Metro Interstate Traffic Volume Forecasting/Metro_Interstate_Traffic_Volume-(Time Series Forecasts w. Facebook’s Prophet).ipynb

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   "source": [
    "For this project, I will analyze Metro Interstate Traffic Volume Data Set from UCI Machine Learning Repository.\n",
    "(http://archive.ics.uci.edu/ml/datasets/Metro+Interstate+Traffic+Volume)\n",
    "\n",
    "The data contains the following fields:\n",
    "\n",
    "\n",
    "| Columns Name | Description|\n",
    "|------|------|\n",
    "|holiday|Categorical US National holidays plus regional holiday, Minnesota State Fair |\n",
    "|temp|Numeric Average temp in kelvin |\n",
    "|rain_1h|Numeric Amount in mm of rain that occurred in the hour |\n",
    "|snow_1h|Numeric Amount in mm of snow that occurred in the hour |\n",
    "|clouds_all|Numeric Percentage of cloud cover|\n",
    "|weather_main|Categorical Short textual description of the current weather|\n",
    "|weather_description|Categorical Longer textual description of the current weather |\n",
    "|date_time|DateTime Hour of the data collected in local CST time |\n",
    "|traffic_volume|Numeric Hourly I-94 ATR 301 reported westbound traffic volume|\n",
    "\n",
    "\n",
    "I will try to do trafffic volume forecasting with Facebook Prophets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
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   "outputs": [],
   "source": [
    "#import libraries\n",
    "import warnings\n",
    "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "import pandas_profiling\n",
    "import datetime\n",
    "from fbprophet import Prophet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('Metro_Interstate_Traffic_Volume.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "      <td>2012-10-02 09:00:00</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>290.13</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>Clouds</td>\n",
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       "      <td>2012-10-02 12:00:00</td>\n",
       "      <td>5026</td>\n",
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       "      <th>4</th>\n",
       "      <td>None</td>\n",
       "      <td>291.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>broken clouds</td>\n",
       "      <td>2012-10-02 13:00:00</td>\n",
       "      <td>4918</td>\n",
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      "text/plain": [
       "  holiday    temp  rain_1h  snow_1h  clouds_all weather_main  \\\n",
       "0    None  288.28      0.0      0.0          40       Clouds   \n",
       "1    None  289.36      0.0      0.0          75       Clouds   \n",
       "2    None  289.58      0.0      0.0          90       Clouds   \n",
       "3    None  290.13      0.0      0.0          90       Clouds   \n",
       "4    None  291.14      0.0      0.0          75       Clouds   \n",
       "\n",
       "  weather_description            date_time  traffic_volume  \n",
       "0    scattered clouds  2012-10-02 09:00:00            5545  \n",
       "1       broken clouds  2012-10-02 10:00:00            4516  \n",
       "2     overcast clouds  2012-10-02 11:00:00            4767  \n",
       "3     overcast clouds  2012-10-02 12:00:00            5026  \n",
       "4       broken clouds  2012-10-02 13:00:00            4918  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
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   ],
   "source": [
    "df.head()"
   ]
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       "      <th>holiday</th>\n",
       "      <th>temp</th>\n",
       "      <th>rain_1h</th>\n",
       "      <th>snow_1h</th>\n",
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       "      <th>48199</th>\n",
       "      <td>None</td>\n",
       "      <td>283.45</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>broken clouds</td>\n",
       "      <td>2018-09-30 19:00:00</td>\n",
       "      <td>3543</td>\n",
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       "      <th>48200</th>\n",
       "      <td>None</td>\n",
       "      <td>282.76</td>\n",
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       "      <td>None</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>Thunderstorm</td>\n",
       "      <td>proximity thunderstorm</td>\n",
       "      <td>2018-09-30 21:00:00</td>\n",
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       "      <th>48202</th>\n",
       "      <td>None</td>\n",
       "      <td>282.09</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>90</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>overcast clouds</td>\n",
       "      <td>2018-09-30 22:00:00</td>\n",
       "      <td>1450</td>\n",
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       "      <th>48203</th>\n",
       "      <td>None</td>\n",
       "      <td>282.12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>overcast clouds</td>\n",
       "      <td>2018-09-30 23:00:00</td>\n",
       "      <td>954</td>\n",
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      "text/plain": [
       "      holiday    temp  rain_1h  snow_1h  clouds_all  weather_main  \\\n",
       "48199    None  283.45      0.0      0.0          75        Clouds   \n",
       "48200    None  282.76      0.0      0.0          90        Clouds   \n",
       "48201    None  282.73      0.0      0.0          90  Thunderstorm   \n",
       "48202    None  282.09      0.0      0.0          90        Clouds   \n",
       "48203    None  282.12      0.0      0.0          90        Clouds   \n",
       "\n",
       "          weather_description            date_time  traffic_volume  \n",
       "48199           broken clouds  2018-09-30 19:00:00            3543  \n",
       "48200         overcast clouds  2018-09-30 20:00:00            2781  \n",
       "48201  proximity thunderstorm  2018-09-30 21:00:00            2159  \n",
       "48202         overcast clouds  2018-09-30 22:00:00            1450  \n",
       "48203         overcast clouds  2018-09-30 23:00:00             954  "
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   "source": [
    "df.tail()"
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       "        <p class=\"h4\">Dataset info</p>\n",
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       "                <th>Number of variables</th>\n",
       "                <td>9 </td>\n",
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       "                <td>48204 </td>\n",
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       "                <th>Total Missing (%)</th>\n",
       "                <td>0.0% </td>\n",
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       "                <td>3.3 MiB </td>\n",
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       "                <td>72.0 B </td>\n",
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       "                <th>Text (Unique)</th>\n",
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       "        \n",
       "        <p class=\"h4\">Warnings</p>\n",
       "        <ul class=\"list-unstyled\"><li><a href=\"#pp_var_clouds_all\"><code>clouds_all</code></a> has 1988 / 4.1% zeros <span class=\"label label-info\">Zeros</span></li><li><a href=\"#pp_var_date_time\"><code>date_time</code></a> has a high cardinality: 40575 distinct values  <span class=\"label label-warning\">Warning</span></li><li><a href=\"#pp_var_rain_1h\"><code>rain_1h</code></a> is highly skewed (γ1 = 219.39)  <span class=\"label label-info\">Skewed</span></li><li><a href=\"#pp_var_rain_1h\"><code>rain_1h</code></a> has 44737 / 92.8% zeros <span class=\"label label-info\">Zeros</span></li><li><a href=\"#pp_var_snow_1h\"><code>snow_1h</code></a> is highly skewed (γ1 = 48.367)  <span class=\"label label-info\">Skewed</span></li><li><a href=\"#pp_var_snow_1h\"><code>snow_1h</code></a> has 48141 / 99.9% zeros <span class=\"label label-info\">Zeros</span></li><li>Dataset has 17 duplicate rows <span class=\"label label-warning\">Warning</span></li> </ul>\n",
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       "    <div class=\"row headerrow highlight\">\n",
       "        <h1>Variables</h1>\n",
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       "        <p class=\"h4 pp-anchor\" id=\"pp_var_clouds_all\">clouds_all<br/>\n",
       "            <small>Numeric</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-6\">\n",
       "    <div class=\"row\">\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "                <tr>\n",
       "                    <th>Distinct count</th>\n",
       "                    <td>60</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>0.1%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "\n",
       "        </div>\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "\n",
       "                <tr>\n",
       "                    <th>Mean</th>\n",
       "                    <td>49.362</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>100</td>\n",
       "                </tr>\n",
       "                <tr class=\"alert\">\n",
       "                    <th>Zeros (%)</th>\n",
       "                    <td>4.1%</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "<div class=\"col-md-3 collapse in\" id=\"minihistogram6404467641471815863\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAABKUlEQVR4nO3csW2EQBBA0ePkklzE9eTYPbmI62mdXmB9YSTEHryXI03ymWUDljHGuAF/uh89AMzs4%2BgBOK/Pr59/P/P8fuwwyXY2CASBQBAIhOm%2BQc5wbuU8bBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgTDdz6vZnx%2BEr2eDQLBBduRN/f5sEAgCgSAQCAKBIBAIl73FcsPEGpcN5Ey2xM46jlgQBAJBIBCWMcY4eohXztPXNttFyHSBwEwcsSAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCD8Ar2eH/sEs/QRAAAAAElFTkSuQmCC\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives6404467641471815863,#minihistogram6404467641471815863\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives6404467641471815863\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles6404467641471815863\"\n",
       "                                                  aria-controls=\"quantiles6404467641471815863\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram6404467641471815863\" aria-controls=\"histogram6404467641471815863\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common6404467641471815863\" aria-controls=\"common6404467641471815863\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme6404467641471815863\" aria-controls=\"extreme6404467641471815863\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Extreme Values</a></li>\n",
       "\n",
       "    </ul>\n",
       "\n",
       "    <div class=\"tab-content\">\n",
       "        <div role=\"tabpanel\" class=\"tab-pane active row\" id=\"quantiles6404467641471815863\">\n",
       "            <div class=\"col-md-4 col-md-offset-1\">\n",
       "                <p class=\"h4\">Quantile statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Minimum</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>1</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>1</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>64</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>90</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>90</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>100</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>100</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>89</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "            <div class=\"col-md-4 col-md-offset-2\">\n",
       "                <p class=\"h4\">Descriptive statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Standard deviation</th>\n",
       "                        <td>39.016</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.7904</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>-1.7423</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>49.362</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>36.9</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>-0.19726</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>2379457</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>1522.2</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>376.7 KiB</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-8 col-md-offset-2\" id=\"histogram6404467641471815863\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAAgAElEQVR4nO3df1zV9d3/8SdwUA4gQiHautlwCJZlyUTJNJYomSXq1GLZTCvrWpCEE3R%2B1XQWqZNZKdM5s1zq7Yp0uqbDH22XMy8z0ObMWhRg/miagKDyM359vn/s8lw7oy7R3sfDwcf9dju3Ou/P57w/r/frdqgnn8/nHLwsy7IEAAAAY7zdXQAAAEB7Q8ACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIbZ3F3AtaK0tNL4nN7eXrruugCVl1erudkyPv%2B1jN66Dr11LfrrOvTWdVzZ2y5dOhmdr7U4g%2BXBvL295OXlJW9vL3eX0u7QW9eht65Ff12H3rpOe%2BwtAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgWJsPWOXl5UpISFBeXp4k6bnnnlN0dLTT45ZbbtETTzwhSWpublZ0dLT69u3rtE9NTY0k6ezZs0pOTlZMTIxiY2OVmZmpxsZGx/EOHz6sBx98UNHR0YqPj9fGjRuv/qIBAIBHa9MB64MPPlBSUpJOnDjhGFuwYIEOHTrkeCxfvlxBQUH62c9%2BJkkqKipSQ0OD8vPznfbz9/eXJKWlpcnf31979%2B7Vpk2btH//fq1du1aSdP78eT311FMaM2aMDhw4oMzMTC1cuFAffvjhVV87AADwXG02YG3ZskXp6emaNm3aN%2B5TXl6u9PR0zZ49W5GRkZKkI0eOqFevXurQoUOL/Y8fP678/HxlZGTIbrere/fuSk5O1oYNGyRJu3btUnBwsB555BHZbDYNHDhQiYmJju0AAACt0Wb/2PPgwYOVmJgom832jSErKytLt912m0aNGuUYO3LkiL766iuNGzdO//jHPxQREaHp06fr%2B9//vgoLCxUcHKyuXbs69o%2BIiNCpU6d04cIFFRYWKioqyukYPXv21KZNmy6r9pKSEpWWljqN2Wz%2BCgsLu6x5LsXHx9vpnzCH3roOvXUt%2Bus69NZ12mNv22zA6tKly/%2B5/eTJk/rDH/7Q4h4pPz8/3X777Xr22WfVuXNnbdiwQU888YT%2B8Ic/qLq6Wna73Wn/i89ramq%2Bdrufn5/j/q3WysnJUXZ2ttNYSkqKUlNTL2ue1goKsl96J1wReus69Na16K/r0FvXaU%2B9bbMB61J%2B97vfOW5w/1cX78W66IknntDmzZu1Z88ede3aVbW1tU7bLz4PCAiQ3W5XZWWl0/a6ujoFBARcVm1JSUmKj493GrPZ/FVRUX1Z81yKj4%2B3goLsunChVk1NzUbnvtbRW9eht65Ff13HE3ubkLXX3SW02sHM%2B1zS25CQy/t/uCkeG7B27dqlxx9/vMX4Sy%2B9pOHDh6t3796Osfr6enXs2FGRkZE6d%2B6cysrKFBoaKkkqLi5Wt27d1KlTJ0VFRWnfvn1O8xUVFTnu72qtsLCwFpcDS0sr1djomh/IpqZml819raO3rkNvXYv%2Bug69dZ321FuPvNhZUVGh4uJi9e/fv8W2zz77TJmZmSotLVV9fb2ys7NVVVWlhIQEhYeHq1%2B/fnrxxRdVVVWlkydPasWKFRo/frwkKSEhQWVlZVq7dq0aGhr0/vvva%2BvWrRo3btzVXiIAAPBgHhmwvvjiC0lyuln9ooULF%2Bqmm27S6NGjFRsbq/z8fL3%2B%2BusKDg6WJC1btkyNjY0aOnSoHnroId19991KTk6WJIWEhOi1117Tjh07FBsbqzlz5mjOnDm68847r97iAACAx/OyLMtydxHXgtLSykvvdJlsNm%2BFhASooqK63ZxSbSvorevQW9eiv67jib0d8fK%2BS%2B/URhzMvM8lve3SpZPR%2BVrLI89gAQAAtGUELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAw2zuLgDfTszsHe4uodW2pw1ydwkAAFwVnMECAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIa12YCVm5ur3r17Kzo62vHIyMhwbN%2BzZ48SExPVt29fjRgxQrt373Z6/erVqxUXF6e%2Bfftq4sSJOnr06NVeAgAAuEa12YB15MgRjR49WocOHXI8lixZIkk6duyYpk6dqmeffVYHDx7U1KlTlZaWpjNnzkiStmzZonXr1mnNmjXKy8vTrbfeqtTUVFmW5c4lAQCAa0SbDli33Xbb127bsmWLYmJiNGzYMNlsNt1///3q37%2B/cnJyJElvvfWWJkyYoMjISHXs2FHTp0/XqVOnlJeXdzWXAAAArlFtMmA1Nzfr448/1l/%2B8hcNGTJEcXFxmjt3rs6fPy9JKioqUlRUlNNrevbsqYKCgq/d7uvrq/DwcMd2AAAAV7K5u4CvU15ert69e2v48OFatmyZKioqNHPmTGVkZOg3v/mNqqurZbfbnV7j5%2BenmpoaSbrkdlcrKSlRaWmp05jN5q%2BwsDCjx/HxaZP5%2BBvZbJ5T78XeelqPPQG9dS366zr01vXaU2/bZMAKDQ3Vhg0bHM/tdrsyMjL00EMPqaqqSna7XXV1dU6vqaurU0BAgGP//2u7q%2BXk5Cg7O9tpLCUlRampqVfl%2BG1VSMjV6b9JQUH2S%2B%2BEK0JvXYv%2Bug69dZ321Ns2GbAKCgq0bds2TZ8%2BXV5eXpKk%2Bvp6eXt7q0OHDoqKitLHH3/s9JqioiLHPVuRkZEqLCzUkCFDJEkNDQ06duxYi8uKrpKUlKT4%2BHinMZvNXxUV1UaP42lJ3/T6XcnHx1tBQXZduFCrpqZmd5fTrtBb16K/rkNvXc8VvXXXL/dtMmAFBwdrw4YN6ty5sx577DGVlJRoyZIl%2BuEPf6gOHTpo1KhRev3115Wbm6t7771Xu3btUn5%2BvmbPni1JGjdunJYvX664uDj16NFDL730kkJDQxUTE3NV6g8LC2txObC0tFKNjdf2D6Qnrr%2Bpqdkj6/YE9Na16K/r0FvXaU%2B9bZMBq1u3blq1apWWLl2qlStXqmPHjnrggQcc34MVERGhX/3qV8rKytLs2bN14403avny5erRo4ckafz48aqsrFRKSorKy8vVp08frVq1Sr6%2Bvu5cFgAAuEa0yYAlSQMGDNCbb775jdvvvvtu3X333V%2B7zcvLS48//rgef/xxV5UHAADwjTzrJh4AAAAPQMACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMKzNB6zy8nIlJCQoLy/PMbZz506NHj1a3//%2B9xUfH6/s7Gw1Nzc7to8YMUJ33HGHoqOjHY/i4mJJUk1NjWbNmqXY2Fj169dPM2bMUHV1teO1n3/%2BuSZNmqTo6GgNHjxYv/71r6/eYgEAQLvQpgPWBx98oKSkJJ04ccIx9tFHH2nGjBlKS0vTwYMHtXr1am3evFlr166VJFVVVenzzz9Xbm6uDh065HhERERIkp5//nmdPn1aO3fu1K5du3T69GllZWVJkhoaGvSTn/xEffr0UV5enn7zm99ow4YN2r59%2B1VfOwAA8FxtNmBt2bJF6enpmjZtmtP4P/7xD/3oRz/SkCFD5O3trYiICCUkJOjAgQOS/hnAgoODdeONN7aYs7a2Vlu3blVqaqqCg4N1/fXXKz09XZs3b1Ztba0OHDigkpISpaamqkOHDurdu7cmTpyoDRs2XJU1AwCA9qHNBqzBgwfrnXfe0f333%2B80Pnz4cM2aNcvxvK6uTn/5y1906623SpKOHDkiu92uH//4x4qNjdXYsWO1e/duSdLx48fV0NCgqKgox%2BsjIiJUV1enY8eOqbCwUD169FCHDh0c23v27KmCggJXLhUAALQzNncX8E26dOlyyX2qqqr07LPPys/PT5MnT5YkeXl5qU%2BfPvrpT3%2Bq73znO9qxY4emTp2q9evXq7GxUZLk7%2B/vmMNut0uSqqurVV1d7Xj%2Br9tramouq/aSkhKVlpY6jdls/goLC7useS7Fx6fN5uOvZbN5Tr0Xe%2BtpPfYE9Na16K/r0FvXa0%2B9bbMB61KOHj2q1NRUXX/99XrjjTcUGBgoSZoyZYrTfqNGjdK2bdu0c%2BdOJSYmSvrnpcKAgADHv0tSYGCg/P39Hc8v%2Btd9WysnJ0fZ2dlOYykpKUpNTb2sedqbkJDL62NbEBRkv/ROuCL01rXor%2BvQW9dpT731yIC1Z88e/fSnP9VDDz2k6dOny2b732WsWbNGvXv31sCBAx1j9fX16tixo3r06CFfX18VFRXpjjvukCQVFxfL19dX4eHhOnv2rI4dO6bGxkbHnEVFRYqMjLys%2BpKSkhQfH%2B80ZrP5q6Ki%2BhtecWU8LembXr8r%2Bfh4KyjIrgsXatXU1HzpF6DV6K1r0V/Xobeu54reuuuXe48LWH/729%2BUkpKi%2BfPna/z48S22nz59Whs3btTq1at1ww036Pe//70OHTqkn//857Lb7RoxYoSysrL0yiuvSJKysrI0cuRI%2Bfn5KTY2ViEhIfrlL3%2BptLQ0ff7551q3bl2LG%2B0vJSwsrMXlwNLSSjU2Xts/kJ64/qamZo%2Bs2xPQW9eiv65Db12nPfXW4wLWr3/9azU2NiozM1OZmZmO8X79%2BunVV1/VjBkz5O3trQkTJqiyslI9e/bUb37zG333u9%2BVJM2bN0%2BLFy9WYmKiGhoaNHToUM2dO1eSZLPZ9Nprr2nBggUaNGiQ/P39NXHiRI0dO9YtawUAAJ7Jy7Isy91FXAtKSyuNz2mzeSsha6/xeV1le9ogd5fQajabt0JCAlRRUd1ufptqK%2Bita9Ff1/HE3o54eZ%2B7S2i1g5n3uaS3Xbp0Mjpfa3nWTTwAAAAegIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAw4wGrqanJ9JQAAAAexXjAiouL0y9%2B8QsVFRWZnhoAAMAjGA9YzzzzjP76179q5MiRevDBB/Xmm2%2BqsrLS9GEAAADaLOMB6%2BGHH9abb76pHTt26K677tLq1as1ePBgTZ8%2BXe%2B9957pwwEAALQ5LrvJPTw8XNOmTdOOHTuUkpKiP//5z3riiScUHx%2Bv119/nXu1AABAu2Vz1cSHDx/W73//e%2BXm5qq%2Bvl4JCQkaO3aszpw5o1deeUVHjhzR0qVLXXV4AAAAtzEesFasWKG3335bx48fV58%2BfTRt2jSNHDlSgYGBjn18fHz03HPPmT40AABAm2A8YK1fv16jRo3S%2BPHj1bNnz6/dJyIiQunp6aYPDQAA0CYYD1jvvvuuqqqqdO7cOcdYbm6uBg4cqJCQEElS79691bt3b9OHBgAAaBOM3%2BT%2B97//XcOHD1dOTo5jbMmSJUpMTNRnn31m%2BnAAAABtjvGA9Ytf/EL33nuvpk2b5hj705/%2BpLi4OC1atMj04QAAANoc4wHr448/1lNPPaUOHTo4xnx8fPTUU0/pb3/7m%2BnDAQAAtDnGA1ZgYKBOnDjRYvzLL7%2BUn5%2Bf6cMBAAC0OcYD1vDhwzV//ny99957qqqqUnV1td5//30tWLBACQkJpg8HAADQ5hj/FOH06dN18uRJPf744/Ly8nKMJyQkaMaMGaYPBwAA0OYYP4Nlt9u1atUqbd%2B%2BXS%2B99JKys7O1fft2LVu2TAEBAZc9X3l5uRISEpSXl%2BcYO3z4sB588EFFR0crPj5eGzdudHrNli1blJCQoL59%2B2rs2LE6dOiQY1tTU5MWL16su%2B66S9HR0Xr66adVUlLi2H727FklJycrJiZGsbGxyszMVGNj4xV0AgAAXKtc9rcIe/Toofvuu09Dhw5VeHj4Fc3xwQcfKCkpyemervPnz%2Bupp57SmDFjdODAAWVmZmrhwoX68MMPJUl5eXl6/vnntWjRIh04cECjRo3S008/rdraWknSypUrtW/fPv3ud7/T3r175efnpzlz5jjmT0tLk7%2B/v/bu3atNmzZp//79Wrt27RX3AQAAXHuMB6zPP/9cjz32mG6//XbdcsstLR6ttWXLFqWnpzt93YMk7dq1S8HBwXrkkUdks9k0cOBAJSYmasOGDZKkjRs36oEHHlC/fv3k6%2BuryZMnKyQkRLm5uY7tTz75pG644QYFBgZq9uzZevfdd3Xy5EkdP35c%2Bfn5ysjIkN1uV/fu3ZWcnOyYGwAAoDWM34M1f/58nTp1Sunp6erUqdMVzzN48GAlJibKZrM5hazCwkJFRUU57duzZ09t2rRJklRUVKRx48a12F5QUKDKykp9%2BeWXTq8PDQ1V586d9emnn0qSgoOD1bVrV8f2iIgInTp1ShcuXFBQUFCrai8pKVFpaanTmM3mr7CwsFa9vrV8fFx2AtIlbDbPqfdibz2tx56A3roW/XUdeut67am3xgPWoUOH9Nvf/lbR0dHfap4uXbp87Xh1dbXsdrvTmJ%2Bfn2pqai65vbq6WpLk7%2B/fYvvFbf/%2B2ovPa2pqWh2wcnJylJ2d7TSWkpKi1NTUVr2%2BvQoJufx78NwtKMh%2B6Z1wReita9Ff16G3rtOeems8YIWEhFzRzeytZbfbVVlZ6TRWV1fnOKbdblddXV2L7SEhIY6wdPF%2BrH9/vWVZLbZdfH45a0pKSlJ8fLzTmM3mr4qK6lbP0RqelvRNr9%2BVfHy8FRRk14ULtWpqanZ3Oe0KvXUt%2Bus69Nb1XNFbd/1ybzxgTZw4UUuXLtWSJUu%2B1SXCbxIVFaV9%2B/Y5jRUVFSkyMlKSFBkZqcLCwhbb4%2BLi1LlzZ3Xt2lVFRUWOy4SlpaU6d%2B6coqKi1NzcrHPnzqmsrEyhoaGSpOLiYnXr1u2y1hIWFtbicmBpaaUaG6/tH0hPXH9TU7NH1u0J6K1r0V/Xobeu0556a/wUyJ49e7Rv3z7Fxsbq7rvv1tChQ50e31ZCQoLKysq0du1aNTQ06P3339fWrVsd912NHz9eW7du1fvvv6%2BGhgatXbtWZ8%2BedXzJ6dixY7Vy5UqdPHlSVVVVevHFFzVgwADddNNNCg8PV79%2B/fTiiy%2BqqqpKJ0%2Be1IoVKzR%2B/PhvXTcAALh2GD%2BDFRsbq9jYWNPTOoSEhOi1115TZmamli1bpuuuu05z5szRnXfeKUkaOHCg5s2bp/nz5%2BvMmTPq2bOnVq9ereDgYEn/vBeqsbFRjzzyiKqrqxUbG6uXX37ZMf%2ByZcu0YMECDR06VN7e3hozZoySk5Ndth4AAND%2BeFmWZbm7iGtBaWnlpXe6TDabtxKy9hqf11W2pw1ydwmtZrN5KyQkQBUV1e3mdHVbQW9di/66jif2dsTL%2By69UxtxMPM%2Bl/S2Sxfztyu1hkvuki4oKNCsWbP0ox/9SGfOnNGGDRucvokdAACgPTMesD766CM9%2BOCD%2BuKLL/TRRx%2Bpvr5en3zyiR5//HHt3r3b9OEAAADaHOMBKysrS48//rjWrVsnX19fSdILL7ygRx99tMV3QwEAALRHLjmDNWbMmBbjDz/8sI4ePWr6cAAAAG2O8YDl6%2BurqqqqFuOnTp1q8S3pAAAA7ZHxgDVs2DD98pe/VEVFhWOsuLhYmZmZuueee0wfDgAAoM0xHrBmzpypuro63XXXXaqtrdXYsWM1cuRI2Ww2zZgxw/ThAAAA2hzjXzQaGBioN998U/v379ff//53NTc3KyoqSnfffbe8vT3rb%2BcBAABcCeMB66KBAwdq4MCBrpoeAACgzTIesOLj4%2BXl5fWN2//85z%2BbPiQAAECbYjxg/fCHP3QKWA0NDTp%2B/LjeffddpaWlmT4cAABAm2M8YE2dOvVrx9evX68PPvhAjz76qOlDAgAAtClX7a7zIUOGaM%2BePVfrcAAAAG5z1QJWfn6%2BOnbseLUOBwAA4DbGLxH%2B%2ByVAy7JUVVWlTz/9lMuDAADgmmA8YH3nO99p8SlCX19fTZo0SYmJiaYPBwAA0OYYD1iLFi0yPSUAAIBHMR6wDhw40Op9%2B/fvb/rwAAAAbmc8YE2ePFmWZTkeF128bHhxzMvLS5988onpwwMAALid8YC1fPlyLVy4UDNnztSdd94pX19fHT58WPPnz9eECRM0ZMgQ04cEAABoU4x/TcPixYs1b948DRs2TIGBgerYsaMGDBigBQsW6LXXXtONN97oeAAAALRHxgNWSUmJbrjhhhbjgYGBqqioMH04AACANsd4wOrbt6%2BWLl2qqqoqx9i5c%2Be0ZMkSDRw40PThAAAA2hzj92DNmTNHkyZNUlxcnMLDwyVJn3/%2Bubp06aI33njD9OEAAADaHOMBKyIiQrm5udq6dauKi4slSRMmTNADDzwgu91u%2BnAAAABtjvGAJUlBQUF68MEH9cUXX6h79%2B6S/vlt7gAAANcC4/dgWZalrKws9e/fXyNHjtSXX36pmTNnatasWWpoaDB9OAAAgDbHeMBat26d3n77bc2bN08dOnSQJA0bNkz/9V//pVdeecX04QAAANoc4wErJydHzz33nMaOHev49vb7779fmZmZ%2BuMf/2j6cAAAAG2O8YD1xRdf6JZbbmkx3qtXL5WVlZk%2BHAAAQJtjPGDdeOON%2BvDDD1uM79mzx3HDOwAAQHtm/FOETzzxhH7%2B85/rzJkzsixL%2B/fv15tvvql169Zp1qxZpg8HAADQ5hgPWOPGjVNjY6NWrlypuro6Pffcc7r%2B%2Bus1bdo0Pfzww6YPBwAA0OYYD1h/%2BMMfdN999ykpKUnl5eWyLEvXX3%2B98WPMmzfPaeziV0B89NFHmjJlivLy8mSz/e/yXnnlFcXFxampqUlZWVl6%2B%2B23VVtbqzvvvFM///nPFRYWJkk6e/as5s6dq/z8fPn4%2BGjUqFGaOXOm01wAAAD/F%2BP3YL3wwguOm9mvu%2B464%2BFKkkaNGqVDhw45Hjt27FBwcLAyMzMl/TNkrVmzxmmfuLg4SdLKlSu1b98%2B/e53v9PevXvl5%2BenOXPmOOZOS0uTv7%2B/9u7dq02bNmn//v1au3at8TUAAID2y3jACg8P16effmp62m9kWZYyMjJ0zz33aPTo0Tp58qTOnz%2Bv3r17f%2B3%2BGzdu1JNPPqkbbrhBgYGBmj17tt59912dPHlSx48fV35%2BvjIyMmS329W9e3clJydrw4YNV209AADA8xm/7hUZGan09HS9%2BuqrCg8PV8eOHZ22L1y40Ojx3n77bRUVFWnFihWSpCNHjiggIEDTpk3TkSNHFBoaqsmTJ2v8%2BPGqrKzUl19%2BqaioKMfrQ0ND1blzZ0coDA4OVteuXR3bIyIidOrUKV24cEFBQUFGawcAAO2T8YB14sQJ9evXT5JUWlpqenonzc3NWrlypX7yk58oMDBQklRfX6%2B%2Bfftq2rRpioyMVF5enqZOnaqAgABFR0dLkvz9/Z3m8fPzU3V1tSS1%2BIPUF5/X1NS0OmCVlJS0WLvN5u%2B4z8sUHx/jJyBdymbznHov9tbTeuwJ6K1r0V/Xobeu1556ayRgLVy4UM8%2B%2B6z8/f21bt06E1O2Sl5enkpKSjR%2B/HjH2JgxYzRmzBjH88GDB2vMmDHavn277rrrLklSbW2t0zx1dXUKCAiQZVkttl18HhAQ0Oq6cnJylJ2d7TSWkpKi1NTUVs/RHoWEtL6HbUVQkP3SO%2BGK0FvXor%2BuQ29dpz311kjAeuONN/TUU085nRl64okntHDhQuNnbf7Vzp07lZCQ4HTcTZs2KSAgQCNGjHCM1dfXq2PHjurcubO6du2qoqIix2XC0tJSnTt3TlFRUWpubta5c%2BdUVlam0NBQSVJxcbG6deumTp06tbqupKQkxcfHO43ZbP6qqKj%2BNsttwdOSvun1u5KPj7eCguy6cKFWTU3N7i6nXaG3rkV/XYfeup4reuuuX%2B6NBCzLslqM/fWvf9VXX31lYvpv9MEHH%2BjRRx91GquqqtLSpUv13e9%2BVzfffLPeffddbdu2TWvWrJEkjR07VitXrlSfPn0UEhKiF198UQMGDNBNN90kSerXr59efPFFLViwQBUVFVqxYoXTGbLWCAsLaxEsS0sr1dh4bf9AeuL6m5qaPbJuT0BvXYv%2Bug69dZ321FuP/nKnL774okWQmTRpkmpqavTMM8/o7Nmz6t69uxYvXqyYmBhJ/7xU19jYqEceeUTV1dWKjY3Vyy%2B/7Hj9smXLtGDBAg0dOlTe3t4aM2aMkpOTr%2Bq6AACAZ/PogHXo0KEWY15eXkpOTv7GUOTr66v09HSlp6d/7fbQ0FAtW7bMaJ0AAODaYuwmHi8vL1NTAQAAeDRjZ7BeeOEFp%2B%2B8amho0JIlS1p8%2Bs7092ABAAC0NUYCVv/%2B/Vt871N0dLQqKipUUVFh4hAAAAAew0jAuuspaoEAABTmSURBVJrffQUAANDWedYXKQEAAHgAAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAY5rEBKzc3V71791Z0dLTjkZGRIUnas2ePEhMT1bdvX40YMUK7d%2B92eu3q1asVFxenvn37auLEiTp69KhjW01NjWbNmqXY2Fj169dPM2bMUHV19VVdGwAA8Gw2dxdwpY4cOaLRo0dr4cKFTuPHjh3T1KlTtXTpUt1zzz3atWuX0tLStGvXLnXt2lVbtmzRunXrtGbNGt1000166aWXlJqaqq1bt8rLy0vPP/%2B8Tp8%2BrZ07d6qpqUlpaWnKysrSvHnz3LRSAGi/Rry8z90lXJaDmfe5uwR4CI89g3XkyBHddtttLca3bNmimJgYDRs2TDabTffff7/69%2B%2BvnJwcSdJbb72lCRMmKDIyUh07dtT06dN16tQp5eXlqba2Vlu3blVqaqqCg4N1/fXXKz09XZs3b1Ztbe3VXiIAAPBQHhmwmpub9fHHH%2Bsvf/mLhgwZori4OM2dO1fnz59XUVGRoqKinPbv2bOnCgoKJKnFdl9fX4WHh6ugoEDHjx9XQ0OD0/aIiAjV1dXp2LFjV2VtAADA83nkJcLy8nL17t1bw4cP17Jly1RRUaGZM2cqIyND9fX1stvtTvv7%2BfmppqZGklRdXf2N26uqqiRJ/v7%2Bjm0X972c%2B7BKSkpUWlrqNGaz%2BSssLKz1i2wFHx/Pysc2m%2BfUe7G3ntZjT0BvXYv%2Buh69dZ321FuPDFihoaHasGGD47ndbldGRoYeeughxcbGqq6uzmn/uro6BQQEOPb9pu0Xg1Vtba1j/4uXBgMDA1tdX05OjrKzs53GUlJSlJqa2uo52qOQkAB3l3DZgoLsl94JV4Teuhb9dR166zrtqbceGbAKCgq0bds2TZ8%2BXV5eXpKk%2Bvp6eXt76/bbb9cnn3zitH9RUZHjfq3IyEgVFhZqyJAhkqSGhgYdO3ZMUVFR6tGjh3x9fVVUVKQ77rhDklRcXOy4jNhaSUlJio%2BPdxqz2fxVUWH204ielvRNr9%2BVfHy8FRRk14ULtWpqanZ3Oe0KvXUt%2But69NZ1XNFbd/1y75EBKzg4WBs2bFDnzp312GOPqaSkREuWLNEPf/hDjRkzRr/97W%2BVm5ure%2B%2B9V7t27VJ%2Bfr5mz54tSRo3bpyWL1%2BuuLg49ejRQy%2B99JJCQ0MVExMjX19fjRgxQllZWXrllVckSVlZWRo5cqT8/PxaXV9YWFiLy4GlpZVqbLy2fyA9cf1NTc0eWbcnoLeuRX9dh966TnvqrUcGrG7dumnVqlVaunSpVq5cqY4dO%2BqBBx5QRkaGOnbsqF/96lfKysrS7NmzdeONN2r58uXq0aOHJGn8%2BPGqrKxUSkqKysvL1adPH61atUq%2Bvr6SpHnz5mnx4sVKTExUQ0ODhg4dqrlz57pzuQAAwMN4WZZlubuIa0FpaaXxOW02byVk7TU%2Br6tsTxvk7hJazWbzVkhIgCoqqtvNb1NtBb11LU/rryd%2BD5an9FbyrP66qrddunQyOl9redZNPAAAAB6AgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGeeT3YAHwbDGzd7i7hMviSV8xAqBt4AwWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhnlswCooKNBjjz2mAQMGaNCgQZoxY4bKy8slSfPmzdNtt92m6OhoxyMnJ8fx2tWrVysuLk59%2B/bVxIkTdfToUce2mpoazZo1S7GxserXr59mzJih6urqq74%2BAADguTwyYNXV1WnKlCmKjo7Wf//3f2vbtm06d%2B6c/t//%2B3%2BSpCNHjuj555/XoUOHHI%2BkpCRJ0pYtW7Ru3TqtWbNGeXl5uvXWW5WamirLsiRJzz//vE6fPq2dO3dq165dOn36tLKysty2VgAA4Hk8MmCdOnVKN998s1JSUtShQweFhIQoKSlJBw4cUH19vT777DPddtttX/vat956SxMmTFBkZKQ6duyo6dOn69SpU8rLy1Ntba22bt2q1NRUBQcH6/rrr1d6ero2b96s2traq7xKAADgqWzuLuBKfO9739Orr77qNLZz507deuutKigoUGNjo5YtW6YPPvhAnTp10rhx4zRlyhR5e3urqKhITz75pON1vr6%2BCg8PV0FBgYKDg9XQ0KCoqCjH9oiICNXV1enYsWO65ZZbWlVfSUmJSktLncZsNn%2BFhYV9i1W35OPjWfnYZvOcei/21tN67Ak8sae8d/Gv6K3rtKfeemTA%2BleWZenll1/W7t27tX79epWVlWnAgAGaOHGili5dqk8%2B%2BUQpKSny9vbWlClTVF1dLbvd7jSHn5%2BfampqVFVVJUny9/d3bLu47%2BXch5WTk6Ps7GynsZSUFKWmpl7pMtuFkJAAd5dw2YKC7JfeCe0e7138K3rrOu2ptx4dsKqqqjRr1ix9/PHHWr9%2BvXr16qVevXpp0KBBjn1uv/12TZo0Sbm5uZoyZYrsdrvq6uqc5qmrq1NAQIAjWNXW1iogIMDx75IUGBjY6rqSkpIUHx/vNGaz%2BauiwuzN8p6W9E2v35V8fLwVFGTXhQu1ampqdnc57YqnvW8l3rtwRm9dxxW9ddcvSB4bsE6cOKEnn3xS3/nOd7Rp0yZdd911kqQ//elPKisr049%2B9CPHvvX19fLz85MkRUZGqrCwUEOGDJEkNTQ06NixY4qKilKPHj3k6%2BuroqIi3XHHHZKk4uJix2XE1goLC2txObC0tFKNjdf2D6Qnrr%2Bpqdkj64ZZnvge4L3rOvTWddpTbz3vV0lJ58%2Bf16RJk/T9739fa9ascYQr6Z%2BXDBcuXKj9%2B/fLsiwdOnRIb7zxhuNThOPGjdP69etVUFCgr776Sr/85S8VGhqqmJgY2e12jRgxQllZWSovL1d5ebmysrI0cuRIR0ADAAC4FI88g7V582adOnVK27dv144dO5y2HTp0SLNmzdL8%2BfN15swZhYaGaurUqRo9erQkafz48aqsrFRKSorKy8vVp08frVq1Sr6%2BvpL%2B%2BR1aixcvVmJiohoaGjR06FDNnTv3qq8RAAB4Li/r4hdAwaVKSyuNz2mzeSsha6/xeV1le9qgS%2B/URths3goJCVBFRXW7OV3dVnja%2B1bivetKI17e5%2B4SLsvBzPs8preSZ/XXVb3t0qWT0flayyMvEQIAALRlBCwAAADDPPIeLOBqiJm949I7tSGedBkLANo7zmABAAAYRsACAAAwjIAFAABgGAELAADAMG5yB4B2xtM%2BoAG0R5zBAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhtncXQAAAJ4iZvYOd5cAD8EZLAAAAMM4gwW0EyNe3ufuEgAA/4OA9TXOnj2ruXPnKj8/Xz4%2BPho1apRmzpwpm412fRsEAADAtYLE8DXS0tLUtWtX7d27V2VlZXr66ae1du1aTZkyxd2lAXADfjkAcLm4B%2BvfHD9%2BXPn5%2BcrIyJDdblf37t2VnJysDRs2uLs0AADgIQhY/6awsFDBwcHq2rWrYywiIkKnTp3ShQsX3FgZAADwFFwi/DfV1dWy2%2B1OYxef19TUKCgo6JJzlJSUqLS01GnMZvNXWFiYuUIl%2BfiQjwEA7Ud7%2Bv8aAevf%2BPv7q7a21mns4vOAgIBWzZGTk6Ps7GynsWeeeUZTp041U%2BT/KCkp0aRuhUpKSjIe3q51JSUlysnJobcuQG9di/66Dr11nZKSEi1fvrxd9bb9REVDIiMjde7cOZWVlTnGiouL1a1bN3Xq1KlVcyQlJWnz5s1Oj6SkJOO1lpaWKjs7u8XZMnx79NZ16K1r0V/Xobeu0x57yxmsfxMeHq5%2B/frpxRdf1IIFC1RRUaEVK1Zo/PjxrZ4jLCys3SRwAABw%2BTiD9TWWLVumxsZGDR06VA899JDuvvtuJScnu7ssAADgITiD9TVCQ0O1bNkyd5cBAAA8lM/8%2BfPnu7sIXLmAgAANGDCg1Tfgo/XorevQW9eiv65Db12nvfXWy7Isy91FAAAAtCfcgwUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABuOqampo0ceJE/exnP3OM7dmzR4mJierbt69GjBih3bt3u7FCAPh2CFgArrrs7GwdPHjQ8fzYsWOaOnWqnn32WR08eFBTp05VWlqazpw548YqAeDKEbA81NmzZ5WcnKyYmBjFxsYqMzNTjY2N7i7LIxUUFOixxx7TgAEDNGjQIM2YMUPl5eWSpMOHD%2BvBBx9UdHS04uPjtXHjRjdX6/n279%2BvXbt26d5773WMbdmyRTExMRo2bJhsNpvuv/9%2B9e/fXzk5OW6stG07d%2B6cZsyYodjYWPXv31/JyckqKSmRxPvWhI8//liPPPKIYmJiNHjwYL3wwguqr6%2BXxNnWK1VeXq6EhATl5eU5xi71Xt2yZYsSEhLUt29fjR07VocOHbraZV85Cx7pxz/%2BsTV9%2BnSrpqbGOnHihPXAAw9Yq1evdndZHqe2ttYaNGiQ9corr1hfffWVVV5ebj355JPWf/zHf1jnzp2zBgwYYK1fv95qaGiw3nvvPSs6Oto6fPiwu8v2WGVlZdaQIUOsTz75xJo5c6Y1c%2BZMy7IsKzk52Vq4cKHTvgsXLrSefvppd5TpEX784x9bKSkp1vnz563KykrrmWeesZ566inetwY0NTVZgwYNsn77299aTU1N1unTp63hw4db2dnZ1ueff2716dPHeuedd6yGhgbrj3/8o3X77bdbX375pbvLbtMOHjxoDRs2zIqKirLef/99y7KsS75X33//fSs6Oto6ePCgVV9fb73%2B%2ButWbGysVVNT486ltBpnsDzQ8ePHlZ%2Bfr4yMDNntdnXv3l3JycnasGGDu0vzOKdOndLNN9%2BslJQUdejQQSEhIUpKStKBAwe0a9cuBQcH65FHHpHNZtPAgQOVmJhIn69Qc3OzMjIy9Nhjj%2Bnmm2922lZdXS273e405ufnp5qamqtZosf46KOPdPjwYS1atEhBQUEKDAzU888/r/T0dN63Bpw/f16lpaVqbm6W9T9/Tc7b21t2u52zrVdgy5YtSk9P17Rp05zGL/Ve3bhxox544AH169dPvr6%2Bmjx5skJCQpSbm%2BuOZVw2ApYHKiwsVHBwsLp27eoYi4iI0KlTp3ThwgU3VuZ5vve97%2BnVV1%2BVj4%2BPY2znzp269dZbVVhYqKioKKf9e/bsqYKCgqtdZruwatUqdejQQRMnTmyxzW63q66uzmmsrq6u3fzRV9M%2B/PBD9ezZU2%2B99ZYSEhI0ePBgLV68WF26dOF9a0BISIgmT56sxYsXq0%2BfPvrBD36g8PBwTZ48WUVFRfT3Mg0ePFjvvPOO7r//fqfxS71XPb3XBCwP9HW/7V98zm/8V86yLL300kvavXu3Zs%2BezVkVw95%2B%2B23l5%2BcrJiZGMTEx2rZtm7Zt26aYmBhFRUWpsLDQaf%2BioiJFRka6qdq27fz58/r000917NgxbdmyRb///e915swZzZw5k/etAc3NzfLz89PcuXP1t7/9Tdu2bVNxcbGWLVtGf69Aly5dZLPZWoxfqpee3msClgfy9/dXbW2t09jF5/zGf2WqqqqUmpqqrVu3av369erVqxdnVQzbsWOH/vrXv%2BrgwYM6ePCgRo4cqZEjR%2BrgwYMaNWqU8vPzlZubq8bGRuXm5io/P1%2BjR492d9ltUocOHSRJs2fPVmBgoEJDQ5WWlqY9e/bIsizet9/SO%2B%2B8o507d2rChAnq0KGDIiMjlZKSov/8z//kvwsGXaqXnt5rApYHioyM1Llz51RWVuYYKy4uVrdu3dSpUyc3VuaZTpw4oXHjxqmqqkqbNm1Sr169JImzKldRRESEfvWrX2nVqlXq37%2B/VqxYoeXLl6tHjx7uLq1N6tmzp5qbm9XQ0OAYa25uliTdcsstvG%2B/pdOnTzs%2BMXiRzWaTr68v/10w6FK9jIyM9Oxeu/kme1yhhx9%2B2Jo2bZpVWVnp%2BBThsmXL3F2Wxzl37px1zz33WD/72c%2BspqYmp23l5eVWTEyM9frrr1v19fXW/v37rejoaGv//v1uqhb4p/r6eishIcGaOnWqVVVVZZ09e9Z69NFHrZSUFN63BhQWFlq33XabtXLlSquxsdE6ceKENXLkSGvRokVWUVGR1adPH%2BuPf/yj41OEffr0sY4ePerusj3Cv36K8FLv1YufKty/f7/jU4T9%2B/e3Kioq3LmEVvOyrP/5iAQ8SllZmRYsWKC8vDx5e3trzJgxSk9Pd7pZG5f2%2Buuva9GiRbLb7fLy8nLadujQIR05ckSZmZn67LPPdN111yk5OVljx451U7XA/zpz5owWLVqkAwcO6KuvvlJ8fLxmz56toKAg3rcGvPfee3r55Zd19OhRderUSaNGjXJ82njv3r3KysrSiRMndOONNyojI0M/%2BMEP3F2yR%2BjVq5feeOMNxcbGStIl36tvv/22Vq5cqTNnzqhnz56aM2eO7rjjDneVf1kIWAAAAIZxDxYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYNj/B3HoKBHJ6YpdAAAAAElFTkSuQmCC\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common6404467641471815863\">\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">90</td>\n",
       "        <td class=\"number\">16442</td>\n",
       "        <td class=\"number\">34.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1</td>\n",
       "        <td class=\"number\">12761</td>\n",
       "        <td class=\"number\">26.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:77%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">75</td>\n",
       "        <td class=\"number\">5069</td>\n",
       "        <td class=\"number\">10.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:31%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">40</td>\n",
       "        <td class=\"number\">3993</td>\n",
       "        <td class=\"number\">8.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:25%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0</td>\n",
       "        <td class=\"number\">1988</td>\n",
       "        <td class=\"number\">4.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:12%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20</td>\n",
       "        <td class=\"number\">1849</td>\n",
       "        <td class=\"number\">3.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:12%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">64</td>\n",
       "        <td class=\"number\">1558</td>\n",
       "        <td class=\"number\">3.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:10%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">5</td>\n",
       "        <td class=\"number\">1094</td>\n",
       "        <td class=\"number\">2.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">92</td>\n",
       "        <td class=\"number\">776</td>\n",
       "        <td class=\"number\">1.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:5%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">12</td>\n",
       "        <td class=\"number\">273</td>\n",
       "        <td class=\"number\">0.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:2%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (50)</td>\n",
       "        <td class=\"number\">2401</td>\n",
       "        <td class=\"number\">5.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:15%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\"  id=\"extreme6404467641471815863\">\n",
       "            <p class=\"h4\">Minimum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">0</td>\n",
       "        <td class=\"number\">1988</td>\n",
       "        <td class=\"number\">4.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:16%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1</td>\n",
       "        <td class=\"number\">12761</td>\n",
       "        <td class=\"number\">26.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">3</td>\n",
       "        <td class=\"number\">3</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">4</td>\n",
       "        <td class=\"number\">3</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "            <p class=\"h4\">Maximum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">96</td>\n",
       "        <td class=\"number\">14</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:15%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">97</td>\n",
       "        <td class=\"number\">8</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:9%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">98</td>\n",
       "        <td class=\"number\">21</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:23%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">99</td>\n",
       "        <td class=\"number\">44</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:47%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">100</td>\n",
       "        <td class=\"number\">94</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "</div><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_date_time\">date_time<br/>\n",
       "            <small>Categorical</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-3\">\n",
       "    <table class=\"stats \">\n",
       "        <tr class=\"alert\">\n",
       "            <th>Distinct count</th>\n",
       "            <td>40575</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <th>Unique (%)</th>\n",
       "            <td>84.2%</td>\n",
       "        </tr>\n",
       "        <tr class=\"ignore\">\n",
       "            <th>Missing (%)</th>\n",
       "            <td>0.0%</td>\n",
       "        </tr>\n",
       "        <tr class=\"ignore\">\n",
       "            <th>Missing (n)</th>\n",
       "            <td>0</td>\n",
       "        </tr>\n",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-6 collapse in\" id=\"minifreqtable5899988660845862940\">\n",
       "    <table class=\"mini freq\">\n",
       "        <tr class=\"\">\n",
       "    <th>2013-04-18 22:00:00</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:1%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 0.0%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        6\n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>2013-05-19 10:00:00</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:1%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 0.0%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        6\n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>2013-12-03 13:00:00</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:1%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 0.0%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        5\n",
       "    </td>\n",
       "</tr><tr class=\"other\">\n",
       "    <th>Other values (40572)</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:100%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 100.0%\">\n",
       "            48187\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr>\n",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#freqtable5899988660845862940, #minifreqtable5899988660845862940\"\n",
       "       aria-expanded=\"true\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 extrapadding collapse\" id=\"freqtable5899988660845862940\">\n",
       "    \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">2013-04-18 22:00:00</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2013-05-19 10:00:00</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2013-12-03 13:00:00</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2016-12-25 02:00:00</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2012-10-25 15:00:00</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2016-05-27 18:00:00</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2013-06-01 02:00:00</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2013-05-31 02:00:00</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2013-04-11 01:00:00</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2013-05-21 23:00:00</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (40565)</td>\n",
       "        <td class=\"number\">48152</td>\n",
       "        <td class=\"number\">99.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "</div>\n",
       "</div><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_holiday\">holiday<br/>\n",
       "            <small>Categorical</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-3\">\n",
       "    <table class=\"stats \">\n",
       "        <tr class=\"\">\n",
       "            <th>Distinct count</th>\n",
       "            <td>12</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <th>Unique (%)</th>\n",
       "            <td>0.0%</td>\n",
       "        </tr>\n",
       "        <tr class=\"ignore\">\n",
       "            <th>Missing (%)</th>\n",
       "            <td>0.0%</td>\n",
       "        </tr>\n",
       "        <tr class=\"ignore\">\n",
       "            <th>Missing (n)</th>\n",
       "            <td>0</td>\n",
       "        </tr>\n",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-6 collapse in\" id=\"minifreqtable-6629287863723574548\">\n",
       "    <table class=\"mini freq\">\n",
       "        <tr class=\"\">\n",
       "    <th>None</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:100%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 99.9%\">\n",
       "            48143\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>Labor Day</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:1%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 0.0%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        7\n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>Martin Luther King Jr Day</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:1%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 0.0%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        6\n",
       "    </td>\n",
       "</tr><tr class=\"other\">\n",
       "    <th>Other values (9)</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:1%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 0.1%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        48\n",
       "    </td>\n",
       "</tr>\n",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#freqtable-6629287863723574548, #minifreqtable-6629287863723574548\"\n",
       "       aria-expanded=\"true\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 extrapadding collapse\" id=\"freqtable-6629287863723574548\">\n",
       "    \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">None</td>\n",
       "        <td class=\"number\">48143</td>\n",
       "        <td class=\"number\">99.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Labor Day</td>\n",
