YouBike Data Analysis/YouBike_EDA.ipynb

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   "source": [
    "For this project, I will analyze YouBike dataset provided by New Taipei City Government.\n",
    "  (https://data.gov.tw/dataset/28318)\n",
    "\n",
    "\n",
    "The data contains the following fields: (I translated all into English)\n",
    "  \n",
    "  \n",
    "\n",
    "| Columns Name | Description|\n",
    "|------|------|\n",
    "| sno |ID number of YouBike Station|\n",
    "| sna |Chinese Station Name|\n",
    "| tot |Station Total Parking Space|\n",
    "| sbi |Number of availble YouBikes|\n",
    "| sarea|Chinese Station Area|\n",
    "| mday|Data Update Time|\n",
    "| lat|Latitude|\n",
    "| lng|Longtitude|\n",
    "| ar|Chinese Address|\n",
    "| sareaen|English Station Area|\n",
    "| snaen|English Station Name|\n",
    "| aren|English Address|\n",
    "| bemp|Available Parking Space|\n",
    "| act|Whether the station is in operation or not|\n",
    "\n",
    "\n",
    "Let's import libraries first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('youbike.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "        <h1>Overview</h1>\n",
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       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
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       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
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       "        <td class=\"fillremaining\">麗園路121號(對面)</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
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       "        <td class=\"fillremaining\">龍泉街131號旁人行道(立體停車場前)</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
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       "        <td class=\"fillremaining\">龍濱路192號對面</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
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       "        <td class=\"fillremaining\">龍米路一段318號(對面停車場)</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
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       "<div class=\"col-md-6 collapse in\" id=\"minivalues-6145101811452347595\"><table border=\"1\" class=\"dataframe example_values\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Last 3 values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table></div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#values-6145101811452347595,#minivalues-6145101811452347595\" aria-expanded=\"false\"\n",
       "       aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 collapse\" id=\"values-6145101811452347595\">\n",
       "    <p class=\"h4\">First 10 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\"> Baochang Rd./Ln. 45, Baochang Rd.</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1st Rd./Ln. 153, Sec. 2, Daguan Rd.</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Aly. 2, Ln. 31, Huqian St./Ln. 31, Huqian St.</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Aly. 23, Ln. 49, Guoqing Rd. (opposite)</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Aly. 265, Sec. 2, Daguan Rd./Heyi 1st Rd., Banqiao Dist.</td>\n",
       "        <td class=\"number\">1</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",
       "    <p class=\"h4\">Last 10 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\">Zhongzheng Rd./Siyuan Rd.(intersection)</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Zhongzheng Road Section / Datong Road (next to the sidewalk)</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Zhong’an St./Ln. 378, Zhonghe Rd.</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Zhuangjing Rd./Ln. 182, Sec. 2, Wenhua Rd.</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Ziyou St., Yonghe Dist.(oppsite)</td>\n",
       "        <td class=\"number\">1</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><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_bemp\">bemp<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>54</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>9.9%</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>23.016</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>81</td>\n",
       "                </tr>\n",
       "                <tr class=\"ignore\">\n",
       "                    <th>Zeros (%)</th>\n",
       "                    <td>0.9%</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "<div class=\"col-md-3 collapse in\" id=\"minihistogram6042281789775369434\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAAS5JREFUeJzt3cFpw0AQQFHLpKQU4Z5ydk8pIj1tGjCf2BA0lt67C/byGa3QSttaa12Ah657LwAm%2B9h7AXv5/Pp%2B%2Bpqf%2B%2B0fVsJkJggEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCITTngd5xbNnSJwfeX8mCASBQBAIBIFAOMQm/ZUPMMBfmCAQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQDvE271R%2B8/b%2BTBAIAoEgEAjj9iBOBzKJCQJBIBDG3WKdnUfDs5ggEAQCQSAQ7EEOYOqj8SPsjba11tp7ETCVWywIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIv/K%2BGmldH2BmAAAAAElFTkSuQmCC\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives6042281789775369434,#minihistogram6042281789775369434\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives6042281789775369434\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles6042281789775369434\"\n",
       "                                                  aria-controls=\"quantiles6042281789775369434\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram6042281789775369434\" aria-controls=\"histogram6042281789775369434\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common6042281789775369434\" aria-controls=\"common6042281789775369434\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme6042281789775369434\" aria-controls=\"extreme6042281789775369434\"\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=\"quantiles6042281789775369434\">\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>8</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>16</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>22</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>29</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>41</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>81</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>81</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>13</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>10.564</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.45897</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>2.7335</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>23.016</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>7.9785</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>0.97875</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>12613</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>111.6</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>4.4 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=\"histogram6042281789775369434\">\n",
       "            <img 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wMBANWnSRElJSdq0aZOknwJYeHg44QoAAFw0vw1YHTt21IcffqiePXt61Lt3765JkyZV3S8pKdEnn3yim2%2B%2BWZK0fft2ud1u3XfffWrXrp369%2B%2Bv1atXX9beAQCAs/ntKcJGjRqdd53i4mI9/PDDCg4O1tChQyVJAQEBio6O1p///Gddc801%2BuCDDzR69GgtXLhQMTExXj12Xl6e8vPzPWouV4giIyMveI5fExQU6PHVX/jrXPgXl8u3n1t/3QeZy1mYy9n8NmCdz9dff63U1FRdeeWVWrBggerXry9JGjlypMd6ffv21fLly7Vy5UqvA1ZWVpYyMzM9aikpKUpNTTXT/FnCwtw1sl27%2BetckCIiQu1uwSv%2Bug8yl7MwlzP5XMCqqKhQUFBQjT7GmjVr9Oc//1l33nmnxo4dK5frX9%2BG%2BfPnq2XLlurQoUNVrbS0VPXq1fN6%2B8nJyUpMTPSouVwhKiw8cenN/0xQUKDCwtw6fvyUKioqjW7bTv46F/7F9GvBNH/dB5nLWZjLDLt%2BofO5gNWpUyf169dP/fv3V9OmTY1vf%2BvWrUpJSdGUKVM0cODAast/%2BOEHLV68WHPnztVvf/tbvfPOO9qyZYueeOIJrx8jMjKy2unA/PwilZfXzI5UUVFZY9u2k7/OBTnmefXXfZC5nIW5nMnnAtZDDz2kpUuX6uWXX1Z0dLQGDBigXr166YorrjCy/f/%2B7/9WeXm5MjIylJGRUVVv06aN5s2bp/HjxyswMFD33HOPioqK1LRpU7300ku6/vrrjTw%2BAADwfwGWZVl2N3Eu33zzjbKzs7V8%2BXIdPnxY3bp104ABA3Trrbfa3dpFyc8vMr5NlytQERGhKiw84Ve/BfjKXE764E6n8fUPGvWVfdA05nIW5jKjUSMzB2gulM9ewt%2B4cWOlpaXpgw8%2BUEpKij7%2B%2BGONGDFCiYmJeuWVV1RRUWF3iwAAAOfkc6cIz9i2bZveeecdrVixQqWlpUpKSlL//v116NAhPfvss9q%2BfbtmzZpld5sAAADV%2BFzAev7557V06VJ9%2B%2B23io6OVlpamnr37l31MQqSFBQUpMcff9zGLgEAAH6ZzwWshQsXqm/fvho4cOAvvouwSZMmGjdu3GXuDAAAwDs%2BF7DWrl2r4uJiHT16tKq2YsUKdejQQREREZKkli1bqmXLlna1CAAA8Kt87iL3f/7zn%2BrevbuysrKqajNnzlSfPn301Vdf2dgZAACAd3wuYP3nf/6nbr/9dqWlpVXVPvroI3Xq1EkzZsywsTMAAADv%2BFzA2rlzpx588EHVrVu3qhYUFKQHH3xQW7dutbEzAAAA7/hcwKpfv772799frf7jjz8qODjYho4AAAAujM8FrO7du2vKlCn67LPPVFxcrBMnTujzzz/X1KlTlZSUZHd7AAAA5%2BVz7yIcO3asvvvuOw0fPlwBAQFV9aSkJI0fP97GzgAAALzjcwHL7XbrxRdf1L59%2B7R7927VqVNHTZo0UePGje1uDQAAwCs%2BF7DOuOGGG3TDDTfY3QYAAMAF87mAtW/fPk2dOlWbN29WWVlZteW7du2yoSsAAADv%2BVzAmjJlig4ePKhx48bpiiuusLsdAACAC%2BZzAWvLli167bXXFBsba3crAAAAF8XnPqYhIiJCoaGhdrcBAABw0XwuYA0ePFizZs1SUVGR3a0AAABcFJ87RbhmzRpt3bpV7dq105VXXunxJ3Mk6eOPP7apMwAAAO/4XMBq166d2rVrZ3cbAAAAF83nAtZDDz1kdwuoIT1mr7O7BQAALgufuwZLknJycjRp0iTdddddOnTokBYtWqQNGzbY3RYAAIBXfC5g7dixQ4MGDdKBAwe0Y8cOlZaWateuXRo%2BfLhWr15td3sAAADn5XMB6%2Bmnn9bw4cP1%2Buuvq06dOpKkJ598Uvfff78yMzNt7g4AAOD8fC5g7dixQ3fccUe1%2Bt13362vv/7aho4AAAAujM8FrDp16qi4uLha/eDBg3K73TZ0BAAAcGF8LmB169ZNf/vb31RYWFhV27t3rzIyMtSlSxf7GgMAAPCSzwWsCRMmqKSkRLfeeqtOnTql/v37q3fv3nK5XBo/frzd7QEAAJyXz30OVv369fXGG29o/fr1%2Buc//6nKyko1a9ZMt912mwIDfS4PAgAAVOOziaVDhw4aMWKEHnjgAXXu3Pmiw1VBQYGSkpI8Pkdr27ZtGjRokGJjY5WYmKjFixd7/Jvs7GwlJSUpJiZG/fv315YtWy5pFgAAULv43BGsxMREBQQE/OLyC/lbhJs3b9bEiRO1f//%2BqtqxY8f04IMPKjU1VcnJydq0aZNSUlLUvHlztW7dWhs2bNC0adM0d%2B5ctW7dWosWLdKf/vQnrV69movsAQCAV3zuCNYf/vAHj1vv3r0VHR2twsJCDRkyxOvtZGdna9y4cUpLS/Oor1q1SuHh4br33nvlcrnUoUMH9enTR4sWLZIkLV68WL169VKbNm1Up04dDR06VBEREVqxYoXROQEAgP/yuSNYo0ePPmd94cKF2rx5s%2B6//36vttOxY0f16dNHLpfLI2Tt2bNHzZo181i3adOmWrJkiSQpNzdXAwYMqLY8JyfnQsYAAAC1mM8FrF/StWtXzZo1y%2Bv1GzVqdM76iRMnqp3qCw4O1smTJ71a7o28vDzl5%2Bd71FyuEEVGRnq9DW8EBQV6fAWcwuXy7X3WX19bzOUszOVsjglYGzduVL169S55O263W0VFRR61kpIShYaGVi0vKSmptjwiIsLrx8jKyqr2Z31SUlKUmpp6kV3/urAwrg2Ds0REhNrdglf89bXFXM7CXM7kcwHr7FOAlmWpuLhYu3fv9vr04K9p1qyZ1q1b51HLzc1VVFSUJCkqKkp79uyptrxTp05eP0ZycrISExM9ai5XiAoLT1xk1%2BcWFBSosDC3jh8/pYqKSqPbBmqS6deCaf762mIuZ2EuM%2Bz6hc7nAtY111xT7V2EderU0ZAhQ9SnT59L3n5SUpJmzpypV199Vffee682b96sZcuW6fnnn5ckDRw4UCkpKerRo4fatGmjRYsW6ciRI0pKSvL6MSIjI6udDszPL1J5ec3sSBUVlTW2baAmOGV/9dfXFnM5C3M5k88FrBkzZtTo9iMiIvTyyy8rIyNDc%2BbMUYMGDfTYY4%2Bpffv2kn76/K3JkydrypQpOnTokJo2baq5c%2BcqPDy8RvsCAAD%2Bw%2BcC1qZNm7xet23btl6tt3v3bo/70dHReuONN35x/X79%2Bqlfv35e9wEAAPBzPhewhg4dKsuyqm5nnDlteKYWEBCgXbt22dIjAADAr/G5gPXcc89p%2BvTpmjBhgtq3b686depo27ZtmjJliu655x517drV7hYBAAB%2Blc99CMVTTz2lyZMnq1u3bqpfv77q1aun%2BPh4TZ06VS%2B//LKuvfbaqhsAAIAv8rmAlZeXp9/%2B9rfV6vXr11dhYaENHQEAAFwYnwtYMTExmjVrloqLi6tqR48e1cyZM9WhQwcbOwMAAPCOz12D9dhjj2nIkCHq1KmTGjduLEnat2%2BfGjVqpAULFtjbHAAAgBd8LmA1adJEK1as0LJly7R3715J0j333KNevXpV%2BxuBAAAAvsjnApYkhYWFadCgQTpw4ICuu%2B46ST99mjsAAIAT%2BNw1WJZl6emnn1bbtm3Vu3dv/fjjj5owYYImTZqksrIyu9sDAAA4L58LWK%2B//rqWLl2qyZMnq27dupKkbt266X//93/17LPP2twdAADA%2BflcwMrKytLjjz%2Bu/v37V316e8%2BePZWRkaH33nvP5u4AAADOz%2BcC1oEDB3TTTTdVqzdv3lyHDx%2B2oSMAAIAL43MB69prr9WXX35Zrb5mzZqqC94BAAB8mc%2B9i3DEiBF64okndOjQIVmWpfXr1%2BuNN97Q66%2B/rkmTJtndHgAAwHn5XMAaMGCAysvL9cILL6ikpESPP/64rrzySqWlpenuu%2B%2B2uz0AAIDz8rmA9e677%2Br3v/%2B9kpOTVVBQIMuydOWVV9rdFgAAgNd87hqsJ598supi9gYNGhCuAACA4/hcwGrcuLF2795tdxsAAAAXzedOEUZFRWncuHGaN2%2BeGjdurHr16nksnz59uk2dAQAAeMfnAtb%2B/fvVpk0bSVJ%2Bfr7N3QAAAFw4nwhY06dP18MPP6yQkBC9/vrrdrcDAABwSXziGqwFCxbo1KlTHrURI0YoLy/Ppo4AAAAunk8ELMuyqtW%2B%2BOILnT592oZuAAAALo1PBCwAAAB/QsACAAAwzGcCVkBAgN0tAAAAGOET7yKUfvoE959/5lVZWZlmzpyp0NBQj/X4HCwAAODrfCJgtW3bttpnXsXGxqqwsFCFhYU2dQUAAHBxfCJg8dlXAADAn/hEwLrc3n33XU2ePNmjVlZWJknasWOHRo4cqQ0bNsjl%2Bte359lnn1WnTp0ua58AAMCZamXA6tu3r/r27Vt1/9ChQxowYIDS09Ml/RSy5s%2Bfr/j4eLtaBAAADuYz7yK0i2VZSk9PV5cuXdSvXz999913OnbsmFq2bGl3awAAwKFqfcBaunSpcnNzNXHiREnS9u3bFRoaqrS0NLVv3169e/fWkiVLbO4SAAA4Sa08RXhGZWWlXnjhBf3xj39U/fr1JUmlpaWKiYlRWlqaoqKitGHDBo0ePVqhoaHq0aOHV9vNy8ur9q5IlytEkZGRRvsPCgr0%2BAo4hcvl2/usv762mMtZmMvZAqxz/SHAWmL9%2BvUaNWqU1q1bp5CQkF9c74knntCRI0c0Z84cr7b73HPPKTMz06OWkpKi1NTUS%2BrX6eIe/cDuFuAj/pHxe7tbAIAaVauPYK1cuVJJSUke4WrJkiXVjlaVlpZ6fAjq%2BSQnJysxMdGj5nKFqLDwxKU3/TNBQYEKC3Pr%2BPFTqqioNLptoCaZfi2Y5q%2BvLeZyFuYyIyIi9Pwr1YBaHbA2b96s%2B%2B%2B/36NWXFysWbNm6frrr1eLFi20du1aLV%2B%2BXPPnz/d6u5GRkdVOB%2BbnF6m8vGZ2pIqKyhrbNlATnLK/%2Butri7mchbmcqVYHrAMHDlQLQkOGDNHJkyf10EMP6ciRI7ruuuv01FNPKS4uzqYuAQCA09TqgLVly5ZqtYCAAI0aNUqjRo2yoSMAAOAP/PsSfgAAABsQsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGBYrQ1YK1asUMuWLRUbG1t1S09PlyStWbNGffr0UUxMjHr06KHVq1fb3C0AAHASl90N2GX79u3q16%2Bfpk%2Bf7lH/5ptvNHr0aM2aNUtdunTRqlWrNGbMGK1atUpXXXWVTd0CAAAnqbVHsLZv365WrVpVq2dnZysuLk7dunWTy%2BVSz5491bZtW2VlZdnQJQAAcKJaeQSrsrJSO3fulNvt1rx581RRUaHOnTtr3Lhxys3NVbNmzTzWb9q0qXJycmzqFvA/PWavs7uFC/L%2BmAS7WwDgMLUyYBUUFKhly5bq3r275syZo8LCQk2YMEHp6ekqLS2V2%2B32WD84OFgnT570evt5eXnKz8/3qLlcIYqMjDTS/xlBQYEeXwHUDJfLP15j/vozg7mcxV/nOlutDFgNGzbUokWLqu673W6lp6frzjvvVLt27VRSUuKxfklJiUJDQ73eflZWljIzMz1qKSkpSk1NvbTGf0FYmPv8KwG4aBER3r/%2BncBff2Ywl7P461xn1MqAlZOTo%2BXLl2vs2LEKCAiQJJWWliowMFCtW7fWrl27PNbPzc095/VavyQ5OVmJiYkeNZcrRIWFJy69%2BZ8JCgpUWJhbx4%2BfUkVFpdFtA/gX069du/jrzwzmcpbLPZddvyDVyoAVHh6uRYsW6Te/%2BY2GDRumvLw8zZw5U3/4wx90xx136LXXXtOKFSt0%2B%2B23a9WqVdq4caMeffRRr7cfGRlZ7XRgfn6RystrZkeqqKissW0DkN%2B9vvz1ZwZzOYu/znWGf58A/QVXX321XnzxRX388ceKj4/XgAEDFB0drccff1xNmjTRf/3Xf%2BnFF19U27Zt9fzzz%2Bu5557TDTfcYHfbAADAIWrlESxJio%2BP1xtvvHHOZbfddptuu%2B22y9wRAADwF7XyCBYAAEBNImDnpTdSAAAO70lEQVQBAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwl90N4NLEPfqB3S0AAICzcAQLAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMKxWBqycnBwNGzZM8fHxSkhI0Pjx41VQUCBJmjx5slq1aqXY2NiqW1ZWls0dAwAAJ6l1AaukpEQjR45UbGysPv30Uy1fvlxHjx7VI488Iknavn27pk2bpi1btlTdkpOTbe4aAAA4Sa0LWAcPHlSLFi2UkpKiunXrKiIiQsnJydq0aZNKS0v11VdfqVWrVna3CQAAHKzWBawbb7xR8%2BbNU1BQUFVt5cqVuvnmm5WTk6Py8nLNmTNHt956q7p3766XXnpJlZWVNnYMAACcplb/LULLsjR79mytXr1aCxcu1OHDhxUfH6/Bgwdr1qxZ2rVrl1JSUhQYGKiRI0d6vd28vDzl5%2Bd71FyuEEVGRhrtPyio1uVjwBYul3%2B81s78zPC3nx3M5Sz%2BOtfZAizLsuxuwg7FxcWaNGmSdu7cqRdeeEHNmzc/53rz5s3TihUr9Pbbb3u97eeee06ZmZketZSUFKWmpl5Sz%2BfCH3sGat4/Mn5vdwsAHKZWHsHav3%2B/HnjgAV1zzTVasmSJGjRoIEn66KOPdPjwYd11111V65aWlio4OPiCtp%2BcnKzExESPmssVosLCE5fe/M/4e/oHfIXp165dgoICFRbm1vHjp1RR4T%2BXPjCXs1zuuSIiQmv8Mc6l1gWsY8eOaciQIWrfvr0yMjIUGPivkGJZlqZPn67rr79e7du319atW7VgwQJNmjTpgh4jMjKy2unA/PwilZf7zwsEqE387bVbUVHpdzNJzOU0/jrXGbUuYL399ts6ePCg3n//fX3wgefptS1btmjSpEmaMmWKDh06pIYNG2r06NHq16%2BfTd0CAAAnqrXXYF1u%2BflFxrfpcgUq6em/G98uAE/vj0mwuwUjXK5ARUSEqrDwhF8dOWAuZ7ncczVqdEWNP8a51LojWABwoXrMXmd3CxfEXwIh4GRcJQ0AAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGCYy%2B4GAABm9Zi9zu4WvPb%2BmAS7WwBqBEewAAAADCNgAQAAGEbAOocjR45o1KhRiouLU7t27ZSRkaHy8nK72wIAAA5BwDqHMWPGKCQkRH//%2B9%2B1ZMkSrV%2B/Xq%2B%2B%2BqrdbQEAAIfgIvezfPvtt9q4caPWrl0rt9ut6667TqNGjdLMmTM1cuRIu9sDAL/ipAvynYg3EdiHgHWWPXv2KDw8XFdddVVVrUmTJjp48KCOHz%2BusLAwG7sDAMB7Tgqw/hYGCVhnOXHihNxut0ftzP2TJ096FbDy8vKUn5/vUXO5QhQZGWmuUUlBQZzhBQD4B5fLv/5PI2CdJSQkRKdOnfKonbkfGhrq1TaysrKUmZnpUXvooYc0evRoM03%2Bv7y8PA25eo%2BSk5ONhzc75eXlKSsri7kcwB9nkpjLaZjLWfx1rrP5V1w0ICoqSkePHtXhw4eranv37tXVV1%2BtK664wqttJCcn6%2B233/a4JScnG%2B81Pz9fmZmZ1Y6WOR1zOYc/ziQxl9Mwl7P461xn4wjWWRo3bqw2bdror3/9q6ZOnarCwkI9//zzGjhwoNfbiIyM9OtUDgAAfh1HsM5hzpw5Ki8v1%2B9%2B9zvdeeeduu222zRq1Ci72wIAAA7BEaxzaNiwoebMmWN3GwAAwKGCpkyZMsXuJnDxQkNDFR8f7/UF%2BE7BXM7hjzNJzOU0zOUs/jrXzwVYlmXZ3QQAAIA/4RosAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELIc6cuSIRo0apbi4OLVr104ZGRkqLy%2B3u62LVlBQoKSkJG3YsKGqtm3bNg0aNEixsbFKTEzU4sWLbezQezk5ORo2bJji4%2BOVkJCg8ePHq6CgQJJzZ5Kk9evXa9CgQbrllluUkJCgadOmqaSkRJKz5zqjoqJCgwcP1sSJE6tqa9asUZ8%2BfRQTE6MePXpo9erVNnZ4YVasWKGWLVsqNja26paeni7J2XMdPXpU48ePV7t27dS2bVuNGjVKeXl5kpy7H7777rsez1NsbKxatWqlVq1aSXL287Vz507de%2B%2B9iouLU8eOHfXkk0%2BqtLRUkrPn8ooFR7rvvvussWPHWidPnrT2799v9erVy5o7d67dbV2Uf/zjH1a3bt2sZs2aWZ9//rllWZZ19OhRKz4%2B3lq4cKFVVlZmffbZZ1ZsbKy1bds2m7v9dadOnbISEhKsZ5991jp9%2BrRVUFBgPfDAA9Z//Md/OHYmy7KsI0eOWNHR0dZbb71lVVRUWIcOHbJ69%2B5tPfvss46e6%2Bdmz55ttWjRwpowYYJlWZa1b98%2BKzo62vrwww%2BtsrIy67333rNat25t/fjjjzZ36p0ZM2ZYEydOrFZ3%2Blz33XeflZKSYh07dswqKiqyHnroIevBBx/0m/3Qsizrxx9/tBISEqx33nnH0c9XRUWFlZCQYL322mtWRUWF9cMPP1jdu3e3MjMzHT2XtziC5UDffvutNm7cqPT0dLndbl133XUaNWqUFi1aZHdrFyw7O1vjxo1TWlqaR33VqlUKDw/XvffeK5fLpQ4dOqhPnz4%2BP%2BPBgwfVokULpaSkqG7duoqIiFBycrI2bdrk2JkkqUGDBvrss8/Uv39/BQQE6OjRozp9%2BrQaNGjg6LnOWL9%2BvVatWqXbb7%2B9qpadna24uDh169ZNLpdLPXv2VNu2bZWVlWVjp97bvn171RGQn3PyXDt27NC2bds0Y8YMhYWFqX79%2Bpo2bZrGjRvnF/uhJFmWpfT0dHXp0kX9%2BvVz9PN17Ngx5efnq7KyUtb//1W%2BwMBAud1uR8/lLQKWA%2B3Zs0fh4eG66qqrqmpNmjTRwYMHdfz4cRs7u3AdO3bUhx9%2BqJ49e3rU9%2BzZo2bNmnnUmjZtqpycnMvZ3gW78cYbNW/ePAUFBVXVVq5cqZtvvtmxM51Rv359SVLnzp3Vp08fNWrUSP3793f8XEeOHNGjjz6qv/3tb3K73VX13Nxcx85VWVmpnTt36pNPPlHXrl3VqVMn/eUvf9GxY8ccPdeXX36ppk2b6s0331RSUpI6duyop556So0aNXL8fnjG0qVLlZubW3Wq2snPV0REhIYOHaqnnnpK0dHR6ty5sxo3bqyhQ4c6ei5vEbAc6MSJEx7/EUiqun/y5Ek7WrpojRo1ksvlqlY/14zBwcGOms%2ByLD3zzDNavXq1Hn30Ub%2BYSfrp6OLatWsVGBio1NRUR89VWVmp9PR0DRs2TC1atPBY5uS5CgoK1LJlS3Xv3l0rVqzQG2%2B8oW%2B%2B%2BUbp6emOnuvYsWPavXu3vvnmG2VnZ%2Budd97RoUOHNGHCBEfPdUZlZaVeeOEF/fGPf6z6hcbJc1VWVio4OFh/%2BctftHXrVi1fvlx79%2B7VnDlzHD2XtwhYDhQSEqJTp0551M7cDw0NtaMl49xud9UF1GeUlJQ4Zr7i4mKlpqZq2bJlWrhwoZo3b%2B74mc4IDg7WVVddpfT0dP3973939Fwvvvii6tatq8GDB1db5uS5GjZsqEWLFmngwIFyu9265pprlJ6errVr18qyLMfOVbduXUnSo48%2Bqvr166thw4YaM2aM1qxZ4%2Bi5ztiwYYPy8vI0cODAqpqT98MPP/xQK1eu1D333KO6desqKipKKSkp%2Bp//%2BR9Hz%2BUtApYDRUVF6ejRozp8%2BHBVbe/evbr66qt1xRVX2NiZOc2aNdOePXs8arm5uYqKirKpI%2B/t379fAwYMUHFxsZYsWaLmzZtLcvZMX3zxhX7/%2B99XvftHkkpLS1WnTh01bdrUsXMtXbpUGzduVFxcnOLi4rR8%2BXItX75ccXFxjn6%2BcnJy9PTTT1dd9yL99HwFBgaqdevWjp2radOmqqysVFlZWVWtsrJSknTTTTc5dq4zVq5cqaSkJIWEhFTVnLwf/vDDDx4/MyTJ5XKpTp06jp7La3ZeYY%2BLd/fdd1tpaWlWUVFR1bsI58yZY3dbl%2BTn7yIsKCiw4uLirFdeecUqLS211q9fb8XGxlrr16%2B3uctfd/ToUatLly7WxIkTrYqKCo9lTp3JsiyruLjY6ty5s/XXv/7VOn36tHXgwAFr4MCB1uTJkx0919kmTJhQ9S7C3NxcKzo62nrvvfeq3uUUHR1tff311zZ3eX4//PCDFRMTY7300ktWWVmZ9f3331t33nmn9cgjjzh6rtLSUispKckaPXq0VVxcbB05csS6//77rZSUFL/YD3v37m29%2BeabHjUnP1979uyxWrVqZb3wwgtWeXm5tX//fqt3797WjBkzHD2XtwhYDpWfn2%2BNHj3aio%2BPt9q3b2/NmDHDKi8vt7utS/LzgGVZlvXll19aycnJVmxsrPW73/3Oeuutt2zszjsvv/yy1axZM%2Bvf//3frZiYGI%2BbZTlzpjP27NljDRs2zIqLi7O6du1qzZo1yzp9%2BrRlWc6e6%2Bd%2BHrAsy7LWrl1r9e3b14qJibF69eplffLJJzZ2d2E2bNhQ9Zy0b9/emjZtmlVSUmJZlrPn%2BvHHH60xY8ZYCQkJVlxcnDV%2B/Hjr2LFjlmU5fz%2BMiYk553Ph5Odr3bp11qBBg6w2bdpYXbp08fi54eS5vBFgWT87hgwAAIBLxjVYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBh/wfi4d21QvFBQQAAAABJRU5ErkJggg%3D%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common6042281789775369434\">\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\">21</td>\n",
       "        <td class=\"number\">33</td>\n",
       "        <td class=\"number\">6.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:11%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">18</td>\n",
       "        <td class=\"number\">31</td>\n",
       "        <td class=\"number\">5.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:10%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">24</td>\n",
       "        <td class=\"number\">26</td>\n",
       "        <td class=\"number\">4.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:9%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">22</td>\n",
       "        <td class=\"number\">24</td>\n",
       "        <td class=\"number\">4.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">27</td>\n",
       "        <td class=\"number\">23</td>\n",
       "        <td class=\"number\">4.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">16</td>\n",
       "        <td class=\"number\">22</td>\n",
       "        <td class=\"number\">4.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">17</td>\n",
       "        <td class=\"number\">22</td>\n",
       "        <td class=\"number\">4.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20</td>\n",
       "        <td class=\"number\">21</td>\n",
       "        <td class=\"number\">3.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">23</td>\n",
       "        <td class=\"number\">20</td>\n",
       "        <td class=\"number\">3.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">12</td>\n",
       "        <td class=\"number\">19</td>\n",
       "        <td class=\"number\">3.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (44)</td>\n",
       "        <td class=\"number\">307</td>\n",
       "        <td class=\"number\">56.0%</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=\"extreme6042281789775369434\">\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\">5</td>\n",
       "        <td class=\"number\">0.9%</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\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:20%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">4</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:40%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">5</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">6</td>\n",
       "        <td class=\"number\">3</td>\n",
       "        <td class=\"number\">0.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:60%\">&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\">61</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">63</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">65</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">71</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">81</td>\n",
