ClickstreamDataAnalysis/profile.html at master · samkeet/ClickstreamDataAnalysis · GitHub

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<!doctype html>

<html lang="en">
<head>
  <meta charset="utf-8">

  <title>Profile report</title>
  <meta name="description" content="Profile report generated by pandas-profiling. See GitHub.">
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<div class="container pandas-profiling">
     <div class="row headerrow highlight">
            <h1>Overview</h1>
    </div>


    <div class="row variablerow">
        <div class="col-md-6 namecol">
            <p class="h4">Dataset info</p>
             <table class="stats" style="margin-left: 1em;" >
                        <tbody><tr><th>Number of variables</th>
                        <td>13</td></tr>
                        <tr><th>Number of observations</th>
                        <td>1100987</td></tr>
                        <tr><th>Total Missing (%)</th>
                        <td>0.9%</td></tr>
                        <tr><th>Total size in memory</th>
                        <td>117.6 MiB</td></tr>
                        <tr><th>Average record size in memory</th>
                        <td>112.0 B</td></tr>
                        </tbody></table>
        </div>
        <div class="col-md-6 namecol">
            <p class="h4">Variables types</p>
             <table class="stats" style="margin-left: 1em;">
                        <tbody><tr><th>Numeric</th>
                        <td>11</td></tr>
                        <tr><th>Categorical</th>
                        <td>0</td></tr>
                        <tr><th>Date</th>
                        <td>0</td></tr>
                        <tr><th>Text (Unique)</th>
                        <td>0</td></tr>
                        <tr><th>Rejected</th>
                        <td>2</td></tr>
                        </tbody></table>
        </div>
        <div class="col-md-12" style="padding-left: 1em;">
            <p class="h4">Feature Facts</p>
            <ul class="list-unstyled"><li><code>AvgTimeBtwClicks</code> has 62662 / 5.7% missing values <span class="label label-default">Missing</span></l><li><code>BuyOrNot</code> has 591291 / 53.7% zeros</l><li><code>Distinct_Items</code> is highly correlated with <code>Clicks</code> (ρ = 0.91423) <span class="label label-primary"></span></l><li><code>MaxTimeBtwClicks</code> has 62662 / 5.7% missing values <span class="label label-default">Missing</span></l><li><code>Month</code> is highly correlated with <code>Session_ID</code> (ρ = 0.99022) <span class="label label-primary"></span></l><li><code>Session_Time</code> has 62692 / 5.7% zeros</l></ul>
        </div>
     </div>


    <div class="row headerrow highlight">
            <h1>Variables</h1>
    </div>

    <div class="row variablerow">
        <div class="col-md-3 namecol">
            <p class="h4">AvgTimeBtwClicks<br/><small>Numeric</small></p>
        </div>

        <div class="col-md-6">
            <div class="row">
                <div class="col-sm-6">
                    <table class="stats ">
                        <tr><th>Distinct count</th>
                        <td>730141</td></tr>
                        <tr><th>Unique (%)</th>
                        <td>70.3%</td></tr>
                        <tr class="alert"><th>Missing (%)</th>
                        <td>5.7%</td></tr>
                        <tr class="alert"><th>Missing (n)</th>
                        <td>62662</td></tr>
                    </table>

                </div>
                <div class="col-sm-6">
                    <table class="stats ">

                        <tr><th>Mean</th>
                        <td>3.0556</td></tr>
                        <tr><th>Minimum</th>
                        <td>0</td></tr>
                        <tr><th>Maximum</th>
                        <td>59.982</td></tr>
                        <tr class="ignore"><th>Zeros (%)</th>
                        <td>0.0%</td></tr>
                    </table>
                </div>
            </div>
        </div>
        <div class="col-md-3 collapse in" id="minihistogram862806059">
             <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAABAtJREFUeJzt3U9ok3ccx/FPmpC1axntZhLHyhhDD7uN4qAGpA0KQhQCQpdDLx14EQQvHitjA28tUhbPnnoI1B48VAQpHhIm6E3YoXRgPDXPM9tNo3Uk4bfTOsTuCyn6e/Lo%2B3UL9MfvW/i9yZM/D0k455w8C4JA1WpV5XJZ2WzW9/aImSjPSyKKQIC4GIh6AKCfpaLaONhpHWhdZnRYiUTiLU8D7C%2ByQH68%2BUibzZc9rTmS%2B1i/zH2nVCqysfGBieyk/bXb0c7Ldk9rnu123tE0wP54DQIYCAQwEAhgIBDAQCCAgUAAA4EABgIBDAQCGAgEMBAIYCAQwEAggIFAAAOBAAYCAQwEAhgIBDAQCGAgEMBAIICBQAADgQAGAgEMBAIYCAQwEAhgIBDAQCCAgUAAA4EABgIBDAQCGAgEMBAIYCAQwEAggIFAAEOsfnA8OZBQt9s92NpkUolE4i1PhPddrAL5YmxQP918pMdPd3ta99VnQ/r5%2B2%2BVSsXq30UfiN2Jefx0VxtbL6IeAx%2BI2AVyEAe9NHPOSdKBLs24pHs/JNy/p8Cz1V9/15%2B77Z7WfPnpoNZ/%2B6PnS6zJr0eVTg2o%2BezvntZ98/mItl%2B0e16X%2B%2BQj/TB9RMlksqd1%2BH9RXR5HEkgQBKpWqyqXy8pms763R8xEeV4ieZs3DENVKhWFYRjF9oiZKM8Ln4MABgIBDAQCGAgEMEQSSCaT0cWLF5XJZKLYHjET5XmJ7HMQIA64xAIMBAIYCAQwEAhgIBDAQCCAgUAAg/dAbt%2B%2BrbNnz%2Br06dO6fv267%2B0RA%2Bvr6zp37pyKxaKuXr0qSdrY2FC5XFaxWNSlS5f06tUrP8M4j8IwdIVCwe3s7LhOp%2BPm5uZcrVbzOQL63JMnT9yJEydcs9l0nU7Hzc7Ounv37rlSqeQePHjgnHNuaWnJLS4uepnH6zNIvV7X5OSkRkdHlUwmVSqVtLa25nME9Lm7d%2B/qzJkzymazSiaTunbtmo4ePapWq6Vjx45JkmZmZrydG6/3MTabTeVyub3HuVxOW1tbPkdAn2s0Gkqn0zp//rzCMFShUND09PRr5yabzarZbHqZx2sgbp%2BvfQ0M8D4B/tPtdlWr1bS8vKzh4WFduHBBQ0NDb/ydr3Pj9XTmcjkFQbD3OAgCHT582OcI6HOHDh3S8ePHNTY2pnQ6rZMnT6rRaLx2u20Yht7OjddA8vm87t%2B/r%2B3tbbXbbd26dUtTU1M%2BR0CfKxQKqtfrev78%2Bd6zycTEhAYHB/Xw4UNJ0srKirdz4/3r7nfu3FGlUlG73dapU6d0%2BfJln9sjBlZXV3Xjxg11Oh3l83nNz89rc3NTV65cUavV0vj4uBYWFjQyMvLOZ%2BF%2BEMDAK2TAQCCA4R9/bBqCwCG42AAAAABJRU5ErkJggg%3D%3D">

        </div>
       <div class="col-md-12 text-right">
            <a role="button" data-toggle="collapse" data-target="#descriptives862806059,#minihistogram862806059" aria-expanded="false" aria-controls="collapseExample">
                Toggle details
            </a>
        </div>
        <div class="row collapse col-md-12" id="descriptives862806059">
            <div class="col-sm-4">
                  <p class="h4">Quantile statistics</p>
                  <table class="stats indent">
                        <tr><th>Minimum</th>
                        <td>0</td></tr>
                        <tr><th>5-th percentile</th>
                        <td>0.22382</td></tr>
                        <tr><th>Q1</th>
                        <td>0.81546</td></tr>
                        <tr><th>Median</th>
                        <td>1.5664</td></tr>
                        <tr><th>Q3</th>
                        <td>3.138</td></tr>
                        <tr><th>95-th percentile</th>
                        <td>10.762</td></tr>
                        <tr><th>Maximum</th>
                        <td>59.982</td></tr>
                        <tr><th>Range</th>
                        <td>59.982</td></tr>
                        <tr><th>Interquartile range</th>
                        <td>2.3225</td></tr>
                  </table>
                  <p class="h4">Descriptive statistics</p>
                  <table class="stats indent">
                        <tr><th>Standard deviation</th>
                        <td>5.0121</td></tr>
                        <tr><th>Coef of variation</th>
                        <td>1.6403</td></tr>
                        <tr><th>Kurtosis</th>
                        <td>35.814</td></tr>
                        <tr><th>Mean</th>
                        <td>3.0556</td></tr>
                        <tr><th>MAD</th>
                        <td>2.6684</td></tr>
                        <tr class=""><th>Skewness</th>
                        <td>5.1152</td></tr>
                        <tr><th>Sum</th>
                        <td>3172700</td></tr>
                        <tr><th>Variance</th>
                        <td>25.121</td></tr>
                        <tr><th>Memory size</th>
                        <td>8.4 MiB</td></tr>
                 </table>
            </div>
             <div class="col-sm-8 histogram">
                 <img 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%2BflKT0/X5MmTVVZWZtm3r7UBAAD6ErCAtXLlSu3fv19bt27V%2BvXrtXPnTu3cuVOStHjxYrlcLlVVVWnWrFnKzc1VY2OjJOnDDz9UTk6OsrOzVVVVpaioKOXk5JjH3bVrl0pKSrRixQpt375dR48eVVFRkTm/bt061dXVqby8XAUFBSouLtbLL79szufk5PS6NgAAgC8CErBOnz6t//qv/9LKlSuVmJioCRMm6Cc/%2BYmOHj2q1157TQ0NDVq%2BfLmuv/56LVq0SMnJyaqsrJQk7dy5U2PHjtX8%2BfM1atQorVmzRidPntSBAwckSeXl5Zo3b56mTp2qxMREFRYWqrKyUm63W%2B3t7aqsrNTDDz%2Bs%2BPh4ZWZmauHChdqxY4ckaf/%2B/aqvr%2B91bQAAAF8EJGBVV1crIiJC48aNM8d%2B%2BtOfatWqVTp69KgSEhLkdDrNubS0NB05ckSSVFNTo/T0dHMuLCxMN9xwgw4fPiyv16va2lrLcZOTk9XZ2aljx47p2LFj6u7uVnJysuXYNTU15rE/b20AAABfBCRg1dfXKy4uTs8%2B%2B6y%2B%2B93vKjMzUyUlJTIMQy0tLXK5XJbto6Oj1dTUJElqbm7uMT9s2DA1NTXpzJkzcrvdlvmQkBANGTJEjY2Namlp0ZAhQ%2BRwOCzHdrvdOnXqVJ9rAwAA%2BMLR9yb2%2B%2BSTT/Tee%2B9p586dWrt2rVpaWvToo48qPDxc7e3tCg0NtWwfGhoqj8cjSero6Oh1vqOjw3x8oXmv13vBOenTm9/7WhsAAMAXloB12223KTs7W9/73vcUERFxyRYNCQnRuXPntGHDBl199dWSpJMnT%2BqZZ57RTTfdpLa2Nsv2Ho9HYWFhkiSn09kj8Hg8HkVGRlrC0vnz4eHh6urquuCcJIWHh8vpdOr06dO9ru2L5uZmtbS0%2BLz9QOFwBClQ74kICQm2/I2LQ//8Q//8Q//8Q//8ExIS3Ot5OSYmpserVnayBKwJEyboV7/6ldasWaNvfetbuvXWWzVp0iQFBQXZuqjL5ZLT6TTDlSSNHDlSTU1Nio2N1dtvv23ZvrW1VTExMZKk2NjYHo1qbW3VmDFjFBUVJafTqdbWVo0cOVKS1N3drba2NsXExMjr9aqtrU1er1fBwcHmvmFhYYqMjFRsbKyOHz/e69q%2BqKioUHFxcY/xtNwtPh/jShMUFKSIiHDLS6uBEBkZHtD1Bzr65x/65x/65x/613/bt2%2B54Hk5NzdXS5YsuWTrWs6YP//5z3Xfffdp3759evbZZ7VkyRJFRkbq%2B9//vr7//e%2BbocVfSUlJcrvdev/99/W1r31NknTixAnFxcUpKSlJmzdvlsfjMa9IVVdXmzeuJyUl6dChQ%2Bax2tvbVVdXp6VLlyooKEhjx45VdXW1eSP84cOHNWjQIMXHx8swDDkcDh05ckSpqamSpIMHDyoxMdE8dmlpaa9r%2B2LOnDnKyMjoMb5q998utk1XDMMwdPZsuwJ5BSsyMlxnzrSru9sbkBoGMvrnH/rnH/rnH/rnn5CQ4F7Pyxdz8aQ/elySCAoK0qRJkzRp0iS1t7ervLxcJSUleuqpp5Samqp58%2Bbp5ptv9mvRkSNHaurUqcrLy1NBQYFaWlpUWlqqnJwcpaena/jw4crLy9PixYu1e/du1dbWau3atZKk7Oxsbd26VaWlpZo2bZqKi4s1YsQIM1DNnTtXBQUFGj16tFwulwoLCzV79mzznYFZWVkqKCjQ6tWr1dTUpLKyMvPY48eP/9y1feFyuS58yXH3Hr96FmhdXYakwD65u7u96uriF0x/0T//0D//0D//0L/%2B6/W8fIkFGYZhnD/Y3Nys559/Xs8//7zeeustpaam6gc/%2BIEaGxtVXl6urKwsLVu2zK%2BFP/74Y61cuVK/%2B93vFB4erh/96Ee65557JH36LsP8/HzV1NTo2muv1bJlyzRhwgRz3z179mjVqlVqampSamqqli9frri4OHO%2BtLRU27ZtU2dnp6ZPn65HHnnEvCLV0dGhwsJC7dq1SxEREVq4cKHuvPNOc9%2B%2B1u6vuRv36K3Gc34fJxASrrlK62ffKMnel4p95XAEKypqsE6dOscvmH6gf/6hf/6hf/6hf/75rH%2BBYAlYzz33nJ577jn9%2Bc9/1tChQ/X9739f2dnZuu6668wdKisrtWrVKh0%2BfDgQ9Q5YBKz%2B4xeMf%2Biff%2Biff%2Biff%2BiffwIZsCwvES5btkzTpk3Tpk2bNGXKFPNG8H90/fXX64477rhsBQIAAAw0loD16quvKioqSm1tbWa4%2BuzTzUNCQiRJqamp5g3iAAAA6Mlyierjjz/Wd77zHZWWlppjixYtUlZWlj788MPLXhwAAMBAZAlYq1ev1te%2B9jUtWLDAHHvppZc0fPhwrVmz5rIXBwAAMBBZAtbBgweVl5dn%2BWyIoUOH6t/%2B7d/02muvXfbiAAAABiJLwHI4HDpz5kyPjdrb23WBT3MAAADABVgC1pQpU7Ry5Up98MEH5lh9fb3WrFmjyZMnX/biAAAABiLLuwgffPBBLViwQNOnT1dkZKQk6cyZM0pISNBDDz0UkAIBAAAGGkvAio6O1m9%2B8xvt27dPb7/9thwOh0aPHq2JEyfa/oXPAAAAX1Q9voswJCREkydP5iVBAACAfrIErJaWFj3xxBM6dOiQOjs7e9zY/r//%2B7%2BXtTgAAICByBKwHnnkEb3xxhv63ve%2Bp4iIiEDVBAAAMKBZAtZrr72mLVu2aNy4cYGqBwAAYMCzfEzDV77yFUVHRweqFgAAgC8ES8DKysrSli1b1N3dHah6AAAABjzLS4RtbW168cUX9Yc//EEjRoxQaGioZeOnn376shYHAAAwEPX4mIYZM2YEog4AAIAvDEvAWrNmTaDqAAAA%2BMIIPn%2BgublZxcXF%2BvnPf66PPvpI//M//6N33nknELUBAAAMSJaA9f7772vmzJn6zW9%2Bo127dumTTz7RSy%2B9pOzsbB09ejRQNQIAAAwoloC1du1aZWZm6pVXXtGgQYMkSRs2bFBGRobWr18fkAIBAAAGGkvAOnTokBYsWGD5YmeHw6HFixerrq7ushcHAAAwEFkCltfrldfr7bHRuXPnFBISctmKAgAAGMgsAeumm27S5s2bLSGrra1NRUVFmjBhwmUvDgAAYCCyBKy8vDy98cYbuummm%2BR2u3XPPfdo2rRpamho0IMPPhioGgEAAAYUy%2BdgxcbG6tlnn9WLL76oN998U16vV7fffruysrJ01VVXBapGAACAAaXHJ7mHh4frtttuC0QtAAAAXwiWgPXjH//4czfmuwgBAAD6ZglYcXFxlsmuri69//77euuttzRv3rzLWhgAAMBA5dN3EW7atEmNjY2XpSAAAICBrsd3EV5IVlaW/vu///tS1wIAAPCF4FPAOnz4MB80CgAA4KM%2Bb3L/%2BOOP9de//lVz5869bEUBAAAMZJaAdc0111i%2Bh1CSBg0apDvuuEOzZs26rIUBAAAMVJaAtXbt2kDVAQAA8IVhCVgHDhzwecf09HTbiwEAAPgisASsO%2B%2B803yJ0DAMc/z8saCgIL355puXq0YAAIABxRKwfvWrX2nlypV64IEHNH78eIWGhqq2tlbLly/XD37wA91yyy2BqhMAAGDAsHxMw5o1a/Too49q%2BvTpioqK0uDBgzVhwgQtX75c//Ef/6G4uDjzDwAAAC7MErCam5svGJ6uuuoqnTp16rIVBQAAMJBZAlZycrI2bNigjz/%2B2Bxra2tTUVGRJk6ceNmLAwAAGIgs92A9/PDD%2BvGPf6wpU6bouuuuk2EYeu%2B99xQTE6Onn346UDUCAAAMKJaANWrUKL300kt68cUXdeLECUnSj370I33ve99TeHh4QAoEAAAYaBznD3z1q1/VbbfdpoaGBo0YMULSp5/mDgAAAN9Y7sEyDEPr169Xenq6ZsyYocbGRj344INatmyZOjs7A1UjAADAgGIJWOXl5XruuedUUFCg0NBQSVJmZqZeeeUVFRcXB6RAAACAgcYSsCoqKvToo4/q1ltvNT%2B9/ZZbbtHKlSv1wgsvBKRAAACAgcYSsBoaGjRmzJgeG8XHx6ulpeWyFQUAADCQWQJWXFycamtre2z06quvmje8AwAA4PNZ3kV41113qbCwUC0tLTIMQ/v371dFRYXKy8uVl5cXqBoBAAAGFEvAys7OVldXl5588kl1dHTo0Ucf1dChQ/Wv//qvuv322wNVIwAAwIBiCVgvvviivvOd72jOnDn629/%2BJsMwFB0dHajaAAAABiTLPVjLly83b2YfOnToZQlXixYt0kMPPWQ%2Bbmho0IIFC5SSkqIZM2Zo7969lu337dunmTNnKjk5WfPnz1d9fb1lftu2bZoyZYrS0tK0bNkyud1uc87j8Sg/P1/p6emaPHmyysrKLPv2tTYAAIAvLAHruuuu01tvvXXZFv/tb3%2BrV1991TKWk5Mjl8ulqqoqzZo1S7m5uWpsbJQkffjhh8rJyVF2draqqqoUFRWlnJwcc99du3appKREK1as0Pbt23X06FEVFRWZ8%2BvWrVNdXZ3Ky8tVUFCg4uJivfzyyz6tDQAA4CvLS4Tx8fG6//77tWXLFl133XVyOp2WjdesWWPbwqdPn1ZRUZFuvPFGc2z//v2qr6/Xzp075XQ6tWjRIu3fv1%2BVlZXKzc3Vzp07NXbsWM2fP9%2BsZ9KkSTpw4IDS09NVXl6uefPmaerUqZKkwsJC3XXXXXrggQfk9XpVWVmpX//614qPj1d8fLwWLlyoHTt26Oabb%2B5zbQAAAF9ZAta7776rtLQ0Sbrkn3u1bt06ZWVlqbm52RyrqalRQkKCJdilpaXpyJEj5nx6ero5FxYWphtuuEGHDx9WWlqaamtrtWTJEnM%2BOTlZnZ2dOnbsmLxer7q7u5WcnGw59ubNm31aGwAAwFeOX/ziF8rNzdVXvvIVlZeXX5ZF9%2B/fr%2Brqar3wwgsqKCgwx1taWuRyuSzbRkdHq6mpSZLU3NzcY37YsGFqamrSmTNn5Ha7LfMhISEaMmSIGhsbFRQUpCFDhsjhcFiO7Xa7derUqT7XBgAA8FVwWVmZ2tvbLYOLFi2yXFmyk8fj0WOPPWb5vsPPtLe39xgLDQ2Vx%2BORJHV0dPQ639HRYT6%2B0Hxvx/6spr7WBgAA8JXDMIwegwcOHLC8%2B85OGzduVGJior75zW/2mHM6nTp9%2BrRlzOPxKCwszJw/P/B4PB5FRkZawtL58%2BHh4erq6rrgnCSFh4f3ubavmpubv5BfK%2BRwBOm890RcNiEhwZa/cXHon3/on3/on3/on39CQoJ7PS/HxMT0eOXKTo6%2BN7HXSy%2B9pI8%2B%2BkgpKSmSpM7OTkmfvgPw7rvv1vHjxy3bt7a2KiYmRpIUGxvbo0mtra0aM2aMoqKi5HQ61draqpEjR0qSuru71dbWppiYGHm9XrW1tcnr9So4ONjcNywsTJGRkYqNjf3ctX1VUVGh4uLiHuNpuVsu6jhXkqCgIEVEhFteXg2EyMjwgK4/0NE//9A//9A//9C//tu%2BfcsFz8u5ubmW%2B7btdtnPmDt27FBXV5f5%2BLOPUXjggQd08uRJPfXUU/J4POYVqerqao0bN06SlJSUpEOHDpn7tre3q66uTkuXLlVQUJDGjh2r6upq80b4w4cPa9CgQYqPj5dhGHI4HDp69qXUAAAVcUlEQVRy5IhSU1MlSQcPHlRiYqJ57NLS0l7X9tWcOXOUkZHRY3zV7r9d1HGuJIZh6OzZdgXyClZkZLjOnGlXd7c3IDUMZPTPP/TPP/TPP/TPPyEhwb2ely/2AsrFckifXqG4XIYPH255PHjwYEnSiBEjFBcXp%2BHDhysvL0%2BLFy/W7t27VVtbq7Vr10r69Kt8tm7dqtLSUk2bNk3FxcUaMWKEGajmzp2rgoICjR49Wi6XS4WFhZo9e7b5zsCsrCwVFBRo9erVampqUllZmXns8ePHf%2B7avnK5XBe%2B5Lh7z0Ud50rT1WVICuyTu7vbq64ufsH0F/3zD/3zD/3zD/3rv17Py5eYQ5JWrlxp%2BXiCzs5OFRUVmeHnM3Z%2BDtaFBAcHq6SkRPn5%2BcrOzta1116rTZs26eqrr5YkxcXFaePGjVq1apVKSkqUmpqqTZs2mfvfcsstOnnypAoKCtTZ2anp06fr/vvvN%2BcfeughFRYWat68eYqIiNC9996rzMxMn9YGAADwVdAdd9zR8y73Xlyuj3H4Ipq7cY/eajwX6DL6JeGaq7R%2B9o2SLt%2BVzn/kcAQrKmqwTp06x//B9QP98w/98w/98w/9889n/QvI2oQmAAAAe/G%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%2BfPV319vWV%2B27ZtmjJlitLS0rRs2TK53W5zzuPxKD8/X%2Bnp6Zo8ebLKysos%2B/a1NgAAQF8CFrCWLl0qt9utZ555Rhs2bNDvf/97/fKXv5QkLV68WC6XS1VVVZo1a5Zyc3PV2NgoSfrwww%2BVk5Oj7OxsVVVVKSoqSjk5OeZxd%2B3apZKSEq1YsULbt2/X0aNHVVRUZM6vW7dOdXV1Ki8vV0FBgYqLi/Xyyy%2Bb8zk5Ob2uDQAA4IuABKx33nlHNTU1WrNmjUaNGqW0tDQtXbpUL774ol577TU1NDRo%2BfLluv7667Vo0SIlJyersrJSkrRz506NHTtW8%2BfP16hRo7RmzRqdPHlSBw4ckCSVl5dr3rx5mjp1qhITE1VYWKjKykq53W61t7ersrJSDz/8sOLj45WZmamFCxdqx44dkqT9%2B/ervr6%2B17UBAAB8EZCAFRMToy1btmjo0KGW8bNnz%2Bro0aNKSEiQ0%2Bk0x9PS0nTkyBFJUk1NjdLT0825sLAw3XDDDTp8%2BLC8Xq9qa2s1btw4cz45OVmdnZ06duyYjh07pu7ubiUnJ1uOXVNTYx7789YGAADwhSMQi0ZERGjSpEnmY8MwtGPHDk2cOFEtLS1yuVyW7aOjo9XU1CRJam5u7jE/bNgwNTU16cyZM3K73Zb5kJAQDRkyRI2NjQoKCtKQIUPkcDgsx3a73Tp16lSfawMAAPjiingX4S9%2B8Qu9%2Beab%2BtnPfqb29naFhoZa5kNDQ80b4Ds6Onqd7%2BjoMB9faL63Y0v63PnP1gYAAPBFQK5g/aOioiKVl5friSee0OjRo%2BV0OnX69GnLNh6PR2FhYZIkp9PZI/B4PB5FRkZawtL58%2BHh4erq6rrgnCSFh4f3ubYvmpub1dLS4vP2A4XDEaRA5fGQkGDL37g49M8/9M8/9M8/9M8/ISHBvZ6XY2JierxqZaeABqwVK1aooqJCRUVFyszMlCTFxsbq%2BPHjlu1aW1sVExNjzp/fqNbWVo0ZM0ZRUVFyOp1qbW3VyJEjJUnd3d1qa2tTTEyMvF6v2tra5PV6FRwcbO4bFhamyMjIPtf2RUVFhYqLi3uMp%2BVu8fkYV5qgoCBFRIRbXloNhMjI8ICuP9DRP//QP//QP//Qv/7bvn3LBc/Lubm5WrJkySVbN2BnzOLiYlVUVOjxxx/Xt7/9bXM8KSlJpaWl8ng85hWp6upq88b1pKQkHTp0yNy%2Bvb1ddXV1Wrp0qYKCgjR27FhVV1ebN8IfPnxYgwYNUnx8vAzDkMPh0JEjR5SamipJOnjwoBITE31a2xdz5sxRRkZGj/FVu/92Me25ohiGobNn2xXIK1iRkeE6c6Zd3d3egNQwkNE//9A//9A//9A//4SEBPd6Xr6Yiyf9EZCAdeLECT355JP6l3/5F6WkpKi1tdWcGz9%2BvIYPH668vDwtXrxYu3fvVm1trdauXStJys7O1tatW1VaWqpp06apuLhYI0aMMAPV3LlzVVBQoNGjR8vlcqmwsFCzZ8823xmYlZWlgoICrV69Wk1NTSorKzOP3dfavnC5XBe%2B5Lh7T3/bdUXo6jIkBfbJ3d3tVVcXv2D6i/75h/75h/75h/71X6/n5UssyDAM43Iv%2BtRTT%2Bnxxx%2B3jBmGoaCgIL355pv64IMPtGzZMtXU1Ojaa6/VsmXLNGHCBHPbPXv2aNWqVWpqalJqaqqWL1%2BuuLg4c760tFTbtm1TZ2enpk%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%2B9rfc%2Bag90Kf1yXXS4fvbtrwe6DADAlwgBCz5576N2vdV4LtBlAAAwIHAPFgAAgM0IWAAAADYjYAEAANiMgAUAAGAzAhYAAIDNCFgAAAA2I2ABAADYjIAFAABgMwIWAACAzQhYAAAANiNgAQAA2IyABQAAYDMCFgAAgM0IWAAAADZzBLoA4FILCQ6SZAS6DBsEBboAAICPCFgX4PF49Nhjj%2Bl3v/udwsLC9JOf/EQLFiwIdFnop7ioMD3%2Bu7f13kftgS6lX66LDtfPvv31QJcBALgIBKwLWLdunerq6lReXq6GhgY9%2BOCDiouL08033xzo0tBP733UrrcazwW6DADAlwT3YJ2nvb1dlZWVevjhhxUfH6/MzEwtXLhQO3bsCHRpAABggCBgnefYsWPq7u5WcnKyOZaWlqaampoAVoUvs7/fQ9bfP151dXVJ8vp5HH//AMCXBy8RnqelpUVDhgyRw/H31kRHR8vtduvUqVOKiooKYHX4Mhro95BdPyxc92b%2Bv0CX4QevDIOACODiELDO097ertDQUMvYZ489Hk8gSgIG9D1k10aHD/iA%2BMitY/X3K4ADzWc1B%2BpdqOdfQe0v3kWLgYWAdR6n09kjSH32ODw8vM/9m5ub1dLS0mP8uui%2B971SXf3VMHkH4nnl/3fNV50D%2BrXwL0L9jafdgS6j31yRTpX94biazgzM/4Yxw6/S3851Dtj6YyOdmjN%2BRKDLCJjgYKmrq0vBwZKDM/ZFCw7u/bwcExMjl8t1ydbmn%2Bs8sbGxamtrk9frVXDwp6e11tZWhYWFKTIyss/9KyoqVFxc3GM8PT1dT2zYcEn/Mb%2BompubVVFRoTlz5tC/fqB//vmsf/fQv37h588/zc3NevrprfSvn5qbm3XffffpwIEDPeZyc3O1ZMmSS7Y2Aes8Y8aMkcPh0JEjR5SamipJOnjwoBITE33af86cOcrIyLCMnThxQg888IBaWlp4gvRDS0uLiouLlZGRQf/6gf75h/75h/75h/75p6WlRQcOHFBRUZFGjRplmYuJibmkaxOwzhMWFqasrCwVFBRo9erVampqUllZmdauXevT/i6XiycBAABXkFGjRikhIeGyrknAuoCHHnpIhYWFmjdvniIiInTvvfcqMzMz0GUBAIABgoB1AWFhYVqzZo3WrFkT6FIAAMAANJDfnAQAAHBFCnnsscceC3QRXwaDBw/W%2BPHjNXjw4ECXMiDRP//QP//QP//QP//QP/8Eqn9BBh9RDAAAYCteIgQAALAZAQsAAMBmBCwAAACbEbAAAABsRsACAACwGQELAADAZgQsAAAAmxGwLjGPx6P8/Hylp6dr8uTJKisrC3RJA4LH49HMmTN14MABc6yhoUELFixQSkqKZsyYob179wawwitTU1OTli5dqm984xuaOnWq1q5dK4/HI4n%2B%2BeKDDz7QXXfdpZSUFGVkZOjXv/61OUf/fLdo0SI99NBD5mN655tXXnlF8fHxGjNmjPn3vffeK4ke%2BsLj8aiwsFDjx4/XTTfdpMcff9ycC0T/CFiX2Lp161RXV6fy8nIVFBSouLhYL7/8cqDLuqJ5PB7dd999On78uGU8JydHLpdLVVVVmjVrlnJzc9XY2BigKq9MS5culdvt1jPPPKMNGzbo97//vX75y19KkhYvXkz/PodhGFq0aJGGDRum5557To899piefPJJ/fa3v5VE/3z129/%2BVq%2B%2B%2BqpljOeub44fP66MjAzt3btXe/fu1Z/%2B9CetWrVKEj9/vli5cqX279%2BvrVu3av369dq5c6d27twpKUD9M3DJfPLJJ8aNN95oHDhwwBwrKSkx7rzzzgBWdWU7fvy4kZWVZWRlZRnx8fHG66%2B/bhiGYezbt89ISUkxOjo6zG3nz59vbNy4MVClXnFOnDhhxMfHGx999JE59uKLLxpTpkwx9u/fT//60NzcbPzsZz8zzp07Z47l5uYahYWF9M9HbW1txtSpU43bbrvNyMvLMwyD5%2B7FuP/%2B%2B40NGzb0GKeHfWtrazMSEhIs59unnnrKyM/PD9jzlytYl9CxY8fU3d2t5ORkcywtLU01NTUBrOrK9vrrr2vixImqqKiQ8Q/f4lRTU6OEhAQ5nU5zLC0tTUeOHAlEmVekmJgYbdmyRUOHDrWMnz17VkePHqV/fYiJidGGDRv0la98RZJUXV2tgwcPavz48fTPR%2BvWrVNWVpZGjRpljvHc9d2JEyc0cuTIHuP0sG/V1dWKiIjQuHHjzLGf/vSnWrVqVcCevwSsS6ilpUVDhgyRw%2BEwx6Kjo%2BV2u3Xq1KkAVnbluv322/Xggw9angjSp710uVyWsejoaDU1NV3O8q5oERERmjRpkvnYMAzt2LFDEydOpH8XKSMjQ3fccYeSk5N188030z8f7N%2B/X9XV1crJybGM0zvfvfvuu9qzZ4%2BmT5%2Bub3/72/r3f/93dXZ20kMf1NfXKy4uTs8%2B%2B6y%2B%2B93vKjMzUyUlJTIMI2D9c/S9Cfqrvb1doaGhlrHPHn924zF801sv6WPvfvGLX%2BjNN99UZWWlysrK6N9F2Lhxo1pbW/XYY49p9erV/Pz1wePx6LHHHlNBQUGPPtE73/zf//2fOjo65HQ69ctf/lINDQ1atWqVOjo66KEPPvnkE7333nvauXOn1q5dq5aWFj366KMKDw8PWP8IWJeQ0%2Bns8Q/42ePw8PBAlDRgOZ1OnT592jLm8XgUFhYWoIqubEVFRSovL9cTTzyh0aNH07%2BLlJCQIEnKy8vT/fffrx/%2B8Ic6c%2BaMZRv693cbN25UYmKivvnNb/aY42fPN9dcc43%2B/Oc/KzIyUpIUHx8vr9erBx54QLfeeis/f30ICQnRuXPntGHDBl199dWSpJMnT%2BqZZ57RTTfdpLa2Nsv2l6N/BKxLKDY2Vm1tbfJ6vQoO/vTV2NbWVoWFhZlPIvgmNja2x7sKW1tbFRMTE6CKrlwrVqxQRUWFioqKlJmZKYn%2B%2BeKjjz7S4cOHzZ5J0ujRo9XZ2amYmBidOHHCsj39%2B7uXXnpJH330kVJSUiRJnZ2dkqRdu3bp7rvv5mfPR%2BefF0aNGiW3261hw4bx89cHl8slp9NphitJGjlypJqamhQbG6u3337bsv3l6B/3YF1CY8aMkcPhsNxId/DgQSUmJgawqoEpKSlJdXV1liuC1dXVljcQQCouLlZFRYUef/xxffe73zXH6V/fGhoatGTJEjU3N5tjtbW1io6OVlpamv7yl7/Qv17s2LFDL7zwgp5//nk9//zzysjIUEZGhp577jndeOON/Oz54E9/%2BpO%2B8Y1vyO12m2N1dXWKiorSuHHj%2BPnrQ1JSktxut95//31z7MSJE4qLi1NSUlJA%2BkfAuoTCwsKUlZWlgoIC1dbW6pVXXlFZWZnmzZsX6NIGnPHjx2v48OHKy8vT8ePH9dRTT6m2tlY//OEPA13aFePEiRN68skntWjRIqWkpKi1tdX8Q//6NnbsWCUmJio/P18nTpzQH//4R61fv1733HOP0tPT6d/nGD58uEaMGGH%2BGTx4sAYPHqwRI0bws%2BejlJQUhYeHa9myZXr33Xf1xz/%2BUUVFRfrpT3/Kz58PRo4cqalTpyovL0/Hjh3Tnj17VFpaqrlz5wauf5f0QyBgtLe3G3l5eUZKSooxZcoU4%2Bmnnw50SQPGP34OlmEYxgcffGDccccdxo033mjMmDHD2L9/fwCru/Js3rzZiI%2BPt/z553/%2BZyM%2BPt4wDMN4//336V8fmpubjSVLlhjjxo0zJk%2BebGzevNmc4%2BfPd3l5eebnYBkGvfPV8ePHjZ/85CdGamqqMXnyZGPTpk3mHD3s29mzZ40HH3zQSE1NNSZNmmSUlJSYc4HoX5Bh/MOHDQEAAMBvvEQIAABgMwIWAACAzQhYAAAANiNgAQAA2IyABQAAYDMCFgAAgM0IWAAAADYjYAEAANiMgAUAAGAzAhYAAIDNCFgAAAA2I2ABAADYjIAFAABgs/8PGXJ9paJOPZQAAAAASUVORK5CYII%3D">
             </div>
      </div>
    </div><div class="row variablerow">
        <div class="col-md-3 namecol">
            <p class="h4">BuyOrNot<br/><small>Numeric</small></p>
        </div>

        <div class="col-md-6">
            <div class="row">
                <div class="col-sm-6">
                    <table class="stats ">
                        <tr><th>Distinct count</th>
                        <td>2</td></tr>
                        <tr><th>Unique (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (n)</th>
                        <td>0</td></tr>
                    </table>

                </div>
                <div class="col-sm-6">
                    <table class="stats ">