       "        <td class=\"number\">7</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Martin Luther King Jr Day</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Thanksgiving Day</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Christmas Day</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">New Years Day</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Veterans Day</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Columbus Day</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">State Fair</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Independence Day</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (2)</td>\n",
       "        <td class=\"number\">10</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "</div>\n",
       "</div><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_rain_1h\">rain_1h<br/>\n",
       "            <small>Numeric</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-6\">\n",
       "    <div class=\"row\">\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "                <tr>\n",
       "                    <th>Distinct count</th>\n",
       "                    <td>372</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>0.8%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "\n",
       "        </div>\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "\n",
       "                <tr>\n",
       "                    <th>Mean</th>\n",
       "                    <td>0.33426</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>9831.3</td>\n",
       "                </tr>\n",
       "                <tr class=\"alert\">\n",
       "                    <th>Zeros (%)</th>\n",
       "                    <td>92.8%</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "<div class=\"col-md-3 collapse in\" id=\"minihistogram4674101350673835189\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAAA%2B0lEQVR4nO3VsQkCURBFUVcsaYuwJ2N7sgh7GnORCxvI3%2BCcfOAll9lmZi7AT9fVA%2BDMbqsHfNsfr8M37%2Bf9D0vAB4EkEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCNvMzOoRcFY%2BCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCIQP2hsLj2bol0UAAAAASUVORK5CYII%3D\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives4674101350673835189,#minihistogram4674101350673835189\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives4674101350673835189\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles4674101350673835189\"\n",
       "                                                  aria-controls=\"quantiles4674101350673835189\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram4674101350673835189\" aria-controls=\"histogram4674101350673835189\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common4674101350673835189\" aria-controls=\"common4674101350673835189\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme4674101350673835189\" aria-controls=\"extreme4674101350673835189\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Extreme Values</a></li>\n",
       "\n",
       "    </ul>\n",
       "\n",
       "    <div class=\"tab-content\">\n",
       "        <div role=\"tabpanel\" class=\"tab-pane active row\" id=\"quantiles4674101350673835189\">\n",
       "            <div class=\"col-md-4 col-md-offset-1\">\n",
       "                <p class=\"h4\">Quantile statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Minimum</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>0.3</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>9831.3</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>9831.3</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "            <div class=\"col-md-4 col-md-offset-2\">\n",
       "                <p class=\"h4\">Descriptive statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Standard deviation</th>\n",
       "                        <td>44.789</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>133.99</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>48156</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>0.33426</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>0.62402</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"alert\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>219.39</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>16113</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>2006.1</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>376.7 KiB</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-8 col-md-offset-2\" id=\"histogram4674101350673835189\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAAgAElEQVR4nO3deXRUVb7%2B/4ekAqkwJYzaLl0gSbBVNDGBgCgKEm3GSwdoRIigXvCSSDosGURQEQxDMwjIhVYUUWBdEQQRxBa9TSONyKSi7TWYIAH9IiRkgIxm2r8//KW6y2gbZB9SBe/XWllae5%2Bzzz4fTlJP6uyqNDDGGAEAAMCagPqeAAAAwKWGgAUAAGAZAQsAAMAyAhYAAIBlBCwAAADLCFgAAACWEbAAAAAsI2ABAABYRsACAACwjIAFAABgGQELAADAMgIWAACAZQQsAAAAywhYAAAAlhGwAAAALCNgAQAAWEbAAgAAsIyABQAAYBkBCwAAwDICFgAAgGUELAAAAMsIWAAAAJYRsAAAACwjYAEAAFhGwAIAALCMgAUAAGAZAQsAAMAyAhYAAIBlBCwAAADLCFgAAACWEbAAAAAsI2ABAABYRsACAACwjIAFAABgGQELAADAMgIWAACAZQQsAAAAywhYAAAAlvlswNq%2Bfbuuv/56RUdHe74mTZokSdq1a5cGDBigqKgo9enTRzt37vTad%2BXKlerRo4eioqKUmJior7/%2B2tNXUlKiqVOnKi4uTjExMZo8ebKKi4s9/ceOHdOoUaMUHR2t2267TX/%2B858vzgkDAIBLRgNjjKnvSfyUefPmqaCgQHPmzPFqz8rK0sCBA7Vo0SLdeeed2rFjh6ZOnaodO3aobdu22rx5s5599lm99NJLuuaaa/Tss8/q73//u7Zu3aoGDRpo6tSp%2Bu6777R48WJVVVUpNTVV4eHheuqpp1RRUaH%2B/fsrPj5eKSkpyszM1MMPP6zHH39cffr0uaDzyckpvKD9f0pAQAO1aNFYeXnFqq72yX9Gv0eNnUV9nUeNnUeNnXchNW7duqlDs/r3fPYVrM8//1w33nhjrfbNmzcrNjZWvXv3lsvlUt%2B%2BfdW5c2etX79ekvT666/rvvvuU0REhBo1aqRHH31UJ0%2Be1L59%2B1RaWqqtW7cqJSVFoaGhatmypSZOnKhNmzaptLRUBw4cUHZ2tlJSUtSwYUNdf/31SkxM1Lp16y726ddJQEADNWjQQAEBDep7Kpcsauws6us8auw8auw8f6yxTwas6upqffHFF/rb3/6mnj17qkePHnriiSd09uxZZWZmKjIy0mv78PBwpaenS1Kt/qCgILVr107p6ek6fvy4KioqvPo7dOigsrIyZWVlKSMjQ%2B3bt1fDhg1/cmwAAIC6cNX3BH5KXl6err/%2Bet1zzz1aunSp8vPzNWXKFE2aNEnl5eVyu91e2wcHB6ukpESSVFxc/LP9RUVFkqSQkBBPX822xcXFP7mv2%2B32jF1X2dnZysnJ8WpzuULUpk2b8xrnlwQGBnj9F/ZRY2dRX%2BdRY%2BdRY%2Bf5Y419MmC1atXK67ac2%2B3WpEmT9Ic//EFxcXEqKyvz2r6srEyNGzf2bPtz/TXBqrS01LN9aWmpJKlJkyYKCQnxPK7xr9vW1fr167Vs2TKvtuTkZKWkpJzXOHXVrJn7lzfCBaHGzqK%2BzqPGzqPGzvOnGvtkwEpPT9e2bdv06KOPqkGDH%2B63lpeXKyAgQDfddJO%2B/PJLr%2B0zMzM967UiIiKUkZGhnj17SpIqKiqUlZWlyMhItW/fXkFBQcrMzNTNN98sSTp69KjnNmJubq6ysrJUWVkpl8vlGTsiIuK85j9s2DD16tXLq83lClF%2BfvHP7PHrBAYGqFkzt86dK1VVVbXVsfEDauws6us8auw8auy8C6lxWNj5vUhii08GrNDQUK1bt07NmzfXAw88oOzsbM2fP1%2B///3vNWjQIL3yyivavn277r77bu3YsUP79%2B/XtGnTJEmDBw/Wc889px49eqh9%2B/Z69tln1apVK8XGxiooKEh9%2BvTRggULtGTJEknSggUL1L9/fwUHBysuLk5hYWFauHChUlNTdezYMa1Zs0YTJkw4r/m3adOm1u3AnJxCVVY6841XVVXt2Nj4ATV2FvV1HjV2HjV2nj/V2Gc/pmH//v1atGiRvvrqKzVq1Ej9%2BvXTpEmT1KhRI%2B3evVsLFizQiRMndNVVV2nSpEm64447JEnGGL388stat26d8vLy1KlTJz399NNq3769JKmoqEjz5s3TX//6V1VUVOiuu%2B7SE0884bl9ePz4cc2cOVOHDx9WSEiIRo4cqbFjx17w%2BTjxMQ0uV4DCwhorP7/Yby44f0ONnUV9nUeNnUeNnXchNa6vj2nw2YB1qSFg%2BSdq7Czq6zxq7Dxq7Dx/DFj%2BsxwfAADATxCwAAAALCNgAQAAWEbAAgAAsIyABQAAYBkBCwAAwDKf/KBR1F3stL/U9xTq7J3U7vU9BQAALgpewQIAALCMgAUAAGAZAQsAAMAyAhYAAIBlBCwAAADLCFgAAACWEbAAAAAsI2ABAABYRsACAACwjIAFAABgGQELAADAMgIWAACAZQQsAAAAywhYAAAAlhGwAAAALCNgAQAAWEbAAgAAsIyABQAAYBkBCwAAwDICFgAAgGUELAAAAMsIWAAAAJYRsAAAACwjYAEAAFhGwAIAALCMgAUAAGAZAQsAAMAyAhYAAIBlBCwAAADLCFgAAACWEbAAAAAsI2ABAABYRsACAACwjIAFAABgGQELAADAMgIWAACAZQQsAAAAywhYAAAAlhGwAAAALCNgAQAAWEbAAgAAsIyABQAAYBkBCwAAwDICFgAAgGUELAAAAMsIWAAAAJYRsAAAACzz%2BYBVVVWlxMREPfbYY562Xbt2acCAAYqKilKfPn20c%2BdOr31WrlypHj16KCoqSomJifr66689fSUlJZo6dari4uIUExOjyZMnq7i42NN/7NgxjRo1StHR0brtttv05z//2fmTBAAAlxSfD1jLli3TwYMHPY%2BzsrI0fvx4/fGPf9TBgwc1fvx4paam6vTp05KkzZs3a82aNXrppZe0b98%2B3XDDDUpJSZExRpI0a9Ysfffdd3r33Xe1Y8cOfffdd1qwYIEkqaKiQv/1X/%2BlTp06ad%2B%2BfXrhhRe0bt06vfPOOxf/xAEAgN/y6YC1d%2B9e7dixQ3fffbenbfPmzYqNjVXv3r3lcrnUt29fde7cWevXr5ckvf7667rvvvsUERGhRo0a6dFHH9XJkye1b98%2BlZaWauvWrUpJSVFoaKhatmypiRMnatOmTSotLdWBAweUnZ2tlJQUNWzYUNdff70SExO1bt26%2BioBAADwQ676nsDPyc3N1bRp07R8%2BXKtXr3a056ZmanIyEivbcPDw5Wenu7pHzNmjKcvKChI7dq1U3p6ukJDQ1VRUeG1f4cOHVRWVqasrCxlZGSoffv2atiwodfYL7zwwnnNPTs7Wzk5OV5tLleI2rRpc17j/JLAQJ/Ox7W4XP41X%2BmfNfa3WvsL6us8auw8auw8f6yxTwas6upqTZo0SQ888ICuu%2B46r77i4mK53W6vtuDgYJWUlPxif1FRkSQpJCTE01ezbXFx8U/u63a7PWPX1fr167Vs2TKvtuTkZKWkpJzXOJeasLDG9T2FX61ZM/cvb4Rfjfo6jxo7jxo7z59q7JMB6/nnn1fDhg2VmJhYq8/tdqusrMyrraysTI0bN/7F/ppgVVpa6tm%2BtLRUktSkSROFhIR4Htf4123ratiwYerVq5dXm8sVovz84p/Z49fxpyQvyfr5XwyBgQFq1sytc%2BdKVVVVXd/TueRQX%2BdRY%2BdRY%2BddSI3r65d7nwxYW7ZsUXZ2tmJjYyXJE5jef/99jRgxQl988YXX9pmZmbrxxhslSREREcrIyFDPnj0l/bBwPSsrS5GRkWrfvr2CgoKUmZmpm2%2B%2BWZJ09OhRz23E3NxcZWVlqbKyUi6XyzN2RETEec2/TZs2tW4H5uQUqrLy8v7G8%2Bfzr6qq9uv5%2Bzrq6zxq7Dxq7Dx/qrFPvgTyl7/8RR9//LEOHjyogwcPqn///urfv78OHjyogQMHav/%2B/dq%2BfbsqKyu1fft27d%2B/X//xH/8hSRo8eLDWrl2r9PR0ff/991q4cKFatWql2NhYud1u9enTRwsWLFBeXp7y8vK0YMEC9e/fX8HBwYqLi1NYWJgWLlyo77//Xunp6VqzZo2GDBlSzxUBAAD%2BxCdfwfp3OnTooP/%2B7//WggULNG3aNF111VV67rnn1L59e0nSkCFDVFhYqOTkZOXl5alTp056/vnnFRQUJEl66qmnNG/ePA0YMEAVFRW666679MQTT0iSXC6XVq1apZkzZ6p79%2B4KCQlRYmKiEhIS6u18AQCA/2lgaj4gCo7KySm0PqbLFaD4Bbutj%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%2BPs3btXQ4cO1S233KLu3btr1qxZKisrkyQdPnxYQ4cOVXR0tHr16qUNGzZ47bt582bFx8crKipKCQkJ%2BuSTT7zmN2/ePN16662Kjo7WuHHjlJ2d7enPzc1VUlKSYmNjFRcXp7S0NFVWVlo5JwAAcHmwHrB69OihP/3pT8rMzPzVY%2BTl5enhhx/W8OHDdfDgQW3evFn79%2B/XCy%2B8oLNnz2rs2LEaNGiQDhw4oLS0NM2ZM0efffaZJGnfvn2aNWuW5s6dqwMHDmjgwIEaN26cSktLJUkrVqzQnj179MYbb2j37t0KDg7W9OnTPcdOTU1VSEiIdu/erY0bN2rv3r1avXr1BdUEAABcXqwHrEceeUQff/yx%2Bvfvr6FDh%2Bq1115TYWHheY3RokULffjhh0pISFCDBg1UUFCg77//Xi1atNCOHTsUGhqqESNGyOVyqVu3bhowYIDWrVsnSdqwYYP69eunmJgYBQUFafTo0QoLC9P27ds9/WPGjNGVV16pJk2aaNq0afrggw/0zTff6Pjx49q/f78mTZokt9utq6%2B%2BWklJSZ6xAQAA6sJle8Dhw4dr%2BPDhysrK0ubNm7Vy5UrNmTNHvXv31uDBg3XrrbfWaZwmTZpIku644w6dPn1asbGxSkhI0OLFixUZGem1bXh4uDZu3ChJyszM1ODBg2v1p6enq7CwUKdOnfLav1WrVmrevLmOHDkiSQoNDVXbtm09/R06dNDJkyd17tw5NWvWrE5zz87OVk5OjlebyxWiNm3a1Gn/ugoM9K8ldC6Xf81X%2BmeN/a3W/oL6Oo8aO48aO88fa2w9YNVo166dJkyYoEceeUQvv/yyli9fru3bt%2BvKK69UYmKi7r//fgUGBv7iODt27NDZs2c1ceJEpaSkqG3btnK73V7bBAcHq6SkRJJUXFz8s/3FxcWSpJCQkFr9NX0/3rfmcUlJSZ0D1vr167Vs2TKvtuTkZKWkpNRp/0tVWFjj%2Bp7Cr9asmfuXN8KvRn2dR42dR42d5081dixgHT58WG%2B%2B%2Baa2b9%2Bu8vJyxcfHKyEhQadPn9aSJUv0%2Beefa9GiRb84TnBwsIKDgzVp0iQNHTpUiYmJtW45lpWVqXHjH5683W63ZzH8v/aHhYV5wlLNeqwf72%2BMqdVX87hm/LoYNmyYevXq5dXmcoUoP7%2B4zmPUhT8leUnWz/9iCAwMULNmbp07V6qqqur6ns4lh/o6jxo7jxo770JqXF%2B/3FsPWMuXL9eWLVt0/PhxderUSRMmTFD//v09t/wkKTAwUE8%2B%2BeTPjvHxxx/r8ccf11tvvaWGDRtKksrLyxUUFKTw8HDt2bPHa/vMzExFRERIkiIiIpSRkVGrv0ePHmrevLnatm2rzMxMz23CnJwcFRQUKDIyUtXV1SooKNCZM2fUqlUrSdLRo0d1xRVXqGnTpnWuQZs2bWrdDszJKVRl5eX9jefP519VVe3X8/d11Nd51Nh51Nh5/lRj6y%2BBrF27Vj179tS2bdu0YcMG3XvvvV7hSvphXdPEiRN/doyOHTuqrKxMCxcuVHl5uf7f//t/mjdvnoYMGaJ77rlHZ86c0erVq1VRUaGPPvpIW7du9ay7GjJkiLZu3aqPPvpIFRUVWr16tXJzcxUfHy9JSkhI0IoVK/TNN9%2BoqKhIs2fPVpcuXXTNNdeoXbt2iomJ0ezZs1VUVKRvvvlGy5cv15AhQ2yXCQAAXMIaGGOMzQErKytVVFSkgoICtWvXTpK0fft2devWTWFhYXUeJzMzU7Nnz9bnn3%2Bupk2basCAAUpOTlbDhg31%2BeefKy0tTV999ZVatGihpKQkJSQkePbdsmWLVqxYodOnTys8PFzTp0/XzTffLEmqqKjQkiVL9NZbb6m4uFhxcXGaNWuWWrZsKUk6c%2BaMZs6cqX379ikgIECDBg3SxIkT67Re7N/JyTm/d1LWhcsVoPgFu62P65R3UrvX9xTOm8sVoLCwxsrPL/ab35r8CfV1HjV2HjV23oXUuHXrut%2BBssl6wPrss880ZswYJSQkaMqUKZKknj17qqKiQqtWrar1DsDLBQGLgIXaqK/zqLHzqLHz/DFgWb9F%2BKc//Ul33323JkyY4Gl7//331aNHD82dO9f24QAAAHyO9YD1xRdfaOzYsZ7F6dIPi9rHjh2rTz/91PbhAAAAfI71gNWkSROdOHGiVvupU6cUHBxs%2B3AAAAA%2Bx3rAuueeezRjxgx9%2BOGHKioqUnFxsT766CPNnDnT804%2BAACAS5n1z8F69NFH9c033%2BjBBx9UgwYNPO3x8fGaPHmy7cMBAAD4HOsBy%2B126/nnn9exY8d05MgRBQUFqUOHDp6PbAAAALjUOfanctq3b6/27ds7NTwAAIDPsh6wjh07ppkzZ%2BrQoUOqqKio1f/ll1/aPiQAAIBPsR6wZsyYoZMnT2rixInn9ff7AAAALhXWA9Ynn3yiV155RdHR0baHBgAA8AvWP6YhLCxMjRs3tj0sAACA37AesBITE7Vo0SIVFtr/23sAAAD%2BwPotwl27dunTTz9VXFycWrZs6fUncyTpf//3f20fEgAAwKdYD1hxcXGKi4uzPSwAAIDfsB6wHnnkEdtDAgAA%2BBXra7AkKT09XVOnTtW9996r06dPa926ddq3b58ThwIAAPA51gPWP/7xDw0dOlTffvut/vGPf6i8vFxffvmlHnzwQe3cudP24QAAAHyO9YC1YMECPfjgg1qzZo2CgoIkSc8884zuv/9%2BLVu2zPbhAAAAfI4jr2ANGjSoVvvw4cP19ddf2z4cAACAz7EesIKCglRUVFSr/eTJk3K73bYPBwAA4HOsB6zevXtr4cKFys/P97QdPXpUaWlpuvPOO20fDgAAwOdYD1hTpkxRWVmZbr31VpWWliohIUH9%2B/eXy%2BXS5MmTbR8OAADA51j/HKwmTZrotdde0969e/V///d/qq6uVmRkpG6//XYFBDjyqRAAAAA%2BxXrAqtGtWzd169bNqeEBAAB8lvWA1atXLzVo0OBn%2B/lbhAAA4FJnPWD9/ve/9wpYFRUVOn78uD744AOlpqbaPhwAAIDPsR6wxo8f/5Pta9eu1aFDh3T//ffbPiQAAIBPuWirznv27Kldu3ZdrMMBAADUm4sWsPbv369GjRpdrMMBAADUG%2Bu3CH98C9AYo6KiIh05coTbgwAA4LJgPWD95je/qfUuwqCgII0aNUoDBgywfTgAAACfYz1gzZ071/aQAAAAfsV6wDpw4ECdt%2B3cubPtwwMAANQ76wFr9OjRMsZ4vmrU3DasaWvQoIG%2B/PJL24cHAACod9YD1nPPPac5c%2BZoypQp6tq1q4KCgnT48GHNmDFD9913n3r27Gn7kAAAAD7F%2Bsc0zJs3T0899ZR69%2B6tJk2aqFGjRurSpYtmzpypVatW6aqrrvJ8AQAAXIqsB6zs7GxdeeWVtdqbNGmi/Px824cDAADwOdYDVlRUlBYtWqSioiJPW0FBgebPn69u3brZPhwAAIDPsb4Ga/r06Ro1apR69Oihdu3aSZKOHTum1q1b69VXX7V9OAAAAJ9jPWB16NBB27dv19atW3X06FFJ0n333ad%2B/frJ7XbbPhwAAIDPsR6wJKlZs2YaOnSovv32W1199dWSfvg0dwAAgMuB9TVYxhgtWLBAnTt3Vv/%2B/XXq1ClNmTJFU6dOVUVFhe3DAQAA%2BBzrAWvNmjXasmWLnnrqKTVs2FCS1Lt3b/31r3/VkiVLbB8OAADA51gPWOvXr9eTTz6phIQEz6e39%2B3bV2lpaXr77bdtHw4AAMDnWA9Y3377rX7729/Wau/YsaPOnDlj%2B3AAAAA%2Bx3rAuuqqq/TZZ5/Vat%2B1a5dnwTsAAMClzPq7CB966CE9/fTTOn36tIwx2rt3r1577TWtWbNGU6dOtX04AAAAn2M9YA0ePFiVlZVasWKFysrK9OSTT6ply5aaMGGChg8fbvtwAAAAPsd6wHrrrbf0u9/9TsOGDVNeXp6MMWrZsqXtwwAAAPgs62uwnnnmGc9i9hYtWhCuAADAZcd6wGrXrp2OHDlie1gAAAC/Yf0WYUREhCZOnKgXX3xR7dq1U6NGjbz658yZY/uQAAAAPsV6wDpx4oRiYmIkSTk5ObaHBwAA8HlWAtacOXP0xz/%2BUSEhIVqzZo2NIZWenq558%2Bbpiy%2B%2BUFBQkLp3767HHntMLVq00OHDh/XMM88oMzNTYWFhGjdunIYOHerZd/PmzVq%2BfLlycnJ07bXX6oknnlB0dLQkqaqqSgsWLNCWLVtUWlqqrl276umnn1abNm0kSbm5uXriiSe0f/9%2BBQYGauDAgZoyZYpcLkf%2BLjYAALgEWVmD9eqrr6q0tNSr7aGHHlJ2dvavGq%2BsrEz/%2BZ//qejoaP3973/Xtm3bVFBQoMcff1xnz57V2LFjNWjQIB04cEBpaWmaM2eO58NN9%2B3bp1mzZmnu3Lk6cOCABg4cqHHjxnnmt2LFCu3Zs0dvvPGGdu/ereDgYE2fPt1z7NTUVIWEhGj37t3auHGj9u7dq9WrV/%2B6wgAAgMuSlYBljKnV9vHHH%2Bv777//VeOdPHlS1113nZKTk9WwYUOFhYVp2LBhOnDggHbs2KHQ0FCNGDFCLpdL3bp104ABA7Ru3TpJ0oYNG9SvXz/FxMQoKChIo0ePVlhYmLZv3%2B7pHzNmjK688ko1adJE06ZN0wcffKBvvvlGx48f1/79%2BzVp0iS53W5dffXVSkpK8owNAABQF9bfRWjDtddeqxdffFGBgYGetnfffVc33HCDMjIyFBkZ6bV9eHi40tPTJUmZmZk/219YWKhTp0559bdq1UrNmzfXkSNHlJGRodDQULVt29bT36FDB508eVLnzp1z4lQBAMAlyOcXFhljtHjxYu3cuVNr167Vq6%2B%2BKrfb7bVNcHCwSkpKJEnFxcU/219cXCxJCgkJqdVf0/fjfWsel5SUqFmzZnWac3Z2dq0F/i5XiGedly2BgT6Zj3%2BWy%2BVf85X%2BWWN/q7W/oL7Oo8bOo8bO88caWwtYDRo0sDWUR1FRkaZOnaovvvhCa9euVceOHeV2u1VYWOi1XVlZmRo3bizph0BUVlZWqz8sLMwTln68Xqxmf2NMrb6axzXj18X69eu1bNkyr7bk5GSlpKTUeYxLUVhY3Wvoa5o1c//yRvjVqK/zqLHzqLHz/KnG1gLWM8884/WZVxUVFZo/f36tYFLXz8E6ceKExowZo9/85jfauHGjWrRoIUmKjIzUnj17vLbNzMxURESEpB8%2BhysjI6NWf48ePdS8eXO1bdvW6zZiTk6OCgoKFBkZqerqahUUFOjMmTNq1aqVJOno0aO64oor1LRp0zrXYtiwYerVq5dXm8sVovz84jqPURf%2BlOQlWT//iyEwMEDNmrl17lypqqqq63s6lxzq6zxq7Dxq7LwLqXF9/XJvJWB17ty51i2x6Oho5efnKz8//7zHO3v2rEaNGqWuXbsqLS1NAQH/DBLx8fGaP3%2B%2BVq9erREjRujQoUPaunWrli9fLkkaMmSIkpOT1adPH8XExGjdunXKzc1VfHy8JCkhIUErVqxQp06dFBYWptmzZ6tLly665pprJEkxMTGaPXu2Zs6cqfz8fC1fvlxDhgw5r/m3adOm1u3AnJxCVVZe3t94/nz%2BVVXVfj1/X0d9nUeNnUeNnedPNbYSsGx99lWNTZs26eTJk3rnnXf0l7/8xavvk08%2B0apVq5SWlqalS5eqRYsWmj59urp27SpJ6tatm5566inNmDFDp0%2BfVnh4uFauXKnQ0FBJP9yqq6ys1IgRI1RcXKy4uDgtXrzYM/7SpUs1c%2BZM3XXXXQoICNCgQYOUlJRk9fwAAMClrYH5qc9YgHU5OYW/vNF5crkCFL9gt/VxnfJOavf6nsJ5c7kCFBbWWPn5xX7zW5M/ob7Oo8bOo8bOu5Aat25d9yU%2BNvnXIh4AAAA/QMACAACwjIAFAABgGQELAADAMgIWAACAZQQsAAAAywhYAAAAlhGwAAAALCNgAQAAWEbAAgAAsIyABQAAYBkBCwAAwDICFgAAgGUELAAAAMsIWAAAAJYRsAAAACwjYAEAAFhGwAIAALCMgAUAAGAZAQsAAMAyAhYAAIBlBCwAAADLCFgAAACWEbAAAAAsI2ABAABYRsACAACwjIAFAABgGQELAADAMgIWAACAZQQsAAAAyxAIkw8AABEnSURBVAhYAAAAlhGwAAAALCNgAQAAWEbAAgAAsIyABQAAYBkBCwAAwDICFgAAgGUELAAAAMsIWAAAAJYRsAAAACwjYAEAAFhGwAIAALCMgAUAAGAZAQsAAMAyAhYAAIBlBCwAAADLCFgAAACWEbAAAAAsI2ABAABYRsACAACwjIAFAABgGQELAADAMgIWAACAZT4fsPLy8hQfH699%2B/Z52g4fPqyhQ4cqOjpavXr10oYNG7z22bx5s%2BLj4xUVFaWEhAR98sknnr6qqirNmzdPt956q6KjozVu3DhlZ2d7%2BnNzc5WUlKTY2FjFxcUpLS1NlZWVzp8oAAC4ZPh0wDp06JCGDRumEydOeNrOnj2rsWPHatCgQTpw4IDS0tI0Z84cffbZZ5Kkffv2adasWZo7d64OHDiggQMHaty4cSotLZUkrVixQnv27NEbb7yh3bt3Kzg4WNOnT/eMn5qaqpCQEO3evVsbN27U3r17tXr16ot63gAAwL/5bMDavHmzJk6cqAkTJni179ixQ6GhoRoxYoRcLpe6deumAQMGaN26dZKkDRs2qF%2B/foqJiVFQUJBGjx6tsLAwbd%2B%2B3dM/ZswYXXnllWrSpImmTZumDz74QN98842OHz%2Bu/fv3a9KkSXK73br66quVlJTkGRsAAKAufDZg3XbbbXrvvffUt29fr/aMjAxFRkZ6tYWHhys9PV2SlJmZ%2BbP9hYWFOnXqlFd/q1at1Lx5cx05ckQZGRkKDQ1V27ZtPf0dOnTQyZMnde7cOdunCAAALlGu%2Bp7Az2nduvVPthcXF8vtdnu1BQcHq6Sk5Bf7i4uLJUkhISG1%2Bmv6frxvzeOSkhI1a9asTnPPzs5WTk6OV5vLFaI2bdrUaf%2B6Cgz02Xz8k1wu/5qv9M8a%2B1ut/QX1dR41dh41dp4/1thnA9bPcbvdKiws9GorKytT48aNPf1lZWW1%2BsPCwjxhqWY91o/3N8bU6qt5XDN%2BXaxfv17Lli3zaktOTlZKSkqdx7gUhYXVvYa%2Bplkz9y9vhF%2BN%2BjqPGjuPGjvPn2rsdwErMjJSe/bs8WrLzMxURESEJCkiIkIZGRm1%2Bnv06KHmzZurbdu2XrcRc3JyVFBQoMjISFVXV6ugoEBnzpxRq1atJElHjx7VFVdcoaZNm9Z5jsOGDVOvXr282lyuEOXnF5/3%2Bf47/pTkJVk//4shMDBAzZq5de5cqaqqqut7Opcc6us8auw8auy8C6lxff1y73cBKz4%2BXvPnz9fq1as1YsQIHTp0SFu3btXy5cslSUOGDFFycrL69OmjmJgYrVu3Trm5uYqPj5ckJSQkaMWKFerUqZPCwsI0e/ZsdenSRddcc40kKSYmRrNnz9bMmTOVn5%2Bv5cuXa8iQIec1xzZt2tS6HZiTU6jKysv7G8%2Bfz7%2Bqqtqv5%2B/rqK/zqLHzqLHz/KnGfhewwsLCtGrVKqWlpWnp0qVq0aKFpk%2Bfrq5du0qSunXrpqeeekozZszQ6dOnFR4erpUrVyo0NFTSD7fqKisrNWLECBUXFysuLk6LFy/2jL906VLNnDlTd911lwICAjRo0CAlJSXVy7kCAAD/1MAYY%2Bp7EpeDnJzCX97oPLlcAYpfsNv6uE55J7V7fU/hvLlcAQoLa6z8/GK/%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%2BTZo0SW63W1dffbWSkpK0bt26%2Bp4aAADwEwSsH8nIyFBoaKjatm3raevQoYNOnjypc%2BfO1ePMAACAv3DV9wR8TXFxsdxut1dbzeOSkhI1a9bsF8fIzs5WTk6OV5vLFaI2bdrYm6ikwED/yscul3/NV/pnjf2t1v6C%2BjqPGjuPGjvPH2tMwPqRkJAQlZaWerXVPG7cuHGdxli/fr2WLVvm1fbII49o/Pjxdib5/8vOztaoKzI0bNgw6%2BENP8jOztYrr7xIjR1CfZ1HjZ1HjZ3njzX2nyh4kURERKigoEBnzpzxtB09elRXXHGFmjZtWqcxhg0bpk2bNnl9DRs2zPpcc3JytGzZslqvlsEeauws6us8auw8auw8f6wxr2D9SLt27RQTE6PZs2dr5syZys/P1/LlyzVkyJA6j9GmTRu/SdgAAMA%2BXsH6CUuXLlVlZaXuuusu/eEPf9Dtt9%2BupKSk%2Bp4WAADwE7yC9RNatWqlpUuX1vc0AACAnwqcMWPGjPqeBH69xo0bq0uXLnVegI/zR42dRX2dR42dR42d5281bmCMMfU9CQAAgEsJa7AAAAAsI2ABAABYRsACAACwjIAFAABgGQELAADAMgIWAACAZQQsAAAAywhYAAAAlhGw/FRubq6SkpIUGxuruLg4paWlqbKysr6n5dPS09P1wAMPqEuXLurevbsmT56svLw8SdLhw4c1dOhQRUdHq1evXtqwYYPXvps3b1Z8fLyioqKUkJCgTz75xNNXVVWlefPm6dZbb1V0dLTGjRun7Ozsi3puvqSqqkqJiYl67LHHPG27du3SgAEDFBUVpT59%2Bmjnzp1e%2B6xcuVI9evRQVFSUEhMT9fXXX3v6SkpKNHXqVMXFxSkmJkaTJ09WcXHxRTsfX1JQUKDJkycrLi5OnTt3VlJSkuda4xq244svvtCIESMUGxur2267Tc8884zKy8slcR1fqLy8PMXHx2vfvn2eNiev23p/njTwSyNHjjSPPvqoKSkpMSdOnDD9%2BvUzK1eurO9p%2BazS0lLTvXt3s2TJEvP999%2BbvLw8M2bMGPPwww%2BbgoIC06VLF7N27VpTUVFhPvzwQxMdHW0OHz5sjDHmo48%2BMtHR0ebgwYOmvLzcvPzyyyYuLs6UlJQYY4x57rnnzIABA8zJkydNYWGhSU1NNWPGjKnP061XixcvNtddd52ZMmWKMcaYY8eOmU6dOpn33nvPVFRUmLffftvcdNNN5tSpU8YYYzZt2mRuv/1289VXX5mysjIzZ84c069fP1NdXW2MMeaxxx4zo0aNMvn5%2BebMmTNm5MiRZsaMGfV2fvVp5MiRJjk52Zw9e9YUFhaaRx55xIwdO5Zr2JKqqirTvXt388orr5iqqirz3XffmXvuuccsW7aM6/gCHTx40PTu3dtERkaajz76yBhjHL9u6/t5koDlh7KyskxkZKTnG9sYY95%2B%2B21z55131uOsfNvRo0fNQw89ZCorKz1t77//vrnlllvM66%2B/bu6%2B%2B26v7Z988kkzefJkY4wxjz76qJk%2BfbpX/%2B9%2B9zuzceNGY4wxPXr0MG%2B99ZanLycnx3Ts2NGcOHHCqdPxWR9%2B%2BKHp27evSUlJ8QSsRYsWmQceeMBru4ceesgsWbLEGGPMvffea1asWOHpKy8vN9HR0Wbv3r2mpKTE3HDDDebQoUOe/k8//dTcdNNNnh%2Byl4vPP//cdOrUyRQWFnra8vPzzVdffcU1bEleXp6JjIw0L7/8sqmsrDTfffed6dOnj3nppZe4ji/Apk2bzJ133mnefvttr4Dl5HXrC8%2BT3CL0QxkZGQoNDVXbtm09bR06dNDJkyd17ty5epyZ77r22mv14osvKjAw0NP27rvv6oYbblBGRoYiIyO9tg8PD1d6erokKTMz82f7CwsLderUKa/%2BVq1aqXnz5jpy5IiDZ%2BR7cnNzNW3aNC1cuFBut9vT/u/q91P9QUFBateundLT03X8%2BHFVVFR49Xfo0EFlZWXKyspy9oR8zGeffabw8HC9/vrrio%2BP12233aZ58%2BapdevWXMOWhIWFafTo0Zo3b546deqkO%2B64Q%2B3atdPo0aO5ji/Abbfdpvfee099%2B/b1anfyuvWF50kClh8qLi72egKT5HlcUlJSH1PyK8YYPfvss9q5c6emTZv2k/UMDg721PLf9desoQgJCanVfzmtr6iurtakSZP0wAMP6LrrrvPqu5D6FhUVSfKub822l1N9Jens2bM6cuSIsrKytHnzZr355ps6ffq0pkyZwjVsSXV1tYKDg/XEE0/o008/1bZt23T06FEtXbqU6/gCtG7dWi6Xq1a7k9etLzxPErD8UEhIiEpLS73aah43bty4PqbkN4qKipSSkqKtW7dq7dq16tixo9xut8rKyry2Kysr89Ty3/XXfMP%2B%2BN/jX/e/HDz//PNq2LChEhMTa/VdSH1rfnj%2Ba31r/r9JkyZWz8HXNWzYUJI0bdo0NWnSRK1atVJqaqp27dolYwzXsAXvvfee3n33Xd13331q2LChIiIilJycrP/5n//hOnaAkz97feF5koDlhyIiIlRQUKAzZ8542o4ePaorrrhCTZs2rceZ%2BbYTJ05o8ODBKioq0saNG9WxY0dJUmRkpDIyMry2zczMVEREhKQf6v1z/c2bN1fbtm2VmZnp6cvJyVFBQUGtl7YvZVu2bNH%2B/fsVGxur2NhYbdu2Tdu2bVNsbOx517eiokJZWVmKjIxU%2B/btFRQU5FXfo0ePem6/XE7Cw8NVXV2tiooKT1t1dbUk6be//S3XsAXfffed5x2DNVwul4KCgriOHeDkz16feJ68aKu9YNXw4cPNhAkTTGFhoefdEUuXLq3vafmsgoICc%2Bedd5rHHnvMVFVVefXl5eWZ2NhY8/LLL5vy8nKzd%2B9ez%2BJUY4znnS179%2B71vJOlc%2BfOJj8/3xhjzLPPPmv69%2B9vTpw44Xkny8iRIy/6OfqSKVOmeBa5Z2Zmmk6dOpm3337b8%2B6rTp06ma%2B//toY88NC19tvv918%2BeWXnndfxcfHm/LycmOMMRMnTjQjR440ubm5Jjc314wcOdIz9uWkvLzcxMfHm/Hjx5uioiKTm5tr7r//fpOcnMw1bElGRoa58cYbzYoVK0xlZaU5ceKE6d%2B/v5k7dy7XsSX/usjd6eu2vp8nCVh%2BKicnx4wfP9506dLFdO3a1cydO9frHXLwtmrVKhMZGWluvvlmExUV5fVljDGfffaZGTZsmImOjjZ33XWXeeONN7z2f/PNN80999xjoqKizJAhQ8ynn37q6SsvLzfz5883t99%2Bu7nlllvMuHHjzJkzZy7q%2Bfmafw1YxhjzwQcfmIEDB5qoqCjTr18/87e//c3TV11dbV566SXTq1cvExUVZRITEz1PWsYYU1hYaKZPn25uvfVW07lzZ/PYY4%2BZ4uLii3o%2BvuLUqVMmNTXVdO/e3cTGxprJkyebs2fPGmO4hm3Zs2ePGTp0qImJiTF33nmnWbRokfn%2B%2B%2B%2BNMVzHNvxrwDLG2eu2vp8nGxhjzMV5rQwAAODywBosAAAAywhYAAAAlhGwAAAALCNgAQAAWEbAAgAAsIyABQAAYBkBCwAAwDICFgAAgGUELAAAAMsIWAAAAJYRsAAAACwjYAEAAFhGwAIAALCMgAUAAGAZAQsAAMCy/w/TTQxQxNHyJAAAAABJRU5ErkJggg%3D%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common4674101350673835189\">\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.0</td>\n",