       "        <td class=\"number\">1</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_lat\">lat<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>547</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>99.8%</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>25.03</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>24.907</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>25.201</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=\"minihistogram-8425372844644930805\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAAThJREFUeJzt3dFpwzAUQFGndKQO0Z363Z06RHdSFygXElCsWOd850MQLs8yD3wbY4wD%2BNfb2QeAlb2ffYBX8vH1c9fvf78/J52EZxHIYu6N8DiEOJNHLAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBsO2qySMrHezHBIEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBsO0u1jPY93p9JggEgUAQCASBQBAIBIFAuMRrXq9TmcUEgSAQCAKBcIk7yO58Gm4eEwSCQCAIBIJAILikM80VPmltgkAQCASBQFjuDmLxcE27/i8mCITlJgjz7ToNHnEbY4yzDwGr8ogFQSAQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQC4Q9Ubx0JwR%2BltAAAAABJRU5ErkJggg%3D%3D\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives-8425372844644930805,#minihistogram-8425372844644930805\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives-8425372844644930805\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles-8425372844644930805\"\n",
       "                                                  aria-controls=\"quantiles-8425372844644930805\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram-8425372844644930805\" aria-controls=\"histogram-8425372844644930805\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common-8425372844644930805\" aria-controls=\"common-8425372844644930805\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme-8425372844644930805\" aria-controls=\"extreme-8425372844644930805\"\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=\"quantiles-8425372844644930805\">\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>24.907</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>24.952</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>24.992</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>25.021</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>25.067</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>25.135</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>25.201</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>0.2938</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>0.074979</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>0.054336</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.0021708</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>0.74311</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>25.03</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>0.043665</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>0.7182</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>13717</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>0.0029524</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>4.4 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=\"histogram-8425372844644930805\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzt3Xt0VOW9//EPyQQyBCJBia0e14KSDFbAgkAg3I6kBA5IQBFMFalcCh4MIAhyVQE1CxQqCIHKgYMcgSMpCrUeKDcPpatoIaIFoYYSEHM0QEYSIOTCJbN/f/Tn2DGB7MiTzCXv11pZMc9%2BZu/vfHlm/GT2zE49y7IsAQAAwJgwfxcAAAAQaghYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAyrkwGroKBAycnJ2r9/f4Vt%2Bfn56tq1qzZv3uwzvmrVKvXs2VPt2rXT8OHDdfLkydoqFwAABJk6F7AOHjyo1NRU5ebmVtjm8Xg0depUFRYW%2Boxv2bJF69at03/%2B539q//79at26tSZOnCjLsmqrbAAAEETqVMDasmWLpk6dqsmTJ1e6ffny5frRj36kH//4xz7jv/3tb/XYY48pPj5eDRo00JQpU5SXl1fpK2AAAAB1KmB1795du3btUv/%2B/Sts%2B8tf/qKtW7dqzpw5Fbbl5OTI5XJ5f46IiFDz5s2VnZ1do/UCAIDg5PB3AbWpWbNmlY6fO3dOs2bN0tKlSxUVFVVhe3FxsZxOp89YZGSkSkpKbB/b7S6yNS8srJ6aNo1SQUGxPB5OQV4PfbKHPtlHr%2ByhT/bQJ3tqo0/NmjWukf1WpU4FrMpYlqVp06Zp%2BPDhatOmTaVznE6nysrKfMbKysoqDWPSP94o73a7fcYcjoaKjY2tsp7w8DDVq1dPERHhKi/32LwXdQ99soc%2B2Uev7KFP9tAne0K5T3U%2BYJ0%2BfVoHDhzQoUOHtHz5cknSpUuXNG/ePO3YsUMrV65UfHy8jh8/rl69ekmSrl69qlOnTvmcNvxnmZmZysjI8BlLS0vTxIkTbdcVHe2sehLok030yT56ZQ99soc%2B2ROKfarzAeuOO%2B7QZ5995jOWlJSk8ePHa/DgwZKkhx9%2BWMuWLVPPnj3VokULLV68WLfddps6duxY6T5TU1OVlJTkM%2BZwNFRhYXGV9YSHhyk62qmLF0tDLs2bRJ/soU/20St76JM99Mme2uhTTEzlZ5tqWp0PWHYMGTJERUVFSktLU0FBgdq2bauVK1cqIiKi0vmxsbEVTge63UW6ds3%2B4ikv91Rrfl1Fn%2ByhT/bRK3vokz30yZ5Q7FM9i4s51Qq7b3J3OMIUExOlwsLikFtsJtEne%2BiTffTKHvpkD32ypzb65K83udepyzQAAADUBgIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDD%2BVA4QIvot2efvEmz7w6Ru/i4BAGoUr2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAw7hMAwBUIZgugSFxGQwgEPAKFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhoV8wCooKFBycrL279/vHduxY4cGDRqk%2B%2B67T0lJScrIyJDH4/Fu37Jli5KTk9WuXTsNHjxYn376qT9KBwAAQSqkA9bBgweVmpqq3Nxc79iRI0c0bdo0TZo0SR9//LFWrVqlzZs3a%2B3atZKk/fv366WXXtKCBQuUlZWlgQMHaty4cSotLfXTvQAAAMEmZAPWli1bNHXqVE2ePNln/Ouvv9YvfvEL9erVS2FhYWrZsqWSk5OVlZUlSdq0aZMeeOABdejQQRERERoxYoRiYmK0bds2f9wNAAAQhEI2YHXv3l27du1S//79fcb79u2rmTNnen8uKyvTH//4R7Vu3VqSlJOTI5fL5XObuLg4ZWdn13zRAAAgJDj8XUBNadasWZVzLl26pKefflqRkZEaMWKEJKm4uFhOp9NnXmRkpEpKSmwfOz8/X26322fM4Wio2NjYKm8bHh7m8x2Vo0/BzeEIvH%2B3UFpTNdnfUOpTTaJP9oRyn0I2YFXl5MmTmjhxom699Va99dZbatSokSTJ6XSqrKzMZ25ZWZliYmJs7zszM1MZGRk%2BY2lpaZo4caLtfURHO6ueBPoUpGJiovxdwnWFwpqqjf6GQp9qA32yJxT7VCcD1t69e/XMM8/okUce0ZQpU%2BRwfNeG%2BPh4HT9%2B3Gd%2BTk6OevbsaXv/qampSkpK8hlzOBqqsLC4ytuGh4cpOtqpixdLVV7uqXJ%2BXUWfgpudx0JtC6U1VZP9DaU%2B1ST6ZE9t9Mlfv9DVuYD117/%2BVWlpaZo7d66GDBlSYfuQIUOUlpamfv36qUOHDtqwYYPOnTun5ORk28eIjY2tcDrQ7S7StWv2F095uada8%2Bsq%2BhScAvnfLBTWVG3UHwp9qg30yZ5Q7FOdC1hvvPGGrl27pvT0dKWnp3vHO3TooNWrVysxMVFz5szR3LlzdfbsWcXFxWnVqlVq0qSJH6sGAADBpE4ErGPHjnn/%2B4033qhy/qBBgzRo0KCaLAkAAISw0HvbPgAAgJ8RsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwLOQDVkFBgZKTk7V//37v2KFDhzR06FC1b99eSUlJ2rRpk89ttmzZouTkZLVr106DBw/Wp59%2BWttlAwCAIBbSAevgwYNKTU1Vbm6ud%2BzChQsaO3asHnzwQWVlZSk9PV3z58/X4cOHJUn79%2B/XSy%2B9pAULFigrK0sDBw7UuHHjVFpa6q%2B7AQAAgkzIBqwtW7Zo6tSpmjx5ss/4zp071aRJEw0bNkwOh0OJiYlKSUnRhg0bJEmbNm3SAw88oA4dOigiIkIjRoxQTEyMtm3b5o%2B7AQAAglDIBqzu3btr165d6t%2B/v8/48ePH5XK5fMbi4uKUnZ0tScrJybnhdgAAgKo4/F1ATWnWrFml48XFxXI6nT5jkZGRKikpsbXdjvz8fLndbp8xh6OhYmNjq7xteHiYz3dUjj4FN4cj8P7dQmlN1WR/Q6lPNYk%2B2RPKfQrZgHU9TqdTRUVFPmNlZWWKiorybi8rK6uwPSYmxvYxMjMzlZGR4TOWlpamiRMn2t5HdLSz6kmgT0EqJibK3yVcVyisqdrobyj0qTbQJ3tCsU91LmC5XC7t27fPZywnJ0fx8fGSpPj4eB0/frzC9p49e9o%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%2BvD755BMNGDBAQ4cO1caNG1VUVOTvsgAAAGwLuID16KOPauPGjdq%2Bfbu6du2qVatWqXv37poyZYo%2B/PBDf5cHAABQpYALWN9q3ry5Jk%2BerO3btystLU0ffPCBRo8eraSkJL355pu8VwsAAAQsh78LuJ5Dhw7pd7/7nbZt26YrV64oOTlZgwcP1tmzZ/X666/rs88%2B02uvvebvMgEAACoIuIC1YsUKvffee/ryyy/Vtm1bTZ48WQMGDFCjRo28c8LDw/XCCy/4sUoAAIDrC7iAtX79eg0cOFBDhgxRXFxcpXNatmypqVOn1nJlAAAA9gTce7D%2B9Kc/6d///d/lcHyX/bZt26bCwkLvz/fcc4%2BGDRt2U8c5evSohg0bpo4dO6p79%2B56%2BeWXdeXKFUnS3r17lZKSonbt2qlfv37as2fPTR0LAADULQEXsP72t7%2Bpb9%2B%2ByszM9I4tXLhQKSkp%2Bvvf/27kGB6PR08%2B%2BaT69u2rAwcO6J133tGf//xnrVq1SqdOndKECRP09NNP6%2BOPP9aECRM0adIknT171sixAQBA6Au4gPXqq6%2BqT58%2Bmjx5snds9%2B7d6tmzpxYsWGDkGBcuXJDb7ZbH45FlWZKksLAwOZ1ObdmyRR07dlTv3r3lcDjUv39/derUySfwAQAA3EjAvQfr6NGjmj9/vurXr%2B8dCw8P19ixYzV48GAjx4iJidGIESP0yiuv6NVXX1V5ebl%2B/vOfa8SIEZowYYJcLpfP/Li4OGVnZ9vef35%2Bvtxut8%2BYw9FQsbGxVd42PDzM5zsqR5%2BCm8MReP9uobSmarK/odSnmkSf7AnlPgVcwGrUqJFyc3N11113%2BYyfOXNGkZGRRo7h8XgUGRmp559/XkOGDNGXX36p8ePHa%2BnSpSouLpbT6fSZHxkZqZKSEtv7z8zMVEZGhs9YWlqaJk6caHsf0dHOqieBPgWpmJgof5dwXaGwpmqjv6HQp9pAn%2BwJxT4FXMDq27ev5s6dq3nz5unee%2B9VvXr19Nlnn%2BnFF19UcnKykWPs2rVLO3bs0Pbt2yVJ8fHxSktLU3p6uu677z6VlZX5zC8rK1NUlP0nrNTUVCUlJfmMORwNVVhYXOVtw8PDFB3t1MWLpSov99g%2BZl1Dn4KbncdCbQulNVWT/Q2lPtUk%2BmRPbfTJX7/QBVzAmjJliv7v//5Po0aNUr169bzjycnJmjZtmpFjnD592vuJwW85HA5FRETI5XLp6NGjPttycnLUpk0b2/uPjY2tcDrQ7S7StWv2F095uada8%2Bsq%2BhScAvnfLBTWVG3UHwp9qg30yZ5Q7FPABSyn06mVK1fqiy%2B%2B0LFjxxQREaGWLVuqefPmxo7RvXt3/frXv9Ybb7yhMWPGKC8vT7/5zW%2BUkpKigQMH6s0339S2bdvUp08f7dy5UwcOHNDs2bONHR8AAIS2gAtY32rRooVatGhRI/uOi4vTypUrtWTJEq1evVqNGzfWwIEDlZaWpvr162v58uVatGiRZs%2BerTvvvFPLli2rsVoAAEDoCbiA9cUXX%2BjFF1/UwYMHdfXq1QrbP//8cyPH6dq1q7p27Vrpth49eqhHjx5GjgMAAOqegAtYc%2BfOVV5enqZOnarGjRv7uxwAAIBqC7iA9emnn%2Bq//uu/1L59e3%2BXAgAA8IME3JW9YmJiqnVJBAAAgEATcAFr%2BPDheu2111RUVOTvUgAAAH6QgDtFuHfvXv31r39V586ddeutt/r8yRxJ%2BuCDD/xUGQAAgD0BF7A6d%2B6szp07%2B7sMAACAHyzgAtb48eP9XQIAAMBNCbj3YElSdna2Zs6cqV/84hc6e/asNmzYoP379/u7LAAAAFsCLmAdOXJEQ4cO1VdffaUjR47oypUr%2BvzzzzVq1Cjt2bPH3%2BUBAABUKeAC1qJFizRq1CitW7dOERERkqSXX35Zv/zlL5WRkeHn6gAAAKoWcAHryJEjevDBByuMP/roozp58qQfKgIAAKiegAtYERERunTpUoXxvLw8OZ1OP1QEAABQPQEXsHr37q1f//rXKiws9I6dOHFC6enpuv/%2B%2B/1XGAAAgE0BF7CmT5%2BusrIyde3aVaWlpRo8eLAGDBggh8OhadOm%2Bbs8AACAKgXcdbAaNWqkjRs36qOPPtLf/vY3eTweuVwu9ejRQ2FhAZcHAQAAKgi4gPWtxMREJSYm%2BrsMAACAagu4gJWUlKR69epddzt/ixAAAAS6gAtYDz30kE/Aunr1qr788kv96U9/0qRJk/xYGQAAgD0BF7AmTJhQ6fj69et18OBB/fKXv6zligAAAKonaN413qtXL%2B3du9ffZQAAAFQpaALWgQMH1KBBA3%2BXAQAAUKWAO0X4/VOAlmXp0qVLOnbsGKcHAQBAUAi4gHXHHXdU%2BBRhRESEnnjiCaWkpPipKgAAAPsCLmAtWLDA3yUAAADclIALWFlZWbbndurUqQYrAVBT%2Bi3Z5%2B8SAKBGBVzAGjFihCzL8n5969vTht%2BO1atXT59//rlfagQAALiRgAtYy5Yt0/z58zV9%2BnR16dJFEREROnTokObOnavHHntMvXr18neJAAAANxRwl2l45ZVXNGfOHPXu3VuNGjVSgwYNlJCQoBdffFFr1qzRnXfe6f0CAAAIRAEXsPLz8/XjH/%2B4wnijRo1UWFjoh4oAAACqJ%2BACVrt27fTaa6/p0qVL3rHz589r4cKFSkxM9GNlAAAA9gTce7Cee%2B45PfHEE%2BrZs6eaN28uSfriiy/UrFkzvfXWW/4tDgAAwIaAC1gtW7bUtm3b9P777%2BvEiROSpMcee0wPPPCAnE6nn6sDAACoWsAFLEmKjo7W0KFD9dVXX%2Bmuu%2B6S9I%2BruQMAAASDgHsPlmVZWrRokTp16qQBAwbozJkzmj59umbOnKmrV6/6uzwAAIAqBVzAWrdund577z3NmTNH9evXlyT17t1b//u//6vXX3/dz9UBAABULeACVmZmpl544QUNHjzYe/X2/v37Kz09XVu3bjVyjPPnz2vatGnq3LmzOnXqpKeeekr5%2BfmSpEOHDmno0KFq3769kpKStGnTJiPHBAAAdUfABayvvvpKP/3pTyuMt2rVSt98842RY0yYMEElJSXatWuX9uzZo/DwcD3//PO6cOGCxo4dqwcffFBZWVlKT0/X/PnzdfjwYSPHBQAAdUPAvcn9zjvv1OHDh/Uv//IvPuN79%2B71vuH9Zhw5ckSHDh3Shx9%2BqEaNGkmSXnrpJbndbu3cuVNNmjTRsGHDJEmJiYlKSUnRhg0bdO%2B99970sQEAQN0QcAFr9OjRmjdvns6ePSvLsvTRRx9p48aNWrdunWbOnHnT%2Bz98%2BLDi4uL029/%2BVm%2B//bZKS0vVo0cPTZ8%2BXcePH5fL5fKZHxcXp3feeeemjwsAAOqOgAtYDz/8sK5du6bf/OY3Kisr0wsvvKBbb71VkydP1qOPPnrT%2B79w4YKOHTumNm3aaMuWLSorK9O0adM0ffp03XbbbRWutRUZGamSkpJqHSM/P19ut9tnzOFoqNjY2CpvGx4e5vMdlaNPwPU5HDX3uOCxZw99sieU%2BxRwAev3v/%2B9/u3f/k2pqakqKCiQZVm69dZbje3/208mzp49Ww0aNFCjRo00adIkPfLIIxo8eLDKysp85peVlSkqKqpax8jMzFRGRobPWFpamiZOnGh7H9HRXFTVDvoEVBQTU73nrB%2BCx5499MmeUOxTwAWsl19%2BWa1bt9Ytt9yipk2bGt9/XFycPB6Prl69qgYNGkiSPB6PJOmnP/2p/vu//9tnfk5OjuLj46t1jNTUVCUlJfmMORwNVVhYXOVtw8PDFB3t1MWLpSov91TruHUJfQKuz85zzQ/FY88e%2BmRPbfSpNn7hqEzABazmzZvr2LFjatmyZY3sv2vXrrrrrrs0a9YszZ8/X5cvX9bixYvVu3dvDRgwQEuXLtXatWs1bNgwHTx4UO%2B//75WrFhRrWPExsZWOB3odhfp2jX7i6e83FOt%2BXUVfQIqqo3HBI89e%2BiTPaHYp4ALWPHx8Zo6dapWr16t5s2be19l%2Btb8%2BfNvav8RERFat26dFixYoL59%2B%2Bry5ctKSkrS7NmzFR0drTVr1ig9PV1Lly5V06ZN9dxzz6lLly43dUwAAFC3BFzAys3NVYcOHSSpwhvFTbn99tu1ePHiSre1bdtWGzdurJHjAgCAuiEgAtb8%2BfP19NNPq2HDhlq3bp2/ywEAALgpAfG5yLfeekulpaU%2BY6NHj/b%2B%2BRoAAIBgEhABy7KsCmOffPKJLl%2B%2B7IdqAAAAbk5ABCwAAIBQQsACAAAwLGACVr169fxdAgAAgBEB8SlC6R9XcP/na15dvXpVCxcurPBnam72OlgAAAA1LSACVqdOnSpc86p9%2B/YqLCxUYWGhn6oCAAD4YQIiYHHtKwAAEEoC5j1YAAAAoYKABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwzOHvAlB39Fuyz98lAABQK3gFCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMCwOh2wysvLNXz4cM2YMcM7tnfvXqWkpKhdu3bq16%2Bf9uzZ48cKAQBAMKrTASsjI0Mff/yx9%2BdTp05pwoQJevrpp/Xxxx9rwoQJmjRpks6ePevHKgEAQLCpswHro48%2B0s6dO9WnTx/v2JYtW9SxY0f17t1bDodD/fv3V6dOnZSZmenHSgEAQLCpk3/s%2Bdy5c5o9e7ZWrFihtWvXesdzcnLkcrl85sbFxSk7O7ta%2B8/Pz5fb7fYZczgaKjY2tsrbhoeH%2BXwHgOpyOGru%2BYPnKHvokz2h3Kc6F7A8Ho%2BeffZZjRw5UnfffbfPtuLiYjmdTp%2BxyMhIlZSUVOsYmZmZysjI8BlLS0vTxIkTbe8jOtpZ9SQAqERMTFSNH4PnKHvokz2h2Kc6F7BWrlyp%2BvXra/jw4RW2OZ1OlZWV%2BYyVlZUpKqp6T1apqalKSkryGXM4GqqwsLjK24aHhyk62qmLF0tVXu6p1nEBQJKt55ofiucoe%2BiTPbXRp9r4haMydS5gvffee8rPz1fHjh0lyRuodu/erWHDhuno0aM%2B83NyctSmTZtqHSM2NrbC6UC3u0jXrtlfPOXlnmrNB4Bv1cZzB89R9tAne0KxT3UuYG3fvt3n528v0bBgwQKdOHFCb775prZt26Y%2Bffpo586dOnDggGbPnu2PUgEAQJAKvXeV3YSWLVtq%2BfLlWrlypTp16qQVK1Zo2bJlatGihb9LAwAAQaTOvYL1fQsWLPD5uUePHurRo4efqgEAAKGAV7AAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhtX5C40CQKjpt2Sfv0uw7Q%2BTuvm7BKBG8AoWAACAYQQsAAAAwwhYAAAAhhGwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAw%2BpkwMrOztbIkSOVkJCgbt26adq0aSooKJAkHTp0SEOHDlX79u2VlJSkTZs2%2BblaAAAQbOpcwCorK9OvfvUrtW/fXn/%2B85/1P//zPzp//rxmzZqlCxcuaOzYsXrwwQeVlZWl9PR0zZ8/X4cPH/Z32QAAIIjUuYCVl5enu%2B%2B%2BW2lpaapfv75iYmKUmpqqrKws7dy5U02aNNGwYcPkcDiUmJiolJQUbdiwwd9lAwCAIFLnAtZPfvITrV69WuHh4d6xHTt2qHXr1jp%2B/LhcLpfP/Li4OGVnZ9d2mQAAIIg5/F2AP1mWpSVLlmjPnj1av3693nrrLTmdTp85kZGRKikpqdZ%2B8/Pz5Xa7fcYcjoaKjY2t8rbh4WE%2B3wEglDkcoflcx3O5PaHcpzobsC5duqSZM2fq6NGjWr9%2BvVq1aiWn06mioiKfeWVlZYqKiqrWvjMzM5WRkeEzlpaWpokTJ9reR3S0s%2BpJABDkYmKq9/wabHgutycU%2B1QnA1Zubq7GjBmjO%2B64Q%2B%2B8846aNm0qSXK5XNq3b5/P3JycHMXHx1dr/6mpqUpKSvIZczgaqrCwuMrbhoeHKTraqYsXS1Ve7qnWcQEg2Nh5XgxGPJfbUxt98leIr3MB68KFC3riiSfUpUsXpaenKyzsu5clk5OTtXDhQq1du1bDhg3TwYMH9f7772vFihXVOkZsbGyF04Fud5GuXbO/eMrLPdWaDwDBKNSf5/z9XN5vyb6qJwWIP0zq5u8SjKpzAWvz5s3Ky8vTH/7wB23fvt1n26effqo1a9YoPT1dS5cuVdOmTfXcc8%2BpS5cufqoWAAAEozoXsEaOHKmRI0ded3vbtm21cePGWqwIAACEmtB72z4AAICfEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMAIWAACAYQQsAAAAwwhYAAAAhhFkfj8OAAAKDUlEQVSwAAAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwh78LwM3pt2Sfv0sAAADfwytYAAAAhvEKFgAANnHWAHbxChYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGAELAADAMC40CgDwGy7ciVDFK1gAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABgGJ8irAH5%2Bflyu90%2BYw5HQ8XGxlZ52/DwMJ/vAADUBQ5HaP1/r55lWZa/iwg1y5YtU0ZGhs/Y%2BPHjNWHChCpvm5%2Bfr8zMTKWmptoKZHUVfbKHPtlHr%2ByhT/bQJ3tCuU%2BhFRcDRGpqqjZv3uzzlZqaauu2brdbGRkZFV4Bgy/6ZA99so9e2UOf7KFP9oRynzhFWANiY2NDLokDAAD7eAULAADAMAIWAACAYeFz586d6%2B8i4CsqKkoJCQmKiorydykBjT7ZQ5/so1f20Cd76JM9odonPkUIAABgGKcIAQAADCNgAQAAGEbAAgAAMIyABQAAYBgBCwAAwDACFgAAgGEELAAAAMMIWAAAAIYRsGpAdna2Ro4cqYSEBHXr1k3Tpk1TQUGBz5z8/Hx17dpVmzdvvu5%2BioqK9NxzzykxMVGdO3fWzJkzdfHiRe/2c%2BfO6amnnlLHjh3VuXNnpaen69q1azV2v0yrrT5t27ZN99xzj9q3b%2B/9evbZZ2vsfpl2oz7NmTNHbdq08blvmZmZle6nvLxcr7zyirp27ar27dtr3Lhxys/P924P9vUk1V6vWFO%2BysvLNX78eC1btsxnPBTW1I1Ut1fX6xPr6R8KCws1Y8YMdevWTZ06ddITTzyhzz//3Ls96NaTBaNKS0utbt26Wa%2B//rp1%2BfJlq6CgwBozZoz15JNPeueUl5dbw4cPt%2B6%2B%2B27r3Xffve6%2B0tLSrCFDhlh5eXnWpUuXrGeeecZ6/PHHvdsff/xxa8qUKVZJSYmVm5trPfDAA9aqVatq9P6ZUpt9WrBggTVjxowavT81pao%2BPfTQQ9bmzZtt7WvZsmVWSkqKlZeXZxUVFVmTJk2yxowZ490ezOvJsmq3V6yp73z99dfWqFGjLJfLZS1dutRnW7CvqapUp1c36hPr6R/GjRtnjR071iooKLAuX75sLVmyxOratatVXFxsWVbwrScClmEnTpywRo8ebV27ds07tnv3buu%2B%2B%2B7z/rx06VLr2WeftXr16nXd4FBSUmLdfffd1oEDB7xjbrfbcrlcVk5OjnXq1CnL5XJZZ86c8W7funWrdf/999fAvTKvtvpkWZY1bNgwa/369TV0T2rWjfp0%2BfJlq3Xr1tbf//53W/vq2bOn9fvf/977s9vttlq1amXl5uYG/XqyrNrrlWWxpr518uRJKyEhwXr99det1NRUn%2BAQCmvqRqrTqxv1ybJYT5ZlWR6Px3rqqaeso0ePeseKioosl8tlHT16NCjXk8Pfr6CFmp/85CdavXq1z9iOHTvUunVrSdJf/vIXbd26Ve%2B%2B%2B65SUlKuux%2BPxyPLsuR0Or1jYWH/OKN78uRJ1atXT02aNNHtt9/u3d6yZUvl5eXp4sWLio6ONnm3jKutPrVo0UJHjx6V0%2BnU6tWrVV5ern/913/V1KlTdcstt9TAPTPrRn3Kzs7WtWvXtHTpUh08eFCNGzfWww8/rF/96lfeHnyrqKhIZ86ckcvl8o7ddtttuuWWW3Ts2DFJCur1JNVer%2B68807W1P/XrFkz7d69W40bN1ZWVpbPtuPHjwf9mrqR6vTqRn3yeDysJ0n16tXT8uXLfca2b9%2Buhg0bqkWLFtq3b1/QrSfeg1WDLMvS4sWLtWfPHs2ePVvnzp3TrFmztGjRoir/anhUVJS6deumxYsXy%2B1269KlS3r11VcVHh6usrIyFRcX%2B4QKSd6fS0pKauw%2B1YSa7FNBQYHuuece9e3bV9u2bdPGjRt16tSpoHp/w7e%2B36eioiIlJCRo%2BPDh2rt3rxYuXKh169ZpzZo1FW5bXFwsSWrYsKHPeGRkpIqLi0NqPUk12yvW1HcaNWqkxo0bV7ot1NbU91WnVzfqE%2Bupch988IFefvllzZkzR06nMzjXk/9ePAttRUVF1vjx461evXpZ2dnZlsfjsUaNGmWtWbPGO%2BdGp74sy7LOnTtnTZkyxUpMTLT69Oljvf3221ZCQoL1xz/%2B0dq5c6eVkJDgMz87O9tyuVzWxYsXa%2Bx%2BmVbTfarMoUOHrFatWllFRUXG709N%2BX6frmfVqlXWQw89VGH8/Pnzlsvlso4dO%2BYznpCQYO3atStk1pNl1XyvKlMX19T3Pf744z6nvkJpTdllp1ff71Nl6vJ68ng81vLly6127dpZW7du9Y4H43riFawakJubq4cffliXLl3SO%2B%2B8o1atWun06dM6cOCAli9fro4dO6pjx47Ky8vTvHnz9OSTT1a6H7fbreeff14ffvihduzYoU6dOunChQtq06aN4uPjdf78eX3zzTfe%2BSdOnNCPfvSj6/6mFGhqo0/Z2dlatGiRLMvyzr9y5YrCwsJUv3792rqrN6WyPknS7t27tXHjRp%2B5V65cUWRkZIV93HLLLbr99tuVk5PjHXO73Tp//rxcLldIrCepdnrFmrInVNbU9ZjqFevpO6WlpRo3bpzeffddbdiwQf379/duC8r15OeAF3LOnz9v3X///daMGTOs8vLyG86t6pWZ0aNHWzNmzLAuX75snTlzxho%2BfLj1zDPPeLc/%2Buij1uTJk62ioiLvJyqq%2Bs0oUNRWn06fPm21a9fO%2Bo//%2BA/r6tWr1tdff2098sgj1qxZs4zen5pyoz7t3LnTuvfee60PP/zQ8ng81ieffGJ17tzZ%2Bt3vflfpvhYvXmwNGDDAys3N9X4y7p8/bRnM68myaq9XrKnKVfbKTLCvqRv5ob36fp9YT9958sknrUGDBlmFhYWVbg%2B29UTAMmzNmjWWy%2BWyfvazn1nt2rXz%2Bfq%2B7weH9957z2fe6dOnrTFjxlgdOnSwunTpYs2bN88qLS31bne73daECROshIQEq0uXLtaCBQt8PskRyGqzT/v377dSU1Ot9u3bW126dLFeeuklq6ysrGbvoCFV9entt9%2B2%2BvTpY/3sZz%2Bzfv7zn/t8Eun7fbpy5Yq1cOFCq0ePHtZ9991njRs3zvrmm2%2B824N5PVlW7faKNVVRZQEr2NdUVa7Xq%2Br2ifVkWUeOHLFcLpfVpk2bCvvJysqyLCv41lM9y/qn1yUBAABw03gPFgAAgGEELAAAAMMIWAAAAIYRsAAAAAwjYAEAABhGwAIAADCMgAUAAGAYAQsAAMAwAhYAAIBhBCwAAADDCFgAAACGEbAAAAAMI2ABAAAYRsACAAAwjIAFAABg2P8Dr%2Bq6VZXF67sAAAAASUVORK5CYII%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common-8425372844644930805\">\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\">25.027694</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">25.030261</td>\n",
       "        <td class=\"number\">1</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\">25.011498</td>\n",
       "        <td class=\"number\">1</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\">25.055865</td>\n",
       "        <td class=\"number\">1</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\">25.010284</td>\n",
       "        <td class=\"number\">1</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\">25.012614000000003</td>\n",
       "        <td class=\"number\">1</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\">25.004185999999997</td>\n",
       "        <td class=\"number\">1</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\">24.993406</td>\n",
       "        <td class=\"number\">1</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\">24.991643</td>\n",
       "        <td class=\"number\">1</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\">24.99006</td>\n",
       "        <td class=\"number\">1</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=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (537)</td>\n",
       "        <td class=\"number\">537</td>\n",
       "        <td class=\"number\">98.0%</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=\"extreme-8425372844644930805\">\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\">24.907449</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">24.92679</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">24.927551</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">24.928438</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">24.930341000000002</td>\n",
       "        <td class=\"number\">1</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",
       "            <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\">25.18995</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">25.191229</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">25.19524</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">25.19623</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">25.20125</td>\n",
       "        <td class=\"number\">1</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_lng\">lng<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>546</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>99.6%</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>121.47</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>121.33</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>121.81</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=\"minihistogram-5969151805382708493\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAAS5JREFUeJzt3cEJwjAYgFEVR3IId/LsTg7hTvHqQT60II31vXshl4%2B/JaTZjzHGDnjpsPYCYGbHtRewltPl9vEz9%2Bv5CythZiYIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUD42wNTS3x6yMoBq99ngkAQCASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQBAIhE0cmFpyWxS8wwSBMN0EMQ2YiQkCYboJsiVu0v19JggEgUDwirUB/tf1PSYIBIFAEAgEgUDYjzHG2ot4Zid9Tks%2B7LewDzRdIDATr1gQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQHrmMIWKd5BmyAAAAAElFTkSuQmCC\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives-5969151805382708493,#minihistogram-5969151805382708493\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives-5969151805382708493\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles-5969151805382708493\"\n",
       "                                                  aria-controls=\"quantiles-5969151805382708493\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram-5969151805382708493\" aria-controls=\"histogram-5969151805382708493\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common-5969151805382708493\" aria-controls=\"common-5969151805382708493\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme-5969151805382708493\" aria-controls=\"extreme-5969151805382708493\"\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=\"quantiles-5969151805382708493\">\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>121.33</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>121.37</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>121.43</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>121.46</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>121.5</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>121.63</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>121.81</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>0.48016</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>0.06388</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>0.069746</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.00057418</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>3.5423</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>121.47</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>0.048085</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>1.2698</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>66566</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>0.0048646</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>4.4 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=\"histogram-5969151805382708493\">\n",