                        <tr><th>Mean</th>
                        <td>0.46294</td></tr>
                        <tr><th>Minimum</th>
                        <td>0</td></tr>
                        <tr><th>Maximum</th>
                        <td>1</td></tr>
                        <tr class="alert"><th>Zeros (%)</th>
                        <td>53.7%</td></tr>
                    </table>
                </div>
            </div>
        </div>
        <div class="col-md-3 collapse in" id="minihistogram-1494417826">
             <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAA5pJREFUeJzt3bFLM3ccx/GPJh1CFYIPSaRQeNpC6eD4KNZFdMmQEx0KgUeQrBUnV6E4uThW/4FukWeQDOokliooFOzUodOzaMyFJzqkOpjz26lpH5Qv9aGXU573azsuP%2B8X%2BL293JEjfWZm6rEwDPXzr7/riy%2B/UiaT%2Bc/j%2BiR98/mQ%2Bvv745scnpwwDFWtVlUul5XP53t67L4kApGk1z/%2Boj8u/nzUmK%2BHP9VP33%2BrdDod06yA9/GvGHAQCOAgEMBBIICDq130jJkpiqIPGpvUjRkCQc9EUaQftn7T23c3jxr38kVGa69fxTQrH4Ggp96%2Bu3n07f0kcQ0COAgEcBAI4CAQwEEggINAAAeBAA4CARwEAjgIBHAQCOAgEMBBIICDQAAHgQAOAgEcBAI4CARwEAjgIBDAQSCAg0AAB4EADgIBHAQCOAgEcBAI4CAQwEEggINAAAeBAA4CARwEAjgIBHAQCOAgEMBBIICDQAAHgQCOxH4n/btXn%2Bnq5vZRY7KZTxRFUUwzQtyiKNLLF5lHj/uQMf%2BXPjOzXh80DENVq1WVy2Xl8/leHx7PTJLrJZGPWM1mUxsbG2o2m0kcHs9MkuuFaxDAQSCAg0AAB4EAjkQCyeVyWlpaUi6XS%2BLweGaSXC%2BJ3OYFngs%2BYgEOAgEcBAI4CARwEAjgIBDAQSCAI/ZAdnd3FQSBisWiNjc37%2B1vNBpaWFhQqVRSpVJRq9WKe0p4wtrttmZmZnR%2Bfn5vXyJrxWLUbDZtamrKLi8vrdPpWKVSscPDw/des7i4aNvb22Zm9ubNG1teXo5zSnjCTk9PLQgCGxkZsbOzs3v7k1grsZ5Bjo6OND4%2Brmw2q1QqpdnZWe3s7HT3dzodnZycKAgCSdLc3JwODg54avAjtbW1pdXV1QcfikpqrcT6yG2j0VChUOhuFwoFXVxcdLevrq40MDCgVColSUqlUhocHFSr1eJ7Wh%2BhtbU1SZI98O2npNZKrGeQh95of/8/h7y7u3twzL9fA0jJrZVY/3qhUFAYht3tMAw1PDzc3R4aGlK73e6%2B%2BSiKdH19rWw2G%2Be08AwltVZiDWRiYkLHx8dqtVq6vb1VrVbT5ORkd386ndbo6KhqtZokqVaraWxsrHsaBf6W2FqJ%2By7A3t6eBUFgxWLR1tfXzcxsZWXF9vf3zcysXq9bpVKxUqlk8/PzVq/X454Snrjp6enuXayk1wrPgwAOroYBB4EAjr8A7VkINFUB1CYAAAAASUVORK5CYII%3D">

        </div>
       <div class="col-md-12 text-right">
            <a role="button" data-toggle="collapse" data-target="#descriptives-1494417826,#minihistogram-1494417826" aria-expanded="false" aria-controls="collapseExample">
                Toggle details
            </a>
        </div>
        <div class="row collapse col-md-12" id="descriptives-1494417826">
            <div class="col-sm-4">
                  <p class="h4">Quantile statistics</p>
                  <table class="stats indent">
                        <tr><th>Minimum</th>
                        <td>0</td></tr>
                        <tr><th>5-th percentile</th>
                        <td>0</td></tr>
                        <tr><th>Q1</th>
                        <td>0</td></tr>
                        <tr><th>Median</th>
                        <td>0</td></tr>
                        <tr><th>Q3</th>
                        <td>1</td></tr>
                        <tr><th>95-th percentile</th>
                        <td>1</td></tr>
                        <tr><th>Maximum</th>
                        <td>1</td></tr>
                        <tr><th>Range</th>
                        <td>1</td></tr>
                        <tr><th>Interquartile range</th>
                        <td>1</td></tr>
                  </table>
                  <p class="h4">Descriptive statistics</p>
                  <table class="stats indent">
                        <tr><th>Standard deviation</th>
                        <td>0.49863</td></tr>
                        <tr><th>Coef of variation</th>
                        <td>1.0771</td></tr>
                        <tr><th>Kurtosis</th>
                        <td>-1.9779</td></tr>
                        <tr><th>Mean</th>
                        <td>0.46294</td></tr>
                        <tr><th>MAD</th>
                        <td>0.49725</td></tr>
                        <tr class=""><th>Skewness</th>
                        <td>0.14863</td></tr>
                        <tr><th>Sum</th>
                        <td>509700</td></tr>
                        <tr><th>Variance</th>
                        <td>0.24863</td></tr>
                        <tr><th>Memory size</th>
                        <td>8.4 MiB</td></tr>
                 </table>
            </div>
             <div class="col-sm-8 histogram">
                 <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAIABJREFUeJzt3X14VPWd//9XbsiNlGwiZICyWBHWBhLMJCGsLoILm2pLgWhTQFEbqMhuSYDdipUbdQz3NFZrCbE1SNRwdQsm26LWXaylrRZQIQQSG6NCbSGWJBNNBHUyk2TO7w9/zrdDiJmBkxwmPB/XxRXn8znnfN55m%2BS8cubMJMwwDEMAAAAwTbjVBQAAAPQ3BCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMJllAcvj8aigoEATJ07U9ddfr0cffdQ3V19frwULFigtLU0zZszQvn37/Pbdv3%2B/Zs6cKbvdrvnz5%2BvkyZN%2B80899ZSmTJmijIwMrV69Wm6322/dVatWKTMzU5MnT1Zpaanfvj2tDQAA0BPLAta6det04MABbd%2B%2BXQ8//LB27dqlXbt2SZIWL14sm82miooKzZo1S/n5%2BWpoaJAknTp1Snl5ecrJyVFFRYUSEhKUl5fnO%2B6ePXtUXFystWvX6umnn9bRo0dVWFjom9%2B8ebNqa2tVVlYmh8OhoqIivfTSS775vLy8btc%2BX01NTdqyZYuampou6Dg4P/TfWvTfWvTfWvTfWpb237BAa2urkZycbBw8eNA39sQTTxirVq0yDhw4YKSlpRltbW2%2Bufnz5xtbtmwxDMMwfvzjHxt33nmnb87lchnp6enGG2%2B8YRiGYdx%2B%2B%2B1GUVGRb/7QoUNGamqq0dbWZnz66afGNddc47ducXGx73j79%2B//wrXP15tvvmlcffXVxptvvnlBx8H5of/Wov/Wov/Wov/WsrL/llzBqqys1KBBgzRhwgTf2N13363169fr6NGjSk5OVnR0tG8uIyNDR44ckSRVV1crMzPTNxcTE6Nx48apqqpKXq9XNTU1fse12%2B1qb29XXV2d6urq1NnZKbvd7nfs6upq37G/aG0AAIBAWBKwTp48qREjRuhXv/qVvvGNbygrK0vFxcUyDENOp1M2m81v%2B8GDB6uxsVHSZ5f7zp4fMmSIGhsbdfr0abndbr/5iIgIxcfHq6GhQU6nU/Hx8YqMjPQ7ttvtVktLS49rAwAABCKy503M9%2Bmnn%2Bovf/mLdu3apU2bNsnpdOrBBx9UbGysXC6XoqKi/LaPioqSx%2BORJLW1tXU739bW5nt8rnmv13vOOemzm997WhsAACAQlgSsiIgIffLJJ3rkkUc0bNgwSdL777%2Bvn//857r%2B%2BuvV2trqt73H41FMTIwkKTo6ukvg8Xg8iouL8wtLZ8/Hxsaqo6PjnHOSFBsbq%2BjoaH300Ufdrh2IpqYmOZ1Ov7Hjx48HvD8AADDXuc7DiYmJXZ61MpMlActmsyk6OtoXriRp1KhRamxs1NChQ/Xuu%2B/6bd/c3KzExERJ0tChQ7sEmObmZo0dO1YJCQmKjo5Wc3OzRo0aJUnq7OxUa2urEhMT5fV61draKq/Xq/DwcN%2B%2BMTExiouL09ChQ3Xs2LFu1w7Ezp07VVRU1GU8Ly9PycnJAR8H5klOTtbbb79tdRmXLPpvLfpvLfpvreTkZGVmZuree%2B/tMpefn68lS5b02tqWBKzU1FS53W799a9/1Ve%2B8hVJn6XLESNGKDU1VT/72c/k8Xh8V6QqKyt9N66npqbq8OHDvmO5XC7V1tZq6dKlCgsL0/jx41VZWem7Eb6qqkoDBgxQUlKSDMNQZGSkjhw5ovT0dEnSoUOHlJKS4jt2SUlJt2sHYu7cuZo2bVqX8cTERJ0%2B7VJnpzfYduECRUSEKy4ulv5bhP5bi/5bi/5bKyIiXI888kiXCzOSgrp4cj4sCVijRo3SDTfcoBUrVsjhcMjpdKqkpER5eXnKzMzU8OHDtWLFCi1evFh79%2B5VTU2NNm3aJEnKycnR9u3bVVJSoqlTp6qoqEgjR470Bap58%2BbJ4XBozJgxstlsKigo0Jw5c3yvDMzOzpbD4dCGDRvU2Nio0tJS37EnTpz4hWsHwmazdXvJsaXlE3V08A1mlc5OL/23EP23Fv23Fv23zhedl3tTmGEYRp%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%2BZM2fKbrdr/vz5OnnypN/8U089pSlTpigjI0OrV6%2BW2%2B32zXk8Hq1atUqZmZmaPHmySktL/fbtaW0AAICeWBawjh07pmnTpmnfvn3at2%2Bf/vjHP2r9%2BvWSpMWLF8tms6miokKzZs1Sfn6%2BGhoaJEmnTp1SXl6ecnJyVFFRoYSEBOXl5fmOu2fPHhUXF2vt2rV6%2BumndfToURUWFvrmN2/erNraWpWVlcnhcKioqEgvvfSSbz4vL6/btQEAuLQYIf7Pa35LAhRp1cLHjx/XP/3TP%2Bnyyy/3Gz9w4IDq6%2Bv17LPPKjo6WosWLdKBAwdUXl6u/Px87dq1S%2BPHj9f8%2BfMlSRs3btSkSZN08OBBZWZmqqysTLm5ubrhhhskSQUFBbrrrrt07733yuv1qry8XE8%2B%2BaSSkpKUlJSkhQsXaseOHbrxxht14MABnTx5Urt27Trn2gAAXGoe/c07%2BssHLqvLOC9XDo7VhnkTLFnb0oA1adKkLuPV1dVKTk5WdHS0bywjI0NHjhzxzWdmZvrmYmJiNG7cOFVVVSkjI0M1NTVasmSJb95ut6u9vV11dXXyer3q7OyU3W73O/bPfvazgNYGAOBS85cPXHqn4ROrywg5lj1F%2BN577%2BnVV1/VTTfdpK997Wv60Y9%2BpPb2djmdTtlsNr9tBw8erMbGRklSU1NTl/khQ4aosbFRp0%2Bfltvt9puPiIhQfHy8Ghoa5HQ6FR8fr8jISL9ju91utbS09Lg2AABAICy5gvW3v/1NbW1tio6O1mOPPab6%2BnqtX79ebW1tcrlcioqK8ts%2BKipKHo9HktTW1tbtfFtbm%2B/xuea9Xu8556TPbn7vaW0AAIBAWBKwvvzlL%2Bv1119XXFycJCkpKUler1f33nuvvvWtb%2Bn06dN%2B23s8HsXExEiSoqOjuwQej8ejuLg4v7B09nxsbKw6OjrOOSdJsbGxio6O1kcffdTt2oFoamqS0%2BkMePtQERkZplB9V4%2BIiHC/j%2Bhb9N9a9N9aod9/624SN0t35%2BXExMQuz1qZybJ7sD4PV58bPXq03G63hgwZouPHj/vNNTc3KzExUZI0dOjQLo1qbm7W2LFjlZCQoOjoaDU3N2vUqFGSpM7OTrW2tioxMVFer1etra3yer0KDw/37RsTE6O4uDgNHTpUx44d63btQOzcuVNFRUVdxjPytwV8jIvRoEGxfk%2BthqK4uFirS7ik0X9r0X9rhWr/Ozo6rC7hgnV3Xs7Pz/e7Z9tslpwx//jHP%2Bqee%2B7RK6%2B84ruhvLa2VgkJCZowYYK2b98uj8fjuyJVWVmpCRM%2BexVAamqqDh8%2B7DuWy%2BVSbW2tli5dqrCwMI0fP16VlZW%2BG%2BGrqqo0YMAAJSUlyTAMRUZG6siRI0pPT5ckHTp0SCkpKb5jl5SUdLt2IObOnatp06Z1GV%2B/98Ng23RROXPGpVC%2BghUXF6vTp13q7Az938ZCDf23Fv23Vuj3PxRr9tfdeTmYiyfnw5KAlZaWptjYWK1evVp5eXk6ceKECgsLdffddyszM1PDhw/XihUrtHjxYu3du1c1NTXatGmTJCknJ0fbt29XSUmJpk6dqqKiIo0cOdIXqObNmyeHw6ExY8bIZrOpoKBAc%2BbM8QW57OxsORwObdiwQY2NjSotLfUde%2BLEiV%2B4diBsNtu5LznuffUCu2atjg5r30/EDJ2dXnV0hPbnEMrov7Xov7VCt/%2BG1QVcsG7Py73MkksSAwcO1JNPPqmWlhZ9%2B9vf1gMPPKBbb71V3/3udxUeHq7HH39cTqdTOTk5ev7557V161YNGzZMkjRixAht2bJFFRUVmj17ts6cOaOtW7f6jj19%2BnQtWrRIDodDCxculN1u1/Lly33zK1euVEpKinJzc7V27VotW7ZMWVlZkqTw8HAVFxd3uzYAAEAgwgzDCP14GgLmbXk1ZN9H5OphA/XYramSwqwu5bxERoYrIWGgWlo%2BCdHfIEMb/bcW/bdW6Pff0LJfHA3p89fPl0y2ZO3QvKkGAADgIkbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADCZ5QFr0aJFWrlype9xfX29FixYoLS0NM2YMUP79u3z237//v2aOXOm7Ha75s%2Bfr5MnT/rNP/XUU5oyZYoyMjK0evVqud1u35zH49GqVauUmZmpyZMnq7S01G/fntYGAAAIhKUB69e//rVeeeUVv7G8vDzZbDZVVFRo1qxZys/PV0NDgyTp1KlTysvLU05OjioqKpSQkKC8vDzfvnv27FFxcbHWrl2rp59%2BWkePHlVhYaFvfvPmzaqtrVVZWZkcDoeKior00ksvBbQ2AABAoCwLWB999JEKCwt1zTXX%2BMYOHDigkydPas2aNbrqqqu0aNEi2e12lZeXS5J27dql8ePHa/78%2BRo9erQ2btyo999/XwcPHpQklZWVKTc3VzfccINSUlJUUFCg8vJyud1uuVwulZeX6/7771dSUpKysrK0cOFC7dixI6C1AQAAAmVZwNq8ebOys7M1evRo31h1dbWSk5MVHR3tG8vIyNCRI0d885mZmb65mJgYjRs3TlVVVfJ6vaqpqdGECRN883a7Xe3t7aqrq1NdXZ06Oztlt9v9jl1dXR3Q2gAAAIGyJGAdOHBAlZWVfk/vSZLT6ZTNZvMbGzx4sBobGyVJTU1NXeaHDBmixsZGnT59Wm63228%2BIiJC8fHxamhokNPpVHx8vCIjI/2O7Xa71dLS0uPaAAAAgYrseRNzeTwePfTQQ3I4HIqKivKbc7lcXcaioqLk8XgkSW1tbd3Ot7W1%2BR6fa97r9Z5z7vOaelobAAAgUH0esLZs2aKUlBT9y7/8S5e56OhoffTRR35jHo9HMTExvvmzA4/H41FcXJxfWDp7PjY2Vh0dHeeck6TY2Nge1w5UU1OTnE5nUPuEgsjIMF0ELzo9LxER4X4f0bfov7Xov7VCv/9eqwu4YN2dlxMTE7s8c2WmPg9YL774oj744AOlpaVJktrb2yV99grA//iP/9CxY8f8tm9ublZiYqIkaejQoV2a1NzcrLFjxyohIUHR0dFqbm7WqFGjJEmdnZ1qbW1VYmKivF6vWltb5fV6FR4e7ts3JiZGcXFxGjp06BeuHaidO3eqqKioy3hG/ragjnOxGTQo1u/p1VAUFxdrdQmXNPpvLfpvrVDtf0dHh9UlXLDuzsv5%2BflasmRJr63b52fMHTt2%2BP0P%2B/xtFO699169//77euKJJ%2BTxeHxXpCorK303rqempurw4cO%2BfV0ul2pra7V06VKFhYVp/Pjxqqys9N0IX1VVpQEDBigpKUmGYSgyMlJHjhxRenq6JOnQoUNKSUnxHbukpKTbtQM1d%2B5cTZs2rcv4%2Br0fBnWci82ZMy6F8hWsuLhYnT7tUmdn6P82Fmrov7Xov7VCv/%2BhWLO/7s7LwV5ACVafB6zhw4f7PR44cKAkaeTIkRoxYoSGDx%2BuFStWaPHixdq7d69qamq0adMmSVJOTo62b9%2BukpISTZ06VUVFRRo5cqQvUM2bN08Oh0NjxoyRzWZTQUGB5syZ43tlYHZ2thwOhzZs2KDGxkaVlpb6jj1x4sQvXDtQNpvt3Jcc974a1HEuNh0dhkL9G62z06uOjtD%2BHEIZ/bcW/bdW6PbfsLqAC9btebmXXVSXJMLDw1VcXCyn06mcnBw9//zz2rp1q4YNGyZJGjFihLZs2aKKigrNnj1bZ86c0datW337T58%2BXYsWLZLD4dDChQtlt9u1fPly3/zKlSuVkpKi3NxcrV27VsuWLVNWVlZAawMAAAQqzDCM0I%2BnIWDellf1TsMnVpdxXq4eNlCP3ZoqKczqUs5LZGS4EhIGqqXlkxD9DTK00X9r0X9rhX7/DS37xdGQPn/9fMlkS9a%2BqK5gAQAA9AcELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAEwWVMCaPXu2fvGLX%2BjMmTO9VQ8AAEDICypgXXvttfrpT3%2Bq66%2B/Xt///vf1xz/%2BUYZh9FZtAAAAISmogHXPPffod7/7nYqLixUREaElS5boX//1X/Xoo4/qvffe660aAQAAQkpksDuEhYVp0qRJmjRpklwul8rKylRcXKwnnnhC6enpys3N1Y033tgbtQIAAISEoAOWJDU1Nem5557Tc889p3feeUfp6em65ZZb1NDQoPvvv18HDx7U6tWrza4VAAAgJAQVsHbv3q3du3fr9ddf1%2BWXX66bb75ZP/nJT3TllVf6thk%2BfLjWr19PwAIAAJesoALW6tWrNXXqVG3dulVTpkxReHjXW7iuuuoq3XHHHaYVCAAAEGqCClivvPKKEhIS1Nra6gtX1dXVSk5OVkREhCQpPT1d6enp5lcKAAAQIoJ6FeHHH3%2Bsr3/96yopKfGNLVq0SNnZ2Tp16pTpxQEAAISioALWhg0b9JWvfEULFizwjb344osaPny4Nm7caHpxAAAAoSiogHXo0CGtWLFCiYmJvrHLL79cP/jBD/Taa6%2BZXhwAAEAoCipgRUZG6vTp013GXS4X7%2BgOAADw/wsqYE2ZMkXr1q3TiRMnfGMnT57Uxo0bNXnyZNOLAwAACEVBvYrwvvvu04IFC3TTTTcpLi5OknT69GklJydr5cqVvVIgAABAqAkqYA0ePFi//OUvtX//fr377ruKjIzUmDFjdN111yksLKy3agQAAAgpQf%2BpnIiICE2ePJmnBAEAALoRVMByOp368Y9/rMOHD6u9vb3Lje2//e1vTS0OAAAgFAUVsB544AG9%2Beab%2BuY3v6lBgwb1Vk0AAAAhLaiA9dprr2nbtm2aMGFCb9UDAAAQ8oJ6m4bLLrtMgwcP7q1aAAAA%2BoWgAlZ2dra2bdumzs7O3qoHAAAg5AX1FGFra6teeOEF/f73v9fIkSMVFRXlN//MM8%2BYWhwAAEAoCvptGmbMmNEbdQAAAPQbQQWsjRs39lYdAAAA/UZQ92BJUlNTk4qKinTPPffogw8%2B0P/93//pz3/%2Bc2/UBgAAEJKCClh//etfNXPmTP3yl7/Unj179Omnn%2BrFF19UTk6Ojh492ls1AgAAhJSgAtamTZuUlZWll19%2BWQMGDJAkPfLII5o2bZoefvjhoBY%2BceKE7rrrLqWlpWnatGl68sknfXP19fVasGCB0tLSNGPGDO3bt89v3/3792vmzJmy2%2B2aP3%2B%2BTp486Tf/1FNPacqUKcrIyNDq1avldrt9cx6PR6tWrVJmZqYmT56s0tJSv317WhsAAKAnQQWsw4cPa8GCBX5/2DkyMlKLFy9WbW1twMcxDEOLFi3SkCFDtHv3bj300EN6/PHH9etf/1qStHjxYtlsNlVUVGjWrFnKz89XQ0ODJOnUqVPKy8tTTk6OKioqlJCQoLy8PN%2Bx9%2BzZo%2BLiYq1du1ZPP/20jh49qsLCQt/85s2bVVtbq7KyMjkcDhUVFemll17yzefl5XW7NgAAQCCCClher1der7fL%2BCeffKKIiIiAj9Pc3Kxx48bJ4XDoiiuu0JQpU3TdddepsrJSr732murr67VmzRpdddVVWrRokex2u8rLyyVJu3bt0vjx4zV//nyNHj1aGzdu1Pvvv6%2BDBw9KksrKypSbm6sbbrhBKSkpKigoUHl5udxut1wul8rLy3X//fcrKSlJWVlZWrhwoXbs2CFJOnDggE6ePNnt2gAAAIEIKmBdf/31%2BtnPfuYXslpbW1VYWKhrr7024OMkJibqkUce0WWXXSZJqqys1KFDhzRx4kQdPXpUycnJio6O9m2fkZGhI0eOSJKqq6uVmZnpm4uJidG4ceNUVVUlr9ermpoavz/lY7fb1d7errq6OtXV1amzs1N2u93v2NXV1b5jf9HaAAAAgQgqYK1YsUJvvvmmrr/%2Berndbn3ve9/T1KlTVV9fr/vuu%2B%2B8Cpg2bZruuOMO2e123XjjjXI6nbLZbH7bDB48WI2NjZI%2BexXj2fNDhgxRY2OjTp8%2BLbfb7TcfERGh%2BPh4NTQ0yOl0Kj4%2BXpGRkX7Hdrvdamlp6XFtAACAQAT1PlhDhw7Vr371K73wwgt666235PV6ddtttyk7O1tf%2BtKXzquALVu2qLm5WQ899JA2bNggl8vV5R3io6Ki5PF4JEltbW3dzre1tfken2ve6/Wec0767Ob3ntYGAAAIRNDv5B4bG6vZs2ebVkBycrKkz66OLV%2B%2BXN/%2B9rd1%2BvRpv208Ho9iYmIkSdHR0V0Cj8fjUVxcnF9YOns%2BNjZWHR0d55z7/POKjo7WRx991O3agWhqapLT6Qx4%2B1ARGRmm83jbtItCRES430f0LfpvLfpvrdDvf9f7rkNNd%2BflxMTELs9amSmogPWd73znC%2BcD/VuEH3zwgaqqqpSVleUbGzNmjNrb25WYmKjjx4/7bd/c3KzExERJn11FO7tRzc3NGjt2rBISEhQdHa3m5maNGjVKktTZ2anW1lYlJibK6/WqtbVVXq9X4eHhvn1jYmIUFxenoUOH6tixY92uHYidO3eqqKioy3hG/raAj3ExGjQo1u%2Bp1VAUFxdrdQmXNPpvLfpvrVDtf0dHh9UlXLDuzsv5%2BflasmRJr60b1BlzxIgRfo87Ojr017/%2BVe%2B8845yc3MDPk59fb2WLFmiP/zhD770WFNTo8GDBysjI0NPPvmkPB6P74pUZWWl78b11NRUHT582Hcsl8ul2tpaLV26VGFhYRo/frwqKyt9N8JXVVVpwIABSkpKkmEYioyM1JEjR5Seni5JOnTokFJSUnzHLikp6XbtQMydO1fTpk3rMr5%2B74cBH%2BNidOaMS6F8BSsuLlanT7vU2Rn6v42FGvpvLfpvrdDvfyjW7K%2B783IwF0/Ohyl/i3Dr1q1BvVfU%2BPHjlZKSolWrVmnlypWqr6/Xww8/rO9973vKzMzU8OHDtWLFCi1evFh79%2B5VTU2NNm3aJEnKycnR9u3bVVJSoqlTp6qoqEgjR470Bap58%2BbJ4XBozJgxstlsKigo0Jw5c3yvDMzOzpbD4dCGDRvU2Nio0tJS37EnTpz4hWsHwmaznfuS495XAz7Gxaijw1Cof6N1dnrV0RHan0Moo//Wov/WCt3%2BG1YXcMG6PS/3MlMuSWRnZ%2Bt///d/A180PFzFxcW67LLLdOutt%2BqBBx7Qd77zHd1xxx0KDw/X448/LqfTqZycHD3//PPaunWrhg0bJumzq2hbtmxRRUWFZs%2BerTNnzmjr1q2%2BY0%2BfPl2LFi2Sw%2BHQwoULZbfbtXz5ct/8ypUrlZKSotzcXK1du1bLli3zPVX5eV3drQ0AABCIMMMwLjiePv/881q3bp1ef/11M2rql%2BZteVXvNHxidRnn5ephA/XYramSwnrc9mIUGRmuhISBamn5JER/gwxt9N9a9N9aod9/Q8t%2BcTSkz18/XzLZkrUv%2BCb3jz/%2BWG%2B//bbmzZtnWlEAAAChLKiA9eUvf9nv7xBK0oABA3THHXdo1qxZphYGAAAQqoIKWMHc7A0AAHCpCipgff4HlQPx938vEAAA4FISVMC68847fU8R/v298WePhYWF6a233jKrRgAAgJASVMD66U9/qnXr1unee%2B/VxIkTFRUVpZqaGq1Zs0a33HKLpk%2Bf3lt1AgAAhIyg3gdr48aNevDBB3XTTTcpISFBAwcO1LXXXqs1a9bov//7vzVixAjfPwAAgEtVUAH4%2BGHXAAAZlklEQVSrqanpnOHpS1/6klpaWkwrCgAAIJQFFbDsdrseeeQRffzxx76x1tZWFRYW6rrrrjO9OAAAgFAU1D1Y999/v77zne9oypQpuvLKK2UYhv7yl78oMTFRzzzzTG/VCAAAEFKCClijR4/Wiy%2B%2BqBdeeEHHjx%2BXJN1%2B%2B%2B365je/qdjY2F4pEAAAINQEFbAk6R/%2B4R80e/Zs1dfXa%2BTIkZI%2Bezd3AAAAfCaoe7AMw9DDDz%2BszMxMzZgxQw0NDbrvvvu0evVqtbe391aNAAAAISWogFVWVqbdu3fL4XAoKipKkpSVlaWXX35ZRUVFvVIgAABAqAkqYO3cuVMPPvigvvWtb/nevX369Olat26dnn/%2B%2BV4pEAAAINQEFbDq6%2Bs1duzYLuNJSUlyOp2mFQUAABDKggpYI0aMUE1NTZfxV155xXfDOwAAwKUuqFcR3nXXXSooKJDT6ZRhGDpw4IB27typsrIyrVixordqBAAACClBBaycnBx1dHTo8ccfV1tbmx588EFdfvnl%2Bs///E/ddtttvVUjAABASAkqYL3wwgv6%2Bte/rrlz5%2BrDDz%2BUYRgaPHhwb9UGAAAQkoK6B2vNmjW%2Bm9kvv/xywhUAAMA5BBWwrrzySr3zzju9VQsAAEC/ENRThElJSVq%2BfLm2bdumK6%2B8UtHR0X7zGzduNLU4AACAUBRUwHrvvfeUkZEhSbzvFQAAQDd6DFg//OEPlZ%2Bfr8suu0xlZWV9URMAAEBI6/EerNLSUrlcLr%2BxRYsWqampqdeKAgAACGU9BizDMLqMHTx4UG63u1cKAgAACHVBvYoQAAAAPSNgAQAAmCyggBUWFtbbdQAAAPQbAb1Nw7p16/ze86q9vV2FhYUaOHCg33a8DxYAAEAAASszM7PLe16lpaWppaVFLS0tvVYYAABAqOoxYPHeVwAAAMHhJncAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGSWBazGxkYtXbpU//zP/6wbbrhBmzZtksfjkSTV19drwYIFSktL04wZM7Rv3z6/fffv36%2BZM2fKbrdr/vz5OnnypN/8U089pSlTpigjI0OrV6%2BW2%2B32zXk8Hq1atUqZmZmaPHmySktL/fbtaW0AAICeWBawli5dKrfbrZ///Od65JFH9Lvf/U6PPfaYJGnx4sWy2WyqqKjQrFmzlJ%2Bfr4aGBknSqVOnlJeXp5ycHFVUVCghIUF5eXm%2B4%2B7Zs0fFxcVau3atnn76aR09elSFhYW%2B%2Bc2bN6u2tlZlZWVyOBwqKirSSy%2B95JvPy8vrdm0AAIBAWBKw/vznP6u6ulobN27U6NGjlZGRoaVLl%2BqFF17Qa6%2B9pvr6eq1Zs0ZXXXWVFi1aJLvdrvLycknSrl27NH78eM2fP1%2BjR4/Wxo0b9f777%2BvgwYOSPvvTPrm5ubrhhhuUkpKigoIClZeXy%2B12y%2BVyqby8XPfff7%2BSkpKUlZWlhQsXaseOHZKkAwcO6OTJk92uDQAAEAhLAlZiYqK2bdumyy%2B/3G/8zJkzOnr0qJKTkxUdHe0bz8jI0JEjRyRJ1dXVyszM9M3FxMRo3LhxqqqqktfrVU1NjSZMmOCbt9vtam9vV11dnerq6tTZ2Sm73e537Orqat%2Bxv2htAACAQPT4x557w6BBgzRp0iTfY8MwtGPHDl133XVyOp2y2Wx%2B2w8ePFiNjY2SpKampi7zQ4YMUWNjo06fPi232%2B03HxERofj4eDU0NCgsLEzx8fGKjIz0O7bb7VZLS0uPawMAAATiongV4Q9/%2BEO99dZb%2Bq//%2Bi%2B5XC5FRUX5zUdFRflugG9ra%2Bt2vq2tzff4XPPdHVvSF85/vjYAAEAgLLmC9fcKCwtVVlamH//4xxozZoyio6P10Ucf%2BW3j8XgUExMjSYqOju4SeDwej%2BLi4vzC0tnzsbGx6ujoOOecJMXGxva4diCamprkdDoD3j5UREaG6SLJ40GLiAj3%2B4i%2BRf%2BtRf%2BtFfr991pdwAXr7rycmJjY5VkrM1kasNauXaudO3eqsLBQWVlZkqShQ4fq2LFjfts1NzcrMTHRN392o5qbmzV27FglJCQoOjpazc3NGjVqlCSps7NTra2tSkxMlNfrVWtrq7xer8LDw337xsTEKC4urse1A7Fz504VFRV1Gc/I3xbwMS5GgwbF%2Bj21Gori4mKtLuGSRv%2BtRf%2BtFar97%2BjosLqEC9bdeTk/P19LlizptXUtO2MWFRVp586devTRR/W1r33NN56amqqSkhJ5PB7fFanKykrfjeupqak6fPiwb3uXy6Xa2lotXbpUYWFhGj9%2BvCorK303wldVVWnAgAFKSkqSYRiKjIzUkSNHlJ6eLkk6dOiQUlJSAlo7EHPnztW0adO6jK/f%2B2Ew7bnonDnjUihfwYqLi9Xp0y51dob%2Bb2Ohhv5bi/5bK/T7H4o1%2B%2BvuvBzMxZPzYUnAOn78uB5//HH9%2B7//u9LS0tTc3OybmzhxooYPH64VK1Zo8eLF2rt3r2pqarRp0yZJUk5OjrZv366SkhJNnTpVRUVFGjlypC9QzZs3Tw6HQ2PGjJHNZlNBQYHmzJnje2Vgdna2HA6HNmzYoMbGRpWWlvqO3dPagbDZbOe%2B5Lj31fNt10Who8NQqH%2BjdXZ61dER2p9DKKP/1qL/1grd/htWF3DBuj0v9zJLAtZvf/tbeb1ePf7443r88cclffZKwrCwML311lvaunWrVq9erZycHF1xxRXaunWrhg0bJkkaMWKEtmzZovXr16u4uFjp6enaunWr79jTp0/X%2B%2B%2B/L4fDofb2dt10001avny5b37lypUqKChQbm6uBg0apGXLlvmengwPD1dxcbFWrVp1zrUBAAACEWYYRujH0xAwb8ureqfhE6vLOC9XDxuox25NlRRmdSnnJTIyXAkJA9XS8kmI/gYZ2ui/tei/tUK//4aW/eJoSJ%2B/fr5ksiVrh%2BZNNQAAABcxAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAySwPWB6PRzNnztTBgwd9Y/X19VqwYIHS0tI0Y8YM7du3z2%2Bf/fv3a%2BbMmbLb7Zo/f75OnjzpN//UU09pypQpysjI0OrVq%2BV2u/3WW7VqlTIzMzV58mSVlpb67dvT2gAAAD2xNGB5PB59//vf17Fjx/zG8/LyZLPZVFFRoVmzZik/P18NDQ2SpFOnTikvL085OTmqqKhQQkKC8vLyfPvu2bNHxcXFWrt2rZ5%2B%2BmkdPXpUhYWFvvnNmzertrZWZWVlcjgcKioq0ksvvRTQ2gAAAIGwLGAdP35cc%2BbMUX19vd/4gQMHdPLkSa1Zs0ZXXXWVFi1aJLvdrvLycknSrl27NH78eM2fP1%2BjR4/Wxo0b9f777/uugJWVlSk3N1c33HCDUlJSVFBQoPLycrndbrlcLpWXl%2Bv%2B%2B%2B9XUlKSsrKytHDhQu3YsSOgtQEAAAJhWcB64403dN1112nnzp0yDMM3Xl1dreTkZEVHR/vGMjIydOTIEd98Zmamby4mJkbjxo1TVVWVvF6vampqNGHCBN%2B83W5Xe3u76urqVFdXp87OTtntdr9jV1dXB7Q2AABAICKtWvi2224757jT6ZTNZvMbGzx4sBobGyVJTU1NXeaHDBmixsZGnT59Wm63228%2BIiJC8fHxamhoUFhYmOLj4xUZGel3bLfbrZaWlh7XBgAACIRlAas7LpdLUVFRfmNRUVHyeDySpLa2tm7n29rafI/PNe/1es85J312P1hPawMAAATiogtY0dHR%2Buijj/zGPB6PYmJifPNnBx6Px6O4uDi/sHT2fGxsrDo6Os45J0mxsbE9rh2IpqYmOZ3OgLcPFZGRYboIXnR6XiIiwv0%2Bom/Rf2vRf2uFfv%2B9Vhdwwbo7LycmJnZ51spMF13AGjp0aJdXFTY3NysxMdE3f3ajmpubNXbsWCUkJCg6OlrNzc0aNWqUJKmzs1Otra1KTEyU1%2BtVa2urvF6vwsPDffvGxMQoLi6ux7UDsXPnThUVFXUZz8jfFvAxLkaDBsX6PbUaiuLiYq0u4ZJG/61F/60Vqv3v6OiwuoQL1t15OT8/X0uWLOm1dS%2B6M2ZqaqpKSkrk8Xh8V6QqKyt9N66npqbq8OHDvu1dLpdqa2u1dOlShYWFafz48aqsrPTdCF9VVaUBAwYoKSlJhmEoMjJSR44cUXp6uiTp0KFDSklJCWjtQMydO1fTpk3rMr5%2B74fn0Y2Lx5kzLoXyFay4uFidPu1SZ2fo/zYWaui/tei/tUK//6FYs7/uzsvBXDw5HxddwJo4caKGDx%2BuFStWaPHixdq7d69qamq0adMmSVJOTo62b9%2BukpISTZ06VUVFRRo5cqQvUM2bN08Oh0NjxoyRzWZTQUGB5syZ43tlYHZ2thwOhzZs2KDGxkaVlpb6jt3T2oGw2WznvuS499UL7Iy1OjoMhfo3WmenVx0dof05hDL6by36b63Q7b/R8yYXuW7Py73sorgkERYW5vvv8PBwFRcXy%2Bl0KicnR88//7y2bt2qYcOGSZJGjBihLVu2qKKiQrNnz9aZM2e0detW3/7Tp0/XokWL5HA4tHDhQtntdi1fvtw3v3LlSqWkpCg3N1dr167VsmXLlJWVFdDaAAAAgQgz/v5NqNBr5m15Ve80fGJ1Gefl6mED9ditqZLCetz2YhQZGa6EhIFqafkkRH%2BDDG3031r031qh339Dy35xNKTPXz9fMtmStS%2BKK1gAAAD9CQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkB6xw8Ho9WrVqlzMxMTZ48WaWlpVaXBAAAQkik1QVcjDZv3qza2lqVlZWpvr5e9913n0aMGKEbb7zR6tIAAEAI4ArWWVwul8rLy3X//fcrKSlJWVlZWrhwoXbs2GF1aQAAIEQQsM5SV1enzs5O2e1231hGRoaqq6strAoAAIQSAtZZnE6n4uPjFRn5/549HTx4sNxut1paWiysDAAAhAoC1llcLpeioqL8xj5/7PF4rCgJAACEGG5yP0t0dHSXIPX549jY2B73b2pqktPp7DJ%2B5eCe971YXTk4VpEh/JUSHi51dHQoPFwh/XmEKvpvLfpvrf7Q/1A/f3V3Xk5MTJTNZuu1tUP0f3fvGTp0qFpbW%2BX1ehUe/tkFvubmZsXExCguLq7H/Xfu3KmioqIu45mZmfrxI4/06v9MnFtTU5OeeWa75s6dS/8tQP%2BtRf%2Bt1R/6v2HeBKtLOG9NTU36/ve/r4MHD3aZy8/P15IlS3ptbQLWWcaOHavIyEgdOXJE6enpkqRDhw4pJSUloP3nzp2radOm%2BY0dP35c9957r5xOZ8h%2Bg4Uyp9OpoqIiTZs2jf5bgP5bi/5bi/5by%2Bl06uDBgyosLNTo0aP95hITE3t1bQLWWWJiYpSdnS2Hw6ENGzaosbFRpaWl2rRpU0D722w2vokAALiIjB49WsnJyX26JgHrHFauXKmCggLl5uZq0KBBWrZsmbKysqwuCwAAhAgC1jnExMRo48aN2rhxo9WlAACAEMTbNAAAAJgs4qGHHnrI6iIuBQMHDtTEiRM1cOBAq0u5JNF/a9F/a9F/a9F/a1nV/zDDMIw%2BXREAAKCf4ylCAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAcskHo9Hq1atUmZmpiZPnqzS0tJut62trdWcOXNkt9s1e/Zs/elPf%2BrDSvunYPr/%2B9//XjfffLPS0tKUnZ2tvXv39mGl/VMw/f9cfX290tLSdPDgwT6osH8Lpv9vv/225s2bp9TUVM2aNUuvv/56H1baPwXT/9/85jeaPn260tLSdPvtt6u2trYPK%2B3fPB6PZs6c%2BYU/U/r0/GvAFGvWrDGys7ONt956y/jNb35jpKenG3v27Omy3aeffmpMmjTJ%2BOEPf2gcP37cWLdunTFp0iTD5XJZUHX/EWj/33rrLSMlJcXYsWOHceLECWPHjh1GcnKyUVdXZ0HV/Ueg/f97d911l5GUlGS88cYbfVRl/xVo/8%2BcOWNMmjTJePDBB40TJ04YP/nJT4wJEyYYH3zwgQVV9x%2BB9v/dd981rrnmGmP37t3GiRMnjDVr1hiTJk0y2traLKi6f3G73UZeXt4X/kzp6/MvAcsEn376qXHNNdcYBw8e9I0VFxcbd955Z5dtn332WSMrK8tv7MYbbzR%2B%2Bctf9nqd/VUw/X/44YeNu%2B%2B%2B22/su9/9rvHoo4/2ep39VTD9/9zu3buN2267jYBlgmD6//TTTxs33nij39i3v/1t4w9/%2BEOv19lfBdP/0tJSIycnx/f4448/Nr761a8ab775Zp/U2l8dO3bMyM7ONrKzs7/wZ0pfn395itAEdXV16uzslN1u941lZGSourq6y7bV1dXKyMjwG0tPT1dVVVWv19lfBdP/W265Rffcc0%2BX8Y8//rhXa%2BzPgum/JLW0tOhHP/qR1q5dK4O/1HXBgun/wYMHNW3aNL%2BxZ599VlOmTOn1OvurYPofHx%2BvY8eO6fDhwzIMQxUVFRo0aJCuuOKKviy533njjTd03XXXaefOnV/4M6Wvz7%2BRvXLUS4zT6VR8fLwiI/9fOwcPHiy3262WlhYlJCT4xpuamnT11Vf77T948GAdO3asz%2Brtb4Lp/1VXXeW377vvvqvXXntN8%2BbN67N6%2B5tg%2Bi9JmzZt0i233KLRo0f3dan9UjD9P3nypMaPH68HH3xQe/fu1T/%2B4z/qBz/4gdLT060ovV8Ipv/Tp0/X3r17NW/ePEVERCg8PFxPPPGEBg0aZEXp/cZtt90W0HZ9ff7lCpYJXC6XoqKi/MY%2Bf%2BzxePzG29razrnt2dshcMH0/%2B99%2BOGHWrJkiTIyMvRv//ZvvVpjfxZM//fv36%2BqqiotXry4z%2Brr74Lp/6effqpt27bJZrNp27ZtmjBhgu666y41Njb2Wb39TTD9b21tVXNzsxwOh5599lndfPPNWrFihT788MM%2Bq/dS1tfnXwKWCaKjo7v8D/r8cWxsbEDbxsTE9G6R/Vgw/f9cc3OzcnNzFRYWpscee6zXa%2BzPAu2/2%2B2Ww%2BGQw%2BHo8kMO5y%2BYr/%2BIiAiNHTtW%2Bfn5SkpK0vLly3XllVdq9%2B7dfVZvfxNM/x9%2B%2BGF99atf1W233aZx48ZpzZo1io2N1f/8z//0Wb2Xsr4%2B/xKwTDB06FC1trbK6/X6xpqbmxUTE6O4uLgu2zqdTr%2Bx5uZmJSYm9kmt/VEw/ZekxsZG3X777ers7FRZWVmXp7AQnED7X11drfr6ei1ZskRpaWlKS0uTJN1999166KGH%2BrrsfiOYr//ExMQuT5NfeeWVOnXqVJ/U2h8F0/8//elPSkpK8j0OCwtTUlKS/va3v/VZvZeyvj7/ErBMMHbsWEVGRurIkSO%2BsUOHDiklJaXLtqmpqV1uqDt8%2BLDfDZIITjD9d7lcWrhwoQYMGKAdO3ZoyJAhfVlqvxRo/1NTU/XSSy9p9%2B7deu655/Tcc89JktavX6%2BlS5f2ac39STBf/3a7XXV1dX5jf/7znzVixIher7O/Cqb/Nputy/0%2B7733nv7xH/%2Bx1%2BtE359/CVgmiImJUXZ2thwOh2pqavTyyy%2BrtLRUubm5kj5LyG63W5J000036cyZM9qwYYOOHz%2BudevWyeVy6Rvf%2BIaVn0JIC6b/P/3pT1VfX6%2BNGzfK6/WqublZzc3NvIrwAgTa/6ioKI0cOdLvn/TZSefyyy%2B38lMIacF8/d966616%2B%2B23VVRUpBMnTuixxx5TfX29Zs2aZeWnENKC6f/s2bP17LPPavfu3Tpx4oQefvhhnTp1SjfffLOVn0K/Zun5t1fe/OES5HK5jBUrVhhpaWnGlClTjGeeecY399WvftXvfTaqq6uNW265xUhNTTXmzJljvPXWW1aU3K8E2v%2Bvf/3rRlJSUpd/K1assKr0fiGYr/%2B/x/tgmSOY/h8%2BfNi45ZZbjGuuuca45ZZbjEOHDllRcr8STP/Ly8uNb3zjG0Z6erpx%2B%2B238/PfZGf/TLHy/BtmGLwRDQAAgJl4ihAAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBk/x%2BRQHqoT2xE%2BwAAAABJRU5ErkJggg%3D%3D">
             </div>
      </div>
    </div><div class="row variablerow">
        <div class="col-md-3 namecol">
            <p class="h4">Clicks<br/><small>Numeric</small></p>
        </div>