       "        <td class=\"number\">44737</td>\n",
       "        <td class=\"number\">92.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.25</td>\n",
       "        <td class=\"number\">948</td>\n",
       "        <td class=\"number\">2.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:3%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.51</td>\n",
       "        <td class=\"number\">256</td>\n",
       "        <td class=\"number\">0.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1.02</td>\n",
       "        <td class=\"number\">123</td>\n",
       "        <td class=\"number\">0.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.3</td>\n",
       "        <td class=\"number\">121</td>\n",
       "        <td class=\"number\">0.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.76</td>\n",
       "        <td class=\"number\">109</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.38</td>\n",
       "        <td class=\"number\">99</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1.78</td>\n",
       "        <td class=\"number\">91</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1.52</td>\n",
       "        <td class=\"number\">69</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.64</td>\n",
       "        <td class=\"number\">55</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (362)</td>\n",
       "        <td class=\"number\">1596</td>\n",
       "        <td class=\"number\">3.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:4%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\"  id=\"extreme4674101350673835189\">\n",
       "            <p class=\"h4\">Minimum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.0</td>\n",
       "        <td class=\"number\">44737</td>\n",
       "        <td class=\"number\">92.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.25</td>\n",
       "        <td class=\"number\">948</td>\n",
       "        <td class=\"number\">2.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:3%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.26</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.27</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.28</td>\n",
       "        <td class=\"number\">23</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "            <p class=\"h4\">Maximum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">28.7</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">31.75</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">44.45</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">55.63</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">9831.3</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "</div><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_snow_1h\">snow_1h<br/>\n",
       "            <small>Numeric</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-6\">\n",
       "    <div class=\"row\">\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "                <tr>\n",
       "                    <th>Distinct count</th>\n",
       "                    <td>12</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "\n",
       "        </div>\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "\n",
       "                <tr>\n",
       "                    <th>Mean</th>\n",
       "                    <td>0.00022239</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>0.51</td>\n",
       "                </tr>\n",
       "                <tr class=\"alert\">\n",
       "                    <th>Zeros (%)</th>\n",
       "                    <td>99.9%</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "<div class=\"col-md-3 collapse in\" id=\"minihistogram8345004444573943185\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAAA%2B0lEQVR4nO3VsQkCURBFUVcsaYuwJ2N7sgh7GnORCxvI3%2BCcfOAll9lmZi7AT9fVA%2BDMbqsHfNsfr8M37%2Bf9D0vAB4EkEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCNvMzOoRcFY%2BCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCIQP2hsLj2bol0UAAAAASUVORK5CYII%3D\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives8345004444573943185,#minihistogram8345004444573943185\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives8345004444573943185\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles8345004444573943185\"\n",
       "                                                  aria-controls=\"quantiles8345004444573943185\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram8345004444573943185\" aria-controls=\"histogram8345004444573943185\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common8345004444573943185\" aria-controls=\"common8345004444573943185\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme8345004444573943185\" aria-controls=\"extreme8345004444573943185\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Extreme Values</a></li>\n",
       "\n",
       "    </ul>\n",
       "\n",
       "    <div class=\"tab-content\">\n",
       "        <div role=\"tabpanel\" class=\"tab-pane active row\" id=\"quantiles8345004444573943185\">\n",
       "            <div class=\"col-md-4 col-md-offset-1\">\n",
       "                <p class=\"h4\">Quantile statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Minimum</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>0.51</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>0.51</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "            <div class=\"col-md-4 col-md-offset-2\">\n",
       "                <p class=\"h4\">Descriptive statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Standard deviation</th>\n",
       "                        <td>0.0081676</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>36.727</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>2620.5</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>0.00022239</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>0.0004442</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"alert\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>48.367</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>10.72</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>6.671e-05</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>376.7 KiB</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-8 col-md-offset-2\" id=\"histogram8345004444573943185\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAAgAElEQVR4nO3de1SVZcL%2B8QvYKBsUwQNarVoyCvVaJgSJVGN5oF7z8Dqo45hjdphsxCRZaY6paRoeJjzm6JQdnIw1OVKOWVg2k6PmKNDJHN8oIFF7TUEEhQ0kh%2Bf3Rz/2mh2W0Nwb9pbvZy3WrH3fz76f%2B7lG6WLvh62PZVmWAAAAYIxva28AAADgckPBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDPLZgZWZmqk%2BfPoqOjnZ%2BzZo1S5K0Z88ejRw5UlFRURo2bJh2797t8tyNGzdq4MCBioqK0qRJk/TVV1855yorKzVnzhzFxcUpJiZGjz/%2BuBwOh3P%2B6NGjmjx5sqKjo3Xbbbfpj3/8Y8tcMAAAuGz4WJZltfYmLmb58uUqKyvT0qVLXcYLCws1atQorVy5UnfccYd27dqlOXPmaNeuXerevbu2bdumVatW6cUXX9Q111yjVatW6YMPPtCOHTvk4%2BOjOXPm6JtvvtHq1atVV1enGTNmqHfv3lqwYIFqamo0YsQIJSQkKDk5Wfn5%2BXr44Yf1xBNPaNiwYf/R9RQXl/9Hz78YX18fde4cpLNnHaqv98j/G70OmboHuboHuZpHpu7Rmrl269axRc/XwGNfwTp8%2BLBuuOGGRuPbtm1TbGyshg4dKpvNprvvvls333yztmzZIkn6y1/%2BonvuuUcRERFq3769HnvsMZ08eVJZWVmqqqrSjh07lJycrJCQEHXp0kUzZ87UG2%2B8oaqqKuXk5KioqEjJyclq166d%2BvTpo0mTJik9Pb2lL79JfH195OPjI19fn9beymWDTN2DXN2DXM0jU/doi7l6ZMGqr6/XkSNH9I9//EODBg3SwIEDNX/%2BfJ07d075%2BfmKjIx0Ob53797Kzc2VpEbz/v7%2B6tmzp3Jzc3Xs2DHV1NS4zPfq1UvV1dUqLCxUXl6ewsPD1a5du4uuDQAA0BS21t7AxZw9e1Z9%2BvTRXXfdpbVr16q0tFSzZ8/WrFmzdOHCBdntdpfjAwICVFlZKUlyOBw/OF9RUSFJCgwMdM41HOtwOC76XLvd7ly7qYqKilRcXOwyZrMFKiwsrFnrXIqfn6/L/%2BI/R6buQa7uQa7mkal7tMVcPbJgde3a1eVtObvdrlmzZumXv/yl4uLiVF1d7XJ8dXW1goKCnMf%2B0HxDsaqqqnIeX1VVJUnq0KGDAgMDnY8b/PuxTbVlyxatW7fOZWzatGlKTk5u1jpNFRxsv/RBaBYydQ9ydQ9yNY9M3aMt5eqRBSs3N1dvvfWWHnvsMfn4fPd%2B7YULF%2BTr66sbb7xRn3/%2Bucvx%2Bfn5zvu1IiIilJeXp0GDBkmSampqVFhYqMjISIWHh8vf31/5%2Bfnq16%2BfJKmgoMD5NmJJSYkKCwtVW1srm83mXDsiIqJZ%2Bx8/frwGDx7sMmazBaq01PEDz/hp/Px8FRxs1/nzVaqrqze6dltFpu5Bru5BruaRqXu0Zq6hoc17kcQUjyxYISEhSk9PV6dOnXT//ferqKhIzzzzjH7xi19o9OjR%2BtOf/qTMzEzdeeed2rVrl7KzszV37lxJ0pgxY/Tss89q4MCBCg8P16pVq9S1a1fFxsbK399fw4YNU1pamtasWSNJSktL04gRIxQQEKC4uDiFhoZqxYoVmjFjho4eParNmzcrJSWlWfsPCwtr9HZgcXG5amvd84eqrq7ebWu3VWTqHuTqHuRqHpm6R1vK1WM/piE7O1srV67Ul19%2Bqfbt22v48OGaNWuW2rdvr3379iktLU3Hjx/XVVddpVmzZun222%2BXJFmWpZdfflnp6ek6e/as%2Bvbtq6eeekrh4eGSpIqKCi1fvlzvv/%2B%2BampqNGTIEM2fP9/59uGxY8e0aNEiHTp0SIGBgfr1r3%2BtKVOm/MfX446PabDZfBUaGqTSUkeb%2BQPrbmTqHuTqHuRqHpm6R2vm2lof0%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%2Bu2227TH//4R/dfJAAAuKx4fMFat26dPvzwQ%2BfjwsJCTZ8%2BXY8%2B%2Bqg%2B/PBDTZ8%2BXTNmzNDp06clSdu2bdPmzZv14osvKisrS9dff72Sk5NlWZYkafHixfrmm2/07rvvateuXfrmm2%2BUlpYmSaqpqdFvf/tb9e3bV1lZWXr%2B%2BeeVnp6unTt3tvyFAwAAr%2BXRBevAgQPatWuX7rzzTufYtm3bFBsbq6FDh8pms%2Bnuu%2B/WzTffrC1btkiS/vKXv%2Biee%2B5RRESE2rdvr8cee0wnT55UVlaWqqqqtGPHDiUnJyskJERdunTRzJkz9cYbb6iqqko5OTkqKipScnKy2rVrpz59%2BmjSpElKT09vrQgAAIAX8tiCVVJSorlz52rFihWy2%2B3O8fz8fEVGRroc27t3b%2BXm5l503t/fXz179lRubq6OHTummpoal/levXqpurpahYWFysvLU3h4uNq1a3fRtQEAAJrC1tobuJj6%2BnrNmjVL999/v6677jqXOYfD4VK4JCkgIECVlZWXnK%2BoqJAkBQYGOucajnU4HBd9rt1ud67dVEVFRSouLnYZs9kCFRYW1qx1LsXPz2P78UXZbJ6/34ZMvS1bT0eu7kGu5pGpe7TFXD2yYD333HNq166dJk2a1GjObrerurraZay6ulpBQUGXnG8oVlVVVc7jq6qqJEkdOnRQYGCg83GDfz%2B2qbZs2aJ169a5jE2bNk3JycnNWudyExravBxbU3Cw/dIHodnI1T3I1TwydY%2B2lKtHFqzt27erqKhIsbGxkuQsTH/72980ceJEHTlyxOX4/Px83XDDDZKkiIgI5eXladCgQZK%2Bu3G9sLBQkZGRCg8Pl7%2B/v/Lz89WvXz9JUkFBgfNtxJKSEhUWFqq2tlY2m825dkRERLP2P378eA0ePNhlzGYLVGmp4wee8dN4208Cpq/fHfz8fBUcbNf581Wqq6tv7e1cNsjVPcjVPDJ1j9bMtbV%2BuPfIgvXOO%2B%2B4PG74iIZly5apoKBAL7/8sjIzM3XnnXdq165dys7O1ty5cyVJY8aM0bPPPquBAwcqPDxcq1atUteuXRUbGyt/f38NGzZMaWlpWrNmjSQpLS1NI0aMUEBAgOLi4hQaGqoVK1ZoxowZOnr0qDZv3qyUlJRm7T8sLKzR24HFxeWqrW3bf1m96frr6uq9ar/eglzdg1zNI1P3aEu5emTB%2BjG9evXSH/7wB6WlpWnu3Lm66qqr9Oyzzyo8PFySNHbsWJWXl2vatGk6e/as%2Bvbtq%2Beee07%2B/v6SpAULFmj58uUaOXKkampqNGTIEM2fP1%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%2B9VYsXL1Z1dbUk6dChQxo3bpyio6M1ePBgbd261eW527ZtU0JCgqKiopSYmKhPPvnEZX/Lly/XLbfcoujoaE2dOlVFRUXO%2BZKSEiUlJSk2NlZxcXFKTU1VbW2tkWsCAABtg/GCNXDgQP3%2B979Xfn7%2BT17j7NmzevjhhzVhwgR9%2BOGH2rZtm7Kzs/X888/r3LlzmjJlikaPHq2cnBylpqZq6dKl%2BuyzzyRJWVlZWrx4sZYtW6acnByNGjVKU6dOVVVVlSRpw4YN2r9/v15//XXt27dPAQEBmjdvnvPcM2bMUGBgoPbt26eMjAwdOHBAmzZt%2Bo8yAQAAbYvxgvXII4/o448/1ogRIzRu3Di99tprKi8vb9YanTt31j//%2BU8lJibKx8dHZWVl%2Bvbbb9W5c2ft2rVLISEhmjhxomw2m%2BLj4zVy5Eilp6dLkrZu3arhw4crJiZG/v7%2Buu%2B%2B%2BxQaGqrMzEzn/EMPPaQrrrhCHTp00Ny5c7V3716dOHFCx44dU3Z2tmbNmiW73a6rr75aSUlJzrUBAACawmZ6wQkTJmjChAkqLCzUtm3btHHjRi1dulRDhw7VmDFjdMsttzRpnQ4dOkiSbr/9dp0%2BfVqxsbFKTEzU6tWrFRkZ6XJs7969lZGRIUnKz8/XmDFjGs3n5uaqvLxcp06dcnl%2B165d1alTJ33xxReSpJCQEHXv3t0536tXL508eVLnz59XcHBwk/ZeVFSk4uJilzGbLVBhYWFNen5T%2Bfl51y10Npvn77chU2/L1tORq3uQq3lk6h5tMVfjBatBz549lZKSokceeUQvv/yy1q9fr8zMTF1xxRWaNGmS7r33Xvn5%2BV1ynV27duncuXOaOXOmkpOT1b17d9ntdpdjAgICVFlZKUlyOBw/OO9wOCRJgYGBjeYb5r7/3IbHlZWVTS5YW7Zs0bp161zGpk2bpuTk5CY9/3IVGhrU2ltosuBg%2B6UPQrORq3uQq3lk6h5tKVe3FaxDhw7pr3/9qzIzM3XhwgUlJCQoMTFRp0%2Bf1po1a3T48GGtXLnykusEBAQoICBAs2bN0rhx4zRp0qRGbzlWV1crKOi7/3jb7XbnzfD/Ph8aGuosSw33Y33/%2BZZlNZpreNywflOMHz9egwcPdhmz2QJVWupo8hpN4W0/CZi%2Bfnfw8/NVcLBd589Xqa6uvrW3c9kgV/cgV/PI1D1aM9fW%2BuHeeMFav369tm/frmPHjqlv375KSUnRiBEjnG/5SZKfn5%2BefPLJH1zj448/1hNPPKE333xT7dq1kyRduHBB/v7%2B6t27t/bv3%2B9yfH5%2BviIiIiRJERERysvLazQ/cOBAderUSd27d1d%2Bfr7zbcLi4mKVlZUpMjJS9fX1Kisr05kzZ9S1a1dJUkFBgXr06KGOHTs2OYOwsLBGbwcWF5ertrZt/2X1puuvq6v3qv16C3J1D3I1j0zdoy3lavwlkFdffVWDBg3SW2%2B9pa1bt%2BpXv/qVS7mSvruvaebMmT%2B4xrXXXqvq6mqtWLFCFy5c0P/93/9p%2BfLlGjt2rO666y6dOXNGmzZtUk1NjQ4ePKgdO3Y477saO3asduzYoYMHD6qmpkabNm1SSUmJEhISJEmJiYnasGGDTpw4oYqKCi1ZskT9%2B/fXNddco549eyomJkZLlixRRUWFTpw4ofXr12vs2LGmYwIAAJcxH8uyLJML1tbWqqKiQmVlZerZs6ckKTMzU/Hx8QoNDW3yOvn5%2BVqyZIkOHz6sjh07auTIkZo2bZratWunw4cPKzU1VV9%2B%2BaU6d%2B6spKQkJSYmOp%2B7fft2bdiwQadPn1bv3r01b9489evXT5JUU1OjNWvW6M0335TD4VBcXJwWL16sLl26SJLOnDmjRYsWKSsrS76%2Bvho9erRmzpzZpPvFfkxxcfN%2Bk7IpbDZfJaTtM76uu%2ByccWtrb%2BGSbDZfhYYGqbTU0WZ%2BymoJ5Ooe5GoembpHa%2BbarVvT34EyyXjB%2Buyzz/TQQw8pMTFRs2fPliQNGjRINTU1eumllxr9BmBbQcGiYLVl5Ooe5GoembpHWyxYxt8i/P3vf68777xTKSkpzrG//e1vGjhwoJYtW2b6dAAAAB7HeME6cuSIpkyZ4rw5XfrupvYpU6bo008/NX06AAAAj2O8YHXo0EHHjx9vNH7q1CkFBASYPh0AAIDHMV6w7rrrLi1cuFD//Oc/VVFRIYfDoYMHD2rRokXO3%2BQDAAC4nBn/HKzHHntMJ06c0AMPPCAfHx/neEJCgh5//HHTpwMAAPA4xguW3W7Xc889p6NHj%2BqLL76Qv7%2B/evXq5fzIBgAAgMud2/6pnPDwcIWHh7treQAAAI9lvGAdPXpUixYt0kcffaSamppG859//rnpUwIAAHgU4wVr4cKFOnnypGbOnNmsf78PAADgcmG8YH3yySf605/%2BpOjoaNNLAwAAeAXjH9MQGhqqoKAg08sCAAB4DeMFa9KkSVq5cqXKy83/23sAAADewPhbhHv27NGnn36quLg4denSxeWfzJGkv//976ZPCQAA4FGMF6y4uDjFxcWZXhYAAMBrGC9YjzzyiOklAQAAvIrxe7AkKTc3V3PmzNGvfvUrnT59Wunp6crKynLHqQAAADyO8YL1r3/9S%2BPGjdPXX3%2Btf/3rX7pw4YI%2B//xzPfDAA9q9e7fp0wEAAHgc4wUrLS1NDzzwgDZv3ix/f39J0tNPP617771X69atM306AAAAj%2BOWV7BGjx7daHzChAn66quvTJ8OAADA4xgvWP7%2B/qqoqGg0fvLkSdntdtOnAwAA8DjGC9bQoUO1YsUKlZaWOscKCgqUmpqqO%2B64w/TpAAAAPI7xgjV79mxVV1frlltuUVVVlRITEzVixAjZbDY9/vjjpk8HAADgcYx/DlaHDh302muv6cCBA/rf//1f1dfXKzIyUj//%2Bc/l6%2BuWT4UAAADwKMYLVoP4%2BHjFx8e7a3kAAACPZbxgDR48WD4%2BPj84z79FCAAALnfGC9YvfvELl4JVU1OjY8eOae/evZoxY4bp0wEAAHgc4wVr%2BvTpFx1/9dVX9dFHH%2Bnee%2B81fUoAAACP0mJ3nQ8aNEh79uxpqdMBAAC0mhYrWNnZ2Wrfvn1LnQ4AAKDVGH%2BL8PtvAVqWpYqKCn3xxRe8PQgAANoE4wXryiuvbPRbhP7%2B/po8ebJGjhxp%2BnQAAAAex3jBWrZsmeklAQAAvIrxgpWTk9PkY2%2B%2B%2BWbTpwcAAGh1xgvWfffdJ8uynF8NGt42bBjz8fHR559/bvr0AAAArc54wXr22We1dOlSzZ49WwMGDJC/v78OHTqkhQsX6p577tGgQYNMnxIAAMCjGP%2BYhuXLl2vBggUaOnSoOnTooPbt26t///5atGiRXnrpJV111VXOLwAAgMuR8YJVVFSkK664otF4hw4dVFpaavp0AAAAHsd4wYqKitLKlStVUVHhHCsrK9Mzzzyj%2BPh406cDAADwOMbvwZo3b54mT56sgQMHqmfPnpKko0ePqlu3bnrllVdMnw4AAMDjGC9YvXr1UmZmpnbs2KGCggJJ0j333KPhw4fLbrebPh0AAIDHMV6wJCk4OFjjxo3T119/rauvvlrSd5/mDgAA0BYYvwfLsiylpaXp5ptv1ogRI3Tq1CnNnj1bc%2BbMUU1NjenTAQAAeBzjBWvz5s3avn27FixYoHbt2kmShg4dqvfff19r1qwxfToAAACPY7xgbdmyRU8%2B%2BaQSExOdn95%2B9913KzU1VW%2B//bbp0wEAAHgc4wXr66%2B/1n/91381Gr/22mt15swZ06cDAADwOMYL1lVXXaXPPvus0fiePXucN7wDAABczoz/FuGDDz6op556SqdPn5ZlWTpw4IBee%2B01bd68WXPmzDF9OgAAAI9jvGCNGTNGtbW12rBhg6qrq/Xkk0%2BqS5cuSklJ0YQJE0yfDgAAwOMYL1hvvvmm/vu//1vjx4/X2bNnZVmWunTpYvo0AAAAHsv4PVhPP/2082b2zp07U64AAECbY7xg9ezZU1988YXpZQEAALyG8bcIIyIiNHPmTL3wwgvq2bOn2rdv7zK/dOlS06cEAADwKMYL1vHjxxUTEyNJKi4uNr08AACAxzNSsJYuXapHH31UgYGB2rx5s4klLyk3N1fLly/XkSNH5O/vr1tvvVW/%2B93v1LlzZx06dEhPP/208vPzFRoaqqlTp2rcuHHO527btk3r169XcXGxfvazn2n%2B/PmKjo6WJNXV1SktLU3bt29XVVWVBgwYoKeeekphYWGSpJKSEs2fP1/Z2dny8/PTqFGjNHv2bNlsbvl3swEAgBcycg/WK6%2B8oqqqKpexBx98UEVFRSaWb6S6ulq/%2Bc1vFB0drQ8%2B%2BEBvvfWWysrK9MQTT%2BjcuXOaMmWKRo8erZycHKWmpmrp0qXODz/NysrS4sWLtWzZMuXk5GjUqFGaOnWqc/8bNmzQ/v379frrr2vfvn0KCAjQvHnznOeeMWOGAgMDtW/fPmVkZOjAgQPatGmTW64TAAB4JyMFy7KsRmMff/yxvv32WxPLN3Ly5Eldd911mjZtmtq1a6fQ0FCNHz9eOTk52rVrl0JCQjRx4kTZbDbFx8dr5MiRSk9PlyRt3bpVw4cPV0xMjPz9/XXfffcpNDRUmZmZzvmHHnpIV1xxhTp06KC5c%2Bdq7969OnHihI4dO6bs7GzNmjVLdrtdV199tZKSkpxrAwAASG64B6sl/OxnP9MLL7zgMvbuu%2B/q%2BuuvV15eniIjI13mevfurYyMDElSfn6%2BxowZ02g%2BNzdX5eXlOnXqlMvzu3btqk6dOjl/MzIkJETdu3d3zvfq1UsnT57U%2BfPnFRwcLEkqKipqdP%2BZzRbofJvRFD8/478E6lY2m%2BfvtyFTb8vW05Gre5CreWTqHm0xV68sWP/OsiytXr1au3fv1quvvqpXXnlFdrvd5ZiAgABVVlZKkhwOxw/OOxwOSVJgYGCj%2BYa57z%2B34XFlZaWzYG3ZskXr1q1zOW7atGlKTk7%2BTy7V64WGBrX2FposONh%2B6YPQbOTqHuRqHpm6R1vK1VjB8vHxMbVUk1VUVGjOnDk6cuSIXn31VV177bWy2%2B0qLy93Oa66ulpBQd/9x91ut6u6urrRfGhoqLMsff9%2BsobnW5bVaK7hccP6kjR%2B/HgNHjzY5TibLVClpY7/4Gob87afBExfvzv4%2BfkqONiu8%2BerVFdX39rbuWyQq3uQq3lk6h6tmWtr/XBvrGA9/fTTLp95VVNTo2eeecaleEjmPgfr%2BPHjeuihh3TllVcqIyNDnTt3liRFRkZq//79Lsfm5%2BcrIiJC0nef05WXl9dofuDAgerUqZO6d%2B%2Bu/Px859uExcXFKisrU2RkpOrr61VWVqYzZ86oa9eukqSCggL16NFDHTt2dK4XFhbW6O3A4uJy1da27b%2Bs3nT9dXX1XrVfb0Gu7kGu5pGpe7SlXI28BHLzzTeruLhYX3/9tfMrOjpapaWlLmNff/21idPp3Llzmjx5sm666Sa9%2BOKLznIlSQkJCTpz5ow2bdqkmpoaHTx4UDt27HDedzV27Fjt2LFDBw8eVE1NjTZt2qSSkhIlJCRIkhITE7VhwwadOHFCFRUVWrJkifr3769rrrlGPXv2VExMjJYsWaKKigqdOHFC69ev19ixY41cFwAAuDwYeQWrpT77qsEbb7yhkydPaufOnXrnnXdc5j755BO99NJLSk1N1dq1a9W5c2fNmzdPAwYMkCTFx8drwYIFWrhwoU6fPq3evXtr48aNCgkJkfTdvVK1tbWaOHGiHA6H4uLitHr1auf6a9eu1aJFizRkyBD5%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%2BdcXV2dli9frltuuUXR0dGaOnWqioqKnPMlJSVKSkpSbGys4uLilJqaqtraWvdfKAAAuGx4dMH66KOPNH78eB0/ftw5du7cOU2ZMkWjR49WTk6OUlNTtXTpUn322WeSpKysLC1evFjLli1TTk6ORo0apalTp6qqqkqStGHDBu3fv1%2Bvv/669u3bp4CAAM2bN8%2B5/owZMxQYGKh9%2B/YpIyNDBw4c0KZNm1r0ugEAgHfz2IK1bds2zZw5UykpKS7ju3btUkhIiCZOnCibzab4%2BHiNHDlS6enpkqStW7dq%2BPDhiomJkb%2B/v%2B677z6FhoYqMzPTOf/QQw/piiuuUIcOHTR37lzt3btXJ06c0LFjx5Sdna1Zs2bJbrfr6quvVlJSknNtAACApvDYgnXbbbfpvffe09133%2B0ynpeXp8jISJex3r17Kzc3V5KUn5//g/Pl5eU6deqUy3zXrl3VqVMnffHFF8rLy1NISIi6d%2B/unO/Vq5dOnjyp8%2BfPm75EAABwmbK19gZ%2BSLdu3S467nA4ZLfbXcYCAgJUWVl5yXmHwyFJCgwMbDTfMPf95zY8rqysVHBwcJP2XlRUpOLiYpcxmy1QYWFhTXp%2BU/n5eWw/viibzfP325Cpt2Xr6cjVPcjVPDJ1j7aYq8cWrB9it9tVXl7uMlZdXa2goCDnfHV1daP50NBQZ1lquB/r%2B8%2B3LKvRXMPjhvWbYsuWLVq3bp3L2LRp05ScnNzkNS5HoaFNz7C1BQfbL30Qmo1c3YNczSNT92hLuXpdwYqMjNT%2B/ftdxvLz8xURESFJioiIUF5eXqP5gQMHqlOnTurevbvL24jFxcUqKytTZGSk6uvrVVZWpjNnzqhr166SpIKCAvXo0UMdO3Zs8h7Hjx%2BvwYMHu4zZbIEqLXU0%2B3p/jLf9JGD6%2Bt3Bz89XwcF2nT9fpbq6%2BtbezmWDXN2DXM0jU/dozVxb64d7rytYCQkJeuaZZ7Rp0yZNnDhRH330kXbs2KH169dLksaOHatp06Zp2LBhiomJUXp6ukpKSpSQkCBJSkxM1IYNG9S3b1%2BFhoZqyZIl6t%2B/v6655hpJUkxMjJYsWaJFixaptLRU69ev19ixY5u1x7CwsEZvBxYXl6u2tm3/ZfWm66%2Brq/eq/XoLcnUPcjWPTN2jLeXqdQUrNDRUL730klJTU7V27Vp17txZ8%2BbN04ABAyRJ8fHxWrBggRYuXKjTp0%2Brd%2B/e2rhxo0JCQiR991ZdbW2tJk6cKIfDobi4OK1evdq5/tq1a7Vo0SINGTJEvr6%2BGj16tJKSklrlWgEAgHfysSzLau1NtAXFxeWXPqiZbDZfJaTtM76uu%2ByccWtrb%2BGSbDZfhYYGqbTU0WZ%2BymoJ5Ooe5GoembpHa%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%2BfMjIydODAAW3atKm1twUAALwEBet7jh07puzsbM2aNUt2u11XX321kpKSlJ6e3tpbAwAAXoKC9T15eXkKCQlR9%2B7dnWO9evXSyZMndf78%2BVbcGQAA8Ba21t6Ap3E4HLLb7S5jDY8rKysVHBx8yTWKiopUXFzsMmazBSosLMzcRiX5%2BXlXP7bZPH%2B/DZl6W7aejlzdg1zNI1P3aIu5UrC%2BJzAwUFVVVS5jDY%2BDgoKatMaWLVu0bt06l7FHHnlE06dPN7PJ/6%2BoqEiTe%2BRp/PjxxstbW1VUVKQ//ekFMjWMXN2DXM0jU/doi7m2nSrZRBERESorK9OZM2ecYwUFBerRo4c6duzYpDXGjx%2BvN954w%2BVr/PjxxvdaXFysdevWNXq1DD8dmboHuboHuZpHpu7RFnPlFazv6dmzp2JiYrRkyRItWrRIpaWlWr9%2BvcaOHdvkNcLCwtpMQwcAAI3xCtZFrF27VrW1tRoyZIh%2B%2Bctf6uc//7mSkpJae1sAAMBL8ArWRXTt2lVr165t7W0AAAAv5bdw4cKFrb0J/HRBQUHq379/k2/Ax6WRqXuQq3uQq3lk6h5tLVcfy7Ks1t4EAADA5YR7sAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbA8XElJiZKSkhQbG6u4uDilpqaqtrb2osfu2bNHI0eOVFRUlIYNG6bdu3e38G69Q3MybfDuu%2B9qyJAhLbRD79ScXP/85z/rrrvuUnR0tO666y6lp6e38G69Q1Mzra%2Bv17PPPqvbb79d0dHRGjlypDIzM1thx97hp3wP%2BPLLL9WvXz9lZWW10C69T3Ny/c1vfqO%2BffsqOjra%2BbV3794W3rGbWfBov/71r63HHnvMqqystI4fP24NHz7c2rhxY6Pjjh49avXt29d67733rJqaGuvtt9%2B2brzxRuvUqVOtsGvP1tRMLcuyLly4YD3//PNWnz59rEGDBrXwTr1LU3N97733rNjYWOuTTz6x6uvrrY8//tiKjY213nnnnVbYtWdraqavvPKKNXjwYOvYsWOWZVnW%2B%2B%2B/b1133XXOx3DVnO8BlmVZlZWV1ogRI6zIyEjr4MGDLbhT79KcXOPi4qysrKwW3mHLomB5sMLCQisyMtKlJL399tvWHXfc0ejYlStXWvfff7/L2IMPPmitWbPG7fv0Js3J1LK%2B%2B4bx4IMPWqtWraJg/Yjm5Prqq69azz33nMvYtGnTrMWLF7t9n96kOZnW1dVZDofDsizL%2Bvbbb62MjAwrOjraOn36dIvt11s093uAZVnW7NmzrdWrV1OwfkRzcj1%2B/Lh13XXXWeXl5S25xRbHW4QeLC8vTyEhIerevbtzrFevXjp58qTOnz/vcmx%2Bfr4iIyNdxnr37q3c3NwW2au3aE6mkvTMM8/ohRde0DXXXNOS2/Q6zcl14sSJmjJlivNxSUmJcnJydMMNN7TYfr1BczL19fVVYGCgPvjgA/Xr109z587Vo48%2BqrCwsJbetsdr7veAv/71rzp27JgeeeSRltym12lOrocPH1ZQUJBSUlI0YMAAjRgxQhkZGS29ZbeztfYG8MMcDofsdrvLWMPjyspKBQcH/%2BixAQEBqqysdP9GvUhzMpWkHj16tNjevFlzc21QXFyshx9%2BWDfccINGjBjh9n16k5%2BSaf/%2B/XX48GHl5OQoKSlJ3bp10913390i%2B/UWzcm1oKBAq1at0p///Gf5%2Bfm16D69TXNyvXDhgqKiopSSkqKIiAhlZWVp%2BvTpCgoK0rBhw1p03%2B7EK1geLDAwUFVVVS5jDY%2BDgoJcxu12u6qrq13GqqurGx3X1jUnUzTdT8n1008/1dixYxUeHq4NGzbIZuPnvX/3UzJt166dbDab4uPj9T//8z/asWOH2/fpbZqa67fffquUlBQ98cQTuvLKK1t0j96oOX9eR48erRdeeEF9%2BvSRv7%2B/brvtNo0ePVo7d%2B5ssf22BAqWB4uIiFBZWZnOnDnjHCsoKFCPHj3UsWNHl2MjIyOVl5fnMpafn6%2BIiIgW2au3aE6maLrm5pqRkaH77rtPkydP1ooVK9SuXbuW3K5XaE6my5Yt07Jly1zGLly4oJCQkBbZqzdpaq6HDx9WYWGh5s6dq9jYWMXGxkqSfvvb32rhwoUtvW2P15w/rxkZGY3K1IULF9S%2BffsW2WuLae2bwPDjJkyYYKWkpFjl5eXO38pYu3Zto%2BPy8/Otvn37Wm%2B//bbztwj79u1rffXVV62wa8/W1Ez/3euvv85N7pfQ1Fzfeecd6/rrr7f27t3bCrv0Lk3N9L333rP69etnZWdnW3V1ddbf//53q1%2B/ftZHH33UCrv2fD/le4BlWdzkfglNzfXll1%2B24uPjrSNHjlh1dXXW7t27rRtvvNHKyclphV27DwXLwxUXF1vTp0%2B3%2Bvfvbw0YMMBatmyZVVtba1mWZUVFRVnbt293Hrt3715r1KhRVlRUlDV8%2BHDrH//4R2tt26M1J9MGFKxLa2quI0aMsK677jorKirK5Wv%2B/PmtuX2P1Jw/q1u3brXuvPNO66abbrISExMpsD/ip3wPsCwK1qU0Ndf6%2BnrrD3/4gzVo0CDrxhtvtIYPH27t3LmzNbfuFj6WZVmt/SoaAADA5YR7sAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAw/4fR2PKN4DqfowAAAAASUVORK5CYII%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common8345004444573943185\">\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.0</td>\n",
