebz99tvcd999jBgxgnnz5rF48WKWLVvG3LlzAZg/f34X1+R//OMfrF27lrVr1/LHP/6xY3tRURHTpk3j5ZdfZu3ataSlpTFt2rSo2Or0yG1GRobfJihKTFGNKy6TrPpeVVXOmKx8xucMbKSqOH84pdq4jWuSVeORsOeFFbR9/CnpX5jOnuf/wZ6Tjydz9jF+m6X0AdV3bOhphDWWpKamMnv2bGbPns306dN56KGH2LJlC1u3buWRRx4BYMuWLWzcuJHJkyf3ml/ANbmoqIiSkpKo2en0yG1BQYHfJihKTFGNKy6TjPo2xrC6upzjCvu+vm0oU/ML+KShhj1tGtQlXklGjUeCaWmh/p6HSCs+gKG/+zlpUyax++bf0l6jczgTCdW3O5SWlrJx48aO72vXrqWtrY26ujoqKirYtGkTmzZt4pprrok4sNQ555zDM888w7Jly6I23xYcb9xWVlb6bYKixBTVuOIyyajvDXU7qWpuHNB82wDF+QW0GcPH9RoxOV5JRo1HQtNfn6G9chu5l1yEZGSQ/9MrMLtqqbv9936bpvQB1bc71NXVceGFF3LQQQcxY8YMPvzwQ4488kjOPvvsTunOPffciBu3w4YN4+ijj6aoqIiJEydGzVan3ZILCwv9NkFRYopqXHGZZNT36ipvvm1hNBq3do3JDburOXjIiAHnp0SfZNR4b7TXN1D/wCOkH3oI6Uf+PwDSpkwi56LzafjD/7Ln5OPIPEHdkxMB1bc7HHrooaxZs6bXdDNmzGD9+vUAbNq0qdO+gEtzME888US0TOzA6ZHbpqYmv01QlJiiGldcJhn1vaq6nLHZ+eyXPfDIsAfk7kOqaMTkeCYZNd4bjUv/hvl8F7mXXtTJNT9n4TxSJ09k9y9+S/sudU9OBFTfih843bitq6vz2wRFiSmqccVlkk3f7d5822MLBj7fFiAzNY2JORoxOZ5JNo33RnvNLhof/jMZJ84i/eDiTvskPZ0hP7vSc0++xycLlb6g+lb8wOnGra6vpbiOalxxmWTT94bd1VQ3N0bFJTnA1PwCbdzGMcmm8d5oeHApprGJ3O8sDLs/bcokchaVsOfZl9nz6muDa5zSZ1Tfih843bjV9bUU11GNKy6TbPqOxvq2oRTnF/Bp/S6aNGJyXJJsGu+Jtq3bafzzcrLOmEPa/vt1my5n0XxSJ0+kTt2T4x7Vt+IHTjdus7Ky/DZBUWKKalxxmWTT96rqcsZl57NfztCo5VmcP5x2DBvrdN5tPJJsGu+Jhj/8LwjkfGtBj+kC7sntNbvUPTnOUX0rfuB043bYsGF+m6AoMUU1rrhMMum73RhWV5VHddQW7MgtoEGl4pRk0nhPtH5SRtPfXyL7vDNJLdq31/TWPXm+uifHOapvxQ+cbtxu3brVbxMUJaaoxhWXSSZ9b9hdzc6WJo4tHBfVfA/I24c0SdF5t3FKMmm8J+p/vxjJziLnwvkRH5OzqITUA/ZX9+Q4RvXtFjfddBMHH3wwM2bMYObMmbzxxhsAVFVVkZ6ezj337PWkWLRoEffee2+n45944glOO+20HvOKBk43bkeM0HX9FLdRjSsuk0z6XuXNt51VMCaq+WakpDIxVyMmxyvJpPHuaHl/Pc3/XEP2BeeRMizyJbAkPZ18dU+Oa1Tf7vDaa6/x9NNP88477/Dee+/x0ksvMW6c7Yx9/PHHOeqoo1iyZElH+pKSEpYuXdopj6VLl1JSUtJjXtHA6cZtfX293yYoSkxRjSsuk0z6XlVVzn7ZQ6I63zZAsUZMjluSSePhMMZQf9cDyPB9yJl/dp+PT596wF735JWvx8BCZSAku75dorKyksLCQjIzMwEoLCxk9OjRACxZsoTbbruNiooKysttR+3JJ5/Mhg0bqKysBKwWXnrpJc4666we84oGaVHLKQ5paGjw2wRFiSmqccVlkkXf7cawprqcU0dOjEn+xfnDWV65kYbWFnLS0mNShtI/kkXj3dHy+lu0vPMeef/1PSQnu1955CwqYc+KNdT9/DekLz2IlKGRj/4qsSXZ9R0rfvXzX1C6oTSqeU4tnspVP7qm2/1z5szh+uuvZ8qUKZxyyinMmzePE044gc2bN1NZWckRRxzB3LlzWbZsGVdccQWpqamce+65PPbYY/zgBz9g+fLlzJ49myFDhnSbV7RweuRW19dSXEc1rrhMsuh7/e4qdrY0cVyUg0kFKM4vwAAf138ek/yV/pMsGg+HaW+n/q4HSRkziqyzTut3PpKeTv5Pr6C9poa6O+7t/QBl0EhmfbtGXl4eb7/9Nvfddx8jRoxg3rx5LF68mGXLljF37lwA5s+f361rcsAluae8ooXTI7dlZWVMnTrVbzMUJWaoxhWXSRZ9r6oKzLeNXeMWbNCqGUN7j0SrDB7JovFw7Hnxn7R+9G/yr/9vJH1gHgXpxZPJWTifhvsfZc/Jx5F53FFRslIZCMms71jS0whrLElNTWX27NnMnj2b6dOn89BDD7Flyxa2bt3KI488AsCWLVvYuHEjkydP5phjjqGyspJ3332XNWvWdJqDGy6vhQsXRsVOp0duc3Jy/DZBUWKKalxxmWTR9+rqcsbnDGFcTmzcKSflDiNdIybHJcmi8VBMSwv19zxE6uSJZM6ZHZU8cy4634ue/Bvaa3dHJU9lYCSrvl2ktLSUjRs3dnxfu3YtbW1t1NXVUVFRwaZNm9i0aRPXXHNNx+itiDBv3jwuvPBCTjvttI51j8PlFc1Rfqcbt7m5uX6boCgxRTWuuEwy6LvdGFZXV8Rs1BYgPSWVSXn76Fq3cUgyaDwcTU8+R3tFJbnfuwhJic6raId78uc1Gj05TkhWfbtIXV0dF154IQcddBAzZszgww8/5Mgjj+TsszsHgjv33HO7uCa/++67HS7J3eV17bXXRs1Wp92Sd+zYwfDhw/02Q1FihmpccZlk0PeHtVV83tLEsTFs3IINKrW2ZntMy1D6TjJoPBTT2ETD/Y+S/oXpZBx9WFTzTi+eTM6F82l4QN2T44Fk1LerHHrooaxZs6bXdDNmzGD9+vUd32fOnIkxpl959RenR25HjhzptwmKElNU44rLJIO+A+vbxr5xW0BZwy4aWltiWo7SN5JB46E0LP0b7dU7yf3eIkQk6vnnfEPdk+OFZNS34j9ON25ramr8NkFRYopqXHGZZND36upyJuQMZWyM5tsGKM6zEZM/qlPX5HgiGTQeTHtNLY1/eoyM448ifcbBMSlD0tPJ/4nnnqzRk30l2fStxAdON26bmpr8NkFRYopqXHEZ1/Vt59uWx3S+bYDgiMlK/OC6xkNp+NNjmIZGcr+7KKblpB84mZyvz2PP319kz6o3YlqW0j3Jpu9YE+remwz0p85ON251fS3FdVTjisu4ru91tTuoadkTc5dkgIm5w8hISdXGbZzhusaDadu2g8bHnyTz9FNImzQh5uXlfON8UidNUPdkH0kmfcearKwsqqurk6qBa4yhurq6I8pypDgdUErX11JcRzWuuIzr+g7Mt51VGPvGbVpKCgfkasTkeMN1jQfT8MeHod2Qe/EFg1KeZGSQ/9MrqbnoMup+fS9DfnrloJSr7CWZ9B1rxo4dS3l5OTt27PDblEElKyuLsWP79ox0unGbl5fntwmKElNU44rLuK7v1VXl7J8zlLHZ+YNSXnH+cN76fOuglKVEhusaD9C66TOalr9A9tyvkDqqaNDKDbgnNzy4hD0nHUfmsUcOWtlK8uh7MEhPT2f//ff324yEwGm35L4OYytKoqEaV1zGZX23G8OanRWDMmoboDi/gM8aa6lrbR60MpWecVnjwdTf8xCSlUnOovmDXnYn9+TddYNefjKTLPpW4gunG7dVVVV+m6AoMUU1rriMy/oezPm2AaZ6QaU0YnL84LLGA7R8WErzK6vIXvBVUvYZNujlS0aGjZ6883Pq7rhn0MtPZpJB30r84XTjdtSoUX6boCgxRTWuuIzL+l5Z5c23HcTGbXH+cEAjJscTLms8QP1dDyD7DCX7/HN8syH9oCnkXDCXPU+/yJ7Vb/pmR7KRDPpW4g+nG7fV1foAV9xGNa64jMv6Xl1dzsTcYYwZpPm2APvnBCIm68htvOCyxgGa33ibln+tJeei80nJzfHVlpxvLiB14njqfv5rdU8eJFzXtxKfON24bW7WeUWK26jGFZdxVd9tpt3Otx3EUVuwEZMn5+2jI7dxhKsaBzDt7dTf9SApo4rIPvt0v83piJ7cvvNz6n99r9/mJAUu61uJX5xu3Or6WorrqMYVl3FV3+tqq9g1yPNtAxTnF2jjNo5wVeMAza+sonXDRnIvvgDJyPDbHMC6J2dfcB5Ny19gz5p/+W2O87isbyV+cbpxW1ZW5rcJihJTVOOKy7iqbz/m2wYoziugvHE3uzViclzgqsZNayv1v19M6qQJZH7pJL/N6UTuN79G6v77qXvyIOCqvpX4xunG7ZAhQ/w2QVFiimpccRlX9b26upxJucMYnT34a0AGgkqV6uhtXOCqxpuWv0Db5gpyL1mEpKb6bU4nJCOD/J9dSXv1Tup/fZ/f5jiNq/pW4hunG7dpaWl+m6AoMUU1rriMi/puM+2sqS73ZdQWrFsyoEGl4gQXNW6ammj448OkHXIwGcce6bc5YUk/aKrnnvy8uifHEBf1rcQ/Tjdud+7Uh7fiNqpxxWVc1PcHu6qobW32Zb4twITcoWSlpOq82zjBRY03PvYU7TuqyfveRYiI3+Z0Syf35Lp6v81xEhf1rcQ/Tjdux4wZ47cJihJTVOOKy7io75XVmwGYVehP4zZVUpicN1wbt3GCaxpvr91Nw0PLyJh1BOkzp/ltTo90uCdX7aT+Do2eHAtc07eSGDjduN22bZvfJihKTFGNKy7jor5XV5dzQO4+jMoa/Pm2ATRicvzgmsYb/vdxTF09uZcs8tuUiAh2T25+Td2To41r+lYSA6cbt+3t7X6boCgxRTWuuIxr+rbzbSuYVeDvaEZx/nC2NNVR27LHVzsUtzTetqOaxqVPkHnqiaRNnui3ORGT+y3rnrz7JnVPjjYu6VtJHJxu3Ko7hOI6qnHFZVzT9/u7drC7tZljfXJJDhAIKlVap/Ph/MYljTf88WFoayP321/325Q+IRkZ5P/0CuuerNGTo4pL+lYSB6cbt5s3b/bbBEWJKapxxWVc0/eq6sD6tuN8tWNvxGR1TfYbVzTe+lkFTU89R9bZp5M6ZpTf5vSZ9IOLyf7aV2l66jmaX3vLb3OcwRV9K4lFTBu3IvKAiGwXkQ+Ctt0iIhtE5D0R+ZuIDOvm2E0i8r6IrBWRft1phg0Lm7WiOINqXHEZ1/S9qqqcybn7MDIr11c7xucMJTslTRu3cYArGm+49yHIyCD3ovP9NqXf5H7rAs89+Q51T44SruhbSSxiPXK7GPhSyLYXgWnGKDiwuwAAIABJREFUmBnAR8A1PRx/ojFmpjHmsBjZpyiKoigxp7W9ndd2VvgWJTmYFBGm5GvEZCU6tKzfyJ4X/0nO+eeQUrCP3+b0G8kMck/+jbonK0qiEtPGrTHmVWBnyLYXjDGt3tfXgZg96WtqamKVtaLEBapxxWVc0vf7tXa+7Syf1rcNxUZM1jm3fuOCxuvvfhAZOoTsBV/125QB0+Ge/KS6J0cDF/StJB5pPpd/EbCsm30GeEFEDHCvMSZsN5qIXAxcDHDJJZdQVFTEqFGjqK6uprGxkaamJsrKyhgyZAhpaWns3LmTMWPGsG3bNtrb2xkzZgybN2/ucJ2oqalh3LhxVFRUkJKSQlFRERUVFQwfPpzW1lZqa2sZP348ZWVlZGRkUFBQQGVlJYWFhTQ1NVFXV9exPysri2HDhrF161ZGjBhBfX09DQ0NHftzcnLIzc1lx44djBw5kpqaGpqamjr25+XlkZWVRVVVVUedmpubO/ZrnbROjY2NVFdXO1UnF6+T1ql/dRo6dCiffvqpE3V6ofrfABySER91KmpNobKpjrc+/ICJI0er9nyqU1tbG7W1tYlbp82V8MbbNJx/FnlpqZSVlib+dTr7S5hXVrHzulsY+vDdfFZdlfh18un3lJOTQ2lpqVN1cvE6JWKdekKMMT0mGCgiMgF42hgzLWT7/wCHAeeYMEaIyBhjTIWI7It1Zf6+NxLcLa+++qo5/vjjO75v3LiRyZMnD7wSihKnqMYVl3FJ3/PeeIJNDbt448QL/TYFgOe3fULJm0/x7Ky5HDl8tN/mJC2JrHFjDDUX/YD2qp0M//MDSGaG3yZFjZYPNlDzzcvJ+vIc8v/ncr/NSVgSWd9KfCMiJ3TXLvQlWrKILATOABaEa9gCGGMqvL/bgb8BR/S1nJQUp4NBK4pqXHEaV/Rt59tu4dg4cUkGjZgcLySyxptXrKZ1XSm5F1/gVMMWIH1aMdkLzrXuya+/7bc5CUsi61tJXAZddSLyJeAq4ExjTEM3aXJFJD/wPzAH+CBc2p4oKioaiKmKEveoxhWXcUXf79Vupy6O5tsCjMseQk6qRkz2m0TVuGlto/73i0ndfz8yTzvFb3NiQu7FXyd1wjiNnjwAElXfSmIT66WAlgCvAVNFpFxEvgHcCeQDL3rL/NzjpR0tIs94hxYBq0TkXeBN4O/GmOf6Wn5FRUVU6qEo8YpqXHEZV/S9qiqwvm38NG5TRJiap0Gl/CZRNd70zEu0bdpM7ncWImmpfpsTEyQzg/yfXEH7jmrqf/sHv81JSBJV30piE9OAUsaYkjCb7+8m7RbgdO//T4BDBlr+8OHDB5qFosQ1qnHFZVzR96rqcibn7UORz+vbhlKcP5x/7PjMbzOSmkTUuGnaQ8N9fyJtWjEZs4/x25yYkj79QLLPP5fGhx8n86TjyDjqUDAGzB5IyfLbvLgnEfWtJD5OO8O3trb2nkhREhjVuOIyLui7tb2d16srOK5gnN+mdGFqfgFb99RT09zktylJSyJqvPEvy2nfXkXu9y5CRPw2J+bkfjvIPXlXOXz23/DxhdCqXg+9kYj6VhIfpxu3tbW1fpugKDFFNa64jAv6fnfXduraWphVGD8uyQE0qJT/JJrG2+vqaXhwKelHHUrGoQN2sEsIAu7JqQXV8Oml0LQR2hthx0N+mxb3JJq+FTdwunE7fvx4v01QlJiiGldcxgV9r64OzLcd47MlXSnOty6D2rj1j0TTeOP/Po6p3U3u9y7y25TBw7STPvp9hv630L5zDy2134LhX4FdL0LjR35bF9ckmr4VN3C6cVtWVua3CYoSU1Tjisu4oO+VVZuZkjecfTPja74twNjsIeSmprOhTt0r/SKRNN5etZOGJX8lc85s0qce4Lc5g0Pbbii/HnYshtxjqb1/JLU3LKE960xIHQbb77VzcJWwJJK+FXdwunGbkeHWumuKEopqXHGZRNd3S3sbb+zcwnFx6JIMXsTk/OE6cusjiaTx+gcfhZZWcr/9db9NGRwaP4JNl0H9O1D0XWTcNeRffRXt26uov+tRGLEQGtdD7Qq/LY1bEknfijs43bgtKCjw2wRFiSmqccVlEl3fHfNt42gJoFCm5hdo49ZHEkXjbeVbaPrrM2SddRqp4+LPxT6qGAOfPwOfXQmmHcb/Cvb5MojY6MnzzqLpiWdp3XUgZB0AOx6wc3CVLiSKvhW3cLpxW1lZ6bcJihJTVOOKyyS6vvfOt43fxm1xfgHb9zSws1lfzv0gUTRef++fIC2NnG+c77cpsaW9CSpvhW13Qs4hsP/vILu4U5KcC86D1FSaHl8O+34HWquh+jGfDI5vEkXfils43bgtLCz02wRFiSmqccVlEl3fq6rKmZo3nBGZOX6b0i3FeRpUyk8SQeOtH/2bPc//g+ySs0gtdHgkbs9m2HS5dTMu/BqMvQ5Sh3RJllI4nMw5s2lc/jztbfvBkNmw86/QvHXQTY53EkHfins43bhtatK1+xS3UY0rLpPI+m5pb+P1nVs4rjD+1rcN5kBdDshXEkHj9Xc/iAzJI+eCuX6bEjtq/wll/wltn8O4G6HwfJDuX5Gz558FjU00PfU8jLgISIEd9w+evQlCIuhbcQ+nG7d1dXV+m6AoMUU1rrhMIut77a7t1Mf5fFuAMdn55KVlsGG3Rkz2g3jXePM779G85l/kXDiflPw8v82JPqYFtt0DW34JmRNgwp2Q+4VeD0svnkz6F6bT+NiTGNkHCubC7tVQ/27sbU4g4l3fips43bjV9bUU11GNKy6TyPpeXWXn2x4Th+vbBiMiTM3TiMl+Ec8aN8ZQf9cDpIwoIPu8M/02J/q0bIeyq+Dzp2Cfs2G/X0J65G602fPPpr1yG80rX4Ph50B6kbc0UFsMjU4s4lnfirs43bjV9bUU11GNKy6TyPpeVV1OcX5BXM+3DVCcX0Cpjtz6QjxrvHnl67S+v56cb30Nycr0xYZ2Y/i0qo09rVFeS7buLfj0+9D8GYz+ERR9CyStT1lkHH8UKaOKaFzyN0jJhBHfgD2boObZ6NqawMSzvhV36dsvOcHIysry2wRFiSmqccVlElXfgfVtzx93kN+mRERxfgGPbF5H9Z5GCjKz/TYnqYhXjZu2NurvfpDU/caSdcapvtjQbgw/+ms9z33QTFoKFI9KZcbYtI7PqKEpiEjfMjVtULUEqpdYN+QxP4KM/nlXSGoq2fPOov7X99KyfiPpxbMgZwbs+F8YcgKk5vcrX5eIV30rbuP0yO2wYcP8NkFRYopqXHGZRNX3/9VsS4j5tgGK8zVisl/Eq8b3PPsKbZ+UkfvdhUha6qCXb4zhlucaeO6DZhYcmckFR2eRmSb89e09XP2Xek7/zS6+eHsNP1y2mwdXN/JOWQuNLb2M7rbugs0/gepHYejJMP62fjdsA2SdeSqSk03j0r+BCOz7bWivh6pHBpSvK8SrvhW3cXrkduvWrQwdOtRvMxQlZqjGFZdJVH0H1reN9/m2AYoDEZPrqplVmBgNcleIR42b5mbq7/sTaQdOIeOkY32x4cHVTSx5cw9fOyqTK+bkdIzQtrQZPt7exnvlrR2fVza0AJCWAlOKUpkeNLo7dh9vdLfhQ9jyC2jbDSP/E4bNiYqdKXm5ZH35VBr/8jRt3/8GqYX7w7DT4POnYdiX7OhwEhOP+lbcx+nG7YgRI/w2QVFiimpccZlE1feq6nIOzC+gMAHm2wKMzsojPy1DR259IB413viXp2nfup38H/+w726/UeCJ/9vDb19u5LTpGfwwqGELkJ4qHDgqjQNHpTHvcLttZ307H1Tsbewuf3cPy/61B4B9cuD7X3iBs8Y8QrOMwIy5lez8A6Jqb/bcM2l87Ema/vI0ud++0K6RW/tP2HYfjLvJjugmKfGob8V9nG7c1tfXM3z4cL/NUJSYoRpXXCYR9d3szbddMO5gv02JGBGhOL9AG7c+EG8ab6+rp+HBpaQf8QUyjuh9SZxo8+pHzdywvJ6jJqZx/VdySYmgYTg8N4Xjp2Rw/JQMANraDf/e0caH5bUc0H4n0/Jf55XyQ/nZmxdT35rLAfvu6jR3d3xBP+buBpE6bgwZxx1J41/+Ts7CEiRzqG3gbr8H6v4/e/cdHkW1PnD8O9uym2RDSCGhdwhSpCigCII0UZDeBEW8VhR7u3rLz2u53msDqYKFXqWKiAUpgqKgXqRIFQKEJKRnN7ubZHfP748NGCBIytbJ+TzPPiY7s2feMW+GeTOn7ALzDZVuO9QFW35L1YOqi1ubzRboECTJp2SOS2oWivn9S246NpeTm+LqBzqUCkkyx7Ix7Xigw6h2gi3H7UtWI3LziJg00e/H3nu6mOdWWmmZqOXtUWb02soVnFqNQosap2lhfQ2K0yD+Pjo1GMwbjVzsPe1kX4qTTfuL+OQnz9PdGiaFNnV1XFtPR9t6OtrU1WI2VmxKGtOYoRRt34Xjiy2Y7ugPNW+D3I1wbi5EdAKNoVLnEuqCLb+l6kHVxa1cX0tSO5njkpqFYn5fGG8bExrjbc9LMsew8NR+MgptIbF8kVoEU467s3OxL1mF4Zbu6K9p6ddj/57h4rGlVuKjNEwfZyYirApdefO+hrQZoI2ABm9AeBtqAN2aaenWzFNkepYYcvPr6T+6M393zI4AFKBJfKmZmevraByn+dOnyPpO16Jt1hj7sjUYB/VDUXSQ8CCcfgly1kLsqMqfTwgLpvyWqg9VF7fJycm0bOnfC7Qk+ZPMcUnNQjG/d2Se4RpzXMgtqXNhUilLlixu/SiYcty+Yh3C7iDiobv9etz0fDeTFlnQaWDWeDMxEZVcyMNdBOmzIO8Lz5I8dZ4HXc0yd9UoCk3jtTSN1zK0o2cNX4vDzf4UF/vOONl7xsnm34pY84vn6W5kmELbelra1tVxbX1P0Vv66a6iKISPHYrllXco3rMXw/XtIaIDRHaFzGUQ1Rv0sZU7rxAWTPktVR+qLm7Dw+U/0JK6yRyX1CzU8rvI7eLHnLOMb9Am0KFUWOnitnuIdakOZcGS48LhwL5qA4buXdE1auC34+bbPYWtxeHmw4lR1KtZyWWHilIh5XUoPA6xoz1jXpWKtWU2arihqYYbmuoBz3JEyVnui2Zm/uBbB24B0SaFxQ9EUTf6j2OE9euFdfqH2Jet8RS3ALXuhxMPQsY8qPN05c4thAVLfkvVi6qL24iIiECHIEk+JXNcUrNQy++fz4+3DZH1bUtLDIughj5MTirlZ8GS446NmxF5+ZjGDfffMYsFjy21cirbxcxxZpISK3lLavkeUt8BFKj3fxDZ2SvxKYpCozgtjeK03NHe83S3oFDwv9PFPP9JAX9dVcCH9/wxNlgJM2AaPhDbh0twnkpB16AuGGpDzaGQvRJq3g6mJK/EFiqCJb+l6qWSfT9CQ0ZGRqBDkCSfkjkuqVmo5ffOzNBa37Y0RVFIiozlkCU70KFUK8GQ48Ltxr5kNbpWLdC390+vA6db8MIqK3tPO3ltaCTXN9ZXvBHhgnMfQsorYKgDjaZ5rbC9kogwhW7NDPxtYDi/nnEye6v9ou2mYQNBq8WxYt0fb8aOBl0MpM8G4fZpfMEmGPJbqn5UXdwmJiYGOgRJ8imZ45KahVp+78g6Q+uoOGIMoTXe9rwkcwyHLFkIIQIdSrURDDletPNHXKfOYLpzmF/WtRVC8NoGG1sPF/P8gHD6ta7ETMLObDj1AmSvgujbocFbYEjwfrBXcGubMIa0N/DRDgc/nii+8L4mLoawfj2xf/oFbovV86Y2HOInguMI5G/xW4zBIBjyW6p+VF3c5ubmBjoESfIpmeOSmoVSfhe5XfyYfZZuIdgl+byW5lhyih2cK5TLd/hLMOS4fclqNAnxhPXu7pfjzdxiZ80vhdzX3ciYzsaKN1CwF05MBscxqP0sJD4Cmko8+a2i5wdE0ChOw0urrWQX/PFE1jR2KNgdONZv+mPnqF5gbAEZH4Or+vx+BUN+S9WPqotbh8MR6BAkyadkjktqFkr5/XNOGna3k+4hXNyWnlRK8o9A53jx4WMU/7QX0+jBKDrfT8OyfLeDud86GNohjEd6VbCHg3BD1nLP8jraSGg0FWr08k2g5WAyKLwxPJI8u+Af6wpwl/R40Ldshr5jO+wr1iOcLs/OigYSHvI8cc5aHrCY/S3Q+S1VT6oubuX6WpLayRyX1CyU8ntH1hkU4EZZ3EoVEOgcty9ZjRJuwjh4gM+P9dXBIt7YaKNnSz0vDQyvWBdolwXOvAwZ88HcHRpNgTD/zep8JS0TdTzVL5wdR4tZvKvwwvumMUNxp6ZTtP27P3Y2JXmWBMpZ45nduRoIdH5L1ZOqi9vk5ORAhyBJPiVzXFKzUMrvnSXjbWsaKtHNMkgkhIUTLWdM9qtA5rjrXCaFX27FeEd/NOZInx5r94liXlxt5dr6Ov49PBKdpgKFrf0InHwMCn6BhElQ5znQBM+49tHXh9GzpZ6pX9s4eNYJgKF7FzR1ErEtXXPxzvH3ADo4N9fvcQZCKF3DJfVQdXEbGenbi7UkBZrMcUnNQiW/C11OfsxODenxtlAyY7JZzpjsT4HMcfvK9SAEptFDfXqcQ2lOnlxupX6MlqljIzHpK1DYWvfAqWc8XZIbvgk1B4IfJr2qCEVR+L87IoiN1PD8KisFhQJFq8U0ejDOvQcoPnjkj531sRA3Gqy7oODnwAXtJ6FyDZfURdXFrdEYun9Bl6TykDkuqVmo5PfPuenY3aG5vu2lksyxHLLKGZP9JVA5Lmx2HKs/w9CzG9q6vpvRNiXHxaOLLUSGKcwab6aGqQK3nc4cSH0bDA2g8TQwtfRZnFUVHa7h9WERpOS4+ffGAgCMg/qjRIRjX7724p1rDgV9IqTP8SxnpGKhcg2X1EXVxW1mZmagQ5Akn5I5LqlZqOS3GsbbnpdkjiWvuJC0woJAh1ItBCrHHRu+RFishN85zGfHyC5w89AiC0VOmDneTEJUBW45hYDUqeC2QZ1nQRvlszi9pVNDPff3MLLh1yI27C1EExmBcVA/Cr/ahiujVFd/jQFq3QdFpyDns8AF7Aehcg2X1EXVxW3t2rUDHYIk+ZTMcUnNQiW/d2adoU1UfEiPtz1PTirlX4HIceFyYVu2Bl2bVujbXeOTY9iKBI8usZCR72banZE0iddWrIG8TVDwo2d92LDQmZTo/h4mOjbQ8dpnBSRnuTCNGgwuF45VGy7eMfIGCG8PmYvAmReYYP0gVK7hkrqourjNypL/OEvqJnNcUrNQyG/PeNvQXt+2tCRzDCCLW38JRI4XffsD7jOphI8b7pP2i12Cp1dYOJzq4r8jI7m2fgXXoC1K8XTZDW8PNe/wSYy+otMovD4sAr1W4YVVVlyJtTF074p99WcIxx+zKaMokPCA58l05qLABexjoXANl9RH1cVtUVFRoEOQJJ+SOS6pWSjk90+5aTjcLm6KU0dxG28IJ0Zv5LCcVMovApHjtsWfoKmdgOHmG73etlt41nz9/riTvw+KoEcLQ8UaEE44+yYoeqj9lGd92BCTWEPLy4Mj+C3VxXubbZjGDkXk5uH4YsvFO4Y1gujbIfdzcJwISKy+FgrXcEl9Qu+qUQFyfS1J7WSOS2oWCvl9YbxtTN1Ah+IVf8yYLJ+4+IO/c7z4wCGcew9gGjMERVfBrsJXIYTgnS9tfL6viMm3mBjSIazijWQuA8cRSJwM+jivxudPvZIMjL4+jEW7CvnBnIS2eRPsy9ZcPlFb/HjQRMC59z3jjFUmFK7hkvqouriV62tJaidzXFKzUMjvnZlnaBsVT7QKxtued764lTMm+56/c9y+dA1KRDjGO271etvzv3OwaFchYzuHce9Nlfh9sB+CrGUQdQtEdfd6fP72VL9wWiRo+cc6G84hQ3AdP0nx7v9dvJPWDPF3ge1XsH4XmEB9KBSu4ZL6qLq4jYoK/tn1JKkqZI5Lahbs+e1wOdmdk0o3lXRJPi/JHEu+s4hUh5wx2df8meOutHMUbt6OcehtaCLCvdr2p3sLmfK1nf6tDTx7azhKRdeiddvh7Fugi4OEh70aW6CE6RTeGB6JvVjwf5ZOKDWjsS9bc/mO0QM8XZTPfQDuwsu3h7Bgv4ZL6qTq4lan0wU6BEnyKZnjkpoFe37/fH68rUomkzpPTirlP/7M8fPrrZpGDfZquzuOFvF/6wro0ljHK0Mi0FS0sAVPYVecCnWeBm2EV+MLpCbxWp6/NYLvTmv47fr+FO34AeeplIt3UrRQ6wEoTofsMorfEBbs13BJnVRd3GZnywkxJHWTOS6pWbDn97eZ59e3Vcd42/PkckD+468cd1sLcKz9nLDePdAm1vJau/vOOHlmpZXmCVreHm3GoKtEYWv5wTOpUswICG/rtdiCxZAOBvq3NvCyuydCp7vwR4aLRLSHyBshazkUq2dt2GC/hkvqpOritm5ddd1wSNKlZI5Lahbs+b0z6wztatSihl49420B4sLCiTOYOGSVxa2v+SvHHZ9+gSiwYbrTe8v/nMx0MXmJhfhIDTPGmYkMq0Rh68yBtCkQ1sQzuZIKKYrC3waGE5YQw4763XBs+BK3xXr5jrXuA9yQ8bHfY/SVYL+GS+qk6uI2PT090CFIkk/JHJfULJjz+8J4W5V1ST5PzpjsH/7IceF0YV+2Fn37NuivaeGVNtPz3Ty8yIJGAzPHm4mNrMTtpBCQOtWz1mudZz3L/6iU2ajhjeGRLK/fH+wO7Os2Xb6TIRFihkH+FrAd9H+QPhDM13BJvVRd3Lrd7kCHIEk+JXNcUrNgzu+fctIoVOF42/OSzLEctmTLGZN9zB85XrR1J+7UdK89tc13uHlksYU8u5sZ48zUj6nkkkJ5m6DgR4ifCGHqXzKmbT0dtw65hr0xrchetA7hdF2+U+wo0MWWLA0UvNe/8grma7ikXqoubmV3CEntZI5LahbM+f1t1mk0KNwQWyfQofhEkjkGi7OIFEcZ3Sclr/FHjtuWrEZbvw6G7l2q3JajWPDEUisnM128M9pMq9qVnDCoKAXS50B4B6h5R5XjChUTuhk50HUgxuxzJH+64/IdNCaIvxccRyHva/8H6GXBfA2X1Munxa2iKB8pinJOUZT9pd6LURTlK0VRjpb8t+YVPjuhZJ+jiqJMqMzxT58+XdnQJSkkyByX1CyY89sz3jZedeNtz5OTSvmHr3O8+NeDOPf/hmnMUBRtJZ+wlnC5BS+utvLzKSevDo2ga5NKdiMWTjj7pqcbcu0nQVH1c5aLaBSFO5+8mfSIWqR+tBpHcRk9I6J6gqkVZMwHl83vMXpTMF/DJfXy9RVlHnDpSuEvAJuFEM2BzSXfX0RRlBjgn0AXoDPwzysVwX8mOjq6oh+RpJAic1xSs2DNb4fLyZ6cNNWOtwVZ3PqLr3PctmQVSlQkxoH9qtSOEILXP7PxzaFinrs1nFvbhFW+scxl4DgCiZNBH1eluEJRfA09mmF30Cz9EPPn/Xr5DooCtR4EVw5kLfV/gF4UrNdwSd18WtwKIbYDl84DPhiYX/L1fGBIGR/tD3wlhMgWQuQAX3F5kSxJkiRJfrcnJ9Uz3jZOvcVtjMFErbBwWdyGMFdKKkVbv8M49HYUU9V6GMzeZmfVz4Xc283InV2q0Jb9EGQtg6hbIKp7lWIKZUkTb6MozETUxvVs/q3o8h1MLaBGX8he5+nCLUlSuQVideUEIURqyddpQEIZ+9QFSvdlOFPy3mUURXkAeABg0qRJJCQkULt2bbKysjh06BC9evUiOTmZqKgodDod2dnZ1K1bl/T0dNxuN3Xr1uX06dMX/rqUm5tL/fr1SUlJQaPRkJCQQEpKCjExMTidTvLz82nYsCHJyckYDAZiY2NJTU0lLi4Oh8OB1Wq9sN1oNBIdHU1aWhrx8fEUFBRgs9kubA8PDyciIoKMjAwSExPJzc3F4XBc2B4ZGYnRaCQzM/PCORUVFV3YLs9JntPPP/9M586dVXVOavw5yXOq3DlZrVZsNlvQndNnvx9EA3QIj+Xw4cOq/Tk1NUbxv4wU8vLyVHNOwfZzOnPmDCaTySfnlDH7Y8I0Co6+PUg5fLjS57ThgIb3v9VyexsttzZI4fjxSv6c6tdCc+p1NEo0BaZxpB0+HDI/p9LnZAwLIyMjE3OUuUo/J3p0pufmHdy/JJmY8RE0iAu76JxchTfRVNlBwe/vYqnxdEj+Pp0+fZrc3Fx5jZDn5PVz+jOKr2dCVBSlEbBBCNGm5PtcIUR0qe05Qoial3zmGcAohHi15Pu/A3YhxFt/dqzt27eLHj16XPjeZrNd9X+AJIUymeOSmgVrfg/cuRK7y8nmHmMDHYpPPb9vC0tPHyR5wCQUpRJrmEpX5ascd1usZA8aj+HmG4l6+blKt7P5tyKeWWHlpuZ63h0TiU5ThTxIfQ/yvoAGb0B428q3EyD5eXksWrCQxQsWYrVaGTt+HI8/9SQmk6lS7bnOnCVr+L2saDGEPb3u5IN7zJf//836BDI+gnr/gsjrvHAW/hWs13Ap9CmKcnNJD+HLXLVbsqIo9yuK0rzka0VRlI8VRclXFOVXRVE6ViKedEVRape0Vxs4V8Y+KUD9Ut/XK3mvQlJSZFcOSd1kjktqFoz5bXc52ZObRjcVd0k+L8kci9VVzBm7JdChqJavctyx9nOEzU74uMov/7PnZDF/XWWlbT0t/x1ZxcLWssuz9E/MiJArbPPz8pg5bToD+vTj/Zmz6HJDV0aNGc3SRYsZM3wkB/bvv3ojZdDWq0NY964MS9nMwZM25myzX75TzcGgrwPn5nom4goxwXgNl9SvPGNuHwdOlnw9FmgHNAaeAqZW4pjrgfOzH08A1pWxzxdAP0VRapZMJNWv5L0K0Wiqzwx8UvUkc1xSs2DM7z05qRSpeH3b0uSkUr7nixwXTif25WvRX9ceXYumlWrjSLqTJ5ZZqVdTw3v78MI+AAAgAElEQVRjzZj0VShsnTmQNhXCmkD8+Mq342f5+fnMmj6D2/r2v1DUrlizinfem8pL//wH73/4AXa7nbvHjmP2jJk4nRUvPk1jh6K35vOkZhdztzvYfbL44h00eqh1PxSdhpwNXjoz/wnGa7ikfuXJOqcQ4vxv20BggRAiSwjxNRDxZx9UFGUp8D3QUlGUM4qi/AV4A+irKMpRoE/J9yiKcp2iKB8ACCGygVeA3SWvf5W8VyEJCWUN55Uk9ZA5LqlZMOb3jqwzaFDoGqPO9W1LO1/c/iaLW5/xRY4Xbv4W97lMTHcOq9TnU3JdPLLIQrgBZow3Ex1ehQJFCEidCm4b1HnWs/xPkLtQ1Pbpx+wZM+nctcuForZlUtKF/breeAOfrF1Nv1v7M2v6DCaMG8/JEycrdCx9x3Zomzeh76HPaRCj8OJqKzk298U7RXaGiE6QuRiceV44Q/8Jxmu4pH7luWK5FUWprSiKEegNlF5V+k8HGgghxgohagsh9EKIekKID0sK495CiOZCiD7ni1YhxB4hxH2lPvuREKJZyevjypyc7A4hqZ3McUnNgjG/d2SeoX10LaL0VVgKJUTUNBhJCAvnsCxufcbbOS6EwL54FdqG9TDceH2FP59d4GbSIgsOJ8wcb6Z2jaqtjUveJij4EeInQljDqrXlY5cWtdd36cLy1Z9cVtSWFlWjBv9+87/85+23OJWczOhhw1mxdBnlnc9GURTCxw5F/H6St5sfJ9cm+L91BRd/XlE8T2/dDshc4I1T9ZtgvIZL6lee4vYfwB48XZPXCyEOgGcgL/C770KrupiYmECHIEk+JXNcUrNgy2+bs5ifctW9vu2lksyxHLJUuOOUVE7ezvHiX/bjPHQU09hhKBXsEmorEjy21EJanpv3xkbSrFYVF9QoOgPpcyC8A9S8o2pt+VB+fj6zZ8y8rKh9d9pUklq1Klcbt942gE/WraVDp4689q9XeOTBhzh3rqwpZS4X1rcnSkw08V+u54k+4Ww7UszSHwsv2akB1BwEuZvAcbyipxgwwXYNl6qHq175hBAbgIZAKyHE/aU27QFG+yowb6jM+AdJCiUyxyU1C7b83pObVm3G257X0hzLYWsWbh+vrFBdeTvH7UtWodSIwnhbnwp9zlEseGKZhYNnXbwxPJIODarYfVg44exbnm7ItZ8EJfjGXpYuamdNn1Gpora0hIQEZs2dw4t//xs/7d7DiDuG8OWmq08Xo4QZMA0bSNGOHxhdO5MeLfS8+5WNQ6mX5EbcWNCaIf19T3fvEBBs13CpeijPbMk9gBuBtoqi9Dj/AjoBlZkt2W/y8/MDHYIk+ZTMcUnNgi2/d2SeQasodKkG423PSzLHYnM5OW0Prp+FWngzx52nUij6dhemEQNRjOXvNl/sEjy70sruE07+NTiCXkmGqgeTuQwcRyBxMujjqt6eF11a1F7XuTPLVlW+qC1NURRG3zmW5as/oV6D+jz75FP89bnnr/pzNg27HfR67CvW8fLgCKLDFZ5fZcVWVKqI1Zoh7m6w7wfLjirF6S/Bdg2Xqofy9Dl5toz3BJ5Zk+sDVRyQ4TsNGwb3+A5JqiqZ45KaBVt+f5NxkmtrVI/xtueVnjG5YXiNAEejPt7McfuyNaDTYRo+qNyfcboFf11t5dujxfzt9nAGXuuF3LYfgqxlEHULRHWventekp+fz5KFi1i0YCGW/Hx69e7Ng5MeptU1VStoy9KocWPmL17Eh3PmMmfWbH7avYdXXn+NLjd0LXN/TVwMYf164tjwJbEPTeD1oZE8sMDCG58X8K/BkX/sGN0fcjfCuQ8g8nrQGL0euzcF2zVcqh7K0y15UOkXntmN9UAaMMTXAVZFcnJyoEOQJJ+SOS6pWTDl9768c/ycm86IumVPLKNWrcyeMXOH5bhbn/BWjrvz8nF8+iXGW29BE1e+cY5u4Zm86OuDxTzdL5wR13mhUHLb4eyboIuDhIer3p4XWCwWz5Pavp5Zja+7/nqWrfqEKdPf80lhe55er+ehRyaxYOliTCYTD9z7F/77+r9xOBxl7m8aMwTsDhzrN3F9Yz33dTey/n9FbNxXavytooWEB8GZAdmrfRa7twTTNVyqPso9CEJRlN6KomwFXgXeEUJ0FUJ86rPIvMBg8ELXGkkKYjLHJTULpvyel7wPo0bLmHq+uxkORjX0RmobI+Ratz7irRx3rNkIhYXlXv5HCMG/P7Ox4dciJvU0cdcNXnoCmD4XitOgzjOg/dPVIn3ufFE74Hz34+uv80tRe6k2bduybNVKxoy7k8ULFzF2xEh+O3Dwsv30LZuh79gO+4r1CKeLB3uaaF9fx2sbCjid7fpjx/C2YO4OWSuhuHyTVgVKMF3DpeqjPGNub1cU5TvgGeBvQoheQoivfB9a1cXGxgY6BEnyKZnjkpoFS35bnEWsPHOIoXVbEm0I7m6AvtAyMlYWtz7ijRwXxcXYV6xD36UTuqaNrr6/ELz7lZ2VPxUysZuR+3t4KactuzxL/8SMgPA23mmzMmFYLLw/c1YZRe00vxa1pZlMJv76t5eY9cEcLBYr48eMZe7s9y+bcMk0Ziju1HSKtn+HTqPw+rAINBrP+NtiV6nxt7XuBQScq9RKmX4TLNdwqXopz5PbT4F6gBN4TlGU9aVfvg2valJTUwMdgiT5lMxxSc2CJb9XnTmE1VXMPQ3bBjqUgEgyx3LEmi1nTPYBb+R44ZdbcWdmE17Op7azt9lZ8L2DMdeH8VhvE4qiVDkGnDmQNhXCmkD8+Kq3Vwmli9qZ06Z7itpPVga0qL3Ujd26sWrdGvr068v0qe8xcfzdnCrVddfQvQuaOonYlq4BoE60lv+7I4KDZ11M22z/oyF9guePCJZtYNvv79Mot2C5hkvVS3kmlOrl8yh8JC4uuGbokyRvkzkuqVkw5LcQgo+Sf6VNVBzXRScGOpyAOD9j8ilbPo0i5KRS3lTVHBdCYFuyGm2Thui7drrq/vN22nl/m4PB7Q08NyDcO4WtEJA6Fdw2qPOGZ/kfP7JYLCxZuIiF8xdgyc+n5y29eGjSJFq1vsavcZRXjeho/vP2W/S8pRev/etVRg4dzjPPP8eIUSNRtFpMowdT8O77FB88gv6aFvRuZWBkpzAWfO+gSxMd3ZqVdPWNHQF5X3qWBmo0xTMeN8gEwzVcqn7KM6HUtj97+SPIyrrSoH1JUguZ45KaBUN+/5Sbxv78TCY2bOedQiAEJZVMKiW7JntfVXO8eM9eXEd/x3Tn8Kvm57IfHUz52k7/1gb+MSgCjbfyOfdzKPgR4u+FMP/NjmuxWJgzaza39fU8qe10XSeWfbKSqTOmB21hW9qA229n1bo1tO/QgVf/72UmPzSJjHMZGAf1R4kIx7587YV9n+4fTrNaWv6+toBMq9vzpsYItf4ChcchLzhHCwbDNVyqfsoz5nafoii/XunljyAry2q1BjoESfIpmeOSmgVDfn+cvI9IrZ4R9arXLMmllV4OSPKuqua4fckqlJhojP3/vJPduv8V8sbnNnq21PPq0Ai0Gi8VtkVn4NxcCO8ANcu/BFFVWK3WC0XtjPem0bFTJ5Z+siJkitrSEhITmTX3fZ5/6UV+/OEHRgwewjff7cQ4qB+FX23DleH5nTPqFd4YHoGtUPDSGusfQwTMPcDUGjLmg6sggGdStmC4hkvVT3nG3A4EBl3hNdh3oVWdXF9LUjuZ45KaBTq/c4scrEk5zIh6SZh11XfWzyh9GHWMkbK49YGq5LjzxCmKdv6IacQglLAr5+cX+wt5eX0BXZvo+M+ISPRaLxW2wgln3/J0Q679JCjlXoCjUs4XtQP69L2sqL2mdWufHtuXNBoNd44fx/LVn1C3Xl2efvxJXj9xCKuzGMeqDRf2a1ZLxzO3hvPD707m7yx5IqoonqWBXPmQuSRAZ3Blgb6GS9VTea5EPYUQyZe+gBTgdR/HVyVyfS1J7WSOS2oW6PxeduY3HG5XtZ1IqrQks5wx2ReqkuP2ZWsgzIBp+MAr7rPtcBEvrSmgfX0d744xE6bzYtf6zGXgOAKJk0Hvu7GVVquVubPfv1DUdujYURVF7aUaN2nC/CWLeXDSw2zasoUHnTl8v2QFwvHHOrfDO4bR9xoDM7bY2XemZKZlYzOo0RdyPoXi9ABFX7ZAX8Ol6qk8xe3jiqI8UPoNRVEigI2AzSdReYnRWP2WbJCqF5njkpoFMr+FEHyc/CudohNpV6NWwOIIFudnTHYJd6BDUZXK5rg7JxfHxq8x3tYHTc3oMvfZ9Xsxz6y00jJRy3t3mjHpvVjY2g9B1jKIugWiunutWZfLxckTJ/jqiy+YOW06T05+nAF9PDMLny9q35s5Q1VFbWl6vZ5Jkx9l3uJFhNWI4umMk/xn8pMUFnoKXEVR+PugcOLNGp5fZcXiKPl9jBsHCp4/OAQReY8iBUJ5ZkvuA2xSFMUohHhPUZR4PIXtZiHEC74Nr2qio8u+4EuSWsgcl9QskPn9XVYKR605TG/fN2AxBJMkcywOt4tkWz5NIuR1x1sqm+P2VRugsAjT2KFlbv/lVDFPLLPQKFbLzPFmIsO8WNi67XD2TdDFQcLDlWpCCEFGRgZHjxzh2JGjHDt6lKNHjvL78eMXFXL1GzTgpu7dueueCaotaMvS7tp2LN+wnjduHczSHdv4ccQoXvvPG7S6phVRRg1vDI/g3o8tvLrBxhvDI1D08RB9G+RsgNiRYKgT6FMA5D2KFBhXLW6FENmKovQBPlcUpQ6ecbazhRBTfR5dFaWlpVGjhly2QFIvmeOSmgUyv+ed2kcNfRhDarcIyPGDTekZk2Vx6z2VyXFRWIT9k08xdOuMrlGDy7YfOOvk0cUWEqM0zL7LTA2Tl8fCps+F4jRo8B/QRlx194KCAo4dOcrRo0c4euSo5+sjR8jLy7uwT1xcHM1atGDU2DE0b9Gc5i1a0LhJE0wmk3djDyHhERG8+PxzdPnHa7yTmcn4MWOY9Oij3POXe7m2vp6He5mY/o2drk30DO0YBrGjIPcLyFwMdZ4NdPiAvEeRAuOqxa2iKOdXBZ8DvANsBk6ff18Isdp34VVNfHx8oEOQJJ+SOS6pWaDyO6PQxvqzR7m3UTvCdf5dszNYtSw1Y/JtiU0DHI16VCbHHV9sQWTnYrpz+GXbjqY7mbTIQnS4hvfvjiI20suFrWUX5G2CmJEQ3uaiTcXFxZw8cZJjR49w7Ogxjh7xFLNnU1Iu7BMeHk6z5s3p068vzVq0oFnzZjRv0YKaNWt6N06VCOvbky7TP+TjZo2Ypi/mvXensH3rVl59499M7FafH08U85/PC7i2vo4m8TFQcyBkr4bY0RB2+R8+/E3eo0iBUJ5uyaXndl9/yXsCCNritqCggJiYmECHIUk+I3NcUrNA5ffS0wcpFm7uadjO78cOVmadgXoms5xUyssqmuNCCOxLVqFt3gT9dddetC05y8WDCy2E6WDO3WYSorxc2DpzIG0qwtCYtOLeHN26jaNHj5Q8iT3KiRO/4yz2THKk0+lo2KgRbdu1Y9iI4TRv0ZxmLVpQp04dNBrfzqqsJkqYAdOwgYgPFvH6yg/pecst/PuVVxk5dBjPPv88rwwZxpj383lhlZWF90URFjMCcjdC5iKo+2Kgw5f3KFJAlKdb8kR/BOILNltQz3clSVUmc1xSs0Dkt1sI5iXv48aYurQ0y5uy0lpGxsji1ssqmuPFu37C9Xsy5n8+g6L8MY42JdfFAwssCAHv3x1F3Zpar8SXn5fH0ZJuxEd/Wcqx389y/LQWi3XAhX0SayfSvHkLburRneYtWtC8RXMaNW6MwVB9l8/yJtOw27HNX45jxTpuf/YROl3XiX+8+Df+9c//o8eWLTwz8e+89HkY735p44XbakDNIZC1FBzHwRjYXhbyHkUKhPJ0S34KyBNCfHjJ+38BzEKIKb4Krqrk+lqS2skcl9QsEPm9NeMUJ215vJR0g9+PHeySzLHsyDqDS7jR+nhN0+qiojluW7IaTVwMYf16XngvPd/NA/Mt2IsEH9xjpnFc5Qpbm83G1m++4fBvhzhaMsHTufQ/lpYxR2ho3qwBtw3qeqFLcbPmzYmKiqrU8aTyOf/zdmz4koiHJpBYuzazP5zL0kWLmfrOu+zbO5LuQ15g2e4b6d/GQIe6Qz3LAmUugnr/DGjs8h5FCoTydEseB3Qt4/2FwB4gaIvb5ORkWrZsGegwJMlnZI5LahaI/J6X/CuxBhMDE5v59bihIMkcS6HbxYmCPJpFyjGS3lCRHHceO0HxDz8RMWkiit4zFjy7wM1DC/PJtbmZfXcULRLKc1t3MVtBAcuXLmP+x/PIyc5Gr9fTpGkTru/c2TO5U5MYmod9SK167VAavArV/A8bRW4XecWFxIeF++2YpjFDKPzsKxzrNxE+bgQajYZxd9/FDd1u5MXnXmD7x88T0WYkr2x4kuUPRqGPGQaZC8B+GEyBu0eQ9yhSIJTnKqgTQhRf+qYQokgp3ScmCIWH++/CI0mBIHNcUjN/5/dZu5XP03/nkSYdCdNWvEhQu6RSk0rJ4tY7KpLj9qWrwRiGcehtAOTZ3Ty00EJqrpuZ4820rVuxnLUVFLBsyVIWfDyPnJwcbrypG/c/+CDt2l+LTlfSlnBC8jNQFA51nqr2he3WjFM8u+8bUuwWVnUdxg2xdf1yXH3LZug7tsO+Yj2m0UNRdJ6n802aNmXh0sX8999vsGLZco7X6s68nTdyf7c7IGctZC6E+q/6JcayyHsUKRDKc5XSKIqScOmbZb0XbCIirj5FvSSFMpnjkpr5O78Xnd6PSwgmNGzr1+OGipallgOSvKO8Oe7OzMaxaQvGQf3Q1IiioFDwyGILJzJdvDPGTMeG5Z/Vu6CggA/nzmVAn35MfeddrmnTmoVLlzBr7hw6Xtfpj8IWIHMZOI5A4mTQx1X09FQj1WHlLz9tZNiu1QigrsnM2B/XcSA/w28xmMYMxZ2aTtH27y56X28w8PTzz5GQmEjUoVnM2VbAqbwwiBkFBT+Dbb/fYryUvEeRAqE8xe2bwGeKotysKIq55NUT2AC85dPoqigjw38XHUkKBJnjkpr5M7+dbjcLkvfTK74BjeU6rmWK1BmoL2dM9qry5rh91afgdGIaPRR7seCxpRZ+O+vivyMiubFp+QrbgoICPpwzlwG9+/LeO1No07YtC5ctZeac92nX/trLP2A/BFnLIKo3RHWvyGmphtPtZvbvv9BlywI2ph3n+RZd2XHzeNZ0HUaEzsDIXWtJtuVdvSEvMHTvgqZOIralay7bZjQamfzE4+Sf/Q3N6c289lkBInoAaGtCxgIQwi8xXkreo0iBcNXiVgixAPg78C/gJHACeBn4hxBivk+jq6LExMRAhyBJPiVzXFIzf+b3V+dOcNZhZaJc/udPJZljOWTJDnQYqlGeHBcOB/ZPNmDo3hV3nTo8tdzCz8lOXhsWQa+kq89IbLVa+eD9OZ6i9t0ptLv2WhYtX8qMObNpd+0V8t1th7Nvgi4OEh6q6Gmpwu6cVHp/u5QXD2yjc83a7Ox5F8+37IpRq6NeeBSrug7F4XYyfNcaMgp9PyuwotViGj0Y594DFB88ctn22wcNpNU112A4OIddRwvYeEADcWPAvh9s//N5fGWR9yhSIJRr8IQQ4nMhxM1CiFghRFzJ15/7Oriqys3NDXQIkuRTMsclNfNnfn+cvI/axgj6JzT22zFDUZI5lmMFOTjd7kCHogrlyXHHxs2IvHwMY4bx3CdWvj/u5J93RHBrm7A//ZzVamXu7PcZ0Kcv06ZMpV379ixesYzp78+ibbur/BEnfS4Up0GdZ0BbvbqW5hQ5eHLv19y6YzmZRXY+7nQ7K7sMocklPTqSzLEs6zyYVLuVUT+sJb+40OexGQf1R4kIx7587WXbNBoNTz33DPlZaSSmreKtL2zkhfUDXXzAnt7KexQpEK5a3CqKsqLU1/+5ZNuXvgjKWxwOR6BDkCSfkjkuqZm/8vuULY/N504yvkEb9BrvrA+qVknmWIrcLn4vkDet3nC1HBduN/alq9G2as7LJxuz9XAxLwwIZ0iHKxe2FouFObNmM6BPX6ZPfY/2HTqwZOVyps+eSZu25RhPbtkFeZsgZgSEt6noKYUstxAsPnWAzlvms+j0AR5u0pFdve5mcJ3mXGn+1M4xdZh33e0cyM/krt2f4nA5fRqjJjIC46B+FH61DVfG5cMDOnfpws29epL380LycrKZ8rUT4saC4zAU/OjT2Moi71GkQCjPk9vmpb7ue8m2eC/G4nVyfS1J7WSOS2rmr/xekLwfBYW7GlSfG/nKOj9j8mGr7JrsDVfL8aLvduNKPsPnLQey6UAxj/c2Maazscx9LRYL78+cxYA+/Zjx3jQ6durE0k9WMG3WTFq3KWduO3MgbSqENYH48RU9nZB1MD+Tgd+tZPLer2gaEc3WHnfyausemHVX7/bdN6Ex09v35dusMzz4yyZcwre9GkyjBoPLhWPVhjK3P/H0UxQ57DTPWsSaXwr5Kfdm0CdCxiLwcWyXkvcoUiCUp7j9s34MgRmhXk7JycmBDkGSfErmuKRm/sjvIreLRacP0C+hMfVMZp8fL9S1iJQzJnvT1XLcvngV1qhY3insyP3djUy8yXTZPvn5+cyeMZMBffoxc9p0rrv+OpZ9spKpM6ZzTevW5Q9GCEid4hlvW+c5UMo/A3OosjqL+MfBb7l5+2KOWLJ579q+bOw2itZRFXt2M6peK15r3YNPU4/x7L4tCB92AdbWq4Ohe1fsqz9DOC7vCt2kaVOGjxzB0e9WE89pXv2sEGfNcVB4HCzfldGi78h7FCkQyrMoWriiKB3wFMKmkq+VktflV9kgEhkZGegQJMmnZI5LauaP/N6YdpxzhTYmyuV/yiVCp6dheJQsbr3kz3K8+PAxin/ay+KkcYy9MYJJvS6+5crPz2fxgoUsXrAQi8VCr969eXDSw7S6plXlgsn7Ggp2Q60HIaxB5doIEUIIPk09xosHtnHWYeWuBm34Z6tuxBgqf1v7cJOOZBbaeffYbuIM4byYdIMXI76YaexQirZ/j+OLLZgG33rZ9ocefYTPPt1A7ZNz+ZV/MW9/F+6rVx8yF4H5BlD8M/xC3qNIgVCe4jYNeKeMr89/H7SMxrK77kiSWsgcl9TMH/k9L3kf9U1mbqklu8+Vl2fGZFncesOf5fi+KSuJ1Rox3HErT/cLvzDuMz8vj0ULFrJk4SIsFgu39OnDg5MeIqlVJYtaAFc+ZHwIplZQc1Dl2wkBJwpyeX7/Vr4+d5I2UXF81Ok2OsfU8Urbf0u6kYwiG28d/YG4MBMPNG7vlXYvpe/YDm3zJtiXrcF4R//LxgTHxsZy7/33MW3KVK5vfYA521sz+N47ic//D+Rvhxq9fBLXpeQ9ihQI5VkKqKcQoteVXv4IsrIyMzMDHYIk+ZTMcUnNfJ3fR63ZbM88zYSGbdEq5Vo8QKJkxmRrDsVuV6BDCXlXyvGVm1Ko/fO3HO7Qm2eGx6MoCvl5ecx4bxoD+vTj/Zmz6Ny1CyvWrOLdaVOrVtgCZMwHlxUSHgWV/i4Uupy8eeQHum1dyK6sFF5r3YNvut/ptcIWQFEU3mnbm9sTm/LX/VtZlXLYa21fepzwsUNxHT9J8e6yl/kZd/ddJCQmkv/9dPRawd++vhYR1hgyF4Pwz++uvEeRAuGqT24VRRn2Z9uFEKu9F4531a5dO9AhSJJPyRwPQcINrlzQxQQ6kqDn6/yen7wfnaJhXP0KjEuUSIqMpVi4+b0gj5ZmmcdVUVaOr/rJQer8tWgQ3PziSCx5eSycv4ClixZjtVrp068vD056mBYtW3onCPshyP0cag4FozqXwtqSkcxz+7ZwvCCXIXWa8+o1N1PH5JsuszqNhrkdBzDyhzVM+uULauqNPukZEta3J9bpH2JftgZD5w6XbTeZTEx+/DH+9tcXGXLzt6w70YM9HcZwvf7fkLcZovt5PaZLyXsUKRDK8+e5QaVecy75fqDvQqu6rCzZbUpSN5njISj3Mzg2Hk69AJbv/fYX9FDky/y2u5wsPX2Q2xObkmCsXut4VtX5GZNl1+SquzTHP/u1kLfWZjPkzGYcN3Zi7icrGNCnH3Nnv88N3W5k5drVvD11ivcKW+GCtOmgi4W4cd5pM4ikOqz85aeNDN+1BgF80mUoH3W63WeF7XlGrY7F199BS3MME/Zs4Kcc74/iU8IMmIYNpGjHDziTz5S5z+13DKJlqyR+WDeDNolOntvUGqehuefprbvY6zFdSt6jSIFQnm7JE8+/gNOlvxdC3OuHGCutqKgo0CFIkk/JHA9Blp2grQlFqZDyCvx+P2SvBZct0JEFHV/m9/qzR8kpdjCxUTufHUOtmkfWREEWt95QOse/+a2If6wtYFzelyzNP8uYrZ/zwZy5dOt+E5+sW8NbU971XlF7Xs6nUPi7ZxIpbbh32w4gp9vN7N9/ocuWBWxMO84LLbuy4+bxfh1bH6UPY2WXocSHhTP6h7UcsXh/+SzTsNtBr8e+Ym2Z2zUaDU8/9yypZ8/S3rEeiwOWHh8JzgzI+8Lr8VxK3qNIgVDRgRVBvfTPpeT6WpLayRwPMS4b2A5AjT7Q9COo86Lnicm5OXD8LkifDUVnAx1l0PBlfn+c/CvNImrSPbaez46hVuE6PY3Ca8ji1gvO5/jOY0U8u+gMMcfnsGjz2ywtsnBTz56sXLuGN999h+YtWnj/4MVZkLkQIjqBuZv32w+Q3Tmp9P52KS8e2EbnmrXZ2fMunmvRFaO2PHOoeleCMYJVXYei02gYvmsNKXaLV9vXxMUQ1q8njk+/xJ1fdttdunal+803s3bxB4xs6+Dt71phUa6BrOXgvnwpIW+S9yhSIKhz1oAScn0tSe1kjocY2y+ACyKv8yzFEHUTNHwTGk6ByMFxY40AACAASURBVK6Qs9HzJPfMy1DwP8+6k9WYr/L7QH4GP+akMqFh28tmGZXKR86Y7B3Jycl8s/cck194C9eno8jYvYgumjCWvPh33nz3bZq3aO67g5+bC8IJCQ+DCn4PsovsPLH3a/rvWE5mkZ15nW5nZZchNImIDmhcjSOiWdFlCPnOQobvWkN2kd2r7ZvGDAFHIY71m664z5PPPIXNZqN438fUidbynz3DwZkFuRu9Gsul5D2KFAjlmVDqU/54YttEUZT1pbcLIe7wRWDeEBUVFegQJMmnZI6HGOse0IR7ltsozdQCTM9Crb9AzmeeGw7rDxDWCGoOhqieoAkLRMQB5av8npe8jzCNlrH1qzjDbDWWZI7lq3MnKXK7MGj8s2am2mRnZzP7oxV8s3EdOB3c0v9WJmRYqG+1EzN2pG8PXvAzWLZD3HgweG+24EBwC8HS0wf5v992kFvs4JEmHXmuZVfMOkOgQ7ugXY1aLL5+ECN/WMuYH9exputwInR6r7Stb9kMfcd22JetxTR8EIrp8uV3mjZrxrARI1izYgUvThvFK9ta8lCbdtTLWgHRt4Km8uv7/hl5jyIFQnme3L4FvF3yGlzq6/OvoKXT+b8LiiT5k8zxECIEFOyBiI6gXOHnpouB+Lug6XxIfBLQQNpUOD7Bs1RHcfV6UuaL/LY6i1h+5hBD6rQgxuCbG7rqIMkci1O4OV6QG+hQQtL3O79jQJ/+fLN+OeGNb+LD5Wv57wP3U/foSUxjhqDofPgHA3cRpM0EfR2IGeG74/jBwfxMbt+5ksl7v6JpRDRbe9zJK617BFVhe95NcfWZ23EAP+ekc8+eDV5dSiv8wbtxn8vEtmD5Ffd5+NFJGAwGdqyaTv/WBv6+cxi48iBn/RU/U1XyHkUKhPIUtweBDCHEttIvIKNkW9DKzvb+4H1JCiYyx0NI4UlPN7CI666+r8YA0X2h0TSo/waYWkPWCjh+D5z9L9h9s3ZisPFFfq9OOYLVWcSEhm293nZ1klSyBJDsmlxxO3fsYPLDj1BsrE30sHmsWvA217Vrhn3JapSIcIyD+vs2gOxPoPgsJE7yXGtCkMVZxN8PbOfm7Ys5as1m2rV92dhtFK2j4gMd2p8aWLsZ77TrzeaMZB7931e4vTT0xNChLWH9emJbuBJXStkzM8fGxXHv/ffxzddf0z/hN47mN+fXnA6IrFXgKvBKHJeS9yhSIJSnuJ0GxJXxfiww1bvheFfdunUDHYIk+ZTM8RBSsNvz34hO5f+MokBEO6j3d2jyAdQc5OmunPwkJD8N+ds8Y+ZUyhf5PS/5V1qZY+lSU66/WBXNI2PQoMjitoJ2bP+WxydNxm1uSMzA95j9UEvqRGtxpZ2jcPN2jENvQxPpw6WpilI9EwmZe3h6kYQYIQTrzx6l65YFzPj9Z8bVb82Pt0xgXIPWaEJk3PDdDdvwt6QbWZlyiL8d2I7wUoEbMfk+0GiwvjfnivuMn3A3tRIS+GDaWzx+Sxiv7x6G4rZC9hqvxHApeY8iBUJ5ittmQojtl74phPgWCOo1FNLT0wMdgiT5lMzxEGLdDWFNQB9buc8bakPCA9B0IdR6CJy5cPY/cPxez1NdV7534w0C3s7vX3LT+V/eOSY2bCcnkqoio1ZH4wg5Y3JFbN+6jccfnYzL3Ij4Qe8x7+H6GIrOAWBfsQ4A06jBvgtACEif6RkWUet+3x3HR04U5DLqh7Xc89NnxBqMbOo2iinX9gnJ4QVPNrueBxu3Z/aJX5h6bI9X2tQmxBM+cSxFW3ZS9OPPZe5jMpmY/MRjHNi3n4iMLRgimrPt7PWI7DU++TdE3qNIgVCe4tb8J9u8MxreR9xud6BDkCSfkjkeIlxWsP8GkddXvS1tOMTcAU3mQr1/gqEeZMyDYxMgbRoUnqr6MYKEt/P74+RfCdfqGFUvyavtVlctI2NkcVtOW7ds4YnJj+GOakKdIVOZ93Bd6tXU4na7cVsLcKzZSFjvHmgTa/kuCMtOKPgJ4u6q/B/ZAsDhcvLfI7u4cetCfsg+y2ute/BN9zvpHBO6E2EpisJrrW9mRN2W/OvQThYk7/dKu+F3DkdTtzbWt2chnGX36rl90CBatkpi2jtTeL6vlhn7hiPcDsha5ZUYSpP3KFIglKe4PaYoym2XvqkoygDg98ocVFGUloqi/K/UK19RlCcu2aenoih5pfb5R0WPI7tDSGonczxEFPwCuMs33ra8FA1EdoEGr0OjGZ4ZlfM2w4mH4NRLnifFIrRvLLyZ33nFDlanHGZ43SSi9NVv5mlfSDLH8ntBLoUu9XaN94Ytm7/hqceewF2jOfWHTeXjh+pRu4Znwqi6devi+PQLRIEN053DfBeEywbn3vf0Hqk5yHfH8aLcIgfzkvfRfdsi3ji8i9sSm7Kr1wQebtIRnSb0V7LUKArT2/ejd3xDnvp1M5+lHqtym0qYgcgnH8R14hT2Tz4tcx+tVsvTzz7L2bNn2fP1Cm5q3YxNp27Alb0enDlVjqE0eY8iBUJ5rg5PAFMURZmnKMrkktd8PONtH6/MQYUQh4UQ7YUQ7YFOgA0oq8P/t+f3E0L8q6LHOX36dGXCk6SQIXM8RBTsBk0kmHz0xNDYGGo/7pllOW4CFJ2CM/+EEw9Czqfg9u66iv7izfxeceYQNpeTiSqbSMp55Diu9HMBOXaSORaXEHLG5D+x+auveerxJ3HXaEGTEVOY92Bdapn/uPU6ffIk9mVr0bdvg/6alr4LJHMxOLMh8VHPGttBqtjtYlPa79yz5zNafTWXp37djEGj5ZMuQ/mw023UMUUGOkSvMmi0zLtuIB2iE7jv58/ZmXmm6m1274q+Sydscxbizi77d7PLDV3p3qMHc2e/z6hrC1l7eji4i3FlrKjy8UuT9yhSIFy1uBVCHAXaAtuARiWvbUA7IcQRL8TQGzguhPD6Ss/R0YFduFuSfE3meAgQbrD+VLIEkI9vKnU1IG40NP0Y6jwHmghInwXH7oZzH0BRaI1/8lZ+CyH4OHkfHWok0D46wSttBgN3bj459z9F7r1PBKTATTJ7urb+Jrsml+nrL7/kmSefRkS3pMXoKXz0QB1iIi6+7Yo+dBx3ajqmO4f7LhDHCchZ51nP1Fd/YKsCIQQ/56bx/L4tXPPVB9y5ez3fZZ1hQsO2bO4+lh03j+eWWg0DHabPROj0LO8ymIbhNbhz93r25VXtd1lRFCKfeghhd1Aw6+Mr7vfEM09TUFDAgrmzuadnU9af7I7I3QjFmVU6fmnyHkUKhHItQCWEKASu/BsCKIryvRDihkrEMAZYeoVtNyiKshc4CzwjhDhQxnEfAB4AmDRpEgkJCdSuXZusrCzOnj1LjRo1SE5OJioqCp1OR3Z2NnXr1iU9PR23203dunU5ffr0hV/A3Nxc6tevT0pKChqNhoSEBFJSUoiJicHpdJKfn0/Dhg1JTk7GYDAQGxtLamoqcXFxOBwOrFbrhe1Go5Ho6GjS0tKIj4+noKAAm812YXt4eDgRERFkZGSQmJhIbm4uDofjwvbIyEiMRiOZmZkXzqmoqOjCdnlO8pyOHTuGTqdT1Tmp7ecUb84n0pWDhVbkp6T475xSaxMV9TxGw0m0+RswZ6+F7DUU0BZdrREkn4skumbNoP45abVabDZblX9OvzpyOGTJ4q8JbcjIyFBN7sV8vhXsDtxA1qN/JffFyTRoleS3c4ox6NEAv2aepWORQV4jSp3TkUOH+fuLLyFirqHVqLd5rmcBxQVZpOZdfE7hy9ZhrJPAyYSaxGVlef+cIsKp5ZiCggmbcThZJ04Ezc/pl9Mn2OHKY3X6UU4WWgnTaLkpPJ7BdTvQN7EJuVlZJCpGTp06FRTXcl/n3gctezJy70aGf7+GDxp1I0HRV/6cnIWY+veE9V+Q3qkNNTq1L/OcBt4xiGVLltL/tgH8ah3IQLGDnFOLOee81SvnlJ+fT25urqp+TmrMvVA8pz+jeGsKckVRfhFCdKjgZwx4CtfWQoj0S7ZFAW4hhLVkzO9UIUTzP2tv+/btokePHhe+P3z4MC1b+rCbjyQFmMzxEJC5FDIXQrPFoKsZuDiKMyBnA+RuArcFwppCzBDPkiCa4Jwb0Fv5/eDPm9iU/jsH+95PhC44z7Wi3AU2sgffhb5DO0wj7yDv8ZfQd2pHjSmvoujK9Xdrr+j8zXySzDEsuD40xnH6w6aNn/PXZ5/HHduaDuPeYcY9iUSEXT47d/GvB8m970kin30E08g7fBNM7peQNgUSn/SsnR1g+cWFrE89xvIzB9mZlQLAjTF1GVWvFYPrNKOG3hjgCAPriCWb23auIEofxufdRpFgrPyyUG5rAdkj7kVbtzbRH7xb5gzxmRkZDLx1ADd268aLr7/Lt99OYVDDLWibzkEJq/pyafIeRfIVRVFuLms1HyjfmNvyqkyVPAD4+dLCFkAIkS+EsJZ8vRHQK4pS1nq7V1S/fv1KhCRJoUPmeAgo2APG5oEtbAH08VBrIjSbD4mTQRRD6ttw/B7IWOT1iUS8wRv5nVVoZ13qUcbUa6WawhbAseYzRL6V8HtGY+jcAfNLT1L84y9Y/z3Va+tmlkeSOYZDlmy/HS/YbdywgReeeQ53bBuun/Aus+4tu7AFsC1ZDeZIjAP7+SYYVz5kfASm1lCjt2+OUQ5Ot5uv0k9w308bSfpyDo/t/Yo0RwEvtryBX3pPZEO3kdzdsE21L2wBWphjWNZlMOcKCxj5wxryiwsr3ZYmMoLIR+7Fue83Cjd9U+Y+cfHxTPzLX9j81decOvwL+oTRuISGU0cXV/q4pcl7FCkQAj3d3Fiu0CVZUZREpeTPTIqidMYTa4UG9qSkpFQ5QEkKZjLHg5wrH+yHIcILSwB5i8YI0QOg8Syo/yoYm0HWEjj5GLgrfyPlC97I76VnDlLkdjFBRRNJicIi7ItXo+/cAX1rzxhK48C+hN83HsenX2L7aInfYmlZMmOyQ86YzIb1n/Lic39FxLXjxnvfZcaEBEz6sgtbZ/IZirbuxNHzBhSTj4q6cx95liFLfMQzu7ofCSHYm3uOF/dvo83XHzD6x3VsyTjF+AZt+PKm0fzYawLPtOhCw/Aafo0rFFxXszbzrxvIIUs243avr9LvVtjtfdFd04KCaR/gLrCVuc/dE+8hvlYt3v7vmwxoX5ut6X2op91CXl7VJ4OS9yhSIHjzalf2FfxKOytKBNAXWF3qvYcURXmo5NsRwP6SMbfvAWNEBf8crVHBVPGS9Gdkjge5gp8BN0R6cQkgb1EUzyRX9V+Gei+DMwvyy+zhEzBVzW+3EMxP3keXmnW4JqpCHX+CmmPDl7izsgm/Z8xF74ffP56w2/pge38Bjo1f+yWWJHMsbgTHC4Lvyb8/fbp2HS+98FdE/P+zd5bhUR1dAH7varK7EWJIcA0uRYt7seJFi7VIoTi0pUjRFigOxd0dSnHaYqW4F9cQAgmEENndbNbu92MpXykBNrJJSO/7PHmy2Tt35kz2ZDLnnjnnlKJG9+nM+jQAteLN2yLDjAUI7m5YGtZyjUDGqxC9H3yagzq3a8ZIgNC4WGbePk3lw6upeXQtS4MvUT5TNlaXa8K1et2ZXLwmZTNlTfCIrMT/qR2Qm3ml63HsWSjdz+3BmsR6sYJMhm5IH+wRkRiXJZzext3dnb4D+vHXpcsc2LuPgkXaYrapuH99VXKmAEh7FIm04Z1aJwjCfif7+jQxA4uiaBBF0VcUxeh/vDdfFMX5L17PEUWxqCiKJUVRrCiK4p+J6R8gc+aMkxVTQiIhJB1P5+jPgNzTcSw5PaMtC6ocELUrrSV5heTq99GIEO4YouiaOwN5ba02jCs3oihWGOUHJTl18iQPgh3FBgRBwGP4AJRlSxE7fjrm0xdcLk/hFxmTr/+HMyZv37qNEd8Oh4Ay1Os1nSnt/VHK32y8xR89gfnYKTSfdySgUMGUF0i0QfhPoPAHv/Yp3/+/iLWaWRdylebHt1Di1yWMuXYMT4WKacVrca1ud1aWa0zDLPlQydJvCaL0SMvAIH4oWp1dYXcYfPn3JIcbKIsFoW5Ul7i1W7E+SNiT2vjjjykUVIiZ06YT6OPFlbiGFPc8xl93kld7V9qjSKQFzjxS8XemI1EU/0qmLCmOdBxCIqMj6Xg6RrSD4SxoP0jXdSUBhxfXuyGYboLpVlpL85Lk6vey4MtkUrrxcdZ0/nAhEcQfOIT9cTiG5vUZ3H8A3bt0o2Obdly7chUAQanEc9JI5DkDifl6LNY7910qTz6tN3JB+M/G3W7bvIXvRoyEgLI06jONiW1832rYivFm9NPnI8+TE/c2TV2zhj/fAfH3IHNPkLmnfP+ATbTz+5Ngep7bS+H9C+lzYT/BxhiGFqzAmVpd2FulDV1ylyCTSoqjTQ4985ZmcIHyrHrwFxOuJ9rH8xJtn64IahWGGQsSvC6Xyxk0dCiPQkNZt2YtxYq3Ic7qRszDVcRbkx7DL+1RJNICZ4xbL0EQWrzpy+USJgMfH5+0FkFCwqVIOp6OMd0GW7TDK/o+4FUbBDU8Tz/e2+Tod5jJwO6wO7TPUQQ3eeplD3Ylot2Oftk6dnqpaTN2NH8cOUr3Xj3RaDR07/YZly9dAkDmocNr+jgEtZrogSOxRbjOq6qWK8ir9f5Pem43b9zE6JGjIHM5mvebyvhWvshlbz9ua1yzGfvDx+gGf4GgUKT8Gm6JgIjVjjh/XVKqM76dKzFPGXX1KMUPLKHVyW3sf3KPT7IXZnflTzhbqwvfFKpEXq1U2zQl+bZQJTrnLMa026eZd/dckvqQ+/mi+aw95j9OEn/sVIJtKn5YiSpVq7Jo/gJMcXYi1U35MPNpfj7+WhVOp5H2KBJpgVPGLdAYaJLAV2PXiZZ8rFYpwYVExkbS8XSM4TTwIq71fUCuA88aEHPYkYQmHZAc/V7z4ApW0Z6hEkldW7+FflfOMuPhHYoWK8bmn7fxZf9+LF21Ek9PT3p2+5wL588DIM+aGc/pY7FHxxAzaBSiMc5lcgV5+P7njNuN6zcw7rvRkLUibQZO5bvmPsjeEUdqC3+Ccfl6VDUroyrvWBdSfA1/stBxLDlzL8eJjBQgzGRgzp2zVDu8mqqH1zD/7nnKeGdm+QeNuFa3O9NK1KaiTzYpjtZFCILAlBK1aJwlP8OvHGHTw+tJ6se9TTPkObNjmDYf0WJJsM2AIYMx6PUsmj+fHPlaYrRpyWpZy70IW5LGlPYoEmmBM8ZtsCiK3URR7JrAVzeXS5gMYmJi0loECQmXIul4OkZ/GtwKguI9ygaaqRGI8RD9W1pLAiRdv22inRUPLlPdLwf5dWlcgikFiI+P56dZs/l0/BhCBBtjx49jwdLF5MyVC4BsgdlYtmoFvn5+9Pq8O2dPnwFAGVQAz++HY715l5jh3yNak7ZBfRdBHr7cM0T/ZzImr1+7jgljxkK2SnQeOpVhTTI5ZdgZZi4CUUTXv8fL91J0Ddefhdg/wLcNqJJXo9RgtbDp4XVandhGsQOLGXX1KCqZnMnFanKtbndWl/+Yj7MVyDCnItI7ckHGwjIfUcU3O30u7OdA+L1E9yEolegG98IWEkrc+u0JtilQsADNW7Zg/bp1PHgYAT6tqJrtAusOnU9SzK+0R5FIC5wxbt/bR3G5Xvzjl5DIqEg6nk6xRjtiV3XpqASQM7jldxjkUbshFWulvomk6vdvT4J5GBdLl1wlUlii1OfMqdN80rwlC+fNp4bcnQ3fjKBpyxavGVOZs2Rh6coVZMmSld49enLy+AkA1JXLoxvaB/OxU+inznVJDdy/Mybf0mf8uNu1q9fyw7jxkK0y3b+ZwsCPvJwybM1nLhD/6xE0ndogz5bl5fsptobb4yF8LqgCwadVkroQRZEjESH0Ob+PwvsX0vP8Xm7pIxlYoBwna3bi16rt+DxPSXzVronjlXg7bnIFq8s1oYiHL13O7OJU5KNE96GqVA5V1YoYl6x5Y7jCF19+iVKpZNb0GWgyN8UkelHLbwM/XzAnejxpjyKRFjhj3HYWBKHyv98UBKGyIAj5XCBTihH8IoOkhERGRdLxdIrhLCC+P/G2/yRTYzCHgPFSWkuSZP1eFnyJzGoNDbPkTWGJUo+Y6GjGjBzFZ527YLFYmFKiPN/mLEDWT5q98R7/AH+WrFhG9hw56PtFb4798QcA7i0b4/5pa0xbdhK3enOKyxr0MmNyxjZuV61YxaQJEyCwCl+OnMKXdb2dMmxFqw391HnIsmZG82nrV66l2Br+bBNYHkPmPiBTJvr2088f0+DYRpod38LOsDs0CyzIzg9bcb52N4YHfUgBnRQ7mR7wVKrZWLEZWdy0tD31c5LCAXQDeiBarBjmLE3wun+AP126dePAvv1cuHgNVUBrKma5wsFzZ4g0JK4kkbRHkUgLnDFuvwcSOlcQA8xIWXFSFpVKldYiSEi4FEnH0ymG0yD3dnhC3zc8qoJMly7KAiVFv0OMMewPv0fHnMVQvoelR0RRZO/uPTRr3ISft22ny2fd2PD9RErde4R7+5YI7/id+Pr5sXjFMnLnzUP/3l9y+OAhALR9uqGuWx3D7MWYDhxOUZnzab1RCLIMHXe7bOkKpkycCNmrMWj0FLrX8HT63rgtv2C7cx/dgJ4IbupXrqXIGm4OhciN4FkdtKUSdesDYzSfn91N/T82EGyMZlqJ2lyv14NZJevyoW/2d8YRS6Q+AWotWyq2QC2T0+rENh4aE3f0V54jEPf2LYjf/SuWy9cSbNOpaxf8/f2ZOulHBO+GWAUfuhTcxLT9hkSNJe1RJNICZ4zbzKIoXv73my/ey53iEqUgvr6+aS2ChIRLkXQ8HSLaQH/uRQmg97CAvUwN3vUg9jhY09YTlxT9XvnAUZWuU85iKS2Oy3kU+oi+X/Th68FDyJIlC2s3bWDgkMHY129H8PTAvXlDp/rJlCkTi5YuoWChggzq35/fDvyKIJPhMWoIipJFiR3zI5aLSc+A+m9UMjn5MnDG5MWLlzHjx8mQvTrDxk2mcxUPp++1R0ZhXLASZYUyqGp8+Nr1ZK/hogjh80BQQUB3p2+LscQz5tofVDi4kj1hdxlSoAKna3WhS67iuEtxtOme3FovNldsjt5qpuXJbTyLT1zCOG3Xdsj8fdFPmYtof90bq9Fo6NO/H5cuXmT//kMoAtpR2v8mz56c5eTdhJNRJYS0R5FIC5zZeb0tp3u6Drx4/PhxWosgIeFSJB1Ph5hugj0WdO/hkeS/8W4A2CBqb5qKkVj9tthtrHlwhToBucmhcd6zltbYbDZWr1hJi48/5szpUwz95mtWrV9HUOHCWG/dxXz0BO5tmyFonP+X6+XtzYKlSyhSpChDBw5i3569CGoVXj+ORp4lM9GDv8P6IOVqUGbUjMkLFy5h9tQpkKMmo76fTNuKzhu2AIa5yxDjTI7SPwl4QZO9hsceBcM58OsEincfHbba7Sy5f5EPfl/OzNtnaJ6tIKdqdebboEroFJKX7X2iqKc/68o3JcQYQ5tT29FbnY+JFTTuaPt+jvXaTUw7DyTY5uNmTSlYqCAzp03HrKmBqAhgUKnNjN+ld7r2rbRHkUgLnDFuzwiC8NrjQEEQPgfOprxIKYefn19aiyAh4VIkHU+H6E8DsvenBFBCqAJBUxqi9jg80WlEYvV7b/g9wuINdH2PEkldu3qNT9u248eJkyhbthxbd+ygY+dOyOWOI9XGFRsQNO64t/74tXstNpExOwxM2mPgmf5174uHhwfzlyyiRKmSfDNkKDt3/ILM2xOvGeNAJiN6wHDsz6NSZB5BHr7cN0ZjtDrv1UnvzJ27kJ+mT0PIWYvxkyfRspwuUfdbrt7A9Ms+3Ns2Q5E7Z4JtkrWG24yO0j/qfI5M529BFEX2h9+jyuHVDL18kCAPH36v2o65pesT6J44g10i/VDJN5AlHzTkYvQTup3djT0RCePU9WuiKFEEw09LsMe+Xv5NLpczaOhQQh8+ZP26TQh+7SngdZd8bmdYctQ5T7G0R5FIC5wxbgcAXQVBOCQIwtQXX4eBz4D+rhUveZhMprQWQULCpUg6ng4xnAH3IJC/5xvGTI3A+gz0J9NMhMTq97L7lwh086Bu5tyuESgFiYuLY/qPU+jwSRvCwsKYPG0qs+fPJVtgtpdtbCGhxP96BLcWjZF5veqJtosiI7cb2HY+no2n42k8K4q5B40Y4l/d3Gq1WuYuXMAH5coy4pth/LxtG/Ls2fCaOgb702dEDx6NaIpP9nyCPHwRgVv658nuKz0wZ84CFsyeiZCrDpOmTKJJKW2i7hftdvQ//oTMJxOazzq8sV2y1vCI1WB9Dlm+BOHN8eV/RT+lxYmttD31MzbRzupyTdhRqRWlvDMnfWyJdEODLPmYVKwGvz65z093zzl9nyAI6Ib0RoyKwbh4TYJtKlX+kMpVq7Bw3gKixbKgzMbX5bay7A8jd5+++8GntEeRSAveadyKohguiuKHwBjg/ouvMaIoVhJFMcy14iUPvf71J1ESEhkJScfTGdZIMN0G7XtWAighdBVA4ecoC5RGJEa/7xqiOBTxgE65iiFP57HOfx47RsuPm7F86TKaNm/G9p2/UL/BR68dWzWu2gQKOe7tm7/yviiKTNpjZO9fZvrXdmdrHy+qFFCx8IiJxrOiWHvShPkfxwY1Gg2z582lQqVKjPp2BJs3bkRZvDCeY7/GeuU6MaMnJxh3lxj+nzH5/T+aPGPmXBb9NAtZ7rpMn/4D9YtrEt1H/K4DWK/cQNv3M2S6NxvGSV7DTXfg+Q5HCIF7oQSbPDbp6XvhANWPrOFS9FN+KFqdYzU+pWGWfE5leZZ4f+iaqwSNs+Rn/LVjXIgKd/o+ZVAB3Jo1IG7jz1jvJpzZeOCQIRj0ehYuWAR+HcjqFkzD3KcZv9PwTk+xtEeRSAveuQMQBMFNEIQBQEvADMwTRfF3HyykSAAAIABJREFUl0uWAkj1tSQyOpKOpzP0LyI13ud4278R5OD9kSOez5xysZmJITH6vSL4MnJBoGPOoi6UKHlERkby7Vff8MXnPVAoFCxZsZzvxo3F08vrtba2JxGYdh7ArUl95H6vJmWZfziODafj6VTJjS6V3cjlK+fH1jpWf+5J/gA5k/caaf5TNLsvx7/cfLq7uzNr7hyqVqvGuO/GsG7NGtQ1q6Dt3wPz739gmLUoWXPLq/VCKci4rn+/jdup035i2fyfkOf9iNkzJ1KzcOINW3usHv2cJShKFEHdoPZb2yZpDRftEPaT43SIf+fXLhusFibfPEG535ez8eE1vshbhrO1utAzb2lU72EGcYl3IwgCM0vWwU+tofu5PYmKv9X26oygcUc/fX6CdbALFCxAsxbNWb92LSFReUCVkyEfbOVCiJmfz799HGmPIpEWOPN4ewVQFrgMNACmuFSiFESqryWR0ZF0PJ1hOONI6qJ+f+urvoJXfUDuiL1NA5zV73iblTUPrtAgcz6yuiUuLjI1EEWRHdu306xhY/bt3UOPL3qxaftWypZ/s4c/bs0WEO1oOr5aF3XtSRMLDptoVkrFwLrur3jgigUqWNjJg7kddOjcBL7daqDdwhiO3TYjiiJqtZpps2dSs3YtJo7/nlXLV+DerjnunzQlbu1W4jb+nOQ5KmVy8ukyvbeeW1EUmTxlFisXzUWerwHzZ02gSkG3JPVlXLQKMSoG3ZDe7/SQJmkNj94PpusQ8Pkr4Q92UWRdyFXKH1zOxBsnqB2QmxM1OzG+aDW8VUmbi8T7