        <div class="col-md-6">
            <div class="row">
                <div class="col-sm-6">
                    <table class="stats ">
                        <tr><th>Distinct count</th>
                        <td>158</td></tr>
                        <tr><th>Unique (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (n)</th>
                        <td>0</td></tr>
                    </table>

                </div>
                <div class="col-sm-6">
                    <table class="stats ">

                        <tr><th>Mean</th>
                        <td>5.0007</td></tr>
                        <tr><th>Minimum</th>
                        <td>1</td></tr>
                        <tr><th>Maximum</th>
                        <td>200</td></tr>
                        <tr class="ignore"><th>Zeros (%)</th>
                        <td>0.0%</td></tr>
                    </table>
                </div>
            </div>
        </div>
        <div class="col-md-3 collapse in" id="minihistogram-347142115">
             <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAABFBJREFUeJzt3D9IO2ccx/HPeaL4h%2BpgErGgIoVMLkUacYmKjiq4xD%2BLHRRBBwdRUBAEFR3E5TIL/hkCIaCDIg4uitpNLGhLWysI6h2JUC1YE/N0KAR%2B%2BOPbwK93l9DPawt55PkKz9vk9KKmlFJwmGmaiEQiCIVC8Hq9Tm9PecbN86K5EQhRvihwewCiXMZAiASFbm2cTqeRTqezWqtpGnRdt3kioo9cC%2BT850cYh79ktTYU%2BBrd3zXYPBHRR64F8p5W%2BOnhz6zWPr%2B%2B2zwN0efxGoRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiASFbg%2BQDU0DUqlU1ut1XYemaTZORP8XmlJKubHxj79b%2BOG3eFZrv62twNmvCTz%2B8de/rvV9VYzvW7%2BBrutfOiIJCgvz4mfrF3MlENM0EYlEEAqF4PV6nd6e8oyb58WVaxDLsmAYBizLcmN7yjNunhdepBMJGAiRgIEQCRgIkcCVQDweD8bHx%2BHxeNzYnvKMm%2BfFtb%2BDEOUDvsUiEjAQIgEDIRIwECIBAyESMBAiAQMhEjh%2BU//%2B/j7C4TCSySS6u7sxNjbm9AiUg9bX1xGLxQAAjY2NmJ%2BfRywWg2EYqKqqAgAEg0FMTEzg5eUFU1NTuL29RWlpKVZXV1FbW2vPYMpBlmWptrY29fT0pFKplBoaGlLHx8dOjkA56OLiQnV1danX11ellFJTU1NqfX1dzczMqMPDww/rFxcXlWEYSimlTk9PVSgUsm02R99inZycoLm5GZWVldB1HT09Pdjb23NyBMpBFRUVmJubQ3FxMQDA7/fj/v4el5eXiEaj6OnpwfT0NF5eXgAAR0dH6O3tBQA0NzcjHo/j4eHBltkcDeTx8RE%2Bny/z2Ofz2faNUf6oq6tDU1MTACAej2Nrawvt7e2oqanBxMQEdnZ24PV6sbCwAODjOfJ4PLadI0evQdRnbvsqKODvCegfd3d3GB0dRV9fHwKBAAKBQOa54eFhdHZ2AgDS6fSHr7XrHDl6On0%2BH0zTzDw2TRPV1dVOjkA56urqCgMDA%2Bjv78fIyAgSiQS2t7czz7%2B/v2f%2BUUR1dfUnH7%2B1LOuTV5T/kqOBtLS04OzsDIlEAslkEru7uwgGg06OQDkokUhgeHgYc3NzGBwcBACUlJQgHA7j%2BvoaALC5uZl5BWltbUU0GgUAnJ%2Bfo6yszLZAHL/d/eDgAIZhIJlMoqOjA5OTk05uTzlobW0NGxsbqK%2Bvh1IKmqYhGAwiEAhgZWUFb29vaGhowPLyMsrLy/H8/IzZ2Vnc3NygqKgIS0tL8Pv9tszGz4MQCXiFTCRgIESCvwEnQzCE%2BxELEQAAAABJRU5ErkJggg%3D%3D">

        </div>
       <div class="col-md-12 text-right">
            <a role="button" data-toggle="collapse" data-target="#descriptives-347142115,#minihistogram-347142115" aria-expanded="false" aria-controls="collapseExample">
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            </a>
        </div>
        <div class="row collapse col-md-12" id="descriptives-347142115">
            <div class="col-sm-4">
                  <p class="h4">Quantile statistics</p>
                  <table class="stats indent">
                        <tr><th>Minimum</th>
                        <td>1</td></tr>
                        <tr><th>5-th percentile</th>
                        <td>1</td></tr>
                        <tr><th>Q1</th>
                        <td>2</td></tr>
                        <tr><th>Median</th>
                        <td>3</td></tr>
                        <tr><th>Q3</th>
                        <td>6</td></tr>
                        <tr><th>95-th percentile</th>
                        <td>14</td></tr>
                        <tr><th>Maximum</th>
                        <td>200</td></tr>
                        <tr><th>Range</th>
                        <td>199</td></tr>
                        <tr><th>Interquartile range</th>
                        <td>4</td></tr>
                  </table>
                  <p class="h4">Descriptive statistics</p>
                  <table class="stats indent">
                        <tr><th>Standard deviation</th>
                        <td>5.5292</td></tr>
                        <tr><th>Coef of variation</th>
                        <td>1.1057</td></tr>
                        <tr><th>Kurtosis</th>
                        <td>69.813</td></tr>
                        <tr><th>Mean</th>
                        <td>5.0007</td></tr>
                        <tr><th>MAD</th>
                        <td>3.3011</td></tr>
                        <tr class=""><th>Skewness</th>
                        <td>5.4403</td></tr>
                        <tr><th>Sum</th>
                        <td>5505688</td></tr>
                        <tr><th>Variance</th>
                        <td>30.572</td></tr>
                        <tr><th>Memory size</th>
                        <td>8.4 MiB</td></tr>
                 </table>
            </div>
             <div class="col-sm-8 histogram">
                 <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAIABJREFUeJzt3X90VPWd//FXMkMmEYmJMJMiiwXhtAGCGRJCYRVYaLa2FohtVlmtSGhZVknArT9WBDQNvzE9qDViMZaAobWhybZW17NYa7sqYIVAEmxMFaiaUJJM3ARUJjNJ5n7/8OtthxASy00uic/HOZyc%2BXzuvZ933pnJvLhzZxJhGIYhAAAAWCbS7gIAAAAGGgIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFis1wNWMBjU3LlzdeDAAXOsoqJC//qv/6pJkybpG9/4hn7xi1%2BE7bNv3z7NnTtXXq9XWVlZqq2tDZvfsWOHZsyYodTUVK1atUqBQCBsvZUrVyotLU3Tp09XUVFR2L51dXVatGiRJk2apDlz5mjv3r2faW0AAIDu9GrACgaDuuuuu3T06FFzrKmpSUuWLNHUqVP17LPPatmyZVq3bp3%2B93//V5L0l7/8RdnZ2crMzFRZWZni4%2BOVnZ1t7r9nzx5t3bpVa9eu1c6dO1VZWan8/HxzfvPmzaqurlZxcbFyc3NVUFCgF1980ZzPzs6Wx%2BNRWVmZ5s2bp5ycHNXX10uSTp48ed61/16NjY167LHH1NjYeMHHwmdH/%2B1F/%2B1F/%2B1F/%2B1la/%2BNXnL06FEjIyPDyMjIMBITE4033njDMAzDeOaZZ4zrr78%2BbNsHHnjAuOeeewzDMIxHHnnEWLBggTnn9/uNlJQUc//vfOc7RkFBgTl/8OBBIzk52WhtbTXOnDljXH311caBAwfM%2Ba1bt5rH27dvnzFp0iSjtbXVnM/KyjIee%2ByxHq3993rzzTeNL33pS8abb755QcfB34f%2B24v%2B24v%2B24v%2B28vO/vfaGaw33nhD06ZNU0lJiQzDMMdnzJihjRs3dtr%2Bww8/lCRVVVUpLS3NHI%2BOjtb48eN1%2BPBhhUIhHTlyRJMnTzbnvV6v2traVFNTo5qaGnV0dMjr9ZrzqampqqqqMo89YcIEuVyusPmKiopu1wYAAOgpZ28d%2BOabbz7n%2BBVXXKErrrjCvP3BBx/ohRde0PLlyyV9cjrP4/GE7TNs2DA1NDTo9OnTCgQCYfMOh0NxcXGqr69XRESE4uLi5HT%2B9dsaOnSoAoGAmpub5fP5Oh176NChamho6HZtAACAnuq1gNUTgUBAy5Ytk8fj0fz58yVJra2tioqKCtsuKipKwWBQra2t5u1zzYdCoXPOSZ9cD%2Bb3%2B7vct7u1AQAAesq2gHXmzBndcccdev/99/XMM8%2BYL9u5XK5OgSYYDCo2NjYsLJ09HxMTo/b29nPOSVJMTIxcLpdOnTrVaT46OrrbtXuqsbFRPp8vbOzYsWM93h8AAFjrXM/Dbre706tWVrIlYH300UdavHix6urqtHPnTo0cOdKcS0hI6BRQmpqaNG7cOMXHx8vlcqmpqUmjR4%2BWJHV0dKilpUVut1uhUEgtLS0KhUKKjIw0942OjlZsbKwSEhLC3tH46bzb7e527Z4qKSlRQUFBp/Hs7GxNmDChx8eBdSZMmKA//elPdpfxuUX/7UX/7UX/7TVhwgSlpaXp3nvv7TSXk5OjZcuW9drafR6wDMNQTk6OTpw4oV27dmnUqFFh88nJyTp06JB52%2B/3q7q6WsuXL1dERIQmTpyo8vJy82L0w4cPa9CgQUpMTJRhGHI6naqoqFBKSook6eDBg0pKSjKPXVhYqGAwaJ4NKy8vNy%2Ba72rtz/IDmD9/vmbPnt1p3O126/Rpvzo6Qj0%2BFqzhcEQqNjaG/tuE/tuL/tuL/tvL4YjUli1bOp08kWSeXOktfR6wfvGLX%2BiNN97QE088oUsvvVRNTU2SpEGDBumyyy5TZmamtm/frsLCQs2aNUsFBQUaOXKkGahuueUW5ebmauzYsfJ4PMrLy9NNN91kvsSYkZGh3NxcbdiwQQ0NDSoqKtKmTZskSVOmTNHw4cO1YsUKLV26VC%2B//LKOHDlizp9r7SuvvFJTpkzp8ffn8Xi6POXY3Pyx2tt5gNmloyNE/21E/%2B1F/%2B1F/%2B1zvufl3hRh/O1nKPSScePGqbi4WJMnT9bixYs7fXq6JKWlpenpp5%2BWJL366qtav369GhoalJKSojVr1mjEiBHmtoWFhdqxY4fa2tp03XXX6YEHHjDPSLW2tiovL0979uzRkCFDtHjxYi1YsMDct7a2VitXrlRVVZWuvPJKrVq1SlOnTjXnu1v7QhCw7OF0Rio%2BfjD9twn9txf9txf9t9en/bdDnwQsfIIHmD34BWcv%2Bm8v%2Bm8v%2Bm8vOwMWf%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%2BeHAwGtXLlSqWlpWn69OkqKioK2/dC1wYAAOhOrwasYDCou%2B66S0ePHg0bz87OlsfjUVlZmebNm6ecnBzV19dLkk6ePKns7GxlZmaqrKxM8fHxys7ONvfds2ePtm7dqrVr12rnzp2qrKxUfn6%2BOb9582ZVV1eruLhYubm5Kigo0IsvvmjJ2gAAAD3RawHr2LFjuummm1RXVxc2vn//ftXW1mrNmjW66qqrtGTJEnm9XpWWlkqSdu/erYkTJyorK0tjxozRxo0bdeLECfMMWHFxsRYuXKiZM2cqKSlJeXl5Ki0tVSAQkN/vV2lpqVavXq3ExESlp6dr8eLF2rVrlyVrAwAA9ESvBaw33nhD06ZNU0lJiQzDMMerqqo0YcIEuVwucyw1NVUVFRXmfFpamjkXHR2t8ePH6/DhwwqFQjpy5IgmT55sznu9XrW1tammpkY1NTXq6OiQ1%2BsNO3ZVVdUFrw0AANBTzt468M0333zOcZ/PJ4/HEzY2dOhQNTQ0SJIaGxs7zQ8bNkwNDQ06ffq0AoFA2LzD4VBcXJzq6%2BsVERGhuLg4OZ3OsGMHAgE1Nzdf0NoAAAA91WsBqyt%2Bv19RUVFhY1FRUQoGg5Kk1tbWLudbW1vN2%2BeaD4VC55yTPrke7ELWBgAA6Kk%2BD1gul0unTp0KGwsGg4qOjjbnzw40wWBQsbGxYWHp7PmYmBi1t7efc06SYmJiLmjtnmpsbJTP5%2Bs07na7FelwnWOPi0NkZISczoH5qR0OR2TYV/Qt%2Bm8v%2Bm8v%2Bm8vhyPyvM/LZ79qZaU%2BD1gJCQmd3lXY1NQkt9ttzp/diKamJo0bN07x8fFyuVxqamrS6NGjJUkdHR1qaWmR2%2B1WKBRSS0uLQqGQIiMjzX2jo6MVGxt7QWv3VElJiQoKCjqN5%2BTk6Nas7/X4OH3tkkuiFB8/2O4yelVsbIzdJXyu0X970X970X/77Nz5VJfPy8uWLeu1dfs8YCUnJ6uwsFDBYNA8I1VeXm5euJ6cnKxDhw6Z2/v9flVXV2v58uWKiIjQxIkTVV5ebl6MfvjwYQ0aNEiJiYkyDENOp1MVFRVKSUmRJB08eFBJSUkXtPZn%2BQHMnz9fs2fP7jTudrvl97f1%2BDh97cyZoJojPra7jF7hcEQqNjZGp0/71dERsruczx36by/6by/6by%2BHI/K8z8u9qc8D1pQpUzR8%2BHCtWLFCS5cu1csvv6wjR45o06ZNkqTMzExt375dhYWFmjVrlgoKCjRy5EgzUN1yyy3Kzc3V2LFj5fF4lJeXp5tuusl8Z2BGRoZyc3O1YcMGNTQ0qKioyDz237P2lVdeqSlTpvT4%2B/N4PF2ecqw72fx39623hUKG2tsH9oO/oyM04L/Hixn9txf9txf9t8/5npd7U5%2B8KBwREfHXBSMjtXXrVvl8PmVmZuq5557T448/ri984QuSpBEjRuixxx5TWVmZbrzxRn344Yd6/PHHzf2vv/56LVmyRLm5uVq8eLG8Xq/uuecec/7%2B%2B%2B9XUlKSFi5cqLVr1%2BrOO%2B9Uenr63732uU4rAgAAnE%2BE8bcfUoVeVXeyWbcXV6j%2BVKD7jfvQZTFObbvNq8tiLt6L8C%2BE0xmp%2BPjBam7%2BmP9B2oD%2B24v%2B24v%2B2%2BvT/tuBtzUAAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDHbAlZ9fb1uv/12paam6qtf/ap27txpztXV1WnRokWaNGmS5syZo71794btu2/fPs2dO1der1dZWVmqra0Nm9%2BxY4dmzJih1NRUrVq1SoFAwJwLBoNauXKl0tLSNH36dBUVFYXt293aAAAA3bEtYN15550aPHiwfvnLX2rlypV65JFH9NJLL0mSli5dKo/Ho7KyMs2bN085OTmqr6%2BXJJ08eVLZ2dnKzMxUWVmZ4uPjlZ2dbR53z5492rp1q9auXaudO3eqsrJS%2Bfn55vzmzZtVXV2t4uJi5ebmqqCgQC%2B%2B%2BKI5n52d3eXaAAAAPWFLwDp9%2BrQqKyt1xx136Morr9RXv/pVTZ8%2BXa%2B//rpef/111dXVac2aNbrqqqu0ZMkSeb1elZaWSpJ2796tiRMnKisrS2PGjNHGjRt14sQJHThwQJJUXFyshQsXaubMmUpKSlJeXp5KS0sVCATk9/tVWlqq1atXKzExUenp6Vq8eLF27dolSdq/f79qa2u7XBsAAKAnbAlY0dHRiomJUVlZmdrb23X8%2BHEdOnRI48aNU2VlpSZMmCCXy2Vun5qaqoqKCklSVVWV0tLSwo41fvx4HT58WKFQSEeOHNHkyZPNea/Xq7a2NtXU1KimpkYdHR3yer1hx66qqjKPfb61AQAAesKWgBUVFaUHH3xQP//5z5WcnKzrr79eM2bMUGZmpnw%2BnzweT9j2Q4cOVUNDgySpsbGx0/ywYcPU0NCg06dPKxAIhM07HA7FxcWpvr5ePp9PcXFxcjqdYccOBAJqbm7udm0AAICecHa/Se84duyYZs%2Bere9973t6%2B%2B23tXbtWk2bNk1%2Bv19RUVFh20ZFRSkYDEqSWltbu5xvbW01b59rPhQKnXNO%2BuTi9%2B7WBgAA6AlbAtb%2B/ftVWlqqV155RVFRURo/frzq6%2Bv1xBNPaNq0aWppaQnbPhgMKjo6WpLkcrk6BZ5gMKjY2NiwsHT2fExMjNrb2885J0kxMTFyuVw6depUl2v3RGNjo3w%2BX6dxt9utSIfrHHtcHCIjI%2BR0DsxP7XA4IsO%2Bom/Rf3vRf3vRf3s5HJHnfV4%2B%2B1UrK9kSsP74xz9q1KhRYWeLxo0bp23btikhIUHvvPNO2PZNTU1yu92SpISEhE6Nampq0rhx4xQfHy%2BXy6WmpiaNHj1aktTR0aGWlha53W6FQiG1tLQoFAopMjLS3Dc6OlqxsbFKSEjQ0aNHu1y7J0pKSlRQUNBpPCcnR7dmfa/Hx%2Blrl1wSpfj4wXaX0atiY2PsLuFzjf7bi/7bi/7bZ%2BfOp7p8Xl62bFmvrWtLwPJ4PHrvvffU3t5uXg91/Phx/cM//IOSk5O1bds2BYNBM4CVl5ebF64nJyfr0KFD5rH8fr%2Bqq6u1fPlyRUREaOLEiSovLzcvhD98%2BLAGDRqkxMREGYYhp9OpiooKpaSkSJIOHjyopKQk89iFhYVdrt0T8%2BfP1%2BzZszuNu91u%2Bf1tn7VVfebMmaCaIz62u4xe4XBEKjY2RqdP%2B9XREbK7nM8d%2Bm8v%2Bm8v%2Bm8vhyPyvM/LvcmWgDV79mzl5%2Bdr9erVuv3223X8%2BHFt27ZNd999t9LS0jR8%2BHCtWLFCS5cu1csvv6wjR45o06ZNkqTMzExt375dhYWFmjVrlgoKCjRy5EgzUN1yyy3Kzc3V2LFj5fF4lJeXp5tuusl8Z2BGRoZyc3O1YcMGNTQ0qKioyDz2lClTzrt2T3g8ni5POdadbL6QtvWqUMhQe/vAfvB3dIQG/Pd4MaP/9qL/9qL/9jnf83JvijAMw%2BjzVfXJRe4bNmxQVVWVLr/8ct16661asGCBJKm2tlYrV65UVVWVrrzySq1atUpTp04193311Ve1fv16NTQ0KCUlRWvWrNGIESPM%2BcLCQu3YsUNtbW267rrr9MADD5hnpFpbW5WXl6c9e/ZoyJAhWrx4sbluT9a%2BEHUnm3V7cYXqTwW637gPXRbj1LbbvLos5uK9RuxCOJ2Rio8frObmj/kFZwP6by/6by/6b69P%2B28H2wLW5xEByx78grMX/bcX/bcX/beXnQGLtzUAAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxcIC1o033qif//zn%2BvDDD%2B2qBwAAoN8LC1hTp07Vj3/8Y1177bW666679Nprr8kwDLtqAwAA6JfCAtbdd9%2Bt3/3ud9q6dascDoeWLVumf/qnf9LDDz%2BsP//5z3bVCAAA0K84zx6IiIjQNddco2uuuUZ%2Bv1/FxcXaunWrnnzySaWkpGjhwoX62te%2BZketAAAA/UKngCVJjY2N%2BvWvf61f//rXevvtt5WSkqJvfetbqq%2Bv1%2BrVq3XgwAGtWrWqr2sFAADoF8IC1rPPPqtnn31Wf/jDH3T55Zfrhhtu0I9%2B9CONGjXK3Gb48OFav349AQsAAKALYQFr1apVmjVrlh5//HHNmDFDkZGdP8Xhqquu0q233tpnBQIAAPQ3YQHrlVdeUXx8vFpaWsxwVVVVpQkTJsjhcEiSUlJSlJKS0veVAgAA9BNhp6g%2B%2Bugjff3rX1dhYaE5tmTJEmVkZOjkyZN9XhwAAEB/FBawNmzYoC9%2B8YtatGiROfbCCy9o%2BPDh2rhxY58XBwAA0B%2BFBayDBw9qxYoVcrvd5tjll1%2Bu//zP/9Trr7/e58UBAAD0R2EBy%2Bl06vTp05028vv9fKI7AABAD4UFrBkzZmjdunV6//33zbHa2lpt3LhR06dP7/PiAAAA%2BqOwdxHed999WrRoka677jrFxsZKkk6fPq0JEybo/vvvt6VAAACA/iYsYA0dOlS//OUvtW/fPr3zzjtyOp0aO3aspk2bpoiICLtqBAAA6Fc6/akch8Oh6dOn85IgAADA3yksYPl8Pj3yyCM6dOiQ2traOl3Y/tvf/rZPiwMAAOiPwgLWAw88oDfffFPf/OY3NWTIELtqAgAA6NfCAtbrr7%2Bup556SpMnT7arHgAAgH4v7GMaLrnkEg0dOtSuWgAAAAaEsICVkZGhp556Sh0dHXbVAwAA0O%2BFvUTY0tKi559/Xr///e81cuRIRUVFhW389NNP92lxAAAA/VGnj2mYM2eOHXUAAAAMGGEBa%2BPGjXbVAQAAMGBEnj3Q2NiogoIC3X333frggw/0P//zPzp%2B/LgdtQEAAPRLYQHrvffe09y5c/XLX/5Se/bs0ZkzZ/TCCy8oMzNTlZWVdtUIAADQr4QFrE2bNik9PV0vvfSSBg0aJEnasmWLZs%2BerR/%2B8IeWLhwMBpWXl6cpU6bo2muv1cMPP2zO1dXVadGiRZo0aZLmzJmjvXv3hu27b98%2BzZ07V16vV1lZWaqtrQ2b37Fjh2bMmKHU1FStWrVKgUAgbN2VK1cqLS1N06dPV1FRUdi%2B3a0NAADQnbCAdejQIS1atCjsDzs7nU4tXbpU1dXVli68bt067d%2B/X9u3b9cPf/hD7d69W7t375YkLV26VB6PR2VlZZo3b55ycnJUX18vSTp58qSys7OVmZmpsrIyxcfHKzs72zzunj17tHXrVq1du1Y7d%2B5UZWWl8vPzzfnNmzerurpaxcXFys3NVUFBgV588UVzPjs7u8u1AQAAeiIsYIVCIYVCoU4bffzxx3I4HJYteurUKf3Xf/2X1q1bp6SkJE2dOlXf/e53VVlZqddff111dXVas2aNrrrqKi1ZskRer1elpaWSpN27d2vixInKysrSmDFjtHHjRp04cUIHDhyQJBUXF2vhwoWaOXOmkpKSlJeXp9LSUgUCAfn9fpWWlmr16tVKTExUenq6Fi9erF27dkmS9u/fr9ra2i7XBgAA6ImwgHXttddq27ZtYSGrpaVF%2Bfn5mjp1qmWLlpeXa8iQIWF/kuff/u3ftH79elVWVmrChAlyuVzmXGpqqioqKiRJVVVVSktLM%2Beio6M1fvx4HT58WKFQSEeOHAk7rtfrVVtbm2pqalRTU6OOjg55vd6wY1dVVZnHPt/aAAAAPREWsFasWKE333xT1157rQKBgO644w7NmjVLdXV1uu%2B%2B%2ByxbtLa2ViNGjNCvfvUrfeMb31B6erq2bt0qwzDk8/nk8XjCth86dKgaGhokffIux7Pnhw0bpoaGBp0%2BfVqBQCBs3uFwKC4uTvX19fL5fIqLi5PT6Qw7diAQUHNzc7drAwAA9ETY52AlJCToV7/6lZ5//nm99dZbCoVCuvnmm5WRkaFLL73UskXPnDmjd999V7t379amTZvk8/n04IMPKiYmRn6/v9MnyEdFRSkYDEqSWltbu5xvbW01b59rPhQKnXNO%2BuTi9%2B7WBgAA6IlOn%2BQeExOjG2%2B8sVcXdTgc%2Bvjjj7VlyxZ94QtfkCSdOHFCP/vZz3TttdeqpaUlbPtgMKjo6GhJksvl6hR4gsGgYmNjw8LS2fMxMTFqb28/55z0yfftcrl06tSpLtfuicbGRvl8vk7jbrdbkQ7XOfa4OERGRsjp7PSxaAOCwxEZ9hV9i/7bi/7bi/7by%2BGIPO/z8tmvWlkpLGDddttt593Yqr9F6PF45HK5zHAlSaNHj1ZDQ4MSEhL0zjvvhG3f1NQkt9st6ZOzbGc3qqmpSePGjVN8fLxcLpeampo0evRoSVJHR4daWlrkdrsVCoXU0tKiUCikyMhIc9/o6GjFxsYqISFBR48e7XLtnigpKVFBQUGn8ZycHN2a9b0eH6evXXJJlOLjB9tdRq%2BKjY2xu4TPNfpvL/pvL/pvn507n%2BryeXnZsmW9tm5YwBoxYkTYZHt7u9577z29/fbbWrhwoWWLJicnKxAI6L333tMXv/hFSdKxY8c0YsQIJScna9u2bQoGg%2BYZqfLycvPC9eTkZB06dMg8lt/vV3V1tZYvX66IiAhNnDhR5eXl5oXwhw8f1qBBg5SYmCjDMOR0OlVRUaGUlBRJ0sGDB5WUlGQeu7CwsMu1e2L%2B/PmaPXt2p3G32y2/v%2B2ztqrPnDkTVHPEx3aX0SscjkjFxsbo9Gm/Ojo6v0sWvYv%2B24v%2B24v%2B28vhiDzv83Jv6tHfInz88cct/Syo0aNHa%2BbMmVqxYoVyc3Pl8/lUWFio7OxspaWlafjw4VqxYoWWLl2ql19%2BWUeOHNGmTZskSZmZmdq%2BfbsKCws1a9YsFRQUaOTIkWaguuWWW5Sbm6uxY8fK4/EoLy9PN910k/nOwIyMDOXm5mrDhg1qaGhQUVGReewpU6acd%2B2e8Hg8XZ5yrDvZfCFt61WhkKH29oH94O/oCA347/FiRv/tRf/tRf/tc77n5d4UYRiG0d1GdXV1uuGGG3Tw4EHLFv7oo4%2B0bt06/eY3v1FMTIy%2B853v6I477pD0ybsMV65cqaqqKl155ZVatWpV2MdEvPrqq1q/fr0aGhqUkpKiNWvWhJ19Kyws1I4dO9TW1qbrrrtODzzwgHlGqrW1VXl5edqzZ4%2BGDBmixYsXa8GCBea%2B3a19IepONuv24grVnwp0v3EfuizGqW23eXVZzMV7jdiFcDojFR8/WM3NH/MLzgb031703170316f9t8OPQpYzz33nNatW6c//OEPfVHTgEXAsge/4OxF/%2B1F/%2B1F/%2B1lZ8Dq9iL3jz76SH/60590yy239FlRAAAA/VlYwLriiivC/g6hJA0aNEi33nqr5s2b16eFAQAA9FdhAeuzXMwNAACAcwsLWJ/%2BweSe%2BNu/BwgAAIC/CgtYCxYsMF8i/Ntr388ei4iI0FtvvdVXNQIAAPQrYQHrxz/%2BsdatW6d7771XU6ZMUVRUlI4cOaI1a9boW9/6lq6//nq76gQAAOg3wv440saNG/Xggw/quuuuU3x8vAYPHqypU6dqzZo1euaZZzRixAjzHwAAAM4tLGA1NjaeMzxdeumlam6%2BeD%2BFHAAA4GISFrC8Xq%2B2bNmijz6ndaAAAAAZ%2BUlEQVT6yBxraWlRfn6%2Bpk2b1ufFAQAA9Edh12CtXr1at912m2bMmKFRo0bJMAy9%2B%2B67crvdevrpp%2B2qEQAAoF8JC1hjxozRCy%2B8oOeff17Hjh2TJH3nO9/RN7/5TcXExNhSIAAAQH/jPHvgsssu04033qi6ujqNHDlS0ief5g4AAICeCbsGyzAM/fCHP1RaWprmzJmj%2Bvp63XfffVq1apXa2trsqhEAAKBfCQtYxcXFevbZZ5Wbm6uoqChJUnp6ul566SUVFBTYUiAAAEB/ExawSkpK9OCDD%2Brb3/62%2Bent119/vdatW6fnnnvOlgIBAAD6m7CAVVdXp3HjxnXaKDExUT6fr8%2BKAgAA6M/CAtaIESN05MiRThu98sor5gXvAAAAOL%2BwdxF%2B73vfU15ennw%2BnwzD0P79%2B1VSUqLi4mKtWLHCrhoBAAD6lbCAlZmZqfb2dj3xxBNqbW3Vgw8%2BqMsvv1z/8R//oZtvvtmuGgEAAPqVsID1/PPP6%2Btf/7rmz5%2Bv//u//5NhGBo6dKhdtQEAAPRLYddgrVmzxryY/fLLLydcAQAA/B3CAtaoUaP09ttv21ULAADAgBD2EmFiYqLuuecePfXUUxo1apRcLlfYxhs3buzT4gAAAPqjsID15z//WampqZLE514BAAD8nZwPPfSQcnJydMkll6i4uNjuegAAAPq9yKKiIvn9/rDBJUuWqLGx0aaSAAAA%2BrdIwzA6DR44cECBQMCGcgAAAPq/yO43AQAAwGdBwAIAALBYpCRFRETYXQcAAMCA4ZSkdevWhX3mVVtbm/Lz8zV48OCwjfkcLAAAgO4509LSOn3m1aRJk9Tc3Kzm5mabygIAAOi/nHz2FQAAgLW4yB0AAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsJjtAWvJkiW6//77zdt1dXVatGiRJk2apDlz5mjv3r1h2%2B/bt09z586V1%2BtVVlaWamtrw%2BZ37NihGTNmKDU1VatWrVIgEDDngsGgVq5cqbS0NE2fPl1FRUVh%2B3a3NgAAQE/YGrD%2B%2B7//W6%2B88krYWHZ2tjwej8rKyjRv3jzl5OSovr5eknTy5EllZ2crMzNTZWVlio%2BPV3Z2trnvnj17tHXrVq1du1Y7d%2B5UZWWl8vPzzfnNmzerurpaxcXFys3NVUFBgV588cUerQ0AANBTtgWsU6dOKT8/X1dffbU5tn//ftXW1mrNmjW66qqrtGTJEnm9XpWWlkqSdu/erYkTJyorK0tjxozRxo0bdeLECR04cECSVFxcrIULF2rmzJlKSkpSXl6eSktLFQgE5Pf7VVpaqtWrVysxMVHp6elavHixdu3a1aO1AQAAesq2gLV582ZlZGRozJgx5lhVVZUmTJggl8tljqWmpqqiosKcT0tLM%2Beio6M1fvx4HT58WKFQSEeOHNHkyZPNea/Xq7a2NtXU1KimpkYdHR3yer1hx66qqurR2gAAAD1lS8Dav3%2B/ysvLw17ekySfzyePxxM2NnToUDU0NEiSGhsbO80PGzZMDQ0NOn36tAKBQNi8w%2BFQXFyc6uvr5fP5FBcXJ6fTGXbsQCCg5ubmbtcGAADoKWf3m1grGAzqBz/4gXJzcxUVFRU25/f7O41FRUUpGAxKklpbW7ucb21tNW%2Bfaz4UCp1z7tOaulsbAACgp/o8YD322GNKSkrSP/7jP3aac7lcOnXqVNhYMBhUdHS0OX924AkGg4qNjQ0LS2fPx8TEqL29/ZxzkhQTE9Pt2j3V2Ngon8/XadztdivS4TrHHheHyMgIOZ22v6m0VzgckWFf0bfov73ov73ov70cjsjzPi%2Bf/cqVlfo8YL3wwgv64IMPNGnSJElSW1ubpE/eAXj77bfr6NGjYds3NTXJ7XZLkhISEjo1qampSePGjVN8fLxcLpeampo0evRoSVJHR4daWlrkdrsVCoXU0tKiUCikyMhIc9/o6GjFxsYqISHhvGv3VElJiQoKCjqN5%2BTk6Nas732mY/WlSy6JUnz8YLvL6FWxsTF2l/C5Rv/tRf/tRf/ts3PnU10%2BLy9btqzX1u3zgLVr1y61t7ebtz/9GIV7771XJ06c0JNPPqlgMGiekSovLzcvXE9OTtahQ4fMff1%2Bv6qrq7V8%2BXJFRERo4sSJKi8vNy%2BEP3z4sAYNGqTExEQZhiGn06mKigqlpKRIkg4ePKikpCTz2IWFhV2u3VPz58/X7NmzO4273W75/W2f6Vh96cyZoJojPra7jF7hcEQqNjZGp0/71dERsruczx36by/6by/6by%2BHI/K8z8u9qc8D1vDhw8NuDx78yVmTkSNHasSIERo%2BfLhWrFihpUuX6uWXX9aRI0e0adMmSVJmZqa2b9%2BuwsJCzZo1SwUFBRo5cqQZqG655Rbl5uZq7Nix8ng8ysvL00033WS%2BMzAjI0O5ubnasGGDGhoaVFRUZB57ypQp5127pzweT5enHOtONn%2BmY/WlUMhQe/vAfvB3dIQG/Pd4MaP/9qL/9qL/9jnf83JvuqheFI6MjNTWrVvl8/mUmZmp5557To8//ri%2B8IUvSJJGjBihxx57TGVlZbrxxhv14Ycf6vHHHzf3v/7667VkyRLl5uZq8eLF8nq9uueee8z5%2B%2B%2B/X0lJSVq4cKHWrl2rO%2B%2B8U%2Bnp6T1aGwAAoKciDMMw7C7i86LuZLNuL65Q/alA9xv3octinNp2m1eXxVy8F%2BFfCKczUvHxg9Xc/DH/g7QB/bcX/bcX/bfXp/23w0V1BgsAAGAgIGABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWMy2gNXQ0KDly5frK1/5imbOnKlNmzYpGAxKkurq6rRo0SJNmjRJc%2BbM0d69e8P23bdvn%2BbOnSuv16usrCzV1taGze/YsUMzZsxQamqqVq1apUAgYM4Fg0GtXLlSaWlpmj59uoqKisL27W5tAACA7tgWsJYvX65AIKCf/exn2rJli373u9/p0UcflSQtXbpUHo9HZWVlmjdvnnJyclRfXy9JOnnypLKzs5WZmamysjLFx8crOzvbPO6ePXu0detWrV27Vjt37lRlZaXy8/PN%2Bc2bN6u6ulrFxcXKzc1VQUGBXnzxRXM%2BOzu7y7UBAAB6wpaAdfz4cVVVVWnjxo0aM2aMUlNTtXz5cj3//PN6/fXXVVdXpzVr1uiqq67SkiVL5PV6VVpaKknavXu3Jk6cqKysLI0ZM0YbN27UiRMndODAAUlScXGxFi5cqJkzZyopKUl5eXkqLS1VIBCQ3%2B9XaWmpVq9ercTERKWnp2vx4sXatWuXJGn//v2qra3tcm0AAICesCVgud1uPfXUU7r88svDxj/88ENVVlZqwoQJcrlc5nhqaqoqKiokSVVVVUpLSzPnoqOjNX78eB0%2BfFihUEhHjhzR5MmTzXmv16u2tjbV1NSopqZGHR0d8nq9Yceuqqoyj32%2BtQEAAHrCaceiQ4YM0TXXXGPeNgxDu3bt0rRp0%2BTz%2BeTxeMK2Hzp0qBoaGiRJjY2NneaHDRumhoYGnT59WoFAIGze4XAoLi5O9fX1ioiIUFxcnJxOZ9ixA4GAmpubu10bAACgJy6KdxE%2B9NBDeuutt/T9739ffr9fUVFRYfNRUVHmBfCtra1dzre2tpq3zzXf1bElnXf%2B07UBAAB6wpYzWH8rPz9fxcXFeuSRRzR27Fi5XC6dOnUqbJtgMKjo6GhJksvl6hR4gsGgYmNjw8LS2fMxMTFqb28/55wkxcTEdLt2TzQ2Nsrn83Uad7vdinS4zrHHxSEyMkJO50WRty3ncESGfUXfov/2ov/2ov/2cjgiz/u8fParVlayNWCtXbtWJSUlys/PV3p6uiQpISFBR48eDduuqalJbrfbnD%2B7UU1NTRo3bpzi4%2BPlcrnU1NSk0aNHS5I6OjrU0tIit9utUCiklpYWhUIhRUZGmvtGR0crNja227V7oqSkRAUFBZ3Gc3JydGvW93p8nL52ySVRio8fbHcZvSo2NsbuEj7X6L%2B96L%2B96L99du58qsvn5WXLlvXaurYFrIKCApWUlOjhhx/WP//zP5vjycnJKiwsVDAYNM9IlZeXmxeuJycn69ChQ%2Bb2fr9f1dXVWr58uSIiIjRx4kSVl5ebF8IfPnxYgwYNUmJiogzDkNPpVEVFhVJSUiRJBw8eVFJSUo/W7on58%2Bdr9uzZncbdbrf8/rbP0qI%2BdeZMUM0RH9tdRq9wOCIVGxuj06f96ugI2V3O5w79txf9txf9t5fDEXne5%2BXeZEvAOnbsmJ544gn9%2B7//uyZNmqSmpiZzbsqUKRo%2BfLhWrFihpUuX6uWXX9aRI0e0adMmSVJmZqa2b9%2BuwsJCzZo1SwUFBRo5cqQZqG655Rbl5uZq7Nix8ng8ysvL00033WS%2BMzAjI0O5ubnasGGDGhoaVFRUZB67u7V7wuPxdHnKse5k89/Vr74QChlqbx/YD/6OjtCA/x4vZvTfXvTfXvTfPud7Xu5NEYZhGH296JNPPqmHH344bMwwDEVEROitt97S%2B%2B%2B/r1WrVqmqqkpXXnmlVq1apalTp5rbvvrqq1q/fr0aGhqUkpKiNWvWaMSIEeZ8YWGhduzYoba2Nl133XV64IEHzDNSra2tysvL0549ezRkyBAtXrxYCxYsMPetra3VypUru1z7QtSdbNbtxRWqPxXofuM%2BdFmMU9tu8%2BqymIv3GrEL4XRGKj5%2BsJqbP%2BYXnA3ov73ov73ov70%2B7b8dbAlYn1cELHvwC85e9N9e9N9e9N9edgYs3tYAAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDEC1jkEg0GtXLlSaWlpmj59uoqKiuwuqVc5IyPkiJQk4yL9BwBA/%2BK0u4CL0ebNm1VdXa3i4mLV1dXpvvvu04gRI/S1r33N7tJ6xReHxajwlXf17gd%2Bu0sJM2pojL7/z1%2ByuwwAAD4zAtZZ/H6/SktL9ZOf/ESJiYlKTEzU4sWLtWvXrgEbsCTp3Q/8erv%2BY7vLAABgQOAlwrPU1NSoo6NDXq/XHEtNTVVVVZWNVQEAgP6EgHUWn8%2BnuLg4OZ1/Pbk3dOhQBQIBNTc321gZAADoL3iJ8Cx%2Bv19RUVFhY5/eDgaDdpT0ueWIjJA1F7mH1N7eLilk0fH%2BVoTFxwMADAQErLO4XK5OQerT2zExMd3u39jYKJ/P12nc7XYr0uHSVe5LFBtzcbV9ZHyM/G0ddpfRSdqoy1R2qE4NpwN2l9JJQqxL86eMtLuMfiEyUmpvb1dkpOS8uO76nwv0316R//91IoeDF4zs4HBEnvd52ePx9NraPNzOkpCQoJaWFoVCIUX%2B/0dGU1OToqOjFRsb2%2B3%2BJSUlKigo6DSelpamLVu26EeLvmJ5zTi/xsZGlZSUaP78%2Bb36YMK5NTY26umnt9N/m9B/ezU2Nuqxx%2Bi/XRobG3XXXXfpwIEDneZycnK0bNmyXlubgHWWcePGyel0qqKiQikpKZKkgwcPKikpqUf7z58/X7Nnzw4bO3bsmO699175fD4eYDbw%2BXwqKCjQ7Nmz6b8N6L%2B96L%2B96L%2B9fD6fDhw4oPz8fI0ZMyZszu129%2BraBKyzREdHKyMjQ7m5udqwYYMaGhpUVFSkTZs29Wh/j8fDgwgAgIvImDFjNGHChD5dk4B1Dvfff7/y8vK0cOFCDRkyRHfeeafS09PtLgsAAPQTBKxziI6O1saNG7Vx40a7SwEAAP0Qb2sAAACwmOMHP/jBD%2Bwu4vNg8ODBmjJligYPHmx3KZ9L9N9e9N9e9N9e9N9edvU/wjAMqz95EQAA4HONlwgBAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIErF4WDAa1cuVKpaWlafr06SoqKrK7pAHtpZdeUmJiosaNG2d%2BvfPOOyVJdXV1WrRokSZNmqQ5c%2BZo7969Nlc7cASDQc2dO1cHDhwwx7rr9759%2BzR37lx5vV5lZWWptra2r8seMM7V/3Xr1nV6LPz0pz815%2Bn/hWtoaNDy5cv1la98RTNnztSmTZsUDAYlcf/vC%2Bfr/8Vw/ydg9bLNmzerurpaxcXFys3NVUFBgV588UW7yxqwjh49qtmzZ2vv3r3au3evXnvtNa1fv16StHTpUnk8HpWVlWnevHnKyclRfX29zRX3f8FgUHfddZeOHj0aNp6dnd1lv0%2BePKns7GxlZmaqrKxM8fHxys7OtqP8fq%2Br/h8/flz33HOPXnvtNfOx8C//8i%2BS6L9Vli9frkAgoJ/97GfasmWLfve73%2BnRRx%2BVdP7fN/TfGufr/0Vx/zfQa86cOWNcffXVxoEDB8yxrVu3GgsWLLCxqoHtnnvuMbZs2dJpfN%2B%2BfcakSZOM1tZWcywrK8t47LHH%2BrK8Aefo0aNGRkaGkZGRYSQmJhpvvPGGYRjd9/uRRx4Jexz4/X4jJSXF3B8901X/DcMwZsyYYezdu/ec%2Bz366KP0/wIdO3bMSExMND744ANz7PnnnzdmzJhh7N%2B/n/t/Lztf/w3j4rj/cwarF9XU1Kijo0Ner9ccS01NVVVVlY1VDWzHjh3T6NGjO41XVVVpwoQJcrlc5lhqaqoqKir6srwB54033tC0adNUUlIi42/%2B6lZ3/a6qqlJaWpo5Fx0drfHjx%2Bvw4cN9V/wA0FX/P/roIzU0NGjUqFHn3K%2ByspL%2BXyC3262nnnpKl19%2Bedj4hx9%2BqMrKSu7/vexc/TcMQx9%2B%2BOFFc/93Wno0hPH5fIqLi5PT%2Bdc2Dx06VIFAQM3NzYqPj7exuoHpz3/%2Bs1599VU98cQTCoVC%2BvrXv67ly5fL5/PJ4/GEbTt06FA1NDTYVOnAcPPNN59zvLt%2BNzY2dpofNmwYP4/PqKv%2BHz9%2BXBEREXriiSf0yiuvKC4uTosWLdINN9wgif5bYciQIbrmmmvM24ZhaNeuXZo2bRr3/z7QVf//8R//8aK5/xOwepHf71dUVFTY2Ke3P70QD9b5y1/%2BotbWVrlcLj366KOqq6vT%2BvXr1dra2uXPgp9D7%2Biu362trfw8etHx48cVGRmpMWPGaMGCBXrjjTf0wAMP6NJLL1V6ejr97wUPPfSQ3nrrLZWWlqqoqIj7fx976KGHVFNTo9LSUr355psXxf2fgNWLXC5Xpx/Yp7djYmLsKGlAu%2BKKK/SHP/xBsbGxkqTExESFQiHde%2B%2B9%2Bva3v63Tp0%2BHbR8MBhUdHW1HqQOey%2BXSqVOnwsb%2Btt9dPTY%2B/dnhwtxwww2aPXu22c8vfelLevfdd/XMM88oPT2d/lssPz9fxcXFeuSRRzR27Fju/33s7P6PHTv2orj/cw1WL0pISFBLS4tCoZA51tTUpOjoaB5IveTsvo4ZM0aBQEDDhg2Tz%2BcLm2tqapLb7e7L8j43EhISztvv7uZx4c5%2BLFx11VVqbGyURP%2BttHbtWu3cuVP5%2BflKT0%2BXxP2/L52r/9LFcf8nYPWicePGyel0hl1IffDgQSUlJdlY1cD12muv6Stf%2BYoCgYA5Vl1drfj4eE2ePFl//OMfw/7XUl5eHvYGBFgnOTlZ1dXVXfY7OTlZhw4dMuf8fr%2Bqq6v5eVjkRz/6kRYtWhQ29tZbb5lvAKH/1igoKFBJSYkefvhhfeMb3zDHuf/3ja76f9Hc/y19TyI6efDBB405c%2BYYVVVVxm9%2B8xsjNTXV%2BM1vfmN3WQPSRx99ZMycOdO4%2B%2B67jePHjxu///3vjenTpxs/%2BclPjI6ODuOb3/ym8f3vf9945513jG3bthkpKSnGyZMn7S57wPjyl79svs25o6PDmDNnTpf9rqurM5KTk40nn3zSeOedd4w777zTuOGGG%2Bwsv9/72/5XVVUZEyZMMLZv3268//77xk9/%2BlPj6quvNiorKw3DoP9WOHr0qDF%2B/Hjj0UcfNXw%2BX9g/7v%2B973z9v1ju/wSsXub3%2B40VK1YYkyZNMmbMmGE8/fTTdpc0oB09etT47ne/a6SkpBjTp083Hn/8cXPu/fffN2699Vbj6quvNubMmWPs37/fxkoHnrM/h6m7fr/yyivGddddZ3i9XuO73/2uUVdX19clDyhn9/%2B3v/2tMW/ePCM5Odm4/vrrO/3Hjv5fmG3bthmJiYlh/7785S8biYmJhmEYxnvvvcf9vxd11/%2BL4f4fYRh/8%2BEpAAAAuGBcgwUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGCx/weUUoPasf31QgAAAABJRU5ErkJggg%3D%3D">
             </div>
      </div>
    </div><div class="row variablerow">
        <div class="col-md-3 namecol">
            <p class="h4">Day_Of_Month<br/><small>Numeric</small></p>
        </div>