       "        <td class=\"number\">48141</td>\n",
       "        <td class=\"number\">99.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.05</td>\n",
       "        <td class=\"number\">14</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.06</td>\n",
       "        <td class=\"number\">12</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.1</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.13</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.51</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.25</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.32</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.17</td>\n",
       "        <td class=\"number\">3</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.08</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (2)</td>\n",
       "        <td class=\"number\">3</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\"  id=\"extreme8345004444573943185\">\n",
       "            <p class=\"h4\">Minimum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.0</td>\n",
       "        <td class=\"number\">48141</td>\n",
       "        <td class=\"number\">99.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.05</td>\n",
       "        <td class=\"number\">14</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.06</td>\n",
       "        <td class=\"number\">12</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.08</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.1</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "            <p class=\"h4\">Maximum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.21</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:17%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.25</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.32</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:83%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.44</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:34%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.51</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "</div><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_temp\">temp<br/>\n",
       "            <small>Numeric</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-6\">\n",
       "    <div class=\"row\">\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "                <tr>\n",
       "                    <th>Distinct count</th>\n",
       "                    <td>5843</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>12.1%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "\n",
       "        </div>\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "\n",
       "                <tr>\n",
       "                    <th>Mean</th>\n",
       "                    <td>281.21</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>310.07</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Zeros (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "<div class=\"col-md-3 collapse in\" id=\"minihistogram8089706752032045360\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAABBUlEQVR4nO3awQnCUBRFQSOWZBH25NqeLMKeng3IQQOSEGb2H%2B7m8DZ/mZk5AR%2Bdtx4Ae3bZegDHdb0/f37zetz%2BsGQ9FwSCQCAIBIJAIAgEgkAgCASCQCAIBIJAIPhqwlfWfBs5AhcEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBMIyM7P1CNgrFwSCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCATCGwt1DPhBE2rEAAAAAElFTkSuQmCC\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives8089706752032045360,#minihistogram8089706752032045360\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives8089706752032045360\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles8089706752032045360\"\n",
       "                                                  aria-controls=\"quantiles8089706752032045360\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram8089706752032045360\" aria-controls=\"histogram8089706752032045360\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common8089706752032045360\" aria-controls=\"common8089706752032045360\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme8089706752032045360\" aria-controls=\"extreme8089706752032045360\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Extreme Values</a></li>\n",
       "\n",
       "    </ul>\n",
       "\n",
       "    <div class=\"tab-content\">\n",
       "        <div role=\"tabpanel\" class=\"tab-pane active row\" id=\"quantiles8089706752032045360\">\n",
       "            <div class=\"col-md-4 col-md-offset-1\">\n",
       "                <p class=\"h4\">Quantile statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Minimum</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>258.34</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>272.16</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>282.45</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>291.81</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>299.29</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>310.07</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>310.07</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>19.646</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "            <div class=\"col-md-4 col-md-offset-2\">\n",
       "                <p class=\"h4\">Descriptive statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Standard deviation</th>\n",
       "                        <td>13.338</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.047432</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>39.915</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>281.21</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>10.874</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>-2.2472</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>13555000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>177.91</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>376.7 KiB</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-8 col-md-offset-2\" id=\"histogram8089706752032045360\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAAgAElEQVR4nO3df1TUdaL/8RcwKAOKYIjVnkoTsOuvIAwsXO%2BqkWtGqVDsyWWtc3TvBsniUSoz11YXyxuWkddKyyzl3KVU2uMurm7nmnndRGvtx3HDQEM9YYKiAgPIr8/3D7/O3okhsd78GHg%2BzuHQvN%2BfeX/e8zof5dXMOHhZlmUJAAAAxnh39QYAAAB6GgoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADDM1tUb6C0qKqqNr%2Bnt7aWBAwNUWelQS4tlfH1PRS5tIxv3yMU9cmkb2bjXHXMZNKh/l5yXZ7A8mLe3l7y8vOTt7dXVW%2BlWyKVtZOMeubhHLm0jG/fI5V8oWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgmK2rNwAAADrG1NX7unoL7bYjI66rt2AUz2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCs2xasoqIiPfLII4qJiVFcXJwef/xxVVZWSpKWLl2qUaNGKSoqyvmVl5fnvO/69es1YcIERUZGKiUlRceOHXPO1dbWatGiRYqNjVV0dLQef/xxORwO5/zXX3%2Bt2bNnKyoqSuPHj9err77aeQ8aAAD0CN2yYNXX12vOnDmKiorS//7v/%2BrPf/6zzp8/r6eeekqS9MUXX2j58uU6dOiQ8ys5OVmSlJ%2Bfr02bNumNN95QYWGhRo4cqfT0dFmWJUlavny5Tp06pZ07d2rXrl06deqUsrOzJUmNjY36zW9%2Bo9GjR6uwsFDr1q1Tbm6uduzY0TVBAAAAj9QtC1ZZWZluueUWpaWlqU%2BfPgoODlZycrIOHjyohoYGffXVVxo1apTb%2B77zzjt66KGHFB4err59%2B2rBggUqKytTYWGh6urqtH37dqWnpysoKEjXXHONFi5cqG3btqmurk4HDx5UeXm50tPT1adPH40YMUIpKSnKzc3t5AQAAIAn65YF6%2Babb9brr78uHx8f59jOnTs1cuRIFRUVqampSTk5Obrzzjs1ZcoUrVu3Ti0tLZKkkpISRUREOO/n6%2BurIUOGqKioSMePH1djY6PL/LBhw1RfX6/S0lIVFxdr6NCh6tOnj3M%2BLCxMRUVFnfCoAQBAT2Hr6g1ciWVZWr16tXbv3q3NmzfrzJkziomJUUpKil544QV9%2BeWXSktLk7e3t%2BbMmSOHwyG73e6yhp%2Bfn2pra1VTUyNJ8vf3d85dPtbhcLi9r91uV21t7VXtuby8XBUVFS5jNpu/QkNDr2qdK/Hx8Xb5jkvIpW1k4x65uEcubSMb82y2npVlty5YNTU1WrRokQ4fPqzNmzdr%2BPDhGj58uOLi4pzHjBkzRrNnz1ZBQYHmzJkju92u%2Bvp6l3Xq6%2BsVEBDgLFZ1dXUKCAhw/rck9evXT/7%2B/s7bl/3fY9srLy9Pa9ascRlLS0tTenr6Va3TXoGB9isf1AuRS9vIxj1ycY9c2kY25gQHX93P2u6u2xasEydOaO7cubr%2B%2Buu1ZcsWDRw4UJL0/vvv68yZM/rFL37hPLahoUF%2Bfn6SpPDwcBUXF2vixImSLr1xvbS0VBERERo6dKh8fX1VUlKiW2%2B9VZJ09OhR58uIZ8%2BeVWlpqZqammSzXYqmpKRE4eHhV7X35ORkTZo0yWXMZvPXuXOONu7xw/j4eCsw0K6qqjo1N7cYXduTkUvbyMY9cnGPXNpGNuaZ/hl5WVcVt25ZsC5cuKDZs2dr3LhxysrKkrf3v542tCxLzz77rG666SaNGzdOn376qd5%2B%2B20tWrRIkpSYmKiXX35ZEyZM0NChQ/Xiiy8qJCREY8eOla%2Bvr6ZOnars7Gy99NJLkqTs7Gzde%2B%2B98vPzU2xsrIKDg7Vq1SplZGTo66%2B/1qZNmzR//vyr2n9oaGirlwMrKqrV1NQxfwibm1s6bG1PRi5tIxv3yMU9cmkb2ZjT03LslgVr27ZtKisr044dO/TXv/7VZe7QoUNatGiRnnnmGZ0%2BfVohISGaN2%2Be7r//fklSUlKSqqurlZaWpsrKSo0ePVqvvfaafH19JV36DK2VK1cqISFBjY2Nmjx5spYsWSJJstls2rBhg5YtW6a4uDj5%2B/srJSVFM2fO7NwAAACAR/OyLn9AFDpURUW18TVtNm8FBwfo3DlHj2v%2BPwa5tI1s3CMX98ilbZ6SzdTV%2B7p6C%2B22IyPuygf9AIMG9e%2BQda%2BkZ71lHwAAoBugYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDjBeso0eP6vPPP3fe3rBhg44dO2b6NAAAAN2W0YK1d%2B9ezZgxQ//zP//jHCsoKFBiYqI%2B/vhjk6cCAADotowWrNWrV2vOnDnKyMhwjm3ZskW/%2BtWvlJ2dbfJUAAAA3ZbRgnX06FHNmDGj1XhSUpKOHDli8lQAAADdltGCNXDgQP3zn/9sNV5cXKzAwECTpwIAAOi2bCYXmzFjhn7/%2B9%2BrqqpKY8aMkZeXl7744gutXr3a7TNbAAAAPZHRgpWamqpz585p2bJlampqkmVZstlsSklJ0bx580yeCgAAoNsyWrB8fHz0u9/9TgsWLNDXX38tm82mIUOGyM/Pz%2BRpAAAAujWjBeuyuro6XXPNNbIsS5WVlc7x66%2B/viNOBwAA0K0YLViffvqpnnjiCZ04ccJl3LIseXl56csvvzR5OgAAOtXU1fu6egvwEEYL1h/%2B8AcNGDBAa9asUf/%2B/U0uDQAA4DGMFqwjR47onXfe0b/927%2BZXBYAAMCjGP0crOuuu06NjY0mlwQAAPA4RgtWamqqVqxYoSNHjlC0AABAr2X0JcKcnByVl5dr%2BvTpbud5kzsAAOgNjBYskx8mWlRUpJUrV%2Brw4cPy9fVVXFycnnzySQ0cOFCfffaZ/vCHP6ikpETBwcF69NFH9cADDzjvm5%2Bfr7Vr16qiokI333yzlixZoqioKElSc3OzsrOz9ac//Ul1dXUaN26cfv/73ys0NFSSdPbsWS1ZskQHDhyQj4%2BP7rvvPj3xxBOy2TrkEy0AAEAPZPxX5ZhQX1%2BvOXPm6MEHH9Rrr70mh8OhJ554Qk899ZRWrlypX//610pPT1dycrIOHjyotLQ0DR8%2BXGPGjFFhYaGWL1%2Bu9evXa8yYMcrNzdWjjz6q3bt3y26365VXXtG%2Bffu0detW9e/fX0uWLNHTTz%2BtdevWSZIyMjI0ePBg7d27V2fOnNGjjz6qjRs3as6cOUYeGwAA6PmMvgdLkvbs2aNf/epXGj9%2BvL755hvl5OTovffeu6o1ysrKdMsttygtLU19%2BvRRcHCws0zt2rVLQUFBmjVrlmw2m%2B644w4lJCQoNzdXkvTuu%2B9q2rRpio6Olq%2Bvrx5%2B%2BGEFBweroKDAOT937lxdd9116tevnxYvXqwPP/xQJ0%2Be1PHjx3XgwAFlZmbKbrfrhhtuUGpqqnNtAACA9jBasPbt26fHHntM119/vaqqqtTS0qLm5mY99dRT2rp1a7vXufnmm/X666/Lx8fHObZz506NHDlSxcXFioiIcDk%2BLCxMRUVFkqSSkpI256urq/Xtt9%2B6zIeEhGjAgAE6cuSIiouLFRQUpMGDBzvnhw0bprKyMlVVVV1VFgAAoPcy%2BhLhyy%2B/rAULFujhhx/Wzp07JUnz589XYGCg3nzzTSUmJl71mpZlafXq1dq9e7c2b96st99%2BW3a73eUYPz8/1dbWSpIcDkeb8w6HQ5Lk7%2B/fav7y3Hfve/l2bW2tAgMD27Xn8vJyVVRUuIzZbP7O93mZ4uPj7fIdl5BL28jGPXJxj1zQmWy2nnWdGf%2Bg0f/8z/9sNX733XcrJyfnqterqanRokWLdPjwYW3evFnDhw%2BX3W5XdXW1y3H19fUKCAiQdKkQ1dfXt5oPDg52lqW6ujq397csq9Xc5duX12%2BPvLw8rVmzxmUsLS1N6enp7V7jagQG2q98UC9ELm0jG/fIxT1yQWcIDm7/z1lPYLRg9e/fX6dPn9aNN97oMl5cXKwBAwZc1VonTpzQ3Llzdf3112vLli0aOHCgJCkiIkL79rn%2BLqiSkhKFh4dLksLDw1VcXNxqfsKECRowYIAGDx7s8jJiRUWFzp8/r4iICLW0tOj8%2BfM6c%2BaMQkJCJElHjx7Vtddee1W/%2Bic5OVmTJk1yGbPZ/HXunOOqMrgSHx9vBQbaVVVVp%2BbmFqNrezJyaRvZuEcu7pELOpPpn5GXdVVxM1qwEhISlJWVpaysLHl5ecnhcGjPnj1avny57rnnnnavc%2BHCBc2ePVvjxo1TVlaWvL3/9bRhfHy8nn/%2BeW3cuFGzZs3SJ598ou3bt2vt2rWSpKSkJKWlpWnq1KmKjo5Wbm6uzp49q/j4eEnSzJkz9corr2j06NEKDg7WihUrFBMT4yyF0dHRWrFihZYtW6Zz585p7dq1SkpKuqocQkNDW70cWFFRraamjvkLqrm5pcPW9mTk0jaycY9c3CMXdIaedo0ZLVgZGRn69ttvne%2B1mjFjhizL0s9%2B9jPNnz%2B/3ets27ZNZWVl2rFjh/7617%2B6zB06dEgbNmxQVlaWcnJyNHDgQD399NMaN26cJOmOO%2B7Q0qVL9cwzz%2Bj06dMKCwvT%2BvXrFRQUJOnSS3VNTU2aNWuWHA6HYmNjtXr1auf6OTk5WrZsmSZPnixvb29Nnz5dqampPzYaAADQi3hZlmWZXvT48eP68ssv1dLSooiICIWFhZk%2BhcepqKi%2B8kFXyWbzVnBwgM6dc/S45v9jkEvbyMY9cnGPXFqbunrflQ/CD7IjI65D1h00qP1v8TGpQz6e/KabbtJNN93UEUsDAAB0e0YL1i233CIvL6825/ldhAAAoDcwWrBWrFjhUrCamppUWlqq/Px8PfnkkyZPBQAA0G0ZLVgzZ850O37LLbfoT3/6k%2B677z6TpwMAAOiWOuVjU2%2B77TZ9/PHHnXEqAACALtcpBesvf/nLVX/QKAAAgKcy%2BhLhpEmTXN6DZVmWHA6HqqqqrupzsAAAADyZ0YI1Y8aMVv%2BK0NfXV7fddptuv/12k6cCAADotowWrHnz5plcDgAAwCMZLVhr1qxp97GPPfaYyVMDAAB0G0YL1ieffKJ//OMfkqShQ4eqT58%2BOnbsmBwOh6677jrncV5eXhQsAADQYxktWLfffrsaGxu1evVqhYSESJJqamr0xBNPaOTIkfzSZAAA0CsY/ZiGzZs3a/Hixc5yJUn9%2BvVTRkaG3nrrLZOnAgAA6LaMFqzGxkbV1ta2Gq%2BoqDB5GgAAgG7NaMG666679PTTT2v//v1yOByqqanRnj179Lvf/Y5fkwMAAHoNo%2B/BWrx4sdLT0/Xwww%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%2B88YYKCws1cuRIpaeny7IsSdLy5ct16tQp7dy5U7t27dKpU6eUnZ0tSWpsbNRvfvMbjR49WoWFhVq3bp1yc3O1Y8eOzn3gAADAo3XbgpWfn6%2BFCxdq/vz5LuMNDQ366quvNGrUKLf3e%2Bedd/TQQw8pPDxcffv21YIFC1RWVqbCwkLV1dVp%2B/btSk9PV1BQkK655hotXLhQ27ZtU11dnQ4ePKjy8nKlp6erT58%2BGjFihFJSUpSbm9sZDxkAAPQQtq7eQFvGjx%2BvhIQE2Ww2l5JVVFSkpqYm5eTk6JNPPlH//v2VmJioOXPmyNvbWyUlJZo7d67zeF9fXw0ZMkRFRUUKCgpSY2OjIiIinPPDhg1TfX29SktLVVxcrKFDh6pPnz7O%2BbCwMK1bt%2B6q9l5eXq6KigqXMZvNX6GhoVcbw/fy8fF2%2BY5LyKVtZOMeubhHLuhMNlvPus66bcEaNGiQ2/Hq6mrFxMQoJSVFL7zwgr788kulpaXJ29tbc%2BbMkcPhkN1ud7mPn5%2BfamtrVVNTI0ny9/d3zl0%2B1uFwuL2v3W5XbW3tVe09Ly9Pa9ascRlLS0tTenr6Va3TXoGB9isf1AuRS9vIxj1ycY9c0BmCgwO6egtGdduC1Za4uDjFxcU5b48ZM0azZ89WQUGB5syZI7vdrvr6epf71NfXKyAgwFms6urqFBAQ4PxvSerXr5/8/f2dty/7v8e2V3JysiZNmuQyZrP569w5Rxv3%2BGF8fLwVGGhXVVWdmptbjK7tycilbWTjHrm4Ry7oTKZ/Rl7WVcXN4wrW%2B%2B%2B/rzNnzugXv/iFc6yhoUF%2Bfn6SpPDwcBUXF2vixImSLr1xvbS0VBERERo6dKh8fX1VUlKiW2%2B9VZJ09OhR58uIZ8%2BeVWlpqZqammSzXYqmpKRE4eHhV7XH0NDQVi8HVlRUq6mpY/6Cam5u6bC1PRm5tI1s3CMX98gFnaGnXWMe94KnZVl69tln9dFHH8myLB06dEhvv/22818RJiYmavPmzSoqKtLFixe1atUqhYSEaOzYsbLb7Zo6daqys7NVWVmpyspKZWdn695775Wfn59iY2MVHBysVatW6eLFiyoqKtKmTZuUlJTUxY8aAAB4Eo97Bis%2BPl6LFi3SM888o9OnTyskJETz5s3T/fffL0lKSkpSdXW10tLSVFlZqdGjR%2Bu1116Tr6%2BvpEufobVy5UolJCSosbFRkydP1pIlSyRJNptNGzZs0LJlyxQXFyd/f3%2BlpKRo5syZXfZ4AQCA5/GyLn9AFDpURUW18TVtNm8FBwfo3DlHj3tq9ccgl7aRjXvk4h65tDZ19b6u3kKPtSMj7soH/QCDBvXvkHWvxONeIgQAAOjuKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDjBesPXv2KCUlRePHj9c333yjnJwcvffee6ZPAwAA0G0ZLVj79u3TY489pp/85CeqqqpSS0uLmpub9dRTT2nr1q0mTwUAANBtGS1YL7/8shYsWKDnnntOPj4%2BkqT58%2BdrwYIFevPNN02eCgAAoNsyWrCOHDmiSZMmtRq/%2B%2B67dfLkSZOnAgAA6LaMFqz%2B/fvr9OnTrcaLi4s1YMAAk6cCAADotowWrISEBGVlZenw4cPy8vKSw%2BHQnj17tHz5ct1zzz0mTwUAANBt2UwulpGRoW%2B//VaJiYmSpBkzZsiyLP3sZz/T/PnzTZ4KAACg2zJasL755hutWrVKv/3tb/XPf/5TLS0tioiIUFhYmMnTAAAAdGtGC9Yvf/lLrV27VmPGjNGNN95ocmkAAACPYfQ9WH369JHNZrSzAQAAeByjbei%2B%2B%2B7TnDlzdP/99%2Bumm26Sn5%2Bfy/z06dNNng4AAKBbMlqwXn31VUly%2B6GiXl5eFCwAANArGC1YRUVFJpcDAADwSMZ/2TMAAEBvR8ECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADOv2BauyslLx8fEqLCx0jn322Wd64IEHFBUVpUmTJundd991uU9%2Bfr7i4%2BMVGRmpmTNn6tChQ8655uZmrVy5UnfeeaeioqL06KOPqry83Dl/9uxZpaamauzYsYqNjVVWVpaampo6/oECAIAeo1sXrE8%2B%2BUTJyck6ceKEc%2BzChQv69a9/renTp%2BvgwYPKysrSs88%2Bq88//1ySVFhYqOXLl%2Bu5557TwYMHdd999%2BnRRx9VXV2dJOmVV17Rvn37tHXrVu3du1d%2Bfn56%2BumnnetnZGTI399fe/fu1ZYtW/TRRx9p48aNnfq4AQCAZ%2Bu2BSs/P18LFy7U/PnzXcZ37dqloKAgzZo1SzabTXfccYcSEhKUm5srSXr33Xc1bdo0RUdHy9fXVw8//LCCg4NVUFDgnJ87d66uu%2B469evXT4sXL9aHH36okydP6vjx4zpw4IAyMzNlt9t1ww03KDU11bk2AABAexj9XYQmjR8/XgkJCbLZbC4lq7i4WBERES7HhoWFacuWLZKkkpISJSYmtpovKipSdXW1vv32W5f7h4SEaMCAATpy5IgkKSgoSIMHD3bODxs2TGVlZaqqqlJgYGC79l5eXq6KigqXMZvNX6Ghoe26f3v5%2BHi7fMcl5NI2snGPXNwjF3Qmm61nXWfdtmANGjTI7bjD4ZDdbncZ8/PzU21t7RXnHQ6HJMnf37/V/OW579738u3a2tp2F6y8vDytWbPGZSwtLU3p6entuv/VCgy0X/mgXohc2kY27pGLe%2BSCzhAcHNDVWzCq2xasttjtdlVXV7uM1dfXKyAgwDlfX1/faj44ONhZli6/H%2Bu797csq9Xc5duX12%2BP5ORkTZo0yWXMZvPXuXOOdq/RHj4%2B3goMtKuqqk7NzS1G1/Zk5NI2snGPXNwjF3Qm0z8jL%2Buq4uZxBSsiIkL79u1zGSspKVF4eLgkKTw8XMXFxa3mJ0yYoAEDBmjw4MEqKSlxvkxYUVGh8%2BfPKyIiQi0tLTp//rzOnDmjkJAQSdLRo0d17bXXqn///u3eY2hoaKuXAysqqtXU1DF/QTU3t3TY2p6MXNpGNu6Ri3vkgs7Q064xj3vBMz4%2BXmfOnNHGjRvV2Nio/fv3a/v27c73XSUlJWn79u3av3%2B/GhsbtXHjRp09e1bx8fGSpJkzZ%2BqVV17RyZMnVVNToxUrVigmJkY33nijhgwZoujoaK1YsUI1NTU6efKk1q5dq6SkpK58yAAAwMN43DNYwcHB2rBhg7KyspSTk6OBAwfq6aef1rhx4yRJd9xxh5YuXapnnnlGp0%2BfVlhYmNavX6%2BgoCBJl94L1dTUpFmzZsnhcCg2NlarV692rp%2BTk6Nly5Zp8uTJ8vb21vTp05WamtoljxUAAHgmL8uyrK7eRG9QUVF95YOuks3mreDgAJ075%2BhxT63%2BGOTSNrJxj1zcI5fWpq7ed%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%2Bv5559XaWmp5s2bp9/%2B9rf6%2BOOPNW/ePGVkZOj06dOSpPz8fG3atElvvPGGCgsLNXLkSKWnp8uyLEnS8uXLderUKe3cuVO7du3SqVOnlJ2d3ZUPFQAAeBiPLlijRo1qNZ6fn6%2BxY8fqrrvuks1m0z333KPbb79deXl5kqR33nlHDz30kMLDw9W3b18tWLBAZWVlKiwsVF1dnbZv36709HQFBQXpmmuu0cKFC7Vt2zbV1dV19kMEAAAeyiMLVktLiw4fPqwPPvhAEydO1IQJE7RkyRJduHBBJSUlioiIcDk%2BLCxMRUVFktRq3tfXV0OGDFFRUZGOHz%2BuxsZGl/lhw4apvr5epaWlnfLYAJPSodEAAA3TSURBVACA57N19QZ%2BiMrKSo0YMUJTpkxRTk6Ozp07pyeeeEKZmZlqaGiQ3W53Od7Pz0%2B1tbWSJIfD0eZ8TU2NJMnf3985d/nYq3kfVnl5uSoqKlzGbDZ/hYaGtv9BtoOPj7fLd1xCLm0jG/fIxT1yQWey2XrWdeaRBSskJES5ubnO23a7XZmZmXrwwQcVGxur%2Bvp6l%2BPr6%2BsVEBDgPLat%2BcvFqq6uznn85ZcG%2B/Xr1%2B795eXlac2aNS5jaWlpSk9Pb/caVyMw0H7lg3ohcmkb2bhHLu6RCzpDcHBAV2/BKI8sWEVFRfrzn/%2BsBQsWyMvLS5LU0NAgb29vjRkzRl9%2B%2BaXL8SUlJc73a4WHh6u4uFgTJ06UJDU2Nqq0tFQREREaOnSofH19VVJSoltvvVWSdPToUefLiO2VnJysSZMmuYzZbP46d87sv0b08fFWYKBdVVV1am5uMbq2JyOXtpGNe%2BTiHrmgM5n%2BGXlZVxU3jyxYQUFBys3N1YABA/TII4%2BovLxczz//vGbMmKHp06frrbfeUkFBge6%2B%2B27t2rVLBw4c0OLFiyVJiYmJevnllzVhwgQNHTpUL774okJCQjR27Fj5%2Bvpq6tSpys7O1ksvvSRJys7O1r333is/P7927y80NLTVy4EVFdVqauqYv6Cam1s6bG1PRi5tIxv3yMU9ckFn6GnXmEcWrGuvvVavvfaaXnjhBb3yyivq27evpk2bpszMTPXt21f/9V//pezsbC1evFg/%2BclP9PLLL2vo0KGSpKSkJFVXVystLU2VlZUaPXq0XnvtNfn6%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%2BHEdOHBAmZmZstvtuuGGG5Samqrc3Nyu3hoAAPAQFKzvKC4uVlBQkAYPHuwcGzZsmMrKylRVVdWFOwMAAJ7C1tUb6G4cDofsdrvL2OXbtbW1CgwMvOIa5eXlqqiocBmz2fwVGhpqbqOSfHy8Xb7jEnJpG9m4Ry7udUYu8dl7O2xteBabrWf9%2BaNgfYe/v7/q6upcxi7fDggIaNcaeXl5WrNmjcvYY489pnnz5pnZ5P9XXl6ut956XcnJycbLmycjl7aRjXvk4l5n5PJx1s87ZN2OVl5erry8PK6Z7yCXf%2BlZddGA8PBwnT9/XmfOnHGOHT16VNdee6369%2B/frjWSk5O1bds2l6/k5GTje62oqNCaNWtaPVvW25FL28jGPXJxj1zaRjbukcu/8AzWdwwZMkTR0dFasWKFli1bpnPnzmnt2rVKSkpq9xqhoaG9vrkDANCb8QyWGzk5OWpqatLkyZP14IMP6qc//alSU1O7elsAAMBD8AyWGyEhIcrJyenqbQAAAA/l88wzzzzT1ZvADxcQEKCYmJh2vwG/tyCXtpGNe%2BTiHrm0jWzcI5dLvCzLsrp6EwAAAD0J78ECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbB8lBnz55Vamqqxo4dq9jYWGVlZampqamrt9XpCgoKNGLECEVFRTm/MjMzJUl79uxRQkKCIiMjNXXqVO3evbuLd9vxKisrFR8fr8LCQufYZ599pgceeEBRUVGaNGmS3n33XZf75OfnKz4%2BXpGRkZo5c6YOHTrU2dvuFO6yWbp0qUaNGuVy/eTl5Tnn169frwkTJigyMlIpKSk6duxYV2y9QxQVFemRRx5RTEyM4uLi9Pjjj6uyslIS18z3ZdObr5mPPvpIDzzwgG677TbFxcVp%2BfLlqq%2Bvl8Q145YFj/TLX/7SWrBggVVbW2udOHHCmjZtmrV%2B/fqu3lane%2B6556wnn3yy1fjXX39tjR492vrb3/5mNTY2Wn/5y1%2BsMWPGWN9%2B%2B20X7LJzfPzxx9Zdd91lRUREWPv377csy7LOnz9vxcTEWJs3b7YaGxutv//971ZUVJT12WefWZZlWfv377eioqKsjz/%2B2GpoaLDefPNNKzY21qqtre3Kh2Kcu2wsy7JmzJhhbdu2ze19tm3bZv30pz%2B1vvrqK6u%2Bvt569tlnrWnTplktLS2dte0OU1dXZ8XFxVkvvfSSdfHiRauystKaO3eu9R//8R%2B9/pr5vmwsq/deM2fPnrVGjx5tbd261WpubrZOnz5t3XvvvdZLL73U66%2BZtvAMlgc6fvy4Dhw4oMzMTNntdt1www1KTU1Vbm5uV2%2Bt033xxRcaNWpUq/H8/HyNHTtWd911l2w2m%2B655x7dfvvtLv%2Bn2ZPk5%2Bdr4cKFmj9/vsv4rl27FBQUpFmzZslms%2BmOO%2B5QQkKC81p59913NW3aNEVHR8vX11cPP/ywgoODVVBQ0BUPo0O0lU1DQ4O%2B%2Buort9ePJL3zzjt66KGHFB4err59%2B2rBggUqKytzeQbMU5WVlemWW25RWlqa%2BvTpo%2BDgYCUnJ%2BvgwYO9/pr5vmx68zUzcOBA/f3vf9fMmTPl5eWl8%2BfP6%2BLFixo4cGCvv2baQsHyQMXFxQoKCtLgwYOdY8OGDVNZWZmqqqq6cGedq6WlRYcPH9YHH3ygiRMnasKECVqyZIkuXLigkpISRUREuBwfFhamoqKiLtptxxo/frz%2B9re/6Z577nEZLy4u/t4cekNObWVTVFSkpqYm5eTk6M4779SUKVO0bt06tbS0SGqdja%2Bvr4YMGdIjsrn55pv1%2Buuvy8fHxzm2c%2BdOjRw5stdfM9%2BXTW%2B%2BZiSpX79%2BkqR///d/V0JCggYNGqSZM2f2%2BmumLRQsD%2BRwOGS3213GLt%2Bura3tii11icrKSo0YMUJTpkxRQUGB/vjHP6q0tFSZmZluM/Lz8%2Bux%2BQwaNEg2m63V%2BJVy6A05tZVNdXW1YmJilJKSoj179uj555/Xpk2btGHDBkm9IxtJsixLL774onbv3q3Fixdzzfwf382Ga%2BaSXbt26cMPP5S3t7fS09O5ZtpAwfJA/v7%2Bqqurcxm7fDsgIKArttQlQkJClJubq6SkJNntdl1//fXKzMzUhx9%2BKMuynG%2B%2BvKy%2Bvr5X5SNdKt7fl8OV5nuyuLg4vf3224qJiZGvr6/GjBmj2bNnO1%2B26A3Z1NTUKD09Xdu3b9fmzZs1fPhwrpn/z102XDOX%2BPn5afDgwcrMzNTevXu5ZtpAwfJA4eHhOn/%2BvM6cOeMcO3r0qK699lr179%2B/C3fWuYqKipSdnS3LspxjDQ0N8vb21pgxY1RcXOxyfElJicLDwzt7m10qIiLie3MIDw/vtTm9//77%2BuMf/%2Bgy1tDQID8/P0mts2lsbFRpaWmrlzo81YkTJ5SYmKiamhpt2bJFw4cPl8Q1I7WdTW%2B%2BZv7xj3/o5z//uRoaGpxjDQ0N8vX1VVhYWK%2B/ZtyhYHmgIUOGKDo6WitWrFBNTY1OnjyptWvXKikpqau31qmCgoKUm5ur119/XU1NTSorK9Pzzz%2BvGTNmaPr06Tpw4IAKCgrU1NSkgoICHThwQPfff39Xb7tTxcfH68yZM9q4caMaGxu1f/9%2Bbd%2B%2BXYmJiZKkpKQkbd%2B%2BXfv371djY6M2btyos2fPKj4%2Bvot33vEsy9Kzzz6rjz76SJZl6dChQ3r77beVnJwsSUpMTNTmzZtVVFSkixcvatWqVQoJCdHYsWO7eOc/3oULFzR79mzddttteuONNzRw4EDnXG%2B/Zr4vm958zQwfPlz19fVatWqVGhoa9M0332jlypVKSkrSlClTevU106au%2BweM%2BDEqKiqsefPmWTExMda4ceOs5557zmpqaurqbXW6wsJCKzk52YqKirLGjRtnLV%2B%2B3Kqvr7csy7I%2B/PBD67777rMiIyOtadOmWR988EEX77ZzfPejCD7//HNnRpMnT7a2bt3qcvx7771nTZkyxYqMjLSSkpKsTz/9tLO33Gm%2Bm81///d/W3fffbd16623WpMnT7Y2b97snGtpabHeeOMNa9KkSVZkZKSVkpJiHTt2rCu2bdyGDRusiIgI69Zbb7UiIyNdviyrd18zV8qmt14zlmVZxcXF1iOPPGKNHTvWmjhxovXCCy9YFy9etCyrd18zbfGyrP/z%2BgoAAAB%2BNF4iBAAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAM%2B38s71IgLOm4PwAAAABJRU5ErkJggg%3D%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common8089706752032045360\">\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">274.15</td>\n",