       "            <img 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8/XsDJAADarqgC66233orPfe5z%2Bxz/3d/93di2bVsBJgIA%2BPiKKrD69esX//7v/77P8UcffTT69%2B9fgIkAAD6%2BonqT%2B/Tp02PGjBnx0ksvRUtLSyxfvjxeffXVWLVqVdx8882FHg8AoE2K6grWqaeeGrfeemts2LAhysrKYsmSJfHrX/86br755hg7dmyhxwMAaJOiuoIVEXHyySfHySefXOgxAAA%2BsaK6ggUA0BkILACAxAQWAEBiAgsAIDGBBQCQmMACAEhMYAEAJNbpA2vLli1RXV0da9asaT32i1/8Is4555wYNGhQjBkzJu6///6cr1m%2BfHlUV1fHCSecEGeffXasW7cu32MDAB1Ypw6sZ599NmpqauKNN95oPfbuu%2B/GRRddFBMmTIi1a9fG3LlzY968efHcc89FRMSaNWviuuuuixtuuCHWrl0bf/InfxIXX3xx7Nq1q1APAwDoYDptYC1fvjxmzZoVM2fOzDm%2BatWqOOSQQ%2BL888%2BPTCYTI0aMiHHjxsV9990XERH3339/nHnmmTF48OA44IAD4oILLoiKiop47LHHCvEwAIAOqOj%2BqZxURo0aFePGjYtMJpMTWS%2B//HIMGDAg59z%2B/fvHAw88EBERGzdujIkTJ%2B7z%2Bfr6%2Bjbf9%2BbNm6OhoSHnWCbTIyorKz/uw%2BADlJWV5vxMx5LJ%2BO%2B2P57X%2BWPX%2BdNVd91pA6tv3777Pd7Y2Bjl5eU5x7p37x47d%2B5s0%2BfbYtmyZbFw4cKcY7W1tVFXV9fm26Btevcu/%2BiTKDoVFT0LPUJR87zOH7vOn662604bWB%2BkvLw8tm/fnnOsqakpevbs2fr5pqamfT5fUVHR5vuoqamJMWPG5BzLZHrE1q2Nn3Bq3q%2BsrDR69y6Pbdt2RUvL3kKPw8fke2H/PK/zx67zp9C7LtQf6AoeWPX19TFgwIAoLc3PpcMBAwbE6tWrc45t3LgxqqqqIiKiqqoqXn755X0%2Bf/LJJ7f5PiorK/d5ObChYXvs2eObOLWWlr322gH5b/bhPK/zx67zp6vtuuAviJ511lmxdevWnGMPPfRQNDa2z59wq6ur4%2B2334677rordu/eHU899VQ88sgjre%2B7mjRpUjzyyCPx1FNPxe7du%2BOuu%2B6Kd955J6qrq9tlHgCg8yn4FaxsNrvPsWuvvTYGDx7c%2BrJdShUVFfG9730v5s6dGwsWLIg%2BffrE17/%2B9Rg%2BfHhERIwYMSKuuuqquPrqq%2BOtt96K/v37x5133hmHHHJI8lkAgM6p4IG1P/uLrk/jxRdfzPn4uOOOi%2B9///sfeP748eNj/PjxSWcAALqOgr9ECADQ2QgsAIDEiuIlwnXr1sXBBx/c%2BnE2m43nnnsu3nzzzZzzhg4dmu/RAAA%2BtqIIrOnTp%2B/zvqtLL7005%2BOSkpLYsGFDPscCAPhECh5YP/7xjws9AgBAUgUPrM9%2B9rOFHgEAIClvcgcASExgAQAkJrAAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYwAIASExgAQAkJrAAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYwAIASExgAQAkJrAAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYwAIASExgAQAkJrAAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYwAIASExgAQAkJrAAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYwAIASExgAQAklin0AHQdZ8xfXegRACAvXMECAEhMYAEAJCawAAASE1gAAIkJLACAxAQWAEBiAgsAIDGBBQCQmMACAEhMYAEAJCaw9uOxxx6LgQMHxqBBg1p/zJ49OyIinnzyyRg3blyccMIJccYZZ8QTTzxR4GkBgGLj3yLcj/Xr18f48eNj3rx5Ocdff/31mD59enz729%2BOP/zDP4xVq1bFjBkzYtWqVXHYYYcVaFoAoNi4grUf69evj2OPPXaf48uXL48hQ4bEaaedFplMJr70pS/F0KFDY9myZQWYEgAoVq5gvc/evXvjhRdeiPLy8li8eHG0tLTEKaecErNmzYqNGzfGgAEDcs7v379/1NfXF2haAKAYCaz32bJlSwwcODDGjh0bCxYsiK1bt8bll18es2fPjubm5igvL885v3v37rFz586cY5s3b46GhoacY5lMj6isrGz3%2BaEjyGRcPN%2BfsrLSnJ9pP3adP1111wLrfQ499NC47777Wj8uLy%2BP2bNnx7nnnhsnnnhiNDU15Zzf1NQUPXv2zDm2bNmyWLhwYc6x2traqKura7/BoQOpqOj50Sd1Yb17l3/0SSRh1/nT1XYtsN6nvr4%2BHn300bj00kujpKQkIiKam5ujtLQ0jj/%2B%2BNiwYUPO%2BRs3btzn/Vo1NTUxZsyYnGOZTI/YurUx%2BbzV3/pp8tuE9tYe3wudQVlZafTuXR7btu2Klpa9hR6nU7Pr/Cn0rgv1BzqB9T6HHHJI3HfffXHwwQfH1KlTY/PmzXHjjTfGWWedFRMmTIi77747HnvssTj99NNj1apV8fTTT8cVV1yRcxuVlZX7vBzY0LA99uzxTQwR4XvhI7S07LWjPLHr/Olqu%2B5aL4i2weGHHx633357/PjHP45hw4bFxIkT47jjjosrr7wy%2BvXrF9/5znfi9ttvj6FDh8aiRYvi1ltvjc9//vOFHhsAKCKuYO3HsGHD4vvf//5%2BPzd69OgYPXp0nicCADoSV7AAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYv6YByLsz5q8u9Agfy4oZIws9AtDBuIIFAJCYwAIASExgAQAkJrAAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYwAIASExgAQAkJrAAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYwAIASCxT6AEASOuM%2BasLPUKbrZgxstAjQLtwBQsAIDGBBQCQmMACAEhMYAEAJCawAAASE1gAAIkJLACAxAQWAEBiAgsAIDGBBQCQmMACAEhMYAEAJCawAAASE1gAAIkJLACAxAQWAEBiAgsAIDGBBQCQmMACAEhMYAEAJCawAAASE1gAAIkJLACAxAQWAEBiAgsAIDGBBQCQmMACAEhMYAEAJCawAAASE1gAAIkJLACAxAQWAEBimUIPAEDXdcb81YUe4WNZMWNkoUegg3AFaz/eeeeduOSSS2LIkCFx4oknxty5c2PPnj2FHgsA6CBcwdqPGTNmxGGHHRY//elP4%2B23346LL7447rrrrpg2bVqhRwOANutIVwg729VBgfU%2Bv/zlL%2BPpp5%2BOf/3Xf43y8vL4/d///bjkkkvixhtvFFjQRXWk36SA4uAlwvd5%2BeWX45BDDonDDjus9Vi/fv1i06ZNsW3btgJOBgB0FK5gvU9jY2OUl5fnHPufj3fu3Bm9e/f%2ByNvYvHlzNDQ05BzLZHpEZWVlukEByLtMxnWJ9tLZdiuw3qdHjx6xa9eunGP/83HPnj3bdBvLli2LhQsX5hz7q7/6q5g%2BfXqaIf%2BPZ%2Bb%2Bv%2BS32RFs3rw5li1bFjU1NcK1ndl1/th1/nSVXRfD7xFdZdfv17lyMYGqqqr47W9/G2%2B//XbrsVdeeSUOP/zw6NWrV5tuo6amJh588MGcHzU1Ne01cpfU0NAQCxcu3OdKIenZdf7Ydf7Ydf501V27gvU%2BRxxxRAwePDiuv/76uPbaa2Pr1q2xaNGimDRpUptvo7KysktVOgCQyxWs/ViwYEHs2bMn/uiP/ijOPffcGD16dFxyySWFHgsA6CBcwdqPQw89NBYsWFDoMQCADqrs6quvvrrQQ8An0bNnzxg2bFib/%2BcDPjm7zh%2B7zh%2B7zp%2BuuOuSbDabLfQQAACdifdgAQAkJrAAABITWAAAiQksAIDEBBYAQGICCwAgMYEFAJCYwAIASExgUXBbtmyJ6urqWLNmTeuxlStXxvjx4%2BOLX/xijBkzJhYuXBh79%2B7d52v//u//PiZPntzm%2B5o9e/bHOr%2Bzae9d/%2BIXv4ijjz46Bg0a1Prj/PPPT/44OoL23vV7770Xf/d3fxcjR46MwYMHx5QpU%2BKVV15J/jiK1Ysvvhh/8Rd/EcOGDYtjjz02vvCFL%2BQ87wYOHBhjx44t9JidTns/r3/1q1/FhRdeGMOGDYsRI0bEZZddFtu2bUv%2BOPIiCwX0zDPPZE877bTsgAEDsk899VQ2m81m169fnz3%2B%2BOOzjz/%2BeLalpSW7cePG7KmnnppdsmRJ69c1NjZm582blx0wYED2y1/%2Bcpvu6/77788effTRbT6/s8nHrpcuXdpl9/t/5WPXf/M3f5M977zzsm%2B99Vb2vffey15zzTXZM888s10fV7HYtWtXdtSoUdlbbrkl%2B95772W3bNmSvfDCC7Nf%2BcpXstlsNrthw4bs0KFDsz/72c8KPGnnko/n9aRJk7I33HBDtrm5Obt169bs%2Beefn50zZ067Pq724goWBbN8%2BfKYNWtWzJw5M%2Bf4b37zmzjvvPPi1FNPjdLS0ujXr19UV1fH2rVrW88ZP358NDQ0xJ/%2B6Z%2B26b42btwYixYtinPOOSfpY%2Bgo8rXr9evXx7HHHpt8/o4kH7t%2B55134uGHH4558%2BZFZWVldOvWLWbNmhXf/OY3I9sF/vWzTZs2xVFHHRW1tbXRrVu3qKioiJqamli7dm00NzfHjBkzYurUqTF8%2BPBCj9pp5OvXkFdeeSWy2Wzrj5KSkigvL0/%2BePJBYFEwo0aNih/96EfxpS99Kef42LFjY86cOa0fNzU1xU9%2B8pM45phjWo8tXbo0brrppvid3/mdj7yfpqammDlzZlx11VXRt2/fdA%2BgA8nXrtevXx8vvPBCnH766XHSSSfFjBkz4s0330z3QDqAfOz6%2Beefj169esXPf/7zOPPMM1tfSqmoqIiSkpK0D6gIHXnkkbF48eIoKytrPbZy5co45phj4s4774wDDjggLrroogJO2Pnk69eQ6dOnx7333hsnnHBCDB8%2BPJqbm2PWrFnpHkgeCSwKpm/fvpHJZD70nB07dkRtbW107949Lrjggtbjhx9%2BeJvv59prr42RI0fGKaec8klH7fDyseuWlpaorKyMUaNGxT/%2B4z/Go48%2BGiUlJXHRRRdFS0vLpxm/Q8nHrt99993Yvn17rFq1KpYuXRqrVq2K8vLy%2BOpXv9qldh0Rkc1m4%2Babb44nnngirrjiirj77rtjxowZOfHFp5evX69LSkri4osvjmeeeSYef/zxiIi48sorP9HMhSawKFqvvvpqnHfeebFnz56455574qCDDvrYt/FP//RPUV9fH3/913/dDhN2Hil2XVZWFnfddVdcdNFF0atXr%2BjTp0984xvfiBdffLFLvfn6o6TYdbdu3aKlpSUuv/zy6NOnT/Tq1SvmzJkTL774Yrz22mvtMHVx2rFjR9TV1cUjjzwS9957bzz33HPRu3fvGDNmTKFH63JSPK%2Bff/75uOWWW%2BIrX/lK9OjRIz772c/GZZddFo888kjs2LGjHaZuXwKLovTkk0/GOeecE6NHj44lS5bEwQcf/Ilu5%2BGHH47XXnstTjrppBgyZEjccccd8eyzz8aQIUNi06ZNiafumFLt%2Bj//8z9j3rx50djY2Hqsubk5IiK6d%2B%2BeZNaOLtWu%2B/fvHxH/u9%2BIaL1y1RXegxUR8cYbb8TEiRNjx44d8cADD8RRRx0Vq1atinHjxnWJl0mLScpfQ1paWnL%2BD8QDDjggSkpKOuQVyQ%2B/3gcF8POf/zxqa2vj6quvjkmTJn2q21qyZEnOx7feems8/fTTsXTp0k91u51Fyl1XVFTED3/4w2hpaYnZs2dHY2NjXHPNNTFixIj43Oc%2Bl2jijivlrvv37x9Dhw6NK6%2B8Mr7zne/EgQceGDfccEMcc8wxUVVVlWji4vXuu%2B/GlClTYvjw4TF37twoLS2NbDYb69ati6lTpxZ6vC4l5fN68ODBUV5eHtdff33MmTMnduzYETfddFNUV1d3yDe6u4JF0fnud78be/bsiblz5%2Bb8vTbTpk1r89efeeaZ7Txl55By1927d4/FixfHK6%2B8EqNGjYqxY8fGQQcdFPPnz2/Ph9BhpH5e33bbbVFVVRUTJkyI0aNHx86dO2PRokXtNX5RefDBB2PTpk3x0EMPxeDBg2PQoEHxxS9%2BMbZv3x6HHXZYocfrUlI%2Br/v06RNLliyJ119/PUaPHh0TJkyII444Iq6//vr2fAjtpiTbVa4nAwDkiStYAACJCSwAgMQEFgBAYgILACAxgQUAkJjAAgBITGABACQmsAAAEhNYAACJCSwAgMQEFgBAYgJaDgUrAAAAGUlEQVQLACAxgQUAkJjAAgBITGABACT2/wEjlfLJqq8/4QAAAABJRU5ErkJggg%3D%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common-5969151805382708493\">\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\">121.42218500000001</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.45244</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.444423</td>\n",
       "        <td class=\"number\">1</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\">121.463894</td>\n",
       "        <td class=\"number\">1</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\">121.47272199999999</td>\n",
       "        <td class=\"number\">1</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\">121.46544399999999</td>\n",
       "        <td class=\"number\">1</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\">121.5474</td>\n",
       "        <td class=\"number\">1</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\">121.37883500000001</td>\n",
       "        <td class=\"number\">1</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\">121.487799</td>\n",
       "        <td class=\"number\">1</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\">121.36915800000001</td>\n",
       "        <td class=\"number\">1</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=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (536)</td>\n",
       "        <td class=\"number\">536</td>\n",
       "        <td class=\"number\">97.8%</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=\"extreme-5969151805382708493\">\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\">121.33025400000001</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.333095</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.334639</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.334806</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.334938</td>\n",
       "        <td class=\"number\">1</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",
       "            <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\">121.66978799999998</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.674342</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.80646000000002</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.809735</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">121.81041</td>\n",
       "        <td class=\"number\">1</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_mday\">mday<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>46</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>8.4%</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>20191000000000</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>20190218151440</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>20190604111402</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=\"minihistogram-1988407417782134870\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAB5pJREFUeJzt2l1IVOsex/FfJxt6gci7rhICJzWx0Rk139PMDkaUol2kYiVlIlSaibDRqDhWWBZkmAVpiRCISGmiYAUV5ktdCJWRZcpoviQToqYzOvM/F52GPVt99uxDbjfx%2B4AXa63nWS%2BjX9ashctEREBE8/rXUp8A0T%2BZy1KfAP26DL81/uU5L//z70U4k/8f7yBECgyESIGBECkwECIFBkKkwECIFBgIkQIDIVJgIEQKDIRIgYEQKTAQIgUGQqTAQIgUGAiRAgMhUmAgRAoMhEiBgRApMBAiBQZCpMBAiBQYCJECAyFSYCBECgyESIGBECkwECIFBkKkwECIFBgIkQIDIVJgIEQKDIRIgYEQKTAQIgUGQqTAQIgUGAiRAgMhUmAgRAoMhEiBgRApMBAiBQZCpMBAiBSWiYgs9UkQ/VPxDkKkwECIFBgIkQID%2BclMJhN27NiBtrY2p8bbbDZcuXIF4eHh0Ov12LdvH9rb250%2B3tevX5GXl4eQkBD4%2B/sjNTUVXV1dC47/9OkTUlNT4evri9DQUNy4cWPecU1NTdi%2BfbvDOovFgqKiIoSHh8Pf3x%2BZmZkYHBx0%2Blx/6OvrQ2BgIPr7%2B%2B3rbDYbrl27hoiICPj6%2BmL37t1oaGj4y/v%2B6YR%2BmpcvX0p0dLRotVppbW11ak5VVZXExsbK0NCQWK1WKS8vF51OJ9PT0w7jampqJDk5ec78jIwMOXLkiJhMJjGbzXL16lUJDg6WycnJOWMtFovExMRIUVGRmM1mefPmjYSGhkpDQ4PDmJs3b4qXl5dERkY6zC8sLJTo6Gh5//69mM1muXjxouzcuVPMZrNT1yoi0tzcLEFBQaLVasVoNNrX3717V6KioqSvr09ERB4/fiweHh725aXCO8hPUltbi5ycHGRlZc3Z1tLSgoSEBBgMBuzatQsPHjywb%2Bvp6YHNZoPNZoOIYNmyZVi5cqVTx/wx/vjx43B1dYVGo0FaWhpGR0fR29s7Z3xHRwdGRkZw7NgxaDQaeHl5ISUlBVVVVfYxhw4dQltbGw4fPjxnfn19PTIzM%2BHu7g6NRoOTJ09ieHgYL168AACMjo4iJycHISEhCA0NRUFBASYmJuzzS0pKUFxcPO9nlJSUhLq6OmzYsAEWiwUmkwmrVq1y%2BrNYNEua5y9kZGREZmZmREQc7iBdXV3i4%2BMjTU1NMjs7K69evZLAwEB5%2BvSpiIh0d3fLtm3bRKvViqenp%2Bh0OmlvbxcRkYGBAdHr9aLX68XHx0c8PT3ty2VlZfOeR3V1teh0Ovn27ducbRUVFRIXF%2Bew7tGjR6LX6%2B3Lg4ODIvL9jvXHO0hgYKA0Njbal61Wq%2Bh0OikvLxer1SqJiYly6tQpGR8fF5PJJOnp6ZKVlWUfPzQ0JDabTYxG45w7yA/Pnj0TDw8P2bRpk1RUVCzwaf99GMgi%2BH0gp0%2BfdvgjERG5fPmypKeni4jI27dvJTc3Vz5%2B/ChTU1NSUlIiW7dulZGREYc5C33F%2Br3m5mbZsmWL1NbWzrv9%2BvXrsn//fod1LS0t4unpOWfsfIHk5%2BfL3r17pa%2BvT6anp6W4uFg8PT2ltLRUOjs7xcvLSyYmJuzje3p6RKvVislkctiPKhCz2SwzMzPS0tIiOp1OHj58qLzmxeaytPevX9/AwABaW1thMBjs66xWKzZs2AAAyM3NxdGjR7Fx40YAQGZmJu7fv4/GxkakpKQ4dQwRQWlpKW7duoXCwkLExsbOO2716tWYmppyWDc1NYU1a9Y4dZy8vDxcunQJSUlJcHFxQUJCArRaLdauXYv%2B/n5YrVZEREQ4zNFoNDAajXB1dXXqGBqNBgAQFBSEPXv2oK6ubsHr%2BTswkEW2fv16xMXF4ezZs/Z1IyMjkP/9A8Pnz59hsVgc5ri4uGDFihVO7X9qagpZWVno7u5GVVUVvLy8Fhzr7u6O3t5ezM7OwsXl%2B6/%2Bw4cPcHd3d%2BpYw8PDyMjIQEFBAQBgbGwMZWVl8Pb2xuzsLFauXIm2tjYsX74cwPe3XkajEW5ubn%2B67wsXLgD4HuEPFosF69atc%2BrcFgsf0hdZQkIC6uvr8fz5c9hsNvT29iI5ORm3b98GAERFRaG0tBRGoxEzMzO4c%2BcOvnz5gsjISIf9xMfHo7Kycs7%2Bs7KyMDQ0hJqaGmUcABAYGAhXV1dcvnwZZrMZ7969Q2VlJRISEpy6loqKCuTl5WFychJjY2M4c%2BYMNm/eDB8fH/j4%2BMDNzQ0XLlzA5OQkpqenUVhYiAMHDsBqtf7pvg0GA%2B7du4eOjg7YbDY8fvwYDQ0NSExMdOrcFs2SfsH7Rf3xNe%2BTJ08kLi5O/Pz8JCQkRM6fP29/NToxMSHnzp2TsLAwMRgMkpSUJJ2dnU4d5/Xr16LVasXb21t0Op3DT0dHh4iIpKWlSX5%2Bvn1Ob2%2BvHDp0SPR6vYSFhS34sD/fM8j4%2BLhkZ2dLQECABAQESHZ2tsPzxeDgoJw4cUKCg4NFr9fLwYMHpbu7e86%2BF3oGqa6ulpiYGPHz85P4%2BHj7i4ylxH9WJFLgVywiBQZCpMBAiBQYCJECAyFSYCBECgyESIGBECkwECIFBkKkwECIFBgIkcJ/Af8JzhtqmN9WAAAAAElFTkSuQmCC\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives-1988407417782134870,#minihistogram-1988407417782134870\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives-1988407417782134870\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles-1988407417782134870\"\n",
       "                                                  aria-controls=\"quantiles-1988407417782134870\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram-1988407417782134870\" aria-controls=\"histogram-1988407417782134870\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common-1988407417782134870\" aria-controls=\"common-1988407417782134870\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme-1988407417782134870\" aria-controls=\"extreme-1988407417782134870\"\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=\"quantiles-1988407417782134870\">\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>20190218151440</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>20191000000000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>20191000000000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>20191000000000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>20191000000000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>20191000000000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>20190604111402</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>385959962</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>15</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>23873000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>1.1824e-06</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>185.2</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>20191000000000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>3966900</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>-13.306</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>11064449956059919</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>569900000000000</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>4.4 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=\"histogram-1988407417782134870\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzt3X1cVHXe//E3ciMj5Dpm1NZjNy3ALkuDxLu8KUn08gYtRbnKvLxLy0jK1NR01TTLFm9KzTLNLOXxgLXNTCNza13bzBDNzFxpoSQrNlFBU%2BSe8/ujn3M5gYr1xRkOr%2BfjwR98z5kznzfM5LszZwYfy7IsAQAAwJgGnh4AAADAbihYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwP08PUF8cP35aTZsGKT%2B/UJWVlqfHqRUNGvjYOqPd80n2z2j3fJL9M9o9n0RG06666opaPf75cAbrMmnQwEc%2BPj5q0MDH06PUGrtntHs%2Byf4Z7Z5Psn9Gu%2BeTyGgXFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMMzP0wMAAIDa0fv5HZ4eocbee6yzp0cwijNYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYZtuClZaWplatWikyMtL1NXnyZEnS9u3bFRsbq4iICPXu3Vvbtm1zu%2B3KlSvVrVs3RUREaNiwYfrmm288EQEAANRRti1Y%2B/fv14ABA7R3717XV1JSknJycjR%2B/Hg9%2Buij2r17t8aPH6/HHntMR44ckSRt2LBBa9eu1auvvqr09HTdfPPNSkxMlGVZHk4EAADqClsXrFtuuaXK%2BoYNGxQVFaUePXrIz89Pffr0Ubt27ZSamipJ%2Bstf/qL77rtPYWFhatiwoSZOnKjc3Fylp6df7ggAAKCO8vP0ALWhsrJSBw4ckMPh0KpVq1RRUaE77rhDkyZNUnZ2tsLDw932Dw0NVWZmpiQpOztbY8aMcW3z9/dX8%2BbNlZmZqY4dO9bo/vPy8nT06FG3tcDAYDmdQfL1tW2ndWWza0a755Psn9Hu%2BST7Z7R7Pql%2BZKyOn5%2B98tqyYOXn56tVq1bq1auXlixZooKCAk2ZMkWTJ09WaWmpHA6H2/6BgYE6c%2BaMJKmwsPCC22siNTVVy5Ytc1tLSEhQYmKiGjd2nOdW9mH3jHbPJ9k/o93zSfbPaPd8Uv3IeC6nM8jTIxhly4LVrFkzJScnu753OByaPHmyhgwZog4dOqi4uNht/%2BLiYgUFBbn2vdD2moiPj1d0dLTbWmBgsCTpp5%2BKVFFReUl56gpf3wZq3Nhh24x2zyfZP6Pd80n2z2j3fFL9yFidgoLCWjmup4qbLQtWZmamNm/erIkTJ8rHx0eSVFpaqgYNGqhNmzY6ePCg2/7Z2dmu67XCwsKUlZWl7t27S5LKysqUk5NT5WXFCwkJCVFISIjb2tkHTkVFpcrL7f2EsXtGu%2BeT7J/R7vkk%2B2e0ez6pfmQ8l92y2usFz/%2BvSZMmSk5O1qpVq1ReXq7c3FwlJSXpnnvu0d13361du3YpLS1N5eXlSktL065duzRgwABJ0qBBg7Ru3TplZmaqpKRECxcuVLNmzRQVFeXhVAAAoK6w5Rmsa665RitWrNCiRYv00ksvqWHDhurbt68mT56shg0b6sUXX9SCBQs0ffp0XXfddVq6dKlatGghSYqLi9OpU6eUkJCg/Px8tW7dWitWrJC/v7%2BHUwEAgLrClgVLktq3b6%2BUlJRqt3Xt2lVdu3atdpuPj49GjRqlUaNG1eZ4AADAxmz5EiEAAIAnUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwWxesiooKDRs2TFOnTnWtbd%2B%2BXbGxsYqIiFDv3r21bds2t9usXLlS3bp1U0REhIYNG6Zvvvnmco8NAADqOFsXrGXLlmn37t2u73NycjR%2B/Hg9%2Buij2r17t8aPH6/HHntMR44ckSRt2LBBa9eu1auvvqr09HTdfPPNSkxMlGVZnooAAADqINsWrJ07d2rr1q3q2bOna23Dhg2KiopSjx495Ofnpz59%2Bqhdu3ZKTU2VJP3lL3/Rfffdp7CwMDVs2FATJ05Ubm6u0tPTPRUDAADUQX6eHqA2HD9%2BXNOnT9fy5cu1Zs0a13p2drbCw8Pd9g0NDVVmZqZr%2B5gxY1zb/P391bx5c2VmZqpjx441vv%2B8vDwdPXrUbS0wMFhOZ5B8fW3baV3Z7JrR7vkk%2B2e0ez7J/hntnk%2BqHxmr4%2Bdnr7y2K1iVlZWaPHmyRo4cqZtuusltW2FhoRwOh9taYGCgzpw5U6PtNZWamqply5a5rSUkJCgxMVGNGzvOcyv7sHtGu%2BeT7J/R7vkk%2B2e0ez6pfmQ8l9MZ5OkRjLJdwVqxYoUCAgI0bNiwKtscDoeKi4vd1oqLixUUFFSj7TUVHx%2Bv6Ohot7XAwGBJ0k8/FamiovKSjldX%2BPo2UOPGDttmtHs%2Byf4Z7Z5Psn9Gu%2BeT6kfG6hQUFNbKcT1V3GxXsDZu3Ki8vDxFRUVJkqswffDBBxo6dKgOHDjgtn92drZuueUWSVJYWJiysrLUvXt3SVJZWZlycnKqvKx4MSEhIQoJCXFbO/vAqaioVHm5vZ8wds9o93yS/TPaPZ9k/4x2zyfVj4znsltWe73gKWnLli367LPPtHv3bu3evVv9%2BvVTv379tHv3bvXv31%2B7du1SWlqaysvLlZaWpl27dmnAgAGSpEGDBmndunXKzMxUSUmJFi5cqGbNmrnKGgAAQE3Y7gzWhdx444168cUXtWDBAk2fPl3XXXedli5dqhYtWkiS4uLidOrUKSUkJCg/P1%2BtW7fWihUr5O/v7%2BHJAQBAXWL7gjV//ny377t27aquXbtWu6%2BPj49GjRqlUaNGXY7RAACATdnuJUIAAABPo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAM87qCVVFR4ekRAAAAfhOvK1jdunXTn//8Z2VnZ3t6FAAAgF/F6wrWI488os8%2B%2B0z9%2BvXT4MGDlZKSolOnTnl6LAAAgBrzuoJ17733KiUlRVu2bNHtt9%2BulStXqkuXLpo4caI%2B%2BeQTT48HAABwUV5XsM5q3ry5JkyYoC1btighIUEffvihRo8erejoaL322mtcqwUAALyWn6cHOJ99%2B/bp7bffVlpamkpLSxUTE6OBAwfqyJEjeuGFF7R//34tWrTI02MCAABU4XUFa/ny5dq4caO%2B/fZbtW7dWhMmTFC/fv0UHBzs2sfX11czZ8704JQAAADn53UFa926derfv7/i4uIUGhpa7T433nijJk2adJknAwAAqBmvK1gfffSRTp8%2BrRMnTrjW0tLS1KlTJzmdTklSq1at1KpVK0%2BNCAAAcEFed5H7v/71L/Xq1UupqamutaSkJMXGxurf//63BycDAACoGa8rWH/%2B85/Vs2dPTZgwwbX2wQcfqFu3bpo/f74HJwMAAKgZrytYBw4c0NixYxUQEOBa8/X11dixY/X55597cDIAAICa8bqCFRwcrMOHD1dZ//HHHxUYGOiBiQAAAC6N1xWsXr16afbs2frkk090%2BvRpFRYW6tNPP9WcOXMUExPj6fEAAAAuyuveRThx4kR99913GjVqlHx8fFzrMTExeuKJJzw4GQAAQM14XcFyOBxasWKFDh06pK%2B%2B%2Bkr%2B/v668cYb1bx5c0%2BPBgAAUCNeV7DOatGihVq0aOHpMQAAAC6Z1xWsQ4cOac6cOdqzZ4/KysqqbD948KAHpgIAAKg5rytYs2fPVm5uriZNmqQrrrjC0%2BMAAABcMq8rWHv37tXrr7%2BuyMhIT48CAADwq3jdxzQ4nU4FBQV5egwAAIBfzesK1rBhw7Ro0SKdOnXqNx1n586dGjx4sG677TZ17txZc%2BfOVXFxsSRp3759Gjx4sCIjIxUdHa3169e73XbDhg2KiYlRRESEBg4cqL179/6mWQAAQP3idS8Rbt%2B%2BXZ9//rk6dOigK6%2B80u1P5kjShx9%2BeNFj5Ofn68EHH9Ts2bN1991369ixYxo9erReeeUVDR8%2BXGPHjlViYqLi4%2BOVkZGhhIQEtWzZUm3atFF6errmzp2rlStXqk2bNkpOTta4ceO0bds2ORyO2ooNAABsxOsKVocOHdShQ4ffdIymTZvqk08%2BUXBwsCzL0okTJ1RSUqKmTZtq69atatKkiYYOHSpJ6tSpk2JjY5WcnKw2bdpo/fr16tu3r9q2bStJGjFihFJTU5WWlqZBgwb95nwAAMD%2BvK5gPfLII0aOExwcLEm64447dOTIEUVFRWngwIF6/vnnFR4e7rZvaGio3nzzTUlSdnZ2lSIVGhqqzMxMI3MBAAD787qCJUmZmZl6/fXXdejQIb3wwgv64IMPFBoa%2BqvObG3dulUnT57UpEmTlJiYqKuvvrrKS32BgYE6c%2BaMJKmwsPCC22siLy9PR48e/cUxguV0BsnX1%2BsuezPmbDa7ZrR7Psn%2BGe2eT7J/Rrvnk%2BpHxur4%2Bdkrr9cVrC%2B//FL33nuvIiIi9OWXX6q0tFQHDx7UM888o2XLlql79%2B6XdLzAwEAFBgZq8uTJGjx4sIYNG1blAvri4mLXOxcdDofrYvhztzudzhrfZ2pqqpYtW%2Ba2lpCQoMTERDVubP/ruOye0e75JPtntHs%2Byf4Z7Z5Pqh8Zz%2BV02usTBLyuYC1YsECjRo3ShAkTXJ%2BF9fTTT%2BuKK66occH67LPP9OSTT%2Bqdd95xXSRfWloqf39/hYaGaseOHW77Z2dnKywsTJIUFhamrKysKtu7detW4wzx8fGKjo52WwsM/Pkly59%2BKlJFRWWNj1WX%2BPo2UOPGDttmtHs%2Byf4Z7Z5Psn9Gu%2BeT6kfG6hQUFNbKcT1V3LyuYH355ZeaNWtWlfV7771XKSkpNTpGy5YtVVxcrIULF2rixIk6evSonnvuOcXFxalXr15auHCh1qxZo6FDh2rPnj3atGmTli9fLkmKi4tTQkKCevfurbZt2yo5OVnHjx9XTExMjTOEhIQoJCTEbe3sA6eiolLl5fZ%2Bwtg9o93zSfbPaPd8kv0z2j2fVD8ynstuWb2uYPn7%2B%2Bv06dNV1nNzc2v8MQlBQUFatWqVnnnmGXXu3FlXXHGFYmNjlZCQoICAAK1evVrz5s3TkiVL1LRpU82YMUMdO3aU9PO7CmfNmqXZs2fryJEjCg0N1cqVK9WkSROjOQEAgH15XcHq0aOHFi5cqMWLF7vWvv76a82bN0933nlnjY8TGhqq1atXV7utdevWFzwbNmDAAA0YMKDG9wUAAHAur7tkf8qUKSouLtbtt9%2BuoqIiDRw4UP369ZOfn5%2BeeOIJT48HAABwUV53Bis4OFgpKSnauXOn/vWvf6myslLh4eHq2rWrGjTwuj4IAABQhdcVrLM6deqkTp06eXoMAACAS%2BZ1BSs6Olo%2BPj7n3V6Tv0UIAADgSV5XsO655x63glVWVqZvv/1WH330kR577DEPTgYAAFAzXlewxo8fX%2B36unXrtGfPHv3v//7vZZ4IAADg0tSZq8a7d%2B%2Bu7du3e3oMAACAi6ozBWvXrl1q2LChp8cAAAC4KK97ifCXLwFalqXTp0/rq6%2B%2B4uVBAABQJ3hdwbr22murvIvQ399fw4cPV2xsrIemAgAAqDmvK1jz58/39AgAAAC/idcVrIyMjBrv265du1qcBAAA4NfxuoI1YsQIWZbl%2Bjrr7MuGZ9d8fHx08OBBj8wIAABwIV5XsJYuXapnn31WU6ZMUceOHeXv7699%2B/Zp9uzZuu%2B%2B%2B9S9e3dPjwgAAHBBXvcxDc8995xmzZqlHj16KDg4WA0bNlT79u01Z84crV69Wtddd53rCwAAwBt5XcHKy8vT73//%2ByrrwcHBKigo8MBEAAAAl8brClZERIQWLVqk06dPu9ZOnDihpKQkderUyYOTAQAA1IzXXYM1Y8YMDR8%2BXN26dVPz5s0lSYcOHdJVV12lN954w7PDAQAA1IDXFawbb7xRaWlp2rRpk77%2B%2BmtJ0n333ae%2BffvK4XB4eDoAAICL87qCJUmNGzfW4MGD9f333%2BsPf/iDpJ8/zR0AAKAu8LprsCzL0oIFC9SuXTv169dPP/74o6