        <div class="col-md-6">
            <div class="row">
                <div class="col-sm-6">
                    <table class="stats ">
                        <tr><th>Distinct count</th>
                        <td>586</td></tr>
                        <tr><th>Unique (%)</th>
                        <td>0.1%</td></tr>
                        <tr class="ignore"><th>Missing (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (n)</th>
                        <td>0</td></tr>
                    </table>

                </div>
                <div class="col-sm-6">
                    <table class="stats ">

                        <tr><th>Mean</th>
                        <td>16.202</td></tr>
                        <tr><th>Minimum</th>
                        <td>1</td></tr>
                        <tr><th>Maximum</th>
                        <td>31</td></tr>
                        <tr class="ignore"><th>Zeros (%)</th>
                        <td>0.0%</td></tr>
                    </table>
                </div>
            </div>
        </div>
        <div class="col-md-3 collapse in" id="minihistogram-1884967603">
             <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAABI1JREFUeJzt3T9IM2ccB/BvPGlNh9a3b3MRS8uLUHApOHQIggQlGDDKkVKaRdDFzSGTitBii4ODQwYDjhl0SNFBBx0UmkEhY6mQiii%2BdBC9%2BKetvDUkd3m6FJfqQ87qc7nk%2B9kCF59f4n3N/X6XO31CCAHFTNNENptFIpGAruuql392QgjYtu3oOZqmwefzvVBFjcXN/cXnRkAajWVZ%2BP6nX/D26q6m7d%2B89uPHb3vQ2tr6wpXR/8Xf0DN5e3WHo/N3bpdBz6zF7QKI6hkDQiTBQywP4BDAPQyIB9i2zSGAS/gOegSHAO5gD0IkwYAQSTAgRBLsQVygtfgcTaWcTrDo%2BTAgLvj0VRt%2BWD%2BoeSoV6mp/4YroMQyIS5xMpT5/7X/haugx7EGIJPgJ8gCnZ67ZIzQuBuQBTs9cs0doXAzII9gjEMAehEiKASGSYECIJJqiB%2BFUip6qKQLCqRQ9VVMEBOBUip6GPQiRBANCJNE0h1jNxOnX6QHe5OExDEgDcvp1%2Bq5P/Pju6y%2BhaVrNazRLoBiQBuV0KOEkUM1015TGf4VUE9415WFs0okk%2BAlCjjXTEIABIcecDgG83LN4r2KqC83Ss7AHIZJgQIgkGBAiibroQYQQuL6treH79wn48IP3ap6K8PoOeqq6CIht25hb%2BxUnxb9r2r7vi49xW7J4fQe9uLoICABcvavA/Ktc07Z/liz8zus7SAH2IEQSDAiRBANCJMGAEEkwIEQSDAiRBANCJMGAEEnUzYnCb77qxB93lZq2/exVG37%2B7bLmn9350fuO/hJw%2B%2Bfd/o2HT9T6hBBC9aKmaSKbzSKRSEDXddXLk8e4ub%2B4cohVLBaxtLSEYrHoxvLkMW7uL%2BxBiCQYECIJBoRIggEhknAlIIFAAJOTkwgEAm4sTx7j5v7iypiXyCt4iEUkwYAQSTAgRBIMCJEEA0IkwYAQSTAgRBLKA7K9vY3h4WFEo1Gk02nVy5MHLC4uIhaLYWRkBJlMBgCQzWbR19eHeDyOeDyOVCqlphihULFYFP39/eLm5kZYliXGx8fF3t6eyhKozuVyOTE6Oiqq1aoolUpiYGBAnJ6eitnZWbGzs6O8HqWfIPv7%2BwiFQmhvb4emaTAMA1tbWypLoDoXDoeRyWTg8/lweXmJarUKv9%2BPg4MDrK2twTAMTE9P4/b2Vkk9SgNycXGBYDB4/zgYDOL8/FxlCeQBmqYhlUohFoshFAohEAigs7MTyWQSGxsb0HUd8/PzSmpRGhDxwNe%2BWlo4J6D/SiaTyOfzODs7w/r6OpaXl9Hd3Q0AmJiYQC6XU1KH0r0zGAzCNM37x6ZpoqOjQ2UJVOeOj49xdHQEAGhra8Pg4CAKhQJWV1fvt7FtW9k/BFUakN7eXuTzeVxfX6NSqWBzcxPhcFhlCVTnTk5OMDc3B8uyUC6Xsbu7i56eHqTTaRweHgIAVlZWEIlElNSj9LY/uq5jamoKY2NjqFQqiEQiyl4oeUM0GkWhUIBhGNA0DUNDQzAMA7quY2ZmBuVyGV1dXVhYWFBSD68HIZJgh0wkwYAQSfwDnkCfsBsq3BgAAAAASUVORK5CYII%3D">

        </div>
       <div class="col-md-12 text-right">
            <a role="button" data-toggle="collapse" data-target="#descriptives-1884967603,#minihistogram-1884967603" aria-expanded="false" aria-controls="collapseExample">
                Toggle details
            </a>
        </div>
        <div class="row collapse col-md-12" id="descriptives-1884967603">
            <div class="col-sm-4">
                  <p class="h4">Quantile statistics</p>
                  <table class="stats indent">
                        <tr><th>Minimum</th>
                        <td>1</td></tr>
                        <tr><th>5-th percentile</th>
                        <td>4</td></tr>
                        <tr><th>Q1</th>
                        <td>11</td></tr>
                        <tr><th>Median</th>
                        <td>16</td></tr>
                        <tr><th>Q3</th>
                        <td>21</td></tr>
                        <tr><th>95-th percentile</th>
                        <td>28</td></tr>
                        <tr><th>Maximum</th>
                        <td>31</td></tr>
                        <tr><th>Range</th>
                        <td>30</td></tr>
                        <tr><th>Interquartile range</th>
                        <td>10</td></tr>
                  </table>
                  <p class="h4">Descriptive statistics</p>
                  <table class="stats indent">
                        <tr><th>Standard deviation</th>
                        <td>7.0265</td></tr>
                        <tr><th>Coef of variation</th>
                        <td>0.43368</td></tr>
                        <tr><th>Kurtosis</th>
                        <td>-0.61709</td></tr>
                        <tr><th>Mean</th>
                        <td>16.202</td></tr>
                        <tr><th>MAD</th>
                        <td>5.7902</td></tr>
                        <tr class=""><th>Skewness</th>
                        <td>-0.0022144</td></tr>
                        <tr><th>Sum</th>
                        <td>17838000</td></tr>
                        <tr><th>Variance</th>
                        <td>49.372</td></tr>
                        <tr><th>Memory size</th>
                        <td>8.4 MiB</td></tr>
                 </table>
            </div>
             <div class="col-sm-8 histogram">
                 <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAIABJREFUeJzt3XtwVGWe//FPLpBEIJsQOoAU/hBYJxCQXAjKamBIRXGRi24UVkcERmRrSYAVYeSmmXALmBkQCWEUJGJw3MyGmtWlHFHHsZTLyJ3gBoYBRAhDbiyRi53uJH1%2Bfzi2Nk1IWk9y0uT9qqKoPE%2Bfc7758oT%2B5PTp0wGGYRgCAACAaQKtLgAAAOBmQ8ACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJNZFrDKy8s1c%2BZM3XXXXRo%2BfLhWrFghp9MpSSotLdWUKVMUHx%2Bv0aNHa%2BfOnR7b7tq1S2PGjFFcXJwmT56ss2fPesy//vrrGjZsmBITE7Vw4UI5HA73nNPp1IIFC5SUlKTk5GTl5%2Bd7bNvYsQEAABpjWcCaOXOmHA6Hfvvb32rVqlX605/%2BpDVr1kiSpk%2BfrujoaG3dulVjx45VRkaGysrKJEnnz59Xenq60tLStHXrVkVGRio9Pd293%2B3btysvL09LlizR5s2bdfjwYeXk5LjnV65cqZKSEhUUFCgzM1O5ubl6//333fPp6ekNHvuHqqio0Nq1a1VRUfGj9nMzoSee6Ic3euKJfnijJ57ohzdLe2JY4OTJk0ZMTIxx4cIF99i2bduMYcOGGbt37zbi4%2BONmpoa99zkyZONtWvXGoZhGC%2B99JIxceJE95zdbjcSEhKMPXv2GIZhGD/72c%2BM3Nxc9/y%2BffuMQYMGGTU1NcbXX39t3HnnncbevXvd83l5ee797dq164bH/qE%2B//xz44477jA%2B//zzH7Wfmwk98UQ/vNETT/TDGz3xRD%2B8WdkTS85g2Ww2bdy4UZ07d/YYv3z5sg4fPqzY2FiFhIS4xxMTE3Xo0CFJUnFxsZKSktxzoaGh6t%2B/vw4ePCiXy6UjR45o8ODB7vm4uDjV1tbq2LFjOnbsmOrr6xUXF%2Bex7%2BLiYve%2Bb3RsAACApgi24qCdOnXSPffc4/7aMAxt2bJFQ4cOVWVlpaKjoz0eHxUVpfLycknfnO67dr5Lly4qLy/XpUuX5HA4POaDgoIUERGhsrIyBQQEKCIiQsHBwR77djgcunjxYqPHBgAAaIpW8S7CF198UUePHtUzzzwju92u9u3be8y3b9/efQF8TU1Ng/M1NTXur68339C%2BJd1w/ttjAwAANIUlZ7C%2BLycnRwUFBXrppZfUt29fhYSE6KuvvvJ4jNPpVGhoqCQpJCTEK/A4nU6Fh4d7hKVr58PCwlRXV3fdOUkKCwtr9NhNUVFRocrKSo%2BxkydPNnl7AABgrus9D9tsNq9XrcxkacBasmSJCgsLlZOTo9TUVElS165ddeLECY/HVVVVyWazueevDTBVVVXq16%2BfIiMjFRISoqqqKt1%2B%2B%2B2SpPr6elVXV8tms8nlcqm6uloul0uBgYHubUNDQxUeHt7osZuisLBQubm5XuPp6emKjY1t8n5udrGxsfrLX/5idRmtBv3wRk880Q9v9MQT/fAWGxurpKQkzZ0712suIyNDM2bMaLZjWxawcnNzVVhYqNWrV%2Bu%2B%2B%2B5zjw8aNEgbNmyQ0%2Bl0n5Hav3%2B/%2B8L1QYMG6cCBA%2B7H2%2B12lZSUaObMmQoICNDAgQO1f/9%2B94XwBw8eVLt27RQTEyPDMBQcHKxDhw4pISFBkrRv3z4NGDCgScduigkTJiglJcVr3Gaz6dIlu%2BrrXb606aYVFBSo8PAwevJ39MMbPfFEP7zRE0/0w1tQUKBWrVrldWJGkk8nT34ISwLWyZMntX79ev3bv/2b4uPjVVVV5Z4bMmSIunfvrnnz5mn69On66KOPdOTIEa1YsUKSlJaWpk2bNmnDhg0aMWKEcnNz1bNnT3egevzxx5WZmam%2BffsqOjpaWVlZGj9%2BvPudgePGjVNmZqaWL1%2Bu8vJy5efnu/fd2LGbIjo6usFTjhcvXlVdHYv%2B%2B%2BrrXfTke%2BiHN3riiX54oyee6IenGz0vN6cAwzCMlj7oq6%2B%2BqtWrV3uMGYahgIAAHT16VGfOnNHChQtVXFys2267TQsXLtTdd9/tfuynn36qZcuWqby8XAkJCVq8eLF69Ojhnt%2BwYYNef/111dbWauTIkXr%2B%2BefdZ6RqamqUlZWl7du3q1OnTpo6daomTpzo3vbs2bNasGBBg8f%2BMQhY3wkODlRkZAd68nf0wxs98UQ/vNETT/TD27c9sYIlAautYtF/h/8IPNEPb/TEE/3wRk880Q9vVgYsy99FCMBftPTvYi7V1dVJcv2AYwc0Qz0A0HQELABNtvqD4zp9wW51GQ3qFRWmZ%2B67w%2BoyAICABaDpTl%2Bw63jZVavLAIBWr1XcyR0AAOBmQsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATBZsdQEA0PYYP2Abl%2Brq6iS5fuD2P1RACx4LuHkQsADAAqs/OK7TF%2BxWl9GgXlFheua%2BO6wuA/BbBCwAsMDpC3YdL7tqdRkAmgnXYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmMzygOV0OjVmzBjt3bvXPbZ06VLFxMSoX79%2B7r/ffPNN9/yuXbs0ZswYxcXFafLkyTp79qzHPl9//XUNGzZMiYmJWrhwoRwOh8fxFixYoKSkJCUnJys/P99j29LSUk2ZMkXx8fEaPXq0du7c2UzfOQAAuFlZGrCcTqdmz56tEydOeIyfOnVKc%2BbM0Y4dO7Rz507t2LFDjzzyiCTp/PnzSk9PV1pamrZu3arIyEilp6e7t92%2Bfbvy8vK0ZMkSbd68WYcPH1ZOTo57fuXKlSopKVFBQYEyMzOVm5ur999/3z2fnp6u6Ohobd26VWPHjlVGRobKysqauRMAAOBmYlnAOnnypMaPH6/S0tLrzvXv319RUVHuPyEhIZKk//qv/9LAgQM1efJk9enTR9nZ2Tp37pz7DFhBQYEmTZqk4cOHa8CAAcrKylJRUZEcDofsdruKioq0aNEixcTEKDU1VVOnTtWWLVskSbt379bZs2e1ePFi9e7dW9OmTVNcXJyKioparjEAAMDvWRaw9uzZo6FDh6qwsFCGYbjHr1y5ovLycvXq1eu62x0%2BfFhJSUnur0NDQ9W/f38dPHhQLpdLR44c0eDBg93zcXFxqq2t1bFjx3Ts2DHV19crLi7OPZ%2BYmKji4mJJUnFxsWJjY91h7tv5Q4cOmfVtAwCANiDYqgM/9thj1x0/deqUAgICtH79en3yySeKiIjQlClT9NBDD0mSKioqFB0d7bFNly5dVF5erkuXLsnhcHjMBwUFKSIiQmVlZQoICFBERISCg7/7tqOiouRwOHTx4kVVVlZ67TsqKkrl5eVmfdsAAKANsCxgNeTUqVMKDAxUnz59NHHiRO3Zs0fPP/%2B8OnbsqNTUVNXU1Kh9%2B/Ye27Rv315Op1M1NTXur68373K5rjsnfXM9mN1ub3BbAACApmp1Aeuhhx5SSkqKwsPDJUl33HGHTp8%2BrbfeekupqakKCQnxCjxOp1Ph4eEeYena%2BbCwMNXV1V13TpLCwsIUEhKir776yms%2BNDS0yfVXVFSosrLSa9xmsyk0tFOT93OzCwoK9Pi7rfOPfrisLqBJgoMD1AreIN0IemkG//i5aTn0w1tQUOANn5evfdXKTK0uYElyh6tv9e7dW5999pkkqWvXrl6NqqqqUr9%2B/RQZGamQkBBVVVXp9ttvlyTV19erurpaNptNLpdL1dXVcrlcCgwMdG8bGhqq8PBwde3a1esdjVVVVbLZbE2uvbCwULm5uV7jGRkZmjFjRpP301aEh4dZXUKr0pr7UVdXZ3UJTdKpU5jHZQCtEb00V2v%2BubEC/fC0efNGS56XW91Pzssvv6yDBw963J/q6NGj7sA0aNAgHThwwD1nt9tVUlKimTNnKiAgQAMHDtT%2B/fvdF8IfPHhQ7dq1U0xMjAzDUHBwsA4dOqSEhARJ0r59%2BzRgwAD3vjds2CCn0%2Bk%2BG7Z//36Pi%2BYbM2HCBKWkpHiN22w2XbpkV329f/zm2tyCggIVHh5GT/7OP/rRWuv6TlBggC5f/lpSgNWlNMJo/CGtwOXLdrX2M1it/%2Bem5dAPb0FBgTd8Xm5OrS5gjRgxQq%2B%2B%2Bqry8/OVmpqqTz/9VO%2B8844KCgokSWlpadq0aZM2bNigESNGKDc3Vz179nQHqscff1yZmZnq27evoqOjlZWVpfHjx7vfGThu3DhlZmZq%2BfLlKi8vV35%2BvlasWCFJGjJkiLp376558%2BZp%2BvTp%2Buijj3TkyBH3fFNER0c3eMrx4sWrqqtj0X9ffb2LnnxP6%2B5H6w8FPSJDlfOH4zp9wW51KTd0d%2B8Iq0tokro6Q/4QrFv3z03Lox%2BebvS83JxaRcAKCPjut82BAwfq5Zdf1po1a7RmzRr16NFDv/71r3XnnXdKknr06KG1a9dq2bJlysvLU0JCgtatW%2BfeftSoUTp37pwyMzNVW1urkSNHas6cOe75%2BfPnKysrS5MmTVKnTp00a9YspaamSpICAwOVl5enBQsWKC0tTbfddpvWrVunbt26tVAnAPxYpy/YdbzsqtVl3NBtUbyEA9zsAozv34QKzYozWN8JDg5UZGQHevJ3/tEPQ7P%2B83CrDi%2BpsV10xg8Clj/UeUe3Dlrzr4PUml9u9Y%2Bfm5ZDP7x92xMrtN4X1wEAAPwUAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMFmx1AQAkyVBdXZ0klyTD6mIa0FrrAoDWh4AFtAqGXvjdIZ2%2BYLe6kAbd3TvC6hIAwG8QsIBW4vQFu46XXbW6jAbdFhVmdQkA4De4BgsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAEzmU8B69NFH9Z//%2BZ%2B6fPlyc9UDAADg93wKWHfffbd%2B85vf6N5779Xs2bO1Y8cOGYbRXLUBAAD4JZ8C1rPPPqs//elPysvLU1BQkGbMmKGf/vSnWr16tb744ovmqhEAAMCvBPu6QUBAgO655x7dc889stvtKigoUF5enl599VUlJCRo0qRJuv/%2B%2B5ujVgAAAL/gc8CSpIqKCr3zzjt65513dPz4cSUkJOjhhx9WWVmZFi1apL1792rhwoVm1woAAOAXfApYb7/9tt5%2B%2B2199tln6ty5sx566CG9/PLL6tWrl/sx3bt317JlywhYAACgzfIpYC1cuFAjRozQunXrNGzYMAUGel/C1bt3bz3xxBOmFQgAAOBvfApYn3zyiSIjI1VdXe0OV8XFxYqNjVVQUJAkKSEhQQkJCeZXCgAA4Cd8ehfhlStX9MADD2jDhg3usWnTpmncuHE6f/686cUBAAD4I58C1vLly/X//t//05QpU9xj7777rrp3767s7GzTiwMAAPBHPgWsffv2ad68ebLZbO6xzp076xe/%2BIX%2B/Oc/m14cAACAP/IpYAUHB%2BvSpUte43a7nTu6AwAA/J1PAWvYsGFaunSpzpw54x47e/assrOzlZycbHpxAAAA/sindxE%2B99xzmjJlikaOHKnw8HBJ0qVLlxQbG6v58%2Bc3S4EAAAD%2BxqeAFRUVpd///vfatWuX/vrXvyo4OFh9%2B/bV0KFDFRAQ0Fw1AgAA%2BBWfPyonKChIycnJvCQIAADQAJ8CVmVlpV566SUdOHBAtbW1Xhe2//GPfzS1OAAAAH/kU8B6/vnn9fnnn%2BvBBx9Up06dmqsmAAAAv%2BZTwPrzn/%2BsjRs3avDgwc1VD9AMuIUIAKBl%2BRSwbrnlFkVFRTVXLUCzWf3BcZ2%2BYLe6jAbd3TvC6hIAACbyKWCNGzdOGzdu1OLFi90f7gz4g9MX7DpedtXqMhp0W1SY1SUAAEzkU8Cqrq7Wtm3b9PHHH6tnz55q3769x/wbb7xhanEAAAD%2ByOfbNIwePbo56gAAALhp%2BBSwsrOzm6sOAACAm4ZPn0UoSRUVFcrNzdWzzz6rCxcu6L333tOpU6eaozYAAAC/5FPA%2BvLLLzVmzBj9/ve/1/bt2/X111/r3XffVVpamg4fPtxcNQIAAPgVnwLWihUrlJqaqg8//FDt2rWTJK1atUopKSn61a9%2B9YMKcDqdGjNmjPbu3eseKy0t1ZQpUxQfH6/Ro0dr586dHtvs2rVLY8aMUVxcnCZPnqyzZ896zL/%2B%2BusaNmyYEhMTtXDhQjkcDo/jLViwQElJSUpOTlZ%2Bfr7Hto0dGwAAoDE%2BBawDBw5oypQpHh/sHBwcrOnTp6ukpMTngzudTs2ePVsnTpzwGE9PT1d0dLS2bt2qsWPHKiMjQ2VlZZKk8%2BfPKz09XWlpadq6dasiIyOVnp7u3nb79u3Ky8vTkiVLtHnzZh0%2BfFg5OTnu%2BZUrV6qkpEQFBQXKzMxUbm6u3n///SYdGwAAoCl8Clgul0sul8tr/OrVqz7fF%2BvkyZMaP368SktLPcZ3796ts2fPavHixerdu7emTZumuLg4FRUVSZJ%2B97vfaeDAgZo8ebL69Omj7OxsnTt3zn0GrKCgQJMmTdLw4cM1YMAAZWVlqaioSA6HQ3a7XUVFRVq0aJFiYmKUmpqqqVOnasuWLU06NgAAQFP4FLDuvfdevfLKKx4hq7q6Wjk5Obr77rt9OvCePXs0dOhQFRYWenxodHFxsWJjYxUSEuIeS0xM1KFDh9zzSUlJ7rnQ0FD1799fBw8elMvl0pEjRzw%2ByicuLk61tbU6duyYjh07pvr6esXFxXnsu7i4uEnHBgAAaAqfbtMwb948Pfnkk7r33nvlcDj07//%2B7zp37pwiIiK0YsUKnw782GOPXXe8srJS0dHRHmNRUVEqLy%2BX9M27GK%2Bd79Kli8rLy3Xp0iU5HA6P%2BaCgIEVERKisrEwBAQGKiIhQcHCwx74dDocuXrzY6LEBAACawqeA1bVrV/33f/%2B3tm3bpqNHj8rlcumxxx7TuHHj1LFjR1MKstvtXneIb9%2B%2BvZxOpySppqamwfmamhr319ebd7lc152TvrkerLFjAwAANIXPd3IPCwvTo48%2B2hy1SJJCQkL01VdfeYw5nU6Fhoa6568NPE6nU%2BHh4R5h6dr5sLAw1dXVXXdO%2Bub7auzYTVFRUaHKykqvcZvNptDQTk3ez80uKCjQ4%2B/m5X3dIIDGBQcH6AfcLrHFtOz/I60f/fAWFBR4w%2Bfla1%2B1MpNPAevJJ5%2B84bwZn0XYtWtXr3cVVlVVyWazueevbVRVVZX69eunyMhIhYSEqKqqSrfffrskqb6%2BXtXV1bLZbHK5XKqurpbL5VJgYKB729DQUIWHhzd67KYoLCxUbm6u13hGRoZmzJjR5P20FeHhzf8hx3V1dc1%2BDOBm1KlTmMclFa1VS/w/4k/oh6fNmzda8rzs009Ojx49PL6uq6vTl19%2BqePHj2vSpEmmFDRo0CBt2LBBTqfTfUZq//797gvXBw0apAMHDrgfb7fbVVJSopkzZyogIEADBw7U/v373RfCHzx4UO3atVNMTIwMw1BwcLAOHTqkhIQESdK%2Bffs0YMCAJh27KSZMmKCUlBSvcZvNpkuX7Kqv52yK9M1vFeHhYS3UE3oO/BCXL9vV2s9gtdz/I60f/fAWFBR4w%2Bfl5mTKZxGuW7fOtHtFDRkyRN27d9e8efM0ffp0ffTRRzpy5Ij7Ivq0tDRt2rRJGzZs0IgRI5Sbm6uePXu6A9Xjjz%2BuzMxM9e3bV9HR0crKytL48ePd7wwcN26cMjMztXz5cpWXlys/P9%2B978aO3RTR0dENnnK8ePGq6upY9N9XX%2B9qgZ4YjT8EgJe6OkP%2B8AtKy/w/4j/oh6cbPS83J1N%2BNRk3bpz%2B8Ic//ODtv3/j0sDAQOXl5amyslJpaWn6n//5H61bt07dunWT9M1ZtLVr12rr1q169NFHdfnyZa1bt869/ahRozRt2jRlZmZq6tSpiouL05w5c9zz8%2BfP14ABAzRp0iQtWbJEs2bNUmpqapOODQAA0BSmvLh%2B8OBBn280%2Bn1Hjx71%2BLpnz54qKCho8PHJycl67733Gpx/%2Bumn9fTTT193LjQ0VNnZ2Q2ejWvs2AAAAI350Re5X7lyRX/5y1/0%2BOOPm1YUAACAP/MpYN16660eL%2BdJUrt27fTEE09o7NixphYGAADgr3wKWL7erR0AAKAt8ilgffuByk3x/c8LBAAAaEt8ClgTJ050v0T4/Q9ovnYsICDA68J1AACAtsKngPWb3/xGS5cu1dy5czVkyBC1b99eR44c0eLFi/Xwww9r1KhRzVUnAACA3/DpPljZ2dl64YUXNHLkSEVGRqpDhw66%2B%2B67tXjxYr311lvq0aOH%2Bw8AAEBb5VPAqqiouG546tixoy5evGhaUQAAAP7Mp4AVFxenVatW6cqVK%2B6x6upq5eTkaOjQoaYXBwAA4I98ugZr0aJFevLJJzVs2DD16tVLhmHo9OnTstlseuONN5qrRgAAAL/iU8Dq06eP3n33XW3btk0nT56UJP3sZz/Tgw8%2BqLCwsGYpEAAAwN/4/FmE//AP/6BHH31UpaWl6tmzp6Rv7uYOAACAb/h0DZZhGPrVr36lpKQkjR49WmVlZXruuee0cOFC1dbWNleNAIAWFhQYIMlo5X9cHvdkBFoTn85gFRQU6O2331ZmZqYWL14sSUpNTVVWVpa6dOmiZ555plmKBAC0rB6RoVr9wV91%2BoLd6lIa1CsqTIvHx1ldBnBdPgWswsJCvfDCC7rvvvu0ZMkSSdKoUaPUrl07ZWdnE7AA4CZy%2BoJdx8uuWl0G4Jd8eomwtLRU/fr18xqPiYlRZWWlaUUBAAD4M58CVo8ePXTkyBGv8U8%2B%2BcR9wTsAAC0hKDBA9fX1klyy/nqwxv6grfHpJcKnnnpKWVlZqqyslGEY2r17twoLC1VQUKB58%2BY1V40AAHjpERmqrK1HWv11Ys/cd4fVZcACPgWstLQ01dXVaf369aqpqdELL7ygzp076z/%2B4z/02GOPNVeNAABcF9eJobXyKWBt27ZNDzzwgCZMmKD/%2B7//k2EYioqKaq7aAAAA/JJP12AtXrzYfTF7586dCVcAAADX4VPA6tWrl44fP95ctQAAANwUfHqJMCYmRnPmzNHGjRvVq1cvhYSEeMxnZ2ebWhwAAIA/8ilgffHFF0pMTJQk7nsFAADQgEYD1osvvqiMjAzdcsstKigoaImaAAAA/Fqj12Dl5%2BfLbve8x8i0adNUUVHRbEUBAAD4s0YD1vU%2BqXzv3r1yOBzNUhAAAIC/8%2BldhAAAAGgcAQsAAMBkTQpYAQEBzV0HAADATaNJt2lYunSpxz2vamtrlZOTow4dOng8jvtgAQAANCFgJSUled3zKj4%2BXhcvXtTFixebrTAAAAB/1WjA4t5XAAAAvuEidwAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMFmjn0UIAAB%2BmKDAAElGCx3Npbq6OkmuH3jMAJPradsIWAAANJMekaFa/cFfdfqC3epSGtQrKkzP3HeH1WXcdAhYAAA0o9MX7DpedtXqMtDCuAYLAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkrTZgffjhh4qJiVG/fv3cf8%2BaNUuSVFpaqilTpig%2BPl6jR4/Wzp07PbbdtWuXxowZo7i4OE2ePFlnz571mH/99dc1bNgwJSYmauHChXI4HO45p9OpBQsWKCkpScnJycrPz2/%2BbxYAANxUWm3AOnHihFJSUrRz507t3LlTO3bs0LJlyyRJ06dPV3R0tLZu3aqxY8cqIyNDZWVlkqTz588rPT1daWlp2rp1qyIjI5Wenu7e7/bt25WXl6clS5Zo8%2BbNOnz4sHJyctzzK1euVElJiQoKCpSZmanc3Fy9//77LfvNAwAAv9ZqA9bJkyf1j//4j%2BrcubOioqIUFRWljh07avfu3SotLdXixYvVu3dvTZs2TXFxcSoqKpIk/e53v9PAgQM1efJk9enTR9nZ2Tp37pz27t0rSSooKNB1vh64AAAQ2UlEQVSkSZM0fPhwDRgwQFlZWSoqKpLD4ZDdbldRUZEWLVqkmJgYpaamaurUqdqyZYuVrQAAAH6mVQes22%2B/3Wu8uLhYsbGxCgkJcY8lJibq0KFD7vmkpCT3XGhoqPr376%2BDBw/K5XLpyJEjGjx4sHs%2BLi5OtbW1OnbsmI4dO6b6%2BnrFxcV57Lu4uLg5vkUAAHCTarUB64svvtCnn36qkSNH6r777tOvf/1r1dbWqrKyUtHR0R6PjYqKUnl5uSSpoqLCa75Lly4qLy/XpUuX5HA4POaDgoIUERGhsrIyVVZWKiIiQsHBwR77djgcunjxYjN%2BtwAA4GYS3PhDWt7f/vY31dTUKCQkRGvWrFFpaamWLVummpoa2e12tW/f3uPx7du3l9PplCTV1NQ0OF9TU%2BP%2B%2BnrzLpfrunOS3PsHAABoTKsMWLfeeqs%2B%2B%2BwzhYeHS5JiYmLkcrk0d%2B5c/cu//IsuXbrk8Xin06nQ0FBJUkhIiFcYcjqdCg8PbzAsOZ1OhYWFqa6u7rpzkhQWFtak2isqKlRZWek1brPZFBraqUn7aAuCggI9/m5erhY4BgD4r%2BDgALXiF7V%2BsKCgwBs%2BL1/7ipeZWmXAkuQOV9/q06ePHA6HunTpopMnT3rMVVVVyWazSZK6du3q1ciqqir169dPkZGRCgkJUVVVlfv6rvr6elVXV8tms8nlcqm6uloul0uBgYHubUNDQ73qaUhhYaFyc3O9xjMyMjRjxoymffNtSHh404Lrj1FXV9fsxwAAf9apU5jH5TE3k82bN1ryvNwqu7ljxw49%2B%2Byz%2BuSTT9wXs5eUlCgyMlKDBw/Wpk2b5HQ63Wek9u/f775wfdCgQTpw4IB7X3a7XSUlJZo5c6YCAgI0cOBA7d%2B/330h/MGDB9WuXTvFxMTIMAwFBwfr0KFDSkhIkCTt27dPAwYMaHLtEyZMUEpKite4zWbTpUt21ddzNkX65reK8PCwFuoJPQeAG7l82a6b9QzWjZ6Xm1OrDFjx8fEKCwvTwoULlZ6erjNnzignJ0dPP/20kpKS1L17d82bN0/Tp0/XRx99pCNHjmjFihWSpLS0NG3atEkbNmzQiBEjlJubq549e7oD1eOPP67MzEz17dtX0dHRysrK0vjx491Bbty4ccrMzNTy5ctVXl6u/Px8976bIjo6usFTjhcvXlVdHU/231df72qBnhjNvH8A8G91dYZu1l9Gb/S83JxaZcDq0KGDXnvtNS1fvlyPPPKIOnTooH/913/Vz3/%2Bc0nS%2BvXrtWDBAqWlpem2227TunXr1K1bN0lSjx49tHbtWi1btkx5eXlKSEjQunXr3PseNWqUzp07p8zMTNXW1mrkyJGaM2eOe37%2B/PnKysrSpEmT1KlTJ82aNUupqakt2wAAAODXWmXAkr655uq111677lzPnj1VUFDQ4LbJycl67733Gpx/%2Bumn9fTTT193LjQ0VNnZ2crOzvatYAAAgL9rtQEL/uKHvvzm%2BvvF564fsY%2Bm4iVCAEDLImDhR1v9wXGdvmC3uowG3d07wuoSAABtDAELP9rpC3YdL7tqdRkNui2q%2BW8FAQDA9xGwWjFHXZ2%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%2BvtUlAQAAPxJsdQGt0cqVK1VSUqKCggKVlpbqueeeU48ePXT//fdbXRoAAPADnMG6ht1uV1FRkRYtWqSYmBilpqZq6tSp2rJli9WlAQAAP0HAusaxY8dUX1%2BvuLg491hiYqKKi4strAoAAPgTAtY1KisrFRERoeDg7149jYqKksPh0MWLFy2sDAAA%2BAsC1jXsdrvat2/vMfbt106n04qSAACAn%2BEi92uEhIR4Balvvw4LC2t0%2B4qKClVWVnqN22w2hYZ28qmWoMAA3dGtg0/btLTOt7RTr6jG%2B2KlW/8hpNX/JkGN5vCHGiX/qJMazeEPNfaKClNwcIBuxnMuQUGBN3xejo6ObrZjE7Cu0bVrV1VXV8vlcikw8JvFVlVVpdDQUIWHhze6fWFhoXJzc73Gk5KStGrVKp/%2BMSMjO%2Bi3/9it6cVbJO0e37epqKhQYWGhJkyY0KwL3F9824//oB9urBFP9MMbPzeeWCPeKioqNHv2bO3du9drLiMjQzNmzGi2YxOwrtGvXz8FBwfr0KFDSkhIkCTt27dPAwYMaNL2EyZMUEpKisfYyZMnNXfuXFVWVrLo/66yslK5ublKSUmhJ6If10NPPNEPb/TEE/3wVllZqb179yonJ0d9%2BvTxmLPZbM16bALWNUJDQzVu3DhlZmZq%2BfLlKi8vV35%2BvlasWNGk7aOjo1nYAAC0In369FFsbGyLHpOAdR3z589XVlaWJk2apE6dOmnWrFlKTU21uiwAAOAnCFjXERoaquzsbGVnZ1tdCgAA8EM331sGAAAALBb0y1/%2B8pdWF9EWdOjQQUOGDFGHDq37tgstiZ54oh/e6Ikn%2BuGNnniiH96s6kmAYRhGix4RAADgJsdLhAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgJWM3M6nVqwYIGSkpKUnJys/Px8q0uy1IcffqiYmBj169fP/fesWbOsLssSTqdTY8aM0d69e91jpaWlmjJliuLj4zV69Gjt3LnTwgpb3vV6snTpUq818%2Babb1pYZfMrLy/XzJkzddddd2n48OFasWKFnE6npLa7Rm7Uk7a4Rs6cOaOnnnpK8fHxSklJ0Wuvveaea6tr5EY9sWKN8FmEzWzlypUqKSlRQUGBSktL9dxzz6lHjx66//77rS7NEidOnFBKSoqWLl2qb%2B9xGxISYnFVLc/pdGr27Nk6ceKEx3h6erpiYmK0detWffjhh8rIyNAf/vAHdevWzaJKW05DPTl16pTmzJmjhx9%2B2D3WsWPHli6vRc2cOVMRERH67W9/q%2Brqai1YsEBBQUGaO3eupk%2Bfrn79%2BrW5NXKjnrS1NWIYhqZNm6ZBgwbp7bff1unTpzV79mx169ZNDz74YJtcI431xJI1YqDZfP3118add95p7N271z2Wl5dnTJw40cKqrDVnzhxj1apVVpdhqRMnThjjxo0zxo0bZ8TExBh79uwxDMMwdu3aZcTHxxs1NTXux06ePNlYu3atVaW2mIZ6YhiGMWzYMGPnzp0WVteyTp48acTExBgXLlxwj23bts0YNmyYsXv37ja5Rm7UE8Noe2ukoqLCeOaZZ4yrV6%2B6xzIyMoysrKw2u0Zu1BPDsGaN8BJhMzp27Jjq6%2BsVFxfnHktMTFRxcbGFVVnr5MmTuv32260uw1J79uzR0KFDVVhY6D6LJ0nFxcWKjY31OKOXmJioQ4cOWVFmi2qoJ1euXFF5ebl69eplXXEtzGazaePGjercubPH%2BOXLl3X48OE2uUau1xPDMHT58uU2u0ZWrVqlW265RZK0f/9%2B7du3T0OGDGnTa%2BTanuzdu1d33XWXZWuElwibUWVlpSIiIhQc/F2bo6Ki5HA4dPHiRUVGRlpYnTW%2B%2BOILffrpp1q/fr1cLpceeOABzZw5U%2B3atbO6tBbz2GOPXXe8srJS0dHRHmNRUVEqLy9vibIs1VBPTp06pYCAAK1fv16ffPKJIiIiNGXKFD300EMtXGHL6dSpk%2B655x7314ZhaMuWLRo6dGibXSMN9eSf/umf2uQa%2Bb6UlBSdP39eP/3pT3X//fdr%2BfLlbXKNfN%2B1PSkuLrZkjRCwmpHdblf79u09xr79%2BtuLM9uSv/3tb6qpqVFISIjWrFmj0tJSLV26VA6HQwsWLLC6PMs1tF7a4lr51qlTpxQYGKg%2Bffpo4sSJ2rNnj55//nl17NhRqampVpfXIl588UUdPXpURUVFys/PZ43om54cO3ZMRUVF%2Bvzzz9v0Glm7dq2qqqr0y1/%2BUsuXL%2Bf/EX3Xk8zMTC1btkwDBgywZI0QsJpRSEiI16L%2B9uuwsDArSrLUrbfeqs8%2B%2B0zh4eGSpJiYGLlcLv3iF7/Q/PnzFRAQYHGF1goJCdFXX33lMeZ0OhUaGmpRRdZ76KGHlJKS4l4zd9xxh06fPq233nqrTTx55uTkqKCgQC%2B99JL69u3LGpF3T/r27dum10hsbKwkad68eZozZ44eeeQRXbp0yeMxbW2NfNuT%2BfPna%2B7cuXruuecsWSNcg9WMunbtqurqarlcLvdYVVWVQkND3f/Qbc2133efPn3kcDhUXV1tUUWtR9euXVVZWekxVlVVJZvNZlFFrcO1a6Z3796qqKiwqJqWs2TJEm3evFk5OTnuJ4G2vkau1xOp7a2RCxcu6MMPP/QY69u3r2pra2Wz2drkGrlRT65evWrJGiFgNaN%2B/fopODjY4%2BLCffv2acCAARZWZZ0dO3borrvuksPhcI%2BVlJQoIiKiTV6Pdq1BgwappKTE46zn/v37Pd4k0da8/PLLmjJlisfY0aNHb/o3SuTm5qqwsFCrV6/WP//zP7vH2/IaaagnbXGNlJaWasaMGR4B4ciRI4qKilJiYqL%2B93//t82tkYZ60rlzZ73xxhvWrJEWfc9iG/TCCy8Yo0ePNoqLi40PPvjASExMND744AOry7LElStXjOHDhxvPPvuscerUKePjjz82kpOTjddee83q0izzk5/8xH1Lgvr6emP06NHGM888Y/z1r381XnnlFSMhIcE4f/68xVW2rO/3pLi42IiNjTU2bdpknDlzxnjzzTeNO%2B%2B80zh8%2BLDFVTafEydOGP379zfWrFljVFZWevxpq2vkRj1pi2ukvr7eeOSRR4ynnnrKOHHihPHxxx8b99xzj1FQUGDU19cbDz74YJtbIzfqiVVrhIDVzOx2uzFv3jwjPj7eGDZsmPHGG29YXZKlTpw4Yfz85z83EhISjOTkZGPdunVWl2Spa%2B/5dObMGeOJJ54w7rzzTmP06NHG7t27LazOGtf25I9//KMxduxYY9CgQcaoUaNu%2Bl9QXnnlFSMmJsbjz09%2B8hMjJibGMAzD%2BPLLL9vcGmmsJ21tjRjGN/d9mjFjhjF48GAjOTnZeOWVV9xzbfX/kRv1xIo1EmAY37vpDAAAAH40rsECAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAw2f8Hgit7CYtTlF4AAAAASUVORK5CYII%3D">
             </div>
      </div>
    </div><div class="row variablerow">
        <div class="col-md-3 namecol">
            <p class="h4">Day_Of_Week<br/><small>Numeric</small></p>
        </div>