       "        <td class=\"number\">128</td>\n",
       "        <td class=\"number\">0.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">275.15</td>\n",
       "        <td class=\"number\">89</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">274.08</td>\n",
       "        <td class=\"number\">85</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">276.793</td>\n",
       "        <td class=\"number\">78</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">291.15</td>\n",
       "        <td class=\"number\">73</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">271.15</td>\n",
       "        <td class=\"number\">70</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">272.15</td>\n",
       "        <td class=\"number\">69</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">292.15</td>\n",
       "        <td class=\"number\">64</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">287.15</td>\n",
       "        <td class=\"number\">63</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">276.15</td>\n",
       "        <td class=\"number\">63</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (5833)</td>\n",
       "        <td class=\"number\">47422</td>\n",
       "        <td class=\"number\">98.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\"  id=\"extreme8089706752032045360\">\n",
       "            <p class=\"h4\">Minimum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">0.0</td>\n",
       "        <td class=\"number\">10</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">243.39</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:10%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">243.62</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:10%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">244.22</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:10%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">244.82</td>\n",
       "        <td class=\"number\">3</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:30%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "            <p class=\"h4\">Maximum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">308.87</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">308.95</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">309.08</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">309.29</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">310.07</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "</div><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_traffic_volume\">traffic_volume<br/>\n",
       "            <small>Numeric</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-6\">\n",
       "    <div class=\"row\">\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "                <tr>\n",
       "                    <th>Distinct count</th>\n",
       "                    <td>6704</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>13.9%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Missing (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Infinite (n)</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "\n",
       "        </div>\n",
       "        <div class=\"col-sm-6\">\n",
       "            <table class=\"stats \">\n",
       "\n",
       "                <tr>\n",
       "                    <th>Mean</th>\n",
       "                    <td>3259.8</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>7280</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Zeros (%)</th>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "<div class=\"col-md-3 collapse in\" id=\"minihistogram3445092563038050879\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjAsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy%2B17YcXAAABNElEQVR4nO3bwU3DQBBAUYJSEkXQE%2Bf0RBHpabkj9LVGcryy37tH2sv3jOXNbYwx3oA/vR99AFjZ/egD/Pbx9b35N8/H5w4ngQUDYbutDxUPlHlWLAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoHgsuIFuTE9zwSBIBAIp1ixrAzsxQSBcIoJ8ir/mVRbmWxrMUEgCASCFWsxr1jjmGeCQBAIBCsWU676rckEgSAQCAKBIBAIl31J972BGSYIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUC47FUT9neG/5CYIBAEAkEgEAQCQSAQbmOMcfQhYFUmCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCIQf6UMgbYsZaNEAAAAASUVORK5CYII%3D\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives3445092563038050879,#minihistogram3445092563038050879\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives3445092563038050879\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles3445092563038050879\"\n",
       "                                                  aria-controls=\"quantiles3445092563038050879\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram3445092563038050879\" aria-controls=\"histogram3445092563038050879\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common3445092563038050879\" aria-controls=\"common3445092563038050879\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme3445092563038050879\" aria-controls=\"extreme3445092563038050879\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Extreme Values</a></li>\n",
       "\n",
       "    </ul>\n",
       "\n",
       "    <div class=\"tab-content\">\n",
       "        <div role=\"tabpanel\" class=\"tab-pane active row\" id=\"quantiles3445092563038050879\">\n",
       "            <div class=\"col-md-4 col-md-offset-1\">\n",
       "                <p class=\"h4\">Quantile statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Minimum</th>\n",
       "                        <td>0</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>339</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>1193</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>3380</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>4933</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>6197</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>7280</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>7280</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>3740</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "            <div class=\"col-md-4 col-md-offset-2\">\n",
       "                <p class=\"h4\">Descriptive statistics</p>\n",
       "                <table class=\"stats indent\">\n",
       "                    <tr>\n",
       "                        <th>Standard deviation</th>\n",
       "                        <td>1986.9</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.6095</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>-1.3091</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>3259.8</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>1745.1</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>-0.089381</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>157136284</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>3947600</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>376.7 KiB</td>\n",
       "                    </tr>\n",
       "                </table>\n",
       "            </div>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-8 col-md-offset-2\" id=\"histogram3445092563038050879\">\n",
       "            <img 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vIyW8PX1rHxss13cfJvq9bS6fy7q9W5trd5zudj9QmvU1rZtW6u3pTwyYLVv316SlJmZqcsuu0zBwcGaPHmy7r//fiUlJammpsZpfE1NjYKCgiRJAQEBP9ofGhrqCF5N12P92ONbIicnR8uWLXNqS0tLU3p6eouX4Y1CQ1v%2BO/wpHTsGnH%2BQF6Fe79bW6v0hq/YLrVFb27Ztrd7z8ciAFR4ersbGRtXV1emyyy6TJDU2NkqSrr/%2Bev3P//yP0/ji4mJFRERIkiIiIlRUVNSsf/DgwerUqZO6devmdBrRbrfr5MmTzU4r/pSUlBTFx8c7tdlsgSovb/lRsJbwtHcLF1u/r6%2BPOnYM0OnT1WpoaLRoVq0X9Xq3tlbvuVi9X2wN2tq2be31uivEe2TAGjBggK6%2B%2Bmo9%2BeSTmj9/vs6ePatFixZp6NChGjFihJYsWaLXXntNqamp2rNnjzZu3Kjly5dLkpKTk5WWlqZhw4apd%2B/eWrt2rU6cOKGEhARJUlJSklasWKGoqCiFhoZq3rx56tu3r6655poWzy8sLKzZ6UC7vUL19a3viedKVtXf0NDYpn6X1Ovd2lq9P%2BTNtbe1bdvW6j0fjwxYfn5%2BWr16tRYsWKC77rpLZ8%2BeVXx8vDIzM9WxY0e98sorysrK0pIlS9S5c2fNnDlT/fr1kyT1799fs2fP1pw5c3T8%2BHGFh4dr1apVCgkJkfTdqbz6%2BnqlpqaqsrJScXFxWrx4sTvLBQAAHqadMca4exJtgd1eYfkybTYfJWRvs3y5l8pfJg%2B8qMfbbD4KDQ1SeXllm3iXRL3e7VLWO2zxdkuXdyld7H6hNeK53Lp07drBLev1rIt4AAAAPAABCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwmEd%2BVQ4AwDt40l3nJe%2B88zwuDY5gAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFjM5QGroaHB1asEAABwKZcHrMGDB%2Bu//uu/VFxcfFHLycvL0w033KCYmBjHz7Rp0yRJW7ZsUWJioqKjozVs2DBt3rzZ6bGrVq3S4MGDFR0drbFjx%2BqLL75w9FVVVWnGjBmKi4tT7969lZGRocrKyouaKwAAaFtsrl7hY489pnfeeUevvPKKoqKiNGrUKA0fPlwdOnS4oOV8%2BumnuvfeezV//nyn9pKSEk2aNEnPP/%2B8br/9duXn52vy5MnKz89Xt27dlJubq9WrV%2Bvll1/WNddco0WLFik9PV0bN25Uu3btNHfuXB09elSbNm1SQ0ODJk%2BerOzsbM2ePdvKX0ObNGzxdndP4YL8ZfJAd08BAOChXH4E64EHHtAbb7yhDz74QAMGDNCqVas0aNAgTZkyRR999FGLl/Ppp5%2BqV69ezdpzc3MVGxuroUOHymaz6Z577lGfPn2Uk5MjSVq3bp0efPBBRURE6LLLLtOUKVN05MgRFRQUqLq6Whs3blR6erpCQkJ0%2BeWXa%2BrUqdqwYYOqq6st%2Bx0AAADv5raL3Lt3767HH39cH3zwgdLS0vS3v/1NjzzyiOLj4/Xqq6/%2B5LVajY2NOnDggP7xj39oyJAhGjx4sGbNmqVTp06puLhYkZGRTuPDw8NVWFgoSc36/fz81L17dxUWFuqrr75SXV2dU3/Pnj1VU1OjkpISa38BAADAa7n8FGGTffv26e2331ZeXp5qa2uVkJCgpKQkHT9%2BXC%2B88II%2B/fRTPf/88z/62LKyMt1www266667tGTJEpWXl2v69OmaNm2aamtrFRAQ4DTe399fVVVVkqTKyspz9p85c0aSFBgY6OhrGnsh12GVlpbKbrc7tdlsgQoLC2vxMlrC15cPgV5KNpt7f79N27etbGfqhSdoyX6hrW3btlZvS7k8YC1fvlzvvPOOvvrqK0VFRenxxx/XiBEjFBwc7Bjj6%2Burp5566pzL6NKli9auXev4f0BAgKZNm6b7779fcXFxqqmpcRpfU1OjoKAgx9hz9TcFq%2Brqasf4plOD35/f%2BeTk5GjZsmVObWlpaUpPT2/xMuB%2BoaFB7p6CJKljx4DzD/Ii1IvW7EL2C21t27a1es/H5QFrzZo1GjlypJKTkxUeHv6jY3r27KmpU6eecxmFhYV67733NGXKFLVr106SVFtbKx8fH9100036/PPPncYXFxc7rteKiIhQUVGRhgwZIkmqq6tTSUmJIiMj1aNHD/n5%2Bam4uFg333yzJOnQoUOO04gtlZKSovj4eKc2my1Q5eXWfhqRdwuXltXb60L5%2BvqoY8cAnT5drYaGRrfOxRWoF56gJfuFtrZtW3u97nqz7PKAtXXrVp05c0YnT550tOXl5al///4KDQ2VJN1www264YYbzrmMkJAQrV27Vp06ddLDDz%2Bs0tJSPfvss/r1r3%2Bt%2B%2B67T3/%2B85%2BVl5enO%2B%2B8U/n5%2Bdq5c6cyMzMlSaNGjdLSpUs1ePBg9ejRQ4sWLVKXLl0UGxsrPz8/DRs2TNnZ2XrhhRckSdnZ2RoxYoT8/f1bXGNYWFiz04F2e4Xq61vfEw/n1lq2V0NDY6uZiytQL1qzC9lWbW3btrV6z8flh0A%2B%2B%2Bwz3XXXXY5P9UnSs88%2Bq8TERP373/9u0TKuuOIKrVy5Un/729/Ut29fjRo1SlFRUXrqqafUs2dPvfjii1q5cqX69Omj5cuXa%2BnSperRo4ckKTk5WePGjVNaWpr69eunzz77TCtXrpSfn58kafbs2erevbsSExN1991365e//OVPnq4EAAD4oXbGGOPKFY4ZM0Y9evTQrFmz1L59e0nf3d191qxZOnbsmF555RVXTsdl7PYKy5dps/koIXub5cvFd9x9HyybzUehoUEqL69sE%2B8Kqdc6nnbPOU/Skv0Cz%2BXWpWvXC7vPplVcfgTrwIEDmjBhgiNcSd9d1D5hwgR98sknrp4OAACA5VwesIKDg3X48OFm7ceOHbug65wAAABaK5cHrLvuuktz5szRRx99pDNnzqiyslL//Oc/9fTTTyshIcHV0wEAALCcyz9FOGXKFH399df63e9%2B57jFgiQlJCQoIyPD1dMB4Aaedo2Qu6/HA%2BB5XB6wAgICtHLlSn355Zc6ePCg/Pz81LNnzwu6zxSA5jwttACAN3PbV%2BX06NHDcesEAAAAb%2BLygPXll1/q6aef1p49e1RXV9es/4d3YQcAAPA0Lg9Yc%2BbM0ZEjRzR16lR16OCee1MAAABcSi4PWHv37tWf//xnxcTEuHrVAAAALuHy2zSEhoYqKMg9X7wIAADgCi4PWGPHjtXzzz%2BvigrrvzoGAACgNXD5KcItW7bok08%2BUVxcnC6//HKnr8yRpL/97W%2BunhIAAIClXB6w4uLiFBcX5%2BrVAgAAuIzLA9Zjjz3m6lUCAAC4lMuvwZKkwsJCzZgxQ7/5zW90/PhxrV27VgUFBe6YCgAAgOVcHrD%2B9a9/afTo0frmm2/0r3/9S7W1tfr888/1u9/9Tps3b3b1dAAAACzn8oCVnZ2t3/3ud1q9erX8/PwkSc8884weeughLVu2zNXTAQAAsJxbjmDdd999zdofeOABffHFF66eDgAAgOVcHrD8/Px05syZZu1HjhxRQECAq6cDAABgOZd/inDo0KF67rnntGjRIkfboUOHlJWVpdtvv93V0wGA8xq2eLu7pwDAw7j8CNb06dNVU1OjAQMGqLq6WklJSRoxYoRsNpsyMjJcPR0AAADLufwIVnBwsN544w3t2LFDn332mRobGxUZGalbb71VPj5uuWsEAACApVwesJr0799f/fv3d9fqAQAALhmXB6z4%2BHi1a9funP18FyEAAPB0Lg9Yv/71r50CVl1dnb766itt3bpVkydPdvV0AAAALOfygDVp0qQfbV%2BzZo327Nmjhx56yMUzAgAAsFaruap8yJAh2rJli7unAQAAcNFaTcDauXOnLrvsMndPAwAA4KK5/BThD08BGmN05swZHTx48GedHmxoaNC4ceN01VVXacGCBZKkLVu2KDs7W19//bWuvPJKZWRkaMiQIY7HrFq1SqtXr9bp06cVFRWlP/7xj/rVr34lSaqqqtLcuXP197//XfX19brjjjs0e/ZsBQUFXUTVAACgLXH5Eaxf/OIXuuqqqxw/v/zlLxUVFaV58%2BZp2rRpF7y8ZcuWaffu3Y7/l5SUaNKkSfrDH/6g3bt3a9KkSZo8ebKOHz8uScrNzdXq1av18ssvq6CgQDfeeKPS09NljJEkzZ07V0ePHtWmTZuUn5%2Bvo0ePKjs725riAQBAm%2BDyI1hNR5mssGPHDuXn5%2BvOO%2B90tOXm5io2NlZDhw6VJN1zzz3asGGDcnJylJ6ernXr1unBBx9URESEJGnKlClat26dCgoKdPPNN2vjxo16/fXXFRISIkmaOnWqHnroIWVkZPBdiQAAoEVcHrB27drV4rF9%2BvQ5Z9%2BJEyeUmZmp5cuX67XXXnO0FxcXKzIy0mlseHi4CgsLHf3jx4939Pn5%2Bal79%2B4qLCxUSEiI6urqnB7fs2dP1dTUqKSkRNdff32L5l1aWiq73e7UZrMFKiwsrEWPbylf31ZzCZ1Xstnc%2B/tt2r5sZ6D1aMl%2Boa397ba1elvK5QFr3LhxMsY4fpo03Rurqa1du3b6/PPPf3QZjY2NmjZtmh5%2B%2BGFdd911Tn2VlZXNjjT5%2B/urqqrqvP1nzpyRJAUGBjr6msZWVla2uMacnBwtW7bMqS0tLU3p6ektXgbcLzS0dVx317EjR06B1uJC9gtt7W%2B3rdV7Pi4PWEuXLtX8%2BfM1ffp09evXT35%2Bftq3b5/mzJmjBx980Oli9HNZuXKl2rdvr7FjxzbrCwgIUE1NjVNbTU2N4yL1n%2BpvClbV1dWO8dXV1ZK%2B%2Bw7FlkpJSVF8fLxTm80WqPLyloe0luDdwqVl9fa6UL6%2BPurYMUCnT1eroaHRrXMB8J2W7Bfa2t9ua6/XXW%2BWXR6wFi5cqNmzZ2vQoEGOtr59%2B%2Brpp59WRkaGxowZc95lvPPOOyotLVVsbKwkOQLTX//6V6WmpurAgQNO44uLi9WrVy9JUkREhIqKihxBrq6uTiUlJYqMjFSPHj3k5%2Ben4uJi3XzzzZKkQ4cOOU4jtlRYWFiz04F2e4Xq61vfEw/n1lq2V0NDY6uZC9DWXcjfYlv7221r9Z6Pyw%2BBlJaW6sorr2zWHhwcrPLy8hYt44MPPtDHH3%2Bs3bt3a/fu3RoxYoRGjBih3bt3a%2BTIkdq5c6fy8vJUX1%2BvvLw87dy5U/fee68kadSoUVqzZo0KCwt19uxZPffcc%2BrSpYtiY2MVEBCgYcOGKTs7W2VlZSorK1N2drZGjBghf39/S38PAADAe7k8YEVHR%2Bv55593XO8kSSdPntSzzz6r/v37X/Tye/bsqRdffFErV65Unz59tHz5ci1dulQ9evSQJCUnJ2vcuHFKS0tTv3799Nlnn2nlypXy8/OTJM2ePVvdu3dXYmKi7r77bv3yl7/UU089ddHzAgAAbUc78/0rzV3g0KFD%2Bu1vf6uqqirHabcvv/xSXbt21euvv64rrrjCldNxGbu9wvJl2mw%2BSsjeZvly8Z2/TB7o1vXbbD4KDQ1SeXlliw67D1u83QWzAtq2luwXLvRv19O19nq7du3glvW6/Bqsnj17Ki8vTxs3btShQ4ckSQ8%2B%2BKCGDx/OfaYAAK2ap72RcfcbxbbM5QFLkjp27KjRo0frm2%2B%2B0dVXXy1JjlN0AAAAns7l12AZY5Sdna0%2BffpoxIgROnbsmKZPn64ZM2aorq7O1dMBAACwnMsD1urVq/XOO%2B9o9uzZat%2B%2BvSRp6NCh%2Bvvf/64XXnjB1dMBAACwnMsDVk5Ojp566iklJSU57t5%2Bzz33KCsrS%2B%2B//76rpwMAAGA5lwesb7755ke/0%2B/aa6/Vt99%2B6%2BrpAAAAWM7lAeuqq67S/v37m7Vv2bLFccE7AACAJ3P5pwgfeeQR/fGPf9Tx48dljNGOHTv0xhtvaPXq1ZoxY4arpwMAAGA5lwesUaNGqb6%2BXitWrFBNTY2eeuopXX755Xr88cf1wAMPuHo6AAAAlnN5wHr33Xd19913KyUlRWVlZTLG6PLLL3f1NAAAAC4Zl1%2BD9cwzzzguZu/cuTPhCgAAeB2XB6zu3bvr4MGDrl4tAACAy7j8FGFERISmTsGgRVYAABqASURBVJ2ql156Sd27d9dll13m1D9//nxXTwkAAMBSLg9Yhw8fVu/evSVJdrvd1asHAAC45FwSsObPn68//OEPCgwM1OrVq12xSgAAALdxyTVYr7/%2Buqqrq53aHnnkEZWWlrpi9QAAAC7lkoBljGnW9vHHH%2Bvs2bOuWD0AAIBLufxThAAAAN6OgAUAAGAxlwWsdu3auWpVAAAAbuWy2zQ888wzTve8qqur07PPPqugoCCncdwHCwAAeDqXBKw%2Bffo0u%2BdVTEyMysvLVV5e7oopAAAAuIxLAhb3vgIAAG0JF7kDAABYjIAFAABgMQIWAACAxQhYAAAAFvPYgLVjxw6NHj1at9xyiwYOHKi5c%2BeqpqZGkrRv3z6NHj1aMTExio%2BP1/r1650em5ubq4SEBEVHRyspKUl79%2B519DU0NGjhwoUaMGCAYmJiNHHiRL4zEQAAXBCPDFhlZWX6/e9/rwceeEC7d%2B9Wbm6udu7cqT/96U86deqUJkyYoPvuu0%2B7du1SVlaW5s%2Bfr/3790uSCgoKNHfuXC1YsEC7du3SyJEjNXHiRMeXUa9YsULbt2/XW2%2B9pW3btsnf318zZ850Z7kAAMDDeGTA6ty5sz766CMlJSWpXbt2OnnypM6ePavOnTsrPz9fISEhSk1Nlc1mU//%2B/ZWYmKi1a9dKktavX6/hw4erd%2B/e8vPz07hx4xQaGqq8vDxH//jx43XllVcqODhYmZmZ2rp1q77%2B%2Bmt3lgwAADyIRwYsSQoODpYk3XbbbUpMTFTXrl2VlJSkoqIiRUZGOo0NDw9XYWGhJKm4uPic/RUVFTp27JhTf5cuXdSpUycdPHjwElcEAAC8hcu%2BKudSyc/P16lTpzR16lSlp6erW7duCggIcBrj7%2B%2BvqqoqSVJlZeU5%2BysrKyVJgYGBzfqb%2BlqitLS02Z3rbbZAhYWFtXgZLeHr67H52CPYbO79/TZtX7YzgJ/LFfsx9lU/zuMDlr%2B/v/z9/TVt2jSNHj1aY8eOVUVFhdOYmpoax3ceBgQEOC6G/35/aGioI3g1XY/1Y49viZycHC1btsypLS0tTenp6S1eBtwvNLTl2/xS6tgx4PyDAOBHuHI/xr7KmUcGrI8//lhPPvmk3n33XbVv316SVFtbKz8/P4WHh2v79u1O44uLixURESFJioiIUFFRUbP%2BwYMHq1OnTurWrZvTaUS73a6TJ082O634U1JSUhQfH%2B/UZrMFqry85UfBWoJ3C5eW1dvrQvn6%2BqhjxwCdPl2thoZGt84FgGdyxX6ste%2Br3PVm2SMD1rXXXquamho999xzmjJliux2uxYuXKjk5GTdddddeu655/Taa68pNTVVe/bs0caNG7V8%2BXJJUnJystLS0jRs2DD17t1ba9eu1YkTJ5SQkCBJSkpK0ooVKxQVFaXQ0FDNmzdPffv21TXXXNPi%2BYWFhTU7HWi3V6i%2BvvU98XBurWV7NTQ0tpq5APAsrtx3sK9y5pEBKygoSC%2B99JLmzZungQMHqkOHDkpMTFRaWprat2%2BvV155RVlZWVqyZIk6d%2B6smTNnql%2B/fpKk/v37a/bs2ZozZ46OHz%2Bu8PBwrVq1SiEhIZK%2BO5VXX1%2Bv1NRUVVZWKi4uTosXL3ZnuQAAwMO0M8YYd0%2BiLbDbK84/6ALZbD5KyN5m%2BXLxnb9MHujW9dtsPgoNDVJ5eWWL3hUOW7z9vGMAtC2u2I9d6L7K1bp27eCW9XIRDwAAgMU88hQh4AocEQIA/FwcwQIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiHhuwCgsL9fDDD6tv374aOHCgMjIyVFZWJknat2%2BfRo8erZiYGMXHx2v9%2BvVOj83NzVVCQoKio6OVlJSkvXv3OvoaGhq0cOFCDRgwQDExMZo4caJKS0tdWhsAAPBsHhmwampq9B//8R%2BKiYnR//7v/%2Bq9997TyZMn9eSTT%2BrUqVOaMGGC7rvvPu3atUtZWVmaP3%2B%2B9u/fL0kqKCjQ3LlztWDBAu3atUsjR47UxIkTVV1dLUlasWKFtm/frrfeekvbtm2Tv7%2B/Zs6c6c5yAQCAh/HIgHXkyBFdd911SktLU/v27RUaGqqUlBTt2rVL%2Bfn5CgkJUWpqqmw2m/r376/ExEStXbtWkrR%2B/XoNHz5cvXv3lp%2Bfn8aNG6fQ0FDl5eU5%2BsePH68rr7xSwcHByszM1NatW/X111%2B7s2QAAOBBPDJg/epXv9JLL70kX19fR9umTZt04403qqioSJGRkU7jw8PDVVhYKEkqLi4%2BZ39FRYWOHTvm1N%2BlSxd16tRJBw8evIQVAQAAb2Jz9wQuljFGixcv1ubNm7VmzRq9/vrrCggIcBrj7%2B%2BvqqoqSVJlZeU5%2BysrKyVJgYGBzfqb%2BlqitLRUdrvdqc1mC1RYWFiLl9ESvr4emY8BAC5is13614mm1yJek5x5dMA6c%2BaMZsyYoQMHDmjNmjW69tprFRAQoIqKCqdxNTU1CgoKkiQFBASopqamWX9oaKgjeDVdj/Vjj2%2BJnJwcLVu2zKktLS1N6enpLV4GAAAXKzS05a9dF6tjx4DzD2pDPDZgHT58WOPHj9cvfvELvfnmm%2BrcubMkKTIyUtu3b3caW1xcrIiICElSRESEioqKmvUPHjxYnTp1Urdu3ZxOI9rtdp08ebLZacWfkpKSovj4eKc2my1Q5eUtPwrWErxbAAD8FKtfd36Mr6%2BPOnYM0OnT1WpoaLzk67tQrgyZ3%2BeRAevUqVP67W9/q379%2BikrK0s%2BPv9/0EhISNCzzz6r1157TampqdqzZ482btyo5cuXS5KSk5OVlpamYcOGqXfv3lq7dq1OnDihhIQESVJSUpJWrFihqKgohYaGat68eerbt6%2BuueaaFs8vLCys2elAu71C9fWt74kHAPBernzdaWho5HXuezwyYG3YsEFHjhzRX/7yF33wwQdOfXv37tUrr7yirKwsLVmyRJ07d9bMmTPVr18/SVL//v01e/ZszZkzR8ePH1d4eLhWrVqlkJAQSd%2Bdyquvr1dqaqoqKysVFxenxYsXu7xGAADgudoZY4y7J9EW2O0V5x90gWw2HyVkb7N8uQAA7/CXyQMv%2BTpsNh%2BFhgapvLyyVR7B6tq1g1vWy0U8AAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMUIWAAAABYjYAEAAFiMgAUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyABQAAYDECFgAAgMU8PmCVlZUpISFBBQUFjrZ9%2B/Zp9OjRiomJUXx8vNavX%2B/0mNzcXCUkJCg6OlpJSUnau3evo6%2BhoUELFy7UgAEDFBMTo4kTJ6q0tNRl9QAAAM/n0QFrz549SklJ0eHDhx1tp06d0oQJE3Tfffdp165dysrK0vz587V//35JUkFBgebOnasFCxZo165dGjlypCZOnKjq6mpJ0ooVK7R9%2B3a99dZb2rZtm/z9/TVz5ky31AcAADyTxwas3NxcTZ06VY8//rhTe35%2BvkJCQpSamiqbzab%2B/fsrMTFRa9eulSStX79ew4cPV%2B/eveXn56dx48YpNDRUeXl5jv7x48fryiuvVHBwsDIzM7V161Z9/fXXLq8RAAB4Jpu7J/BzDRo0SImJibLZbE4hq6ioSJGRkU5jw8PD9eabb0qSiouLNWrUqGb9hYWFqqio0LFjx5we36VLF3Xq1EkHDx7U1Vdf3aK5lZaWym63O7XZbIEKCwu7oBrPx9fXY/MxAMAFbLZL/zrR9FrEa5Izjw1YXbt2/dH2yspKBQQEOLX5%2B/urqqrqvP2VlZWSpMDAwGb9TX0tkZOTo2XLljm1paWlKT09vcXLAADgYoWGBrlsXR07Bpx/UBvisQHrXAICAlRRUeHUVlNTo6CgIEd/TU1Ns/7Q0FBH8Gq6HuvHHt8SKSkpio%2BPd2qz2QJVXt7ykNYSvFsAAPwUq193foyvr486dgzQ6dPVamhovOTru1CuDJnf53UBKzIyUtu3b3dqKy4uVkREhCQpIiJCRUVFzfoHDx6sTp06qVu3biouLnacJrTb7Tp58mSz044/JSwsrNnpQLu9QvX1re%2BJBwDwXq583WloaOR17nu8LmAlJCTo2Wef1WuvvabU1FTt2bNHGzdu1PLlyyVJycnJSktL07Bhw9S7d2%2BtXbtWJ06cUEJCgiQpKSlJK1asUFRUlEJDQzVv3jz17dtX11xzjTvLAgDggg1bvP38g1qJv0we6O4pWMrrAlZoaKheeeUVZWVlacmSJercubNmzpypfv36SZL69%2B%2Bv2bNna86cOTp%2B/LjCw8O1atUqhYSESPruWqn6%2BnqlpqaqsrJScXFxWrx4sTtLAgAAHqadMca4exJtgd1ecf5BF8hm81FC9jbLlwsAgKtdqiNYXbt2uCTLPR%2BukgYAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbB%2BxIkTJ/Too48qNjZWcXFxysrKUn19vbunBQAAPAQB60dMnjxZgYGB2rZtm958803t2LFDr732mrunBQAAPAQB6we%2B%2Buor7dy5U9OmTVNAQICuvvpqPfroo1q7dq27pwYAADwEAesHioqKFBISom7dujnaevbsqSNHjuj06dNunBkAAPAUNndPoLWprKxUQECAU1vT/6uqqtSxY8fzLqO0tFR2u92pzWYLVFhYmHUTleTrSz4GAHgHm827XtMIWD8QGBio6upqp7am/wcFBbVoGTk5OVq2bJlT22OPPaZJkyZZM8n/p7S0VL%2B9okgpKSmWh7fWqLS0VDk5OdTrpajXu7WlettSrVLbq7elvCsuWiAiIkInT57Ut99%2B62g7dOiQrrjiCnXo0KFFy0hJSdGGDRucflJSUiyfq91u17Jly5odLfNW1OvdqNe7taV621KtUturt6U4gvUD3bt3V%2B/evTVv3jw9/fTTKi8v1/Lly5WcnNziZYSFhZHiAQBowziC9SOWLFmi%2Bvp63XHHHbr//vt166236tFHH3X3tAAAgIfgCNaP6NKli5YsWeLuaQAAAA/lO2fOnDnungR%2BvqCgIPXt27fFF%2BB7Our1btTr3dpSvW2pVqnt1dsS7Ywxxt2TAAAA8CZcgwUAAGAxAhYAAIDFCFgAAAAWI2ABAABYjIAFAABgMQIWAACAxQhYAAAAFiNgAQAAWIyA5aFOnDihRx99VLGxsYqLi1NWVpbq6%2BvdPa0LVlZWpoSEBBUUFDja9u3bp9GjRysmJkbx8fFav36902Nyc3OVkJCg6OhoJSUlae/evY6%2BhoYGLVy4UAMGDFBMTIwmTpyo0tJSl9VzLoWFhXr44YfVt29fDRw4UBkZGSorK5PknfXu2LFDo0eP1i233KKBAwdq7ty5qqmpkeSd9UrfzW3s2LF64oknHG1btmxRYmKioqOjNWzYMG3evNnpMatWrdLgwYMVHR2tsWPH6osvvnD0VVVVacaMGYqLi1Pv3r2VkZGhyspKl9XzU/Ly8nTDDTcoJibG8TNt2jRJ3lfzyZMnlZGRobi4OPXp00ePPvqo4znnjc/ld99912m7xsTEqFevXurVq5ck79u%2Bl5SBRxozZoyZMmWKqaqqMocPHzbDhw83q1atcve0Lsju3bvN0KFDTWRkpPnnP/9pjDHm5MmTpm/fvmbNmjWmrq7OfPTRRyYmJsbs27fPGGPMP//5TxMTE2N2795tamtrzauvvmri4uJMVVWVMcaYpUuXmsTERHPkyBFTUVFhJk%2BebMaPH%2B%2B2Go0xprq62gwcONC88MIL5uzZs6asrMyMHz/e/P73v/fKek%2BcOGGioqLMW2%2B9ZRoaGszx48fNiBEjzAsvvOCV9TZZvHixue6668z06dONMcZ8%2BeWXJioqynz44Yemrq7OvP/%2B%2B%2Bamm24yx44dM8YYs2HDBnPrrbeaf//736ampsbMnz/fDB8%2B3DQ2NhpjjHniiSfMb3/7W1NeXm6%2B/fZbM2bMGDNnzhy31fd9CxYsME888USzdm%2BsecyYMSYtLc2cOnXKVFRUmMcee8xMmDDBq5/L33fs2DEzcOBA8/bbb3vl9r2UCFgeqKSkxERGRjqe1MYY8/7775vbb7/djbO6MBs2bDC33367ef/9950C1rp168ydd97pNPapp54yGRkZxhhjpkyZYmbOnOnUf/fdd5s333zTGGPM4MGDzbvvvuvos9vt5tprrzWHDx%2B%2BlOX8pEOHDplHHnnE1NfXO9r%2B%2Bte/mltuucUr6zXGmIqKCmOMMY2NjebgwYMmISHBrF692mvr/eijj8w999xj0tPTHQHr%2BeefNw8//LDTuEceecS88MILxhhjfvOb35gVK1Y4%2Bmpra01MTIzZsWOHqaqqMjfeeKPZs2ePo/%2BTTz4xN910k%2BMF2p1SU1PNmjVrmrV7W82ffvqpiYqKcjyfjTGmvLzc/Pvf//ba5/L3NTY2mrFjx5rMzExjjPdt30uNU4QeqKioSCEhIerWrZujrWfPnjpy5IhOnz7txpm13KBBg/Thhx/qnnvucWovKipSZGSkU1t4eLgKCwslScXFxefsr6io0LFjx5z6u3Tpok6dOungwYOXqJLz%2B9WvfqWXXnpJvr6%2BjrZNmzbpxhtv9Mp6JSk4OFiSdNtttykxMVFdu3ZVUlKSV9Z74sQJZWZm6rnnnlNAQICj/adq%2BbF%2BPz8/de/eXYWFhfrqq69UV1fn1N%2BzZ0/V1NSopKTk0hZ0Ho2NjTpw4ID%2B8Y9/aMiQIRo8eLBmzZqlU6dOeV3N%2B/fvV3h4uNatW6eEhAQNGjRICxcuVNeuXb3yufxD77zzjoqLix2nvb1t%2B15qBCwPVFlZ6bQjl%2BT4f1VVlTumdMG6du0qm83WrP3HavP393fU9VP9TefyAwMDm/W3lvP8xhgtWrRImzdvVmZmptfXm5%2Bfr61bt8rHx0fp6eleV29jY6OmTZumhx9%2BWNddd51T38XUeubMGUnOtTaNdfe2LSsr0w033KC77rpLeXl5euONN1RSUqJp06Z5Xc2nTp3SwYMHVVJSotzcXL399ts6fvy4pk%2Bf7nXP5R9qbGzUihUr9J//%2BZ%2BON0zetn0vNQKWBwoMDFR1dbVTW9P/g4KC3DElywQEBDguhm5SU1PjqOun%2Bpv%2BWH/4u/n%2B493pzJkzSk9P18aNG7VmzRpde%2B21Xl2v9N3OtVu3bpo2bZq2bdvmdfWuXLlS7du319ixY5v1XUytTS9C36%2B16d9NL3bu0qVLF61du1bJyckKCAjQL37xC02bNk1bt26VMcaram7fvr0kKTMzU8HBwerSpYsmT56sLVu2XFStrfG5/EMFBQUqLS1VcnKyo81bn9OXCgHLA0VEROjkyZP69ttvHW2HDh3SFVdcoQ4dOrhxZhcvMjJSRUVFTm3FxcWKiIiQ9F3t5%2Brv1KmTunXrpuLiYkef3W7XyZMnmx3WdrXDhw9r1KhROnPmjN58801de%2B21kryz3o8//lh33323amtrHW21tbXy8/NTeHi4V9X7zjvvaOfOnYqNjVVsbKzee%2B89vffee4qNjb3gbVtXV6eSkhJFRkaqR48e8vPzc6r10KFDjlMu7lRYWKjs7GwZYxxttbW18vHx0U033eRVNYeHh6uxsVF1dXWOtsbGRknS9ddf71XP5R/atGmTEhISnI44eetz%2BpJx7yVg%2BLkeeOAB8/jjj5uKigrHpwiXLFni7mn9LN%2B/yL2srMzExsaaV1991dTW1podO3Y4LpI0xjg%2BqbNjxw7HJ3P69OljysvLjTHGLFq0yIwYMcIcPnzY8cmcMWPGuK02Y777ZOTtt99unnjiCdPQ0ODU5431njlzxtx2221m3rx55uzZs%2Babb74xycnJZvbs2V5Z7/dNnz7dcZF7cXGxiYqKMu%2B//77jE1dRUVHmiy%2B%2BMMZ894GOW2%2B91Xz%2B%2BeeOT1wlJCSY2tpaY4wxU6dONWPGjDEnTpwwJ06cMGPGjHEs252OHj1qoqOjzZ/%2B9CdTV1dn/u///s/cf//95sknn/S6mmtra01CQoKZNGmSOXPmjDlx4oR56KGHTFpamtc/l0eMGGHWrVvn1OZt2/dSI2B5KLvdbiZNmmT69u1r%2BvXrZxYsWOD0KTVP8v2AZYwx%2B/fvNykpKSYmJsbccccd5q233nIa//bbb5u77rrLREdHm%2BTkZPPJJ584%2Bmpra82zzz5rbr31VnPLLbeYiRMnmm%2B//dZltfyYV155xURGRpqbb77ZREdHO/0Y4331GmNMUVGRefjhh01sbKwZMmSIef75583Zs2eNMd5Zb5PvByxjjNm6dasZOXKkiY6ONsOHDzf/%2BMc/HH2NjY3m5ZdfNvHx8SY6OtqMHTvW8UJlzHefxJw5c6YZMGCA6dOnj3niiSdMZWWlS%2Bs5l4KCAsc27Nevn5k7d66pqakxxnhfzceOHTOTJ082AwcONLGxsSYjI8OcOnXKGOPdz%2BXo6GinbdfE27bvpdTOmO8d5wUAAMBF4xosAAAAixGwAAAALEbAAgAAsBgBCwAAwGIELAAAAIsRsAAAACxGwAIAALAYAQsAAMBiBCwAAACLEbAAAAAsRsACAACwGAELAADAYgQsAAAAixGwAAAALEbAAgAAsNj/B7Z9%2BfiUfuoYAAAAAElFTkSuQmCC\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common3445092563038050879\">\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">356</td>\n",
       "        <td class=\"number\">50</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">353</td>\n",
       "        <td class=\"number\">50</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">340</td>\n",
       "        <td class=\"number\">47</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">351</td>\n",
       "        <td class=\"number\">44</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">369</td>\n",
       "        <td class=\"number\">42</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">373</td>\n",
       "        <td class=\"number\">42</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">333</td>\n",
       "        <td class=\"number\">42</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">339</td>\n",
       "        <td class=\"number\">41</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">337</td>\n",
       "        <td class=\"number\">40</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">357</td>\n",
       "        <td class=\"number\">40</td>\n",
       "        <td class=\"number\">0.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (6694)</td>\n",
       "        <td class=\"number\">47766</td>\n",
       "        <td class=\"number\">99.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\"  id=\"extreme3445092563038050879\">\n",
       "            <p class=\"h4\">Minimum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">0</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:23%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1</td>\n",
       "        <td class=\"number\">7</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:78%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2</td>\n",
       "        <td class=\"number\">7</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:78%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">3</td>\n",
       "        <td class=\"number\">9</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">5</td>\n",
       "        <td class=\"number\">6</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:67%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "            <p class=\"h4\">Maximum 5 values</p>\n",
       "            \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">7213</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">7217</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">7241</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">7260</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">7280</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "</div><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_weather_description\">weather_description<br/>\n",
       "            <small>Categorical</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-3\">\n",
       "    <table class=\"stats \">\n",
       "        <tr class=\"\">\n",
       "            <th>Distinct count</th>\n",
       "            <td>38</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <th>Unique (%)</th>\n",
       "            <td>0.1%</td>\n",
       "        </tr>\n",
       "        <tr class=\"ignore\">\n",
       "            <th>Missing (%)</th>\n",
       "            <td>0.0%</td>\n",
       "        </tr>\n",
       "        <tr class=\"ignore\">\n",
       "            <th>Missing (n)</th>\n",
       "            <td>0</td>\n",
       "        </tr>\n",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-6 collapse in\" id=\"minifreqtable8834400372105906760\">\n",
       "    <table class=\"mini freq\">\n",
       "        <tr class=\"\">\n",
       "    <th>sky is clear</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:46%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 24.2%\">\n",
       "            11665\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>mist</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:24%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 12.3%\">\n",
       "            5950\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>overcast clouds</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:20%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 10.5%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        5081\n",
       "    </td>\n",
       "</tr><tr class=\"other\">\n",
       "    <th>Other values (35)</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:100%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 52.9%\">\n",
       "            25508\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr>\n",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#freqtable8834400372105906760, #minifreqtable8834400372105906760\"\n",
       "       aria-expanded=\"true\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 extrapadding collapse\" id=\"freqtable8834400372105906760\">\n",
       "    \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">sky is clear</td>\n",
       "        <td class=\"number\">11665</td>\n",
       "        <td class=\"number\">24.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">mist</td>\n",
       "        <td class=\"number\">5950</td>\n",
       "        <td class=\"number\">12.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:51%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">overcast clouds</td>\n",
       "        <td class=\"number\">5081</td>\n",
       "        <td class=\"number\">10.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:44%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">broken clouds</td>\n",
       "        <td class=\"number\">4666</td>\n",
       "        <td class=\"number\">9.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:40%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">scattered clouds</td>\n",
       "        <td class=\"number\">3461</td>\n",
       "        <td class=\"number\">7.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:30%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">light rain</td>\n",
       "        <td class=\"number\">3372</td>\n",
       "        <td class=\"number\">7.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:29%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">few clouds</td>\n",
       "        <td class=\"number\">1956</td>\n",
       "        <td class=\"number\">4.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:17%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">light snow</td>\n",
       "        <td class=\"number\">1946</td>\n",
       "        <td class=\"number\">4.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:17%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Sky is Clear</td>\n",
       "        <td class=\"number\">1726</td>\n",
       "        <td class=\"number\">3.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:15%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">moderate rain</td>\n",
       "        <td class=\"number\">1664</td>\n",
       "        <td class=\"number\">3.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:15%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (28)</td>\n",
       "        <td class=\"number\">6717</td>\n",
       "        <td class=\"number\">13.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:58%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "</div>\n",
       "</div><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_weather_main\">weather_main<br/>\n",
       "            <small>Categorical</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-3\">\n",
       "    <table class=\"stats \">\n",
       "        <tr class=\"\">\n",
       "            <th>Distinct count</th>\n",
       "            <td>11</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <th>Unique (%)</th>\n",
       "            <td>0.0%</td>\n",
       "        </tr>\n",
       "        <tr class=\"ignore\">\n",
       "            <th>Missing (%)</th>\n",
       "            <td>0.0%</td>\n",
       "        </tr>\n",
       "        <tr class=\"ignore\">\n",
       "            <th>Missing (n)</th>\n",
       "            <td>0</td>\n",
       "        </tr>\n",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-6 collapse in\" id=\"minifreqtable1240242728355858117\">\n",
       "    <table class=\"mini freq\">\n",
       "        <tr class=\"\">\n",
       "    <th>Clouds</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:100%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 31.5%\">\n",
       "            15164\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>Clear</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:88%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 27.8%\">\n",
       "            13391\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>Mist</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:39%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 12.3%\">\n",
       "            5950\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr><tr class=\"other\">\n",
       "    <th>Other values (8)</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:90%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 28.4%\">\n",
       "            13699\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr>\n",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#freqtable1240242728355858117, #minifreqtable1240242728355858117\"\n",
       "       aria-expanded=\"true\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 extrapadding collapse\" id=\"freqtable1240242728355858117\">\n",
       "    \n",
       "<table class=\"freq table table-hover\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        <td class=\"fillremaining\">Value</td>\n",
       "        <td class=\"number\">Count</td>\n",
       "        <td class=\"number\">Frequency (%)</td>\n",
       "        <td style=\"min-width:200px\">&nbsp;</td>\n",
       "    </tr>\n",
       "    </thead>\n",
       "    <tr class=\"\">\n",
       "        <td class=\"fillremaining\">Clouds</td>\n",
       "        <td class=\"number\">15164</td>\n",
       "        <td class=\"number\">31.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Clear</td>\n",
       "        <td class=\"number\">13391</td>\n",
       "        <td class=\"number\">27.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:88%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Mist</td>\n",
       "        <td class=\"number\">5950</td>\n",
       "        <td class=\"number\">12.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:39%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Rain</td>\n",
       "        <td class=\"number\">5672</td>\n",
       "        <td class=\"number\">11.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:38%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Snow</td>\n",
       "        <td class=\"number\">2876</td>\n",
       "        <td class=\"number\">6.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:19%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Drizzle</td>\n",
       "        <td class=\"number\">1821</td>\n",
       "        <td class=\"number\">3.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:12%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Haze</td>\n",
       "        <td class=\"number\">1360</td>\n",
       "        <td class=\"number\">2.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:9%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Thunderstorm</td>\n",
       "        <td class=\"number\">1034</td>\n",
       "        <td class=\"number\">2.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Fog</td>\n",
       "        <td class=\"number\">912</td>\n",
       "        <td class=\"number\">1.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:6%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Smoke</td>\n",
       "        <td class=\"number\">20</td>\n",
       "        <td class=\"number\">0.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr>\n",
       "</table>\n",
       "</div>\n",
       "</div>\n",
       "    <div class=\"row headerrow highlight\">\n",
       "        <h1>Correlations</h1>\n",
       "    </div>\n",
       "    \n",
       "    <div class=\"row headerrow highlight\">\n",
       "        <h1>Sample</h1>\n",
       "    </div>\n",
       "    <div class=\"row variablerow\">\n",
       "    <div class=\"col-md-12\" style=\"overflow:scroll; width: 100%%; overflow-y: hidden;\">\n",
       "        <table border=\"1\" class=\"dataframe sample\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>holiday</th>\n",
       "      <th>temp</th>\n",
       "      <th>rain_1h</th>\n",
       "      <th>snow_1h</th>\n",
       "      <th>clouds_all</th>\n",
       "      <th>weather_main</th>\n",
       "      <th>weather_description</th>\n",
       "      <th>date_time</th>\n",
       "      <th>traffic_volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>None</td>\n",
       "      <td>288.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>scattered clouds</td>\n",
       "      <td>2012-10-02 09:00:00</td>\n",
       "      <td>5545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>None</td>\n",
       "      <td>289.36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>broken clouds</td>\n",
       "      <td>2012-10-02 10:00:00</td>\n",
       "      <td>4516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>None</td>\n",
       "      <td>289.58</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>overcast clouds</td>\n",
       "      <td>2012-10-02 11:00:00</td>\n",
       "      <td>4767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>None</td>\n",
       "      <td>290.13</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>overcast clouds</td>\n",
       "      <td>2012-10-02 12:00:00</td>\n",
       "      <td>5026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>None</td>\n",
       "      <td>291.14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75</td>\n",
       "      <td>Clouds</td>\n",
       "      <td>broken clouds</td>\n",
       "      <td>2012-10-02 13:00:00</td>\n",
       "      <td>4918</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "    </div>\n",
       "</div>\n",
       "</div>"
      ],
      "text/plain": [
       "<pandas_profiling.ProfileReport at 0x1a181d5d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "profile = pandas_profiling.ProfileReport(df)\n",
    "display(profile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Include date time and traffic volume only\n",
    "df = df[['date_time', 'traffic_volume']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['date_time']= pd.to_datetime(df['date_time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date_time</th>\n",
       "      <th>traffic_volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-10-02 09:00:00</td>\n",
       "      <td>5545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-10-02 10:00:00</td>\n",
       "      <td>4516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-10-02 11:00:00</td>\n",
       "      <td>4767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-10-02 12:00:00</td>\n",
       "      <td>5026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-10-02 13:00:00</td>\n",
       "      <td>4918</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            date_time  traffic_volume\n",
       "0 2012-10-02 09:00:00            5545\n",
       "1 2012-10-02 10:00:00            4516\n",
       "2 2012-10-02 11:00:00            4767\n",
       "3 2012-10-02 12:00:00            5026\n",
       "4 2012-10-02 13:00:00            4918"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Deal with Missing Dates\n",
    "\n",
    "There are some missing dates, especially in 2015."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df= df.groupby(['date_time'], as_index=False).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = pd.date_range(start= df.date_time.min(), end= df.date_time.max(), freq ='H')\n",