ZMmaJp06aprKzM0%2BMBAABclNcVrLVr12rjxo2aNWuWAgICJEk9evTQ3//%2Bd73wwgseng4AAODivK5gpaamaubMmRo4cKDr09v79OmjefPm6d133/XwdAAAABfndQXr%2B%2B%2B/13/9139VWW/ZsqWOHTvmgYkAAAAujdcVrOuuu05ffPFFlfXt27e7LngHAADwZl73LsLRo0frqaee0pEjR2RZlnbu3KmUlBStXbtW06ZN8/R4AAAAF%2BV1BWvQoEEqLy/XSy%2B9pOLiYs2cOVNXXnmlJkyYoHvvvdfT4wEAAFyU1xWsd955R//93/%2Bt%2BPh45efny7IsXXnllZ4eCwAAoMa87hqsp59%2B2nUxe9OmTSlXAACgzvG6gtW8eXN99dVXnh4DAADgV/O6lwjDwsI0adIkrVq1Ss2bN1fDhg3dtj/77LMemgwAAKBmvK5gHT58WG3btpUkHT161MPTAAAAXDqvKFjPPvusHn30UTVq1Ehr16719DgAAAC/iVdcg/XGG2%2BoqKjIbW306NHKy8vz0EQAAAC/nlcULMuyqqx99tlnKikp8cA0AAAAv41XFCwAAAA7oWABAAAY5jUFy8fHx9MjAAAAGOEV7yKUfv4E93M/86qsrExJSUkKCgpy24/PwQIAAN7OKwpWu3btqnzmVWRkpAoKClRQUOChqQAAAH4dryhYfPYVAACwE6%2B5BgsAAMAuKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwzLYFKzMzUyNHjlT79u3VuXNnPfHEE8rPz5ck7du3T4MHD1ZkZKSio6O1fv16t9tu2LBBMTExioiI0MCBA7V3715PRAAAAHWULQtWcXGxHnjgAUVGRurjjz/W5s2bdeLECT355JM6efKkxo4dq7vvvlsZGRmaN2%2Benn32WX3xxReSpPT0dM2dO1fz589XRkaG%2Bvfvr3HjxqmoqMjDqQAAQF1hy4KVm5urm266SQkJCQoICJDT6VR8fLwyMjK0detWNWnSREOHDpWfn586deqk2NhYJScnS5LWr1%2Bvvn37qm3btvL399eIESPkdDqVlpbm4VQAAKCusGXBuuGGG7Rq1Sr5%2Bvq61t5//33dfPPNysrKUnh4uNv%2BoaGhyszMlCRlZ2dfcDsAAMDFeMUnudcmy7L0/PPPa9u2bVq3bp3eeOMNORwOt30CAwN15swZSVJhYeEFt9dEXl5elT/9ExgYLKczSL6%2Btuy0kuTKZteMds8n2T%2Bj3fNJ9s9o93xS/chYHT8/e%2BW1dcE6ffq0pk2bpgMHDmjdunVq2bKlHA6HTp065bZfcXGx649KOxwOFRcXV9nudDprfL%2BpqalatmyZ21pCQoISExPVuLHjPLeyD7tntHs%2Byf4Z7Z5Psn9Gu%2BeT6kfGczmdQZ4ewSjbFqzDhw9rzJgxuvbaa/Xmm2%2BqadOmkqTw8HDt2LHDbd/s7GyFhYVJksLCwpSVlVVle7du3Wp83/Hx8YqOjnZbCwwMliT99FORKioqLzlPXeDr20CNGztsm9Hu%2BST7Z7R7Psn%2BGe2eT6ofGatTUFBYK8f1VHGzZcE6efKkhg8fro4dO2revHlq0OD/TjvGxMQoKSlJa9as0dChQ7Vnzx5t2rRJy5cvlyTFxcUpISFBvXv3Vtu2bZWcnKzjx48rJiamxvcfEhKikJAQt7WzD5yKikqVl9v7CWP3jHbPJ9k/o93zSfbPaPd8Uv3IeC67ZbVlwXrrrbeUm5ur9957T1u2bHHbtnfvXq1evVrz5s3TkiVL1LRpU82YMUMdO3aUJHXq1EmzZs3S7NmzdeTIEYWGhmrlypVq0qSJJ6IAAIA6yJYFa%2BTIkRo5cuR5t7du3VopKSnn3T5gwAANGDCgNkYDAAD1gL0u2QcAAPACFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADDM9gUrPz9fMTExSk9Pd63t27dPgwcPVmRkpKKjo7V%2B/Xq322zYsEExMTGKiIjQwIEDtXfv3ss9NgAAqMNsXbD27Nmj%2BPh4HT582LV28uRJjR07VnfffbcyMjI0b948Pfvss/riiy8kSenp6Zo7d67mz5%2BvjIwM9e/fX%2BPGjVNRUZGnYgAAgDrGtgVrw4YNmjRpkiZMmOC2vnXrVjVp0kRDhw6Vn5%2BfOnXqpNjYWCUnJ0uS1q9fr759%2B6pt27by9/fXiBEj5HQ6lZaW5okYAACgDrJtwerSpYv%2B9re/qU%2BfPm7rWVlZCg8Pd1sLDQ1VZmamJCk7O/uC2wEAAC7Gz9MD1Jarrrqq2vXCwkI5HA63tcDAQJ05c6ZG22siLy9PR48e/cUxguV0BsnX17ad1pXNrhntnk%2Byf0a755Psn9Hu%2BaT6kbE6fn72ymvbgnU%2BDodDp06dclsrLi5WUFCQa3txcXGV7U6ns8b3kZqaqmXLlrmtJSQkKDExUY0bO85zK/uwe0a755Psn9Hu%2BST7Z7R7Pql%2BZDyX0xnk6RGMqncFKzw8XDt27HBby87OVlhYmCQpLCxMWVlZVbZ369atxvcRHx%2Bv6Ohot7XAwGBJ0k8/FamiovLXjO71fH0bqHFjh20z2j2fZP%2BMds8n2T%2Bj3fNJ9SNjdQoKCmvluJ4qbvWuYMXExCgpKUlr1qzR0KFDtWfPHm3atEnLly%2BXJMXFxSkhIUG9e/dW27ZtlZycrOPHjysmJqbG9xESEqKQkBC3tbMPnIqKSpWX2/sJY/eMds8n2T%2Bj3fNJ9s9o93xS/ch4LrtlrXcFy%2Bl0avXq1Zo3b56WLFmipk2basaMGerYsaMkqVOnTpo1a5Zmz56tI0eOKDQ0VCtXrlSTJk08PDkAAKgr6kXB%2Buqrr9y%2Bb926tVJSUs67/4ABAzRgwIDaHgsAANiUvS7ZBwAA8AIULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCVY3jx4/r4YcfVlRUlDp06KB58%2BapvLzc02MBAIA6goJVjccee0yNGjXSP//5T7355pvauXOn1qxZ4%2BmxAABAHUHB%2BoVvv/1Wu3bt0uTJk%2BVwOPSHP/xBDz/8sJKTkz09GgAAqCMoWL%2BQlZWlJk2a6Oqrr3at3XjjjcrNzdVPP/3kwckAAEBd4efpAbxNYWGhHA6H29rZ78%2BcOaPGjRtf9Bh5eXk6evSo21pgYLCcziD5%2BprttDEL/mn0eLXpb5O6enqES1KXfraSmZ/v2cen6cept7B7PqnuZayPz7OLqWu/Q1P8/OyVl4L1C40aNVJRUZHb2tnvg4KCanSM1NRULVu2zG1t5MiRCgoKUnx8vEJCQswMK2n3vP82dqzfKi8vT6mpqcYzesovf7Z2y1edvLw8vf76KttmtHs%2Bqe5lvNT/hvE8vDTe9G/EuerD79FeddGAsLAwnThxQseOHXOtff3117rmmmt0xRVX1OgY8fHxeuutt9y%2BOnfurGXLllUKlXdkAAAO6klEQVQ5s2UnR48etXVGu%2BeT7J/R7vkk%2B2e0ez6JjHbBGaxfaN68udq2batnnnlGc%2BbMUUFBgZYvX664uLgaHyMkJKRKIz9w4IDpUQEAgJfiDFY1lixZovLyct11110aMmSIunbtqocfftjTYwEAgDqCM1jVaNasmZYsWeLpMQAAQB3lO3v27NmeHqK%2BCAoKUvv27Wt8sXxdZPeMds8n2T%2Bj3fNJ9s9o93wSGe3Ax7Isy9NDAAAA2AnXYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2DVgszMTI0cOVLt27dX586d9cQTTyg/P7/afbdv367Y2FhFRESod%2B/e2rZtm2vbF198oSFDhigyMlLR0dFav3795YpwXmlpaWrVqpUiIyNdX5MnT/b0WPgV6tPv8t///rduvfVWpaenn3efiooKPffcc7r99tsVGRmpcePGKS8v7zJOeekqKio0bNgwTZ069bz79O7dW7feeqvb7/nrr7%2B%2BjFNeuvr02JTqR95Dhw5p%2BPDhioyMVJcuXfTyyy97eqTaZ8GooqIiq3PnztYLL7xglZSUWPn5%2BdaYMWOsBx98sMq%2Bhw4dslq3bm397W9/s8rKyqx3333XatOmjfXjjz9aJ06csNq3b2%2BtW7fOKisrsz755BMrMjLS2rdvnwdS/Z/58%2BdbU6dO9egMMKO%2B/C7PnDlj9evXzwoPD7c%2B/fTT8%2B63dOlSKzY21srNzbVOnTplPfbYY9aYMWMu46SX7vnnn7duuukma8qUKdVuP3XqlNWyZUvr%2B%2B%2B/v8yT/Tb15bF5lt3zlpaWWj179rSSkpKskpIS68CBA1aXLl2stLQ0T49WqziDZVhubq5uuukmJSQkKCAgQE6nU/Hx8crIyKiy74YNGxQVFaUePXrIz89Pffr0Ubt27ZSamqqtW7eqSZMmGjp0qPz8/NSpUyfFxsYqOTnZA6n%2Bz/79%2B3XLLbd4dAaYUV9%2Bl0899ZR69Ohx0f3Wr1%2BvMWPG6Pe//72Cg4M1ffp0ffTRR/ruu%2B8uw5SXbufOndq6dat69ux53n2%2B/PJLNWnSRNddd91lnOy3qy%2BPzbPsnjcjI0N5eXlKTExUQECAWrVqpWHDhnn837PaRsEy7IYbbtCqVavk6%2BvrWnv//fd18803V9k3Oztb4eHhbmuhoaHKzMxUVlbWebd5SmVlpQ4cOKB//OMf6t69u7p166Y//elPOnnypMdmwq9TX36Xb7/9tr799ls98sgjF9zv1KlT%2BvHHH92ec82aNdPvfvc7ffXVV7U95iU7fvy4pk%2BfroULF8rhcJx3v/3798vhcOj%2B%2B%2B9Xhw4dNHDgQLfLELxRfXlsnlUf8mZlZalFixYKCAhwrXn637PLgYJViyzL0uLFi7Vt2zZNnz69yvbCwsIq/3EMDAzUmTNnLrjNU/Lz89WqVSv16tVLaWlpSklJUU5Oju2uFagP6sPv8uuvv9bixYu1cOFCt//hqU5hYaEkqVGjRm7rgYGBrm3eorKyUpMnT9bIkSN10003XXBfHx8ftW7dWk8//bT%2B%2Bc9/asSIERo/frw%2B//zzyzTtpasPj81z1Ye81f175nA4PPrv2eXg5%2BkB7Or06dOaNm2aDhw4oHXr1qlly5ZV9nE4HCouLnZbKy4uVlBQkBwOh06dOlXtNk9p1qyZ2yldh8OhyZMna8iQITp9%2BrSCg4M9Nhsujd1/lyUlJZowYYKefPJJXXvttRfd/%2Bx//IuKitzWPf2cq86KFSsUEBCgYcOGXXTfBx54wO37/v37a/PmzXr//fcVERFRWyP%2BJnZ/bP5SfcjbqFGjKs%2BtoqIir3tumcYZrFpw%2BPBhDRo0SKdPn9abb75ZbbmSpPDwcGVlZbmtZWdnKyws7ILbPCUzM1MLFiyQZVmutdLSUjVo0MDt1C%2B8n91/l/v371dOTo6mT5%2BuqKgoRUVFSZIeeughzZ49u8r%2Bv/vd73T11VcrOzvbtXb06FGdOHGiykv1nrZx40bt2rXLlWvz5s3avHmzK%2BO5Xn31Ve3cudNtrbS0VA0bNrxc414yuz82f6k%2B5A0LC1NOTo7Ky8tda57%2B9%2Byy8Ogl9jZ04sQJ684777SmTp1qVVRUXHDf7Oxsq3Xr1ta7777rehdh69atrW%2B%2B%2BcbKz8%2B3oqKirNdee80qLS21du7caUVGRlo7d%2B68TEmq%2Bs9//mNFRERYr7zyilVWVmb98MMP1pAhQ6wnn3zSYzPh16mPv8uLvYtw8eLFVr9%2B/azDhw%2B73kV4//33X8YJf50pU6ac912Ec%2BfOtXr16mUdPnzYKisrs9avX2%2B1adPGysnJucxT1lx9e2zWh7xlZWVWdHS0NX/%2BfKu4uNg6ePCg1aVLF%2Buvf/2rp0erVRQsw1avXm2Fh4dbt956qxUREeH2ZVmWFRERYW3cuNG1/0cffWT179/fioiIsPr27Wv94x//cG374osvrPj4eCsyMtK66667vOLBmJ6e7pqpY8eO1ty5c63i4mJPj4Vfob79Ln9ZsDZu3Oh6XlrWz28lT0pKsrp27Wrddttt1rhx46xjx455YtRLcm7B%2BuGHH6yIiAgrIyPDsizLKikpsebNm2d16dLFuvXWW61BgwZdsGR6iws9Nn%2BZ0Q7s%2BFwcPXq09ac//cn1fU5OjjVq1Cirbdu2VteuXa0VK1Z4cLrLw8eyzjkvCQAAgN%2BMa7AAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAC8QH5%2BvmJiYpSenl6j/SsrK7V48WJ169ZNbdu21ZAhQ7Rr164a319BQYGmTp2qzp07q127dho%2BfLgOHjx43v0PHTqk4cOHKzIyUl26dNHLL79c7X7vv/%2B%2B7rrrLre10tJSJSUlqVu3bmrXrp0SEhL0n//8p8aznvXtt9%2BqQ4cO%2Bv77711rlZWVWrp0qe644w5FRkYqNjZWaWlpl3xs0yhYAAB42J49exQfH6/Dhw/X%2BDYpKSn64IMPtH79emVkZKhPnz568MEHVVJS4rbfW2%2B9Ve3frpw%2BfboKCgq0efNm7dixQ7fddpseeOCBav8Ic1lZmR566CG1bt1a6enpeuWVV5ScnKz33nvPbZ%2BVK1fq8ccf1y8/YnPhwoXaunWrXn31Ve3YsUPXX3%2B9Ro4cqdLS0hrn/fDDD3XvvffqxIkTbuvJycl6%2B%2B23tXbtWu3du1ePP/64Jk6ceEk/y9pAwQIAwIM2bNigSZMmacKECVW2ffLJJ4qLi1NUVJT69u2rd955x7Xtm2%2B%2BUWVlpSorK2VZlnx8fBQYGFij%2Bzy7/6OPPiqn06mAgACNHj1ax44dU05OTpX9MzIylJeXp8TERAUEBKhVq1YaNmyY2x%2BqHjVqlNLT0zVmzJgqt9%2B8ebMSEhIUFhamgIAATZw4UUeOHHH9rcxjx45p0qRJ6ty5s7p06aKZM2fq9OnTrtsvW7ZMixYtqvZnNHToUG3atEl//OMfVVpaqvz8fDkcjhr/LGqLn0fvHQCAeq5Lly6KjY2Vn5%2BfW4HIzMzUuHHjlJSUpLvuukv79u3Tww8/LKfTqa5du%2Bp//ud/9OGHH%2BrOO%2B%2BUr6%2BvGjZsqFdeeUUNGzZUbm6u%2BvfvL%2BnnM0tlZWWuPwg%2BduxYjR07Vi%2B%2B%2BKLbHFu2bFGjRo3UokWLKjNmZWWpRYsWbn%2BAOjQ0VK%2B88orr%2B6SkJF1zzTV66623qty%2BoqJCDofD9b2Pj4%2Bkn1927Nq1qx5%2B%2BGE1b95c77//vsrKyjRt2jTNnDlTixYtkiQNHjxYCQkJ%2BuGHH6ocu0GDBmrUqJE%2B/vhjjRkzRpZladq0aQoJCbn4D78WcQYLAAAPuuqqq%2BTnV/V8R0pKiu666y717NlTvr6%2Buu222zRkyBDXWaOysjK1b99e7733nj777DM98MADSkxM1NGjR3Xttddq9%2B7d2r17t2bNmqW2bdu6vh87dmyV%2B/rwww/19NNPa9asWW5F6KzCwsIq6w6Hw%2B3lxGuuuea8GXv27KmXX35Zhw8fVklJiV544QWVlJSouLhYX375pQ4cOKBZs2YpODhYTqdTU6ZM0bvvvquCggJJ0tVXX%2B0qZefTvn177d%2B/X6%2B99pqef/55j1%2BHxRksAAC80A8//KBPP/3UdeZJ%2BvlM0B//%2BEdJ0hNPPKGHHnpIN9xwgyQpISFBGzdu1JYtW6q95qo6lmXppZde0sqVK/XMM8%2BoT58%2B1e7XqFEjFRUVua0VFRUpKCioRvczdepULViwQEOHDpWfn5/i4uIUHh6uxo0b6/vvv1dFRYXuuOMOt9sEBATou%2B%2B%2Bk9PprNF9nD271qlTJw0YMECbNm06b57LgYIFAIAXuuaaa3TPPfdozpw5rrW8vDzXBeS5ublVLhL38/OTv79/jY5fVFSkCRMmKCsrS8nJyWrVqtV59w0LC1NOTo7Ky8tdZ9uys7MVFhZWo/s6cuSIxo0bp5kzZ0qSTp48qRUrVuiWW25ReXm5AgMDlZ6eLl9fX0k/v%2Bvwu%2B%2B%2B0/XXX3/RY8%2BfP1/SzyXurNLSUjVp0qRGs9UWXiIEAMALxcXFafPmzfr4449VWVmpnJwc3X///Vq9erUkKTo6Wi%2B99JK%2B%2B%2B47lZWV6fXXX9fRo0fVvXt3t%2BMMHDhQa9eurXL8CRMm6Mcff9Rf//rXC5YrSerQoYOcTqcWLlyokpISZWZmau3atYqLi6tRljVr1mjq1KkqLCzUyZMn9dRTT%2Bnmm29WmzZt1KZNG11//fWaP3%2B%2BCgsLVVxcrGeeeUYjRoxQRUXFRY8dFRWllJQUZWRkqLKyUn//%2B9%2BVlpamwYMH12i22sIZLAAAvNCtt96qRYsWadGiRXr00UflcDjUr18/Pf7445Kk2bNna/HixRo6dKiKiorUsmVLvfrqq7r66qsveuwDBw5o27ZtCggIqFLIVq5cqaioKD3wwAO69tprNWfOHPn5%2BWn16tWaM2eOOnfurEaNGmnYsGEaOHBgjbJMnjxZs2bNUnR0tKSfL%2Bxfvny5pJ/Puq1YsULPPfecevbsqZKSErVp00avvfaaGjZseNFj9%2BjRQzNmzNCMGTN07NgxNW/eXEuXLtVtt91Wo9lqy/8Dn5B9NpaxpxQAAAAASUVORK5CYII%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common-1988407417782134870\">\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\">20190604111336</td>\n",
       "        <td class=\"number\">25</td>\n",
       "        <td class=\"number\">4.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111322</td>\n",
       "        <td class=\"number\">25</td>\n",
       "        <td class=\"number\">4.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111341</td>\n",
       "        <td class=\"number\">24</td>\n",
       "        <td class=\"number\">4.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111321</td>\n",
       "        <td class=\"number\">24</td>\n",
       "        <td class=\"number\">4.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111318</td>\n",
       "        <td class=\"number\">23</td>\n",
       "        <td class=\"number\">4.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111335</td>\n",
       "        <td class=\"number\">22</td>\n",
       "        <td class=\"number\">4.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111325</td>\n",
       "        <td class=\"number\">22</td>\n",
       "        <td class=\"number\">4.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111344</td>\n",
       "        <td class=\"number\">21</td>\n",
       "        <td class=\"number\">3.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111329</td>\n",
       "        <td class=\"number\">20</td>\n",
       "        <td class=\"number\">3.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111328</td>\n",
       "        <td class=\"number\">19</td>\n",
       "        <td class=\"number\">3.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:6%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (36)</td>\n",
       "        <td class=\"number\">323</td>\n",
       "        <td class=\"number\">58.9%</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=\"extreme-1988407417782134870\">\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\">20190218151440</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190328143658</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190328144404</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190523094234</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190526084339</td>\n",
       "        <td class=\"number\">1</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",
       "            <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\">20190604111357</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:67%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111359</td>\n",
       "        <td class=\"number\">3</td>\n",
       "        <td class=\"number\">0.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111400</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:67%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111401</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:34%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">20190604111402</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:34%\">&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_sarea\">sarea<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>19</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <th>Unique (%)</th>\n",
       "            <td>3.5%</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-1705281289276378605\">\n",
       "    <table class=\"mini freq\">\n",
       "        <tr class=\"\">\n",
       "    <th>板橋區</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:25%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 15.5%\">\n",
       "            85\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>三重區</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:17%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 10.8%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        59\n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>新莊區</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:16%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 10.0%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        55\n",
       "    </td>\n",
       "</tr><tr class=\"other\">\n",
       "    <th>Other values (16)</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: 63.7%\">\n",
       "            349\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=\"#freqtable-1705281289276378605, #minifreqtable-1705281289276378605\"\n",
       "       aria-expanded=\"true\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 extrapadding collapse\" id=\"freqtable-1705281289276378605\">\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\">板橋區</td>\n",
       "        <td class=\"number\">85</td>\n",
       "        <td class=\"number\">15.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:71%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">三重區</td>\n",
       "        <td class=\"number\">59</td>\n",
       "        <td class=\"number\">10.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">新莊區</td>\n",
       "        <td class=\"number\">55</td>\n",
       "        <td class=\"number\">10.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:46%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">中和區</td>\n",
       "        <td class=\"number\">43</td>\n",
       "        <td class=\"number\">7.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:36%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">新店區</td>\n",
       "        <td class=\"number\">43</td>\n",
       "        <td class=\"number\">7.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:36%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">汐止區</td>\n",
       "        <td class=\"number\">32</td>\n",
       "        <td class=\"number\">5.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:27%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">樹林區</td>\n",
       "        <td class=\"number\">31</td>\n",
       "        <td class=\"number\">5.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:26%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">土城區</td>\n",
       "        <td class=\"number\">31</td>\n",
       "        <td class=\"number\">5.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:26%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">林口區</td>\n",
       "        <td class=\"number\">25</td>\n",
       "        <td class=\"number\">4.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:21%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">永和區</td>\n",
       "        <td class=\"number\">25</td>\n",
       "        <td class=\"number\">4.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:21%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (9)</td>\n",
       "        <td class=\"number\">119</td>\n",
       "        <td class=\"number\">21.7%</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_sareaen\">sareaen<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>20</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <th>Unique (%)</th>\n",
       "            <td>3.6%</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-6900608121988095585\">\n",
       "    <table class=\"mini freq\">\n",
       "        <tr class=\"\">\n",
       "    <th>Banqiao Dist.</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:25%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 15.5%\">\n",
       "            85\n",
       "        </div>\n",
       "        \n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>Sanchong Dist.</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:17%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 10.8%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        59\n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>Xinzhuang Dist.</th>\n",
       "    <td>\n",
       "        <div class=\"bar\" style=\"width:16%\" data-toggle=\"tooltip\" data-placement=\"right\" data-html=\"true\"\n",
       "             data-delay=500 title=\"Percentage: 9.9%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        54\n",
       "    </td>\n",
       "</tr><tr class=\"other\">\n",
       "    <th>Other values (17)</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: 63.9%\">\n",
       "            350\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=\"#freqtable-6900608121988095585, #minifreqtable-6900608121988095585\"\n",
       "       aria-expanded=\"true\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 extrapadding collapse\" id=\"freqtable-6900608121988095585\">\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\">Banqiao Dist.</td>\n",
       "        <td class=\"number\">85</td>\n",
       "        <td class=\"number\">15.5%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:71%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Sanchong Dist.</td>\n",
       "        <td class=\"number\">59</td>\n",
       "        <td class=\"number\">10.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:49%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Xinzhuang Dist.</td>\n",
       "        <td class=\"number\">54</td>\n",
       "        <td class=\"number\">9.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:45%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Xindian Dist.</td>\n",
       "        <td class=\"number\">43</td>\n",
       "        <td class=\"number\">7.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:36%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Zhonghe Dist.</td>\n",
       "        <td class=\"number\">43</td>\n",
       "        <td class=\"number\">7.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:36%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Xizhi Dist.</td>\n",
       "        <td class=\"number\">32</td>\n",
       "        <td class=\"number\">5.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:27%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Tucheng Dist.</td>\n",
       "        <td class=\"number\">31</td>\n",
       "        <td class=\"number\">5.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:26%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Shulin Dist.</td>\n",
       "        <td class=\"number\">31</td>\n",
       "        <td class=\"number\">5.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:26%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Yonghe Dist.</td>\n",
       "        <td class=\"number\">25</td>\n",
       "        <td class=\"number\">4.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:21%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Linkou Dist.</td>\n",
       "        <td class=\"number\">25</td>\n",
       "        <td class=\"number\">4.6%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:21%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (10)</td>\n",
       "        <td class=\"number\">120</td>\n",
       "        <td class=\"number\">21.9%</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_sbi\">sbi<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>51</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>9.3%</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>16.786</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>64</td>\n",
       "                </tr>\n",
       "                <tr class=\"alert\">\n",
       "                    <th>Zeros (%)</th>\n",
       "                    <td>1.1%</td>\n",
       "                </tr>\n",
       "            </table>\n",
       "        </div>\n",
       "    </div>\n",
       "</div>\n",
       "<div class=\"col-md-3 collapse in\" id=\"minihistogram3367052894274302102\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAATFJREFUeJzt3cFtwkAQQNEQURJF0BPn9EQR9LRpIPoCJOLBvHdH2svX2N7FPqy11hfwp%2B%2BtFwCTHbdewFZOl%2BvDv7n9nF%2BwEiYzQSAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCATCLg4rPnPwEO5hgkAQCASBQBAIBIFAEAgEgUAQCIRdbBT%2Bl0c3JL0F5f2ZIBAEAkEgEAQCQSAQxj3FcnSdSUwQCAKBIBAIAoEw7iZ9T3yk5/2ZIBAEAkEgEAQCQSAQBAJBIBAEAkEgEOykD2P3fRaB7IC3rbyOSywIJsgHmvyvzWnT7bDWWlsvAqZyiQVBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQBAJBIBAEAkEgEAQCQSAQBALhF4LVHWtYEMTCAAAAAElFTkSuQmCC\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives3367052894274302102,#minihistogram3367052894274302102\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives3367052894274302102\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles3367052894274302102\"\n",