        <div class="col-md-6">
            <div class="row">
                <div class="col-sm-6">
                    <table class="stats ">
                        <tr><th>Distinct count</th>
                        <td>376</td></tr>
                        <tr><th>Unique (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (n)</th>
                        <td>0</td></tr>
                    </table>

                </div>
                <div class="col-sm-6">
                    <table class="stats ">

                        <tr><th>Mean</th>
                        <td>4.0448</td></tr>
                        <tr><th>Minimum</th>
                        <td>1</td></tr>
                        <tr><th>Maximum</th>
                        <td>7</td></tr>
                        <tr class="ignore"><th>Zeros (%)</th>
                        <td>0.0%</td></tr>
                    </table>
                </div>
            </div>
        </div>
        <div class="col-md-3 collapse in" id="minihistogram-1273850290">
             <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAAxlJREFUeJzt3L9rE2EYwPHnegHbiGgpCRLpDxycVUrxLyg6tKQgBtwKGUvXTpWaIX9B/wbTBNxcOjlGsEPAQcjiUSRIYkCwEsGEcxbhsXdt3ufe%2Bv3sx/PS3vfyJrlLEMdxLI71%2B31pNptSqVSkWCy6Hg/PWJ4vgUUggC9mrBcAZFnOegH4f8RxLJPJJNWxuZzNqUogcGYymciLVkei4SjRcSsLc1J/vjqlVekIBE5Fw5F0v/ywXsa5mQXy5v0n%2Bf5znOiYG7M5efJwScIwnNKqgD%2BZBfLq3efEV5J7t6/L4weLU1oR8Dc%2BxQIUBAIoCARQEAigIBBAQSCAgkAABYEACgIBFAQCKLhZUXGR27PDMJQgCC55RXCNQBQXuT279uy%2B2TMMuDz8B//Bt9uzcbkIJEPY0mUPgWSIL1u6tCGnjd8SgWSMD1u6tCE/untrSiuaHgK5AsKZwPnWLE3ISwtziedYI5Ar4M78rLx8/SHzWzMfefWXsbhS%2BsKHrZmPvAqEKyVc8%2B6M4UoJl7gXC1AQCKAgEEBBIICCQAAFgQAKAgEUBAIoCARQEAigIBBAQSCAgkAABYEACgIBFAQCKAgEUBAIoCAQQGH2TPrT1ZJ8G/1KdMzi/Ky8/fg18ayVhbnUvwS4kuK3nFzPK928lupK59M6rQRxHMeuh/b7fWk2m1KpVKRYLLoeD89Yni8mW6zBYCCHh4cyGAwsxsMzlucL70EABYEACgIBFAQCKEwCKRQKsrOzI4VCwWI8PGN5vph8zAv4gi0WoCAQQEEggIJAAAWBAAoCARQEAihMAjk7O5ONjQ3p9XoW4%2BGJo6MjKZfLsrW1JeVyWdbW1mRvb8/pGpx/UdjpdGR/f1%2BiKJLj42MplUoux8NTURRJtVqVRqPh9Bt1568grVZLDg4OeFAKidRqNdnd3XV%2Bu4nzR27r9bqIiHCHC87r5OREhsOhbG5uOp/Nm3RkXqPRkO3tbZPZBIJMG4/H0m63ZX193WQ%2BgSDTut2uLC8vSz6fN5lvFkgQBFaj4ZHT01PTTzp5HgRQsMUCFAQCKH4DxxsXYOiGk98AAAAASUVORK5CYII%3D">

        </div>
       <div class="col-md-12 text-right">
            <a role="button" data-toggle="collapse" data-target="#descriptives-1273850290,#minihistogram-1273850290" aria-expanded="false" aria-controls="collapseExample">
                Toggle details
            </a>
        </div>
        <div class="row collapse col-md-12" id="descriptives-1273850290">
            <div class="col-sm-4">
                  <p class="h4">Quantile statistics</p>
                  <table class="stats indent">
                        <tr><th>Minimum</th>
                        <td>1</td></tr>
                        <tr><th>5-th percentile</th>
                        <td>1</td></tr>
                        <tr><th>Q1</th>
                        <td>2</td></tr>
                        <tr><th>Median</th>
                        <td>4</td></tr>
                        <tr><th>Q3</th>
                        <td>6</td></tr>
                        <tr><th>95-th percentile</th>
                        <td>7</td></tr>
                        <tr><th>Maximum</th>
                        <td>7</td></tr>
                        <tr><th>Range</th>
                        <td>6</td></tr>
                        <tr><th>Interquartile range</th>
                        <td>4</td></tr>
                  </table>
                  <p class="h4">Descriptive statistics</p>
                  <table class="stats indent">
                        <tr><th>Standard deviation</th>
                        <td>2.1854</td></tr>
                        <tr><th>Coef of variation</th>
                        <td>0.54031</td></tr>
                        <tr><th>Kurtosis</th>
                        <td>-1.3951</td></tr>
                        <tr><th>Mean</th>
                        <td>4.0448</td></tr>
                        <tr><th>MAD</th>
                        <td>1.9108</td></tr>
                        <tr class=""><th>Skewness</th>
                        <td>-0.021774</td></tr>
                        <tr><th>Sum</th>
                        <td>4453200</td></tr>
                        <tr><th>Variance</th>
                        <td>4.776</td></tr>
                        <tr><th>Memory size</th>
                        <td>8.4 MiB</td></tr>
                 </table>
            </div>
             <div class="col-sm-8 histogram">
                 <img 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G2MiRI9WnTx8tX75c8%2BfP1759%2B1ReXq7169dLklJTU7Vz505t375d48ePV25urvr27WsEqhkzZigzM1MDBw5UdHS0srKyNG3aNOOdgVOnTlVmZqbWrVun2tpa5efnG9u%2B1tydER0dffVDjvv2X2%2B7uoXWVqesfqK1tTnU2ur9T3ar0D/P0D/P0D/PWNc/pwVzmqvD1%2BUuZknA%2Bv3vfy%2BHw6Ft27Zp27Ztkj57J6GPj49OnjyprVu3auXKlUpNTdVdd92lrVu3qnfv3pKkmJgYbdmyRWvXrlVeXp4SEhK0detWY9uTJk3S%2BfPnlZmZqZaWFk2cOFFLliwxxlesWKGsrCzNmjVLoaGhWrRokXF60tfXV3l5ecrIyLjq3AAAAJ3h43Q6vT%2BeeoEZW/brVM2nVpdxXe7pHaLNjwyX5GPJ/P7%2BvoqICNHFi5/yF/B1oH%2BeoX%2BeoX%2Besb5/Ti36fye8%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%2BerXPnzrlsc9euXRo7dqwSExO1cuVK2Ww2l/kyMjKUlJSkMWPGKD8/32Xd6upqzZkzR/Hx8Zo8ebIOHjzYRY8cAADcrCwNWHa7XYsXL9bp06ddlp85c0ZLlizRgQMHdPDgQR04cEAPP/ywJOmjjz5SWlqaUlNTtWfPHkVERCgtLc1Yd%2B/evcrLy9Pq1av18ssv68SJE8rJyTHGN2zYoIqKChUUFCgzM1O5ubl65513jPG0tDRFR0drz549evDBB5Wenq6ampou7gQAALiZWBawqqqqNG3aNFVXV191bPDgwYqMjDR%2BAgMDJUn/9V//pWHDhmn27NkaMGCAsrOzdf78eeMIWEFBgWbNmqVx48Zp6NChysrKUlFRkWw2m5qamlRUVKSnn35asbGxSklJ0RNPPKHdu3dLkg4fPqxz585p1apVuvvuuzVv3jzFxcWpqKjoxjUGAAB4PcsC1pEjRzRq1CgVFhbK6XQay69cuaLa2lr169fvquudOHFCSUlJxu2goCANHjxYpaWlcjgcKi8v14gRI4zxuLg4tbS0qLKyUpWVlWpra1NcXJwxnpiYqLKyMklSWVmZhgwZYoS5z8ePHz9u1sMGAAC3AH%2BrJn700UevuvzMmTPy8fHRtm3b9O677yo8PFxz5szRQw89JEmqq6tTdHS0yzp33HGHamtrdfnyZdlsNpdxPz8/hYeHq6amRj4%2BPgoPD5e//z8fdmRkpGw2my5evKj6%2Bvp2246MjFRtba1ZDxu4Ds5r3%2BXfcqi1tVWSw4RtecLHwrkB4MayLGB15MyZM/L19dWAAQM0c%2BZMHTlyRM8884xuv/12paSkqLm5WQEBAS7rBAQEyG63q7m52bh9tXGHw3HVMemz68Gampo6XBew0qbfntLZC01Wl3Fd%2BkUG68kJ91hdBgDcUG4FrG9/%2B9tKTU3VAw88oNDQ0C4p6KGHHlJycrLCwsIkSffcc4/Onj2rV199VSkpKQoMDGwXeOx2u8LCwlzC0hfHg4OD1draetUxSQoODlZgYKAuXbrUbjwoKKjT9dfV1am%2Bvr7T9/cW/v4%2BsuqMsp%2Bfr8u/tx6Hzl5o0qmaT60u5LpZuf94iv3PM/TPM9b3z2HRvObp6HU5Kiqq3VkrM7kVsO677z797Gc/U3Z2tv7zP/9T3/rWtzR69Gj5%2BJh76P/zcPW5u%2B%2B%2BW%2B%2B9954kqVevXu0a1dDQoEGDBikiIkKBgYFqaGhQ//79JUltbW1qbGxUVFSUHA6HGhsb5XA45Ovra6wbFBSksLAw9erVq907GhsaGhQVFdXp2gsLC5Wbm9tueWL6jk5vozsKDQ12ObVqhbCwYEvnt8pnp/e8W3fYfzx1q%2B5/ZqF/nrGqfzfD75%2BOXpfT09O1YMGCLpvXrd94Tz31lBYvXqxDhw7p9ddf14IFCxQWFqaHHnpIDz30kBFqPPHTn/5UpaWlLp9PdfLkSWPbw4cP17Fjx4yxpqYmVVRUaOHChfLx8dGwYcNUUlJiXAhfWlqqHj16KDY2Vk6nU/7%2B/jp%2B/LgSEhIkSUePHtXQoUONbW/fvl12u904GlZSUuJy0fy1TJ8%2BXcnJye2Wr933sZud6F4%2B%2BaRJVh7BCgsL1uXLTWpr8/6/ptzn/Y/Zyv3HU%2Bx/nqF/nrG%2Bf97/f9bR67I7B0%2Buh9t/Uvr4%2BGj06NEaPXq0mpqaVFBQoLy8PL344otKSEjQrFmzdP/99193QePHj9eLL76o/Px8paSkaP/%2B/XrzzTdVUFAgSUpNTdXOnTu1fft2jR8/Xrm5uerbt68RqGbMmKHMzEwNHDhQ0dHRysrK0rRp04x3Bk6dOlWZmZlat26damtrlZ%2Bfr/Xr10uSRo4cqT59%2Bmj58uWaP3%2B%2B9u3bp/LycmO8M6Kjo69%2ByHHf/uvuSXfQ2uqU1U%2B0tjaHWlu9/8nuPisvTDdHd9h/PHXr7n/moH%2Besa5/3v/7p8PX5S52Xcfs6%2Brq9Oabb%2BrNN9/UqVOnlJCQoG9%2B85uqqanR008/reLiYq1cubLT2/vXU4zDhg3TT3/6U23evFmbN29WTEyMfvKTn%2BgrX/mKJCkmJkZbtmzR2rVrlZeXp4SEBG3dutVYf9KkSTp//rwyMzPV0tKiiRMnasmSJcb4ihUrlJWVpVmzZik0NFSLFi1SSkqKJMnX11d5eXnKyMhQamqq7rrrLm3dulW9e/e%2BnjYBAIBblI/zXz%2BE6hreeOMNvfHGG3rvvffUs2dPPfTQQ0pNTXX5zKqioiKtXbtWpaWlXVGv15qxZb/XXqR8T%2B8QbX5kuKx6m72/v68iIkJ08eKnt%2BhfwE4t%2Bn8n2H8swv7nGfrnGev75/2/f15ZMMaSud06grVy5UqNHz9eW7du1dixY40Lxf/V3Xffrccff9y0AgEAALyNWwHr3XffVUREhBobG41w9fmnn/v5%2BUmSEhISjAvIAQAAbkVuva3nypUr%2BvrXv67t27cby%2BbNm6epU6fqo48%2BMr04AAAAb%2BRWwFq3bp3%2B4z/%2BQ3PmzDGWvf322%2BrTp4%2Bys7NNLw4AAMAbuRWwjh49quXLl7t8dkTPnj31ox/9SH/%2B859NLw4AAMAbuRWw/P39dfny5XbLm5qa5MabEQEAAG5qbgWssWPHas2aNfrb3/5mLDt37pyys7M1Zow1b4MEAADobtx6F%2BGyZcs0Z84cTZw40fi%2BwMuXL2vIkCFasWJFlxQIAADgbdwKWJGRkfrVr36lQ4cO6a9//av8/f01cOBAjRo1yvQvfAYAAPBWbn9Vjp%2Bfn8aMGcMpQQAAgA64FbDq6%2Bv1wgsv6NixY2ppaWl3Yfvvf/97U4sDAOs51draqs%2B%2BrNqb38zDWQbgRnIrYD3zzDN6//339cADDyg0NLSragKAbsSpZ187rrMXmqwu5Lr0iwzWkxPusboM4JbjVsD685//rB07dmjEiBFdVQ8AdDtnLzR57ZfdArCGWx/TcNtttykyMrKragEAALgpuBWwpk6dqh07dqitra2r6gEAAPB6bp0ibGxs1FtvvaU//vGP6tu3rwICAlzGf/GLX5haHAAAgDdy%2B2MaJk%2Be3BV1AAAA3DTcCljZ2dldVQcAAMBNw61rsCSprq5Oubm5euqpp3ThwgX95je/0ZkzZ7qiNgAAAK/kVsD68MMPNWXKFP3qV7/S3r179Y9//ENvv/22UlNTdeLEia6qEQAAL%2BX08MfxhQ%2B6teIH18OtU4Tr169XSkqK1qxZo4SEBEnSxo0btWzZMj3//PMqKCjokiIBAPBWm357yms/qPa%2Bu8OtLsFruRWwjh07pl/%2B8pcuX%2Bzs7%2B%2Bv%2BfPna9q0aaYXBwCAt/PmD6q9KzLY6hK8llunCB0OhxwOR7vln376qfz8/EwrCgAAwJu5FbC%2B9rWv6ec//7lLyGpsbFROTo7uu%2B8%2B04sDAADwRm4FrOXLl%2Bv999/X1772NdlsNv3gBz/Q%2BPHjVV1drWXLlnVVjQAAAF7FrWuwevXqpddff11vvfWWTp48KYfDoUcffVRTp07V7bff3lU1AgAAeBW3P8k9ODhY3/72t7uiFgAAgJuCWwHrO9/5zr8d57sIAaB78fP1kbWfZfTFz3G6Xj7XvgvQjbgVsGJiYlxut7a26sMPP9SpU6c0a9YsUwsDAHguJiJIm377V6/9HKZ%2BkcF6csI9VpcBuM2U7yLcunWrampqTCkIAGAub/4cJsBbuf1dhFczdepU/e///q8ZmwIAAPB6pgSs0tJSPmgUAADg/3h8kfuVK1f0l7/8RTNmzDCtKAAAAG/mVsC68847Xb6HUJJ69Oihxx9/XA8%2B%2BKCphQEAAHgrtwLW%2BvXru6oOAACAm4ZbAau4uLjT901KSnK7GAAAgJuBWwFr5syZxilCp/OfHxj3xWU%2BPj46efKkWTUCAAB4FbcC1s9%2B9jOtWbNGS5cu1ciRIxUQEKDy8nKtWrVK3/zmNzVp0qSuqhMAAMBruPUxDdnZ2Xr22Wc1ceJERUREKCQkRPfdd59WrVqlV199VTExMcYPAADArcqtgFVXV3fV8HT77bfr4sWLphUFAADgzdwKWHFxcdq4caOuXLliLGtsbFROTo5GjRplenEAAADeyK1rsJ5%2B%2Bml95zvf0dixY9WvXz85nU6dPXtWUVFR%2BsUvftFVNQIAAHgVtwLWgAED9Pbbb%2Butt95SVVWVJOmxxx7TAw88oODg4C4pEAAAwNu4FbAk6Utf%2BpK%2B/e1vq7q6Wn379pX02ae5AwAA4DNuXYPldDr1/PPPKykpSZMnT1ZNTY2WLVumlStXqqWlpatqBAAA8CpuBayCggK98cYbyszMVEBAgCQpJSVFv/vd75Sbm9slBcJ6fr4%2BkpwW/jjU2toqyeHhdgAAuDHcOkVYWFioZ599VhMmTNDq1aslSZMmTVKPHj2UnZ2tJ598skuKhLViIoK06bd/1dkLTVaXcl36RQbryQn3WF0GAOAW4lbAqq6u1qBBg9otj42NVX19vWlFofs5e6FJp2o%2BtboMAAC8glunCGNiYlReXt5u%2Bbvvvmtc8A4AAHCrc%2BsI1ve%2B9z1lZWWpvr5eTqdThw8fVmFhoQoKCrR8%2BfKuqhEAAMCruBWwUlNT1draqm3btqm5uVnPPvusevbsqR/%2B8Id69NFHu6pGAAAAr%2BJWwHrrrbf09a9/XdOnT9fHH38sp9OpyMjIrqoNAADAK7l1DdaqVauMi9l79uxpSriy2%2B2aMmWKiouLjWXV1dWaM2eO4uPjNXnyZB08eNBlnUOHDmnKlCmKi4vT7Nmzde7cOZfxXbt2aezYsUpMTNTKlStls9lc5svIyFBSUpLGjBmj/Px8l3WvNTcAAMC1uBWw%2BvXrp1OnTpk2ud1u1%2BLFi3X69GmX5WlpaYqOjtaePXv04IMPKj09XTU1NZKkjz76SGlpaUpNTdWePXsUERGhtLQ0Y929e/cqLy9Pq1ev1ssvv6wTJ04oJyfHGN%2BwYYMqKipUUFCgzMxM5ebm6p133unU3AAAAJ3h1inC2NhYLVmyRDt27FC/fv0UGBjoMp6dnd3pbVVVVempp55qt/zw4cM6d%2B6cXnvtNQUGBmrevHk6fPiwioqKlJ6ertdee03Dhg3T7NmzjTlHjx6t4uJiJSUlqaCgQLNmzdK4ceMkSVlZWfre976npUuXyuFwqKioSC%2B99JJiY2MVGxurJ554Qrt379b9999/zbkBAAA6w60jWB988IESExMVEhKi%2Bvp6VVdXu/y448iRIxo1apQKCwvldP7zU7bLyso0ZMgQl/CWmJio48fiaB6qAAAU8klEQVSPG%2BNJSUnGWFBQkAYPHqzS0lI5HA6Vl5drxIgRxnhcXJxaWlpUWVmpyspKtbW1KS4uzmXbZWVlnZobAACgM655BOu5555Tenq6brvtNhUUFJg2cUfvOqyvr1d0dLTLssjISNXW1kqS6urq2o3fcccdqq2t1eXLl2Wz2VzG/fz8FB4erpqaGvn4%2BCg8PFz%2B/v4u27bZbLp48eI15wYAAOiMax7Bys/PV1OT61ekzJs3T3V1dV1SUFNTk/E9h58LCAiQ3W6XJDU3N3c43tzcbNy%2B2nhH25b0b8c/nxsAAKAzrnkE619P332uuLjY5Z15ZgoMDNSlS5dcltntdgUFBRnjXww8drtdYWFhLmHpi%2BPBwcFqbW296pgkBQcHX3Puzqirq%2BNrg7ohf38fuXlGvBtxWF2Ax7y5/77eWfZNxZv3n5vh%2BevtOnpdjoqKanfWykxuXeR%2BI/Tq1avduwobGhoUFRVljH%2BxUQ0NDRo0aJAiIiIUGBiohoYG9e/fX5LU1tamxsZGRUVFyeFwqLGxUQ6HQ77/91uzoaFBQUFBCgsLu%2BbcnVFYWKjc3Nx2yxPTd3R6GzBfaGiwy6lhb9La2mp1CR6j//AE%2Bw880dHrcnp6uhYsWNBl83a7PXb48OHavn277Ha7cUSqpKTEuHB9%2BPDhOnbsmHH/pqYmVVRUaOHChfLx8dGwYcNUUlJiXAhfWlqqHj16KDY2Vk6nU/7%2B/jp%2B/LgSEhIkSUePHtXQoUM7NXdnTJ8%2BXcnJye2Wr9338XV0A2b55JMm8Rewdby5/xzBsp437z83w/PX23X0uuzOwZPr0amA5ePj06VF/KuRI0eqT58%2BWr58uebPn699%2B/apvLxc69evl/TZ1/Xs3LlT27dv1/jx45Wbm6u%2BffsagWrGjBnKzMzUwIEDFR0draysLE2bNs14Z%2BDUqVOVmZmpdevWqba2Vvn5%2Bca2rzV3Z0RHR1/9kOO%2B/R52Bp5obXXKe3/RtT9N7228uf9eeuDkpuLN%2B8/N8Pz1dh2%2BLnexTv3qWLNmjctHF7S0tCgnJ0chISEu93Pnc7D%2B1b8GOF9fX%2BXl5SkjI0Opqam66667tHXrVvXu3VuSFBMToy1btmjt2rXKy8tTQkKCtm7daqw/adIknT9/XpmZmWppadHEiRO1ZMkSY3zFihXKysrSrFmzFBoaqkWLFiklJaVTcwMAAHTGNQNWUlJSu2ue4uPjdfHiRV28eNGUIk6ePOlyu2/fvv/2IyHGjBmj3/zmNx2Oz507V3Pnzr3qWFBQkLKzszsMg9eaGwAA4FquGbAIGwAAAO7x1qsGAQAAui0CFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACYjYAEAAJiMgAUAAGAyAhYAAIDJCFgAAAAmI2ABAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWAAAACbrtgHrd7/7nWJjYzVo0CDj30WLFkmSqqurNWfOHMXHx2vy5Mk6ePCgy7qHDh3SlClTFBcXp9mzZ%2BvcuXMu47t27dLYsWOVmJiolStXymazGWN2u10ZGRlKSkrSmDFjlJ%2Bf3/UPFgAA3FS6bcA6ffq0kpOTdfDgQR08eFAHDhzQ2rVrJUnz589XdHS09uzZowcffFDp6emqqamRJH300UdKS0tTamqq9uzZo4iICKWlpRnb3bt3r/Ly8rR69Wq9/PLLOnHihHJycozxDRs2qKKiQgUFBcrMzFRubq7eeeedG/vgAQCAV%2Bu2Aauqqkpf/vKX1bNnT0VGRioyMlK33367Dh8%2BrOrqaq1atUp333235s2bp7i4OBUVFUmSXnvtNQ0bNkyzZ8/WgAEDlJ2drfPnz6u4uFiSVFBQoFmzZmncuHEaOnSosrKyVFRUJJvNpqamJhUVFenpp59WbGysUlJS9MQTT2j37t1WtgIAAHiZbh2w%2Bvfv3255WVmZhgwZosDAQGNZYmKijh8/bownJSUZY0FBQRo8eLBKS0vlcDhUXl6uESNGGONxcXFqaWlRZWWlKisr1dbWpri4OJdtl5WVdcVDBAAAN6luG7A%2B%2BOAD7d%2B/XxMnTtSECRP0k5/8RC0tLaqvr1d0dLTLfSMjI1VbWytJqqurazd%2Bxx13qLa2VpcvX5bNZnMZ9/PzU3h4uGpqalRfX6/w8HD5%2B/u7bNtms%2BnixYtd%2BGgBAMDNxP/ad7nx/v73v6u5uVmBgYHavHmzqqurtXbtWjU3N6upqUkBAQEu9w8ICJDdbpckNTc3dzje3Nxs3L7auMPhuOqYJGP7AAAA19ItA9add96p9957T2FhYZKk2NhYORwOLV26VN/61rd0%2BfJll/vb7XYFBQVJkgIDA9uFIbvdrrCwsA7Dkt1uV3BwsFpbW686JknBwcGdqr2urk719fWdfKS4Ufz9fdSND9heg8PqAjzmzf339c6ybyrevP/cDM9fb9fR63JUVFS7M15m6pYBS5IRrj43YMAA2Ww23XHHHaqqqnIZa2hoUFRUlCSpV69e7RrZ0NCgQYMGKSIiQoGBgWpoaDCu72pra1NjY6OioqLkcDjU2Ngoh8Mh3//7rdrQ0KCgoKB29XSksLBQubm57ZYnpu/o3ANHlwgNDXY59etNWltbrS7BY/QfnmD/gSc6el1OT0/XggULumzebrnHHjhwQE899ZTeffdd42L2iooKRUREaMSIEdq5c6fsdrtxRKqkpMS4cH348OE6duyYsa2mpiZVVFRo4cKF8vHx0bBhw1RSUmJcCF9aWqoePXooNjZWTqdT/v7%2BOn78uBISEiRJR48e1dChQztd%2B/Tp05WcnNxu%2Bdp9H19fM2CKTz5pEn8BW8eb%2B88RLOt58/5zMzx/vV1Hr8ufH5jpKt0yYMXHxys4OFgrV65UWlqa/va3vyknJ0dz585VUlKS%2BvTpo%2BXLl2v%2B/Pnat2%2BfysvLtX79eklSamqqdu7cqe3bt2v8%2BPHKzc1V3759jUA1Y8YMZWZmauDAgYqOjlZWVpamTZtmBLmpU6cqMzNT69atU21trfLz841td0Z0dPTVDznu2%2B95Y3DdWlud8t5fdE6rC/CYN/ffSw%2Bc3FS8ef%2B5GZ6/3q7D1%2BUu1i1/dYSEhOill17SunXr9PDDDyskJESPPPKIvvvd70qStm3bpoyMDKWmpuquu%2B7S1q1b1bt3b0lSTEyMtmzZorVr1yovL08JCQnaunWrse1Jkybp/PnzyszMVEtLiyZOnKglS5YY4ytWrFBWVpZmzZql0NBQLVq0SCkpKTe2AQAAwKt1y4AlfXbN1UsvvXTVsb59%2B6qgoKDDdceMGaPf/OY3HY7PnTtXc%2BfOvepYUFCQsrOzlZ2d7V7BAAAA/8dbT2oDAAB0WwQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkB6yrsdrsyMjKUlJSkMWPGKD8/3%2BqSAACAF/G3uoDuaMOGDaqoqFBBQYGqq6u1bNkyxcTE6P7777e6NAAA4AU4gvUFTU1NKioq0tNPP63Y2FilpKToiSee0O7du60uDQAAeAkC1hdUVlaqra1NcXFxxrLExESVlZVZWBUAAPAmBKwvqK%2BvV3h4uPz9/3n2NDIyUjabTRcvXrSwMgAA4C0IWF/Q1NSkgIAAl2Wf37bb7VaUBAAAvAwXuX9BYGBguyD1%2Be3g4OBrrl9XV6f6%2Bvp2y/tFXnvd7urOLwV6dRLvFxksfy/f0715//H2/vv4eHf/ef5aj/3HOv0igzt8XY6KilJ0dHSXze3lu635evXqpcbGRjkcDvn6frZbNTQ0KCgoSGFhYddcv7CwULm5ue2WJyUl6YWNG7v0P/NmVVdXp8LCQk2fPv2W7d%2B6GSOue13655m6ujr1uXBYP6R/14X9j%2Bevlerq6rR48WIVFxe3G0tPT9eCBQu6bG4C1hcMGjRI/v7%2BOn78uBISEiRJR48e1dChQzu1/vTp05WcnOyyrKqqSkuXLlV9fT1PkOtQX1%2Bv3NxcJScn07/rQP88Q/88Q/88Q/88U19fr%2BLiYuXk5GjAgAEuY1FRUV06NwHrC4KCgjR16lRlZmZq3bp1qq2tVX5%2BvtavX9%2Bp9aOjo3kSAADQjQwYMEBDhgy5oXMSsK5ixYoVysrK0qxZsxQaGqpFixYpJSXF6rIAAICXIGBdRVBQkLKzs5WdnW11KQAAwAt585sDAAAAuiW/H//4xz%2B2uohbQUhIiEaOHKmQkBCrS/FK9M8z9M8z9M8z9M8z9M8zVvXPx%2Bl0Om/ojAAAADc5ThECAACYjIAFAABgMgIWAACAyQhYAAAAJiNgAQAAmIyABQAAYDICFgAAgMkIWDeI3W7XlClTVFxcbHUpXqW2tlYLFy7Uvffeq3Hjxmn9%2BvWy2%2B1Wl%2BU1/va3v%2Bl73/ue4uPjlZycrJdeesnqkrzSvHnztGLFCqvL8Dq/%2B93vFBsbq0GDBhn/Llq0yOqyvIbdbldWVpZGjhypr33ta9q0aZPVJXmNX/3qV%2B32vdjYWA0ePPiG1cB3Ed4Adrtdixcv1unTp60uxessXLhQ4eHheuWVV9TY2KiMjAz5%2Bflp6dKlVpfW7TmdTs2bN0/Dhw/XG2%2B8obNnz2rx4sXq3bu3HnjgAavL8xr/8z//o3fffVff/OY3rS7F65w%2BfVrJyclas2aNPv9M68DAQIur8h5r1qzRkSNHtHPnTl25ckVPPvmkYmJiNG3aNKtL6/YeeOABjR071rjd0tKiWbNmKTk5%2BYbVQMDqYlVVVXrqqaesLsMrnTlzRmVlZTp48KB69uwp6bPA9dxzzxGwOqGhoUGDBw9WZmambrvtNt11110aNWqUSkpKCFiddOnSJeXk5OgrX/mK1aV4paqqKn35y182nr/ovEuXLum///u/tWvXLg0dOlSS9N3vflcnTpwgYHVCQECAIiMjjds///nPJUmLFy%2B%2BYTVwirCLHTlyRKNGjVJhYaH4ViL3REVFaceOHS6/nJ1Opz755BMLq/IeUVFR2rhxo2677TZJUklJiYqLi3XvvfdaXJn32LBhg6ZOnaoBAwZYXYpXqqqqUv/%2B/a0uwyuVlJQoNDRUI0aMMJbNnTtXa9eutbAq73Tp0iXt2LFDS5YsUY8ePW7YvASsLvboo49q2bJlHBa/DqGhoRo9erRx2%2Bl0avfu3frqV79qYVXeKTk5WY8//rji4%2BN1//33W12OVzh8%2BLBKSkqUlpZmdSle64MPPtD%2B/fs1ceJETZgwQT/5yU/U0tJidVle4dy5c4qJidHrr7%2Bub3zjG0pJSVFeXh5/qF%2BHV155Rb169dKECRNu6LwELHiN5557TpWVlXryySetLsXrbNmyRT/72c908uRJ/gLuBLvdrh//%2BMfKzMxUQECA1eV4pb///e9qbm5WYGCgNm/erGXLlunXv/61cnJyrC7NK/zjH//Q2bNn9dprr2n9%2BvVavny5CgoK9PLLL1tdmtcpKirSzJkzb/i8XIMFr5CTk6OCggK98MILnK65DkOGDJEkrVixQkuXLtXy5cvl78/TvyNbtmzR0KFDOVrqgTvvvFPvvfeewsLCJEmxsbFyOBz60Y9%2BpBUrVsjHx8fiCrs3Pz8/ffrpp9q4caN69%2B4tSTp//rxeffVVzZ4929rivEhZWZlqa2s1adKkGz43v2HR7a1evVqFhYXKyclRSkqK1eV4jQsXLqi0tNSlZwMHDlRLS4uuXLmi8PBwC6vr3t5%2B%2B21duHBB8fHxkmSc1tq7d6%2BOHTtmZWle5fNw9bkBAwbIZrOpsbFRERERFlXlHaKjoxUYGGiEK0nq37%2B/ampqLKzK%2Bxw4cEBJSUkKDQ294XNzihDdWm5urgoLC7Vp0yZ94xvfsLocr1JdXa0FCxaorq7OWFZeXq6ePXsSrq5h9%2B7d%2BvWvf60333xTb775ppKTk5WcnKw33njD6tK8xoEDB3TvvffKZrMZyyoqKhQeHk646oThw4fLZrPpww8/NJZVVVUpJibGwqq8T1lZmRISEiyZm4CFbquqqkrbtm3TvHnzFB8fr4aGBuMH1zZs2DANHTpUGRkZqqqq0p/%2B9Cc9//zz%2BsEPfmB1ad1enz591LdvX%2BMnJCREISEh6tu3r9WleY34%2BHgFBwdr5cqV%2BuCDD/SnP/1JOTk5mjt3rtWleYX%2B/ftr3LhxWr58uSorK7V//35t375dM2bMsLo0r3Lq1CnLLivhFOENxDUH7vn9738vh8Ohbdu2adu2bZI%2Beyehj4%2BPTp48aXF13Z%2Bvr6/y8vK0evVqPfLIIwoODtZ3vvMdPf7441aXhltASEiIXnrpJa1bt04PP/ywQkJC9Mgjj%2Bi73/2u1aV5jeeff15r1qzRY489puDgYM2cOVOPPfaY1WV5lY8//lhf%2BtKXLJnbx8l7PgEAAEzFKUIAAACTEbAAAABMRsACAAAwGQELAADAZAQsAAAAkxGwAAAATEbAAgAAMBkBCwAAwGQELAAAAJMRsAAAAExGwAIAADAZAQsAAMBkBCwAAACT/X%2BlhgWjS14I5wAAAABJRU5ErkJggg%3D%3D">
             </div>
      </div>
    </div><div class="row variablerow ignore">
        <div class="col-md-3 namecol">
            <p class="h4"><s>Distinct_Items</s><br/><small>Highly correlated</small></p>
        </div>