QyaVGwtK1+euIYpvrzhf7kuWyRttj05YTp7DfOR4gm169+2LQqFk1oxZ4NcRD1koX5Q+wfQDxrfWvpX2KBJpgTPGbRFRFDuKorgAaAVUc7FMKYabm7SYS2RsJB1PR4g2MJwHbVnIKEf+lL7gUQmiDoA9+XGZicVZ/f7l8W0iLSa65i7uYokSz4PgYHp0+4yRw4aTJ28eNmzZQp9+fVGr1W+8xx4VTdy2Xajr1UQemOXl+7suxTN5r5GaQUpGNNEmaDgJgsCH+VWs6+HJ9y206E0ifdbo6bEylr9CrahUKn6cPo269esxZdJkli5ejHZgT1TVKqGfNp/4N2xunSHIw+e9NG5FUeSHSTNZs2QByvyNWPzTBMrnS9raar1zn7hNO3Br1gBlUIF3tk/0Gm6NhidLwb0YeNZ6+fbRiBBqHVlLnwv7yeqmY/eHrVlRtjF5tG8reCGR0ajil4OB+cux+sEVtj+66fR9bi0bI8+bC/30BYjxr3tj/QP86fpZN/bv3cfFOxpQ56NLoa3EWyxM3W98c7/SHkUiDXDGuH2Z+lAURasLZUlxvL2lRV0iYyPpeDoi7jrY9Q7jNiPh3chR2ij2aOoP7aR+Lwu+TB6NF9X9Es5ImxZYLBaWLFpEq6bNufrXFYZ/N4plq1eRv0D+d94bt2E7mOLRdG7z8r0jN81897OBcrkVTGypQyF7+wMUmSDQsLia7V968fVHGm4/sdFxcQxDNsXyKEbGxCk/0rBxI2ZNm8GC+QvwHP8NiqD8xAz/AcvVG0mac5CHL8HGGAzvUcZkURQZ/8N0NqxYhLJAE5bNG0+ZXG9+8PCuvvRT5iJoNWi/6OrUPYlew58uBXscZOkDgsAtfSQdTu2g6fEtRFpMLCrzEfurtKWib2ASZiCREfi6UEXKeGdm4KXfeGiMceoeQSFHN+gL7I/CMK7ZnGCbTl274O/vz9TJUxH9OqK0hzGxznF2XTJz4g21b6U9ikRa4IxxW1IQhJgXX7FAib9fC4Lg3F9NGhEWlq7zXUlIJBtJx9MRhr9LAJVOa0lSFk0JUOWA57tSfWhn9Pta7DOOR4bSOVdxZOnEY37p4iXatfqEWdNmUKVaVbbt+oVP2rZBJnv3v1y73kDcxh2oalRGkdcRr3b+gYWhm/QUzCxnelsP1Arn56mUC7Sr4MbOft70rO7GsVsWWvwUzcS98fQfPoEmTT9m3pyf+GnBQjynjEHmm4noQaOwhSZ+bQnSOWKDb+ojE31vWiCKIqPHTWXzqiWoCzVl1fyxFM+e9Fqv5t+OYjl7EW2vLsi8nauznKg13HgFog+ATwueEcA3fx2i8qHVHH32kFFBlTlZszMtA4PSzd+BRNqglMlZVKYBNrudnuf3YROdSxanKl8aVa0qGJevxxb+5LXrGo2G3v36cvHCBX49FgVuhajht5U8vjYm7DRgsrweryvtUSTSAmeyJctFUfR88eUhiqLiH6+dW73TCH9//7QWQULCpUg6no7QnwH3IiBPXMmQdI8gODKymm44MkGnIs7o94rgy6hkctrnKJIKEr0dg8HAxAnf06lde6Kjo5k+exbTZs0kICDA6T5MW3chxurRdHF4bW+EWem7Vk8WLxlzOnigUyfNcNGqBb6ooWFnP29al1Wz/Xw8zebGkrnOcJo0b8mi+QuYtWwpntPHgtVK9MAR2GNiEzXG+5QxWRRFRo75ke3rluFWuBlrFoyhcLakG7ZinAn9zIXIC+TFrXlDp+9zeg0XrRA+h3hZALOjC/PB78tYfO8in+YsytlaXRhQoBzuckUSpZfIaOTRevNj8Vocjwxlxq0zTt+n69cdRBHD7CUJXm/avBn5CxRgxrTpmL3aIVifMr3+MUKe21mcQO1baY8ikRak73oJycRgMKS1CBISLkXS8XSCJQLi74IuA5QASgivOiCoU917+y79NlgtrA+5ysdZ8+OnTnxW25Tk0MGDNG/8MevXrKVN+3Zs27mDWnXenin334imeIxrt6KsUAZlkUKERNrovToWrVpg/qce+GiT/y/bVyfjm4ZatvXxokYhFUuOmTnq1Z9SNVuzfOkypq9bi8ek77CFhhHz1VhEs/NZV/NqvVHJ5OneuBVFkWEjJ/LLhhVoirRgw8IxFMisTFafxhUbsIc/dSSRkjufkdjZNVx8tp3tESYqBlfgu+snKO+TjaM1OjK1RG3801j3JdInn2QPolVgISbePM7p54+dukeeLQuaTz8hfv8hzOcuv35dLmfQV0N4GBLChp+vgXtxcrOJ5iVFlh8zcfvJq9GL0h5FIi3I0Mat0fjmIHcJiYyApOPpBMOLEkAZLd72b+Q68KwOMYfAlnp1C9+l39se3STGaqZLrrRLJPX0yVOGDBhI/95f4uHhwcq1axg2Yjg6XeKzNpt27keMfI6mS1uexNrptSoWmx3mdfQgq1fKlnDJ4SNnYksd63p4UjibkgsBfdEWa82aVav58ZftaEcMxHLuErHjpjldA1chk5Ffm74zJouiyFfDv2fPltXoirVm06LvyO2XPI+nLfQxxtWbUNeviap04nTRmTX8zNNrNDh/hW5hJdEqdWyu0JyNFZpR2MP3nfdK/HcRBIEpxWsR6OZBj3N7iLE4lxRQ06k1siwB6KfORbTZXrteuUoVKlX+kIXz5xOtag625wytcBCtWmDCLuMrtW+lPYpEWpChjVupvpZERkfS8XSC/jQofEGdO60lcR2ZGoEYD9G/pdqQ79Lv5cGXKKjzoZJP6ifPsdvtbNqwkeaNm3D44CH6DRzA+i2bKFGqZJL6E61WjKs2oShemLjCxei9OpZIg505HTzI6++62qSFsyqY/6knCzp5kqvOAAhqz6YNGxi05yBuvToTv+8gxvkrnO4vyMOHG7HpM+ZWFEUGfT2e/dvW4lHiEzYvGkF2n+Qf5dVPnw9yOdq+nyf63rfp+ANjNJ+f3U29E/u4b3FnRtHyHK7egVoB0rov4RyeSjULy3zEw7hYvrp80Kl7BDc3dP17YLt1F9P2hMvADRo6hNiYWBatPALaMmj0mxlaV+D8Ayvbz//fiJb2KBJpQYY2bqX6WhIZHUnH0wGiFYznQVsu45QASgi3AuBWEKJ2g/h64hBX8Db9vhj1hHNR4XTNVfydtURTmrt37tCtU2fGjx5D4aJF2Pzzdj7r0R2lMulHW+P3HcT+OBxFx7b0W28g+JmNGW09KBaYOnGUFfMqWdPDi0njBuP5QWeOH9jGx7vPEVO7Lsbl64l7wyb33wR5+PIgLga91fnjzKmB3W6n39Cx/P7LerxKt2ProhFk9U7+7zb+z9OYj5xA26098gC/RN+fkI7HWOIZc+0PKhxcyZ6w2wz2ucPpsjnolPdD5EKG3rZJuIDyPtn4qmBFNoZeZ+PDa07do6pVBeUHJTDMW449+vXcsQULFaJZixasW7OGh6a6YIuhUY49fJBLwfQDcTzTO057SHsUibQgQ6+SGo0UhyKRsZF0PB1gvOoozaHLoEeS/4l3IzCHgPH1WCxX8Db9Xh58CXeZgjbZC6eKLABms5l5c36idfMW3L19h7Hfj2fh0iXkyp0874Rot2NcsQFZ/jx8E1qEyw+tTGypo0Le5MWBJhaZIPBRMTd+XzGUai16EXllDy3PBXMrVwliJ87CfPzdiWn+TiqVnjImhz95Qq9+IziyayOZPujAtoXDCPBMvjdcNJsxTJ2HPGd23Ns1T1If/9Rxq93O0vsXKfv7cmbePkOzrPk4me8Kw7Oa8fBvlWx5Jf67DCpQjko+gQy5fJD7huh3thcEAd3g3oh6A4aFKxNs07vflygUSmbO3QG6igiRWxnVUCTOLDLlRe1baY8ikRZkaONWq81gWUslJP6FpOPpAMNpQAGaUmktievxrAYyHUTtTJXh3qTfMZZ4NofeoHlgQbxVbqkiy4PgYDp80ob5P82l3kcfsW3XLzRt3jxFvMbmw39iux/CjsLNOHbHyojGGmoXTnrm3uSilAvMntCX3v0HIj74nf7RsdzSBvJ06DjCz789Y/bfxu3l6KepIeor2EWR0CgbR2+ZWXDgKZ1HrOPD+p2pV6M2J3/7Gb/yndi+8Gt8dSlzzDtu3TZsIaHoBvdCUCXt89JqtYiiyIHwe1Q5vJohlw9SyMOH36u2Y16OCLITApl7g5C6DzokMhZyQcaC0vWRAd3P7cFifz2W9t8o8ufBrWVjTFt2Yb1197XrAQEBdOnWlf1793IxtCzYDeQSfqZbFTf2XDbz5x2LtEeRSBMytHH79Gnq/3OVkEhNJB1PBxjOgKYoyP8DT6hlavCqC7HHwep6z9yb9Htz6HUMNgtdc5VwuQzgyITcvnUbwsPCmT1vLj9MnoSvb8ok8xFFEeOy9UT7ZGW2rSz9a7vTokzqGOzvomevzxny9VeYQ44yyRMiBDci+49k4ZYHxMQlnGQqj9aLALWGQZd+o9nxLax+cMXpRDbOYhdFHr0wYpcfi2Pkdj0dFkXz4fgwGg7ZwZe9BzB3QD0ubBmPNeYxxep2o/fkLexY+BXempQxbG1PIjAsXYuqWkVUlZKeJf34wzu0OLGNNqd+xibaWVW2MTsqtaKUuwUiN4NnTdAmLY5bQuKfZNd4Mr1kHc5GhTH55kmn7tH2+BTBQ4d+6jzEBMJROnftgp+fH9NmrkHUVYbnP/PZh2Zy+cr4fpeB0MfSHkUi9cnQRdGyZMmS1iJISLgUScfTGMsTiA8G/7ppLUnqkakhPN8GUXvBr71Lh0pIv0VRZOn9y5Tw9KeMd2aXjm+z2Zg3ew6LFiykSNGiTJk5ncDAlE1eZTl1Duv1Wywp3p1PK2voWsU9RftPLp926YxSqeSH8ROYXfIDvg2JosTccbS+Npp2NX1oW94NN+X/vddyQcb+Km1YG3KVzaE36HfxAEMv/079zHlpHViIOgG5UTtZj9UuioRF27nz1MadJzbuRrz4/tRGnMXRRrTb8NJfRPXwANabh8CkxzOTL/XafEKzZo0oVtw1MdmG2YvBZkM3sFei77Xa7Zx6/oi1IVdZF3IVb6Ub3xetTrfcJVDJ5I6Y9vC5jvJbAYlPUiUh8SaaZyvI70+CmXbrFDX8clLZL/tb28u8PNF+0QX9xFnE/3oEt7rVX7mu0Wrp068vY0Z9x28XG1En33HU0VsY0agT3VfGsvd+AMWLunJGEhKvk6GN26ioKLy8vNJaDAkJlyHpeBqjfxGDmIh4W3tUDObjp1HXq5GoepjpBlUgaEo7jFvfNiC4bg4J6ffp54+5GhvBtBK1XZpI6vnz53wz5CtO/PknLVq15JsRw1Gr1Sk+zr1Za7G5+eDesDYD6qQvw/Zv2nZoj0KpYPzosUwsUpQRD0MYc2EGfSxDWXcqni9quNO4pAqFzPF55NR48U2hSnxdsCJno8LYHHqDraE32PH4Ft5KNR9nLUDrwCAq+QYiEwREUeTxCyP27lPbS2P2XoQN4z/yUvnpBPL5y2laSoXWcIuQC/s4e3QfEU+foNVqafBRHRo0bkT5ChVQKFy3vTGfv0z8voNourVHHpjVqXsMVgsHnwazJ+wO+8LvEWkxoZLJ6eCXn7Ef1Hn1eH3sETBecBxHVmRy0Swk/qv8UKw6JyJD6Xl+L39U7/jO0A63ph9h2roLw6xFqKtWQHB7tX3TFs1Zs2o1M2atpPrCmiif76RcvuY0LaVi3dl4ahezUCaXdKxeIvXI0MatyWRKaxEkJFyKpONpjOEMKAJAlcP5W+Ytw7RtN/H7DuIxfhgy3XsYk5SpEYSOB/0p8KjksmES0u/lwZfRKVS0DCzksnGv/PUXg/sN4NmzZ3w3dgwtWrsmmc/hrRcocusvDtTowrfNvVM963NiaPXJJyiVSr4bPpLv8uRlTPAFNuVbySjd54zeYWDln3H0ra2hRiHly3kIgkDZTFkpmykr44tU49DTYFbcu87GkOusfPAXOlFLgDEv9ke5scf+34jz0wnk9ZfTtJSafP5y8gXIyesvJ/pJCLt37mLP+t3cv3cPhVJB1WrVaNi4MdVqVMfNzfXHuUWbDf2Uucgy+6Pp0uatbcNNBvaF32NP+B0OP32AyW7DS6mmXkAeGmTJSy3/XDy+e/9V48JmgPCFjuzk3g1cPBuJ/yI6hYpFZRpQ/48NDLj0G8s+aPjWtUeQy9EN6U1Uj8EYV25E26PTK9flcjmDhg6md49ebPxdS4dKFni2ka8+6smJ23F8u9XAxl6eeLpn6EhIiXREhjZupfpaEhkdScfTELsFDBfAq7bTJYDsBiPx+w4iz5cb88lzRH02AK9pY532/qQbdBUcdX2jdrnUuP23fj83m9j26CYdchTFQ+GahEtbN23m+3Hj8fPzY/maVRQtVswl4xy5aSZm6QYMbh60GNnspdczPdO0eXMUCiUjvhnGiCzZGPf7PhYUzMrx1q2Z/buRgRv0lMyhoH9td7J6y7jz5IUX9oVH9u5TL4zmCvjJyhDnFYLF/x73tH8hFrhMdoUvDfwK0jlfEEV8/u+tfxYRwd49e5mycyd/XbqMIAh8UK4snbp0pm79enim8skV07bd2G7dxfP74a95sERR5Kb+OXvC7rA7/A5nn4chAjncPeiUqzgNs+Sjkk82lLL/n3ZQ/XsNj1gFtijI/p1LT0VI/Lcp5Z2Z4UEfMvraH6wOucKnOd++zilLFUNdrwbGlRtxa1QPeeCrISMfVqlCxQ8/ZMGCtTSp3AzPqN1ofVrwQwstPVbHM3angR9b6dL1AzyJjEOGNm6Dg4MpVMh1T/clJNIaScfTkLgrIJpA6/yR5PgDhxCNcXgM64cYbyFm2Died+2P56SRqEoXd6GwKYwgd3iVIlaD+RGosrlkmH/r97qQq8TbbXTJlfK/K5PJxA/jJrB961YqVf6QH36cTKZMrjkSei7YwtzFV5j95ByKzzvh5pE+jyMnRKMmjVEoFAwb+hXDvH2YMH85VbJlofoXtfj5QjwLDsXRbXnsK/f4agXyBcj5uKSafAFy8vnLyevvj7emLE/jjWx/dJNNoddZFHacxWHHqajxpdj9GJ79eY6zJ05ht9spVDiIQUOHUL/BR2TJmjYPg+xR0RjmL0f5QUlUtasCYBPtnI58zO7wu+wJu8MdQxQApbwC+LpQRRpmzkdRT783bupf0XHTbXi+E7wbgnvBVJmTxH+XL/N9wMGnwQz76xAVfbJRQOfz1vbavp8Tf+Q4+lkL8Zo06pVrgiAwaOhg2rRoxaItcQxuATzbgNZcjz41czLztzi2nY9PN8nyJDI2Gdq41el0aS2ChIRLkXQ8DdGfBkGRqEympq27kefLjaJ4EQRBwHvJTGIGf0d0n2/w+LY/bo3ruVDgFMarPkSshag9EPCZS4b4p36LosiK4MuUzZSFYl7+KTpOaGgog/sN4NrVq3Tv1ZMvvuyD3EXx0DfCrPRbp2fY/R2gccer7ccuGceV1G/wEQqFgq8GDeZrdy0/jPmRHP6+tCpbikYl1PxyIR5B4IURK8db8+bjiP5qDd3zlKJLYBE2H9jH2m1beHDqPA8tVqw+HmRrXJ02TVvQsUI13JxMROUqDPOWIxqMyAb1YE/4XXaH3WF/+D0izHEoBRlV/LLTK29pPsqcl0B3D6f6fKnjog3C5oDcE/w7u3AWEhIOZILA3NL1qXpoNd3P7mFflTZvTfYmz+yPpms7jPOWYz51DlX5Mq9cLxQUxMfNm7Fu3Tba1G9LdnE/XtoqdK7sxvG7FibvNVI6p5I8ftKJBAnXkqEPwKdG/I2ERFoi6XgaYjgD7sVB5txnYLl2C+v1W7g3+398kyJXdryXzkBZuhixY6ein70Y0fbu+oPpAqWv40hy1H6wp2ypl7/5p34fe/aQW4bnKV7+59jRo7Rr2ZqHISHMnDuHL/v3c5lh+yDSRu/VseQ1h1HuwQncWzVB5umcEZTeqF23DtNmzeSuychX8ZGEDBmF9W4w7kqBT8q50bqsG2VyKd9q2Nrtds6cOs3YUd9Rq1p1Jg75htirt2nTujUjFs7m4/kTCaldgq+eXSJo/0L6XTzA0YgQ7AmUJHE1j/76i9X3LvFlvwYUvrmXjqd/Yefj21T3z8niMg24Vb8nWyq24LPcJZ02bOEfOh61D0w3HdmR5dJDS4nUIaubjlml6nIp5ikTbhx/Z3tN+5bIArM6SgNZra9d79OvL3K5nFmrQkGQk8m6C5kgML65DjeFwDdb9Jitqf/3K/HfIkN7biMiIlKsFqGERHpE0vE0whwG5pBEJXwxbd8NahXqBrVeeV/m6YHXzAnop8wlbtUmbMEheI79BkHzHhxV9W4Esccg9g9H7HEK80/9XhZ8GS+lmmbZUua4pt1uZ9H8Bcyb8xMFChZg6swZ5HRhDPuTWDu9VsVis8MPlj0ISgWadi1cNl5qUL1mDWbOncPAPn0ZHBnKj32/Id+Kn5D5vfl4oyiK3Lh+nT07d7Fn9x7Cw8Jw17hTq3YdGjZuRIVKFVEqHZlVWwPjilbjSEQIm0Ovsz30JqsfXCGrm45WgYVoHRj01iO/yeWWPpI9YQ4P7enIR4hNihOodqdj1vw0yJKPD30DHaV7kkFERAS+XnJ4uhw0JRx1bSUkUpGGWfLRLVcJ5tw5S03/nNT0f/M6KKhV6Ab2JGbIaOI2/4KmbfNXrmfOnJlOXbuwcN58OjbtQIksf4DxMgEexRnTVEv/9Xpm/WZkSP33MJGixHuDkFBR5veVI0eOiNWqVXv5c0xMDJ6enmkokYSEa5F0PI14vtNRhzLvQlC9vU4gOBJJRTZqj6pmFTy/G5JgG1EUMW3agX7afOT5cuM1dQzyLAEpLXnKIopwryfIdJB7Wop3/7d+P4k3UPzAEj7LXZLvi1V/943v6jc6mm+/HsbRw4dp1KQJI8d8h7u76x4mxMTZ6bY8lkdRNhY3NOP/xWe4NW+Ax9AvXTZmanLyxAn69epNgNXO9GLlyLdsNoL7qycaHoaEsGfXbnbv3MndO3dRKBR8WKUyDRs3pnrNGmg0mneOY7Ra2BN+l82h1/ntSTBW0U6Qhy+tAwvRKjCIHJrkrYU20c6Z52HsCbvDnrC73DI8B6AYbtQ8fJnG1etRtvHHKWpMx8TE4KlfDDGHIM8cUOdMsb4lJJzFaLVQ++g6oiwmjlbviJ/6zX+PoigS3X841r+u47NlKbJM3q/2ZTDQ+KMG5MiRnaWjFcgV7g7dFpT8sNvAhtPx/NRBR+X8rkkKKPHfQBCE6qIoHknoWoY+lvzs2bO0FkFCwqVIOp5G6E+DMgsoA51q/nciKffmb/b0CoKA+ydN8Zo+DvujMJ536Yfl8rWUktg1CIIj+Y3pOpjupHj3f+v32gdXsYj2FEkkdf3aNdq1bsPxP4/x7cgRTJj0g0sN2zizyJdr9QQ/szG9jQc5f9sOooimY+uUGcB42fGwJeYQ6M9C3A1Hki9bjCOOMxWoULEicxctJEIho9/lU9wePBLRZuPZs2esW7OGTu060KjeR8yZOQtv70wM/24Uvx05zOx5c2nQqKFThi2ARqGkZWAh1pVvyrW63ZlSvCZeCjXjrv9Jyd+W0ujYJpbfv8Rzs/Ml0uJsVvaG3aXfxQMU2b+YBsc2MvfuebK5ezCpWA0uVGrH1p8OMSBSQdlGTVLcS2x4egJifgXfFpJhK5FmaBRKFn/QgChLPH0vHuBtji9BENAN6oUYZ8Iwb/nrfWm19OnblwvnL7LtRGHHKafIrQAMrKshf4CckdsNPNPbXTUdif84Gdpze+PGDSmTrESGRtLxNMBuhlttwKseZPnCqVued+6LaDaTae18pzbH1nsPiB40CvvTCDxGDMLto1rvvCfNsMXC7U6O45RZ+6Vo1zdu3KBAwYKU+W0ZOTWe7PgwefVmf9n+M+NGj8HL25upM6ZTopTzycCSgsUmMmC9nuN3LPzYWkfNLEaeNe2Euna1N3rwE0XscQidALxlkyjTOmI4ZTqQezheyz1e/Pym1x4gc3e6xNXfXDh/nt5dP8PDbCWXrx9nnkdgs9koULAgDRs34qOGDckWmPKZtYON0Wx+eINNode5qY9EKcioG5CbVtmDqJ85L+7/SpLzLD6OfU/usifsLgefBmO0WfFQqKgTkJuGWfJSJyA3XkqH51k/cyFxa7fivWwmyiJSQBYSAAAgAElEQVQpvNaKFuJv9ECtECHvfKfj9yUkXMWCu+cZduUwk4vV5PM8b18f9TMWELduG97LZ6MsXOCVa1arlU+at+TZswjWzKxKds/rkGceqLJy+4mVDotiKJtbyez2OmRSeSCJJPA2z22GNm5NJpOUcEciQyPpeBqgPwsPR0L2MaAr987mluu3iOr0JbrBvXFv09TpYexR0cR8PQ7L+ctourVH0+NTBFk6PWzzeAbEHIb8q0GecrFUJpOJP2LC+OTkdhaXaUCLwKQZF2azmR9/mMjG9RsoV6E8k6ZOcXmsul0U+Xargb1/mRnVREOLMm4Y5q/AuGwdmdYvRJEnmV66uOvwYBioc0Pgt2A3OR402PWO7zb9q69terD/67X4ekKY/yP7h1H8D8NY9vbXf10N5ouuPXGLt1Bb40njnp9T9LNOqVLfUhRFLsc8ZePD62wNvUFYvAGdQkWTrPn5OGt+bumfsyfsLicjH2FHJJubjgZZ8tIgcz6q+GV/LX7Weu8Bz9v3wq1RXTxGDEx5gZ9tgqfLIPA78KiQ8v1LSCQSURRpc+pnjkaE8FvVdhTx9HtjW7veQGSrbsgDs+K9ePprf+O3b92ma8dP8fb2YPk4d3yzlnT83xQENpw28cNuI0Pqa+hYUdrDSCSe/6xxK3m1JDI6ko6nAeHzIWovFNgAMvU7m8f+MBPT7l/x3bU20ZlxRYsF/cTZmH7Zh6pWVTxHD0FIjw8zTLfgfn8I6AU+KVfa5saNG4yLvsGp54/5q+7nSUreE/b4MYMHDOSvS5fp8lk3+g7oj0Lh2lyKoijyw24jG8/E07+OO10ruzs2gh9/irJ8abwmjkzeAOZQCB7sMChzTQWFV1KEBDH+hbEb+w5D+N8Gs563eYvjLXLkynzE748hbmsoyjIV0A3rj9w/9ZLf2UQ7f0Q8ZGPodX55fBu91QxAMU8/Psqcj4ZZ8lLSK+CNRrcoikT3+xbrlRv4bF6KzMc7wXZJIv6+42FQ5HZixQJ4BE1Oub4lJJLJ03gjVQ+vxlflzq9V27128uGfmH7ZR+y4aXiM+Qq3Bq8nFdzx889MGD2WfLl9WTRKhjbfCPCsgiiKDNyg59htC6s+8yQoa4bObyvhAt5m3GZobZIS7UhkdCQdTwP0ZxxZTZ0wbO0GI/H7DqKuUz1JJV8EpRLdiIHI8+bCMGsRUY/C8JwyGnnAm5+mpwluBcCtIETtgkxNEn2c9U0Y3RTsvXmPfvk/SJJhe/L4Cb4ePASz2czUmdOpUy916gjPOxTHxjPxdP7Qja6VHfG8pi07EfUGNJ3bJq9zaxSEjHK8zjE2aYYtOD4jwc1xFFaZSH0S7WCP+5cRHPvS8FVbn4P+FIp6YWjqKDFfPINhcjdUtXqh/uijVPHiygUZ1f1zUt0/J1OK1+L4s1Dy67zJqXHu92U+9CeWk+fQDv4iZQxb82OIOQKxhyA+GJCBtjRGWTvez2JQEhkVf7WGOaXq8cnJ7Yy+epRJxd+cwVvdqC5xW3ZimL0YVbVKyLSvxs+XK1+eSdOmMKhvfwb96MmckfNQassgyDV897GWT+ZH880WPet6eOGuko4nS6QM6fSMW8rg6qfzEhJpjaTjqYw5FCyPnDqODM4lknoXgiCg6dASzymjsT14SFSXvliu3kxyfy7Du6EjcYjxcop1ue3ZfUREOuVMXCIpURRZumgxvT7vTiYfH9Zu2pBqhu3akyYWHjHRrJSKAXUchq1oise4bivKih+8FpuWKOwmeDgarJGQfTSoUj5+1SkEmeP4uSozuOUHbSnwrOoojeXbGjL3gLyLINcMBN+mqMp44/mZBVWWWVh2dsL26Pd3HIlOWdzlCmoF5HLasBVN8ehnLECeLzfuLZskfWBrJERuh/sD4e5nELHCEQOd+QvHEf4c45Cp/JPev4SEi6gTkJsv8pZm0f2L7Au/+8Z2gkyGbkgf7BGRGJevf+26QqGgRs2ajBo7hhPnnzNy+i3sT1YCkEkjY3wzHcHP7Ezea3TZXCT+e2Ro4zYyMjKtRZCQcCmSjqcy+jOO79qyTjU3bduDPF9uFMWLJHtoddWKeC+eDkolUT2HEP/b0WT3maJ4VnMck43alSLdWe121ofdpKZ/LnJrnfdO6vV6BvUbwMxpDk/tmg3ryJ0nT4rI9C52XYpn8l4jNYOUjGiifemhNP2yDzEyCk2XdknvXLTBo0lgug3Zvgb3oBSS2kUIArgXhMzdEQquQgycgN0QhCLbM+QxUxCvtkEM+wmMVxye4HSEcdUm7I/D0Q3pjaBI5IkBW6wjbOHBMEeitScLQbSAf1fItwxyTXGcblA4vMHSGi6RXhkVVJlinn58eeEAYSbDG9spiwWhblyXuLVbsT4IfeXa3/rdrEVz+g0awJ6jBqZMW4EYdwuACnmVdKnsxrbz8Ry4anbdZCT+U2Ro4zYw0LkyHRIS7yuSjqcyhjOgCgRV1nc2tVy/hfXaTdybNUyxY5iK/HnItGwWikL5iBk2HsOStW8t2ZCqyNzAqw7E/unwWCWTfeF3ibDF0zUR5X9u37pN+9ZtOHzwIEO+/orJ06ag0aZcgqu3ceSmmVHbDZTLrWBiSx0KmeMzF61WjKs2oShZFGXpYknrXBQdsd76kw6vn0fFFJQ8FRDkCB6lUVSZjt33J/TbAok/bYCIPfBgKNzpCk+WgemeY65piO1RGMaVG1DXqYbqAyezadtNjlJMD8fArQ4QNgssT8G3LeSZ76jx6dsalJlfu1VawyXSK2q5gkVlGmK0Wuh9fh/2t/xt6np3Q1ApMcxY8Mr7/9Tvbp9/ToeObVizM4Zls4e8LFXWu6Y7RbPJGfuLgcfRqVO+TCJjk6GN2/Dw8LQWQULCpUg6norYTWC8BFrnjiSbtu0GtQp1g5Qt4yPz8cb7p0moG9TGuGAFsSMnIpriU3SMJJOpIWCDqH3J6sZitzHl1ikCFG7Uz5zXqXv27NpNhzZt0etjWbRsKZ926ZwqsZ0A54ItDN2kp1AWOdPbeqBW/H/c+L0HsYc9QdOlbdLlidzk8Ij7tIZMjVJI6rRBkTsP2q/mY1d259kAiF2uxBajQ4zcAvf7wL3eELEBzGFpIp9+5kIQBLT9u7+9oWiB2JMQOglutYNHkx1e9UxNINcMx7Fs/47vrF0rreES6ZlCHj5MKFadQxEPmHf3/Bvbyfx80HzeAfMfJ4k/durl+//Ub0EQGDJsBA3qlWXmsttsXz0WAKVcYGJLHTa7yPCtBmz2dPLAVuK9Jc2MW0EQ7guCcFkQhAuCIJxJ4LogCMIsQRBuC4JwSRCEMokdw25PX0edJCRSGknHUxHjZceGVvfuI8miMS5ZiaTehaBW4TF6KNo+3Yjff4io3l9hj0gHxxtV2UFTynEsU0z6E/jpt09zMfoJgzIXQfGO8kcWi4Uff5jIN0OGElQ4iPVbNvNBOeeOjacEN8Ks9FunJ6uXjDkdPNCp/2/AijYbxhXrkRfIi+pD5x6KvEb0QXi6HDxrgH/nFJE5rRHkcjQdWuK9ZB7Wp3mI7HWb2NUlsGs7O8oKRayAu93g/iCI3AHW56kil/nkWcwHj6Hp0hZ55oDXG4g2MFyAxzMdHtrQMWA8D161IOckyLcCMnd3HMd28kGGtIZLpHc65yxG4yz5GHvtDy5FP3ljO/dPmiLPlR3DtPmIFgvwun7LZDLGTV5ExTL+jJ24mcO//QJADh853zbUcu6BlSVHTa6bjMR/grT23NYURbGUKIoJ7UQaAAVefPUA5iW2c+m4j0RGR9LxVER/GgQ1uL/7aKlp/8FkJ5J6F4IgoOncBs9Jo7Devsfzrv2w3rzjsvGcJlMjsD51/L6SwMWoJ0y5eYpWgYXoGPR2I/Xpk6d079qN1StX0eHTjixevoyAgASMEhfxINJG79WxaNUC8z71wEf76r9U8+E/sQU/TLrX1nABHk93ZOfOMtCRyCkDociVA++FU9H270784ctEdt2I6VoDxLzLHDGqohmezIfbn0LICIg6ALY3x/4lB9FiQT91HrLArGg6tPrHBdFRUzh8AdzpDCHfQuwRR1K57GMciaGy9AVN8SR9PtIaLpHeEQSBGSXr4KfW0P3sHgxWS8LtlEp0g3phCwklbv12IGH9VqpVTJuziKC8ar4aPJwL5x0e4UYlVDQormLB4TguhCQ8hoSEM6Tn/5RNgZWigxOAtyAI7w50+wchISGukUxCIp0g6XgqIYqOeFtNSZCp3tk8JRNJvQt1zcp4L5oGosjz7oOIP/yny8d8K7qKoPBNUmKpeJuV3hf24adyZ1Kxmm/V73NnztK2ZSuuXb3GxCmT+erbYSiVyuRIniiexNrptSoWmx3mdfQgq9eriYdEUcS4fD3yHIGoa1VJ/ACmexA6HtSBEDgCZKk3t9TE4cVtRabVc5HnykHsqEnEfDsPu1jbEauaZ54jXtX8CMKmw+32EDoBYo+BPeUS0MRt/Bnb/RB0g3ohqFWOWrRPVziyHAcPcuizWxBkGwb510C2oQ4DV0hexnppDZd4H/BRuTO/dH1uG54z/MrhN7ZTVSqHqmpFjEvWYIt49kb91mYqwOxpXxDgI9C3V09u37qNIAgMb6Qli5eMYVsMxJikUw0SSUM+evToNBl4zJgx/YHWY8aM6TFmzBhGjx599l/XewG7R48e/eDFz82Bk6NHj370z3aCIPQYM2bMgjFjxvTQaDTZ8ufPj0ql4tGjR4SHhxMQEMCdO3ewWCyYTCYePnyIm5sbISEhPHv2DHd3d+7evYvNZsNgMBAaGopGo+H+/ftERUWhUqm4d+8eoigSExPDo0eP0Ol03Llzh9jYWORyOffv30cQBJ4/f87jx49fXjcYDAiCQHBwMDKZjIiICMLCwl5ej4uLw2az8eDBA5RKJeHh4YSHh7+8Hh8fj8ViISQk5OWcnjx58vK6NCdpTvfv30er1Wa4OaW3zynk7kky2fcSo6zF/TDVW+cU/udJVBt/Qd+4NlEBvqkyp1CjAc8m9TGfPo954w6sMoFgjSqNPicjbio7CsNvRNnL8DTS5PScvj61l9+iHzG9YFW0kXrkcjnR0dGvfE5ms5k1K1cxavgIfHx9GDlmNHny5k1V3bsXGkHfDWaexwl8U+052bTG1+YUeeAQyh37if2kMcZsmROle48eXEIbOQFBpuSupQcWUZuh/p4S+pweRD3HVKU82gB/zDv2EbdtF7EqBaFumdBlrsKdyKKYlcVRuelAfwZZ7K/Yn/1MTMQ1ZHI3bgfHYDAYkzQnjcmM/tsJCFULoKirwP54DoqoDYhxVzHasyH4tuWusSlm96qYxAAehoal2N9TdHQ0Hh4e783nlBF1T5qTc3PSGi0YzPGsDLuBV2w8mW3yBOeUqfwHxG/+BcPDx8SVLEJkZGSCc1Logqhf8hK//PaY3bt+pVDhIGwWExUKerHhjIU7j+MoHRArfU7SnBKc0/Tp05ePHj06OCEbU0irTJuCIASKohgqCEIAcADoK4rikX9c3wlMFEXxjxc//wZ8LYria/G5f3PkyBGxWrVqL38ODw8nc+bXsxNKSGQUJB1PJSK3wZNFkHeZo7bnW4j9YSam3b/iu2utS+Jt34Zoiid23FTiDxxG3aguHsP6Iaje7WlOcSwRcKcL+DSHgM+cuuVU5CMaHttEh5xFmVmyDvC6fhsNBkaP/I59e/ZQs3Ztxv0wAQ+P1P0dx5lFeq6K5dpjK3Pae1Ahb8Ie1aieQ7CFPsZn23KExHiUbQZHBmFLOOScAm6pU8YoPWENDvkfe+cdHlXRxeH37m62phdCEnrvXRBBQBFQsQAK2BtNEVCKIjbAhqJUKQIKilgQUSyAfiAIio0aegk9AdLb9na/PzYEQjpkU5Z5n2efbObOzp1Lfszdc8+Zc8ieOgPn/kOou99EwMTRKMJDL3WQXWCOhawtOR5cMyhDPLV2A3uAtnGJ97ziTMP6zRSUQXH41c9p0zX1jBPQFVQhZXx1eRFruKAq4XC7uGPbN5wwZbC1+yPU0BW8/hoXLMXy6Urc779OZPcuhQ9o2sORrRN46rU0qlWPYdnnnxMcEsySrRbmb7Yw9V4D97bReOlqBFUZSZK6X243Xk6FhSXLspyQ8zMJ+B7oeEWXBKDmZb/XyGkrMRkZGdcyRYGg0iM0Xk4Yt4O6ZrGGrbcTSRWHpNUQ8NYk9MMexbZ2AxnPvoQ7vQI04hcOAZ0hc0OJQkfNTgfP7vkf0Tp/3mx2c2775fo+dfIkDw9+kA2//spz48Yy68M55W7YOlwyE1YZ2Z/g5N37/As1bB179uPYvQ/dowNLZ9jKDk8osu0sxLx2XRq2kLMXd8kMDGOGYv97O2kPDMf6y6ZLZa8kJRjaQdRYaPAlxLwC+maQsd4TQnxiiCek2Ham4BO4sj0Zvc+8jHzsUbTt4lBUC7qsFu2MnFq03jVsQazhgqqFn0LJ4nZ34HS7eWb3L7gKqVFteOJBFBFhuOd9kptcquCObWjcug9zXgoj/uxZRj8zErPZzFNdtXSoo+LddSZOp4ryQILSUSHGrSRJBkmSAi6+B3oD+6/o9iPwWE7W5BuBTFmWz5fmPDVr1iy+k0BQhREaLwfcFrDs9+yvK4bySCRVHJIkYRj2CAFvT8J5+BjpT4zBefxU+U8kuC+4siD7j2K7vnl4G8dNGcxr05tAv0tP6S/qe+P/NvDQwMGkp6Xx0cdLeGrY0HIr83OR48kuRn+ZzbY4B6/epadn08I94ubPViIFB6G79/aSn0CW4fxsj0cy6nkwtCmDWVddJKUS/SMDPXtxa9Xw7MV98Q3cqVdkTlaoIaCLx8Bt8CVEjQN1NKSugpNPw8lRnve2eI+nN/6NnFq0c5AdiVi3BZExPRBF86WF1qL1JmINF1Q16hmCmd7yFralJjAnruBgSkmvw3/iaFSnEzAvWVH0gNWG0qFVCNMmtmbf3r28OG4CbpeTt/v7o1ZJTFptxOES5YEEJaeiPLeRwJ+SJMUC/wFrZVn+RZKkpyVJejqnzzrgBBAHLAFGlvYkCQmlcvQKBFUOofFywBQLshMMxZeXKc9EUsWh7dWD4EUfgMNBxtCxeWoPlgv61qCOgfSiE0v9kXKWRSf3MLxuG7qF5/2if+bMGWZ9MIPxzz1P3fr1+Hr1Kjp1vtGbs87HhUwXk38wMnBhJvvinbzSV8+AdtpC+zuPHse+7T90D/ZH0hbeLx8pyyFrM4Q/DkE9y2DmvoGqTi2PF3d0jhd38DCsv26mwC1VSgME3QY134IGn0O1p0GhgeRlcHI4nHsPrMcg5C6oPRvr3gEYF6eiHTwCSa8r/4tDrOGCqsngGk25L6Yx0478zY70gv1Omm6dsfXojHn5NzhiDxQ+mCoEIp7gtnbJvPzCQP7YsoU3Xp9MtQCJyXcbOHjexbxNFi9dicAXubY0f1eJLMsngNYFtH902XsZePZazqMopj6iQFDVERovB0zbQaEDffMiuzkOH8N56Cj+40eWu1exMPyaNSZ42VyyJkwha/xkDGOGeYyu8pifJHm8t0mLwXoctPXzdcl22hm9ZwP1DMG81iTvvqzU1FTenDyF/Xv3MeiBwbww6SXU5bh/OMPsZumfVr7+z4oMPNRJw5CbdYToi/4/Z/70aySDHt39d5f8ZOlrIXUlBN8BYYOubeI+iKRUon90IOqbO5H9xgyyX3sX229/ePbihhUSOqwKgdB7PC/7eU+2c3Vtz/9jSYk7MwvTglfwa9sSTe8e5Xo9lyPWcEFVRJIkZrS8le1p5xm+6xd+7/ZQnqibi9geG4ju6EmyprxPyIoFKAz6ggcMvh0yNzKo62HSjENZuOBjwsLDeX78OO5vr+Gzv6zcWM+PzvV9M2u8oGzx6VVVJGkQ+DpC415GlsG4A/RtQCr6pmr9fh1o1GjuuLWcJlcylJERBC+egbp7Z0yzF2GcNqfoPVBlSVBPT23gjHUFHn79wFbiLdnMb9Mbg+rSv296ejpDHnuCo0eO8ua0t3ll8uvlZtha7DJLtlq4a24mn/9tpU8LNT+MCmJCH0Oxhq3zdDy23/5Ae//dKAL8S3bC7H8hcSEYOkLkyJInQroO8XhxZ3q8uH/959mL+7/fC/biXo46yrOH1tDKs18XMC1ejpxtxH/8MxX6MEqs4YKqSqCfhkXtbueMOYuJ+38vsE9kndoETn0R9/lETLMWFT6YpIDqo8CVzYj7lQwcPJhlH3/C559+xvg+eupFKHltjZE0kygPJCgenzZuRbiPwNcRGvcy9jPgTC52v21FJ5IqDkmnJXDaq+ifeADrmvVkjnkZd0aW90+sDIDAbpC5yZMF+DI2Jp3iszP7GVW/HZ1Co3PbzSYTo55+hoT4eF5+7VXu6dfP+/PEkyzqm+1W7v4wg/mbLXSoo2LVM4G82c+f6GBl8QMAluXfgNoP/QP9S3ZSyxE4967Hqx3zUq7hJSici17ckM8XoKwZTfar08h66c38e3GLwHn0ONbVa9He1xdVo/wRBeWJWMMFVZlOodG82LgTK+MPsSr+cL7jCQkJ+LVujv6xQVh//KXoOuzaehDaDynzFyaN70/PXrfxwXvT2fTLWt69z0CWRWbyD6biH2YJrnt82rgNDQ0tvpNAUIURGvcyxu2en8Xst60MiaSKQ1IoMIx8koCpL+LYe4iMIc/hPFVINtmyJLgvyDbI2pTblGG38lzsBpoEhPFS48657Xa7nbFjnufg/gNMnzmDrt1uLmjEMsUty/y638aABZm8s85MzVAly54MYPYDATSoVvKdO64LSVjXbUR7z+2Fh8pejv08xE/xhM/WmAKKUuzPFaCqW4vgxTMxjBqCfVuOF3dD8V5cWZYxfrAAKcAfw/DHymm2hSPWcEFVZ1yDjtwYGs34fZs4ZcrMc+yivvXDHkHVuAHZ78wu+kFU+MOgCkeZspBp09+hQ8cbeP3lV0iJ+5fne+n545iDr/+zefNyBD6ATxu3TqezoqcgEHgVoXEvY9oBmjqe0jZFUJkSSRWH9o6eBC+cjttkJuOp57H/u9O7J9Q1Am1Dz77SHMNj0oEtJNnMLGjTG63SY0C6XC5emTiJf/76i8lvvsEtPW/1ur7/Pu7g4SVZTFxtQqOSmPugP0ufCKBtrdLv67J8sRoA/SP3F9/ZmQlnXwNkqPlGuZSc8UUklRL9Y4M8XtwaUWS/kuPFTSu8vI7t18049uzHMPJJFEGB5TjbghFruKCqo1IoWNT2dhTA8N3rcbovhQ5f1Lfk50fA1BeRTWay35ld+EMohQ4inwbbKTSmX5g970PqN6jPuDHP0VJ3lJsb+jFrg5mjieL/jaBwfNq4zcoqh7A7gaACERr3Ii4zmA+AoeiQ5IuJpHT97qw0iaSKw69VM0KWzUVRvRqZz7+K5dufvHvC4L6eEG/Lfn4+H8fK+EOMb9iRNsGe/YayLPPuW2/zv19+YeyE8fQb4Anr9Za+9yc4GbE8i2dWZJNhlnmrn4GVIwLp1kh9VX9Dd1oGljXr0dxxK8qoYvZQuq0QPxWcKRDzOqhrXOVVCC6iqluL4CWzMDz7FPY///NkVC7AiyubLZg+/BhVkwZo7+lTQbPNi1jDBb5ATX0gM1r1ZEf6BaYf/Te3/XJ9q+rV9kRa/PEP1h9+KXww/87g3wlSVhCgtTB/0SJCQ8MY/fRIhrZJJlAn8dJqExaHCE8WFIxPG7e1a9eu6CkIBF5FaNyLmPcALvAvJiS5kiaSKg5lVCTBS2ai7nwDxunzyH5/PrLL5Z2TBXYDhT8pSWsZt/c3WgVGML5hx9zDC+fN55uvV/LEU0/yxJCnctvLWt+nU11MWJXNIx9ncTTRxQt99PwwKoi7WmtQKq7+wYTl6+/Bbkf/WDGZjmUXnHsfrEcg+kXQV35Pf1VBUinRPz6YkM/nX/LiTnorjxfXtPRL3Mmp+E94FklZOfY3izVc4CvcF9OYB2s2Y+ax//grNR7Ir2/doHvxu6ENxlkf4TpbyH5zSfJ4bwESPyKiWgQLlywGSeKl0SMYd7OZE8kuZv5q9ublCKowPm3cnj59uqKnIBB4FaFxL2LcDgo96JoW2qWyJ5IqDoVBT+D7k9E9fB/WVT+SPfUDZKcXDFyFFjmwJ+NPZpHlsLGgbR/8FB7j4ssVX7BowULuHdCf5yeMz/OxstJ3UrabN38yMWB+JtuOORjeTctPY4J5+EYtatW1edvdRhOWVT+ivqUrqjq1Cu8oy5C4CIx/Q7UREHDTNZ1XUDCqerUveXH/+DdnL+4WnKfjsXz5HZq+vfBrVXkeKog1XOBLvNuiB3UMQYzY9SsZdms+fUsKBQGvT0BSqcia8n7h9xu/SM/+W+M/kP03tevUZsHij8jIyGDZO6N4oLWDVTttbDpkL4erElQ1fNq4Lc+aiAJBRSA07iVk2bPf1tAWpMKTCln/93ulTyRVHJJSif9zwzGMfBLbL5vIevltZHvZf2H4ztqSn4zVmFRTT7NAzx7m9WvX8t7b73BLz1t5feqUfCHB16rvLKubuRvN3DM3gx/22BjYQcPPY4IZeYsef03ZhJBbv/0J2WRG/8TgojumrYaMnyH0Pk/tVYHXyPXiLp+HMjqS7FfeIWPYOCSNGv9nnyp+gHJErOECXyJApWZxu9tJtJl4fu9v+Pnlz1+gjIzAf+JonPsOYV6+svDBQvuBpjYkfgRuC82aN2fm3DmcOHGCI6tfpEmEk6k/mUjMEuWBBHnxaeM2LCysoqcgEHgVoXEvYTsFztRi99tav1+Hsl7tKpFIqjj0TzyAYfwz2H/fRuYLU5Gt1jIb+7zVyAuHY+mgdzBK/wfILrb98QevvvQyHW64gXc/eB+VKv9DhKvVt9Uh8+k2C3fNyWTpNiu3NFWzZlQQL91pIMy/7G57stWK+avv8OvcAb8mDQvvmPU7JC+FgG4Q8WSZnV9QNKr6dQj+eDaGZ59CNps9SaTCK1d2Yo/Hw8sAACAASURBVLGGC3yNdsHVeaVJZ348f4wNjtQC+2h790DTuwfmJStwHDpW8ECSCiJHecrxpXwJQOcuN/HWtGns2rGDoNi3sNmdvPK9EZdb7L8VXMKnjdvz589X9BQEAq8iNO4lTBdLALUvtEtuIqn+fatMIqni0A/uh/+r43D8s5PM51/Dbbr2PU2yLPN87EZsLhcLmrdF6Uom9q+vGPfcWOo3bMDs+R+i1RZcBqe0+na6Zb7bZeWeDzOYvdFCyxoqvh4RyLQB/tQIKfs9ltYffkVOz0T/xAOFdzLthfMzQdcSosaD5NO33UrHRS9u+O9r0A2sfB5zsYYLfJHR9TvQPbwWrxzdxvLT+wvs4//iKBRhIWRPfg/ZWkh5H31zCOoDad+D9SQAd/S9kxdfnsQ/W3+j2fm5bD/pYNm2snsYK6j6+PRdNjy86PIdAkFVR2jcSxi3g6Ye+BXuVamqiaSKQ3dPHwLefAlH7H4yR72EOyv7msb74uxBNiSd4vWmXWgQ2YO4BD2jxn5AtYgIFi5eREBA4XuVS6pvWZb57ZCdgQszeeMnM5GBCj5+PID5DwfQpHrJa9WWBtnhwLxiFarWzVG3bVlwJ9tpSHgT/KKhxqugKH2JIUHZIBUQGVAZEGu4wBdRSBIrbribrsHRPL93IzOP/Zcve7kiMICA18fjOnUW0/ylhQ9W7SlQ+kPiPJA9IcgPP/oIQ4YPY+em76iftJyFmy3sjRflgQQefNq4tZZhWJ1AUBkRGvcCLiNYDoF/4SHJVT2RVHFoe/cg8N3XcB49QcYzLxZZN7QozpqzePnAFrqG1WBY3TYknEvk6Sln0ajcLFz4NmHFfLEvib63n3Tw6CdZjP/GCMDMQf4sHxJIhzreNSRtv2zCnZiM/skHC+7gSIWzr4NCAzWngtL3dCK4dsQaLvBVDCo/ZtftzMCYJrx1+C8mHdiC+woDV92xHboH+mFZuabwmuvKAKg2zHNfzvw1t3n088/Rb8AAjm/+GMPZH5i02ojRJsKTBT5u3BqNxoqegkDgVYTGvYBpN+AGQ+ElgHwhkVRxaLrfRNDMqbjOJJAxYjyuxORSfd4ty4yO3QCyzLw2vUhPS+PpIcOw2mDh5OrU8N9d7BhF6fvwBScjV2QzbHk2ydkyU+4xsOqZIG5tenW1akuD7HJh/uwbVI3qo+5cgE5cZoifDG4j1JjqyfwpEBSAWMMFvozNZGZh2z48U68ti0/uYcTuX7C782ZINox8CmXdWmS/MQN3ZiF1nwNv9WztSFoGTs/DVkmSeG3qZLr16E7Wthmc2/cb76w1efuSBFUAnzZuRf04ga8jNO4FTNtB4Q+6JoV28aVEUkWh7tSeoLlv405JI2P4eFwJJd8fuPTUXramnOXN5t0IdSt5dvjTJCUm8uFHC2nYvBtkbgB30VmZC9L32TQXL6028sCiLPYnOBnbS8cPo4Lo11aD6hpq1ZYG++ZtuM7Eo3/igfyGtOyAhLc8Ickxr4C2frnMSVA1EWu4wJepXbs2CknirWbdmNy0C6sTjvDgfz9gdF5a+yWthoCpnggh43sf5gtf9nSSoPoocFsh6ePcZpVKxfSZM2jdpjX8+yZrN/7Lz7GF7N8VXDf4tHEr6scJfB2h8TJGdoNxJxjagVRwAiJfTCRVFOq2LQma/x6yyUzGiAk4T50p9jPHjelMOfQHPSNqMziyIc+PGs3RI0d4f9ZM2rZrByF9wZUF2X8UOc7l+k41upm2zkT/+Zn8ftjOU121/PxcEI/fpEPrV35/B1mWMX/6NcpaNVDf0uXKg3B+Lpj3QPUxHh0JBEUg1nCBL3NR35Ik8VyDG5jbuhdbks/S7+/VpNosuf38mjTEMOIxbBu3Yvt1c8GDaWpC2P2QtQlMsbnNOp2OuQvmU7dObRTbJvHmij2cTfNCvXZBlcGnjdvCMnAKBL6C0HgZYzsBrvQi99ta16z3yURSReHXrBHBH72P7HR5DNyjxwvt65LdPLvnf/gplMxscSsvvziR7f/+xxvvvE23Ht09nfStQR0DGeuKPK9Wq8Vok1mw2cxdczP4doeNfm01/DgmmDE99QRqy/8WZv97B86jx9E/PghJecUDkJTPIes3CH8EgnuV+9wEVQ+xhgt8mSv1/Uit5nx+w10czErhzm3fcNZ8KQxZ9+hAVK2aYZw+D1diUsEDhg0Gv+qQOB/cjtzmoOBgFi5ZRFhIALaNExi/9AgOl9h/e73i08ZtcHBwRU9BIPAqQuNljPFiCaCCPW6+nkiqKFQN6hK86AMktZqMZ17Esf9wgf3mH9/Ff+nnebd5d5a+N4PfNmzkhZcmctc9d1/qJCkg+E5PghBrwYayzSmz4UQgd8/NYPFWKzc3UvPds0G8epeBagEVd+syL/sKRWQEmtuveLiR8Qukfu0pWxFWSJIpgeAKxBou8GUK0vcd1euz+sYBJNpM3L7tGw5mpQAgKZUETn0R3G6yp85AdrvzD6jQQORIsMdD2qo8hyKrV2fxJ4vRqVwcWfk8M3+I98o1CSo/Pm3cXrhwoaKnIBB4FaHxMsa0A7QNQRVS4GHr/35HNpl9OpFUUahq1yB48QykoAAyR72EfdfePMcPZafyzpG/uat6fS6s+pXvvl3N0BHDeeTxx/IPFnQbSOo83lu3LLP7jIO3fjbRa0YG87bKNKqu5IthgUy/35/aYWVfq7Y02Hfvwxl7AP0jA5H8LsvGbPwPLszzJCGr/qxnf5hAUALEGi7wZQrTd+ewGNZ1GYQsy/T9axX/pJ0DQBkThWHs0zh27MGyck3Bg/p3gICbIXUl2M/lOVSvfn0WLVmI0pbClx+MYeuBq8v0L6ja+LRxGxERUdFTEAi8itB4GeLKBssRMBQRknydJJIqCmVUJMGLZqCIjCDzuVew/+3xdjvcLp7d/SsBKjWdYxNZuuRj7hs0kFHPjSlkoAAI7A6ZmzmZmM28TWbumpvJk8uy+Xmvja4N/ZjRHxY9Gkjz6IqvUeo4eATju3ORQoLQ3tvn0gHLUUiY5qmLHDMJpIqfq6DqINZwgS9TlL6bBYbzS9dBhKt1DPh7Nb8mngBAe08f1N1uxDR/Kc7jpwr+cLXhIPlB4gJProPLaNWmNe/PmgUZxxk3ZgyJGaLc1vWGTxu3JpNICS7wbYTGyxDTLsDteSpcANdbIqmiUEaEEfzR+6jq1CJz/BRsm7cxK247ezKTePSCxEczZnFb71688vprhf5bJWe7WXf2NpCtfL1xHUv/tFInTMnb/Q1smhDCOwP8aRRS8fp2Z2WT/d6HZDz5HHKWkcApLyBd3EdmPw/xU0AVDDWngEJXgTMVVEXEGi7wZYrTdy19EOu6DKJJQBiPbP+JL88eQJIkAl4ei2TQk/X6e8j2ArLq+4VBxOOe+3b21nyHe/bszsiJU3Gc28kjQyficokEU9cTPm3cms3mip6CQOBVhMbLEON2UAZ6wpIL4HpMJFUUipBggha8h6ppQ/6ZM4cPjvxDz0QXa96fR8cbOzHt/ekor0i4ZLbL/Bxr45kVWfSZlcHL62M4kV2XZ9ps4n9jg1jwSAB9W2nQqz0GcUXqW5ZlrOs2kjZoKNbv16EbdC8hqz5G3TnHs+/KgvjXQXZCjTdAFVphcxVUXcQaLvBlSqLvCI2eH266n65hNRm1ZwNz43agCA0m4NVxuI6dwLRkRcEfDL4TtA0gcTG48teLHvF4f7oNfI6kAxsZPvbtgksMCXwSn46fEvXjBL6O0HgZIbvBVHgJoOs5kVRRKAL80c15i4k/LiT0wBlOffEbjZs0Yfa8D1Gr1QA43TL/HHewdp+dzYftWB0QHaxgSFctd7bSUFd1L1yYDcqDQMs841eUvp0nTmOcPg/Hrr2oWjTBf87b+DVucKmD2wbxU8GRBDXf8ZSoEAiuArGGC3yZkuo7QKVmZad7eWb3r0w59CfJNjNTu96Mtt8dWJZ/g6ZLR/zatMj7IUkJ1UfDqbGQvByqj8w37uwpQ7nrTBI7NnzF+7MieXHciLK4LEElx6eN29OnT9O4ceOKnoZA4DWExssIaxy4Mgvdb3u9J5Iqiuln93DSmEWdLzcR7oIP+tyNXq9nf4KTtXtt/HrATppJJlArcXcrDXe2UtO6pgrFxXBldzdI+hjS14E+r3Fb3vqWLVZMn3yB5YvVSAYd/pOeQ3vv7UiKy4KcZBecex8shyF6Euibl9v8BL6HWMMFvkxp9K1WKFnS7g7C1Trmn9hFit3CnDFDsW/fQ9bk6YR8sRCFvyHvh7QNIeQuSP/Jk6RQ1yjPYaVCwfK5L3HnQ6l8sWQudWLCGDT4/rK6PEElxaeNW71eX9FTEAi8itB4GWHaDkiFlgCyrhGJpApie/p55v+7mVrLNhIYEsI7zTuhXrKCj7fbmR/dD7VKoltjP/q21NClgR9qVQH7bxVaCOoJ6WvBmZ4nU3V56tu25S+MMxbivpCE5q5e+I8eiiLkijIWsgxJS8D4lyehSWDXcpufwDcRa7jAlymtvhWSxLstehCh0fPOkb9Js1tYNHkcjqcnYpq1iIDXxuX/UPhjkP0nXPgQ6szOF30VEajig/ffYszIDN6ZOpXTJ48TGhaKXq+/9DIYct8bDAZ0Oe+1Wu11n2OjKuLTxq3BYCi+k0BQhREaLyOM20HbCFRB+Q45jsThPHgU//EjxU3uMsxOByN//47Ij9ejcEBo/9k8aYpmfI3F9NvzDR2qOak3cShBuhKU7wnuC+k/QMb/IHxwbnN56Nt17gLGGQux//EPyvp1CFr0Aeq2eT3IyC5PJu2s3yHjZwjpB6H9vD43ge8j1nCBL3M1+pYkiQmNOhGu0TNh7yYGhVhZ+sRAWLoS9c03oulxU94PKPVQbQScmwbpP0PovfnG7N7UwANjp/P1zAl88fkXyO6SJZhSKBTo9Xp0OUbvRQPY83vBxnGe9xd/N1wynP38/MR3CS/j08ZtcnIyoaEiyYfAdxEaLwOcmWA9BuEPF3jY+v06kUjqCqwOmSc3/oLxw6/xy7Ri7TEHp38dRt+k5tbnX0S7OJAaq79DEehAnjAyb1hvQWhqgL61p+Zt2P25T969qW/Z4cC84lvMS78ChYRhzFB0D/RHUuXcFu0XPPuwTbvBvAfcZkABQb2g2lCvzElw/SHWcIEvcy36fqJ2S8LUOobvWs/AxoF80rYJ0juz8WvRBEX4FWMGdAVDe0hZDgFdwC8833jj7wznSMqH7D7jALcdnBaq6WzUDLASbbBRTW8jTGPFoLRgs1gwmUyYzWYsZjMmkxmzOedlMpGSnMyZ0573F9tLmrBKpVLlMY51ej2169ShdevWtGrTmoaNGuF3eR11QanxaeO2evXqFT0FgcCrCI2XAaadgAyG/CWARCKpS7jcMjtPe/bRrjl+DOvG2WgSM+k1fBbDB3emUaQy92m0/OIoJJ0Oy4pVyBYrAa+MRVIV48EN7gvn3gHjDgjoBHhP3/btezC+Pw/XqbOob+mC/7inUYb7g3m7p7SEaTc4znk6qyIgoJsnZN3Q2lOfVyAoI8QaLvBlrlXfd0c1YFWnfjy8/ScG92/GkoUXaPr2LAJnvpHX+ylJEDkSTj4DSYsh5uV8Y6lVEsueDOBClptjiS7PK8nzM/a8C1eObapWQt0IJQ0jlTSqpqRdpIpGkUrCDFKhHldZlrFYLFhyDN3CDGPLZccuGsrZ2Ub++/sf1v30MwBarZZmzZvTqk1rWrVuTes2rQkX9bBLhU8btxkZGQQF5Q8zFAh8BaHxMsC0HZTBnpICVyASScHRRCdr99pZv89GUraMRm3FseN1NKcuMGXaNAbc2zPfZyRJwjB6CJJBh3nRcrBaCXhjIlJRT6MDbvSU08lYm2vclrW+3SlpGOcuwfbLJhQ1qhP04QjU9W1geh+OHQZcIGlB3wpC7vEYtOoYzxcngcALiDVc4MuUhb67htfk55vuZ+C/a3hoSBcWL/2TLmvWo+t/Z96O6igIexBSPvNsNfLPnyBSkiSigpREBSnpdlnuKbtT5mRKXoP33+MOfo69VGM3RC/RMFJJw2pKGkaqaBippF6EEp2fx+i9GIYcdhXXKMsy58+dJ3bPHvbFxhIbG8uK5ctxOpwAREdH5xq7rdq0pkmTJvjlVCQQ5MenjVur1VrRUxAIvIrQ+DUiu8C4C/w7gpQ/dPZ6TSSVmOVm3T4b6/baOZbkQqWAmxr4Ma6XHzPnjcd68AQPjhvFgHvvKXQMSZIwDHkYSavFNGcxstVG4LRXkbSaQj6ggqDbIfUrsJ8HdVSZ6Vt2ubCu/hnL18vwa+gg5IM6KKunI7k/hhQ8DzbC7gN9O9A3BUmEhAnKB7GGC3yZstJ3y6BqrO8yiPv/+Z7Hn+jM3O++oV+H1ihrxuTtGDYAsjZB4kJP9n2FtkTjq1USjauraFw9r1mUbnYTd5nBezTRyepdNqwOGwAKCWqGKnK8vCoaRCppFKkkOlhxqSJACZAkieiYaKJjormjr8dot9lsHD54iNjYPeyL3cvuXbv5Zd16z3zVapo1b0bLHM9uq9atiRRRILlIvlTUeOvWrXK3bt1yf7darWi1JRO2QFAVERq/RiyH4PR4iJ4Igd3zHHIciSPj0WfxHz8S3eD8CSp8jWyrm98OOVi718aOU05koFUNJXe21NC7uZpQg4Lnpr7G719/R5NBfVk5dXqJx7Z8txbjex/i1741QR9MQdLrCu7oSIHjT0DoAKj21LXr223FeXg9zh0rUdXIRBWd82VDFQaGth7PrL5tgYnEBILyQKzhAl+mrPWdZDNx/5/fcjg7lem7Unn89Tfyb3kx74MzEyFsEEQ8UWbnvojLLROf7iYuyWPsXvT2xqe5uWhR6dXQoJqShtU8Ht6LHt9AXTH5J4oh8cIF9sbGsjd2L3v37OHggYPY7R7vcmT16rRq3SrX4G3arBkaTSEPk30ASZK6y7K8tcBjvmzcHjlyRNSPE/g0QuPXSPJySP0GGn6Vby9l9rtzsa7dQNjaL316v+35TBdLtlr5OdaG3eV5Ct23paceba3QS18aFixaxKLZc1F1b8ef85aiU5XOu2ld/xvZUz9A1bwxQbPfQhHgX3DH+LfAsh/qL+fIsZOl07fsBttJMO1CzvwPLAeRlDKyA9zOuihq9UTybw/qWiLUWFApEGu4wJfxhr6zHDYe+t/n/OU2Mjnbn+ceKiDB37mZkLUZ6s4DTe0yPX9hWOwycckujl1m8B5LdJFpuWRnRQYqcvfyXvTy1g5T4qe8uvuRw27n8OHDucbu3ti9nEtIAEDlp6JJ06aeUOaccObo6GifydR83Rq3CQkJxMTEFPEJgaBqIzR+jZwaA5Iaan+Qp1k2W0jt+xDqHl0InDyhgibnXZKz3Xzyh4XVu2zIMtzbRkO/thpaxCjz3fy+X/0dU159DUvreny9YDHtQqOu6py2zX+S9co0VPXrEPThOyiCC/CYmnbB2VchagIJxsbF69uZ5kkAdTGzsSvT0xyvwL7XhRTWGc2A0SgCQooeRyCoAMQaLvBlvKVvq8vJkBVzWB+qZHRwPaZ0vTvvfcuZCSeGg6YW1JpeYQ8zZVkm2ShzLNHJ0UQXcTkG74lkF063p49KAbc1UzPqVh01QkpQOq8YUpKTPcZubCx798RyYP/+3PDw8PDwPKHMzVo0R6crJJKqklOUcevTe25FqI/A1xEavwacaWCNg/DH8x3y5URSaSY3n26zsnK7FacL7m2rYVg3LVFBBd9UN238jamvT8bSKIbHX33xqg1bAM0tXQn8YApZE98gY8QEgua9izLiivQb+jbgFw0Za9H6t84/iNsGlgM5WY13ge2Up10ZjNvdGMsv8VjXnkVRsxEBL41G1aj+Vc9XIPA2Yg0X+DLe0rdWqeLTfkN5fuF7fNgc0nb9yqy2vVFdLDunCoJqT8GFOZC5EYJ7eWUexSFJEtUCJKoFqOlyWc5Kh0vmdKqLo4ku9sU7+X63jY0H7Qy+QcOwbjqC9VcfvhweEcGtt/Xk1ts8yR4dDgdxR4+xNzaW2D2x7IuNZfNvvwGgVCpp1LhxnszMNWrWrPLeXZ/23IpwH4GvIzR+DWRuhPMzoc6HoM1rAKU/MRrZaiPkq0VVfpG/SJbFzfK/rXz5rxWLHfq2UjO8uy5P6PGVbP/vP54ZNgJbVCihYx9hY6/H8FNc+5Nl+85YssZPRgoNJnj+eyijIvN2SPsOkj7mFBOo0/gWjwFr2g3mXWDeD7Ldk4BK1wIMbZFVLTB9vg3LF98hGXQYRg1Be8/txdfXFQgqGLGGC3wZb+vb9u8u3l71CfO6N+SOyHp83P5OdMocv53shjMvgj0e6i6q1LkVkrLdLNxs4Yc9NvRqiSE3a3mwoxatn3e+f6SlpbHvonc3Npb9e/dhNpsBCAkNpVXrVgwcPJibu3crZqSK47oNS87KyiIwMLACZyQQeBeh8WsgYZrHA1j/8zwhS76WSMpkk/nyXyuf/WXFaJPp1UzN0z101I8o2kg9dPAQQx57HGeQgbMj7uS325+kWWB4mc3Lse8Qmc+/iqTXETTvXVS1a1w66MqGuEdxKSNQYvF42cGzV9bQzpMMSt8SWdJg3/I3xpkLcV9IQnt3bwyjhqAICS6zeQoE3kSs4QJfpjz0bZz5ER8f28mbdzanU2g0X95wD8HqHI+x7RScHA1BPSHqea/OoyyIS3IyZ6OFP445qB6oYNStOu5spS5V5uWrweVycTwu7jLv7l6eGPIU/Qb09+p5r4Xr1rg9efIkdevWrcAZCQTeRWj8KpFdcOxBCOgMUWPzHPKVRFIWh8w3260s+9NKhkWmR2M/nu6ho0n14nejnD51miceeRSnQuLwsF682rkPzzXIXzPwWnEePU7G6EkgKQie/y6q+nUuHUxcjCt9I8qAdjkGbTvwu2RcuxIuYJyxAPuf/6KsX4eAiaPxa9OizOcoEHgTsYYLfJny0Ldss5P+2LOsraZmQp/GNPAP4dsb+xOlzUlamLQM0lZ59t7qq8Y9YvtJBzM3mDl03kXj6krG9tJzY73yLVEny3Kljlwryrj16Ziti+mxBQJfRWj8KrEcBrcRDHkNNtlswfbrZjS3da+yhq3dKfPVv1bunpvBrA0WmkWr+HxoILMfCCiRYZuUlMTTQ4fhdDk5P6QPbes2YFT99l6Zq6pRfYI/+gBJqSBjxAQcB49eOhg5nDjpTYh5CYJ75xq2st2OadlXpD0wHPvOWAzPDSPk8/nCsBVUScQaLvBlykPfkkZNwBsTuX3nKT7db+KMOYvb/1xJnDHd0yH8QVBVgwvzQXZ4fT6lxei0Y3E587TdUNePL4YF8s4AA1kWmac/z2bkimyOJjoLGaXsqcyGbXH4tOdW1I8T+DpC41dJ8qeQ+i00XAlKQ26zZc16jO/MJvjjmfi1al5x87sKHC6ZH/fYWLLVyoUsN+1rq3j2Fh3tapf8aW9WZiZPPvo4CfHxRL7wJDsCZbZ0f5gG/t7NNOxKOE/GyInIWdkEzXoz11C9Ut/27XswTv8Q1+l41Ld2xX/sCJSR1bw6N4HAm4g1XODLlKe+zZ+txDR/KSenjOYRZQIy8E2nfrQNjgTjvxA/FSKehLCB5TKfy8l0WDlhyuSEKYOTpgxO5LxOmjJJtnv2uhqUfoSpdYRrdJ6fah1hGj3BKi3H41VsO6TEbtbQu1EgY7qFUDdYU6UN0Gvlug1LFokaBL6O0PhVcnIUKPRQe3qe5qqYSMrlllm3z86iLRbi0920jFHy7K16OtVVleoaLBYLTw8ZyoH9B+j3xkRmKhOZ1rw7I+q19eLsL+FKTCZz1Eu4LiQT9MFk1J3a5+rbnZKGcc5ibL9uRhEThf8Lz6K5qezDpAWC8kas4QJfpjz1LbtcZDz9Aq64k6Qte59BcVtJs1tYfsPd9Iio5amhbtoJdeaCOgaksg1eTbdbc43WXCPWnMEJYwZpDmuevlFaf+oZgqhrCKauPggZSLFZSLVbSLGbSbVZSLF7fre5XQWeT4WSalodERr9ZcZwzk+1Po+RHK7REajyLWP4ui0FJJI0CHwdofGrwJECthOeJ7iXNx+Jw3nwKP7jR1aJG4Bbltlw0M5Hv1s4meKmcXUlcx/05+aGfqWev8PhYMJzY4ndE8vEd99iot85ugbVYFjdNl6afX6UkREEf/QBGaMnkTluMoHTXiGwXi0s3/yAaeGnyHYH+qEPo39sMJJWU27zEgi8iVjDBb5MeepbUioJnPIC6Q8/Q7X3FrFuxmsM+u9HBv+7hoVt+zAgcgScfBpOjgAUoPQHhT8oA0EZ4PldGeB5KQLytckKf9JcSo6bsjhpyuSEOa8XNsNhuzQXIEYXQD1DMHdHNaCuIZh6Oa86+iD0qpJFVMmyjNHlyDF2zaTaLRxLN7H2cBYHU0xYtDacEQ7SsBJnTCfVbsHkKjj02k9SEJbHANYRfrlhnOs11hOu1hGi1no9kZW38GnjVqXy6csTCITGrwbTTs9PQ4c8zdbv14FGjeaOWytgUiVHlmW2HHWwYLOFo4ku6kUo+WCgP7c29SvxjcjlcnH08BF27dzJzh072LVzF+lpabw6ZTJfRLggXWZem17lfmNThIUQvHA6mc+/StbEN1DViMZ4Oh6/jm3xf2FU3ozKAoEPINZwgS9T3vpWxkRhGPcMxrdmEvz9BtYOup+H/vuJYbvWk9qiB8NqTQfzXk9Gflc2uIzgygJXOtjPIjuzSXY4OOHQc9Kh54RdzwmHzvPeoSfLfckoVSBTQ+2mnkZiQLCKuno99XT+1DUEUccQitYv6JKxrPT3lK8rJZIkEaBSE6BSU8fgKWXUJxJGNYGD55zM2mBm+z9OaoYqmNRTz21N/bC6XaTazKTYc7y/uV5gc57fz2YmkWIzk+UseF/060268HzDqhkh5dOralpaGhERERU9DYHAawiNXwXG7aAKA02d3KbcRFI9u1XagSJRqwAAIABJREFURFKyLPP3cQfzN1s4cM5FzVAFb/c3cHsLNUpF0Uao3W7nwP797Nqxk107drJn926MRiMA0TExdOnalZ69buNE/XC27t/MrFY9qaWvmJqAiqBAgj6cRtYLU7GdOEXQ2y+jua1blfCmCwSlRazhAl+mIvStvbs39j/+wbRgGSE3tufbG/szbOc6Ju7/nWRbJyY17keizcxJUwbH7Ze8r54w4kyMlxl7SkmillZDXb2KG7QSddVu6qlt1FWbqaXMRiNfNJCzPUkqXTJk4XldiUJ/mVf4Mi+xMgD8O4GuSamus1m0isWPBfBnnIPZGyy8sMpIqxqezMptawVSQ18yr7nd7SLNbvUYv5eFQ3cMiSrVfCoTPr3n1mg04u/vX4EzEgi8i9B4KZGdcGwwBHSHqDG5zZU9kdSOUx6jdvcZJ1FBCkZ013FXazWqQoxas8lE7J5Ydu7Ywe6du9i3dy82mydkql79+rTr0J72HdrTrn17qkd5bmAnTBl027KCzqExfNOpX4Ubk7IsY8zKIiCoYoxsgaA8EGu4wJepKH270zNIe3AEirBQQpbNwaVSMW7fb6w4cwCtQon1sn2sKklBHX0QdXP2wNa77FVTF4Cfouia8LnIbnCbLvMKZ19m9GYX0H6Z9xg3BHSFiMc9+4FLidMt89MeOws2m0k2ytzaxI8xPfXUCS/h3KsglW7PrSRJNYHlQCQgA4tlWZ5zRZ8ewA/AyZym72RZfqM050lMTBQ3DYFPIzReSswHwW0B/ytCktesQ1mvNqqWzSpoYgWzN97J/E1m/j3pJMJfYtKdevq31aBW5TU8M9Iz2L1rV26Y8eGDh3C5XCgUCpo0bcrABwbTvkMH2rZvR0hI/szHLtnNs7v/h59CyZzWvSrcsAVPOFZSSoowbgU+jVjDBb5MRelbERJMwCtjyRo/GdPiz/EfNYQ5rW6jdVA1jhszqO8fTF29x4CtoQtApSiD5FKS4pIntjS4LZD2HaSuhuy/IaQvhD0IqpLf+1QKif7tNNzeQs2Kf6ws22Zhy5FM7muvYUR3HWH+Pl35NR8VFZbsBMbLsrxLkqQAYKckSRtkWT54Rb8/ZFm+62pP4na7r2mSAkFlR2i8lJi2AyrQX0qUVBkTSR0672TBZgt/HHMQopcY31vPwA4atH6e+SUmJrJrxw527djJzh07OR4XB4BaraZFy5Y8NXQIbTu0p3WbNkV+sch22vn1wgm+ij/Iv+nn+KhtH6J1leeLttC3wNcRGhf4MhWpb83NN6LtfyeWz1ehvqkj6nYtGVKndYXNp1AUOgh/GILvgJQvIP1nyNzoKVkUci8oSl5KSaeWGNZNx4B2GhZtsbB6p42f99p4souOR27UolNXju843qZShCVLkvQDME+W5Q2XtfUAJpTGuL0yLNlsNqPX68tyqgJBpUJovJScfAaUwVBrWm5T9rtzsa7dQNjaLyt8v21ckpOFv1v47ZCDQK3E4zdpeaCjhpTzZ9m1c6fHoN25i/izZwHQ6/W0adeWdu3b075DB5q3bIFGU3QmYaPTzq+JJ/nh3FE2JJ3C5nYRpfXnydotGd+wY6Ux8EHoW+D7CI0LfJmK1rdstpD2yDPgchPyxUIU/obiP1TR2M5A8qdg/MeTHyT8MQi6FaTShxifSnEx9zczmw47iAiQGNlDzz1tis/TURWo1HVuJUmqA2wFWsiynHVZew9gNRAPnMNj6B4o4PPDgeEAI0eObD9mzBiioqJITU3l8OHD3HLLLZw+fZrAwEBUKhVpaWnExMSQmJiI2+0mJiaGs2fPEhwcDEBGRgY1a9YkISEBhUJBZGQkCQkJhIaG4nQ6ycrKonbt2pw+fRq1Wk1YWBjnz58nPDwcq9WK0WjMPa7VagkODubChQtERERgMpkwm825x/V6PQaDgeTkZKpXr05GRgZWqzX3uL+/P1qtlpSUlNxrstvtucfFNYlr2rZtGx07dvSpa/LW3ylIb6e6aSJJ3IM2+iHPNWVlE/rc69jatUT5wsgKu6bdx5L56Vgom47KaJQubq9xFkPyH5yKO8zBAwdIS00DIDAokCZNm3JTly5Uj4qiecsWGAyGYv9OCSlJHNa4WH3mEH8aE7HJbsKVGu4Ir83tobWo41RRu1atSvF3ulx7RqOR0NDQKq89X/z/JK6pbK4pPj6eG264waeuyRf/TuKaru6azp49S0hISIVek3X3PgLfmoOtyw24xgypMn+nOpFG3BeWoOMMLlUtzjnvQB/eBavNVuq/04lMA/N+d3As1Y9awS4eamXk3hurc+bMmSqrvVq1alVO41aSJH9gC/C2LMvfXXEsEHDLsmyUJOlOYI4syw2LGu9Kz21iYiKRkZFemLlAUDkQGi8FGevhwodQ9yPQ1ALA8sMvGN+eVWGJpBIyXCz6LYuft+xHStlDlH0/6WdiMWZnA1A9qjrtOnTI8cy2p269eiX2rJqdDjYmnWLN+aP8L/EkZpeTSI2ee6Ia0i+6EZ1Coyt9DTuhb4GvIzQu8GUqi75NH32GeemXBL73Gppbulb0dEqOLEP2Hx5PruOCZ0tVtSGgrX8VQ8lsPORg7m9mzqa5uaGOirG99DSLrpqFcypdQikASZL88Hhmv7jSsAW43Isry/I6SZIWSJIULstySnnOUyAQ+AjG7aCqBuqauU3W79eWeyIpl8vFhi3/8dmafzi0dxdyygFweTIZK+vWpXef3rTr0IH2HToQHRNdqrGtLie/JZ1izflj/HLhBCaXg3C1jgdqNKNfdEM6h8WglK6vxBICgUAguL7RD30Y+1/byX5nDqqWTVGGh1X0lEqGJEFgN/DvDBlrIeUrODUGAm+BiMfAr1ophpLo1UxNj8Z+fLvDxuKtFh5aksUdLdWMulVHTLDvZFauqGzJEvAJcEiW5ZmF9KkOJMqyLEuS1BFQAKmlOU9GRkaleGIkEHgLofES4naAaU/OvhWPt7IiEkklJSXzxLDxJBzdCUgExzSix333c3OXDrRt146w8PBSj2lzOdmUfJo1546xPvEERqedMLWOgTWa0C+6ETeFxpRNJsgKQOhb4OsIjQt8mcqib0mlIuCNF0l/9FnS7n0cZZ2aqBrUzX0pG9RFER5aqXJO5EHhB6H9IOg2SF0F6Ws8Ht2QeyFskKdubgnxU0o82EnLXa3VfLrNyop/rGw8aOfBjlqG3KwlSFc1vy9cToWEJUuS1BX4A9gHXEyl9jJQC0CW5Y8kSRoFPIMns7IFGCfL8l9FjSsSSgmuN4TGS4hpD5x9GWImQ0AnoPwTSW3cuouXxo/DYcmk6Z1jmTrqbhrXyl+WpyTY3S5+Tz7DmnNHWXvhONlOOyF+Wu6KakC/6IbcHFazyhq0lyP0LfB1hMYFvkxl07dj3yFsW/7CFXcSZ9xJ3EmXgkGloEBUDeqgalAPZYO6nvf16iDpSp6tuNxwJEHy55C1CRT+EP4gBPf1GMGlJDHLzfzNZn7aYydAKzH0Zi0PdNTmKzlY2ajUCaXKkiuN22PHjtGwYZHbdAWCKo3QeAlJXAIZP0HDb0ChRTZbSO37EOruNxE45QWvntrtdvPK+ytYt3wGkr4az742g6F3tyz1E2K728WW5DOsOX+MdReOk+mwEeSn4a7qHoO2W3jNkhebryIIfQt8HaFxgS9T2fXtzszCefwUrmMncR73GLzO46fAYvV0kCSUNaJR5hi9HuO3LoqYKKTK8ADZehySloJ5N/hVh4jHIaBbboRaaTia6GTORgvb4hxEByt46Q493RqpvTDpsqFS7rktDxSVQXgCgRcRGi8hph2ga5lbL866YQuyyYxuwJ1ePe35VBNPjHydC3t/Iaj+TXy8cDqNapbcW+twu9iacpY1546x9kIcGQ4bgSo1favXp190I7pH1ELtYwbt5Qh9C3wdoXGBL1PZ9a0ICkTdrhW0a5XbJrvduM9dwHmZweuKO4X99788CZ4AtBpU9evkhDXX8xi/9euiCA4s3wvQ1odab4NpFyR9AufeA+33nqRT+palGqpRpIr5DwfwzwkHszaYcbq8NOdywKc9t0ajEX//ksehCwRVDaHxEmC/ACeegmrDPXtWgPQnRiNbbYR8tchre2y+2xLHWy+Pw5V2gpv6jeDDt0aiUhZviDrdbv5MjWfNuaP8fD6ONIcV/1yDtiE9wmuhUfr0c8lchL4Fvo7QuMCX8SV9y1YrzhOnccadwhV3AmfcKZzHTiBn5ua/RRERlhPSfNl+3jo1kfxKHy5c+gm6IGszJC8HZwr4d4KIJ3OrQ5QGtywjQeXdg8x17LlNSEigcePGFT0NgcBrCI2XANMOz0//DoD3E0lZHDITZv3Knysmo1AqeGX6fAbd3b3Iz7hkN3+lJvD9uaP8dD6OVLsFf6Uft1evR//oRtwSURvtdWLQXo7Qt8DXERoX+DK+pG9Jq8WvWWP8ml26HlmWcaem4Yo7hTPH4HXFncSyIxYcDk8npTJPAquLxq+iWnjZfgeRlJ6EUwE3Q/oPkPoNnBwJwX0g/GFQhZZ4qMpeJrA4fPrbUmhoyf+QAkFVRGi8BBi3e/ai+MUAYF2zHjRqNHfcWuan2nvGxqiX55C58zNCazRh6cdzqFu7RoF9XbKbf1LPseb8UX48F0ey3YxB6UefyLr0i25Ez2p10F2HBu3lCH0LfB2hcYEv4+v6liQJZXgYyvAw1De2z22XnU5cZxJyQpo9oc2O2APYft186bMB/rnGrua2bqjbli6MuFAUGk8G5aA+kPoVpK+FzM0QOgDC7gOFrmzOU4nx6W9OTqezoqcgEHgVofFicNvBvBeCeoMkIZst2H7ZhKZntzLNkOx0y8xff4FlH0xCvrCdrr37M3P6a2g0mnx9z5gzmX98Fz+eP0aizYxeqaJ3ZF36RTXitmp10KvKIXypiiD0LfB1hMYFvsz1qm9JpUJVrzaqerWhd4/cdne2EdfxU57EVTkv29oNWFf9iLprJwzPPoWqfp2ymYQqCCKfhpB7IPlTSP0SMtZ7vLjBfTyeXh/Fp43brKwsoqKiKnoaAoHXEBovhvQfQbblhiR7I5HU2TQXYxdu59h3L6Owp/PCa1N4+KGB+frJssyXZw8y6cAWnG4XvXI8tL2r1cUgDNoCEfoW+DpC4wJfRug7L4oAfxRtWuDXpkVum2y1Yln5A+bPVpL+8DNo+96GfvijKCOrlc1J1dEQ8zJYDnuSTiXO84QtRzzp2ZdbxUOQC8KnE0pZrVa02kpYn0ogKCOExgtBdkLiIshYC4aOUONVkFRlmkhKlmW+22Xj3Xkrsf83i+DQMBYsnEPzFi3y9U22mRkbu5F1iSfoGlaD+W16U1NfzlkVqyBC3wJfR2hc4MsIfZccd0YW5s++xvLNj6CQ0A26F/3jg8s0ygxZBuM/kLwM7PGga+HJrKyrevuii0ooVblzdF8jp0+frugpCAReRWi8AFzZcPY1j2Ebeh/UeA0kVW4iKV3/vtds2KaZ3IxZkcIbr72O/Z/ptL/hBtb8+G2Bhu26C8fp8vvn/JZ8mreadWNN5/uEYVtChL4Fvo7QuMCXEfouOYrgQPyfG07ot5+g6dkNy4pvSev/BObPVyHb7GVzEkmCgM5QdwFEPusxcE+PhYR3wX6+bM5RCfDpsGS1uvIWHxYIygKh8SuwnYH4N8CZBFHjPJkDcyirRFJbjth5/cs4Mje+AmlHGfr0CEaOehblFWV+shw2Jh3YwldnD9IqMIKF7W6naUDYNZ37ekPoW+DrCI0LfBmh79KjjIokcMoLOB++D9P8pZg+/BjLNz9gGPEYmjt6IpWgpGCxSCoI6QuBt0Dad5C2GrL/8rSFPwjKqv0A3qeN27Aw8UVS4NsIjV+GcQecexckNdR8F/TNcg+VRSIps11mxq9mvl27FcW/b6BTyUxbMI8et9ySr++2lHhG7vmVBIuR8Q078kKjTqgVvpu8wVsIfQt8HaFxgS8j9H31qBrWI2j2W9h37ME07xOy35iBecW3GJ59CnXXTmVTRkiph4hHIOROSF4B6T9B5kZPtuWQezyZl6sgPh2WfP6877jYBYKCEBrHs4ckbQ3ET/GU/KkzO49hC9eeSGpfvJNBH6Wzevki2PoC9WtVZ+W3K/MZtlaXk9cObOWev79FrVCyvusgXmlykzBsrxKhb4GvIzQu8GWEvq8ddYc2BC+bS+C0V8HhJGv8ZDKffgHHvkNldxJVKESN8YQr65p79uSmflN245czPu25DQ8Pr+gpCARe5f/t3Xl8FPX9x/HXd3ezu8nmPiEhBFQ8wCqI4gUqxHrU2tbWtrbVWrVa29pia1tvQfG+bbVq61lba61Hf9rWqgSsiCegKGdFISQhd8i5u9ns7vf3R1YEBLwSdjN5Px8PHrM7M0w+k7yZRz7Md+c77DNu+6DhDuh4DjIPgdLztjmHW/gf/8a9SwWeL4zfxkG2ry9muWdBiD/ObcbzxpXY9S9z3PHHc+nls0hP3/LrvN3RxNlvPsuqrlbOGLMPs/eapqcgf07DPt/ieMq4OJnyPTCMMfgqp+E9/GDC/3iGnnv+QvsZ5+KdfiiBn5yGp6J8YL6QbzSUz4aet8E/ZmCOmQSObm7D4XCySxAZVMM649EOqLsSQsuh4Dv9c7eZjw5Gif7vPaLLV5N53k8+1TCe6tYYFz3RzbLlq8h441IinY1cdOklfOs7J21xnGg8zm/fW8R1q1+lwJvO3w/8GpXFYwbiDIe9YZ1vGRaUcXEy5XtgGY+H9BOPx/+lIwn+9QlCD/2djS++gv8rx5Bx5sm4CwdoGHhgn4E5TpI4urnt7u5Odgkig2rYZjy8Fmovh1g7lJ4P2Ydvd9fQk//+VA+Sstby2OJebnouiFn3Hzyv3UggN4e7/vQg+06auMW+7/e08+M3n+WNjfWcULo7N35hBnleTXswUIZtvmXYUMbFyZTvwWEy0gmc8T3STziO4H0PE3riX4SfqSLjO18n/ZRv4soMJLvEpNI8tyJD2LDMeNerUH9D//Djsssgffft7mqDIVqP+y7eww8he/avP/bQLd1xLn+qhxdX