       "                                                  aria-controls=\"quantiles3367052894274302102\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram3367052894274302102\" aria-controls=\"histogram3367052894274302102\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common3367052894274302102\" aria-controls=\"common3367052894274302102\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme3367052894274302102\" aria-controls=\"extreme3367052894274302102\"\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=\"quantiles3367052894274302102\">\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>3.35</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>10</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>16</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>22</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>33</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>64</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>64</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>12</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>9.8346</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.58587</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>3.1745</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>16.786</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>7.3098</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>1.2697</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>9199</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>96.72</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>4.4 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=\"histogram3367052894274302102\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzt3XtUlXW%2Bx/EPsEU3IAOm2MnliQbJNPWEFxgv2ZFkzBLNW1ij46TWmQVJOoKXPGMOZdpoZsZqJtOpk7KWzDg5lUN2m8asHPGWYZPXTCpOAgIqKnLb54857pnHrYnyg2dv9vu11l7Gb2%2Bf57s/69n24Xk2mwCXy%2BUSAAAAjAm0ewAAAICWhoIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAxz2D2AvygpOW18m4GBAWrXLlRlZWdUX%2B8yvn1fQx5W5GFFHp7IxIo8rFpKHh06tLVlv5zB8mGBgQEKCAhQYGCA3aN4BfKwIg8r8vBEJlbkYUUejUPBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCsxf%2BqnLKyMqWkpOjJJ59UQkKCFixYoDfffNPymKqqKg0YMEBr1qxRfX29%2BvTpI5fLpYCAf3567ccff6yQkJDmHh8AAPigFl2wdu3apblz56qwsNC9lpWVpaysLPfXH330kWbNmqW5c%2BdKkg4fPqyamhrt3r1bwcHBzT4zAADwfS32EuHGjRuVkZGhmTNnXvYxZWVlysjI0Pz58xUbGytJKigoUNeuXSlXAADgmrXYM1iDBg1ScnKyHA7HZUvWsmXL1KNHD40cOdK9VlBQoPPnz2vs2LH69ttvFRMTo1mzZql3794N3ndxcbFKSkosaw5HiKKioq7tyVxGUFCg5U9/Rx5W5GFFHp7IxIo8rMijcVpswerQocP33v/111/rjTfe0B/%2B8AfLeps2bdSrVy89%2Buij%2BsEPfqCcnBxNnTpVb7zxhjp37tygfefm5io7O9uylpaWpvT09Kt7Eg0UHu5sku36KlN59J2/2ch2msvORXddcp3jw4o8PJGJFXlYkce1abEF60r%2B%2BMc/Ki4uTt26dbOsX3gv1gVTp07Va6%2B9pi1btmjixIkN2nZKSooSExMtaw5HiMrLzzRu6IsEBQUqPNypU6fOqa6u3ui2fZG/53Hx8eXveVyMPDyRiRV5WLWUPCIjQ23Zr98WrHfeeUdTpkzxWH/22Wc1bNgwde/e3b1WXV2t1q1bN3jbUVFRHpcDS0pOq7a2aQ7Qurr6Jtu2L/LXPC73nP01j8shD09kYkUeVuRxbfzywmp5ebmOHDmifv36edx38OBBLVq0SCUlJaqurlZ2drYqKyuVlJRkw6QAAMAX%2BWXB%2BuabbyRJHTt29Lhv8eLF%2Bvd//3eNGjVKCQkJys/P18svv6yIiIjmHhMAAPgov7hEeODAAcvXPXv29Fi7ICIiQosXL26OsQAAQAvll2ewAAAAmhIFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGBYiy9YZWVlSkpK0vbt291rjz/%2BuHr06KG4uDj3LTc3133/Sy%2B9pMGDB%2Bu2227TpEmT9OWXX9oxOgAA8FEtumDt2rVLKSkpKiwstKwXFBToiSee0J49e9y3lJQUSdLGjRu1du1arVmzRtu3b9ett96q9PR0uVwuO54CAADwQS22YG3cuFEZGRmaOXOmZb26uloHDx5Ujx49Lvn3fv/73%2BuBBx5QbGysWrdurVmzZqmoqMhyBgwAAOD7tNiCNWjQIL377ru6%2B%2B67Lev79%2B9XbW2tVq5cqQEDBmjYsGFatWqV6uvrJUmHDx/WzTff7H58q1atFB0drf379zfr/AAAwHc57B6gqXTo0OGS66dPn1Z8fLwmTZqk5cuX64svvlBaWpoCAwM1bdo0nTlzRk6n0/J32rRpo7NnzzZ438XFxSopKbGsORwhioqKuvon8j2CggItf/o7f8/D4bA%2Bb3/P42Lk4YlMrMjDijwap8UWrMsZOHCgBg4c6P66V69emjx5svLy8jRt2jQ5nU5VVVVZ/k5VVZVCQ0MbvI/c3FxlZ2db1tLS0pSent644S8jPNx55Qf5EX/NIzLy0seov%2BZxOeThiUysyMOKPK6N3xWs9957T6WlpZowYYJ7rbq6Wm3atJEkxcbG6tChQxoyZIgkqaamRl999ZXlsuGVpKSkKDEx0bLmcISovPyMgWfwT0FBgQoPd%2BrUqXOqq6s3um1f5O95XHx8%2BXseFyMPT2RiRR5WLSWPy33z2dT8rmC5XC4tXrxYN954o370ox/p008/1auvvqp58%2BZJksaOHavnn39egwcP1k033aRnn31W7du3V9%2B%2BfRu8j6ioKI/LgSUlp1Vb2zQHaF1dfZNt2xf5ax6Xe87%2BmsflkIcnMrEiDyvyuDZ%2BV7CSkpI0b948LVy4UMePH1f79u01ffp0jRo1SpI0btw4nT59WmlpaSorK1PPnj314osvqlWrVjZPDgAAfIVfFKwDBw5Yvp4wYYLlEuG/CggI0JQpUzRlypTmGA0AALRA/GgAAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMNafMEqKytTUlKStm/f7l57%2B%2B23NWrUKPXu3VuJiYnKzs5WfX29%2B/7hw4frP/7jPxQXF%2Be%2BHTlyxI7xAQCAD3LYPUBT2rVrl%2BbOnavCwkL32r59%2BzR79mytWLFCd9xxh44ePaqHHnpIISEhmjJliiorK3X06FG9//776tSpk43TtzzDV3xs9wgAADSLFnsGa%2BPGjcrIyNDMmTMt699%2B%2B60mTJigIUOGKDAwUDExMUpKStKOHTsk/aOARUREUK4AAMA1a7FnsAYNGqTk5GQ5HA5LyRo2bJiGDRvm/rqqqkp//etflZycLEkqKCiQ0%2BnUxIkTdejQIXXq1EnTp0/XkCFDGrzv4uJilZSUWNYcjhBFRUU18llZBQUFWv6Ef3M4rMcBx4cVeXgiEyvysCKPxmmxBatDhw5XfExlZaUeffRRtWnTRj/72c8kSQEBAerZs6d%2B8Ytf6IYbbtDmzZs1ffp0rVu3TrfddluD9p2bm6vs7GzLWlpamtLT06/6eTREeLizSbYL3xIZGXrJdY4PK/LwRCZW5GFFHtemxRasK/nyyy%2BVnp6u6667Tq%2B%2B%2BqrCwsIkSdOmTbM8buTIkdq0aZPefvvtBheslJQUJSYmWtYcjhCVl58xM/z/CwoKVHi4U6dOnVNdXf2V/wJatIuPL44PK/LwRCZW5GHVUvK43DefTc0vC9aWLVv0i1/8Qvfdd59mzZolh%2BOfMaxZs0bdu3dX//793WvV1dVq3bp1g7cfFRXlcTmwpOS0amub5gCtq6tvsm3Dd1zuGOD4sCIPT2RiRR5W5HFt/O7C6qeffqq0tDTNmzdPc%2BbMsZQrSfrf//1f/epXv9LXX3%2Bt2tpabdiwQXv27NHo0aNtmhgAAPgavzuD9dvf/la1tbVatGiRFi1a5F7v06ePVq9erdmzZyswMFAPPPCATp8%2BrS5dumjVqlW68cYbbZwaAAD4Er8oWAcOHHD/929/%2B9vvfWxwcLAee%2BwxPfbYY009FgAAaKH87hIhAABAU6NgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAY5nUFq66uzu4RAAAAGsXrCtbgwYP161//WocPH7Z7FAAAgGvidQXrkUce0e7duzVixAiNHz9e69ev1%2BnTp%2B0eCwAAoMG8rmDdf//9Wr9%2BvTZv3qwBAwbopZde0qBBgzRr1ix98skndo8HAABwRV5XsC6Ijo7WzJkztXnzZqWlpen999/X1KlTlZiYqJdffpn3agEAAK/lsHuAy9m7d6/%2B9Kc/KS8vT9XV1UpKStKYMWN0/PhxPffccyooKNDy5cvtHhMAAMCD1xWsF154Qa%2B//rqOHTumnj17aubMmRoxYoTCwsLcjwkKCtKCBQtsnBIAAODyvK5grVu3TiNHjtS4cePUpUuXSz4mJiZGGRkZzTwZAABAw3hdwfrwww9VWVmpiooK91peXp769%2B%2BvyMhISVL37t3VvXt3u0YEAAD4Xl73Jve///3vGjZsmHJzc91rS5cuVXJysg4ePGjjZAAAAA3jdQXr17/%2BtX784x9r5syZ7rX33ntPgwcP1pIlS2ycDAAAoGG8rmB9/vnnevjhhxUcHOxeCwoK0sMPP6xPP/3UxskAAAAaxusKVlhYmAoLCz3Wv/vuO7Vp08aGiQAAAK6O1xWsYcOGaeHChfrkk09UWVmpM2fO6G9/%2B5uysrKUlJRk93gAAABX5HU/RThr1ix9/fXXmjJligICAtzrSUlJmj17to2TAQAANIzXFSyn06kXX3xRR48e1YEDB9SqVSvFxMQoOjq6Uds9ceKEfvnLXyo/P19BQUEaOXKk5syZI4fjnxEcPXpUCxcu1GeffabQ0FBNnDhRP//5zxv5jAAAgL/xukuEF9x000266667dOeddza6XEnSjBkzFBISoq1bt2rDhg3atm2bXnnlFff9NTU1%2BvnPf66ePXtq%2B/btWrVqlXJycvTWW281et8AAMC/eF3BOnr0qB588EH16tVL3bp187hdi2PHjik/P1%2BZmZlyOp3q3LmzUlNTlZOT437Mjh07VFxcrPT0dAUHB6t79%2B6aNGmS5TEAAAAN4XWXCBcuXKiioiJlZGSobdu2RrZ56NAhRUREqGPHju61mJgYFRUV6dSpUwoPD9ehQ4d00003WT4eokuXLlq1apWRGQAAgP/wuoK1Z88e/c///I/i4uKMbfPMmTNyOp2WtQtfnz17VuHh4Zd9zNmzZ696f8XFxSopKbGsORwhioqKuuptfZ%2BgoEDLn/BvDof1OOD4sCIPT2RiRR5W5NE4XlewIiMjFRoaanSbISEhOnfunGXtwtcX9nW5x1zLLLm5ucrOzraspaWlKT09/aq31RDh4c4rPwgtXmTkpY9Vjg8r8vBEJlbkYUUe18brCtakSZO0fPlyLV261NglwtjYWFVUVKi0tFTt27eXJB05ckTXX3%2B9ex%2BxsbH66quvVFtb6/7JwsOHDys2Nvaq95eSkqLExETLmsMRovLyM418JlZBQYEKD3fq1KlzqqurN7pt%2BJ6Ljy%2BODyvy8EQmVuRh1VLyuNw3n03N6wrWli1b9OmnnyohIUHXXXed5T1RkvT%2B%2B%2B9f9Tajo6PVp08fPfXUU8rKylJ5ebleeOEFjRs3zv2YhIQERUZG6plnntGMGTN09OhRrV271vI7ERsqKirK43JgSclp1dY2zQFaV1ffZNuG77jcMcDxYUUensjEijysyOPaeF3BSkhIUEJCgvHtrly5UllZWbrzzjsVGBioe%2B%2B9V6mpqe77HQ6Hfve73ykrK0sDBw5USEiIJk2apDFjxhifBQAAtGxeV7AeeeSRJtlu%2B/bttXLlyu99zI033qg1a9Y0yf4BAID/8MofDdi/f7/mzZunCRMm6Pjx48rJydH27dvtHgsAAKBBvK5g7du3T%2BPHj9c333yjffv2qbq6Wl988YWmTJmiDz74wO7xAAAArsjrCtayZcs0ZcoUrV27Vq1atZIkPfnkk/rpT3/q8dEHAAAA3sjrCta%2Bfft07733eqzff//9%2BvLLL22YCAAA4Op4XcFq1aqVKisrPdaLioo8PmkdAADAG3ldwRo6dKieeeYZlZeXu9eOHDmiRYsW6T//8z/tGwwAAKCBvK5gzZkzR1VVVRowYIDOnTunMWPGaMSIEXI4HJo9e7bd4wEAAFyR130OVlhYmNavX69t27bp73//u%2Brr63XzzTfr9ttvV2Cg1/VBAAAAD15XsC7o37%2B/%2Bvfvb/cYAAAAV83rClZiYqICAgIue/%2B1/C5CwB8MX/Gx3SM02FszBto9AgA0Ka8rWKNHj7YUrJqaGh07dkwffvihZsyYYeNkAAAADeN1BWv69OmXXF%2B3bp127dqln/70p808EQAAwNXxmXeNDxkyRFu2bLF7DAAAgCvymYKVn5%2Bv1q1b2z0GAADAFXndJcKLLwG6XC5VVlbqwIEDXB4EAAA%2BwesK1g033ODxU4StWrXS5MmTlZycbNNUAAAADed1BWvJkiV2jwAAANAoXlewduzY0eDH9uvXrwknAQAAuDZeV7B%2B9rOfyeVyuW8XXLhseGEtICBAX3zxhS0zAgAAfB%2BvK1jPP/%2B8Fi9erDlz5uhHP/qRWrVqpb1792rhwoV64IEHNGTIELtHBAAA%2BF5e9zENTz/9tB5//HENHTpUYWFhat26teLj45WVlaXf/e536tSpk/sGAADgjbyuYBUXF%2Bvf/u3fPNbDwsJUXl5uw0QAAABXx%2BsK1m233ably5ersrLSvVZRUaGlS5eqf//%2BNk4GAADQMF73Hqz//u//1uTJkzV48GBFR0dLko4ePaoOHTro1VdftXc4AACABvC6ghUTE6O8vDy9%2BeabOnLkiCTpgQce0D333COn02nzdAAAAFfmdQVLksLDwzV%2B/Hh988036ty5s6R/fJo7AACAL/C692C5XC4tW7ZM/fr104gRI/Tdd99pzpw5mjdvnmpqauweDwAA4Iq8rmCtXbtWr7/%2Buh5//HEFBwdLkoYOHaq//OUveu6552yeDgAA4Mq8rmDl5uZqwYIFGjNmjPvT2%2B%2B%2B%2B24tWrRIf/7zn22eDgAA4Mq8rmB988036tatm8d6165dVVpaasNEAAAAV8frClanTp302Wefeaxv2bLF/YZ3AAAAb%2BZ1P0U4depU/epXv9Lx48flcrm0bds2rV%2B/XmvXrtW8efPsHg8AAOCKvK5gjR07VrW1tfrNb36jqqoqLViwQNddd51mzpyp%2B%2B%2B/3%2B7xAAAArsjrCtYbb7yhu%2B66SykpKSorK5PL5dJ1111n91gAAAAN5nXvwXryySfdb2Zv165dk5SrvLw8de/eXXFxce5bZmam8f0AAAD/5HVnsKKjo3XgwAHFxMQ02T4KCgo0atQoLV68uMn2AQAA/JfXFazY2FhlZGRo9erVio6OVuvWrS33myhFBQUFGj58eKO3AwAAcCleV7AKCwvVp08fSVJJSYnx7dfX1%2Bvzzz%2BX0%2BnU6tWrVVdXpzvuuEMZGRn6wQ9%2BYGQfxcXFHrM7HCGKiooysv0LgoICLX8CvsLhaP5jlteLJzKxIg8r8micAJfL5bJ7iMWLF%2BvRRx9VSEhIk%2B%2BrtLRUjz76qEaPHq177rlH5eXlmjNnjpxOp1atWmVkH88//7yys7Mta2lpaUpPTzeyfV/Vd/5mu0eAl9i56C67RwCAJuUVBatbt2766KOPLG9onzp1qhYvXmz8rM%2BlfPbZZ7rvvvu0c%2BdOhYWFNXp7zXkGKzzcqVOnzqmurt7otptC0rKtdo8AL/Fuxu3Nvk9fe700BzKxIg%2BrlpJHZGSoLfv1ikuEl%2Bp4u3fv1vnz543va//%2B/dq0aZNmzZrl/l2H1dXVCgwMdP9y6caKioryKFMlJadVW9s0B2hdXX2TbRtoCnYer7xePJGJFXlYkce18bsLqxEREcrJydHq1atVW1uroqIiLV26VKNHjzZWsAAAgH/zu4J1/fXX68UXX9T777%2Bv%2BPh4jR07Vj179tSCBQvsHg0AALQQXnGJUJL7cl1ziI%2BP1/r165ttfwAAwL94TcF68sknLZ95VVNTo6VLlyo01PrmND4cFAAAeDuvKFj9%2BvXz%2BKm7uLg4lZeXq7y83KapAAAAro1XFKy1a9faPQIAAIAxfvcmdwAAgKZGwQIAADDMKy4R4trx62cAAPA%2BnMECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhjnsHgCA/xm%2B4mO7R7gqb80YaPcIAHwMBasJFBcXq6SkxLLmcIQoKirK6H6CgjgBCTQHh6NlvtYu/BvCvyX/QB5W5NE4FKwmkJubq%2BzsbMtaWlqa0tPTbZoIQGNERobaPUKTCg932j2CVyEPK/K4NhSsJpCSkqLExETLmsMRovLyM0b3w3cVQPMw/dr1FkFBgQoPd%2BrUqXOqq6u3exzbkYdVS8nDrm%2BQKFhNICoqyuNyYEnJadXW%2Bu4BCvizlv7araurb/HP8WqQhxV5XBtOgQAAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAML8sWPv379eDDz6o%2BPh4DRw4ULNnz1ZZWZkk6fHHH1ePHj0UFxfnvuXm5to8MQAA8CV%2BV7Cqqqo0bdo0xcXF6aOPPtKmTZtUUVGhxx57TJJUUFCgJ554Qnv27HHfUlJSbJ4aAAD4Er8rWEVFRbrllluUlpam4OBgRUZGKiUlRTt27FB1dbUOHjyoHj162D0mAADwYQ67B2huP/zhD7V69WrL2ttvv61bb71V%2B/fvV21trVauXKldu3apbdu2Gjt2rKZNm6bAwIZ30eLiYpWUlFjWHI4QRUVFGXkOFwQF%2BV0/BmzhcLTM19qFf0P4t%2BQfyMOKPBrH7wrWv3K5XFqxYoU%2B%2BOADrVu3TqWlpYqPj9ekSZO0fPlyffHFF0pLS1NgYKCmTZvW4O3m5uYqOzvbspaWlqb09HTTTwFAM4iMDLV7hCYVHu60ewSvQh5W5HFtAlwul8vuIexQWVmpefPm6fPPP9dvfvMbde3a9ZKPW716tfLy8vTaa681eNvNeQYr8ektRrcJwNO7GbfbPUKTCAoKVHi4U6dOnVNdXb3d49iOPKxaSh52fYPkl2ewCgsL9dBDD%2BmGG27Qhg0b1K5dO0nSe%2B%2B9p9LSUk2YMMH92OrqarVp0%2Baqth8VFeVRpkpKTqu21ncPUMCftfTXbl1dfYt/jleDPKzI49r43YXVkydPavLkyerdu7fWrFnjLlfSPy4ZLl68WNu2bZPL5dKePXv06quv8lOEAADgqvjdGazXXntNRUVFeuutt7R582bLfXv27NG8efO0cOFCHT9%2BXO3bt9f06dM1atQom6YFAAC%2ByG/fg9XcSkpOG9%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%2BaMnE6nZe3C12fPnm1QwSouLlZJSYllzeEIUVRUlLlBJQUFcQISANAyOBwt6/9pFKyLhISE6Ny5c5a1C1%2BHhoY2aBu5ubnKzs62rD3yyCOaPn26mSH/X3FxsSZff0gpKSnGy5svKi4uVm5uLnn8P/KwIg9PZGJFHlbk0Tgtqy4aEBsbq4qKCpWWlrrXjhw5ouuvv15t27Zt0DZSUlL02muvWW4pKSnGZy0pKVF2drbH2TJ/RR5W5GFFHp7IxIo8rMijcTiDdZHo6Gj16dNHTz31lLKyslReXq4XXnhB48Yz%2BRL6AAAHm0lEQVSNa/A2oqKiaPsAAPgxzmBdwsqVK1VbW6s777xT9913n26//XalpqbaPRYAAPARnMG6hPbt22vlypV2jwEAAHxU0MKFCxfaPQSuXWhoqOLj4xv8BvyWjjysyMOKPDyRiRV5WJHHtQtwuVwuu4cAAABoSXgPFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwCpaPOnHihFJTU9W3b18lJCRo0aJFqq2ttXss2GT//v168MEHFR8fr4EDB2r27NkqKyuTJO3du1fjx49XXFycEhMT9Yc//MHmaZvetm3bNH78ePXu3VsDBw7UE088oaqqKkn%2BmccFdXV1mjRpkubOnete27Jli5KTk3Xbbbdp%2BPDh%2BuCDD2ycsPnk5eWpe/fuiouLc98yMzMl%2BWcmFRUVmj17thISEtSvXz%2BlpqaquLhYkn%2B/ZhrFBZ80ceJE16xZs1xnz551FRYWuu655x7XSy%2B9ZPdYsMG5c%2BdcAwcOdD333HOu8%2BfPu8rKylwPPfSQ67/%2B679cFRUVrvj4eNe6detcNTU1rk8%2B%2BcQVFxfn2rt3r91jN5kTJ064evbs6frjH//oqqurcx0/ftw1YsQI13PPPeeXefyrFStWuG655RbXnDlzXC6Xy3X06FFXz549Xe%2B%2B%2B66rpqbG9ec//9nVq1cv13fffWfzpE1vyZIlrrlz53qs%2B2smEydOdKWlpblOnjzpOn36tOuRRx5xPfzww37/mmkMzmD5oGPHjik/P1%2BZmZlyOp3q3LmzUlNTlZOTY/dosEFRUZFuueUWpaWlKTg4WJGRkUpJSdGOHTv0zjvvKCIiQj/5yU/kcDjUv39/JScnt%2BhjpV27dvrkk080ZswYBQQEqKKiQufPn1e7du38Mo8Ltm3bpnfeeUc//vGP3WsbN25U3759NXToUDkcDt19993q16%2BfcnNzbZy0eRQUFKhHjx4e6/6Yyb59%2B7R3714tWbJE4eHhCgsL0xNPPKGMjAy/fs00FgXLBx06dEgRERHq2LGjey0mJkZFRUU6deqUjZPBDj/84Q%2B1evVqBQUFudfefvtt3XrrrTp06JBuvvlmy%2BO7dOmi/fv3N/eYzSosLEySdMcddyg5OVkdOnTQmDFj/DaPEydOaP78%2BXrmmWfkdDrd64cPH/bLPOrr6/X555/rr3/9q4YMGaLBgwfrl7/8pU6ePOmXmXz22Wfq0qWLfv/73yspKUmDBg3S008/rQ4dOvjta8YECpYPOnPmjOUfSUnur8%2BePWvHSPASLpdLzz77rD744APNnz//ksdKmzZt/OY4eeedd/Thhx8qMDBQ6enpfplHfX29MjMz9eCDD%2BqWW26x3OePeUhSWVmZunfvrmHDhikvL0/r16/XV199pczMTL/M5OTJkzpw4IC%2B%2Buorbdy4UX/60590/PhxzZkzxy/zMIWC5YNCQkJ07tw5y9qFr0NDQ%2B0YCV6gsrJS6enpevPNN7Vu3Tp17dpVTqfT/ebuC6qqqvzmOGnTpo06duyozMxMbd261S/zePHFFxUcHKxJkyZ53OePeUhS%2B/btlZOTo3HjxsnpdOqGG25QZmamPvzwQ7lcLr/LJDg4WJI0f/58hYWFqX379poxY4a2bNnil3mYQsHyQbGxsaqoqFBpaal77ciRI7r%2B%2BuvVtm1bGyeDXQoLCzV27FhVVlZqw4YN6tq1qyTp5ptv1qFDhyyPPXz4sGJjY%2B0Ys1ns3r1bd911l6qrq91r1dXVatWqlbp06eJ3ebz%2B%2BuvKz89X37591bdvX23atEmbNm1S3759/fL4kP7xU7fLli2Ty%2BVyr1VXVyswMFC9evXyu0y6dOmi%2Bvp61dTUuNfq6%2BslSd26dfO7PEyhYPmg6Oho9enTR0899ZQqKyv19ddf64UXXtC4cePsHg02OHnypCZPnqzevXtrzZo1ateunfu%2BpKQklZaW6pVXXlFNTY3%2B9re/6c0339TYsWNtnLhpde3aVVVVVXrmmWdUXV2tb7/9Vk8//bTGjRunYcOG%2BV0emzdv1u7du7Vz507t3LlTI0aM0IgRI7Rz506NHDlS%2Bfn5ysvLU21trfLy8pSfn69Ro0bZPXaTioiIUE5OjlavXq3a2loVFRVp6dKlGj16tO69916/y2TAgAHq3LmzHnvsMZ05c0ZlZWV69tlnNXToUI0YMcLvXjOmBLj%2BtcLDZ5SWliorK0vbt29XYGCg7r33XmVkZFje6Az/8PLLL2vJkiVyOp0KCAiw3Ldnzx4VFBRo0aJFOnjwoNq1a6fU1FSNGTPGpmmbx%2BHDh/XUU0%2BpoKBAbdu2VXJysvunLP0xj3914TOwlixZIknaunWrli1bpsLCQnXq1EmZmZm644477ByxWeTn52v58uU6ePCgWrdurXvuuUeZmZlq3bq1X2Zy/PhxLVmyRDt27ND58%2BeVmJio%2BfPnKzw83O9fM9eKggUAAGAYlwgBAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMP%2BD%2BDaRnzj60tHAAAAAElFTkSuQmCC\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common3367052894274302102\">\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\">12</td>\n",
       "        <td class=\"number\">35</td>\n",
       "        <td class=\"number\">6.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:12%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">16</td>\n",
       "        <td class=\"number\">33</td>\n",
       "        <td class=\"number\">6.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:12%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">15</td>\n",
       "        <td class=\"number\">31</td>\n",
       "        <td class=\"number\">5.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:11%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">17</td>\n",
       "        <td class=\"number\">24</td>\n",
       "        <td class=\"number\">4.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:9%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">11</td>\n",
       "        <td class=\"number\">23</td>\n",
       "        <td class=\"number\">4.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">13</td>\n",
       "        <td class=\"number\">23</td>\n",
       "        <td class=\"number\">4.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">14</td>\n",
       "        <td class=\"number\">22</td>\n",
       "        <td class=\"number\">4.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">19</td>\n",
       "        <td class=\"number\">21</td>\n",
       "        <td class=\"number\">3.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">18</td>\n",
       "        <td class=\"number\">21</td>\n",
       "        <td class=\"number\">3.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">8</td>\n",
       "        <td class=\"number\">21</td>\n",
       "        <td class=\"number\">3.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:8%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (41)</td>\n",
       "        <td class=\"number\">294</td>\n",
       "        <td class=\"number\">53.6%</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=\"extreme3367052894274302102\">\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\">6</td>\n",
       "        <td class=\"number\">1.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:50%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1</td>\n",
       "        <td class=\"number\">5</td>\n",
       "        <td class=\"number\">0.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:42%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">2</td>\n",
       "        <td class=\"number\">7</td>\n",
       "        <td class=\"number\">1.3%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:58%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">3</td>\n",
       "        <td class=\"number\">10</td>\n",
       "        <td class=\"number\">1.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:83%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">4</td>\n",
       "        <td class=\"number\">12</td>\n",
       "        <td class=\"number\">2.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&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\">57</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">58</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">59</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">61</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">64</td>\n",
       "        <td class=\"number\">1</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_sna\">sna<br/>\n",
       "            <small>Categorical, Unique</small>\n",
       "        </p>\n",
       "    </div><div class=\"col-md-3 collapse in\" id=\"minivalues-4754258761886224693\"><table border=\"1\" class=\"dataframe example_values\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>First 3 values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table></div>\n",
       "<div class=\"col-md-6 collapse in\" id=\"minivalues-4754258761886224693\"><table border=\"1\" class=\"dataframe example_values\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Last 3 values</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table></div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#values-4754258761886224693,#minivalues-4754258761886224693\" aria-expanded=\"false\"\n",
       "       aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 collapse\" id=\"values-4754258761886224693\">\n",
       "    <p class=\"h4\">First 10 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\">三井Outlet</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">三光國小(金滿意)</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">三多國小</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">三多第1市民活動中心</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">三峽區公所(三峽老街)</td>\n",
       "        <td class=\"number\">1</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",
       "    <p class=\"h4\">Last 10 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\">龍形停車場</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">龍恩公園</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">龍門公園</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">龍門龍濱路口</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">龍鳳公園</td>\n",
       "        <td class=\"number\">1</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><div class=\"row variablerow\">\n",
       "    <div class=\"col-md-3 namecol\">\n",
       "        <p class=\"h4 pp-anchor\" id=\"pp_var_snaen\">snaen<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>547</td>\n",
       "        </tr>\n",
       "        <tr>\n",
       "            <th>Unique (%)</th>\n",
       "            <td>99.8%</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",
       "    </table>\n",
       "</div>\n",
       "<div class=\"col-md-6 collapse in\" id=\"minifreqtable-5149104915845966272\">\n",
       "    <table class=\"mini freq\">\n",
       "        <tr class=\"\">\n",
       "    <th>Zhenyi Village Park</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: 0.4%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        2\n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>Ren Ai Rd 151 Ln</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: 0.2%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        1\n",
       "    </td>\n",
       "</tr><tr class=\"\">\n",
       "    <th>Longmen & Longbin Intersection</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: 0.2%\">\n",
       "            &nbsp;\n",
       "        </div>\n",
       "        1\n",
       "    </td>\n",
       "</tr><tr class=\"other\">\n",
       "    <th>Other values (544)</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: 99.3%\">\n",
       "            544\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=\"#freqtable-5149104915845966272, #minifreqtable-5149104915845966272\"\n",
       "       aria-expanded=\"true\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"col-md-12 extrapadding collapse\" id=\"freqtable-5149104915845966272\">\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\">Zhenyi Village Park</td>\n",
       "        <td class=\"number\">2</td>\n",
       "        <td class=\"number\">0.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:1%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">Ren Ai Rd 151 Ln</td>\n",