         <div class="col-md-3">
            <p> <em>This variable is highly correlated with <code>Clicks</code> and should be ignored for analysis</em></p>

        </div>
        <div class="col-md-6">
            <table class="stats ">
                <tr><th>Correlation</th>
                <td>0.91423</td></tr>
            </table>
        </div>
    </div><div class="row variablerow">
        <div class="col-md-3 namecol">
            <p class="h4">Index<br/><small>Numeric</small></p>
        </div>

        <div class="col-md-6">
            <div class="row">
                <div class="col-sm-6">
                    <table class="stats ">
                        <tr><th>Distinct count</th>
                        <td>1100987</td></tr>
                        <tr><th>Unique (%)</th>
                        <td>100.0%</td></tr>
                        <tr class="ignore"><th>Missing (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (n)</th>
                        <td>0</td></tr>
                    </table>

                </div>
                <div class="col-sm-6">
                    <table class="stats ">

                        <tr><th>Mean</th>
                        <td>550490</td></tr>
                        <tr><th>Minimum</th>
                        <td>0</td></tr>
                        <tr><th>Maximum</th>
                        <td>1100986</td></tr>
                        <tr class="ignore"><th>Zeros (%)</th>
                        <td>0.0%</td></tr>
                    </table>
                </div>
            </div>
        </div>
        <div class="col-md-3 collapse in" id="minihistogram-880658303">
             <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAABUtJREFUeJzt209IlHkcx/HP00iL2bKCzjxjhMTCFoIHWQQHZXFCIcYUY1h3jpoeohK8eNND7JIg9Idg6tStkyILdUgiai65GQXBHlchdSmfeUZt1yZSR%2Be7l20gHL/NHPo9O%2B7ndXN6fvN9hO87HZmxRERgmOu6mJiYQCwWQyAQMD2eSoyX%2B2J5EQhRqTjg9Q0Q/ZeVeTV4e3u76DMiAsuyiroewBc9Y2LGfjzj8/mKut4rngXyy6%2B/48%2B1DwVfH/2%2BBr/Nr2FhtfAzoW8r4fy9%2BUXPmJix384cqyrHzz81oKzMs/UrmGd3OJd8jz%2Bc9wVf/8N3VVhY/VDUmdqqcix94TMmZuzHM6WCr0GIFAyESMFAiBQMhEjBQIgUDIRIwUCIFAyESMFAiBQMhEjBQIgUDIRIwUCIFAyESMFAiBQMhEjBQIgUDIRIwUCIFAyESMFAiBQMhEjBQIgUDIRIwUCIFAyESMFAiBQMhEjBQIgUDIRIwUCIFAyESMFAiBQMhEjBQIgUDIRIwUCIFAyESMFAiBQMhEjBQIgUDIRIUebV4B8bj%2BCvD5mCr68/8jXmkumiZhz55qui/wco9oyJGfvtzLGq8iIneMcSETE91HVdTExMIBaLIRAImB5PJcbLffHkV6xUKoV4PI5UKuXFeCoxXu4LX4MQKRgIkYKBECkYCJHCk0D8fj8GBwfh9/u9GE8lxst98eTPvESlgr9iESkYCJGCgRApGAiRgoEQKRgIkYKBECmMBzI9PY3Ozk6cOnUKN2/eND2eDEmn0%2Bjq6sKbN28AADMzM4hGozhz5gzOnj2L5eXl3HUXLlzA6dOn0dPTg8XFxdxzXLt2DZFIBJFIBIlEIvf4Xjs0NzeHWCyGjo4ODA0NYWNjI%2B%2BMpaWlwr8RMSiVSsnJkyfl7du3sr29LX19ffLkyROTt0AGvHz5Ujo7O6W%2Bvl5ev34tW1tb0tLSIouLiyIiMjk5KefPnxcRkcuXL0s8HhcRkadPn0osFhMRkYcPH0p/f79ks1lxXVfa2tpkfX1d3aHu7m55/vy5iIjcuHFDrl69qs4ohNGfIDMzMwiFQqisrITP50N3dzfu379v8hbIgMnJSVy6dCn34aatrS2MjIygtrYWAFBXVwfHcQAAiUQC0WgUABAKhbC6ugrHcZBIJNDV1QXLsuD3%2B9HU1ITHjx/vuUOO4yCdTqOxsREA0NPTg%2BnpaXVGIYx%2B5DaZTMK27dzXtm0XfKNUOsbGxgAA8u%2B7mCoqKhCJRAAA2WwW8Xgc7e3tAHbvRCAQwPLy8q7H/X4/kskkAOTdoXzP83G38j2X4zgIBoOf/V6M/gSRPG/7OnCAfyf4v9jc3MTQ0BBEBOfOnQOweydEBD6fL%2B%2BuWJa15w5ls9m8jwNQ/%2B1zjG6nbdtwXTf3teu6BVVMpW99fR29vb04dOgQbt26BZ/PBwAIBoOffJQ2lUrBtm3Ytr3r8WAwuOcOBYPBTx7/eL02oxBGA2lubsbs7CzW1taQyWRw7949tLa2mrwF8sjFixfR0NCA8fHxXBwA0NraiqmpKQDAs2fPUFFRAdu2EQ6HcffuXezs7GBlZQWzs7Nobm7Ou0PhcBg1NTUoLy/HixcvAABTU1O53QqHw3lnFML4290fPHiAeDyOTCaD9vZ2DA8PmxxPBrW1teHOnTtYWFjAwMAAjh8/DsuyAADV1dW4ffs23r17h5GREbx69QoHDx7E2NgYTpw4AQC4fv06Hj16hGw2i8HBQXR0dADYe4fm5%2BcxOjqKdDqNo0eP4sqVKzh8%2BLA643P4eRAiBV8hEykYCJHiHw2%2BLjDZl87GAAAAAElFTkSuQmCC">