9VDy3h00LnmC/accwPU33UjBZsOrrLU8UP0Ol654kTSXmxu/MINvlA29eeJS3bDMtwwryrg4mfK9c8RqN9Bz14P0PvcCJiebjDO+S/rXj8M4+GnVmudWxKGGVcathda/Q90c8I6Cilt32NjGaupon3lx4kFSx33s4eetivDNOzt4bVkdpYtn0rjkCX5w+mncfe89WzS29eFuvvXaPzjvnXkcmF/KwsNPUWM7SIZVvmVYUsbFyZTvncM9qpTsKy8k98Hb8ey+Cz0330Xbt84k/J952Hg82eXtdI4elqz/LRKnGzYZj0eg4TbonA9Zh8HIc8G17XO31hJ+/J90//aPGI+HrCvOJ22f7T9IqqfXcsN/evjHWxHK+94kOn8W7ZFebrrtFo486qgt9n1yw//41dvzCMei3PCF6Zxesc/API5ftmnY5FuGLWVcnEz53rnS9hpH7h3XEXltMT2330fXZdcR+vNjBM45A+9Bk5Nd3k7j6OY2Nzc32SWIDKphkfFoG9TOgfBqKDwFCk6C7TSUscYmuq68hb7XlpB20GSyLv4F7pKi7R76rZo+Lnmyh7qNMfYP/Z3FT9/BmLFjuPm3tzF2l1027dceCfPrZfN5vG41k3NHcOeko9ktM2+gz1S2MizyLcOaMi5Opnwnh/fAyaQdMIne516g584H6Pj5RaRNmUTgp2eQtte4ZJc36Bzd3DY0NJCTk5PsMjZZvWoVbreH3cbtluxSxCFSLeMDLrwGaq+AWBeUXQxZh25zN2stvf+eS/dNd2JjMTIv+Dn+E7603buqfTHL3f8Ncd9LYUrSQ0yquZY3Fs7jqGOO4fIrryAj8OHDGOY3V3POW8/T3Bvkoj0O5tzdDsDjcvQnOlKG4/Mtw54yLk6mfCePcbnwHzMD34yphJ74F8F7H6b91HPwHXUEgbNPxT2qNNklDhpHN7dFRdu/Y5MM1199LW8vXco5587k5O+fgtvtTnZJMsSlWsYHVOdLUH8TuLOh4kbw77rN3eJt7XRdcxuR/76MZ98JZM/61Q4v2mtbYlz8RDcr6mNMH1nLu09cyFu1Nfzq/N9w8qnf39QQB6N9zF75EvesW8rumfn85YDjmZhbMiinKtvm6HyLoIyLsynfyWe8XjJOOgH/l48i9OfHCD78OL3zXiL968eRcfp3ceU77+66o28/9PT0JLuELVx/840cOm0qN19/Az889TRqa2qSXZIMcamW8QFhLbQ8DBuuBv8uMObW7Ta2vfNfou2ks4i88gaBmWeSe9cN221srbU88nqYk+7uYEN7nJNLX+Llu04n2NPFH++/j1N+cOqmxnbRxnqOePFh7lm3lB/vMon5h31XjW0SODLfIptRxsXJlO/U4coMEDj7VPKfuB//8UcRevxp2r7+A3ru+TM2GEp2eQPK0c1tMBhMdglbKCgs5Jbf/ZY511zF/1av5sSvncBjjz6Kk6Zjkp0r1TL+ucXDsOFaaPkzZFdC+bXg+ehnW+OdXXTOup7O8+fgHlFM3oO3k/G9EzHbGQ3R1BXnp3/p5tpnguxXbpgeuouHbr6QPffak0cef4zJB+wPQF88xtWrXuHYhY8Sjkf5v4O/wVUTDifd7ehBLinLcfkW2YoyLk6mfKced2EBWRfOJO+RP5B20GSCf3iI1q+fRuixp7HRaLLLGxCa5zZJ6jdsYNbFl/Laq68yddo0Zl15BcXFxckuS4aYVM74p9bXAnVXQPg9KDod8r++zQdHRV55g64rbyHe1k7G6d8l47STMJ5tN5/WWqpW9jHnnz309lnOnNLDggcu4s0lS/jeKSfzi1//irS0NABWdbXy4zefZWlHE98ZtRfX7H0E2Wm+QT1l2TFH5VtkG5RxcTLlO/X1vbOSnt/dQ99by3CXlxL48Wl4K6el/EwQO5rn1tHN7erVq9ljj9SdfzIej/PIw3/ltptuxuvzctGll3LscV9KdlkyhKR6xj+x0Or++WvjISj9DWQe+JFdbDBE921/IPzkv3GPHU3W7N9s86l/1lpWN8SYuzLC3BUR1rXGGV/q5nu7rObm2b+mu6eH2XMu59jj+ue+jVvL3Wvf5IqVC8n0eLl5n0qOH6mHvqUCx+RbZDuUcXEy5XtosNYSWfg6PXfcR+y9dXjG707mL84mbd8JyS5tu3bU3Dp6rF1GRkayS9jC841riVnL0SVjMcbgcrn47snf45BDD+WSCy7kgl/9mnlzq7j4skvJzXPeB7xl4KVaxj+TjvnQcCt4CqDiKvBVfGSXyJJ36LriRuL1jaSf/E0CP/o+xufdtN1ay7K6/oa2amWE2o1x3AYmj/HwvQN9BJf/nUtn3kjZqFHcde89jNu9vymuDXby07eeY0FrLUeXjOXWfY6kxB/4yNeX5HBEvkV2QBkXJ1O+hwZjDL6pB+I9eH96n6mi564HidVsSOnmdkcc3dwGAqn1S+rda99iXnM1h+SXcfn4aUzOGwHAmLFjeOAvD/HAvfdx5x13sGTRImZfOYdphx+24wPKsJdqGf9UbBxaHoLWv0H6F6DsIvBsOWWA7Y3Qc+f9hP76JK7SEeTefSNpE/cGIBa3LK2J8vyKCPNW9dHYGcfjggN3SeOMqekcsWcaXc013H7b73j2mWeYXlnJnGuuIisrC2stf6tdyfnLXsBay237HsnJ5RNSfhjOcDOk8y3yCSjj4mTK99Bi3G78Xz4K35GHQ9rQbRE1LHkn6ovHeGj9Mq5b/RrNkSBfKx3HpXseytjAh3dpV61cycXnX8iad9/l6yd+g19dcL4uDrJdqZbxTywegg03QPerkHMMjPgxmLQtdulb8T+6Lr+B2Nr1+L/xZTJ/9kNifj+L1kWpWhFh3qoIrT0WrxsO2S2NI/fyMm13DxveX03V3LnMr5rHmnffxeVy8bNzZ3LaD8/AGENLb5Bfvj2Pfzas4aD8Un4/8WjGBDQPXyoasvkW+YSUcXEy5VsGy7D9zG1HR0dKTh7dFY1wx3uLuf29xUTicU4fsw+/GjeFQl//8I1IJMLvf3c7D953PyNGjmTO1Vex/5QDkly1pKJUzfgO9TVC7RXQWw3FZ0LeV7Z4cJSNRgne9zDB+/+KqyCf9It+weKifahaEeGF1X20hyz+NJg2zsuRe6Vx0FgXq5ctYd7cKuZXVdFQ34DL5WK/yZOZXjmDGUceSWlZ//RAzza+z8ylc2nv6+WiPQ7mp7vuh9s4+qHxQ9qQzLfIp6CMi5Mp3zJYhm1zW11dTUXFRz+/lyoawj1c/79XeWj9MtLdaZy72/6cPXYSGZ7+O1hvLlnCpRdeRG1NLSef+n1+du5MfD49vVU+lOoZ/4jgcqi7EmwUyi6EwH5bbI6+t46u2TcQXb2GjYdO55Epp/FctZfuXkumz3DY7v13aCeVRXnz9VeYN3cuL77wXzo6OvD5fBx86CFMr6zk8OlHkJf34RRCXdEIlyx/kYfWL2NCdiF3TTqaCdmaXD7VDbl8i3xKyrg4mfItg2XYPlAqHA4nu4QdGuEPcPM+lZw9dhJzVi3kylUvc++6pVywx8F8t3w8k/bbj0efeJxbbryJhx54kIULFnDltdcwYe+9k126pIhUz/gW2p+Hht9BWjGMmg2+UZs22ViMjj89Tu8fHyTkzeC2Kb9kfu4B5NQYKvdK48jxXvbI6+HVl+by1B3zuHDhQsLhMFnZ2Rx+xBFMr5zBIVMP3ebDK15preMnbz1LTbCLc3fbn/N3Pwif5q0dEoZUvkU+A2VcnEz5lmRw9J3boTa/1qutdVy2cgGLNjawZ1YBs/eayheLx2CM4eWFC5l18aW0trRw5tk/4oc/OmvT/JwyfA2JjNsYNN8PbU9AxsT+O7buLAC6wnFeW1BN/h23Ur5hFS+VHMCDB/6QAyYWUTneS5m3mRfDk0+aAAAXQUlEQVTnz2N+VRVLFi0mFotRMmJE/3Djykr223/yR/4dxGycJe2NzGuqpqp5HYs3NlCRkcPvJx3NQfmlyfgOyGc0JPIt8jko4+JkyrcMlmE7LHkofpDdWsvT9WuYs2oh7/W0c2hB/5OV98sdQWdHB9dedQ3/evppxk+YwJXXXs2uu2k+zuEs5TMe64EN10PPG/2frS0+k/aQ4YXVfcxdHqZg/jOcseJh4i43i44/kzHfriQrUs0LVVXMr5rHyhUrANhl112ZcWQlM46sZPyEjz7VuD7czbymauY1VzO/uZr2vl4MsF/uCI4qGcuPd5lEpse7jQIllaV8vkU+J2VcnEz5lsEybJvburo6ysrKkljRZ9cXj/Gn9cu4bvWrtERCnFC6O5fseQhjA7nMfe455sy6nGAwyM9+MZOTv/99XC49FGc4SumMR+qhdjZENtCdezb/rqmkamWEReui5AdbuWjF3ezd8A49+06i+Vtf5MU3lzC/qoqa9TUA7DtxItMrZzC9spIxY8dscejeWJTXNtZT1bSOec3VLO9sAaDEl8GM4jFUFlVwRNFo8r3pO/WUZWCldL5FBoAyLk6mfMtgGbbNbWtrKwUFBUms6PPr7Ovl9veW8Pv3F9O36cnKB0JXD1fMms0L8+Yzef/9ueKaqxg1atTHH1AcJWUz3rOUeO3V9MUst678BY8s2wMLjMk3nBFayMR//ZGlvT28Pq6cBWvX0NbahifNw4EHHcT0ykqOmD6douItH/i0tqedqsRQ45daaumJ9ZFmXByUX0pl8RgqiysYn1WouWodJGXzLTJAlHFxMuVbBsuwbW6dNByiPtzNdatf5c/rlxPw9D9Z+awxE5n7z39x3VXXYK3l1xeczwknfkO/3A8jqZTxcJ+lsTNO3dp/MiXjHqq7RjBzwS9JD5RSuZeXQ7IbePeGOfx32du8biOEYjECgQBTDzuM6ZUzmHrYNLKysjYdrzsaYWFrLVWJ4cbv97QDMCYjh8riCiqLxjC1cJSGGztYKuVbZDAo4+JkyrcMlmHb3HZ2dpKdnZ3Eigbeqq5W5qxcyDON7zPSn8lFexzMYa4cLr/kUt547XWmHX44s664/CN3vcSZBjrjfTFLV9jSGbJ0hi0doTidof51HSFLZyhO52bbOxPrenr7GBWo4xu7zOfb4+byZutElnEeexf2seatF5n7t7+zaOVKoljyAgGmH3sMlV/8IlMOOhCvt785tdaysquVuYmhxq+2bSASj5Hh9jCtsJwZRRVUFo9hl0DugJ2vpDYnXsNFNqeMi5Mp3zJYhm1zu3btWsaOHZvEigbPy621XLZiAUvaG9krq4DL9jiEludf5rabb8Hv93PxrMs4+thjkl2mDLJtZTxuLd3hD5rTDxrReKIR7V/XFe5f98H2rkQjG4zs+OsFvFAQiLJ3YS175a1jt+y1jA6so8RXjcdEAVjedjivr8hn3tz5vL10KQClxs20klKOPm8mE489CrfbDcDGSJgXWtZT1bSO+c3V1Id7ABifVciM4goqiyo4KL9UU/cMU06+houAMi7OpnzLYBm289xGIh/zm/oQdkjBKJ6fehJPJZ6s/J1FTzNtt1HMeuBuHr7mJn7zy/OYN3cuF116CTm5utPlNG09ce6cH6K2yYd9qXOzu6j9jeqO/svK54HsdEO230V2uqE010WW35DtN+Sk96/r327I9fdSmLaOLN7H0/su7U2raGuupq09Stu6GKs7PLzSk0Vrp5e2Th+1GzpYv/5PAOxZUcFpeSM4JGoY/8NTCZz+HeJu1xbT9CzZ2EgcS06aj+lFo5lRNIYZRRWUpmfunG+kpDQnX8NFQBkXZ1O+JRkcfed2uMyvFYnHeLD6HW7432v9T1Yu2ZU9XnmPv91zP3l5ecy+cg5TD5uW7DJlALV0x/nmnR1k+SE3w0VWolHN8Sca03QX2YnXOemmv3lNrPOn9X8m21pLMBiktaWFtrY2WptqaWv8H61Na2lr2UBbSwttG7tp64jR2hGnszu+zVq8Xi8FBQXkFxZQVFTElP0mM+X9DeQ+/yLusaPpueTnLMh1UdVUzQvN69nYF940TU9lcQUziirYL3cEHj3xW7YyXK7hMnwp4+JkyrcMlmE7LHm4fZC9s6+X3723mN+/t4SojXOizafuD4+yds17fOObJ3Le+b8hEAgku0wZQFtnPBaL0d7eTltrK22tbbS2tiSWrR8u21rZ2NpCa2srvb192zxudqabgrwA+fm5FBSVkFdYTn7hSAoKC8nPz6egsCCxLCQjIwNjDDYep+/Nd2i56hYWpUV49cuHsmBUNsu7W4EPp+mZUVTBdE3TI5/AcLuGy/CjjIuTKd8yWIZtc1tfX8/IkSOTWFFy1Ie7uXb1q/xl/XIycXHoq+tZ/uQzlJaVceU1V7Pf/pOTXaJ8Bn19fWyo20BtzXrWr19PbU0ttTU1BINB2lrbaGtro33jRuLxj95h9Xjc5OdlkJ/jJj87Tn52jLwcN1k5HrLyCggUjiajcCzphbviLRhHzJtNOB6lNxb7cBnpJdTeTrizk1BXF+HubsLBHsLhEOHeMOFIhI1+D0sq8gmmubeYpmdGUQUTsjVNj3w6w/UaLsOHMi5OpnzLYBm2zW1zczNFRanz1OBI1JLmZqf9gr+qq5UrVi7kP43vU1rXQcGj/6WjoYlTfnAq58z8OT6fb6fUIZ9cKBSitqaWmvXrqampoaY6sVy/nob6emKx2KZ93T4v3txsvDlZeHIycWcFMFk+CLixATfRgJtYhptIpp9ev4+IdRMmjV7rIhw3bHuQ8Sfnilv8sTi+OPgw+FxuAp40Dhq1G5WluzK1sJwsTdMjn0OqXcNFBpoyLk6mfMtgGbYPlGpra0upf1Q3/vN9Fq/rxe3NJt2XSUGmm8JMF0VZLgoyzWavXeQHDB7X52uC98wq4OEpX2FhSy2zVi7gzZ9kMPa5pfzp/gd46cUFXHXdNYyfMGGAzk4+qc6OjkTDWvORJra5qWmLfXNyciivGM0+++7Dccd/mfLR5ZSPHo2nMJfKpU/hNYZ0t8VnYviJ4DNR/CaOz1gy3V78ngx8ngA+Txa+qA9vOIY3GMbbE8TbFcTb2UXaxi7SNnbgC0XwRWP4onF80ThpLjcZuTn48/LIyM8nvbCA9KIiMkqKyRg5Em9JESYtLUnfRRkOUu0aLjLQlHFxMuVbkiFpd26NMccAtwFu4B5r7bVbbfcBfwImA63At62163Z0zK3v3HZ3d5OZmTpPXW1cPosS9xsAxK2hJ5pBRySTjeFMOiIBOiOJZW//MmYywZ1FmjebNG8W6enZZGdkkZ+ZRlGWoSDTRVGmi3TvxzfB1lr+r/5d5qxcSP2byxjx+ELoCnLWj8/mjLPOJE1NyoCx1tLa0pIYOvzRJrajo2OL/YuKiykvL6e8YnT/cvTo/ia2vJzsnJxtf5FILbx/Vv9r48V6RmOjI4h15hJr9BOtjhKvbyXW0ES8oYl4SxtsNVzZ5OfiLinGNbK4fzmiCPeIElwjinGPLMbkZGsYsSRVql3DRQaaMi5OpnzLYEm5O7fGGDdwB/BFoBZ4wxjzlLV2xWa7nQFstNbuZow5CbgO+Pan+TqNjY0p9Y8q8O8gnXVxXLkeXLluPFkxirK6KM7swmRYyInj8sdw+aLsqKfo6fXR3ZBBZyTA8kiArmgWIXKIu7Kx7ixcnix8viz8vmwCgWxyAlnkZmXzlZHj+NKIXXlgl3e4YdfR2EeruPP2O5j32iv8/Oar8brc+FwefG43Ppc78b5/6Xd7SDMuNTsJsViMhoYGatfX9Dex69ezfn0NtTX9TWwoGNq0r8vlYmRpKeWjR3PUMcdQPrqcUSNLKS8pprSgAD8GG+6FcC82HMaGe7F1zdg1NQR7t1of7sWGwthwGE/5aELLeuDdbmznamD1hwV6PP3NakkxaQdMwj2yGFdJ8YfLkiKMX8PSJbWl2jVcZKAp4+JkyrckQ7KGJU8B1lhr3wcwxjwCfBXYvLn9KjA78fox4HZjjLGf4lbzth6sk0xp+32FaM4+2HCYWDCE3Rjub1RCof5lMNTfxIRCQAjj7sWVCSYArkyDyQRXAEwgRE5miNxA24fbA2AyDWbr2VSiQEf/n75eN5FwGif2+qjMSucPJ+/L3/auYKHLxdxXHv9E5+DD4jXgM+ADvMbgBfwm8Tqx3mcMXmPwkVga8BlX4rXBS//S53LhxeA1LvzGnTiGi1J3Lrt6Rg3kt/8z641EeHJeFbUb6qltqKemqYkNba1EN/v8q9ftpjQzi9KMTPYdUU6p10+Zx0upy0NxHDyRPmxtB3ZNE4RfhkSMQ4k/H8sY8Pswfh/G78f4fcTr/UTSS8g6+qAPm9YR/XdiXfl5GE2tI0Ncql3DRQaaMi5OpnxLMiSruS0DajZ7XwscuL19rLVRY0wHUAC0fOIvUlb2OcscWL7KafgqP/l8szYeh97Ihw1wMLRZM9yLDYWIhsLYjhA2mFjf1wXxbuLxbmLxINaEwBXGnRbB5e3D7Y8QyAiRFWjnqsx6zqtM430CRGghgoswLiK46DWJpe3/E9lsGbYuIvEt12/+euMH7+Nb/Z3E+jgff/f3e92LueyWZZ/n2z1gYtZya3cdPgwjXR7GuDwc7M6gzOOh1OWm1OOlKCOAK9F0mvTEMtGI4vN9+H7TNn9/s+rbzvoP/vj8mHQ/eNO2edfcFwySkZGRhO+KyOBLtWu4yEBTxsXJlG9JhiH/QCljzFnAWQA/+clPKCkpYeTIkbS2trJq1SqmT59OdXU12dnZeDwe2traKCsro7GxkXg8TllZGTU1NeTm5gLQ3t5OeXk5dXV1uFwuSkpKqKurIz8/n2g0SmdnJxUVFVRXV+P1eikoKKC+vp7CwkLC4TDd3d2btvv9fnJzc2loaKCoqIienh6CweCm7RkZGQQCAZqbmxkxYgTt7e2Ew+FN2zMzM/H7/bS0tPSfUyRMxOemYvcJH3tOG3ZwTsXFxWxYu478jAwinT0E2jrZZ/QI6uo2kJaWRm5ODs3NTeTl5hHpDRPs6WbkyBE0bKjD6/OSmZlBW2sLeTnZhMJhenuDlBQX0dTUgM/rI93npaNzI3l5uQR7uoj09VJUUEBLSzN+vw/jcdHW3UV6VoCNPd2EYn1k5OTQ3N4G3jRiLoPP7I33phPZuHEjNm4pLCqkqalp0/CW7u5uiouLaWluwbgMeXl5tLS0kJ2VTSwWoyfYQ0lJCY2NjaR50sjOyaa1tZWcnBwikQihUGjTdq/XS2ZmJm1tbeTm5hIOhQn3hjdt9/v8PBaLEgcKykrpivQStpby3XZlfVMjmTk5uNPTP/w5tbYSiUQ2/Ry3/jk1bPZzWr+9n1M0Qkkg72Ozt3DhQqZMmTL42fuYcxqS/550Til/Tt3d3eTn5zvqnJz4c9I5ffZzqq2t5YADDnDUOTnx56Rz+mznVFNTQ15enqPOyYk/p6F4TjvsDZPxQCljzMHAbGvt0Yn3FwJYa6/ZbJ9nE/u8YozxAA1A0Y6GJW/9QKnGxkZKSkoG6SxEkk8ZFydTvsXplHFxMuVbBsuOHiiVrA/lvQGMM8aMNcZ4gZOAp7ba5yng1MTrE4F5n+bztiIiIiIiIjJ8JKW5tdZGgXOAZ4GVwKPW2uXGmCuMMV9J7HYvUGCMWQP8Erjg036d9vb2gSpZJCUp4+Jkyrc4nTIuTqZ8SzIkbZ7bwbD1sOSgHrYjDqeMi5Mp3+J0yrg4mfItgyUVhyXvFHV1dckuQWRQKePiZMq3OJ0yLk6mfEsyOLq5dWmeT3E4ZVycTPkWp1PGxcmUb0kGR6dOT2gTp1PGxcmUb3E6ZVycTPmWZHB0c6vhEOJ0yrg4mfItTqeMi5Mp35IMjm5u8/Pzk12CyKBSxsXJlG9xOmVcnEz5lmRwdHMbjUaTXYLIoFLGxcmUb3E6ZVycTPmWZHB0c9vZ2ZnsEkQGlTIuTqZ8i9Mp4+Jkyrckg6Ob24qKimSXIDKolHFxMuVbnE4ZFydTviUZHN3cVldXJ7sEkUGljIuTKd/idMq4OJnyLcng6ObW6/UmuwSRQaWMi5Mp3+J0yrg4mfItyeDo5ragoCDZJYgMKmVcnEz5FqdTxsXJlG9JBkc3t/X19ckuQWRQKePiZMq3OJ0yLk6mfEsyGGttsmsYMMaYM4B3N1t1PPB0ksoR2RmUcXEy5VucThkXJ1O+ZbCMs9beu60Njmput2aMWWSt3T/ZdYgMFmVcnEz5FqdTxsXJlG9JBkcPSxYREREREZHhQc2tiIiIiIiIDHlOb27/kOwCRAaZMi5OpnyL0ynj4mTKt+x0jv7MrYiIiIiIiAwPTr9zKyIiIiIiIsOAmlsREREREREZ8hzb3BpjjjHGrDbGrDHGXJDsekQGkjFmnTHmHWPMW8aYRcmuR+TzMsbcZ4xpMsYs22xdvjHmeWPMu4llXjJrFPmstpPv2caYusR1/C1jzJeSWaPIZ2WMKTfGzDfGrDDGLDfGzEys1zVcdjpHNrfGGDdwB3AsMB74jjFmfHKrEhlw0621EzWHnDjEA8AxW627AKiy1o4DqhLvRYaiB/hovgFuSVzHJ1pr/72TaxIZKFHgPGvteOAg4KeJ37t1DZedzpHNLTAFWGOtfd9aGwEeAb6a5JpERGQ7rLUvAm1brf4q8GDi9YPA13ZqUSIDZDv5FnEEa229tXZJ4nUXsBIoQ9dwSQKnNrdlQM1m72sT60ScwgLPGWMWG2POSnYxIoOkxFpbn3jdAJQksxiRQXCOMebtxLBlDdmUIc8YMwaYBLyGruGSBE5tbkWcbqq1dj/6h97/1BhzWLILEhlMtn/eOs1dJ05yJ7ArMBGoB25Kbjkin48xJhN4HDjXWtu5+TZdw2VncWpzWweUb/Z+VGKdiCNYa+sSyybgSfqH4os4TaMxZiRAYtmU5HpEBoy1ttFaG7PWxoE/ouu4DGHGmDT6G9u/WGufSKzWNVx2Oqc2t28A44wxY40xXuAk4Kkk1yQyIIwxAWNM1gevgaOAZTv+WyJD0lPAqYnXpwL/l8RaRAbUB7/0J5yAruMyRBljDHAvsNJae/Nmm3QNl53O9I8ScJ7EI/VvBdzAfdbaq5JcksiAMMbsQv/dWgAP8LDyLUOdMeavwBFAIdAIzAL+ATwKjAaqgW9Za/VQHhlytpPvI+gfkmyBdcCPNvt8osiQYYyZCiwA3gHiidUX0f+5W13DZadybHMrIiIiIiIiw4dThyWLiIiIiIjIMKLmVkRERERERIY8NbciIiIiIiIy5Km5FRERERERkSFPza2IiIiIiIgMeWpuRUREUoAxpnur9z8wxty+2fuzjDGrEn9eT0y/8cG2dcaYws3eH2GM+edmx2k2xryV+Lu/2BnnIyIisrOpuRUREUlxxpgvAz8Cplpr9wTOBh42xoz4hIf4m7V2InAocLExpnyQShUREUkaNbciIiKp73zg19baFgBr7RLgQeCnn+Yg1tpWYA0wcsArFBERSTJPsgsQERERANKNMW9t9j4feCrxegKweKv9FwGnfpovYIwZDfiBtz9rkSIiIqlKza2IiEhqCCWGDgP9n5UF9v+Ef9d+zLpvG2MOA/YEzrHWhj9zlSIiIilKw5JFRERS3wpg8lbrJgPLE69bgbzNtuUDLZu9/5u1dh/gEODaT/FZXRERkSFDza2IiEjqux64zhhTAGCMmQj8APh9YvsLwCmJbW7gZGD+1gex1i4CHgJmDnrFIiIiO5mGJYuIiKQ4a+1Txpgy4GVjjAW6gJOttfWJXeYAdxpjlgIG+A/w5+0c7jpgiTHmamtt12DXLiIisrMYa7f1MR0RERERERGRoUPDkkVERERERGTIU3MrIiIiIiIiQ56aWxERERERERny1NyKiIiIiIjIkKfmVkRERERERIY8NbciIiIiIiIy5Km5FRERERERkSHv/wFJvENCDUuA6QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d1 = metro_hp.loc[metro_hp['STOP_NAME'] == 'NOTRE-DAME-DES-CHAMPS']\n",
    "d1 = d1.pivot(index='HOUR', columns='CAT_DAY', values='PCT_CHECKINS_mean')[1:]\n",
    "d1.reset_index(inplace=True)\n",
    "\n",
    "cat_days = metro_hp.CAT_DAY.unique().tolist()\n",
    "\n",
    "# Colors\n",
    "colors = ['#2F80ED', '#EA3546', '#FFD749','#11B28F','#2E282A']\n",
    "\n",
    "# Figure\n",
    "fig, ax = plt.subplots(1,1,figsize=(16, 7))   \n",
    "\n",
    "# Plot\n",
    "for c in cat_days:\n",
    "    i = cat_days.index(c)\n",
    "    d2 = d1[['HOUR', c]]\n",
    "    plt.plot(d2.HOUR, d2[c], color=colors[i], linewidth=1.5)\n",
    "\n",
    "# Style\n",
    "\n",
    "# Title\n",
    "plt.title('Hourly checkins (PCT_CHECKINS) at NOTRE-DAME-DES-CHAMPS, per day category (CAT_DAY)', fontsize=15)\n",
    "# Grid\n",
    "plt.grid(color='black', alpha=0.3, linestyle=\"--\", lw=0.5)\n",
    "# Spines \n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)  \n",
    "# Labels\n",
    "plt.xlabel(\"HOUR\")\n",
    "plt.ylabel(\"PCT_CHECKINS\")\n",