    "df = df.set_index('date_time').reindex(r).interpolate()\n",
    "#or fillna(value=df['traffic_volume'].mean())\n",
    "df = df.reset_index().rename(columns={'index': 'date_time'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#change columns name to fit prophet model\n",
    "df.columns = ['ds', 'y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-10-02 09:00:00</td>\n",
       "      <td>5545.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-10-02 10:00:00</td>\n",
       "      <td>4516.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-10-02 11:00:00</td>\n",
       "      <td>4767.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-10-02 12:00:00</td>\n",
       "      <td>5026.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-10-02 13:00:00</td>\n",
       "      <td>4918.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2012-10-02 14:00:00</td>\n",
       "      <td>5181.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2012-10-02 15:00:00</td>\n",
       "      <td>5584.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2012-10-02 16:00:00</td>\n",
       "      <td>6015.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2012-10-02 17:00:00</td>\n",
       "      <td>5791.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2012-10-02 18:00:00</td>\n",
       "      <td>4770.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2012-10-02 19:00:00</td>\n",
       "      <td>3539.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2012-10-02 20:00:00</td>\n",
       "      <td>2784.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2012-10-02 21:00:00</td>\n",
       "      <td>2361.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2012-10-02 22:00:00</td>\n",
       "      <td>1529.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2012-10-02 23:00:00</td>\n",
       "      <td>963.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2012-10-03 00:00:00</td>\n",
       "      <td>506.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2012-10-03 01:00:00</td>\n",
       "      <td>321.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2012-10-03 02:00:00</td>\n",
       "      <td>273.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2012-10-03 03:00:00</td>\n",
       "      <td>367.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2012-10-03 04:00:00</td>\n",
       "      <td>814.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2012-10-03 05:00:00</td>\n",
       "      <td>2718.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2012-10-03 06:00:00</td>\n",
       "      <td>5673.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2012-10-03 07:00:00</td>\n",
       "      <td>6092.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2012-10-03 08:00:00</td>\n",
       "      <td>6511.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2012-10-03 09:00:00</td>\n",
       "      <td>5471.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2012-10-03 10:00:00</td>\n",
       "      <td>5346.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2012-10-03 11:00:00</td>\n",
       "      <td>5221.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2012-10-03 12:00:00</td>\n",
       "      <td>5097.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2012-10-03 13:00:00</td>\n",
       "      <td>4887.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2012-10-03 14:00:00</td>\n",
       "      <td>5337.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52521</th>\n",
       "      <td>2018-09-29 18:00:00</td>\n",
       "      <td>4569.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52522</th>\n",
       "      <td>2018-09-29 19:00:00</td>\n",
       "      <td>7636.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52523</th>\n",
       "      <td>2018-09-29 20:00:00</td>\n",
       "      <td>3338.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52524</th>\n",
       "      <td>2018-09-29 21:00:00</td>\n",
       "      <td>2950.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52525</th>\n",
       "      <td>2018-09-29 22:00:00</td>\n",
       "      <td>2607.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52526</th>\n",
       "      <td>2018-09-29 23:00:00</td>\n",
       "      <td>3856.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52527</th>\n",
       "      <td>2018-09-30 00:00:00</td>\n",
       "      <td>1826.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52528</th>\n",
       "      <td>2018-09-30 01:00:00</td>\n",
       "      <td>920.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52529</th>\n",
       "      <td>2018-09-30 02:00:00</td>\n",
       "      <td>696.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52530</th>\n",
       "      <td>2018-09-30 03:00:00</td>\n",
       "      <td>364.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52531</th>\n",
       "      <td>2018-09-30 04:00:00</td>\n",
       "      <td>335.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52532</th>\n",
       "      <td>2018-09-30 05:00:00</td>\n",
       "      <td>444.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52533</th>\n",
       "      <td>2018-09-30 06:00:00</td>\n",
       "      <td>802.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52534</th>\n",
       "      <td>2018-09-30 07:00:00</td>\n",
       "      <td>1175.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52535</th>\n",
       "      <td>2018-09-30 08:00:00</td>\n",
       "      <td>2002.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52536</th>\n",
       "      <td>2018-09-30 09:00:00</td>\n",
       "      <td>2882.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52537</th>\n",
       "      <td>2018-09-30 10:00:00</td>\n",
       "      <td>3701.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52538</th>\n",
       "      <td>2018-09-30 11:00:00</td>\n",
       "      <td>4049.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52539</th>\n",
       "      <td>2018-09-30 12:00:00</td>\n",
       "      <td>4429.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52540</th>\n",
       "      <td>2018-09-30 13:00:00</td>\n",
       "      <td>4547.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52541</th>\n",
       "      <td>2018-09-30 14:00:00</td>\n",
       "      <td>8760.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52542</th>\n",
       "      <td>2018-09-30 15:00:00</td>\n",
       "      <td>8604.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52543</th>\n",
       "      <td>2018-09-30 16:00:00</td>\n",
       "      <td>4283.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52544</th>\n",
       "      <td>2018-09-30 17:00:00</td>\n",
       "      <td>4132.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52545</th>\n",
       "      <td>2018-09-30 18:00:00</td>\n",
       "      <td>3947.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52546</th>\n",
       "      <td>2018-09-30 19:00:00</td>\n",
       "      <td>3543.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52547</th>\n",
       "      <td>2018-09-30 20:00:00</td>\n",
       "      <td>2781.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52548</th>\n",
       "      <td>2018-09-30 21:00:00</td>\n",
       "      <td>2159.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52549</th>\n",
       "      <td>2018-09-30 22:00:00</td>\n",
       "      <td>1450.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52550</th>\n",
       "      <td>2018-09-30 23:00:00</td>\n",
       "      <td>954.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>52551 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       ds            y\n",
       "0     2012-10-02 09:00:00  5545.000000\n",
       "1     2012-10-02 10:00:00  4516.000000\n",
       "2     2012-10-02 11:00:00  4767.000000\n",
       "3     2012-10-02 12:00:00  5026.000000\n",
       "4     2012-10-02 13:00:00  4918.000000\n",
       "5     2012-10-02 14:00:00  5181.000000\n",
       "6     2012-10-02 15:00:00  5584.000000\n",
       "7     2012-10-02 16:00:00  6015.000000\n",
       "8     2012-10-02 17:00:00  5791.000000\n",
       "9     2012-10-02 18:00:00  4770.000000\n",
       "10    2012-10-02 19:00:00  3539.000000\n",
       "11    2012-10-02 20:00:00  2784.000000\n",
       "12    2012-10-02 21:00:00  2361.000000\n",
       "13    2012-10-02 22:00:00  1529.000000\n",
       "14    2012-10-02 23:00:00   963.000000\n",
       "15    2012-10-03 00:00:00   506.000000\n",
       "16    2012-10-03 01:00:00   321.000000\n",
       "17    2012-10-03 02:00:00   273.000000\n",
       "18    2012-10-03 03:00:00   367.000000\n",
       "19    2012-10-03 04:00:00   814.000000\n",
       "20    2012-10-03 05:00:00  2718.000000\n",
       "21    2012-10-03 06:00:00  5673.000000\n",
       "22    2012-10-03 07:00:00  6092.000000\n",
       "23    2012-10-03 08:00:00  6511.000000\n",
       "24    2012-10-03 09:00:00  5471.000000\n",
       "25    2012-10-03 10:00:00  5346.333333\n",
       "26    2012-10-03 11:00:00  5221.666667\n",
       "27    2012-10-03 12:00:00  5097.000000\n",
       "28    2012-10-03 13:00:00  4887.000000\n",
       "29    2012-10-03 14:00:00  5337.000000\n",
       "...                   ...          ...\n",
       "52521 2018-09-29 18:00:00  4569.000000\n",
       "52522 2018-09-29 19:00:00  7636.000000\n",
       "52523 2018-09-29 20:00:00  3338.000000\n",
       "52524 2018-09-29 21:00:00  2950.000000\n",
       "52525 2018-09-29 22:00:00  2607.000000\n",
       "52526 2018-09-29 23:00:00  3856.000000\n",
       "52527 2018-09-30 00:00:00  1826.000000\n",
       "52528 2018-09-30 01:00:00   920.000000\n",
       "52529 2018-09-30 02:00:00   696.000000\n",
       "52530 2018-09-30 03:00:00   364.000000\n",
       "52531 2018-09-30 04:00:00   335.000000\n",
       "52532 2018-09-30 05:00:00   444.000000\n",
       "52533 2018-09-30 06:00:00   802.000000\n",
       "52534 2018-09-30 07:00:00  1175.000000\n",
       "52535 2018-09-30 08:00:00  2002.000000\n",
       "52536 2018-09-30 09:00:00  2882.000000\n",
       "52537 2018-09-30 10:00:00  3701.000000\n",
       "52538 2018-09-30 11:00:00  4049.000000\n",
       "52539 2018-09-30 12:00:00  4429.000000\n",
       "52540 2018-09-30 13:00:00  4547.000000\n",
       "52541 2018-09-30 14:00:00  8760.000000\n",
       "52542 2018-09-30 15:00:00  8604.000000\n",
       "52543 2018-09-30 16:00:00  4283.000000\n",
       "52544 2018-09-30 17:00:00  4132.000000\n",
       "52545 2018-09-30 18:00:00  3947.000000\n",
       "52546 2018-09-30 19:00:00  3543.000000\n",
       "52547 2018-09-30 20:00:00  2781.000000\n",
       "52548 2018-09-30 21:00:00  2159.000000\n",
       "52549 2018-09-30 22:00:00  1450.000000\n",
       "52550 2018-09-30 23:00:00   954.000000\n",
       "\n",
       "[52551 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Downsampling dataframe from Hourly to Daily data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.index = df['ds']\n",
    "df = df.resample('D').mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "df= df.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2012-10-02</td>\n",
       "      <td>4219.266667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2012-10-03</td>\n",
       "      <td>3682.708333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2012-10-04</td>\n",
       "      <td>3747.458333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2012-10-05</td>\n",
       "      <td>3964.270833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2012-10-06</td>\n",
       "      <td>3141.166667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds            y\n",
       "0 2012-10-02  4219.266667\n",
       "1 2012-10-03  3682.708333\n",
       "2 2012-10-04  3747.458333\n",
       "3 2012-10-05  3964.270833\n",
       "4 2012-10-06  3141.166667"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fit Prophet to dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<fbprophet.forecaster.Prophet at 0x1a19e38e80>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = Prophet(daily_seasonality=True)\n",
    "p.fit(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Make dataframe for forecasting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "future = p.make_future_dataframe(periods=365, freq = 'D')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2550</th>\n",
       "      <td>2019-09-26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2551</th>\n",
       "      <td>2019-09-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2552</th>\n",
       "      <td>2019-09-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2553</th>\n",
       "      <td>2019-09-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2554</th>\n",
       "      <td>2019-09-30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ds\n",
       "2550 2019-09-26\n",
       "2551 2019-09-27\n",
       "2552 2019-09-28\n",
       "2553 2019-09-29\n",
       "2554 2019-09-30"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "future.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Predict future traffic volume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "forecast = p.predict(future)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>yhat</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2550</th>\n",
       "      <td>2019-09-26</td>\n",
       "      <td>4122.226657</td>\n",
       "      <td>2565.738902</td>\n",
       "      <td>5734.432856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2551</th>\n",
       "      <td>2019-09-27</td>\n",
       "      <td>4106.263510</td>\n",
       "      <td>2481.681339</td>\n",
       "      <td>5735.244361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2552</th>\n",
       "      <td>2019-09-28</td>\n",
       "      <td>3256.393414</td>\n",
       "      <td>1647.696908</td>\n",
       "      <td>4878.832294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2553</th>\n",
       "      <td>2019-09-29</td>\n",
       "      <td>2838.182880</td>\n",
       "      <td>1251.613206</td>\n",
       "      <td>4468.067959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2554</th>\n",
       "      <td>2019-09-30</td>\n",
       "      <td>3909.054273</td>\n",
       "      <td>2241.799133</td>\n",
       "      <td>5503.838135</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ds         yhat   yhat_lower   yhat_upper\n",
       "2550 2019-09-26  4122.226657  2565.738902  5734.432856\n",
       "2551 2019-09-27  4106.263510  2481.681339  5735.244361\n",
       "2552 2019-09-28  3256.393414  1647.696908  4878.832294\n",
       "2553 2019-09-29  2838.182880  1251.613206  4468.067959\n",
       "2554 2019-09-30  3909.054273  2241.799133  5503.838135"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_p = p.plot(forecast)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x1200 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig_p2 = p.plot_components(forecast)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Diagnostics\n",
    "Use cross validation to measure forecast error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:fbprophet:Making 7 forecasts with cutoffs between 2014-10-16 00:00:00 and 2017-09-30 00:00:00\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ds</th>\n",
       "      <th>yhat</th>\n",
       "      <th>yhat_lower</th>\n",
       "      <th>yhat_upper</th>\n",
       "      <th>y</th>\n",
       "      <th>cutoff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014-10-17</td>\n",
       "      <td>2161.760203</td>\n",
       "      <td>770.900512</td>\n",
       "      <td>3693.264858</td>\n",
       "      <td>1058.369704</td>\n",
       "      <td>2014-10-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2014-10-18</td>\n",
       "      <td>1300.243743</td>\n",
       "      <td>-164.751795</td>\n",
       "      <td>2682.461234</td>\n",
       "      <td>1066.069717</td>\n",
       "      <td>2014-10-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2014-10-19</td>\n",
       "      <td>840.155156</td>\n",
       "      <td>-630.644944</td>\n",
       "      <td>2351.047257</td>\n",
       "      <td>1073.769731</td>\n",
       "      <td>2014-10-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2014-10-20</td>\n",
       "      <td>1906.310924</td>\n",
       "      <td>454.129419</td>\n",
       "      <td>3409.698814</td>\n",
       "      <td>1081.469744</td>\n",
       "      <td>2014-10-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2014-10-21</td>\n",
       "      <td>1898.665269</td>\n",
       "      <td>541.282468</td>\n",
       "      <td>3313.107646</td>\n",
       "      <td>1089.169758</td>\n",
       "      <td>2014-10-16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          ds         yhat  yhat_lower   yhat_upper            y     cutoff\n",
       "0 2014-10-17  2161.760203  770.900512  3693.264858  1058.369704 2014-10-16\n",
       "1 2014-10-18  1300.243743 -164.751795  2682.461234  1066.069717 2014-10-16\n",
       "2 2014-10-19   840.155156 -630.644944  2351.047257  1073.769731 2014-10-16\n",
       "3 2014-10-20  1906.310924  454.129419  3409.698814  1081.469744 2014-10-16\n",
       "4 2014-10-21  1898.665269  541.282468  3313.107646  1089.169758 2014-10-16"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from fbprophet.diagnostics import cross_validation\n",
    "df_cv = cross_validation(p, initial='730 days', period='180 days', horizon = '365 days')\n",
    "df_cv.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>horizon</th>\n",
       "      <th>mse</th>\n",
       "      <th>rmse</th>\n",
       "      <th>mae</th>\n",
       "      <th>mape</th>\n",
       "      <th>coverage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>37 days</td>\n",
       "      <td>1.870104e+06</td>\n",
       "      <td>1367.517605</td>\n",
       "      <td>878.721838</td>\n",
       "      <td>0.244364</td>\n",
       "      <td>0.790476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>38 days</td>\n",
       "      <td>1.905246e+06</td>\n",
       "      <td>1380.306360</td>\n",
       "      <td>888.990649</td>\n",
       "      <td>0.246548</td>\n",
       "      <td>0.788796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39 days</td>\n",
       "      <td>1.906301e+06</td>\n",
       "      <td>1380.688685</td>\n",
       "      <td>887.087637</td>\n",
       "      <td>0.245944</td>\n",
       "      <td>0.790476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40 days</td>\n",
       "      <td>1.922381e+06</td>\n",
       "      <td>1386.499427</td>\n",
       "      <td>889.409794</td>\n",
       "      <td>0.245618</td>\n",
       "      <td>0.788235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>41 days</td>\n",
       "      <td>1.935088e+06</td>\n",
       "      <td>1391.074512</td>\n",
       "      <td>890.548751</td>\n",
       "      <td>0.243792</td>\n",
       "      <td>0.786555</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  horizon           mse         rmse         mae      mape  coverage\n",
       "0 37 days  1.870104e+06  1367.517605  878.721838  0.244364  0.790476\n",
       "1 38 days  1.905246e+06  1380.306360  888.990649  0.246548  0.788796\n",
       "2 39 days  1.906301e+06  1380.688685  887.087637  0.245944  0.790476\n",
       "3 40 days  1.922381e+06  1386.499427  889.409794  0.245618  0.788235\n",
       "4 41 days  1.935088e+06  1391.074512  890.548751  0.243792  0.786555"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from fbprophet.diagnostics import performance_metrics\n",
    "df_p = performance_metrics(df_cv)\n",
    "df_p.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from fbprophet.plot import plot_cross_validation_metric\n",
    "fig = plot_cross_validation_metric(df_cv, metric='mape')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}