        </div>
       <div class="col-md-12 text-right">
            <a role="button" data-toggle="collapse" data-target="#descriptives-880658303,#minihistogram-880658303" aria-expanded="false" aria-controls="collapseExample">
                Toggle details
            </a>
        </div>
        <div class="row collapse col-md-12" id="descriptives-880658303">
            <div class="col-sm-4">
                  <p class="h4">Quantile statistics</p>
                  <table class="stats indent">
                        <tr><th>Minimum</th>
                        <td>0</td></tr>
                        <tr><th>5-th percentile</th>
                        <td>55049</td></tr>
                        <tr><th>Q1</th>
                        <td>275250</td></tr>
                        <tr><th>Median</th>
                        <td>550490</td></tr>
                        <tr><th>Q3</th>
                        <td>825740</td></tr>
                        <tr><th>95-th percentile</th>
                        <td>1045900</td></tr>
                        <tr><th>Maximum</th>
                        <td>1100986</td></tr>
                        <tr><th>Range</th>
                        <td>1100986</td></tr>
                        <tr><th>Interquartile range</th>
                        <td>550490</td></tr>
                  </table>
                  <p class="h4">Descriptive statistics</p>
                  <table class="stats indent">
                        <tr><th>Standard deviation</th>
                        <td>317830</td></tr>
                        <tr><th>Coef of variation</th>
                        <td>0.57735</td></tr>
                        <tr><th>Kurtosis</th>
                        <td>-1.2</td></tr>
                        <tr><th>Mean</th>
                        <td>550490</td></tr>
                        <tr><th>MAD</th>
                        <td>275250</td></tr>
                        <tr class=""><th>Skewness</th>
                        <td>0</td></tr>
                        <tr><th>Sum</th>
                        <td>606085636591</td></tr>
                        <tr><th>Variance</th>
                        <td>1.0101e+11</td></tr>
                        <tr><th>Memory size</th>
                        <td>8.4 MiB</td></tr>
                 </table>
            </div>
             <div class="col-sm-8 histogram">
                 <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAIABJREFUeJzt3X9c1fX9//87gvxYySDjqDmappd3qBgHkJZL8K3jnctUtnFRV62ppawEdWu2/JUMf6HRpdpbwJm%2BQ8PLGg7eWz/WO/vhevd%2Bp31SBKEhK20zYQKHJmoF5wDn9f2jb6/3jkBAvJBz7Ha9XLpcdp6P14/H65Hu3HudFwc/wzAMAQAAwDKDBroBAACAKw0BCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsNuABy%2BVyafbs2Tpy5Ii5Vl5erh/%2B8IeKjY3V7bffrt/97nce%2Bxw6dEizZ8%2BW3W7XwoULdebMGY/6nj17lJSUpPj4eK1du1ZOp9PjfGvWrFFCQoISExNVUFDgsW9NTY0WLVqk2NhYzZo1S2%2B99VY/XDUAALiSDWjAcrlcevDBB3Xy5ElzrbGxUWlpabrlllv03HPPadmyZdq0aZP%2B%2B7//W5L097//Xenp6UpNTVVJSYnCw8OVnp5u7n/gwAHl5%2Bdr48aN2rt3r44fP66cnByzvm3bNlVVVamwsFCZmZnKzc3VK6%2B8YtbT09Nls9lUUlKiOXPmKCMjQ3V1dX26zoaGBm3fvl0NDQ19Os5XFfPrG%2BbXN8yvb5hf3zC/vhnQ%2BRkD5OTJk0ZKSoqRkpJiREVFGe%2B8845hGIbx7LPPGjNnzvTY9pFHHjFWrlxpGIZhPPnkk8Y999xj1pqbm424uDhz/7vvvtvIzc0160ePHjViYmKMlpYW49NPPzVuuukm48iRI2Y9Pz/fPN6hQ4eM2NhYo6WlxawvXLjQ2L59e5%2Bu9d133zX%2B5V/%2BxXj33Xf7dJyvKubXN8yvb5hf3zC/vmF%2BfTOQ8xuwO1jvvPOOJk%2BerKKiIhmGYa4nJSUpOzu7w/YXL16UJFVUVCghIcFcDw4O1vjx41VWVia3263KykpNmjTJrNvtdrW2tqq6ulrV1dVqb2%2BX3W436/Hx8aqoqDCPPWHCBAUFBXnUy8vLrbtwAABwxQsYqBPfeeedna5fd911uu6668zXH330kV566SUtX75c0me3%2B2w2m8c%2B1157rerr63XhwgU5nU6Pur%2B/v8LCwlRXVyc/Pz%2BFhYUpIOD/Lnvo0KFyOp06d%2B6cHA5Hh2MPHTpU9fX1fb5eAADw1TFgAasnnE6nli1bJpvNpvnz50uSWlpaFBgY6LFdYGCgXC6XWlpazNed1d1ud6c16bPnwZqbm7vcFwAAoKe8NmB9%2BumneuCBB/Thhx/q2WefNT%2B2CwoK6hB4XC6XQkNDPcLSpfWQkBC1tbV1WpOkkJAQBQUF6fz58x3qwcHBPe67oaFBDofDY%2B3UqVM93h8AAFirs/fhiIiIDp9aWckrA9bHH3%2BsxYsXq6amRnv37lVkZKRZGzZsWIcA09jYqHHjxik8PFxBQUFqbGzU6NGjJUnt7e1qampSRESE3G63mpqa5Ha7NWjQIHPf4OBghYaGatiwYR4/0fh5PSIiose9FxUVKTc3t8N6enq6JkyY0OPj4P9MmDBBf/nLXwa6DZ/F/PqG%2BfUN8%2Bsb5tc3EyZMUEJCgh566KEOtYyMDC1btqzfzu11AcswDGVkZKi2tlb79u3TqFGjPOoxMTE6duyY%2Bbq5uVlVVVVavny5/Pz8NHHiRJWWlpoPwpeVlWnw4MGKioqSYRgKCAhQeXm54uLiJElHjx5VdHS0eexdu3bJ5XKZd8NKS0s9Hprvzvz58zV9%2BvQO6xEREbpwoVnt7e5ezQOSv/8ghYaGML8vifn1DfPrG%2BbXN8yvb/z9B%2Bnxxx/vcGNGUq9unnwZXhewfve73%2Bmdd97Rjh07dPXVV6uxsVGSNHjwYH39619Xamqqnn76ae3atUvTpk1Tbm6uIiMjzUB11113KTMzU2PHjpXNZlNWVpbmzZtnfsSYkpKizMxMbdmyRfX19SooKNDWrVslSTfffLNGjBihVatWaenSpTp48KAqKyvNek/YbLYubzmeO/eJ2tr4C/Jltbe7mV8fML%2B%2BYX59w/z6hvl9eV/0vtyfvCJg%2Bfn5yc/PT5L0yiuvyDAM3X///R7bJCQk6JlnntHIkSO1fft2bd68Wfn5%2BYqLi1NeXp653cyZM1VbW6vMzEy1trZqxowZWrlypVlfvXq1srKytGDBAg0ZMkQrVqxQcnKyJGnQoEHKz8/XmjVrlJqaquuvv155eXkaPnz4ZZgCAAC4UvgZ//wlVOhX3MH6cgICBik8/Crm9yUxv75hfn3D/PqG%2BfXN5/MbCAP%2BuwgBAACuNAQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALBYwEA3AG9kDHQDl3Crra1Nklud9/b5mt/la6lPLne/3c2vO1/1%2BfZ1ft250ufb3/Prjq/Pd6Dn11O%2BMt/Lh4B1mRwoO62Pm1tluAe6k%2B4NvXqwXq1y6G8fNQ90Kz1yyw1hqjvvpN9%2BQr/9i377F/32r1FDQ/Szf/uXgW7DKxGwLpO9//uh3qv7ZKDb6JGpN16js%2BedPtPv9UND9OFHzfTbT%2Bi3f9Fv/6JfDBSewQIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgMesFwul2bPnq0jR46YazU1NVq0aJFiY2M1a9YsvfXWWx77HDp0SLNnz5bdbtfChQt15swZj/qePXuUlJSk%2BPh4rV27Vk6n0%2BN8a9asUUJCghITE1VQUOCxb3fnBgAA6M6ABiyXy6UHH3xQJ0%2Be9FhPT0%2BXzWZTSUmJ5syZo4yMDNXV1UmSzp49q/T0dKWmpqqkpETh4eFKT0839z1w4IDy8/O1ceNG7d27V8ePH1dOTo5Z37Ztm6qqqlRYWKjMzEzl5ubqlVde6dG5AQAAemLAAtapU6c0b9481dTUeKwfPnxYZ86c0YYNG3TDDTcoLS1NdrtdxcXFkqT9%2B/dr4sSJWrhwocaMGaPs7GzV1taad8AKCwu1YMECTZ06VdHR0crKylJxcbGcTqeam5tVXFysdevWKSoqSsnJyVq8eLH27dvXo3MDAAD0xIAFrHfeeUeTJ09WUVGRDMMw1ysqKjRhwgQFBQWZa/Hx8SovLzfrCQkJZi04OFjjx49XWVmZ3G63KisrNWnSJLNut9vV2tqq6upqVVdXq729XXa73ePYFRUVPTo3AABATwQM1InvvPPOTtcdDodsNpvH2tChQ1VfXy9Jamho6FC/9tprVV9frwsXLsjpdHrU/f39FRYWprq6Ovn5%2BSksLEwBAQEex3Y6nTp37ly35wYAAOiJAQtYXWlublZgYKDHWmBgoFwulySppaWly3pLS4v5urO62%2B3utCZ99jxYd%2BcGAADoCa8LWEFBQTp//rzHmsvlUnBwsFm/NPC4XC6FhoZ6hKVL6yEhIWpra%2Bu0JkkhISHdnrsnGhoa5HA4erw9AAC%2BLCDAT17wpQSd8vcf1OX7ckRERIdPrazkdQFr2LBhHX6qsLGxUREREWb90kE1NjZq3LhxCg8PV1BQkBobGzV69GhJUnt7u5qamhQRESG3262mpia53W4NGjTI3Dc4OFihoaHdnrsnioqKlJub22E9PmN3j48BAICvGDIkxOPRG2%2Bzd%2B/uTt%2BXMzIytGzZsn47r9dNJCYmRrt27ZLL5TLvSJWWlpoPrsfExOjYsWPm9s3NzaqqqtLy5cvl5%2BeniRMnqrS01HwQvqysTIMHD1ZUVJQMw1BAQIDKy8sVFxcnSTp69Kiio6N7dO6emD9/vqZPn95hffPBf3yJaQAA4N0uXmyWN9/B6up9uTc3T74MrwtYN998s0aMGKFVq1Zp6dKlOnjwoCorK7V161ZJUmpqqp5%2B%2Bmnt2rVL06ZNU25uriIjI81AdddddykzM1Njx46VzWZTVlaW5s2bZ/5kYEpKijIzM7VlyxbV19eroKDAPHZ35%2B4Jm83W%2BS3Hg//Tx8kAAOB92toMSe6BbqNLXb4v9zOviJx%2Bfn7m/x40aJDy8/PlcDiUmpqqF154QXl5eRo%2BfLgkaeTIkdq%2BfbtKSko0d%2B5cXbx4UXl5eeb%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%2BXt/5zne0d%2B9es1ZTU6NFixYpNjZWs2bN0ltvveWx76FDhzR79mzZ7XYtXLhQZ86c8ajv2bNHSUlJio%2BP19q1a%2BV0Os2ay%2BXSmjVrlJCQoMTERBUUFPTvhQIAgCuSVwasFStW6KqrrtLvf/97rVmzRk8%2B%2BaRee%2B01SdLSpUtls9lUUlKiOXPmKCMjQ3V1dZKks2fPKj09XampqSopKVF4eLjS09PN4x44cED5%2BfnauHGj9u7dq%2BPHjysnJ8esb9u2TVVVVSosLFRmZqZyc3P1yiuvXN6LBwAAPs/rAtaFCxd0/PhxPfDAA7r%2B%2Buv1ne98R4mJiXr77bf19ttvq6amRhs2bNANN9ygtLQ02e12FRcXS5L279%2BviRMnauHChRozZoyys7NVW1urI0eOSJIKCwu1YMECTZ06VdHR0crKylJxcbGcTqeam5tVXFysdevWKSoqSsnJyVq8eLH27ds3kOMAAAA%2ByOsCVnBwsEJCQlRSUqK2tjZ98MEHOnbsmMaNG6fjx49rwoQJCgoKMrePj49XeXm5JKmiokIJCQkexxo/frzKysrkdrtVWVmpSZMmmXW73a7W1lZVV1erurpa7e3tstvtHseuqKi4DFcNAACuJF4XsAIDA7V%2B/Xr99re/VUxMjGbOnKmkpCSlpqbK4XDIZrN5bD906FDV19dLkhoaGjrUr732WtXX1%2BvChQtyOp0edX9/f4WFhamurk4Oh0NhYWEKCAjwOLbT6dS5c%2Bf68YoBAMCVJqD7TS6/U6dOafr06brvvvv03nvvaePGjZo8ebKam5sVGBjosW1gYKBcLpckqaWlpct6S0uL%2Bbqzutvt7rQmyTw%2BAABAT3hdwDp8%2BLCKi4v15ptvKjAwUOPHj1ddXZ127NihyZMnq6mpyWN7l8ul4OBgSVJQUFCHMORyuRQaGtplWHK5XAoJCVFbW1unNUkKCQnpcf8NDQ1yOBw93h4AAF8WEOAnL/xATJLk7z%2Boy/fliIiIDp96WcnrAtaf//xnjRo1yuNu0rhx47Rz504NGzZM77//vsf2jY2NioiIkCQNGzaswxAbGxs1btw4hYeHKygoSI2NjRo9erQkqb29XU1NTYqIiJDb7VZTU5PcbrcGDRpk7hscHKzQ0NAe919UVKTc3NwO6/EZu3t8DAAAfMWQISEej9d4m717d3f6vpyRkaFly5b123m9biI2m02nT59WW1ub%2BS/sgw8%2B0De%2B8Q3FxMRo586dcrlcZgArLS01H1yPiYnRsWPHzGM1NzerqqpKy5cvl5%2BfnyZOnKjS0lLzQfiysjINHjxYUVFRMgxDAQEBKi8vV1xcnCTp6NGjio6O7lX/8%2BfP1/Tp0zusbz74j94PAwAAL3fxYrO8%2BQ5WV%2B/Ln9%2Bc6S9eF7CmT5%2BunJwcrVu3Tvfff78%2B%2BOAD7dy5Uz//%2Bc%2BVkJCgESNGaNWqVVq6dKkOHjyoyspKbd26VZKUmpqqp59%2BWrt27dK0adOUm5uryMhIM1DdddddyszM1NixY2Wz2ZSVlaV58%2BaZP5WYkpKizMxMbdmyRfX19SooKDCP3VM2m63zW44H/6dvgwEAwAu1tRmS3APdRpe6fF/uZ14XsK6%2B%2Bmrt2bNHW7Zs0dy5c3XNNdcoPT1dc%2BfOlSTt2LFDa9asUWpqqq6//nrl5eVp%2BPDhkqSRI0dq%2B/bt2rx5s/Lz8xUXF6e8vDzz2DNnzlRtba0yMzPV2tqqGTNmaOXKlWZ99erVysrK0oIFCzRkyBCtWLFCycnJl3cAAADA53ldwJKkMWPG6D/%2B4z86rUVGRqqwsLDLfRMTE/Xyyy93WV%2ByZImWLFnSaS04OFjZ2dnKzs7uXcMAAAD/xDs/NAUAAPBhBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAs1quANXfuXP32t7/VxYsX%2B6sfAAAAn9ergHXLLbfo17/%2BtaZMmaIHH3xQ//u//yvDMPqrNwAAAJ/Uq4D185//XH/605%2BUn58vf39/LVu2TP/6r/%2BqJ554Qn/961/7q0cAAACfEtDbHfz8/HTrrbfq1ltvVXNzswoLC5Wfn6%2BnnnpKcXFxWrBggW677bb%2B6BUAAMAn9DpgSVJDQ4Oef/55Pf/883rvvfcUFxen73//%2B6qrq9O6det05MgRrV271upeAQAAfEKvAtZzzz2n5557Tv/v//0/XXPNNfre976nf//3f9eoUaPMbUaMGKHNmzcTsAAAwFdWrwLW2rVrNW3aNOXl5SkpKUmDBnV8hOuGG27Qj370I8saBAAA8DW9ClhvvvmmwsPD1dTUZIariooKTZgwQf7%2B/pKkuLg4xcXFWd8pAACAj%2BjVTxF%2B/PHH%2Bu53v6tdu3aZa2lpaUpJSdHZs2ctbw4AAMAX9SpgbdmyRd/85je1aNEic%2B2ll17SiBEjlJ2dbXlzAAAAvqhXAevo0aNatWqVIiIizLVrrrlGv/jFL/T2229b3hwAAIAv6lXACggI0IULFzqsNzc3843uAAAA/79eBaykpCRt2rRJH374obl25swZZWdnKzEx0fLmAAAAfFGvforw4Ycf1qJFizRjxgyFhoZKki5cuKAJEyZo9erV/dIgAACAr%2BlVwBo6dKh%2B//vf69ChQ3r//fcVEBCgsWPHavLkyfLz8%2BuvHgEAAHxKr39Vjr%2B/vxITE/lIEAAAoAu9ClgOh0NPPvmkjh07ptbW1g4Ptr/%2B%2BuuWNgcAAOCLehWwHnnkEb377ru64447NGTIkP7qCQAAwKf1KmC9/fbb2r17tyZNmtRf/QAAAPi8Xn1Nw9e%2B9jUNHTq0v3oBAAC4IvQqYKWkpGj37t1qb2/vr34AAAB8Xq8%2BImxqatKLL76oN954Q5GRkQoMDPSoP/PMM5Y2BwAA4It6/TUNs2bN6o8%2BAAAArhi9CljZ2dn91QcAAMAVo1fPYElSQ0ODcnNz9fOf/1wfffSRXn75ZX3wwQf90RsAAIBP6lXAOn36tGbPnq3f//73OnDggD799FO99NJLSk1N1fHjx/urRwAAAJ/Sq4C1detWJScn67XXXtPgwYMlSY8//rimT5%2Buxx57zLKmXC6XsrKydPPNN2vKlCl64oknzFpNTY0WLVqk2NhYzZo1S2%2B99ZbHvocOHdLs2bNlt9u1cOFCnTlzxqO%2BZ88eJSUlKT4%2BXmvXrpXT6fQ475o1a5SQkKDExEQVFBRYdk0AAOCro1cB69ixY1q0aJHHL3YOCAjQ0qVLVVVVZVlTmzZt0uHDh/X000/rscce0/79%2B7V//35J0tKlS2Wz2VRSUqI5c%2BYoIyNDdXV1kqSzZ88qPT1dqampKikpUXh4uNLT083jHjhwQPn5%2Bdq4caP27t2r48ePKycnx6xv27ZNVVVVKiwsVGZmpnJzc/XKK69Ydl0AAOCroVcBy%2B12y%2B12d1j/5JNP5O/vb0lD58%2Bf13/%2B539q06ZNio6O1i233KJ7771Xx48f19tvv62amhpt2LBBN9xwg9LS0mS321VcXCxJ2r9/vyZOnKiFCxdqzJgxys7OVm1trY4cOSJJKiws1IIFCzR16lRFR0crKytLxcXFcjqdam5uVnFxsdatW6eoqCglJydr8eLF2rdvnyXXBQAAvjp6FbCmTJminTt3eoSspqYm5eTk6JZbbrGkodLSUg0ZMsTj1/EsWbJEmzdv1vHjxzVhwgQFBQWZtfj4eJWXl0uSKioqlJCQYNaCg4M1fvx4lZWVye12q7Ky0uO4drtdra2tqq6uVnV1tdrb22W32z2OXVFRYcl1AQCAr45eBaxVq1bp3Xff1ZQpU%2BR0OvXAAw9o2rRpqqmp0cMPP2xJQ2fOnNHIkSP1hz/8QbfffruSk5OVn58vwzDkcDhks9k8th86dKjq6%2BslffYTjpfWr732WtXX1%2BvChQtyOp0edX9/f4WFhamurk4Oh0NhYWEKCAjwOLbT6dS5c%2BcsuTYAAPDV0KvvwRo2bJj%2B8Ic/6MUXX9SJEyfkdrt15513KiUlRVdffbUlDX366af629/%2Bpv3792vr1q1yOBxav369QkJC1Nzc3OHb4wMDA%2BVyuSRJLS0tXdZbWlrM153V3W53pzVJ5vEBAAB6otff5B4SEqK5c%2Bf2Ry%2BSPrur9Mknn%2Bjxxx/X8OHDJUm1tbX6zW9%2BoylTpqipqclje5fLpeDgYElSUFBQhzDkcrkUGhraZVhyuVwKCQlRW1tbpzXps2vuqYaGBjkcjh5vDwCALwsI8NOX%2BFrNy8Lff1CX78sREREdPvWyUq8C1o9//OMvrFvxuwhtNpuCgoLMcCVJo0ePVn19vYYNG6b333/fY/vGxkZFRERI%2BuwO26VDbGxs1Lhx4xQeHq6goCA1NjZq9OjRkqT29nY1NTUpIiJCbrdbTU1NcrvdGjRokLlvcHCwQkNDe9x/UVGRcnNzO6zHZ%2Bzu8TEAAPAVQ4aEeDxe42327t3d6ftyRkaGli1b1m/n7dVERo4c6fG6ra1Np0%2Bf1nvvvacFCxZY0lBMTIycTqdOnz6tb37zm5KkU6dOaeTIkYqJidHOnTvlcrnMO1KlpaXmg%2BsxMTE6duyYeazm5mZVVVVp%2BfLl8vPz08SJE1VaWmo%2BCF9WVqbBgwcrKipKhmEoICBA5eXliouLkyQdPXpU0dHRvep//vz5mj59eof1zQf/0fthAADg5S5ebJY338Hq6n3585sz/cWS30WYl5dnfhdVX40ePVpTp07VqlWrlJmZKYfDoV27dik9PV0JCQkaMWKEVq1apaVLl%2BrgwYOqrKzU1q1bJUmpqal6%2BumntWvXLk2bNk25ubmKjIw0A9Vdd92lzMxMjR07VjabTVlZWZo3b575U4kpKSnKzMzUli1bVF9fr4KCAvPYPWWz2Tq/5Xjwf/o2GAAAvFBbmyGp41c4eYsu35f7mSWRMyUlRf/1X/9lxaEkSY899pi%2B%2Bc1v6u6779bq1at1zz336O6779agQYO0Y8cOORwOpaam6oUXXlBeXp75ceLIkSO1fft2lZSUaO7cubp48aLy8vLM486cOVNpaWnKzMzU4sWLZbfbtXLlSrO%2BevVqRUdHa8GCBdq4caNWrFih5ORky64LAAB8NVjyoWlZWZllXzQqSVdffbW2bt3a6d2jyMhIFRYWdrlvYmKiXn755S7rS5Ys0ZIlSzqtBQcHKzs7u8s7dQAAAD3R54fcP/74Y/3lL3/RXXfdZVlTAAAAvqxXAeu6667z%2BD2EkjR48GD96Ec/0pw5cyxtDAAAwFf1KmD19oFvAACAr6JeBazPf2lyT/zz7wQEAAD4KulVwLrnnnvMjwgNwzDXL13z8/PTiRMnrOoRAADAp/QqYP3617/Wpk2b9NBDD%2Bnmm29WYGCgKisrtWHDBn3/%2B9/XzJkz%2B6tPAAAAn9Gr78HKzs7W%2BvXrNWPGDIWHh%2Buqq67SLbfcog0bNujZZ5/VyJEjzX8AAAC%2BqnoVsBoaGjoNT1dffbXOnTtnWVMAAAC%2BrFcBy2636/HHH9fHH39srjU1NSknJ0eTJ0%2B2vDkAAABf1KtnsNatW6cf//jHSkpK0qhRo2QYhv72t78pIiJCzzzzTH/1CAAA4FN6FbDGjBmjl156SS%2B%2B%2BKJOnTolSbr77rt1xx13KCQkpF8aBAAA8DW9/l2EX//61zV37lzV1NQoMjJS0mff5g4AAIDP9OoZLMMw9NhjjykhIUGzZs1SXV2dHn74Ya1du1atra391SMAAIBP6VXAKiws1HPPPafMzEwFBgZKkpKTk/Xaa68pNze3XxoEAADwNb0KWEVFRVq/fr1%2B8IMfmN/ePnPmTG3atEkvvPBCvzQIAADga3oVsGpqajRu3LgO61FRUXI4HJY1BQAA4Mt6FbBGjhypysrKDutvvvmm%2BcA7AADAV12vforwvvvuU1ZWlhwOhwzD0OHDh1VUVKTCwkKtWrWqv3r/p8nVAAAaO0lEQVQEAADwKb0KWKmpqWpra9OOHTvU0tKi9evX65prrtFPf/pT3Xnnnf3VIwAAgE/pVcB68cUX9d3vflfz58/XP/7xDxmGoaFDh/ZXbwAAAD6pV89gbdiwwXyY/ZprriFcAQAAdKJXAWvUqFF67733%2BqsXAACAK0KvPiKMiorSypUrtXv3bo0aNUpBQUEe9ezsbEubAwAA8EW9Clh//etfFR8fL0l87xUAAEAXug1Yjz76qDIyMvS1r31NhYWFl6MnAAAAn9btM1gFBQVqbm72WEtLS1NDQ0O/NQUAAODLug1YhmF0WDty5IicTme/NAQAAODrevVThAAAAOgeAQsAAMBiPQpYfn5%2B/d0HAADAFaNHX9OwadMmj%2B%2B8am1tVU5Ojq666iqP7fgeLAAAgB4ErISEhA7feRUbG6tz587p3Llz/dYYAACAr%2Bo2YPHdVwAAAL3DQ%2B4AAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMW8PmClpaVp9erV5uuamhotWrRIsbGxmjVrlt566y2P7Q8dOqTZs2fLbrdr4cKFOnPmjEd9z549SkpKUnx8vNauXSun02nWXC6X1qxZo4SEBCUmJqqgoKB/Lw4AAFyRvDpg/fGPf9Sbb77psZaeni6bzaaSkhLNmTNHGRkZqqurkySdPXtW6enpSk1NVUlJicLDw5Wenm7ue%2BDAAeXn52vjxo3au3evjh8/rpycHLO%2Bbds2VVVVqbCwUJmZmcrNzdUrr7xyeS4WAABcMbw2YJ0/f145OTm66aabzLXDhw/rzJkz2rBhg2644QalpaXJbreruLhYkrR//35NnDhRCxcu1JgxY5Sdna3a2lodOXJE0me/9mfBggWaOnWqoqOjlZWVpeLiYjmdTjU3N6u4uFjr1q1TVFSUkpOTtXjxYu3bt29Arh8AAPgurw1Y27ZtU0pKisaMGWOuVVRUaMKECQoKCjLX4uPjVV5ebtYTEhLMWnBwsMaPH6%2BysjK53W5VVlZq0qRJZt1ut6u1tVXV1dWqrq5We3u77Ha7x7ErKir68zIBAMAVyCsD1uHDh1VaWurx8Z4kORwO2Ww2j7WhQ4eqvr5ektTQ0NChfu2116q%2Bvl4XLlyQ0%2Bn0qPv7%2ByssLEx1dXVyOBwKCwtTQECAx7GdTqfOnTtn9SUCAIArWED3m1xeLpdLv/zlL5WZmanAwECPWnNzc4e1wMBAuVwuSVJLS0uX9ZaWFvN1Z3W3291p7fOeAAAAesrrAtb27dsVHR2tb3/72x1qQUFBOn/%2BvMeay%2BVScHCwWb80DLlcLoWGhnYZllwul0JCQtTW1tZpTZJCQkJ63H9DQ4McDkePtwcAwJcFBPjJSz8Qk7//oC7flyMiIjp86mUlrwtYL730kj766CPFxsZKklpbWyV99hOA999/v06ePOmxfWNjoyIiIiRJw4YN6zDExsZGjRs3TuHh4QoKClJjY6NGjx4tSWpvb1dTU5MiIiLkdrvV1NQkt9utQYMGmfsGBwcrNDS0x/0XFRUpNze3w3p8xu4eHwMAAF8xZEiIx%2BM13mbv3t2dvi9nZGRo2bJl/XZer5vIvn371NbWZr7%2B/GsUHnroIdXW1uqpp56Sy%2BUy70iVlpaaD67HxMTo2LFj5r7Nzc2qqqrS8uXL5efnp4kTJ6q0tNR8EL6srEyDBw9WVFSUDMNQQECAysvLFRcXJ0k6evSooqOje9X//PnzNX369A7rmw/%2Bo1fHAQDAF1y82CxvvoPV1fvy5zdn%2BovXBawRI0Z4vL7qqqskSZGRkRo5cqRGjBihVatWaenSpTp48KAqKyu1detWSVJqaqqefvpp7dq1S9OmTVNubq4iIyPNQHXXXXcpMzNTY8eOlc1mU1ZWlubNm2f%2BVGJKSooyMzO1ZcsW1dfXq6CgwDx2T9lsts5vOR78n96OAgAAr9fWZkhyD3QbXeryfbmfeV3A%2BiKDBg1Sfn6%2B1qxZo9TUVF1//fXKy8vT8OHDJUkjR47U9u3btXnzZuXn5ysuLk55eXnm/jNnzlRtba0yMzPV2tqqGTNmaOXKlWZ99erVysrK0oIFCzRkyBCtWLFCycnJl/06AQCAb/P6gJWdne3xOjIyUoWFhV1un5iYqJdffrnL%2BpIlS7RkyZJOa8HBwcrOzu5wTgAAgN7wzg9NAQAAfBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiXhmw6uvrtXz5cn3rW9/S1KlTtXXrVrlcLklSTU2NFi1apNjYWM2aNUtvvfWWx76HDh3S7NmzZbfbtXDhQp05c8ajvmfPHiUlJSk%2BPl5r166V0%2Bk0ay6XS2vWrFFCQoISExNVUFDQ/xcLAACuOF4ZsJYvXy6n06nf/OY3evzxx/WnP/1Jv/rVryRJS5culc1mU0lJiebMmaOMjAzV1dVJks6ePav09HSlpqaqpKRE4eHhSk9PN4974MAB5efna%2BPGjdq7d6%2BOHz%2BunJwcs75t2zZVVVWpsLBQmZmZys3N1SuvvHJ5Lx4AAPg8rwtYH3zwgSoqKpSdna0xY8YoPj5ey5cv14svvqi3335bNTU12rBhg2644QalpaXJbreruLhYkrR//35NnDhRCxcu1JgxY5Sdna3a2lodOXJEklRYWKgFCxZo6tSpio6OVlZWloqLi%2BV0OtXc3Kzi4mKtW7dOUVFRSk5O1uLFi7Vv376BHAcAAPBBXhewIiIitHv3bl1zzTUe6xcvXtTx48c1YcIEBQUFmevx8fEqLy%2BXJFVUVCghIcGsBQcHa/z48SorK5Pb7VZlZaUmTZpk1u12u1pbW1VdXa3q6mq1t7fLbrd7HLuioqK/LhUAAFyhAga6gUsNGTJEt956q/naMAzt27dPkydPlsPhkM1m89h%2B6NChqq%2BvlyQ1NDR0qF977bWqr6/XhQsX5HQ6Per%2B/v4KCwtTXV2d/Pz8FBYWpoCAAI9jO51OnTt3TuHh4f1xuQAA4ArkdXewLvXoo4/qxIkT%2BtnPfqbm5mYFBgZ61AMDA80H4FtaWrqst7S0mK87q3d1bEnm8QEAAHrC6%2B5g/bOcnBwVFhbqySef1NixYxUUFKTz5897bONyuRQcHCxJCgoK6hCGXC6XQkNDuwxLLpdLISEhamtr67QmSSEhIT3uuaGhQQ6Ho8fbAwDgywIC/OSt92v8/Qd1%2Bb4cERHR4VMvK3ltwNq4caOKioqUk5Oj5ORkSdKwYcN08uRJj%2B0aGxsVERFh1i8dYmNjo8aNG6fw8HAFBQWpsbFRo0ePliS1t7erqalJERERcrvdampqktvt1qBBg8x9g4ODFRoa2uO%2Bi4qKlJub22E9PmN3zy8eAAAfMWRIiMfjNd5m797dnb4vZ2RkaNmyZf12Xq%2BcSG5uroqKivTEE0/o3/7t38z1mJgY7dq1Sy6Xy7wjVVpaaj64HhMTo2PHjpnbNzc3q6qqSsuXL5efn58mTpyo0tJS80H4srIyDR48WFFRUTIMQwEBASovL1dcXJwk6ejRo4qOju5V7/Pnz9f06dM7rG8%2B%2BI/eDQEAAB9w8WKzvPkOVlfvy5/fnOkvXhewTp06pR07dugnP/mJYmNj1djYaNZuvvlmjRgxQqtWrdLSpUt18OBBVVZWauvWrZKk1NRUPf3009q1a5emTZum3NxcRUZGmoHqrrvuUmZmpsaOHSubzaasrCzNmzfP/KnElJQUZWZmasuWLaqvr1dBQYF57J6y2Wyd33I8%2BD9fciIAAHivtjZDknug2%2BhSl%2B/L/czrAtbrr78ut9utHTt2aMeOHZI%2B%2B0lCPz8/nThxQnl5eVq7dq1SU1N1/fXXKy8vT8OHD5ckjRw5Utu3b9fmzZuVn5%2BvuLg45eXlmceeOXOmamtrlZmZqdbWVs2YMUMrV64066tXr1ZWVpYWLFigIUOGaMWKFebHkwAAAD3ldQErLS1NaWlpXdavv/56FRYWdllPTEzUyy%2B/3GV9yZIlWrJkSae14OBgZWdnKzs7u%2BcNAwAAXMI7PzQFAADwYQQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIErE64XC6tWbNGCQkJSkxMVEFBwUC3BAAAfEjAQDfgjbZt26aqqioVFhaqpqZGDz/8sEaOHKnbbrttoFsDAAA%2BgDtYl2hublZxcbHWrVunqKgoJScna/Hixdq3b99AtwYAAHwEAesS1dXVam9vl91uN9fi4%2BNVUVExgF0BAABfQsC6hMPhUFhYmAIC/u/T06FDh8rpdOrcuXMD2BkAAPAVBKxLNDc3KzAw0GPt89cul2sgWgIAAD6Gh9wvERQU1CFIff46JCSk2/0bGhrkcDg6rI8a2v2%2B3uK6rwcpKMB3svd1Xw/yqf9SoN/%2BRb/9i377l6/1O2poiAIC/OSt92v8/Qd1%2Bb4cEREhm83Wb%2BcmYF1i2LBhampqktvt1qBBn/2BaWxsVHBwsEJDQ7vdv6ioSLm5uR3WExIS9OTjj/frv8wrVUNDg4qKijR//nzm9yUwv75hfn3D/PqG%2BfVNQ0ODHnzwQR05cqRDLSMjQ8uWLeu3cxOwLjFu3DgFBASovLxccXFxkqSjR48qOjq6R/vPnz9f06dP91g7deqUHnroITkcDv6CfAkOh0O5ubmaPn068/sSmF/fML%2B%2BYX59w/z6xuFw6MiRI8rJydGYMWM8ahEREf16bgLWJYKDg5WSkqLMzExt2bJF9fX1Kigo0NatW3u0v81m4y8BAABeZMyYMZowYcJlPScBqxOrV69WVlaWFixYoCFDhmjFihVKTk4e6LYAAICPIGB1Ijg4WNnZ2crOzh7oVgAAgA/yzsf%2BAQAAfJj/L3/5y18OdBNfBVdddZVuvvlmXXXVVQPdik9ifn3D/PqG%2BfUN8%2Bsb5tc3AzU/P8MwjMt6RgAAgCscHxECAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWP3M5XJpzZo1SkhIUGJiogoKCga6pX5VX1%2Bv5cuX61vf%2BpamTp2qrVu3yuVySZJqamq0aNEixcbGatasWXrrrbc89j106JBmz54tu92uhQsX6syZMx71PXv2KCkpSfHx8Vq7dq2cTqdZ627O3Z3bG6WlpWn16tXma%2BbXPZfLpaysLN18882aMmWKnnjiCbPG/LpXV1en%2B%2B%2B/X/Hx8frOd76jvXv3mjXm1zWXy6XZs2fryJEj5po3z6u7c19unc2vvLxcP/zhDxUbG6vbb79dv/vd7zz28Yn5GehXGzZsMFJSUowTJ04Yr776qhEXF2ccOHBgoNvqN/PmzTPS0tKMkydPGkePHjVuu%2B0249FHHzUMwzBmz55t/OIXvzBOnTpl7Ny507Db7cbZs2cNwzCMv//974bdbjcKCgqMkydPGj/96U%2BN2bNnm8d9%2BeWXjYSEBOONN94wKisrjTvuuMPYuHGjWe9uznPmzOny3N7oxRdfNG688UZj1apV5toXXQPz%2B8wjjzxizJgxw6isrDQOHz5s3HLLLUZRUZFhGPz564l58%2BYZDz74oHH69GnjtddeM%2Bx2u/Hqq68ahsH8uuJ0Oo309HQjKirKeOedd8x1b/372t25L7fO5udwOIyEhATjiSeeME6fPm388Y9/NG666SbjjTfeMAzDMGpra31ifgSsfvTpp58aN910k3HkyBFzLT8/37jnnnsGsKv%2Bc%2BrUKSMqKsr46KOPzLUXX3zRSEpKMg4fPmzExsYaLS0tZm3hwoXG9u3bDcMwjCeffNJjLs3NzUZcXJz5F%2B7uu%2B82cnNzzfrRo0eNmJgYo6Wlpds5Hzp06AvP7W2ampqMqVOnGnPnzjUDVnfXwPw%2Bm9uECRM8ruOpp54y1qxZw5%2B/Hjh//rxx4403Gu%2B//765tmzZMmPjxo3MrwsnT540UlJSjJSUFI%2BA4M1/X7s79%2BXU1fyeffZZY%2BbMmR7bPvLII8bKlSsNw/Cd%2BfERYT%2Bqrq5We3u77Ha7uRYfH6%2BKiooB7Kr/REREaPfu3brmmms81i9evKjjx49rwoQJCgoKMtfj4%2BNVXl4uSaqoqFBCQoJZCw4O1vjx41VWVia3263KykpNmjTJrNvtdrW2tqq6urrbOVdUVHzhub3Ntm3blJKSojFjxphr3V0D85NKS0s1ZMgQj%2BtcsmSJNm/ezJ%2B/HggODlZISIhKSkrU1tamDz74QMeOHdO4ceOYXxfeeecdTZ48WUVFRTL%2B6bfOefPf1y869%2BXW1fySkpKUnZ3dYfuLFy9K8p35BfR6Iugxh8OhsLAwBQT835iHDh0qp9Opc%2BfOKTw8fAC7s96QIUN06623mq8Nw9C%2Bffs0efJkORwO2Ww2j%2B2HDh2q%2Bvp6SVJDQ0OH%2BrXXXqv6%2BnpduHBBTqfTo%2B7v76%2BwsDDV1dXJz8/vC%2Bfc3bm9yeHDh1VaWqoXXnhBmZmZ5jrz696ZM2c0cuRI/eEPf9DOnTvV2tqqH/zgB3rggQeYXw8EBgZq/fr12rBhg5555hm1t7frBz/4gVJTU7Vp0ybm14k777yz03Vv/vP2Ree%2B3Lqa33XXXafrrrvOfP3RRx/ppZde0vLlyyX5zvwIWP2oublZgYGBHmufv/78we8r2aOPPqoTJ06ouLhYBQUFnc7i8zm0tLR0WW9paTFfd1Z3u91fOOeu/j14278Dl8ulX/7yl8rMzOzQb3fXwPykTz/9VH/729%2B0f/9%2Bbd26VQ6HQ%2BvXr1dISAjz66FTp05p%2BvTpuu%2B%2B%2B/Tee%2B9p48aNmjx5MvPrJW%2Be1xed2xs5nU4tW7ZMNptN8%2BfPl%2BQ78yNg9aOgoKAOQ//8dUhIyEC0dNnk5OSosLBQTz75pMaOHaugoCCdP3/eYxuXy6Xg4GBJXc8qNDS0y1DqcrkUEhKitra2L5xzd%2Bf2Ftu3b1d0dLS%2B/e1vd6gxv%2B75%2B/vrk08%2B0eOPP67hw4dLkmpra/Wb3/xGU6ZMUVNTk8f2zM/T4cOHVVxcrDfffFOBgYEaP3686urqtGPHDk2ePJn59YI3/339onN7m08//VQPPPCAPvzwQz377LPmx3a%2BMj%2BewepHw4YNU1NTk9xut7nW2Nio4OBgr/zDbJWNGzdq7969ysnJUXJysqTPZuFwODy2a2xsVERERLf18PBwBQUFqbGx0ay1t7erqalJERER3c65u3N7i5deekmvv/66YmNjFRsbqxdeeEEvvPCC4uLiNHz4cObXDZvNpqCgIDNcSdLo0aNVX1/Pn78e%2BPOf/6xRo0Z5/Nf5uHHjdPbsWebXS948L1%2BZ58cff6x7771Xp06d0t69exUZGWnWfGV%2BBKx%2BNG7cOAUEBHg8jHn06FFFR0cPYFf9Kzc3V0VFRXriiSd0%2B%2B23m%2BsxMTGqqqrySP6lpaXmg4YxMTE6duyYWWtublZVVZViY2Pl5%2BeniRMnqrS01KyXlZVp8ODBioqK6nbO3Z3bW%2Bzbt08vvPCCnn/%2BeT3//POaPn26pk%2Bfrueee0433XQT8%2BtGTEyMnE6nTp8%2Bba6dOnVKI0eOVExMjP785z8zvy9gs9l0%2BvRptbW1mWsffPCBvvGNbzC/XvLm/7/r6tzeNE/DMJSRkaHa2lrt27fP4wd%2BJB%2BaX%2B9/sBK9sX79emPWrFlGRUWF8eqrrxrx8fHm98pcaU6ePGmMHz/e%2BNWvfmU4HA6Pf9rb241Zs2YZP/vZz4z333/f2LlzpxEXF2d%2Bt0hNTY0RExNjPPXUU8b7779vrFixwkhJSTGP/cc//tGYNGmS8eqrrxrHjx83Zs2aZWzevNmsf9Gcuzu3t1q1apX5NQ3Mr2d%2B8pOfGD/84Q%2BNEydOGG%2B%2B%2BaYxefJkY9%2B%2BfUZ7e7txxx13ML8vcPHiRWPKlCnGww8/bPz1r381Xn/9deNb3/qWsX//fubXAzfeeKP5o/re/Pe1s3N/73vfu1xj6tI/z6%2BoqMgYN26c8cYbb3i8jzQ1NRmG4TvzI2D1s%2BbmZmPVqlVGbGyskZSUZDzzzDMD3VK/2blzpxEVFeXxz4033mhERUUZhmEYp0%2BfNn70ox8ZN910kzFr1izj8OHDHvu/%2BeabxowZMwy73W7ce%2B%2B9Rk1NjUf9qaeeMr797W8bCQkJxrp16wyn02nWupvzhx9%2B%2BIXn9kb/HLAMo/trYH6fhYSHH37YiIuLM2699VYjPz/frDG/7p08edK49957jUmTJhm33Xabx3Uwvy926ReNevO8ujv3QIiKijK/m%2Bq%2B%2B%2B7r8F4SFRXl8f1TvjA/P8P4py%2BfAAAAQJ/xDBYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDF/j9UyiZAIWLoIwAAAABJRU5ErkJggg%3D%3D">
             </div>
      </div>
    </div><div class="row variablerow">
        <div class="col-md-3 namecol">
            <p class="h4">MaxClicksItems<br/><small>Numeric</small></p>
        </div>

        <div class="col-md-6">
            <div class="row">
                <div class="col-sm-6">
                    <table class="stats ">
                        <tr><th>Distinct count</th>
                        <td>71</td></tr>
                        <tr><th>Unique (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (%)</th>
                        <td>0.0%</td></tr>
                        <tr class="ignore"><th>Missing (n)</th>
                        <td>0</td></tr>
                    </table>

                </div>
                <div class="col-sm-6">
                    <table class="stats ">

                        <tr><th>Mean</th>
                        <td>1.9018</td></tr>
                        <tr><th>Minimum</th>
                        <td>1</td></tr>
                        <tr><th>Maximum</th>
                        <td>140</td></tr>
                        <tr class="ignore"><th>Zeros (%)</th>
                        <td>0.0%</td></tr>
                    </table>
                </div>
            </div>
        </div>
        <div class="col-md-3 collapse in" id="minihistogram-1335404595">
             <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAA55JREFUeJzt2z9IM3ccx/FPohWKhUpLcqFDoVMHBZcWxCVQAw4aBK2ETNJJCBEHIUsWJ6m6ic/iqiARQSoY/yy6BBQcHEoHJ5EiyZ2RQi0tRE2n56GpT79gMXcJz/u15cjx%2BwZ%2B71wOcqF6vV6Xz1zXVaFQUCqVUjQa9Xt5tJkg90soiECAdhEOegCglXUGtXC9XtfT09P/OjccDisUCr3yRMBzgQXy%2BPioH3/6Wb/e/fWi87796lP98N3XBAJfBBaIJP1y87suy3%2B86JzPP/moSdMAz3EPAhgIBDAQCGAgEMBAIICBQAADgQAGAgEMBAIYCAQwEAhgIBDAQCCAgUAAA4EABgIBDAQCGAgEMBAIYCAQwEAggIFAAAOBAAYCAQwEAhgIBDAQCGAgEMBAIICBQAADgQAGAgEMBAIYCAQwEAhgIBDAQCCAgUAAA4EABgIBDAQCGAgEMHQGufj333yh3/6sveicLz/7WA8PDwqHaftD0tkZzFYNZFXXdVUoFJRKpRSNRoMYAW0kyP0SyNew53laXV2V53lBLI82E%2BR%2B4XcKYCAQwEAggIFAAEMggUQiEWWzWUUikSCWR5sJcr%2BE6vV63fdVgTbBTyzAQCCAgUAAA4EABgIBDAQCGAgEMPgeyP7%2BvkZHRzU8PKw3b974vTxa2P39vZLJpG5ubhqOn5ycaGhoqOF9mUxGIyMjmpyc1PX1ddNm8jWQ29tbLS8va2NjQ8ViUefn5yqVSn6OgBZ1cXGhdDqtq6urhuPValVLS0sNx1ZWVtTb26u9vT3Nzc0pl8s1bS5fAymVShoYGFBPT486Ojo0NjamYrHo5whoUVtbW5qfn3/2QFQ%2Bn1c2m204dnx8rPHxcUnSwMCAqtWqyuVyU%2Bby9YnCSqUix3HevXYcp2kfDO1lYWFBkvTPfz6tr6%2Brr69P/f39De/99z6KRCIql8uKxWKvPpevV5D3/e2LZ8vxPpeXlzo6OlImk3m2b/zcR77uTsdx5Lruu9eu6zalerSvUCgkSTo8PJTneZqYmND09LQqlYrS6bQkKRaLNTx%2B63lewxXlNfkayODgoE5PT3V3d6darabd3V3F43E/R0CLe3t1mJmZ0cHBgXZ2drS2tibHcbS5uSlJisfj2t7eliSdnZ2pu7u7aYH4eg8SjUaVy%2BU0NTWlWq2mRCKhRCLh5whocW%2BvIJbZ2Vnl83klk0l1dXVpcXGxefPwPAjw37hDBgwEAhj%2BBinMBmDh8ks3AAAAAElFTkSuQmCC">