       "        <td class=\"number\">1</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\">Longmen & Longbin Intersection</td>\n",
       "        <td class=\"number\">1</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\">MRT Touqianzhuang Sta.(Exit.1)</td>\n",
       "        <td class=\"number\">1</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\">Guanghua dongdishi</td>\n",
       "        <td class=\"number\">1</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\">Fushou Park</td>\n",
       "        <td class=\"number\">1</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\">Luzhou Chongyang Building</td>\n",
       "        <td class=\"number\">1</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\">New Taipei City Library Wugu-Chenggong Branch</td>\n",
       "        <td class=\"number\">1</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\">Ln. 284, Zhongzheng Rd.</td>\n",
       "        <td class=\"number\">1</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\">MRT Xinzhuang Sta. (Exit 1)</td>\n",
       "        <td class=\"number\">1</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=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (537)</td>\n",
       "        <td class=\"number\">537</td>\n",
       "        <td class=\"number\">98.0%</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_sno\">sno<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>548</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>100.0%</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>1282.1</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>1001</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>1648</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=\"minihistogram-146009904290028400\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAASBJREFUeJzt27FNxEAQQFEOXUkUQU/E9EQR19OQI/jCSHe7Mu/FDmaDr/FK9mVm5gn41vPqAWBn19UDfPXy9rF6hB/d3l8PPf%2Bosxydi9/bLpCd7RzvEX85x3%2BN0CsWBIFAEAgEd5ATOMvdaEc2CASBQBAIBIFAEAgEgUAQCASBQBAIBIFAEAgEgUAQCASBQPC5O3dzhl97bRAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoFwmZlZPQTsygaBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKBIBAIAoEgEAgCgSAQCAKB8AnQ3hdjM0VqAgAAAABJRU5ErkJggg%3D%3D\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives-146009904290028400,#minihistogram-146009904290028400\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives-146009904290028400\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles-146009904290028400\"\n",
       "                                                  aria-controls=\"quantiles-146009904290028400\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram-146009904290028400\" aria-controls=\"histogram-146009904290028400\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common-146009904290028400\" aria-controls=\"common-146009904290028400\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme-146009904290028400\" aria-controls=\"extreme-146009904290028400\"\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=\"quantiles-146009904290028400\">\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>1001</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>1028.3</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>1137.8</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>1274.5</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>1417.2</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>1611.7</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>1648</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>647</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>279.5</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>171.1</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.13346</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>-0.85707</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>1282.1</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>144.65</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>0.24157</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>702564</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>29277</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>4.4 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=\"histogram-146009904290028400\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzt3X9w1dWd%2BP8XcrUkUQQHg7Mdd9wKaO1iiUapWrptFK0Wqi1q2unSLuPWXYliZixaq9vtOAus46fWpdSOXe1SF2ZEWX%2BsSimtq9a1shi1yDqLBV3tThmbgAEhgCTkfP/wS%2Bwl/IjlwE3ufTxm/CPnfbn3dc%2B8886Te29wUEopBQAA2RxW6gEAAMqNwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGaFUg9QKdraNme9v8MOGxTHHFMTb7/dEd3dKet9D0T243324n32opj9eJ%2B9KFbO%2B3HssUeV5HG9gjVAHXbYoBg0aFAcdtigUo/SL9iP99mL99mLYvbjffaimP3IT2ABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZoVSD8CBmfj/nin1CPQTP20%2Bp9Qj9NmFdzxb6hHK2kA6F6BceQULACAzgQUAkJnAAgDITGABAGTmQ%2B5QJnxwnIFooJ23foGAvvIKFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGRWkYG1YcOGmD59etTX18f48eNj1qxZ0dXVVeqxAIAyUZGB1dzcHNXV1fHMM8/E4sWL47nnnov58%2BeXeiwAoExUXGC9%2BeabsWLFipg5c2ZUVVXF8ccfH9OnT4%2BFCxeWejQAoExUXGCtWbMmhg0bFiNHjuxZO/HEE2PdunXxzjvvlHAyAKBcFEo9wKHW0dERVVVVRWu7vt66dWsMHTr0gB%2BjtbU12traitYKheqora094PveZfDgimtjoI8KhT1fH3ZdN1w//nh729uBzrmRX8UFVnV1dWzbtq1obdfXNTU1WR5j0aJFMW/evKK1pqammDFjRpb7B9iX4cP3fS0bOrRqn8fZu/3t7UDn3Min4gJr9OjRsXHjxli/fn2MGDEiIiJee%2B21OO644%2BKoo47K8hiNjY3R0NBQtFYoVEd7e0eW%2B494728ZvhGAPdnbtWbXdeOdd7bFzp3dh3iq8pDzOt6flPO5UaoorrjAOuGEE%2BL000%2BP2bNnxy233BLt7e1x5513xqWXXprtMWpra3u9HdjWtjm6usrrpAX6p/1da3bu7HY9%2BiOV%2B745N/KpyDdb586dG11dXXHuuefG5ZdfHhMmTIjp06eXeiwAoExU3CtYEREjRoyIuXPnlnoMAKBMVeQrWAAAB5PAAgDITGABAGQmsAAAMqvID7kDlLML73i21CNAxfMKFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwqNrCWLFkSp5xyStTV1fX8N3PmzIiIePrpp2Py5Mkxbty4uPDCC%2BPJJ58s8bQAwEBSKPUApbJq1aq4%2BOKLY86cOUXrb7zxRlxzzTVx%2B%2B23x6c//elYtmxZNDc3x7Jly2LkyJElmhYAGEgq9hWsVatWxZ//%2BZ/3Wn/ooYeivr4%2BzjvvvCgUCnHRRRfFGWecEYsWLSrBlADAQFSRr2B1d3fHK6%2B8ElVVVXH33XfHzp074y/%2B4i/iG9/4RqxduzbGjBlTdPtRo0bF6tWrSzQtADDQVGRgvf3223HKKafEBRdcEHPnzo329va44YYbYubMmbFjx46oqqoquv2QIUNi69atfb7/1tbWaGtrK1orFKqjtrY2y/wREYMHV%2ByLjwAlUyiU57V3188UP1vyqcjAGjFiRCxcuLDn66qqqpg5c2ZcfvnlMX78%2BNi%2BfXvR7bdv3x41NTV9vv9FixbFvHnzitaamppixowZBzY4ACU1fHjffxYMREOHVu3/RvRJRQbW6tWr47HHHovrrrsuBg0aFBERO3bsiMMOOyxOPfXU%2BJ//%2BZ%2Bi269du3aPn9fam8bGxmhoaChaKxSqo72948CH//8NHnyYbwSAQyzndbw/2fUz5Z13tsXOnd2lHierUkVxRQbWsGHDYuHChXH00UfHtGnTorW1NW677bb4whe%2BEJdcckn85Cc/iSVLlsT5558fy5YtixUrVsRNN93U5/uvra3t9XZgW9vm6Ooqr5MWoNKU%2B3V8587usn%2BOh0pFvtl63HHHxV133RVPPPFEnHnmmTFlypQYO3ZsfPvb344TTzwxfvCDH8Rdd90VZ5xxRtx5553x/e9/P/7sz/6s1GMDAAPEoJRSKvUQlaCtbXPW%2BysUDovhw2ui/qalWe8XgL37afM5pR7hoNj1M6W9vaPsXsE69tijSvK4FfkKFgDAwSSwAAAyE1gAAJkJLACAzAQWAEBmAgsAIDOBBQCQmcACAMhMYAEAZCawAAAyE1gAAJkJLACAzAQWAEBmAgsAIDOBBQCQmcACAMhMYAEAZCawAAAyE1gAAJkJLACAzAQWAEBmAgsAIDOBBQCQmcACAMhMYAEAZCawAAAyE1gAAJkJLACAzAQWAEBmAgsAIDOBBQCQmcACAMhMYAEAZCawAAAyE1gAAJkJLACAzAQWAEBmFR1YO3fujKlTp8Y3v/nNovWVK1fGZZddFnV1ddHQ0BAPPPBAiSYEAAaiig6sefPmRUtLS9Hapk2b4sorr4xLLrkknn/%2B%2BZg1a1bMmTMnXn755RJNCQAMNBUbWM8991wsW7Yszj///KL1ZcuWxbBhw%2BIrX/lKFAqFOOuss2Ly5MmxcOHCEk0KAAw0hVIPUAobNmyIm266Ke68886YP39%2B0bE1a9bEmDFjitZGjRoVixcv7vP9t7a2RltbW9FaoVAdtbW1f/TMuxs8uGLbGKBkCoXyvPbu%2BpniZ0s%2BFRdY3d3dMXPmzJg2bVqcfPLJvY53dHREVVVV0dqQIUNi69atfX6MRYsWxbx584rWmpqaYsaMGX/c0AD0C8OH15R6hINq6NCq/d%2BIPqm4wLrrrrviiCOOiKlTp%2B7xeFVVVWzevLlobfv27VFT0/dvqsbGxmhoaChaKxSqo72944MPvBeDBx/mGwHgEMt5He9Pdv1MeeedbbFzZ3epx8mqVFFccYH1yCOPRGtra9TX10fEe/EUEfGLX/wiWlpaYsyYMfHss88W/Zm1a9fG6NGj%2B/wYtbW1vd4ObGvbHF1d5XXSAlSacr%2BO79zZXfbP8VCpuDdbly5dGi%2B%2B%2BGK0tLRES0tLTJo0KSZNmtTz24QTJ06M9evXx/z586OzszOWL18ejz76aEyZMqXEkwMAA0XFBdb%2BDB8%2BPH784x/H0qVLY/z48XHzzTfHzTffHJ/4xCdKPRoAMEBU3FuEu/vHf/zHXmtjx46N%2B%2B67rwTTAADlwCtYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZVfy/5A4A5erCO54t9Qh99tPmc0o9QlZewQIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJDZgPqHRl944YV44YUXorOzM1JKRceuvvrqEk0FAFBswATWj370o7j99tvj6KOPjpqamqJjgwYNElgAQL8xYAJrwYIFcdVVV8W1115b6lEAAPZpwHwGa9OmTXHJJZeUegwAgP0aMIF1%2Bumnx6pVq0o9BgDAfg2YtwgvvPDCuOWWW%2BK///u/4yMf%2BUgcccQRRce9ugUA9BcDJrD%2B7u/%2BLiIi5s%2Bf3%2BvYoEGDBBYA0G8MmMBavXp1qUcAAOiTAfMZLACAgWLAvILV0NAQgwYN2uvxJ5544hBOAwCwdwMmsL7whS8UBVZnZ2e8%2Beab8ctf/jKam5tLOBkAQLEBE1jXXHPNHtcXLFgQL7zwQnz1q189xBMBAOzZgP8M1mc%2B85l4%2BumnSz0GAECPAR9YK1asiA996EOlHgMAoMeAeYtw97cAU0qxZcuWePXVV709CAD0KwMmsD784Q/3Wjv88MPja1/7WkyePLkEEwEA7NmACaw5c%2BaUegQAgD4Z8J/BAgDobwQWAEBmAgsAIDOBBQCQmcACAMisX/8W4Zw5c%2BLaa6%2BN6urqUo/ygbS2tkZbW1vRWqFQHbW1tdkeY/BgbQxwqBUKrr0HS7ntbb8OrHvvvTeuvPLKosC64oorYs6cOVljJbdFixbFvHnzitaamppixowZJZoIgByGD68p9Qhlq9z2tl8HVkqp19qLL74Y7777bgmm6bvGxsZoaGgoWisUqqO9vSPbYwwefFgMHVqV7f4A2L%2Bc13GKHay9LVW49evAGqhqa2t7vcLW1rY5urq6SzQRADm4jh885ba35fWGJwBAP9DvA2vQoEGlHgEA4APp928R/sM//EN86EMf6vm6s7MzbrvttqipKX5P1f%2BrEADoL/p1YJ1xxhm9/rmDurq6aG9vj/b29hJNBQCwb/06sP71X/%2B11CMAAHxg/f4zWAAAA43AAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsPZg9erVMW3atDjzzDPjnHPOieuvvz7efvvtiIhYuXJlXHbZZVFXVxcNDQ3xwAMPlHhaAKC/EVi72b59e/z1X/911NXVxX/%2B53/GY489Fhs3boxvfetbsWnTprjyyivjkksuieeffz5mzZoVc%2BbMiZdffrnUYwMA/YjA2s26devi5JNPjqampjjiiCNi%2BPDh0djYGM8//3wsW7Yshg0bFl/5yleiUCjEWWedFZMnT46FCxeWemwAoB8plHqA/uYjH/lI3H333UVrP/vZz%2BJjH/tYrFmzJsaMGVN0bNSoUbF48eKitdbW1mhraytaKxSqo7a2NtucgwdrY4BDrVBw7T1Yym1vBdY%2BpJTijjvuiCeffDIWLFgQ9957b1RVVRXdZsiQIbF169aitUWLFsW8efOK1pqammLGjBkHfWYADp7hw2tKPULZKre9FVh7sWXLlrjxxhvjlVdeiQULFsRJJ50UVVVVsXnz5qLbbd%2B%2BPWpqik%2BKxsbGaGhoKForFKqjvb0j23yDBx8WQ4dW7f%2BGAGST8zpOsYO1t6UKN4G1B7/97W/j61//evzJn/xJLF68OI455piIiBgzZkw8%2B%2ByzRbddu3ZtjB49umittra219uBbW2bo6ur%2B%2BAODsBB5Tp%2B8JTb3pbXG54ZbNq0Kb72ta/FaaedFvfcc09PXEVETJw4MdavXx/z58%2BPzs7OWL58eTz66KMxZcqUEk4MAPQ3XsHazYMPPhjr1q2Ln/70p7F06dKiYy%2B99FL8%2BMc/jlmzZsXcuXPjmGOOiZtvvjk%2B8YlPlGhaAKA/Eli7mTZtWkybNm2vx8eOHRv33XffIZwIABhovEUIAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADKryMDasGFDTJ8%2BPerr62P8%2BPExa9as6OrqKvVYAECZqMjAam5ujurq6njmmWdi8eLF8dxzz8X8%2BfNLPRYAUCYqLrDefPPNWLFiRcycOTOqqqri%2BOOPj%2BnTp8fChQtLPRoAUCYqLrDWrFkTw4YNi5EjR/asnXjiibFu3bp45513SjgZAFAuCqUe4FDr6OiIqqqqorVdX2/dujWGDh16wI/R2toabW1tRWuFQnXU1tYe8H3vMnhwxbUxQMkVCq69B0u57W3FBVZ1dXVs27ataG3X1zU1NVkeY9GiRTFv3ryitaamppgxY0aW%2BwegNIYPz/Nzgt7KbW8rLrBGjx4dGzdujPXr18eIESMiIuK1116L4447Lo466qgsj9HY2BgNDQ1Fa4VCdbS3d2S5/4j3XsEaOrRq/zcEIJuc13GKHay9LVW4VVxgnXDCCXH66afH7Nmz45Zbbon29va4884749JLL832GLW1tb3eDmxr2xxdXd3ZHgOAQ891/OApt70trzc8%2B2ju3LnR1dUV5557blx%2B%2BeUxYcKEmD59eqnHAgDKRMW9ghURMWLEiJg7d26pxwAAylRFvoIFAHAwCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnAAgDITGABAGQmsAAAMhNYAACZCSwAgMwEFgBAZgILACAzgQUAkJnA2oMNGzbE9OnTo76%2BPsaPHx%2BzZs2Krq6uUo8FAAwQAmsPmpubo7q6Op555plYvHhxPPfcczF//vxSjwUADBACazdvvvlmrFixImbOnBlVVVVx/PHHx/Tp02PhwoWlHg0AGCAE1m7WrFkTw4YNi5EjR/asnXjiibFu3bp45513SjgZADBQFEo9QH/T0dERVVVVRWu7vt66dWsMHTp0v/fR2toabW1tRWuFQnXU1tZmm3PwYG0McKgVCq69B0u57a3A2k11dXVs27ataG3X1zU1NX26j0WLFsW8efOK1q6%2B%2Buq45ppr8gwZ70XcT35ydyy5tjFruA1Ura2tsWjRomhstB/24n32opj9eF%2Bl7EXLrM/26XaVsh%2BHUnnlYgajR4%2BOjRs3xvr163vWXnvttTjuuOPiqKOO6tN9NDY2xoMPPlj0X2NjY9Y529raYt68eb1eKatU9uN99uJ99qKY/XifvShmP/LzCtZuTjjhhDj99NNj9uzZccstt0R7e3vceeedcemll/b5Pmpra/0NAAAqmFew9mDu3LnR1dUV5557blx%2B%2BeUxYcKEmD59eqnHAgAGCK9g7cGIESNi7ty5pR4DABigBn/nO9/5TqmH4I9TU1MTZ555Zp8/fF/u7Mf77MX77EUx%2B/E%2Be1HMfuQ1KKWUSj0EAEA58RksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQmsfuTtt9%2BOiRMnxn/913/1rK1cuTIuu%2ByyqKuri4aGhnjggQeK/sxDDz0UEydOjHHjxsUXv/jFeOmll3qO7dy5M2699dY4%2B%2Byzo66uLq666qpobW09ZM/nQO1pP3ZpaWmJj3/8473WFy9eHOedd158/OMfjylTpsTLL7/cc6yrqyvmzJkTZ511VtTV1UVTU1OsX7/%2BoD6HXPa0Fz/72c/i4osvjtNOOy0aGhpi3rx50d3d3XO8nM%2BNP7SnvVm4cGGcf/75UVdXF%2Beff34sWLCg6M9Uyt7s3Lkzpk6dGt/85jeL1p9%2B%2BumYPHlyjBs3Li688MJ48skni47/8z//c3zqU5%2BKcePGxdSpU%2BP1118/lGMfNHu7phzIdbY/29vz3bhxY1x//fUxfvz4OOOMM2L69Ol7Pcf7ci7sb/8qVqJfaGlpSeedd14aM2ZMWr58eUoppY0bN6YzzzwzLViwIHV2dqZf/epXqa6uLq1cuTKllNLy5ctTXV1damlpSTt27Ej/8i//ksaPH5%2B2bt2aUkrp%2B9//fpo8eXJat25d2rx5c2pubk5f//rXS/YcP4g97UdKKe3cuTPdf//9ady4cemjH/1o0Z959tln02mnnZZeeuml9O6776a77747nX322Wn79u0ppZS%2B973vpYsvvji99dZbafPmzemaa65Jf/u3f3tIn9cfY097sWrVqnTqqaem//iP/0g7d%2B5Ma9euTZ/5zGfSPffck1Iq73PjD%2B1pb5544ol0xhlnpFWrVqWUUlq5cmUaO3Zseu6551JKlbM3KaV0xx13pJNPPjndcMMNPWv/%2B7//m8aOHZt%2B/vOfp87OzvT444%2BnU089Nb311lsppZQefPDBNGHChPSb3/wmbd%2B%2BPc2ZMyd97nOfS93d3aV6Glns7ZpyoNfZ/mpvzzellP7yL/8yNTU1pU2bNqXNmzenq6%2B%2BOl155ZW97qMv58L%2B9q%2BSCax%2B4MEHH0yf/vSn0%2BOPP170zXD//fen888/v%2Bi23/72t9P111%2BfUkrpuuuuSzfffHPR8c9%2B9rNp8eLFKaWUPvWpT6V///d/7znW1taWTjrppPTb3/72YD6dA7a3/UgppW984xupsbEx3X333b0Cq7m5Of393/990drEiRPTQw89lFJK6ZxzzkmPP/54z7G33nornXTSSel3v/vdwXsyB2hve7F06dI0e/bsotvOnj27JxjL9dz4Q/s6TzZv3pxSSqmzszM99dRT6dRTT02vvPJKSqky9iallH71q1%2Bliy66KM2YMaMosG6//fY0bdq0otteccUV6Z/%2B6Z9SSil96UtfSj/84Q97ju3YsSPV1dX1BOpAtK9z5UCvs/3Rvp7vqlWr0tixY3u%2BR1JKqb29Pf3mN7/pdT99ORf2t3%2BVzFuE/cAnP/nJ%2BPnPfx4XXXRR0fqaNWtizJgxRWujRo2K1atXR0TE2rVr93p88%2BbN8dZbbxUdHzFiRBx99NHx6quvHqRnksfe9iMi4rrrrov77rsvPvrRj/Y6tqf9OPHEE%2BPVV1%2BN9vb2aGtri5NOOqnn2MiRI6OmpqZf78fe9uKCCy6IG2%2B8sefr7du3x1NPPRUf%2B9jHIqJ8z40/tK/z5Mgjj4zXX389Tj311Ljyyivjy1/%2BcpxyyikRURl7s2HDhrjpppviu9/9blRVVRUd29fz39Pxww8/PE444YSe4wPRvs6VA7nO9lf7er4vv/xyjBo1Ku6///6YOHFifPKTn4xbb701jj322F637cu5sL/9q2QCqx849thjo1Ao9Frv6OjodXEcMmRIbN26db/HOzo6IiKiurq61/Fdx/qrve1HRMRxxx231z/X0dHR6/lWVVVFR0dHz3Pefb%2Bqqqp69rM/2tde7LJly5ZoamqKIUOGxF/91V9FRPmeG39of3tz/PHHx8qVK2Px4sXx%2BOOPx49%2B9KOIKP%2B96e7ujpkzZ8a0adPi5JNP7nX8QK4rA9W%2BzpVy3I99Pd9NmzbFq6%2B%2BGm%2B88UY89NBD8fDDD8fvf//7uOGGG3rdti/PfSDuz6EisPqxqqqq2L59e9Ha9u3bo6amZr/Hd53w27Zt2%2BufLzdVVVW9nu%2B2bduipqam5wfm3o4PVK%2B//np86Utfiq6urrj33nvjyCOPjAjnRsR7f9s%2B/PDDY%2BzYsfHVr341HnvssYgo/72566674ogjjoipU6fu8fiBXFfKUaXtxxFHHBERETfddFMceeSRMWLEiGhubo6nn366118i%2BvLcy21/chJY/diYMWNizZo1RWtr166N0aNHR0TE6NGj93r86KOPjpEjR8batWt7jrW1tcXGjRt7vZxbLkaPHl30fCMiXnvttRgzZkwcc8wxMWLEiKLjv//972PLli09%2BznQPP3003HZZZfFhAkT4p577omjjz6651glnxvz58%2BP5ubmorUdO3b07E%2B5780jjzwSK1asiPr6%2Bqivr4/HHnssHnvssaivr4%2BID35d6ezsjDfeeGPAPP8P6kCuswPRqFGjoru7Ozo7O3vWdv32cUqp6LZ9ORf2t3%2BVTGD1YxMnToz169fH/Pnzo7OzM5YvXx6PPvpoTJkyJSIiLr300nj00Udj%2BfLl0dnZGfPnz48NGzbExIkTIyLii1/8Yvzwhz%2BM//u//4stW7bE7Nmz48wzz4w//dM/LeXTOmimTJkSDz/8cDz//POxY8eOuOeee2LTpk1x7rnnRsR7%2B/GDH/wgfve738WWLVti1qxZcdZZZ8WHP/zhEk/%2Bwf3617%2BOpqamuPHGG%2BOGG27o9XZAJZ8b9fX18Ytf/CKWLFkS3d3d8cILL8S9994bX/7ylyOi/Pdm6dKl8eKLL0ZLS0u0tLTEpEmTYtKkSdHS0hIREZ///OdjxYoVsWTJkujq6oolS5bEihUr4uKLL46I976PFixYEKtXr4533303vvvd78aIESN6Aq3cHOh1dqA5%2B%2Byz4/jjj49vfetbsWXLlnj77bfje9/7Xpx33nk9r4Dv0pdzYX/7V9FK/Sl7iu3%2BGx8vv/xyamxsTHV1dencc89N//Zv/1Z0%2B4cffjhdcMEFady4cenSSy9Nv/71r3uO7dixI912221pwoQJ6bTTTktXXXVVWr9%2B/SF7Ljns6VeMU3rvn2TY/bcIU3rvt2d27cdll11W9KvC7777brr11lvThAkT0umnn56amprShg0bDur8Of3hXvzN3/xNOumkk9K4ceOK/rviiit6bl/u58Yf2v08eeKJJ9LkyZNTXV1dmjRpUnrkkUeKbl9Je3PDDTcU/RZhSin98pe/TJ///OfTuHHj0uc%2B97n01FNP9Rzr7u5O99xzT2poaEjjxo1LU6dOTa%2B//vqhHvvZb02SAAAAiUlEQVSg2dM15UCus/3dnp7vW2%2B9lZqbm9M555yT6uvr0/XXX582bdrU68/29VzY3/5VqkEp7faaIAAAB8RbhAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBkJrAAADITWAAAmQksAIDMBBYAQGYCCwAgM4EFAJCZwAIAyExgAQBk9v8B7siciwgg9sIAAAAASUVORK5CYII%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common-146009904290028400\">\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\">1023</td>\n",
       "        <td class=\"number\">1</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\">1203</td>\n",
       "        <td class=\"number\">1</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\">1209</td>\n",
       "        <td class=\"number\">1</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\">1208</td>\n",
       "        <td class=\"number\">1</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\">1207</td>\n",
       "        <td class=\"number\">1</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\">1206</td>\n",
       "        <td class=\"number\">1</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\">1205</td>\n",
       "        <td class=\"number\">1</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\">1204</td>\n",
       "        <td class=\"number\">1</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\">1202</td>\n",
       "        <td class=\"number\">1</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\">1228</td>\n",
       "        <td class=\"number\">1</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=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (538)</td>\n",
       "        <td class=\"number\">538</td>\n",
       "        <td class=\"number\">98.2%</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=\"extreme-146009904290028400\">\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\">1001</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1002</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1003</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1004</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1005</td>\n",
       "        <td class=\"number\">1</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",
       "            <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\">1642</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1644</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1645</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1646</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">1648</td>\n",
       "        <td class=\"number\">1</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_tot\">tot<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>34</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Unique (%)</th>\n",
       "                    <td>6.2%</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",
       "                <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>40.522</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Minimum</th>\n",
       "                    <td>26</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <th>Maximum</th>\n",
       "                    <td>106</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=\"minihistogram-2462492021518939684\">\n",
       "    <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAABLCAYAAAA1fMjoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAAS5JREFUeJzt3dFtgzAUQNFSZaQOkZ3y3Z0yRHdyF6iuAirgJOf8I/nn6skWmGWMMT6AP32evQCY2eXsBfyHr9t99TM/39cdVsKrMUEgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCATCdFePbrlGFPZigkAQCASBQJhuD3IUv0zgESYIBIFAEAgEgUAQCASBQHjbY94t1h4NOxZ%2BfiYIBIFAEAgEgUAQCASnWDvyQuTzE8hkjviiUoSPE8gbOmqyvcIEXcYY4%2BxFwKxs0iEIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCAIBIJAIAgEgkAgCASCQCD8Av/hHwKHU%2B4nAAAAAElFTkSuQmCC\">\n",
       "\n",
       "</div>\n",
       "<div class=\"col-md-12 text-right\">\n",
       "    <a role=\"button\" data-toggle=\"collapse\" data-target=\"#descriptives-2462492021518939684,#minihistogram-2462492021518939684\"\n",
       "       aria-expanded=\"false\" aria-controls=\"collapseExample\">\n",
       "        Toggle details\n",
       "    </a>\n",
       "</div>\n",
       "<div class=\"row collapse col-md-12\" id=\"descriptives-2462492021518939684\">\n",
       "    <ul class=\"nav nav-tabs\" role=\"tablist\">\n",
       "        <li role=\"presentation\" class=\"active\"><a href=\"#quantiles-2462492021518939684\"\n",
       "                                                  aria-controls=\"quantiles-2462492021518939684\" role=\"tab\"\n",
       "                                                  data-toggle=\"tab\">Statistics</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#histogram-2462492021518939684\" aria-controls=\"histogram-2462492021518939684\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Histogram</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#common-2462492021518939684\" aria-controls=\"common-2462492021518939684\"\n",
       "                                   role=\"tab\" data-toggle=\"tab\">Common Values</a></li>\n",
       "        <li role=\"presentation\"><a href=\"#extreme-2462492021518939684\" aria-controls=\"extreme-2462492021518939684\"\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=\"quantiles-2462492021518939684\">\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>26</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>5-th percentile</th>\n",
       "                        <td>30</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q1</th>\n",
       "                        <td>34</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Median</th>\n",
       "                        <td>38</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Q3</th>\n",
       "                        <td>44</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>95-th percentile</th>\n",
       "                        <td>60</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Maximum</th>\n",
       "                        <td>106</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Range</th>\n",
       "                        <td>80</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Interquartile range</th>\n",
       "                        <td>10</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>10.863</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Coef of variation</th>\n",
       "                        <td>0.26808</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Kurtosis</th>\n",
       "                        <td>7.7306</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Mean</th>\n",
       "                        <td>40.522</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>MAD</th>\n",