    "plt.legend({group:col for group, col in zip(cat_days, colors)})\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> ##### *Important*: \n",
    "> As we look at hourly traffic, it is important to note that this dataset only reports the 1st checkin performed with a ticket in the metro network. It doesn't take into account transfers. Therefore, a curve with a peak in the morning but no such peak in the evening means that people first entered the metro network in this station, but only transfered through it in the evening (we'll see later that such is the case for SAINT-LAZARE). A station can be very busy at a certain hour without having a peak in check-ins because people who are in the station are either exiting the metro network or transfering.\n",
    "\n",
    "> ##### *Reminder on day categories*:\n",
    "> - JOHV (Jour Ouvré Hors Vacances): Working day outside school holidays\n",
    "> - JOVS (Jour Ouvré Vacances Scolaires): Working day during school holidays\n",
    "> - SAHV (Samedi Hors Vacances): Saturday outside school holidays\n",
    "> - SAVS (Samedi Vacances Scolaires): Saturday during school holidays\n",
    "> - DIJFP (Dimanche Jour Férié Pont): Sunday & national holidays\n",
    "\n",
    "> ##### Observations:\n",
    "> This plot shows a peak in check-ins around midday on Saturdays outside school holidays. This could be because students have class in the morning, which makes up for most of the traffic for the day.\n",
    "\n",
    "> On a normal working day however, the peak is arround 5pm, which also coincides with a student schedule.\n",
    "\n",
    "> On working days during school holidays, it is intersting to note that the peak moves a little bit later in the day, around 6pm. Perhaps because now, traffic is lead by workers, who finish their day a little bit later than students.\n",
    "\n",
    "> Generally, the fact that check-ins tend to be higher at the end of the day shows that people arrive at this station in the morning and depart from it at the end of the day."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### What are the busiest hours of the *morning/afternoon* of a *working day outside school holidays* at NOTRE-DAME-DES-CHAMPS? <a name=\"3Eaa\"></a>\n",
    "\n",
    "> Answer: Morning: '8H', Afternoon: '17H'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1 = metro_hp.loc[(metro_hp['STOP_NAME'] == 'NOTRE-DAME-DES-CHAMPS') & (metro_hp['CAT_DAY'] == 'JOHV'), ['HOUR', 'PCT_CHECKINS_mean']]\n",
    "d1 = d1.sort_values('PCT_CHECKINS_mean', ascending = False)\n",
    "\n",
    "d2 = d1.loc[d1['HOUR'].isin(range(12)), 'HOUR'].head(1).values[0]\n",
    "d2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17.0"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d3 = d1.loc[d1['HOUR'].isin(range(12,24)), 'HOUR'].head(1).values[0]\n",
    "d3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.E.b. Hourly traffic at ESPLANADE DE LA DEFENSE <a name=\"3Eb\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d1 = metro_hp.loc[metro_hp['STOP_NAME'] == 'ESPLANADE DE LA DEFENSE']\n",
    "d1 = d1.pivot(index='HOUR', columns='CAT_DAY', values='PCT_CHECKINS_mean')[1:]\n",
    "d1.reset_index(inplace=True)\n",
    "\n",
    "cat_days = metro_hp.CAT_DAY.unique().tolist()\n",
    "\n",
    "# Colors\n",
    "colors = ['#2F80ED', '#EA3546', '#FFD749','#11B28F','#2E282A']\n",
    "\n",
    "# Figure\n",
    "fig, ax = plt.subplots(1,1,figsize=(16, 7))   \n",
    "\n",
    "# Plot\n",
    "for c in cat_days:\n",
    "    i = cat_days.index(c)\n",
    "    d2 = d1[['HOUR', c]]\n",
    "    plt.plot(d2.HOUR, d2[c], color=colors[i], linewidth=1.5)\n",
    "\n",
    "# Style\n",
    "\n",
    "# Title\n",
    "plt.title('Hourly checkins (PCT_CHECKINS) at ESPLANADE DE LA DEFENSE, per day category (CAT_DAY)', fontsize=15)\n",
    "# Grid\n",
    "plt.grid(color='black', alpha=0.3, linestyle=\"--\", lw=0.5)\n",
    "# Spines \n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)  \n",
    "# Labels\n",
    "plt.xlabel(\"HOUR\")\n",
    "plt.ylabel(\"PCT_CHECKINS\")\n",
    "plt.legend({group:col for group, col in zip(cat_days, colors)})\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> This plot is very different from that of [NOTRE-DAME-DES-CHAMPS](#3Eb). Although the peak in check-ins also tends to be in the afternoon/evening, as people tend to arrive at ESPLANADE DE LA DEFENSE in the morning and depart from it at the end of their day.\n",
    "\n",
    "> Here, the profile of the hourly check-ins is almost the same on a working day during or outside school holidays. This is probably because, due to the high concentration of offices in the area, most people who check-in to this station work there, and there day remains pretty much the same whether or not it is a school holiday. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### What are the busiest hours of the *morning/afternoon* of a *working day outside school holidays* at ESPLANADE DE LA DEFENSE? <a name=\"3Eba\"></a>\n",
    "\n",
    "> Answer: Morning: '8H', Afternoon: '18H'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.0"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d1 = metro_hp.loc[(metro_hp['STOP_NAME'] == 'ESPLANADE DE LA DEFENSE') & (metro_hp['CAT_DAY'] == 'JOHV'), ['HOUR', 'PCT_CHECKINS_mean']]\n",
    "d1 = d1.sort_values('PCT_CHECKINS_mean', ascending = False)\n",
    "\n",
    "d2 = d1.loc[d1['HOUR'].isin(range(12)), 'HOUR'].head(1).values[0]\n",
    "d2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "18.0"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d3 = d1.loc[d1['HOUR'].isin(range(12,24)), 'HOUR'].head(1).values[0]\n",
    "d3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.E.c. Hourly traffic at SAINT-LAZARE <a name=\"3Ec\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d1 = metro_hp.loc[metro_hp['STOP_NAME'] == 'SAINT-LAZARE']\n",
    "d1 = d1.pivot(index='HOUR', columns='CAT_DAY', values='PCT_CHECKINS_mean')[1:]\n",
    "d1.reset_index(inplace=True)\n",
    "\n",
    "cat_days = metro_hp.CAT_DAY.unique().tolist()\n",
    "\n",
    "# Colors\n",
    "colors = ['#2F80ED', '#EA3546', '#FFD749','#11B28F','#2E282A']\n",
    "\n",
    "# Figure\n",
    "fig, ax = plt.subplots(1,1,figsize=(16, 7))   \n",
    "\n",
    "# Plot\n",
    "for c in cat_days:\n",
    "    i = cat_days.index(c)\n",
    "    d2 = d1[['HOUR', c]]\n",
    "    plt.plot(d2.HOUR, d2[c], color=colors[i], linewidth=1.5)\n",
    "\n",
    "# Style\n",
    "\n",
    "# Title\n",
    "plt.title('Hourly checkins (PCT_CHECKINS) at SAINT-LAZARE, per day category (CAT_DAY)', fontsize=15)\n",
    "# Grid\n",
    "plt.grid(color='black', alpha=0.3, linestyle=\"--\", lw=0.5)\n",
    "# Spines \n",
    "plt.gca().spines[\"top\"].set_alpha(.3)\n",
    "plt.gca().spines[\"bottom\"].set_alpha(.3)\n",
    "plt.gca().spines[\"right\"].set_alpha(.3)\n",
    "plt.gca().spines[\"left\"].set_alpha(.3)  \n",
    "# Labels\n",
    "plt.xlabel(\"HOUR\")\n",
    "plt.ylabel(\"PCT_CHECKINS\")\n",
    "plt.legend({group:col for group, col in zip(cat_days, colors)})\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> This plot is almost the opposite of that of [ESPLANADE DE LA DEFENSE](#3Eb).\n",
    "\n",
    "> Indeed, people check-in to SAINT-LAZARE *in the morning* whereas they check-in to ESPLANADE DE LA DEFENSE *in the afternoon*. This is because SAINT-LAZARE is one of the 6 large terminus railway stations of Paris, where people first check-in to the metro network to reach their workplace. In the evening, however, the peak in traffic appears to be lower because lots of people already checked-in the metro network before transferring through SAINT-LAZARE."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.F. How many people checked in the station SAINT-LAZARE between 8H-9H on 2018-01-01? <a name=\"3F\"></a>\n",
    "\n",
    "> Answer: 1074 (*) \n",
    "(Compared to 12411 checkins a the same hour on January 2nd!)\n",
    "\n",
    "> (*) Estimation based on hourly profiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calendar of the year 2018 indicating working days (HV), national holidays ('JF') and school holidays ('VS')\n",
    "\n",
    "calendar = pd.read_csv('../../datasets/20190506_2018calendar.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a column that combines the day of the week as a number and whether it's a working day, school holiday, or national holiday\n",
    "\n",
    "calendar['WEEKDAY'] = calendar['WEEKDAY'].astype('str')\n",
    "calendar['CONCAT'] = calendar['WEEKDAY'] + calendar['HV_VS_JF_P']\n",
    "\n",
    "# Create a column where we indicate the CAT_DAY of each day of 2018\n",
    "\n",
    "calendar['CAT_DAY'] = 'TBD'\n",
    "\n",
    "calendar.loc[calendar['CONCAT'].str.contains('7'),'CAT_DAY'] = 'DIJFP'\n",
    "calendar.loc[calendar['CONCAT'].str.contains('JF'),'CAT_DAY'] = 'DIJFP'\n",
    "calendar.loc[calendar['CONCAT'].str.contains('6VS'),'CAT_DAY'] = 'SAVS'\n",
    "calendar.loc[calendar['CONCAT'].str.contains('[1-5]VS'),'CAT_DAY'] = 'JOVS'\n",
    "calendar.loc[calendar['CONCAT'].str.contains('6HV'),'CAT_DAY'] = 'SAHV'\n",
    "calendar.loc[calendar['CONCAT'].str.contains('[1-5]HV'),'CAT_DAY'] = 'JOHV'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Takes a STOP_NAME, DAY and HOUR, returns the total NB_CHECKINS\n",
    "\n",
    "def nb_stop_day_hour(stop, day, hour):\n",
    "    cat = calendar.loc[calendar['DATE'] == day, 'CAT_DAY'].values[0]\n",
    "    hp = metro_hp[(metro_hp['STOP_NAME'] == stop) & (metro_hp['CAT_DAY'] == cat) & (metro_hp['HOUR'] == hour)]\n",
    "    nb = metro_nb[(metro_nb['STOP_NAME'] == stop) & (metro_nb['DAY'] == day)]\n",
    "    \n",
    "    if pd.to_datetime(day) < pd.datetime(2018,6,28):\n",
    "        tot = nb['NB_CHECKINS'].sum() * (hp['PCT_CHECKINS_s1'].values[0]/100)\n",
    "    else:\n",
    "        tot = nb['NB_CHECKINS'].sum() * (hp['PCT_CHECKINS_s2'].values[0]/100)\n",
    "    tot = int(round(tot, 0))\n",
    "    return tot "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1074"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nb_stop_day_hour('SAINT-LAZARE', '2018-01-01', 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12411"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nb_stop_day_hour('SAINT-LAZARE', '2018-01-02', 8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.G. Visualization of hourly traffic with kepler.gl <a name=\"3G\"></a>\n",
    "\n",
    "[Kepler.gl](https://kepler.gl/) is a powerful open source geospatial analysis tool for large-scale data sets.\n",
    "\n",
    "We will use it to visualize the hourly traffic in Parisian metro stations as in [this video](https://github.com/fannykassapian/metro-traffic-data-analysis/blob/master/kepler_viz.gif):"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img width=\"600\" height=\"420\" controls src=\"kepler_viz.gif\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.G.a. Prepare data & export to csv <a name=\"3Ga\"></a>\n",
    "\n",
    "Kepler provides sample visualization, where you can take a look at the .csv table that was used to produce it.\n",
    "\n",
    "The functions below format our data accordingly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Takes an hour (string) & formats it as a date+time\n",
    "def stamp(s): \n",
    "    if len(s)==1:\n",
    "        s = '0'+s\n",
    "    return '2018-01-01 {}:00:00'.format(s)\n",
    "\n",
    "# Takes a day category (JOHV for working day outside school holidays), returns a csv to be read in kepler.gl\n",
    "def gen_hp(day):\n",
    "    \n",
    "    # Filter rows and columns\n",
    "    hp = metro_hp[metro_hp['CAT_DAY'] == day]\n",
    "    hp = hp[['STOP_NAME', 'HOUR', 'LAT', 'LONG', 'PCT_CHECKINS_mean']]    \n",
    "    hp.dropna(axis=0, inplace=True)\n",
    "    \n",
    "    # Format the HOUR column\n",
    "    hp['HOUR'] = hp['HOUR'].astype(int)\n",
    "    hp['HOUR'] = hp['HOUR'].astype(str)\n",
    "    hp['HOUR'] = hp['HOUR'].map(stamp)\n",
    "    \n",
    "    # Export to csv\n",
    "    d = day.lower()\n",
    "    f = 'hp_{}.csv'.format(d)\n",
    "    hp.to_csv('../../datasets/{}'.format(f))\n",
    "    \n",
    "    return print('{} has been created'.format(f))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hp_johv.csv has been created\n"
     ]
    }
   ],
   "source": [
    "gen_hp('JOHV')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> You can then drag and drop this csv ([hp_johv.csv](https://github.com/fannykassapian/metro-traffic-data-analysis/blob/master/hp_johv.csv)) in [kepler.gl](https://kepler.gl/) and define your settings.\n",
    "\n",
    "> Once you're happy with the results, you can download the json file. This json file retains all the settings and can therefore be loaded in kepler.gl to reproduce the same visualization later (see [kepler_hp_radius.json](https://github.com/fannykassapian/metro-traffic-data-analysis/blob/master/kepler_hp_radius.json))."
   ]
  }
 ],
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