        </div>
       <div class="col-md-12 text-right">
            <a role="button" data-toggle="collapse" data-target="#descriptives-1335404595,#minihistogram-1335404595" aria-expanded="false" aria-controls="collapseExample">
                Toggle details
            </a>
        </div>
        <div class="row collapse col-md-12" id="descriptives-1335404595">
            <div class="col-sm-4">
                  <p class="h4">Quantile statistics</p>
                  <table class="stats indent">
                        <tr><th>Minimum</th>
                        <td>1</td></tr>
                        <tr><th>5-th percentile</th>
                        <td>1</td></tr>
                        <tr><th>Q1</th>
                        <td>1</td></tr>
                        <tr><th>Median</th>
                        <td>2</td></tr>
                        <tr><th>Q3</th>
                        <td>2</td></tr>
                        <tr><th>95-th percentile</th>
                        <td>4</td></tr>
                        <tr><th>Maximum</th>
                        <td>140</td></tr>
                        <tr><th>Range</th>
                        <td>139</td></tr>
                        <tr><th>Interquartile range</th>
                        <td>1</td></tr>
                  </table>
                  <p class="h4">Descriptive statistics</p>
                  <table class="stats indent">
                        <tr><th>Standard deviation</th>
                        <td>1.3299</td></tr>
                        <tr><th>Coef of variation</th>
                        <td>0.69927</td></tr>
                        <tr><th>Kurtosis</th>
                        <td>479.78</td></tr>
                        <tr><th>Mean</th>
                        <td>1.9018</td></tr>
                        <tr><th>MAD</th>
                        <td>0.83256</td></tr>
                        <tr class=""><th>Skewness</th>
                        <td>9.4233</td></tr>
                        <tr><th>Sum</th>
                        <td>2093847</td></tr>
                        <tr><th>Variance</th>
                        <td>1.7686</td></tr>
                        <tr><th>Memory size</th>
                        <td>8.4 MiB</td></tr>
                 </table>
            </div>
             <div class="col-sm-8 histogram">
                 <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAIABJREFUeJzt3X10VPWB//FPJkMeRFIizgBSrAhnGyCYSUKoVIElZbVSIG2zSKVaQGlWSYBda1eeZBqeMR60SwjFeAgYjhZM1geoZ7HWbm0FKwRCYiNVsGpCSTJxCQ%2BazJDM/f3hj1svAyTKTcaQ9%2Bscjyff79z7/fIxZD7euTOJMAzDEAAAAGzjCPcGAAAArjQULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwGQULAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwGQULAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwWYcXrEAgoMmTJ2vfvn3mWHl5uX70ox8pOTlZd9xxh5577jnLMXv27NHkyZPl8Xg0c%2BZMVVdXW%2Ba3bNmisWPHKjU1VYsXL5bf77est2jRIqWlpWnMmDEqKiqyHFtTU6NZs2YpOTlZkyZN0htvvPGF1gYAAGhLhxasQCCgBx98UEeOHDHHGhoalJWVpZtvvlkvvvii5s6dqxUrVugPf/iDJOnvf/%2B7srOzlZmZqdLSUsXHxys7O9s8fvfu3SooKNDy5cu1detWHTp0SHl5eeb82rVrVVVVpeLiYnm9XuXn5%2BuVV14x57Ozs%2BV2u1VaWqopU6YoJydHtbW1kqTjx49fcu0vq76%2BXuvXr1d9ff1ln%2BtKQSZW5BGKTKzIIxSZWJFHqLBmYnSQI0eOGBkZGUZGRoaRkJBgvPXWW4ZhGMazzz5rTJw40fLYRx55xHjooYcMwzCMJ554wrjnnnvMuaamJiMlJcU8/sc//rGRn59vzu/fv99ISkoympubjU8//dS46aabjH379pnzBQUF5vn27NljJCcnG83Nzeb8zJkzjfXr17dr7S/r7bffNv7pn/7JePvtty/rPFcSMrEij1BkYkUeocjEijxChTOTDruC9dZbb2n06NHavn27DMMwx8eOHavVq1eHPP706dOSpIqKCqWlpZnjMTExGjZsmA4ePKhgMKjKykqNHDnSnPd4PDp79qwOHz6sw4cPq7W1VR6Px5xPTU1VRUWFee7hw4crOjraMl9eXt7m2gAAAO3l7KgT33XXXRccv%2B6663TdddeZX3/88cd6%2BeWXNW/ePEmfXc5zu92WY6699lrV1dXp1KlT8vv9lvnIyEj17t1btbW1ioiIUO/eveV0/uOP1adPH/n9fp04cUI%2Bny/k3H369FFdXV2bawMAALRXhxWs9vD7/Zo7d67cbremTZsmSWpublZUVJTlcVFRUQoEAmpubja/vtB8MBi84Jz02f1gTU1NFz22rbUBAADaK2wF69NPP9UDDzygjz76SM8%2B%2B6z5sl10dHRIoQkEAoqLi7OUpfPnY2Nj1dLScsE5SYqNjVV0dLROnjwZMh8TE9Pm2u1VX18vn89nGTt69Gi7jwcAAPa60POwy%2BUKedXKTmEpWGfOnNHs2bNVU1OjrVu3auDAgeZc3759QwpKQ0ODhg4dqvj4eEVHR6uhoUGDBg2SJLW2tqqxsVEul0vBYFCNjY0KBoNyOBzmsTExMYqLi1Pfvn0t72g8N%2B9yudpcu722b9%2Bu/Pz8kPHs7GwNHz683ee50g0fPlx//etfw72NrwzyCEUmVuQRikysyCPU8OHDlZaWpp///Ochczk5OZo7d26Hrd3pBcswDOXk5OjYsWPatm2bbrjhBst8UlKSDhw4YH7d1NSkqqoqzZs3TxERERoxYoTKysrMm9EPHjyoHj16KCEhQYZhyOl0qry8XCkpKZKk/fv3KzEx0Tx3YWGhAoGAeTWsrKzMvGn%2BYmt/kf8A06ZNU3p6esi4y%2BXSqVNNam0NtvtcV7LISIfi4mLJ5P8jj1BkYkUeocjEijxCRUY6tG7dupCLJ5LMiysdpdML1nPPPae33npLGzdu1NVXX62GhgZJUo8ePfS1r31NmZmZ2rx5swoLCzV%2B/Hjl5%2Bdr4MCBZqGaPn26vF6vhgwZIrfbrdzcXN15553mS4wZGRnyer1atWqV6urqVFRUpDVr1kiSRo0apf79%2B2vBggWaM2eOXnvtNVVWVprzF1r7%2Buuv16hRo9r953O73Re95HjixCdqaeGb/vNaW4Nk8jnkEYpMrMgjFJlYkYfVpZ6XO1KE8fnPUOggQ4cOVXFxsUaOHKnZs2eHfHq6JKWlpenpp5%2BWJP3xj3/UypUrVVdXp5SUFC1btkwDBgwwH1tYWKgtW7bo7Nmzuv322/XII4%2BYV6Sam5uVm5ur3bt3q1evXpo9e7buuece89jq6motWrRIFRUVuv7667V48WLdfPPN5nxba18OCtY/OJ0Oxcf3JJP/jzxCkYkVeYQiEyvyCHUuk3DolIKFz/BN/w/8ILAij1BkYkUeocjEijxChbNg8cueAQAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwGQULAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABs5gz3BrqjmsYz8p0KhHsbX0qkQ0roF6coJ986AABcDM%2BSYfBBw6daueu9cG/jS3HHRang7iRFhXsjAAB8hfESIQAAgM0oWAAAADajYAEAANiMggUAAGAzChYAAIDNKFgAAAA2o2ABAADYjIIFAABgMwoWAACAzShYAAAANqNgAQAA2IyCBQAAYDMKFgAAgM0oWAAAADajYAEAANiMggUAAGAzChYAAIDNKFgAAAA26/CCFQgENHnyZO3bt88cq6mp0axZs5ScnKxJkybpjTfesByzZ88eTZ48WR6PRzNnzlR1dbVlfsuWLRo7dqxSU1O1ePFi%2Bf1%2By3qLFi1SWlqaxowZo6KiIsuxl7s2AABAWzq0YAUCAT344IM6cuSIZTw7O1tut1ulpaWaMmWKcnJyVFtbK0k6fvy4srOzlZmZqdLSUsXHxys7O9s8dvfu3SooKNDy5cu1detWHTp0SHl5eeb82rVrVVVVpeLiYnm9XuXn5%2BuVV16xZW0AAID26LCCdfToUd15552qqamxjO/du1fV1dVatmyZbrzxRmVlZcnj8aikpESStGPHDo0YMUIzZ87U4MGDtXr1ah07dsy8AlZcXKwZM2Zo3LhxSkxMVG5urkpKSuT3%2B9XU1KSSkhItWbJECQkJmjBhgmbPnq1t27bZsjYAAEB7dFjBeuuttzR69Ght375dhmGY4xUVFRo%2BfLiio6PNsdTUVJWXl5vzaWlp5lxMTIyGDRumgwcPKhgMqrKyUiNHjjTnPR6Pzp49q8OHD%2Bvw4cNqbW2Vx%2BOxnLuiouKy1wYAAGgvZ0ed%2BK677rrguM/nk9vttoz16dNHdXV1kqT6%2BvqQ%2BWuvvVZ1dXU6deqU/H6/ZT4yMlK9e/dWbW2tIiIi1Lt3bzmdTsu5/X6/Tpw4cVlrAwAAtFeHFayLaWpqUlRUlGUsKipKgUBAktTc3HzR%2BebmZvPrC80Hg8ELzkmf3Q92OWsDAAC0V6cXrOjoaJ08edIyFggEFBMTY86fX2gCgYDi4uIsZen8%2BdjYWLW0tFxwTpJiY2Mva%2B32qq%2Bvl8/nCxl3uVyKieklSYqIiGj3%2Bb6KHA6HnM7Le3U5MtJh%2BXd3Rx6hyMSKPEKRiRV5hIqMdFzyefn8V63s1OkFq2/fviHvKmxoaJDL5TLnzw%2BioaFBQ4cOVXx8vKKjo9XQ0KBBgwZJklpbW9XY2CiXy6VgMKjGxkYFg0E5HA7z2JiYGMXFxV3W2u21fft25efnh4zn5ORo7ty5knTZ5STcru4Zrfi4q2w5V1xcrC3nuVKQRygysSKPUGRiRR5WW7c%2B1ebzckfo9IKVlJSkwsJCBQIB84pUWVmZeeN6UlKSDhw4YD6%2BqalJVVVVmjdvniIiIjRixAiVlZWZN6MfPHhQPXr0UEJCggzDkNPpVHl5uVJSUiRJ%2B/fvV2Ji4mWt/UX%2BA0ybNk3p6ekh4y6XS6dONam1NaiWlmC7z/dVdOYTvyJajbYfeAmRkQ7FxcWamXR35BGKTKzIIxSZWJFHqMhIxyWflztSpxesUaNGqX///lqwYIHmzJmj1157TZWVlVqzZo0kKTMzU5s3b1ZhYaHGjx%2Bv/Px8DRw40CxU06dPl9fr1ZAhQ%2BR2u5Wbm6s777zTfGdgRkaGvF6vVq1apbq6OhUVFZnn/jJrX3/99Ro1alS7/3xut/uilxxPnPhELS1By7squ6Jg0L6SeCUUTjuRRygysSKPUGRiRR5Wl3pe7kid8lrV5%2B85cjgcKigokM/nU2Zmpnbu3KkNGzaoX79%2BkqQBAwZo/fr1Ki0t1dSpU3X69Glt2LDBPH7ixInKysqS1%2BvV7Nmz5fF49NBDD5nzCxcuVGJiombMmKHly5dr/vz5mjBhwpde%2B0KXFQEAAC4lwujql1O6kHNXsP50pF4rd70X7u18Ke64KBXcnaSe573b8otyOh2Kj%2B9pZtLdkUcoMrEij1BkYkUeoc5lEg5d%2B25rAACAryAKFgAAgM0oWAAAADajYAEAANiMggUAAGAzChYAAIDNKFgAAAA2o2ABAADYjIIFAABgMwoWAACAzShYAAAANqNgAQAA2IyCBQAAYDMKFgAAgM0oWAAAADajYAEAANiMggUAAGAzChYAAIDNKFgAAAA2o2ABAADYjIIFAABgMwoWAACAzShYAAAANqNgAQAA2IyCBQAAYDMKFgAAgM0oWAAAADajYAEAANiMggUAAGAzChYAAIDNKFgAAAA2o2ABAADYjIIFAABgMwoWAACAzShYAAAANqNgAQAA2IyCBQAAYDMKFgAAgM0oWAAAADajYAEAANiMggUAAGAzChYAAIDNwlawamtrdf/99ys1NVXf%2Bc53tHXrVnOupqZGs2bNUnJysiZNmqQ33njDcuyePXs0efJkeTwezZw5U9XV1Zb5LVu2aOzYsUpNTdXixYvl9/vNuUAgoEWLFiktLU1jxoxRUVGR5di21gYAAGhL2ArW/Pnz1bNnTz3//PNatGiRnnjiCb366quSpDlz5sjtdqu0tFRTpkxRTk6OamtrJUnHjx9Xdna2MjMzVVpaqvj4eGVnZ5vn3b17twoKCrR8%2BXJt3bpVhw4dUl5enjm/du1aVVVVqbi4WF6vV/n5%2BXrllVfM%2Bezs7IuuDQAA0B5hKVinTp3SoUOH9MADD%2Bj666/Xd77zHY0ZM0Zvvvmm3nzzTdXU1GjZsmW68cYblZWVJY/Ho5KSEknSjh07NGLECM2cOVODBw/W6tWrdezYMe3bt0%2BSVFxcrBkzZmjcuHFKTExUbm6uSkpK5Pf71dTUpJKSEi1ZskQJCQmaMGGCZs%2BerW3btkmS9u7dq%2Brq6ouuDQAA0B5hKVgxMTGKjY1VaWmpWlpa9P777%2BvAgQMaOnSoDh06pOHDhys6Otp8fGpqqsrLyyVJFRUVSktLs5xr2LBhOnjwoILBoCorKzVy5Ehz3uPx6OzZszp8%2BLAOHz6s1tZWeTwey7krKirMc19qbQAAgPYIS8GKiorS0qVL9etf/1pJSUmaOHGixo4dq8zMTPl8Prndbsvj%2B/Tpo7q6OklSfX19yPy1116ruro6nTp1Sn6/3zIfGRmp3r17q7a2Vj6fT71795bT6bSc2%2B/368SJE22uDQAA0B7Oth/SMY4ePar09HTdd999evfdd7V8%2BXKNHj1aTU1NioqKsjw2KipKgUBAktTc3HzR%2BebmZvPrC80Hg8ELzkmf3fze1toAAADtEZaCtXfvXpWUlOj1119XVFSUhg0bptraWm3cuFGjR49WY2Oj5fGBQEAxMTGSpOjo6JDCEwgEFBcXZylL58/HxsaqpaXlgnOSFBsbq%2BjoaJ08efKia7dHfX29fD5fyLjL5VJMTC9JUkRERLvP91XkcDjkdF7exc/ISIfl390deYQiEyvyCEUmVuQRKjLSccnn5fNftbJTWArWX/7yF91www2Wq0VDhw7Vpk2b1LdvX7333nuWxzc0NMjlckmS%2BvbtGxJUQ0ODhg4dqvj4eEVHR6uhoUGDBg2SJLW2tqqxsVEul0vBYFCNjY0KBoNyOBzmsTExMYqLi1Pfvn115MiRi67dHtu3b1d%2Bfn7IeE5OjubOnStJl11Owu3qntGKj7vKlnPFxcXacp4rBXmEIhMr8ghFJlbkYbV161NtPi93hLAULLfbrQ8//FAtLS3m/VDvv/%2B%2Bvv71ryspKUmbNm1SIBAwC1hZWZl543pSUpIOHDhgnqupqUlVVVWaN2%2BeIiIiNGLECJWVlZk3wh88eFA9evRQQkKCDMOQ0%2BlUeXm5UlJSJEn79%2B9XYmKiee7CwsKLrt0e06ZNU3p6esi4y%2BXSqVNNam0NqqUl%2BEUj%2B0o584lfEa3GZZ0jMtKhuLhYM5PujjxCkYkVeYQiEyvyCBUZ6bjk83JHCkvBSk9PV15enpYsWaL7779f77//vjZt2qSf/exnSktLU//%2B/bVgwQLNmTNHr732miorK7VmzRpJUmZmpjZv3qzCwkKNHz9e%2Bfn5GjhwoFmopk%2BfLq/XqyFDhsjtdis3N1d33nmn%2Bc7AjIwMeb1erVq1SnV1dSoqKjLPPWrUqEuu3R5ut/uilxxPnPhELS1BGcbllZNwCwbtK4lXQuG0E3mEIhMr8ghFJlbkYXWp5%2BWOFJbXqq6%2B%2Bmpt2bJFPp9PU6dO1dq1a5Wdna2pU6fK4XBo48aN8vl8yszM1M6dO7Vhwwb169dPkjRgwACtX79epaWlmjp1qk6fPq0NGzaY5544caKysrLk9Xo1e/ZseTwePfTQQ%2Bb8woULlZiYqBkzZmj58uWaP3%2B%2BJkyYIOmze4sKCgouujYAAEB7RBhd/XJKF3LuCtafjtRr5a732j7gK8gdF6WCu5PU87x3W35RTqdD8fE9zUy6O/IIRSZW5BGKTKzII9S5TMKha99tDQAA8BVEwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwGQULAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmloI1depU/frXv9bp06fDtR8AAIAuz1Kwbr75Zv3qV7/SrbfeqgcffFB/%2BtOfZBhGuPYGAADQJVkK1s9%2B9jP9/ve/V0FBgSIjIzV37lz98z//sx5//HH97W9/C9ceAQAAuhTn%2BQMRERG65ZZbdMstt6ipqUnFxcUqKCjQk08%2BqZSUFM2YMUO33XZbOPYKAADQJYQULEmqr6/XSy%2B9pJdeeknvvvuuUlJS9IMf/EC1tbVasmSJ9u3bp8WLF3f2XgEAALoES8F68cUX9eKLL%2BrPf/6zrrnmGn3/%2B9/Xf/3Xf%2BmGG24wH9O/f3%2BtXLmSggUAAHARloK1ePFijR8/Xhs2bNDYsWPlcIR%2BisONN96ou%2B%2B%2Bu9M2CAAA0NVYCtbrr7%2Bu%2BPh4NTY2muWqoqJCw4cPV2RkpCQpJSVFKSkpnb9TAACALsJyierMmTP67ne/q8LCQnMsKytLGRkZOn78eKdvDgAAoCuyFKxVq1bpG9/4hmbNmmWOvfzyy%2Brfv79Wr17d6ZsDAADoiiwFa//%2B/VqwYIFcLpc5ds011%2Bg///M/9eabb3b65gAAALoiS8FyOp06depUyIOampr4RHcAAIB2shSssWPHasWKFfroo4/Mserqaq1evVpjxozp9M0BAAB0RZZ3ET788MOaNWuWbr/9dsXFxUmSTp06peHDh2vhwoVh2SAAAEBXYylYffr00fPPP689e/bovffek9Pp1JAhQzR69GhFRESEa48AAABdSsivyomMjNSYMWN4SRAAAOBLshQsn8%2BnJ554QgcOHNDZs2dDbmz/3e9%2B16mbAwAA6IosBeuRRx7R22%2B/re9973vq1atXuPYEAADQpVkK1ptvvqmnnnpKI0eODNd%2BAAAAujzLxzRcddVV6tOnT7j2AgAAcEWwFKyMjAw99dRTam1tDdd%2BAAAAujzLS4SNjY3atWuX/vd//1cDBw5UVFSU5cFPP/10p24OAACgKwr5mIZJkyaFYx8AAABXDEvBWr16dbj2AQAAcMVwnD9QX1%2Bv/Px8/exnP9PHH3%2Bs//mf/9H7778fjr0BAAB0SZaC9eGHH2ry5Ml6/vnntXv3bn366ad6%2BeWXlZmZqUOHDoVrjwAAAF2KpWCtWbNGEyZM0KuvvqoePXpIktatW6f09HQ99thjti4cCASUm5urUaNG6dZbb9Xjjz9uztXU1GjWrFlKTk7WpEmT9MYbb1iO3bNnjyZPniyPx6OZM2equrraMr9lyxaNHTtWqampWrx4sfx%2Bv2XdRYsWKS0tTWPGjFFRUZHl2LbWBgAAaIulYB04cECzZs2y/GJnp9OpOXPmqKqqytaFV6xYob1792rz5s167LHHtGPHDu3YsUOSNGfOHLndbpWWlmrKlCnKyclRbW2tJOn48ePKzs5WZmamSktLFR8fr%2BzsbPO8u3fvVkFBgZYvX66tW7fq0KFDysvLM%2BfXrl2rqqoqFRcXy%2Bv1Kj8/X6%2B88oo5n52dfdG1AQAA2sNSsILBoILBYMiDPvnkE0VGRtq26MmTJ/Xf//3fWrFihRITE3XzzTfr3nvv1aFDh/Tmm2%2BqpqZGy5Yt04033qisrCx5PB6VlJRIknbs2KERI0Zo5syZGjx4sFavXq1jx45p3759kqTi4mLNmDFD48aNU2JionJzc1VSUiK/36%2BmpiaVlJRoyZIlSkhI0IQJEzR79mxt27ZNkrR3715VV1dfdG0AAID2sBSsW2%2B9VZs2bbKUrMbGRuXl5enmm2%2B2bdGysjL16tXL8it5fvrTn2rlypU6dOiQhg8frujoaHMuNTVV5eXlkqSKigqlpaWZczExMRo2bJgOHjyoYDCoyspKy3k9Ho/Onj2rw4cP6/Dhw2ptbZXH47Gcu6Kiwjz3pdYGAABoD0vBWrBggd5%2B%2B23deuut8vv9euCBBzR%2B/HjV1NTo4Ycftm3R6upqDRgwQC%2B88ILuuOMOTZgwQQUFBTIMQz6fT2632/L4Pn36qK6uTtJn73I8f/7aa69VXV2dTp06Jb/fb5mPjIxU7969VVtbK5/Pp969e8vpdFrO7ff7deLEiTbXBgAAaA/L52D17dtXL7zwgnbt2qV33nlHwWBQd911lzIyMnT11Vfbtuinn36qDz74QDt27NCaNWvk8/m0dOlSxcbGqqmpKeQT5KOiohQIBCRJzc3NF51vbm42v77QfDAYvOCc9NnN722tDQAA0B4hn%2BQeGxurqVOnduiikZGR%2BuSTT7Ru3Tr169dPknTs2DE988wzuvXWW9XY2Gh5fCAQUExMjCQpOjo6pPAEAgHFxcVZytL587GxsWppabngnPTZnzs6OlonT5686NrtUV9fL5/PFzLucrkUE9NLkixvIuiKHA6HnM6Qj1D7QiIjHZZ/d3fkEYpMrMgjFJlYkUeoyEjHJZ%2BXz3/Vyk6WgvWTn/zkkg%2B263cRut1uRUdHm%2BVKkgYNGqS6ujr17dtX7733nuXxDQ0Ncrlckj67ynZ%2BUA0NDRo6dKji4%2BMVHR2thoYGDRo0SJLU2tqqxsZGuVwuBYNBNTY2KhgMyuFwmMfGxMQoLi5Offv21ZEjRy66dnts375d%2Bfn5IeM5OTmaO3euJF12OQm3q3tGKz7uKlvOFRcXa8t5rhTkEYpMrMgjFJlYkYfV1q1Ptfm83BEsBWvAgAGWyZaWFn344Yd69913NWPGDNsWTUpKkt/v14cffqhvfOMbkqSjR49qwIABSkpK0qZNmxQIBMwrUmVlZeaN60lJSTpw4IB5rqamJlVVVWnevHmKiIjQiBEjVFZWZt4If/DgQfXo0UMJCQkyDENOp1Pl5eVKSUmRJO3fv1%2BJiYnmuQsLCy%2B6dntMmzZN6enpIeMul0unTjWptTWolpbQd2p2JWc%2B8Sui1bisc0RGOhQXF2tm0t2RRygysSKPUGRiRR6hIiMdl3xe7kjt%2Bl2EGzZssPWzoAYNGqRx48ZpwYIF8nq98vl8KiwsVHZ2ttLS0tS/f38tWLBAc%2BbM0WuvvabKykqtWbNGkpSZmanNmzersLBQ48ePV35%2BvgYOHGgWqunTp8vr9WrIkCFyu93Kzc3VnXfeab4zMCMjQ16vV6tWrVJdXZ2KiorMc48aNeqSa7eH2%2B2%2B6CXHEyc%2BUUtLUIZxeeUk3IJB%2B0rilVA47UQeocjEijxCkYkVeVhd6nm5I0UY7Xi2r6mp0fe//33t37/ftoXPnDmjFStW6Le//a1iY2P14x//WA888ICkz95luGjRIlVUVOj666/X4sWLLR8T8cc//lErV65UXV2dUlJStGzZMsvVt8LCQm3ZskVnz57V7bffrkceecS8ItXc3Kzc3Fzt3r1bvXr10uzZs3XPPfeYx7a19uU4V7D%2BdKReK3e91/YBX0HuuCgV3J2knue9GeCLcjodio/vaWbS3ZFHKDKxIo9QZGJFHqHOZRIO7SpYO3fu1IoVK/TnP/%2B5M/Z0xaJg/QM/CKzIIxSZWJFHKDKxIo9Q4SxYbd7kfubMGf31r3/V9OnTO21TAAAAXZmlYF133XUhHyHQo0cP3X333ZoyZUqnbgwAAKCrshSsL3IzNwAAAC7MUrDO/cLk9vj87wMEAADAP1gK1j333GO%2BRPj5e9/PH4uIiNA777zTWXsEAADoUiwF61e/%2BpVWrFihn//85xo1apSioqJUWVmpZcuW6Qc/%2BIEmTpwYrn0CAAB0GZbf2bJ69WotXbpUt99%2Bu%2BLj49WzZ0/dfPPNWrZsmZ599lkNGDCN9xILAAAccElEQVTA/AcAAAAXZilY9fX1FyxPV199tU6cONFpmwIAAOjKLAXL4/Fo3bp1OnPmjDnW2NiovLw8jR49utM3BwAA0BVZ7sFasmSJfvKTn2js2LG64YYbZBiGPvjgA7lcLj399NPh2iMAAECXYilYgwcP1ssvv6xdu3bp6NGjkqQf//jH%2Bt73vqfY2NiwbBAAAKCrcZ4/8LWvfU1Tp05VTU2NBg4cKOmzT3MHAABA%2B1juwTIMQ4899pjS0tI0adIk1dbW6uGHH9bixYt19uzZcO0RAACgS7EUrOLiYr344ovyer2KioqSJE2YMEGvvvqq8vPzw7JBAACArsZSsLZv366lS5fqhz/8ofnp7RMnTtSKFSu0c%2BfOsGwQAACgq7EUrJqaGg0dOjTkQQkJCfL5fJ22KQAAgK7MUrAGDBigysrKkAe9/vrr5g3vAAAAuDTLuwjvu%2B8%2B5ebmyufzyTAM7d27V9u3b1dxcbEWLFgQrj0CAAB0KZaClZmZqZaWFm3cuFHNzc1aunSprrnmGv37v/%2B77rrrrnDtEQAAoEuxFKxdu3bpu9/9rqZNm6b/%2B7//k2EY6tOnT7j2BgAA0CVZ7sFatmyZeTP7NddcQ7kCAAD4EiwF64YbbtC7774brr0AAABcESwvESYkJOihhx7SU089pRtuuEHR0dGWB69evbpTNwcAANAVWQrW3/72N6WmpkoSn3sFAADwJTkfffRR5eTk6KqrrlJxcXG49wMAANDlOYqKitTU1GQZzMrKUn19fZi2BAAA0LU5DMMIGdy3b5/8fn8YtgMAAND1Odp%2BCAAAAL4IChYAAIDNHJIUERER7n0AAABcMZyStGLFCstnXp09e1Z5eXnq2bOn5cF8DhYAAEDbnGlpaSGfeZWcnKwTJ07oxIkTYdoWAABA1%2BXks68AAADsxU3uAAAANqNgAQAA2IyCBQAAYDMKFgAAgM0oWAAAADajYAEAANiMggUAAGAzChYAAIDNwl6wsrKytHDhQvPrmpoazZo1S8nJyZo0aZLeeOMNy%2BP37NmjyZMny%2BPxaObMmaqurrbMb9myRWPHjlVqaqoWL14sv99vzgUCAS1atEhpaWkaM2aMioqKLMe2tTYAAEB7hLVg/eY3v9Hrr79uGcvOzpbb7VZpaammTJminJwc1dbWSpKOHz%2Bu7OxsZWZmqrS0VPHx8crOzjaP3b17twoKCrR8%2BXJt3bpVhw4dUl5enjm/du1aVVVVqbi4WF6vV/n5%2BXrllVfatTYAAEB7ha1gnTx5Unl5ebrpppvMsb1796q6ulrLli3TjTfeqKysLHk8HpWUlEiSduzYoREjRmjmzJkaPHiwVq9erWPHjmnfvn2SpOLiYs2YMUPjxo1TYmKicnNzVVJSIr/fr6amJpWUlGjJkiVKSEjQhAkTNHv2bG3btq1dawMAALRX2ArW2rVrlZGRocGDB5tjFRUVGj58uKKjo82x1NRUlZeXm/NpaWnmXExMjIYNG6aDBw8qGAyqsrJSI0eONOc9Ho/Onj2rw4cP6/Dhw2ptbZXH47Gcu6Kiol1rAwAAtFdYCtbevXtVVlZmeXlPknw%2Bn9xut2WsT58%2BqqurkyTV19eHzF977bWqq6vTqVOn5Pf7LfORkZHq3bu3amtr5fP51Lt3bzmdTsu5/X6/Tpw40ebaAAAA7eVs%2ByH2CgQC%2BsUvfiGv16uoqCjLXFNTU8hYVFSUAoGAJKm5ufmi883NzebXF5oPBoMXnDu3p7bWBgAAaK9OL1jr169XYmKivv3tb4fMRUdH6%2BTJk5axQCCgmJgYc/78whMIBBQXF2cpS%2BfPx8bGqqWl5YJzkhQbG9vm2u1VX18vn88XMu5yuRQT00uSFBER8YXO%2BVXjcDjkdF7exc/ISIfl390deYQiEyvyCEUmVuQRKjLSccnn5fNfubJTpxesl19%2BWR9//LGSk5MlSWfPnpX02TsA77//fh05csTy%2BIaGBrlcLklS3759Q0JqaGjQ0KFDFR8fr%2BjoaDU0NGjQoEGSpNbWVjU2NsrlcikYDKqxsVHBYFAOh8M8NiYmRnFxcerbt%2B8l126v7du3Kz8/P2Q8JydHc%2BfOlaTLLifhdnXPaMXHXWXLueLiYm05z5WCPEKRiRV5hCITK/Kw2rr1qTaflztCpxesbdu2qaWlxfz63Mco/PznP9exY8f05JNPKhAImFekysrKzBvXk5KSdODAAfPYpqYmVVVVad68eYqIiNCIESNUVlZm3gh/8OBB9ejRQwkJCTIMQ06nU%2BXl5UpJSZEk7d%2B/X4mJiea5CwsLL7p2e02bNk3p6ekh4y6XS6dONam1NaiWluAXOudXzZlP/IpoNS7rHJGRDsXFxZqZdHfkEYpMrMgjFJlYkUeoyEjHJZ%2BXO1KnF6z%2B/ftbvu7Zs6ckaeDAgRowYID69%2B%2BvBQsWaM6cOXrttddUWVmpNWvWSJIyMzO1efNmFRYWavz48crPz9fAgQPNQjV9%2BnR5vV4NGTJEbrdbubm5uvPOO813BmZkZMjr9WrVqlWqq6tTUVGRee5Ro0Zdcu32crvdF73keOLEJ2ppCcowLq%2BchFswaF9JvBIKp53IIxSZWJFHKDKxIg%2BrSz0vd6Sv1GtVDodDBQUF8vl8yszM1M6dO7Vhwwb169dPkjRgwACtX79epaWlmjp1qk6fPq0NGzaYx0%2BcOFFZWVnyer2aPXu2PB6PHnroIXN%2B4cKFSkxM1IwZM7R8%2BXLNnz9fEyZMaNfaAAAA7RVhdPXLKV3IuStYfzpSr5W73gv3dr4Ud1yUCu5OUs/z3nH5RTmdDsXH9zQz6e7IIxSZWJFHKDKxIo9Q5zIJh6/UFSwAAIArAQULAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwGQULAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwGQULAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwGQULAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGZhK1h1dXWaN2%2BevvWtb2ncuHFas2aNAoGAJKmmpkazZs1ScnKyJk2apDfeeMNy7J49ezR58mR5PB7NnDlT1dXVlvktW7Zo7NixSk1N1eLFi%2BX3%2B825QCCgRYsWKS0tTWPGjFFRUZHl2LbWBgAAaEvYCta8efPk9/v1zDPPaN26dfr973%2BvX/7yl5KkOXPmyO12q7S0VFOmTFFOTo5qa2slScePH1d2drYyMzNVWlqq%2BPh4ZWdnm%2BfdvXu3CgoKtHz5cm3dulWHDh1SXl6eOb927VpVVVWpuLhYXq9X%2Bfn5euWVV8z57Ozsi64NAADQHmEpWO%2B//74qKiq0evVqDR48WKmpqZo3b5527dqlN998UzU1NVq2bJluvPFGZWVlyePxqKSkRJK0Y8cOjRgxQjNnztTgwYO1evVqHTt2TPv27ZMkFRcXa8aMGRo3bpwSExOVm5urkpIS%2Bf1%2BNTU1qaSkREuWLFFCQoImTJig2bNna9u2bZKkvXv3qrq6%2BqJrAwAAtEdYCpbL5dJTTz2la665xjJ%2B%2BvRpHTp0SMOHD1d0dLQ5npqaqvLycklSRUWF0tLSzLmYmBgNGzZMBw8eVDAYVGVlpUaOHGnOezwenT17VocPH9bhw4fV2toqj8djOXdFRYV57kutDQAA0B7OcCzaq1cv3XLLLebXhmFo27ZtGj16tHw%2Bn9xut%2BXxffr0UV1dnSSpvr4%2BZP7aa69VXV2dTp06Jb/fb5mPjIxU7969VVtbq4iICPXu3VtOp9Nybr/frxMnTrS5NgAAQHt8Jd5F%2BOijj%2Bqdd97Rf/zHf6ipqUlRUVGW%2BaioKPMG%2BObm5ovONzc3m19faP5i55Z0yflzawMAALRHWK5gfV5eXp6Ki4v1xBNPaMiQIYqOjtbJkyctjwkEAoqJiZEkRUdHhxSeQCCguLg4S1k6fz42NlYtLS0XnJOk2NjYNtduj/r6evl8vpBxl8ulmJhekqSIiIh2n%2B%2BryOFwyOm8vG4eGemw/Lu7I49QZGJFHqHIxIo8QkVGOi75vHz%2Bq1Z2CmvBWr58ubZv3668vDxNmDBBktS3b18dOXLE8riGhga5XC5z/vygGhoaNHToUMXHxys6OloNDQ0aNGiQJKm1tVWNjY1yuVwKBoNqbGxUMBiUw%2BEwj42JiVFcXFyba7fH9u3blZ%2BfHzKek5OjuXPnStJll5Nwu7pntOLjrrLlXHFxsbac50pBHqHIxIo8QpGJFXlYbd36VJvPyx0hbAUrPz9f27dv1%2BOPP65/%2BZd/MceTkpJUWFioQCBgXpEqKyszb1xPSkrSgQMHzMc3NTWpqqpK8%2BbNU0REhEaMGKGysjLzRviDBw%2BqR48eSkhIkGEYcjqdKi8vV0pKiiRp//79SkxMbNfa7TFt2jSlp6eHjLtcLp061aTW1qBaWoJfJKqvnDOf%2BBXRalzWOSIjHYqLizUz6e7IIxSZWJFHKDKxIo9QkZGOSz4vd6SwFKyjR49q48aN%2Brd/%2BzclJyeroaHBnBs1apT69%2B%2BvBQsWaM6cOXrttddUWVmpNWvWSJIyMzO1efNmFRYWavz48crPz9fAgQPNQjV9%2BnR5vV4NGTJEbrdbubm5uvPOO813BmZkZMjr9WrVqlWqq6tTUVGRee621m4Pt9t90UuOJ058opaWoAzj8spJuAWD9pXEK6Fw2ok8QpGJFXmEIhMr8rC61PNyRwpLwfrd736nYDCojRs3auPGjZI%2BeydhRESE3nnnHW3YsEGLFy9WZmamrr/%2Bem3YsEH9%2BvWTJA0YMEDr16/XypUrVVBQoJSUFG3YsME898SJE3Xs2DF5vV6dPXtWt99%2Bux566CFzfuHChcrNzdWMGTPUq1cvzZ8/33x50uFwqKCgQIsWLbrg2gAAAO0RYXT1yyldyLkrWH86Uq%2BVu94L93a%2BFHdclAruTlLP895t%2BUU5nQ7Fx/c0M%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%2BfPvL7/Tpx4kQYdwYAALoKCtZ5mpqaFBUVZRk793UgEAjHlgAAQBfDTe7niY6ODilS576OjY1t8/j6%2Bnr5fL6QcZfLpZiYXpKkq6Ii9U/9etqw287Xp2cPOSMdcl7md47DIbW0tMjh0GWf60pAHqHIxIo8QpGJFXmEcjgu/bzsdrs7bG3%2BE5ynb9%2B%2BamxsVDAYlMPx2QW%2BhoYGxcTEKC4urs3jt2/frvz8/JDxtLQ0rVu3Tm63W7en9tTtqTfYvfUupb6%2BXk8/vVnTpk3r0G/wroI8QpGJFXmEIhMr8ghVX1%2BvBx98UPv27QuZy8nJ0dy5cztsbQrWeYYOHSqn06ny8nKlpKRIkvbv36/ExMR2HT9t2jSlp6dbxo4ePaqf//zn8vl8fNP/fz6fT/n5%2BUpPTycTkceFkIkVeYQiEyvyCOXz%2BbRv3z7l5eVp8ODBljmXy9Wha1OwzhMTE6OMjAx5vV6tWrVKdXV1Kioq0po1a9p1vNvt5hsbAICvkMGDB2v48OGduiYF6wIWLlyo3NxczZgxQ7169dL8%2BfM1YcKEcG8LAAB0ERSsC4iJidHq1au1evXqcG8FAAB0QXxMAwAAgM0if/GLX/wi3JvoDnr27KlRo0apZ8%2Bu%2BfEMHYFMrMgjFJlYkUcoMrEij1DhyiTCMAyjU1cEAAC4wvESIQAAgM0oWAAAADajYAEAANiMggUAAGAzChYAAIDNKFgAAAA2o2ABAADYjILVwQKBgBYtWqS0tDSNGTNGRUVF4d5Sp6qrq9O8efP0rW99S%2BPGjdOaNWsUCAQkSTU1NZo1a5aSk5M1adIkvfHGG2HebefLysrSwoULza%2B7YyaBQEC5ubkaNWqUbr31Vj3%2B%2BOPmXHfMQ5Jqa2t1//33KzU1Vd/5zne0detWc667ZRIIBDR58mTt27fPHGsrgz179mjy5MnyeDyaOXOmqqurO3vbHeZCeZSXl%2BtHP/qRkpOTdccdd%2Bi5556zHHMl5yFdOJNzzpw5o7Fjx%2BqFF16wjHdGJhSsDrZ27VpVVVWpuLhYXq9X%2Bfn5euWVV8K9rU4zb948%2Bf1%2BPfPMM1q3bp1%2B//vf65e//KUkac6cOXK73SotLdWUKVOUk5Oj2traMO%2B48/zmN7/R66%2B/bhnLzs7udpmsWLFCe/fu1ebNm/XYY49px44d2rFjh6Tu%2Bz0yf/589ezZU88//7wWLVqkJ554Qq%2B%2B%2Bqqk7pVJIBDQgw8%2BqCNHjljGL/X35Pjx48rOzlZmZqZKS0sVHx%2Bv7OzscGzfdhfKo6GhQVlZWbr55pv14osvau7cuVqxYoX%2B8Ic/SJL%2B/ve/X7F5SBf/Hjnn0Ucflc/ns4x12veIgQ7z6aefGjfddJOxb98%2Bc6ygoMC45557wrirznP06FEjISHB%2BPjjj82xXbt2GWPHjjX27t1rJCcnG83NzebczJkzjfXr14djq52usbHRGDdunDF16lRjwYIFhmEYxp49e7pdJo2Njcbw4cMtf0eefPJJY9GiRd32e%2BTkyZPGN7/5TeO9994zx%2BbOnWssX768W2Vy5MgRIyMjw8jIyDASEhKMt956yzCMtv%2BePPHEE5afsU1NTUZKSop5fFd1sTyeffZZY%2BLEiZbHPvLII8ZDDz1kGMaVm4dhXDyTc/bt22fcdtttxq233mo8//zz5vgvf/nLTsmEK1gd6PDhw2ptbZXH4zHHUlNTVVFREcZddR6Xy6WnnnpK11xzjWX89OnTOnTokIYPH67o6GhzPDU1VeXl5Z29zbBYu3atMjIyNHjwYHOsoqKi22VSVlamXr16aeTIkebYT3/6U61cubLbfo/ExMQoNjZWpaWlamlp0fvvv68DBw5o6NCh3SqTt956S6NHj9b27dtlfO43urX196SiokJpaWnmXExMjIYNG6aDBw923uY7wMXyGDt2rFavXh3y%2BNOnT0u6cvOQLp6J9NmVraVLl8rr9apHjx6WuUOHDnVKJk5bzwYLn8%2Bn3r17y%2Bn8R8x9%2BvSR3%2B/XiRMnFB8fH8bddbxevXrplltuMb82DEPbtm3T6NGj5fP55Ha7LY/v06eP6urqOnubnW7v3r0qKyvTzp075fV6zfHumEl1dbUGDBigF154QZs2bdLZs2f1wx/%2BUA888EC3zEOSoqKitHTpUi1btkxPP/20Wltb9cMf/lCZmZlasWJFt8nkrrvuuuB4W98X9fX1IfPXXnttl8/oYnlcd911uu6668yvP/74Y7388suaN2%2BepCs3D%2BnimUjSr371Kw0fPlzf/va3Q%2BY6KxMKVgdqampSVFSUZezc1%2Bdu9O5OHn30Ub3zzjsqKSlRUVHRBbO50nMJBAL6xS9%2BIa/XG/Lnv9j3y5WcyaeffqoPPvhAO3bs0Jo1a%2BTz%2BbR06VLFxsZ2yzzOOXr0qNLT03Xffffp3Xff1fLlyzV69Ohunck5bWXQ3NzcbTPy%2B/2aO3eu3G63pk2bJql75nHkyBHt2LFDL7300gXnOysTClYHio6ODvkPdu7r2NjYcGwpbPLy8lRcXKwnnnhCQ4YMUXR0tE6ePGl5TCAQUExMTJh22DnWr1%2BvxMTEC/5fVXfMJDIyUp988onWrVunfv36SZKOHTumZ555RrfeeqsaGxstj7/S85A%2Bu8JZUlKi119/XVFRURo2bJhqa2u1ceNGjR49ultm8nlt/T252M/duLi4TttjOHz66ad64IEH9NFHH%2BnZZ581X0Ltjnk88sgjmjdvXsjtKed0Vibcg9WB%2Bvbtq8bGRgWDQXOsoaFBMTExV/Q39/mWL1%2BurVu3Ki8vTxMmTJD0WTbnv7OjoaFBLpcrHFvsNC%2B//LJ%2B97vfKTk5WcnJydq5c6d27typlJQU9evXr9tl4na7FR0dbZYrSRo0aJDq6uq67ffIX/7yF91www2W/8MeOnSojh8/3m0z%2Bby2MuiOGZ05c0b33nuvjh49qq1bt2rgwIHmXHfL4%2B9//7sOHjyoNWvWmD9njx8/rqVLlyorK0tS52VCwepAQ4cOldPptNyAun//fiUmJoZxV50rPz9f27dv1%2BOPP6477rjDHE9KSlJVVZXl/yLKysosbwi4Em3btk07d%2B7USy%2B9pJdeeknp6elKT0/Xiy%2B%2BqJtuuqnbZZKUlCS/368PP/zQHDt69KgGDBigpKQk/eUvf%2BlWeUiflc4PP/xQLS0t5tj777%2Bvr3/96902k89r62dHUlKSDhw4YM41NTWpqqrqis3IMAzl5OTo2LFj2rZtm%2BWNM1L3y6Nfv3767W9/qxdffNH8Oet2uzV//nytWLFCUudlQsHqQDExMcrIyJDX61VlZaVeffVVFRUVacaMGeHeWqc4evSoNm7cqKysLCUnJ6uhocH8Z9SoUerfv78WLFigI0eO6Mknn1RlZaX%2B9V//Ndzb7lD9%2B/fXwIEDzX969uypnj17auDAgd0yk0GDBmncuHFasGCBDh8%2BrD/%2B8Y8qLCzU9OnTlZaW1u3ykKT09HQ5nU4tWbJEH3zwgV577TVt2rRJP/nJT7ptJp/X1t%2BTzMxMHThwQIWFhTpy5IgWLlyo66%2B/XqNGjQrzzjvGc889p7feeksrVqzQ1Vdfbf6MPfcyanfLw%2BFwWH7GDhw4UJGRkerTp495Y3unZWLrhz4gRFNTk7FgwQIjOTnZGDt2rPH000%2BHe0udZtOmTUZCQoLln29%2B85tGQkKCYRiG8eGHHxp33323cdNNNxmTJk0y9u7dG%2BYdd74FCxaYn4NlGIbx0UcfdbtMTp8%2BbTz88MNGSkqKccsttxgFBQXmXHfMwzA%2B%2B3yfe%2B%2B91xg5cqRx2223WX5udMdMzv%2BMo7YyeP31143bb7/d8Hg8xr333mvU1NR09pY7VEJCgvnZcffdd1/Iz9mEhATL5zxd6XkYRuj3yOelp6dbPgfLMDonkwjDOO/DIwAAAHBZeIkQAADAZhQsAAAAm1GwAAAAbEbBAgAAsBkFCwAAwGYULAAAAJtRsAAAAGxGwQIAALAZBQsAAMBmFCwAAACbUbAAAABsRsECAACwGQULAADAZv8PWj9p8e4SpKoAAAAASUVORK5CYII%3D">
             </div>
      </div>
    </div><div class="row variablerow">
        <div class="col-md-3 namecol">
            <p class="h4">MaxTimeBtwClicks<br/><small>Numeric</small></p>
        </div>

        <div class="col-md-6">
            <div class="row">
                <div class="col-sm-6">
                    <table class="stats ">
                        <tr><th>Distinct count</th>
                        <td>535022</td></tr>
                        <tr><th>Unique (%)</th>
                        <td>51.5%</td></tr>
                        <tr class="alert"><th>Missing (%)</th>
                        <td>5.7%</td></tr>
                        <tr class="alert"><th>Missing (n)</th>
                        <td>62662</td></tr>
                    </table>

                </div>
                <div class="col-sm-6">
                    <table class="stats ">

                        <tr><th>Mean</th>
                        <td>6.1145</td></tr>
                        <tr><th>Minimum</th>
                        <td>0</td></tr>
                        <tr><th>Maximum</th>
                        <td>60</td></tr>
                        <tr class="ignore"><th>Zeros (%)</th>
                        <td>0.0%</td></tr>
                    </table>
                </div>
            </div>
        </div>
        <div class="col-md-3 collapse in" id="minihistogram1732830449">
             <img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAABCdJREFUeJzt3UFII1ccx/FfHBsTlF3DmknW2lIKli6lUMSDphUNCkIUAlKbgxcPHioIXjzqoQVvigjx0JMnDwHrwYMiiGshAUFvLRRE6EZ6SGa62tYsWpLweqrFbvnDhPVNxv19bgEf7y%2B8L3EehviUUgqaWZaFTCaDVCoF0zR1b08e4%2BZ58bkRCJFXNLq18Q8//Ypy1Vmb7xg%2BfPHsKQzDuKepiO5yLZDvnv%2BC08IrR2s%2Bijbj84%2Bj9zQR0esa3B6AqJ4xECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhEjAQIgEDIRIwECIBAyESMBAiAQMhErj2HYW1MBp8qFarta01DPh8vjc8ET10ngrk3VAA33z/I168vHa07oMnQXz71WdobPTUr0t1wHMn5sXLa8ffjktUKz6DEAkYCJGAgRAJPPcMUgveflGt3opAar39%2BrAtiIWxT2EYhuM9GdbD8FYEAtR2%2B/X%2Bk6DWsJRSAOA4rIe%2BDoBrV/SuBfJldzt%2Bvy47WvNeKIDnP//meK/2x001PWy1P25C4Y%2B/HK8zHzVh/fAMxT%2BdrX32tAUXr8pc9x%2BRR034evgTR2veFJ/6J2uNLMtCJpNBKpWCaZq6tyePcfO8uHKLZds20uk0bNt2Y3vyGDfPC695iQQMhEjAQIgEDIRI4Eog4XAYMzMzCIfDbmxPHuPmeXHlmpfIK/gnFpGAgRAJGAiRgIEQCRgIkYCBEAkYCJFAeyC7u7sYHR3F8PAw1tbWdG9PHnBwcICxsTEkEgksLi4CAE5PT5FKpZBIJDA7O4ubmxs9wyiNbNtW8XhcXV5eqkqloiYnJ1U2m9U5AtW58/Nz1dfXp4rFoqpUKmpiYkIdHh6qZDKpjo%2BPlVJKra6uquXlZS3zaH0HyeVy6OnpQWtrKwzDQDKZxM7Ojs4RqM7t7%2B9jZGQEpmnCMAysrKygs7MTpVIJ3d3dAIDx8XFt50brR26LxSIikcjt60gkgkKhoHMEqnP5fB5%2Bvx9TU1OwbRvxeBwDAwN3zo1pmigWi1rm0RqI%2Bp9/%2B2po4D0B/atarSKbzWJjYwPNzc2Ynp5GMBh87ed0nRutpzMSicCyrNvXlmUhGo3qHIHqXFtbG3p7exEKheD3%2BzE4OIh8Pn/n47a2bWs7N1oDicViODo6wsXFBcrlMra3t9Hf369zBKpz8XgcuVwOV1dXt%2B8mXV1dCAQCODk5AQBsbm5qOzfa/919b28P6XQa5XIZQ0NDmJub07k9ecDW1hbW19dRqVQQi8UwPz%2BPs7MzLCwsoFQqoaOjA0tLS2hpabn3Wfh5ECIBn5CJBAyESPA3zq9HJADzRfgAAAAASUVORK5CYII%3D">

        </div>
       <div class="col-md-12 text-right">
            <a role="button" data-toggle="collapse" data-target="#descriptives1732830449,#minihistogram1732830449" aria-expanded="false" aria-controls="collapseExample">
                Toggle details
            </a>
        </div>
        <div class="row collapse col-md-12" id="descriptives1732830449">
            <div class="col-sm-4">
                  <p class="h4">Quantile statistics</p>
                  <table class="stats indent">
                        <tr><th>Minimum</th>
                        <td>0</td></tr>
                        <tr><th>5-th percentile</th>