       "                        <td>7.4912</td>\n",
       "                    </tr>\n",
       "                    <tr class=\"\">\n",
       "                        <th>Skewness</th>\n",
       "                        <td>2.2933</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Sum</th>\n",
       "                        <td>22206</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Variance</th>\n",
       "                        <td>118.01</td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th>Memory size</th>\n",
       "                        <td>4.4 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=\"histogram-2462492021518939684\">\n",
       "            <img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAYAAAByNR6YAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAPYQAAD2EBqD%2BnaQAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzt3Xt0VPW99/FPkglkSEwJl8DRx0cUEkARE0jCrVKIpMjNC5emoh5kgV0HIxyshItYoQUKHsBSTLVWtApklYgCCoaLxyq2KASUgnCIh1DRpVmShFyAXMxtP3/4EDuAkuAP9swv79daWchv9sx8P%2Bw9%2BMnekyHIcRxHAAAAMCbY7QEAAABsQ8ECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZ53B6guSgsPO32CI0WHBykNm3CVVxcrvp6x%2B1xjLE1l2RvNltzSfZmszWXZG82W3NJ32Rr2zbCned25Vnh14KDgxQUFKTg4CC3RzHK1lySvdlszSXZm83WXJK92WzNJcnVTBQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADDM4/YAaD6Grdjl9ghNsnX6ALdHAAAEKM5gAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGHWFqzc3FxNnDhRSUlJGjBggGbOnKni4mJJ0rx589SjRw/Fx8c3fGVlZTXc9/nnn9fAgQMVFxen%2B%2B%2B/X//85z/digEAAAKQlQWrqqpKkydPVnx8vP7%2B979ry5YtKi0t1WOPPSZJ%2Bvjjj7VgwQLt37%2B/4Ss1NVWStHHjRq1Zs0YvvPCC9uzZo5tuuknTpk2T4zhuRgIAAAHEyoKVn5%2Bvbt26KS0tTS1atFBUVJRSU1O1d%2B9eVVdX63//93/Vo0ePC973lVde0fjx4xUTE6OWLVvq0UcfVX5%2Bvvbs2XOFUwAAgEBlZcG64YYbtGrVKoWEhDSsbd%2B%2BXTfddJNyc3NVW1urlStXqn///ho6dKj%2B9Kc/qb6%2BXpKUl5en2NjYhvuFhoaqU6dOys3NveI5AABAYLL%2Bk9wdx9GKFSv0zjvvaO3atSoqKlJSUpLuv/9%2BPfXUUzpy5IjS0tIUHBysyZMnq7y8XF6v1%2BcxwsLCVFFR0ejnLCgoUGFhoc%2Bax9NK0dHRRjJdbiEhwT6/NlceT%2BDkt3Wf2ZpLsjebrbkke7PZmktyN5PVBevMmTOaM2eODh8%2BrLVr16pr167q2rWrBgz49p9A6dmzpyZMmKDs7GxNnjxZXq9XVVVVPo9TVVWl8PDwRj9vVlaWMjIyfNbS0tI0bdq0HxboCouM9F58I4tFRTV%2Bn/sLW/eZrbkke7PZmkuyN5utudxibcH6/PPP9eCDD%2Brqq6/Wq6%2B%2BqjZt2kiS/vu//1tFRUX6%2Bc9/3rBtdXW1wsLCJEkxMTE6evSoBg8eLEmqqanR8ePHfS4bXkxqaqqSk5N91jyeViopKf%2Bhsa6IkJBgRUZ6depUperq6t0exzWBsr8ke/eZrbkke7PZmkuyN5utuaRvs7nByoJVVlamCRMmqG/fvlq0aJGCg789Reg4jhYvXqzrrrtOffv21T/%2B8Q%2BtXr1ac%2BbMkSSNGTNGTz/9tAYOHKjrr79ev/vd79SuXTslJCQ0%2Bvmjo6PPuxxYWHhatbWBdeDW1dUH3MwmBWJ2W/eZrbkke7PZmkuyN5utudxiZcHasGGD8vPztXXrVm3bts3ntv3792vOnDmaP3%2B%2BTpw4oXbt2mnq1Km68847JUljx47V6dOnlZaWpuLiYt1888167rnnFBoa6kYUAAAQgIIcPuDpiigsPO32CI3m8QQrKipcJSXlRr%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%2BPl7Jyclav369z303btyolJQUxcXFafTo0dq/f78bEQAAQICysmBVVVVp8uTJio%2BP19///ndt2bJFpaWleuyxx1RWVqZf/OIXuuuuu7R3714tWrRIixcv1sGDByVJe/bs0YIFC7RkyRLt3btXd9xxh6ZMmaLKykqXUwEAgEBhZcHKz89Xt27dlJaWphYtWigqKkqpqanau3evduzYodatW%2Bvee%2B%2BVx%2BNRv379NGrUKGVmZkqS1q9frxEjRqh3794KDQ3VAw88oKioKGVnZ7ucCgAABAorC9YNN9ygVatWKSQkpGFt%2B/btuummm3T06FHFxsb6bN%2BlSxfl5uZKkvLy8r73dgAAgIvxuD3A5eY4jlasWKF33nlHa9eu1erVq%2BX1en22CQsLU0VFhSSpvLz8e29vjIKCAhUWFvqseTytFB0dfYkprqyQkGCfX5srjydw8tu6z2zNJdmbzdZckr3ZbM0luZvJ6oJ15swZzZkzR4cPH9batWvVtWtXeb1enT592me7qqoqhYeHS5K8Xq%2BqqqrOuz0qKqrRz5uVlaWMjAyftbS0NE2bNu0Sk7gjMtJ78Y0sFhUV7vYITWbrPrM1l2RvNltzSfZmszWXW6wtWJ9//rkefPBBXX311Xr11VfVpk0bSVJsbKx27drls21eXp5iYmIkSTExMTp69Oh5tw8cOLDRz52amqrk5GSfNY%2BnlUpKyi8lyhUXEhKsyEivTp2qVF1dvdvjuCZQ9pdk7z6zNZdkbzZbc0n2ZrM1l/RtNjdYWbDKyso0YcIE9e3bV4sWLVJw8LenCFNSUrR06VK99NJLuvfee/Xhhx9q8%2BbNeuaZZyRJY8eOVVpamoYNG6bevXsrMzNTJ0%2BeVEpKSqOfPzo6%2BrzLgYWFp1VbG1gHbl1dfcDNbFIgZrd1n9maS7I3m625JHuz2ZrLLVYWrA0bNig/P19bt27Vtm3bfG7bv3%2B/XnzxRS1atEgrV65UmzZt9Pjjj6tv376SpH79%2BmnevHmaP3%2B%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%2Bbo5z//uU6cOKHMzEzt3r3b7bGarS1bXte9905Qhw4dFR4eof/8zxnavft9ffnlF26PBgCA3/KrS4SHDh3S%2BPHjdcstt%2BjQoUOqrq7WkSNH9Nvf/lYZGRkaPHiw2yM2SkFBgQoLC33WPJ5Wio6OdmmipgkJ%2BaZ3V1aWq6DghGJjY%2BTxfLMWHd1eV10VqePHj%2Bm66/6vm2NedmczB4Kz%2B%2Bzsr7awNZdkbzZbc0n2ZrM1l%2BRuJr8qWMuWLdPEiRP1yCOPKD4%2BXpK0cOFCXXXVVQFVsLKyspSRkeGzlpaWpmnTprk00aUJDq6XJHXs2FZRUeEN661aeRUUVOezZqNAzBcZ6XV7hMvC1lySvdlszSXZm83WXG7xq4J16NAhzZs377z1e%2B65R%2BvWrXNhokuTmpqq5ORknzWPp5VKSspdmqhpQkKCFRnpVW1tkCTpxIliRUS0abi9oqJSkidg8lyqQMp3dp%2BdOlWpurp6t8cxxtZckr3ZbM0l2ZvN1lzSt9nc4FcFKzQ0VGfOnDlvPT8/X15v4DTr6Ojo8y4HFhaeVm1tYB244eERat8%2BWnl5ebruuhskSSdPFunUqTJdd90NAZenqQIxX11dfUDOfTG25pLszWZrLsnebLbmcotfXXAdMmSIli9frpKSkoa1Y8eOadGiRRo0aJB7gzVjw4eP0ssvv6D8/C9VUVGulSuXKy6ul6655v%2B4PRoAAH7Lr85gzZo1S5MnT1b//v3lOI5Gjx6tM2fOqFu3bpo5c6bb4zVLEyc%2BqNraWqWlPaiKinL16pWgBQuWuD0WAAB%2Bza8KVkREhNatW6cPPvhA//M//6P6%2BnrFxsbq1ltvVXCwX51sazY8Ho%2BmTJmqKVOmuj0KAAABw68K1ln9%2BvVTv3793B4DAADgkvhVwUpOTlZQUNB33v72229fwWkAAAAujV8VrLvvvtunYNXU1Oizzz7Te%2B%2B9p%2BnTp7s4GQAAQOP5VcGaOvXC7/NZu3atPvzwQ/37v//7FZ4IAACg6QLineODBw/Wzp073R4DAACgUQKiYOXk5Khly5ZujwEAANAofnWJ8NxLgI7j6MyZM/rkk0%2B4PAgAAAKGXxWsq6%2B%2B%2BryfIgwNDdWECRM0atQol6YCAABoGr8qWEuW8AnhAAAg8PlVwdq7d2%2Bjt01MTLyMkwAAAFw6vypYDzzwgBzHafg66%2Bxlw7NrQUFBOnLkiCszAgAAXIxfFaynn35aixcv1qxZs9S3b1%2BFhobqwIEDmj9/vsaPH6/Bgwe7PSIAAMBF%2BdXHNDz55JOaN2%2BehgwZooiICLVs2VJJSUn6zW9%2BoxdffFHXXHNNwxcAAIC/8quCVVBQoH/7t387bz0iIkIlJSUuTAQAANB0flWw4uLi9NRTT%2BnMmTMNa6WlpVq6dKn69evn4mQAAACN51fvwXr88cc1YcIEDRw4UJ06dZIkffrpp2rfvr1Wr17t7nAAAACN5FcFq3PnzsrOztbmzZt17NgxSdL48eM1YsQIeb1el6cDAABoHL8qWJIUGRmpcePG6YsvvtC1114r6ZtPcwcAAAgUfvUeLMdxtGzZMiUmJmrkyJH66quvNGvWLM2ZM0c1NTVujwcAANAoflWw1qxZo9dff13z5s1TixYtJElDhgzRX//6V/3%2B9793eToAAIDG8auClZWVpSeeeEKjR49u%2BPT24cOHa9GiRXrzzTddng4AAKBx/KpgffHFF%2Brevft56127dlVRUZELEwEAADSdXxWsa665RgcPHjxvfefOnQ1veAcAAPB3fvVThJMmTdKvf/1rnThxQo7j6IMPPtC6deu0Zs0azZkzx%2B3xAAAAGsWvCtaYMWNUW1urZ599VlVVVXriiSfUtm1bPfLII7rnnnvcHg8AAKBR/KpgvfHGG7r99tuVmpqq4uJiOY6jtm3buj0WAABAk/jVe7AWLlzY8Gb2Nm3aUK4AAEBA8quC1alTJ33yySdujwEAAPCD%2BNUlwpiYGM2YMUOrVq1Sp06d1LJlS5/bFy9e7NJkAAAAjedXBevzzz9X7969JUmFhYUuTwMAAHBp/KpgrVmzxu0RAAAAfjDX34O1ePFiVVRUuD0GAACAMa4XrNWrV6uystJnbdKkSSooKHBpIgAAgB/G9YLlOM55ax999JG%2B/vprF6YBAAD44VwvWAAAALahYAEAABjmFwUrKCjI7REAAACM8YuPaVi4cKHPh4rW1NRo6dKlCg8P99mODxoFAACBwPWClZiYeN6HisbHx6ukpEQlJSUuTQUAAHDpXC9YfLgoAACwjV%2B8BwsAAMAmFCwAAADDXL9EiB9m2Ipdbo8AAADOwRksAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgf03CFbd26RUuWLFBoaKhatmyprl2767/%2Ba4U8HnYFAAC24AzWFfTRR/u0aNF89ewZp02btum%2B%2ByYqJ2e3Vq9%2B0e3RAACAQRSsK2jLltclSfPmLVRERITuuec%2BXXddJ7355hsuTwYAAEziutRlUFBQoMLCQp81j6eVjh//pyIjf6SOHTs0rF9//Q16992/qrKyXFddddWVHhXfw%2BMJnO8/QkKCfX61ha25JHuz2ZpLsjebrbkkdzNRsC6DrKwsZWRk%2BKylpaWpqqpS4eGtFBUV3rAeGRkhSWrRQj7rcF8g7o/ISK/bI1wWtuaS7M1may7J3my25nILBesySE1NVXJyss%2Bax9NK27fvUFnZKZWUlDesnzp1RpJUUyOfdbgvkPZHSEiwIiO9OnWqUnV19W6PY4ytuSR7s9maS7I3m625pG%2BzuYGCdRlER0crOjraZ62w8LSuv76z8vKOqqCgUG3atJUkffrpPxUd3UFhYeGqrbXrwA50gbg/6urqA3Lui7E1l2RvNltzSfZmszWXW%2By74OrHRoy4Q15vK02cOF4VFeXKysrU559/poEDB7k9GgAAMIiCdQUlJCTpl7%2BcqdLSUg0blqw1a/6suLhemjr1l26PBgAADOIS4RU2bNhIDRs20u0xAADAZcQZLAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwPgcL%2BA7DVuxye4Qm2bfodrdHAAD8f5zBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAY1mwLVnZ2tm688UbFx8c3fKWnp0uSdu7cqVGjRikuLk7Dhg3TO%2B%2B84/K0AAAgkHjcHsAtH3/8se68804tXrzYZ/348eOaOnWqnnrqKQ0aNEg7duzQ9OnTtWPHDnXo0MGlaQEAQCBptmewPv74Y/Xo0eO89Y0bNyohIUFDhgyRx%2BPR8OHDlZiYqKysLBemBAAAgahZnsGqr6/X4cOH5fV6tWrVKtXV1eknP/mJZsyYoby8PMXGxvps36VLF%2BXm5ro0LQAACDTNsmAVFxfrxhtv1NChQ7Vy5UqVlJRo1qxZSk9PV3V1tbxer8/2YWFhqqioaPTjFxQUqLCw0GfN42ml6OhoI/MDF5Iwd5vbIzTaWzNubdR2ISHBPr/axNZstuaS7M1may7J3UzNsmC1a9dOmZmZDb/3er1KT0/Xz372M/Xp00dVVVU%2B21dVVSk8PLzRj5%2BVlaWMjAyftbS0NE2bNu2HDQ5YIiqq8a8nSYqM9F58owBlazZbc0n2ZrM1l1uaZcHKzc3Vli1b9OijjyooKEiSVF1dreDgYPXs2VNHjhzx2T4vL%2B%2BC79f6LqmpqUpOTvZZ83haqaSk/IcPD1igsa%2BFkJBgRUZ6depUperq6i/zVFeWrdlszSXZm83WXNK32dzQLAtW69atlZmZqR/96EeaOHGiCgoKtHTpUt19992666679PLLLys7O1s//elPtWPHDuXk5Gju3LmNfvzo6OjzLgcWFp5Wba1dBy5wqZr6Wqirq7f29WNrNltzSfZmszWXW%2By74NoIHTt21HPPPae3335bSUlJGjNmjG6%2B%2BWY98cQT6ty5s/7whz/oueeeU2Jiop555hk9/fTTuv76690eGwAABIhmeQZLkpKSkrRu3boL3nbrrbfq1lsb9yZcAACAczXLM1gAAACXEwULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYJjH7QEAND/DVuxye4Qm2Tp9gNsjAAgwnMECAAAwjIIFAABgGAULAADAMAoWAACAYRQsAAAAwyhYAAAAhlGwAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDD%2BLUIAuAj%2B7UQATUXBAgDLBFIhpAzCVlwiBAAAMIyCBQAAYBgF6wJOnjyphx56SAkJCerTp48WLVqk2tpat8cCAAABgvdgXcD06dPVoUMH/e1vf1NRUZGmTJmil156SZMnT3Z7NAAAGo3347mHM1jn%2BOyzz5STk6P09HR5vV5de%2B21euihh5SZmen2aAAAIEBwBuscR48eVevWrdWhQ4eGtc6dOys/P1%2BnTp1SZGSki9MBgF0C6QyLJO1bdLvbIyBAULDOUV5eLq/X67N29vcVFRWNKlgFBQUqLCz0WfN4Wik6OtrcoACAKy5h7ja3R7CWx2P%2BolpIiHsX6ihY52jVqpUqKyt91s7%2BPjw8vFGPkZWVpYyMDJ%2B1hx9%2BWFOnTjUz5L%2B4HN9NFRQUKCsrS6mpqVaVQltzSfZmszWXZG82W3NJ9mazNZf0TbaXX17lSjbeg3WOmJgYlZaWqqioqGHt2LFj6tixo6666qpGPUZqaqo2bNjg85Wamnq5RjausLBQGRkZ552FC3S25pLszWZrLsnebLbmkuzNZmsuyd1snME6R6dOndS7d2/99re/1W9%2B8xuVlJTomWee0dixYxv9GNHR0dZ9FwAAABqPM1gXsHLlStXW1uq2227Tz372M91666166KGH3B4LAAAECM5gXUC7du20cuVKt8cAAAABKmT%2B/Pnz3R4C/ic8PFxJSUmNfmN/oLA1l2RvNltzSfZmszWXZG82W3NJ7mULchzHuaLPCAAAYDnegwUAAGAYBQsAAMAwChYAAIBhFCwAAADDKFgAAACGUbAAAAAMo2ABAAAYRsECABizdu1aVVdXuz0G4DoKVjP2wQcfaNy4cerVq5cGDBigBQsWqKqqSpJ04MABjRs3TvHx8UpOTtb69etdnvbS1NXV6f7779fs2bMb1nbu3KlRo0YpLi5Ow4YN0zvvvOPihE2XnZ2tG2%2B8UfHx8Q1f6enpkgI7W2lpqWbOnKk%2BffooMTFRDz30kAoKCiRd/HgsLi5WSkqK9uzZ07B2sfts3LhRKSkpiouL0%2BjRo7V///7LkuuNN97w2Vfx8fHq0aOHevToISmw99m5XnnlFR0%2BfFjz5s1Tnz591Lt3b82cOVPl5eVuj9Zkx44d06RJk5SQkKBBgwbp2WefVX19vSR7/n60xYVe/2ft27dPt9xyy3nrr776qoYMGaJbbrlFY8aM0cGDB80P5qBZOnnypHPzzTc7r732mlNXV%2BecOHHCGTlypPP73//eKS0tdZKSkpy1a9c6NTU1zvvvv%2B/Ex8c7Bw4ccHvsJluxYoXTrVs3Z9asWY7jOM6nn37q3Hzzzc5bb73l1NTUOG%2B%2B%2BabTs2dP56uvvnJ50sZbsmSJM3v27PPWAz3bfffd56SlpTllZWXO6dOnnYcfftj5xS9%2BcdHjcd%2B%2Bfc6QIUOc2NhYZ/fu3Y7jOBe9z%2B7du534%2BHhn3759TnV1tfPnP//Z6dOnj1NRUXHZc3711VfOgAEDnE2bNgX8PvtXp06dcvr06ePMnj3bmTBhglNSUuIUFRU59913nzN//ny3x2uSM2fOOIMGDXLmzp3rlJeXO1988YUzcuRI5%2Bmnn7bq70cbXOj17ziOU1dX57zyyitOXFyc0717d5/77Nq1y%2BnVq5ezf/9%2B5%2Buvv3ZWrVrl9O/f36mqqjI6G2ewmqk2bdro/fff1%2BjRoxUUFKTS0lJ9/fXXatOmjXbs2KHWrVvr3nvvlcfjUb9%2B/TRq1ChlZma6PXaTfPDBB9qxY4d%2B%2BtOfNqxt3LhRCQkJGjJkiDwej4YPH67ExERlZWW5OGnTfPzxxw1nP/5VIGc7dOiQDhw4oCVLligyMlIRERFasGCBZsyY8b3H48aNGzVjxgw98sgjPo93sWN4/fr1GjFihHr37q3Q0FA98MADioqKUnZ29mXN6TiO0tPTNWjQIN15550Bvc/OlZmZqe7du2vz5s2aNm2aWrdurbZt22rGjBnasGGDKisr3R6x0T788EOdPHlSTzzxhFq1aqVrrrlGU6ZM0V/%2B8hdt377dir8fbfBdr39JmjVrll577TU9/PDD5922fv36hrPGrtF2AAAGZ0lEQVTGLVq00KRJkxQeHq6tW7canY%2BC1YxFRERIkn7yk59o1KhRat%2B%2BvUaPHq2jR48qNjbWZ9suXbooNzfXjTEvycmTJzV37lwtX75cXq%2B3YT0vLy%2Bgs9XX1%2Bvw4cN69913NXjwYA0cOFC/%2BtWvVFZWFtDZDh48qC5duuiVV15RSkqKfvzjH%2BvJJ59U%2B/btv/d4/PGPf6y33npLw4cP97n9YsewW39Wr7/%2BuvLy8houWQfyPjvX9u3bNWjQINXU1Phk6ty5s6qqqnT8%2BHH3hmui%2Bvp6hYaGKjQ0tGEtKChIRUVF2r9/vzX7LNB91%2Btfkh599FGtW7dO3bt3P%2B%2B2C73uOnfurE8%2B%2BcTofBQsaMeOHXrvvfcUHBysadOmqby83KeUSFJYWJgqKipcmrBp6uvrlZ6erokTJ6pbt24%2BtwV6tuLiYt14440aOnSosrOztW7dOh0/flzp6ekBna2srEyffPKJjh8/ro0bN2rTpk06ceKEZs2a9b252rdvL4/Hc97jXezPwo0/q/r6ej377LP6j//4j4ZvbgJ5n/2r6upqHTlypOF/Zq1atWq47Wy%2BQHofVq9evRQWFqbly5ersrJSX375pV544YWG223YZzb4rte/JHXs2PE771deXu5zjErf7FPTxygFCwoLC1OHDh2Unp6uv/3tb/J6vQ1vdj%2BrqqpK4eHhLk3YNM8995xatGih%2B%2B%2B//7zbAj1bu3btlJmZqbFjx8rr9erqq69Wenq63nvvPTmOE7DZWrRoIUmaO3euIiIi1K5dO02fPl07d%2B68pFwX289uHAd79uxRQUGBxo4d2%2Bg5A0Vpaakcx1FYWJgk%2BVwOPPvfZ0tlIIiMjNTzzz%2BvAwcOaNCgQZo%2BfbruuusuSVJISIgV%2B6w583q9512yrqysNL4PKVjN1EcffaTbb7/d58epq6urFRoaqi5duujo0aM%2B2%2Bfl5SkmJuZKj3lJXn/9deXk5CghIUEJCQnasmWLtmzZooSEBMXGxgZ0ttzcXC1btkyO4zSsVVdXKzg4WD179gzYbF26dFF9fb1qamoa1s7%2BxFb37t2bnOti%2BzkmJuaK/1lt375dKSkpPt85B/rxeNbZ/zG1aNFCoaGhysvLa7jt2LFjCg0NVadOnVyarumqq6tVW1ur1atXa8%2BePVq/fr2Cg4PVpUuXgH6d4RsxMTE%2Bx6j0zXF67mXDH4qC1Ux17dpVVVVVWr58uaqrq/Xll1/qySef1NixYzV06FAVFRXppZdeUk1NjXbv3q3NmzdrzJgxbo/dKNu2bdNHH32kffv2ad%2B%2BfRo5cqRGjhypffv26Y477lBOTo6ys7NVW1ur7Oxs5eTk6M4773R77EZp3bq1MjMztWrVKtXW1io/P19Lly7V3Xffrbvuuitgs/Xv31/XXnutHnvsMZWXl6u4uFi/%2B93vNGTIEI0cObLJx2NKSsr33mfs2LHavHmzdu/erZqaGr300ks6efKkUlJSLlvGDz/8UImJiT5rgX48nhUeHq6oqCjl5%2Bdr2LBhWrZsmYqLi1VcXKxly5Zp5MiRDWe3AsWkSZP06quvynEcHTp0SH/84x81YcKEix5b8H9jxozRpk2btHfvXlVXV%2BuFF15QWVmZbrvtNrNPZPRnEhFQjh496kycONFJSEhwBg8e7Dz11FPO119/7TiO4xw8eNBJTU114uPjndtuu8157bXXXJ720s2aNavhYxocx3Hee%2B8954477nDi4uKcESNGOO%2B%2B%2B66L0zXdnj17GvZN3759nQULFjT8eHEgZ/vqq6%2Bc6dOnOwMGDHASEhKcmTNnOmVlZY7jNO54PPfHtC92n02bNjlDhw514uLinLFjxzr/%2BMc/Lmu%2BuLi4C%2B6PQN5n/2rGjBnOkiVLnNOnTzuPP/64079/fycxMdGZPXu2U15e7vZ4TZaTk%2BPcfffdTlxcnHPbbbc5q1evbrjNpr8fbXHu6/%2BsXbt2nfcxDY7jOBs2bGh4/Y8bN%2B6yfMxGkOP8y7UGAAAuwZ49ezR79my9/fbbCg7m4gjAqwAA8IP16dNHnTp10ltvveX2KIBfoGABAIxYuHCh/vSnP/FvEQKSuEQIAABgGGewAAAADKNgAQAAGEbBAgAAMIyCBQAAYBgFCwAAwDAKFgAAgGEULAAAAMMoWAAAAIZRsAAAAAyjYAEAABhGwQIAADCMggUAAGDY/wPo9G%2BpHzDOfgAAAABJRU5ErkJggg%3D%3D\"/>\n",
       "        </div>\n",
       "        <div role=\"tabpanel\" class=\"tab-pane col-md-12\" id=\"common-2462492021518939684\">\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\">36</td>\n",
       "        <td class=\"number\">83</td>\n",
       "        <td class=\"number\">15.1%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:89%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">40</td>\n",
       "        <td class=\"number\">67</td>\n",
       "        <td class=\"number\">12.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:72%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">34</td>\n",
       "        <td class=\"number\">66</td>\n",
       "        <td class=\"number\">12.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:71%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">30</td>\n",
       "        <td class=\"number\">49</td>\n",
       "        <td class=\"number\">8.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:53%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">32</td>\n",
       "        <td class=\"number\">46</td>\n",
       "        <td class=\"number\">8.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:49%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">38</td>\n",
       "        <td class=\"number\">43</td>\n",
       "        <td class=\"number\">7.8%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:46%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">42</td>\n",
       "        <td class=\"number\">33</td>\n",
       "        <td class=\"number\">6.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:36%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">44</td>\n",
       "        <td class=\"number\">23</td>\n",
       "        <td class=\"number\">4.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:25%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">46</td>\n",
       "        <td class=\"number\">23</td>\n",
       "        <td class=\"number\">4.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:25%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">50</td>\n",
       "        <td class=\"number\">22</td>\n",
       "        <td class=\"number\">4.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:24%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"other\">\n",
       "        <td class=\"fillremaining\">Other values (24)</td>\n",
       "        <td class=\"number\">93</td>\n",
       "        <td class=\"number\">17.0%</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=\"extreme-2462492021518939684\">\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\">26</td>\n",
       "        <td class=\"number\">4</td>\n",
       "        <td class=\"number\">0.7%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:7%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">28</td>\n",
       "        <td class=\"number\">11</td>\n",
       "        <td class=\"number\">2.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:17%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">30</td>\n",
       "        <td class=\"number\">49</td>\n",
       "        <td class=\"number\">8.9%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:74%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">32</td>\n",
       "        <td class=\"number\">46</td>\n",
       "        <td class=\"number\">8.4%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:70%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">34</td>\n",
       "        <td class=\"number\">66</td>\n",
       "        <td class=\"number\">12.0%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&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\">88</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">92</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">98</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">102</td>\n",
       "        <td class=\"number\">1</td>\n",
       "        <td class=\"number\">0.2%</td>\n",
       "        <td>\n",
       "            <div class=\"bar\" style=\"width:100%\">&nbsp;</div>\n",
       "        </td>\n",
       "</tr><tr class=\"\">\n",
       "        <td class=\"fillremaining\">106</td>\n",
       "        <td class=\"number\">1</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>\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>sno</th>\n",
       "      <th>sna</th>\n",
       "      <th>tot</th>\n",
       "      <th>sbi</th>\n",
       "      <th>sarea</th>\n",
       "      <th>mday</th>\n",
       "      <th>lat</th>\n",
       "      <th>lng</th>\n",
       "      <th>ar</th>\n",
       "      <th>sareaen</th>\n",
       "      <th>snaen</th>\n",
       "      <th>aren</th>\n",
       "      <th>bemp</th>\n",
       "      <th>act</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1001</td>\n",
       "      <td>大鵬華城</td>\n",
       "      <td>38</td>\n",
       "      <td>14</td>\n",
       "      <td>新店區</td>\n",
       "      <td>20190604111321</td>\n",
       "      <td>24.991160</td>\n",
       "      <td>121.533980</td>\n",
       "      <td>新北市新店區中正路700巷3號</td>\n",
       "      <td>Xindian Dist.</td>\n",
       "      <td>Dapeng Community</td>\n",
       "      <td>No. 3, Lane 700 Chung Cheng Road, Xindian Dist...</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1002</td>\n",
       "      <td>汐止火車站</td>\n",
       "      <td>56</td>\n",
       "      <td>26</td>\n",
       "      <td>汐止區</td>\n",
       "      <td>20190604111335</td>\n",
       "      <td>25.068914</td>\n",
       "      <td>121.662748</td>\n",
       "      <td>南昌街/新昌路口(西側廣場)</td>\n",
       "      <td>Xizhi Dist.</td>\n",
       "      <td>Xizhi Railway Station</td>\n",
       "      <td>Nanchang St./Xinchang Rd.</td>\n",
       "      <td>30</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1003</td>\n",
       "      <td>汐止區公所</td>\n",
       "      <td>46</td>\n",
       "      <td>19</td>\n",
       "      <td>汐止區</td>\n",
       "      <td>20190604111332</td>\n",
       "      <td>25.064162</td>\n",
       "      <td>121.658301</td>\n",
       "      <td>新台五路一段/仁愛路口(新台五路側汐止地政事務所前機車停車場)</td>\n",
       "      <td>Xizhi Dist.</td>\n",
       "      <td>Xizhi Dist. Office</td>\n",
       "      <td>Sec. 1, Xintai 5th Rd./Ren’ai Rd.</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1004</td>\n",
       "      <td>國泰綜合醫院</td>\n",
       "      <td>56</td>\n",
       "      <td>5</td>\n",
       "      <td>汐止區</td>\n",
       "      <td>20190604111337</td>\n",
       "      <td>25.073150</td>\n",
       "      <td>121.662555</td>\n",
       "      <td>建成路78號對面停車場</td>\n",
       "      <td>Xizhi Dist.</td>\n",
       "      <td>Cathay General Hospital</td>\n",
       "      <td>No78, Jiancheng Rd</td>\n",
       "      <td>51</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1005</td>\n",
       "      <td>裕隆公園</td>\n",
       "      <td>40</td>\n",
       "      <td>13</td>\n",
       "      <td>新店區</td>\n",
       "      <td>20190604111336</td>\n",
       "      <td>24.979649</td>\n",
       "      <td>121.546319</td>\n",
       "      <td>寶中路/品牌路口(東南側)</td>\n",
       "      <td>Xindian Dist.</td>\n",
       "      <td>Yulon Park</td>\n",
       "      <td>Baozhong Rd./</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "    </div>\n",
       "</div>\n",
       "</div>"
      ],
      "text/plain": [
       "<pandas_profiling.ProfileReport at 0x1a34b007b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "profile = pandas_profiling.ProfileReport(df)\n",
    "display(profile)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check how many stations are still in operation?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11dd85b70>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x550 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x= 'act', data= df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Draw a boxplot of variables that I want to analyze more"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 8))\n",
    "ax = sns.boxplot(data=df[['tot','sbi', 'bemp']])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then do more data visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "tot = sns.countplot(x=\"tot\", data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How about the number of available YouBikes?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 8))\n",
    "tot = sns.countplot(x='sbi', data=df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then let's combine these two with joint plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x11e6d5ef0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x=\"tot\", y=\"sbi\", data= df, kind ='reg', height = 8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What if we take district into consideration?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1a3445d278>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1149.12x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.relplot(x= 'tot', y= 'sbi', hue = 'sareaen', data = df, height = 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Speaking of distirct, let's see how many stations for each district in New Taipei City!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "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>TOWNNAME</th>\n",
       "      <th>tot</th>\n",
       "      <th>sbi</th>\n",
       "      <th>bemp</th>\n",
       "      <th>act</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>三峽區</td>\n",
       "      <td>676</td>\n",
       "      <td>323</td>\n",
       "      <td>349</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>三重區</td>\n",
       "      <td>2420</td>\n",
       "      <td>996</td>\n",
       "      <td>1400</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>中和區</td>\n",
       "      <td>1712</td>\n",
       "      <td>793</td>\n",
       "      <td>850</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>五股區</td>\n",
       "      <td>572</td>\n",
       "      <td>221</td>\n",
       "      <td>311</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>八里區</td>\n",
       "      <td>188</td>\n",
       "      <td>72</td>\n",
       "      <td>116</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>土城區</td>\n",
       "      <td>1212</td>\n",
       "      <td>619</td>\n",
       "      <td>592</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>新店區</td>\n",
       "      <td>1662</td>\n",
       "      <td>785</td>\n",
       "      <td>860</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>新莊區</td>\n",
       "      <td>2280</td>\n",
       "      <td>858</td>\n",
       "      <td>1415</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>板橋區</td>\n",
       "      <td>3604</td>\n",
       "      <td>1407</td>\n",
       "      <td>2119</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>林口區</td>\n",
       "      <td>972</td>\n",
       "      <td>356</td>\n",
       "      <td>573</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>樹林區</td>\n",
       "      <td>1152</td>\n",
       "      <td>495</td>\n",
       "      <td>650</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>永和區</td>\n",
       "      <td>976</td>\n",
       "      <td>446</td>\n",
       "      <td>514</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>汐止區</td>\n",
       "      <td>1468</td>\n",
       "      <td>478</td>\n",
       "      <td>983</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>泰山區</td>\n",
       "      <td>402</td>\n",
       "      <td>191</td>\n",
       "      <td>205</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>淡水區</td>\n",
       "      <td>996</td>\n",
       "      <td>444</td>\n",
       "      <td>545</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>深坑區</td>\n",
       "      <td>84</td>\n",
       "      <td>31</td>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>瑞芳區</td>\n",
       "      <td>118</td>\n",
       "      <td>39</td>\n",
       "      <td>79</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>蘆洲區</td>\n",
       "      <td>1080</td>\n",
       "      <td>396</td>\n",
       "      <td>674</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>鶯歌區</td>\n",
       "      <td>632</td>\n",
       "      <td>249</td>\n",
       "      <td>325</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   TOWNNAME   tot   sbi  bemp  act\n",
       "0       三峽區   676   323   349   17\n",
       "1       三重區  2420   996  1400   59\n",
       "2       中和區  1712   793   850   42\n",
       "3       五股區   572   221   311   15\n",
       "4       八里區   188    72   116    5\n",
       "5       土城區  1212   619   592   31\n",
       "6       新店區  1662   785   860   43\n",
       "7       新莊區  2280   858  1415   55\n",
       "8       板橋區  3604  1407  2119   84\n",
       "9       林口區   972   356   573   24\n",
       "10      樹林區  1152   495   650   31\n",
       "11      永和區   976   446   514   25\n",
       "12      汐止區  1468   478   983   32\n",
       "13      泰山區   402   191   205   11\n",
       "14      淡水區   996   444   545   24\n",
       "15      深坑區    84    31    53    2\n",
       "16      瑞芳區   118    39    79    3\n",
       "17      蘆洲區  1080   396   674   25\n",
       "18      鶯歌區   632   249   325   15"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "area_table = pd.DataFrame(df.groupby(['sarea']).sum())\n",
    "area_table = area_table[['tot','sbi', 'bemp', 'act']]\n",
    "area_table['new_col'] = range(1, len(area_table) + 1)\n",
    "area_table = area_table.reset_index()\n",
    "area_table.rename(columns={'sarea': 'TOWNNAME'}, inplace=True)\n",
    "area_table = area_table[['TOWNNAME','tot','sbi', 'bemp', 'act']]\n",
    "area_table"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to plot the result on the map, we need to import geopandas and the map of Taiwan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geopandas as gp\n",
    "villages_shp = gp.read_file('/Users/David_Tsai/Downloads/map/TOWN_MOI_1080509.shp') #map of Taiwan\n",
    "newtaipei_shp = villages_shp.query('COUNTYNAME==\"新北市\"') #map of New Taipei City"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>TOWNID</th>\n",
       "      <th>TOWNCODE</th>\n",
       "      <th>COUNTYNAME</th>\n",
       "      <th>TOWNNAME</th>\n",
       "      <th>TOWNENG</th>\n",
       "      <th>COUNTYID</th>\n",
       "      <th>COUNTYCODE</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>F33</td>\n",
       "      <td>65000040</td>\n",
       "      <td>新北市</td>\n",
       "      <td>永和區</td>\n",
       "      <td>Yonghe District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.5123947940001 25.02174595900004,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>F07</td>\n",
       "      <td>65000060</td>\n",
       "      <td>新北市</td>\n",
       "      <td>新店區</td>\n",
       "      <td>Xindian District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.6092225440001 24.96401839600009,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>F19</td>\n",
       "      <td>65000130</td>\n",
       "      <td>新北市</td>\n",
       "      <td>土城區</td>\n",
       "      <td>Tucheng District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4671417850001 24.99298475300009,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>F04</td>\n",
       "      <td>65000140</td>\n",
       "      <td>新北市</td>\n",
       "      <td>蘆洲區</td>\n",
       "      <td>Luzhou District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.491140105 25.09476749800007, 121...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>F03</td>\n",
       "      <td>65000150</td>\n",
       "      <td>新北市</td>\n",
       "      <td>五股區</td>\n",
       "      <td>Wugu District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4590200780001 25.11272426200009,...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    TOWNID  TOWNCODE COUNTYNAME TOWNNAME           TOWNENG COUNTYID  \\\n",
       "213    F33  65000040        新北市      永和區   Yonghe District        F   \n",
       "214    F07  65000060        新北市      新店區  Xindian District        F   \n",
       "215    F19  65000130        新北市      土城區  Tucheng District        F   \n",
       "216    F04  65000140        新北市      蘆洲區   Luzhou District        F   \n",
       "217    F03  65000150        新北市      五股區     Wugu District        F   \n",
       "\n",
       "    COUNTYCODE                                           geometry  \n",
       "213      65000  POLYGON ((121.5123947940001 25.02174595900004,...  \n",
       "214      65000  POLYGON ((121.6092225440001 24.96401839600009,...  \n",
       "215      65000  POLYGON ((121.4671417850001 24.99298475300009,...  \n",
       "216      65000  POLYGON ((121.491140105 25.09476749800007, 121...  \n",
       "217      65000  POLYGON ((121.4590200780001 25.11272426200009,...  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newtaipei_shp.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Merge two tables together!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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",
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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>TOWNID</th>\n",
       "      <th>TOWNCODE</th>\n",
       "      <th>COUNTYNAME</th>\n",
       "      <th>TOWNNAME</th>\n",
       "      <th>TOWNENG</th>\n",
       "      <th>COUNTYID</th>\n",
       "      <th>COUNTYCODE</th>\n",
       "      <th>geometry</th>\n",
       "      <th>tot</th>\n",
       "      <th>sbi</th>\n",
       "      <th>bemp</th>\n",
       "      <th>act</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>F33</td>\n",
       "      <td>65000040</td>\n",
       "      <td>新北市</td>\n",
       "      <td>永和區</td>\n",
       "      <td>Yonghe District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.5123947940001 25.02174595900004,...</td>\n",
       "      <td>976</td>\n",
       "      <td>446</td>\n",
       "      <td>514</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>F07</td>\n",
       "      <td>65000060</td>\n",
       "      <td>新北市</td>\n",
       "      <td>新店區</td>\n",
       "      <td>Xindian District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.6092225440001 24.96401839600009,...</td>\n",
       "      <td>1662</td>\n",
       "      <td>785</td>\n",
       "      <td>860</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>F19</td>\n",
       "      <td>65000130</td>\n",
       "      <td>新北市</td>\n",
       "      <td>土城區</td>\n",
       "      <td>Tucheng District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4671417850001 24.99298475300009,...</td>\n",
       "      <td>1212</td>\n",
       "      <td>619</td>\n",
       "      <td>592</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>F04</td>\n",
       "      <td>65000140</td>\n",
       "      <td>新北市</td>\n",
       "      <td>蘆洲區</td>\n",
       "      <td>Luzhou District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.491140105 25.09476749800007, 121...</td>\n",
       "      <td>1080</td>\n",
       "      <td>396</td>\n",
       "      <td>674</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>F03</td>\n",
       "      <td>65000150</td>\n",
       "      <td>新北市</td>\n",
       "      <td>五股區</td>\n",
       "      <td>Wugu District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4590200780001 25.11272426200009,...</td>\n",
       "      <td>572</td>\n",
       "      <td>221</td>\n",
       "      <td>311</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>F27</td>\n",
       "      <td>65000100</td>\n",
       "      <td>新北市</td>\n",
       "      <td>淡水區</td>\n",
       "      <td>Danshui District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.450669045 25.24424598900004, 121...</td>\n",
       "      <td>996</td>\n",
       "      <td>444</td>\n",
       "      <td>545</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>F21</td>\n",
       "      <td>65000120</td>\n",
       "      <td>新北市</td>\n",
       "      <td>瑞芳區</td>\n",
       "      <td>Ruifang District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.823493854 25.13601305700007, 121...</td>\n",
       "      <td>118</td>\n",
       "      <td>39</td>\n",
       "      <td>79</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>F02</td>\n",
       "      <td>65000170</td>\n",
       "      <td>新北市</td>\n",
       "      <td>林口區</td>\n",
       "      <td>Linkou District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.3709369520001 25.12842823900007,...</td>\n",
       "      <td>972</td>\n",
       "      <td>356</td>\n",
       "      <td>573</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>F32</td>\n",
       "      <td>65000230</td>\n",
       "      <td>新北市</td>\n",
       "      <td>八里區</td>\n",
       "      <td>Bali District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4357293720001 25.16606711400004,...</td>\n",
       "      <td>188</td>\n",
       "      <td>72</td>\n",
       "      <td>116</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>F15</td>\n",
       "      <td>65000090</td>\n",
       "      <td>新北市</td>\n",
       "      <td>三峽區</td>\n",
       "      <td>Sanxia District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.407659574 24.95206866900008, 121...</td>\n",
       "      <td>676</td>\n",
       "      <td>323</td>\n",
       "      <td>349</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>F16</td>\n",
       "      <td>65000080</td>\n",
       "      <td>新北市</td>\n",
       "      <td>鶯歌區</td>\n",
       "      <td>Yingge District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.3426856970001 24.98231470000007,...</td>\n",
       "      <td>632</td>\n",
       "      <td>249</td>\n",
       "      <td>325</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>F18</td>\n",
       "      <td>65000030</td>\n",
       "      <td>新北市</td>\n",
       "      <td>中和區</td>\n",
       "      <td>Zhonghe District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4886834250001 25.01567630600005,...</td>\n",
       "      <td>1712</td>\n",
       "      <td>793</td>\n",
       "      <td>850</td>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>F17</td>\n",
       "      <td>65000070</td>\n",
       "      <td>新北市</td>\n",
       "      <td>樹林區</td>\n",
       "      <td>Shulin District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4125303750001 25.02032064300005,...</td>\n",
       "      <td>1152</td>\n",
       "      <td>495</td>\n",
       "      <td>650</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>F09</td>\n",
       "      <td>65000180</td>\n",
       "      <td>新北市</td>\n",
       "      <td>深坑區</td>\n",
       "      <td>Shenkeng District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.632440351 25.02562973300007, 121...</td>\n",
       "      <td>84</td>\n",
       "      <td>31</td>\n",
       "      <td>53</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>F14</td>\n",
       "      <td>65000010</td>\n",
       "      <td>新北市</td>\n",
       "      <td>板橋區</td>\n",
       "      <td>Banqiao District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4784192090001 25.03983647200005,...</td>\n",
       "      <td>3604</td>\n",
       "      <td>1407</td>\n",
       "      <td>2119</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>F01</td>\n",
       "      <td>65000050</td>\n",
       "      <td>新北市</td>\n",
       "      <td>新莊區</td>\n",
       "      <td>Xinzhuang District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.4620053440001 25.06882662500004,...</td>\n",
       "      <td>2280</td>\n",
       "      <td>858</td>\n",
       "      <td>1415</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>F06</td>\n",
       "      <td>65000160</td>\n",
       "      <td>新北市</td>\n",
       "      <td>泰山區</td>\n",
       "      <td>Taishan District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.3985040480001 25.07668094700006,...</td>\n",
       "      <td>402</td>\n",
       "      <td>191</td>\n",
       "      <td>205</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>F05</td>\n",
       "      <td>65000020</td>\n",
       "      <td>新北市</td>\n",
       "      <td>三重區</td>\n",
       "      <td>Sanzhong District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.491151565 25.09475731400005, 121...</td>\n",
       "      <td>2420</td>\n",
       "      <td>996</td>\n",
       "      <td>1400</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>F28</td>\n",
       "      <td>65000110</td>\n",
       "      <td>新北市</td>\n",
       "      <td>汐止區</td>\n",
       "      <td>Xizhi District</td>\n",
       "      <td>F</td>\n",
       "      <td>65000</td>\n",
       "      <td>POLYGON ((121.6267893060001 25.13970771600009,...</td>\n",
       "      <td>1468</td>\n",
       "      <td>478</td>\n",
       "      <td>983</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   TOWNID  TOWNCODE COUNTYNAME TOWNNAME             TOWNENG COUNTYID  \\\n",
       "0     F33  65000040        新北市      永和區     Yonghe District        F   \n",
       "1     F07  65000060        新北市      新店區    Xindian District        F   \n",
       "2     F19  65000130        新北市      土城區    Tucheng District        F   \n",
       "3     F04  65000140        新北市      蘆洲區     Luzhou District        F   \n",
       "4     F03  65000150        新北市      五股區       Wugu District        F   \n",
       "5     F27  65000100        新北市      淡水區    Danshui District        F   \n",
       "6     F21  65000120        新北市      瑞芳區    Ruifang District        F   \n",
       "7     F02  65000170        新北市      林口區     Linkou District        F   \n",
       "8     F32  65000230        新北市      八里區       Bali District        F   \n",
       "9     F15  65000090        新北市      三峽區     Sanxia District        F   \n",
       "10    F16  65000080        新北市      鶯歌區     Yingge District        F   \n",
       "11    F18  65000030        新北市      中和區    Zhonghe District        F   \n",
       "12    F17  65000070        新北市      樹林區     Shulin District        F   \n",
       "13    F09  65000180        新北市      深坑區   Shenkeng District        F   \n",
       "14    F14  65000010        新北市      板橋區    Banqiao District        F   \n",
       "15    F01  65000050        新北市      新莊區  Xinzhuang District        F   \n",
       "16    F06  65000160        新北市      泰山區    Taishan District        F   \n",
       "17    F05  65000020        新北市      三重區   Sanzhong District        F   \n",
       "18    F28  65000110        新北市      汐止區      Xizhi District        F   \n",
       "\n",
       "   COUNTYCODE                                           geometry   tot   sbi  \\\n",
       "0       65000  POLYGON ((121.5123947940001 25.02174595900004,...   976   446   \n",
       "1       65000  POLYGON ((121.6092225440001 24.96401839600009,...  1662   785   \n",
       "2       65000  POLYGON ((121.4671417850001 24.99298475300009,...  1212   619   \n",
       "3       65000  POLYGON ((121.491140105 25.09476749800007, 121...  1080   396   \n",
       "4       65000  POLYGON ((121.4590200780001 25.11272426200009,...   572   221   \n",
       "5       65000  POLYGON ((121.450669045 25.24424598900004, 121...   996   444   \n",
       "6       65000  POLYGON ((121.823493854 25.13601305700007, 121...   118    39   \n",
       "7       65000  POLYGON ((121.3709369520001 25.12842823900007,...   972   356   \n",
       "8       65000  POLYGON ((121.4357293720001 25.16606711400004,...   188    72   \n",
       "9       65000  POLYGON ((121.407659574 24.95206866900008, 121...   676   323   \n",
       "10      65000  POLYGON ((121.3426856970001 24.98231470000007,...   632   249   \n",
       "11      65000  POLYGON ((121.4886834250001 25.01567630600005,...  1712   793   \n",
       "12      65000  POLYGON ((121.4125303750001 25.02032064300005,...  1152   495   \n",
       "13      65000  POLYGON ((121.632440351 25.02562973300007, 121...    84    31   \n",
       "14      65000  POLYGON ((121.4784192090001 25.03983647200005,...  3604  1407   \n",
       "15      65000  POLYGON ((121.4620053440001 25.06882662500004,...  2280   858   \n",
       "16      65000  POLYGON ((121.3985040480001 25.07668094700006,...   402   191   \n",
       "17      65000  POLYGON ((121.491151565 25.09475731400005, 121...  2420   996   \n",
       "18      65000  POLYGON ((121.6267893060001 25.13970771600009,...  1468   478   \n",
       "\n",
       "    bemp  act  \n",
       "0    514   25  \n",
       "1    860   43  \n",
       "2    592   31  \n",
       "3    674   25  \n",
       "4    311   15  \n",
       "5    545   24  \n",
       "6     79    3  \n",
       "7    573   24  \n",
       "8    116    5  \n",
       "9    349   17  \n",
       "10   325   15  \n",
       "11   850   42  \n",
       "12   650   31  \n",
       "13    53    2  \n",
       "14  2119   84  \n",
       "15  1415   55  \n",
       "16   205   11  \n",
       "17  1400   59  \n",
       "18   983   32  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newtaipei_shp = newtaipei_shp.merge(area_table, left_on='TOWNNAME', right_on = 'TOWNNAME')\n",
    "newtaipei_shp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a363d8a58>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, figsize=(10, 8))\n",
    "newtaipei_shp.plot(column = 'tot', linewidth=0.8, ax=ax, legend = True, cmap ='Reds')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see that:\n",
    "1. There are some districts without YouBikes in New Taipei City (which are not shown on the map).\n",
    "2. There are more youbikes in the district near Taipei City. WE can't tell the reasons right away. \n",
    " However, I guess it's due to the transportation between two cities."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This data anlysis project ends here."
   ]
  }
 ],
 "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
}