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argenisleon/profiler.html

Created November 14, 2018 07:45
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profiler.html
<!doctype html>
<html class="no-js" lang="">
<head>
<meta charset="utf-8">
<meta http-equiv="x-ua-compatible" content="ie=edge">
<title></title>
<meta name="description" content="">
<meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
<link rel="manifest" href="site.webmanifest">
<link rel="apple-touch-icon" href="icon.png">
<!-- Place favicon.ico in the root directory -->
<link rel="stylesheet" href="css/normalize.css">
<link rel="stylesheet" href="css/main.css">
</head>
<body><style>
.main{
width:100%;
overflow:auto;
border-bottom:1px solid #eeeeee;
padding: 10px 0;
}
.panel_profiler{
margin-right:2%;
float:left;
padding-bottom:2%;
}
.title_profiler{
padding:20px;
background-color: #eeeeee
}
.info{
overflow: auto
}
</style>
<div class="title_profiler">
<h1>Overview</h1>
</div>
<div class="main">
<div class="panel_profiler">
<h2>Dataset info</h2>
<table>
<tbody>
<tr>
<td>Number of columns</td>
<td>10</td>
</tr>
<tr>
<td>Number of rows</td>
<td>45716</td>
</tr>
<tr>
<td>Total Missing (%)</td>
<td>0.49%</td>
</tr>
<tr>
<td>Total size in memory</td>
<td>24.5 MB</td>
</tr>
</tbody>
</table>
</div>
<div class="panel_profiler">
<h2>Column types</h2>
<table>
<tbody>
<tr>
<td>String</td>
<td>1</td>
</tr>
<tr>
<td>Numeric</td>
<td>0</td>
</tr>
<tr>
<td>Date</td>
<td>0</td>
</tr>
<tr>
<td>Bool</td>
<td>0</td>
</tr>
<tr>
<td>Array</td>
<td>0</td>
</tr>
<tr>
<td>Not available</td>
<td>0</td>
</tr>
</tbody>
</table>
</div>
</div><style>
.main{
width:100%;
overflow:auto;
border-bottom:1px solid #eeeeee;
padding: 10px 0;
}
.panel_profiler{
margin-right:2%;
float:left;
padding-bottom:2%;
}
.title_profiler{
padding:20px;
background-color: #eeeeee
}
.info{
overflow: auto
}
</style>
<div class="main">
<div class="info">
<div class="panel_profiler">
<div>
<h2>name</h2>
<div>categorical</div>
</div>
<table>
<tbody>
<tr>
<td>Unique</td>
<td> 45515</td>
</tr>
<tr>
<td>Unique (%)</td>
<td> 99.56</td>
</tr>
<tr>
<td>Missing</td>
<td>0.0</td>
</tr>
<tr>
<td>Missing (%)</td>
<td>0</td>
</tr>
</tbody>
</table>
<div>
<h3>
Datatypes
</h3>
</div>
<table>
<tbody>
<tr>
<td>
String
</td>
<td>
45716
</td>
</tr>
<tr>
<td>
Integer
</td>
<td>
0
</td>
</tr>
<tr>
<td>
Float
</td>
<td>
0
</td>
</tr>
<tr>
<td>
Bool
</td>
<td>
0
</td>
</tr>
<tr>
<td>
Date
</td>
<td>
0
</td>
</tr>
<tr>
<td>
Missing
</td>
<td>
0
</td>
</tr>
<tr>
<td>
Null
</td>
<td>
0
</td>
</tr>
</tbody>
</table>
</div>
<div class="panel_profiler">
<h3>Frequency</h3>
<table>
<tbody>
<th>Value</th>
<th>Count</th>
<th>Frecuency (%)</th>
<tr>
<td>Święcany</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Łowicz</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Österplana 064</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Österplana 063</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Österplana 062</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Österplana 061</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Österplana 060</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Österplana 059</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Österplana 058</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>Österplana 057</td>
<td>1</td>
<td>0.002%</td>
</tr>
<tr>
<td>"Missing"</td>
<td>0</td>
<td>0.0%</td>
</tr>
</tbody>
</table>
</div>
</div>
<table>
<tr>
<td>
<div>
<img 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">
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</td>
</tr>
<tr>
<td>
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FBwcrCVLlmRYZtasWQoJCVH58uUlSZUrV3ZHFAAAAAAoNNwygMXExMjX19dx2cfHRzExMRmWiYiIUEREhNq3b6+2bdtq5cqV7ogCAAAAAIWGW05BNMZk+pnNZstw+cqVK4qMjNS6det07Ngx3XnnndqzZ4/KlSuXYbmZM2dq5syZkqS4uDh3xAUAAAAAS7jlFTAfHx9FR0c7Lh87dkzVqlXLtEz37t11yy23yM/PT/Xr11dkZGSmWk8//bTCwsIUFhamSpUquSMuAAAAAFjCLQNYQECAIiMjdfjwYaWkpGjhwoUKCgrKsEyPHj20du1aSVJ8fLwiIiJUu3Ztd8QBAAAAgELBLQOYp6enZsyYoS5duqhhw4bq2bOnGjdurLFjx2rp0qWSpC5dusjb21uNGjXSvffeq/fff1/e3t7uiAMAAAAAhYJb3gMmSYGBgQoMDMzws/Hjxzv+b7PZNGXKFE2ZMsVdEQAAAACgUHHbFzEDAAAAADJiAAMAAAAAizCAAQAAAIBFGMAAAAAAwCIMYAAAAABgEQYwAAAAALAIAxgAAAAAWIQBDAAAAAAswgAGAAAAABZhAAMAAAAAizCAAQAAAIBFGMAAAAAAwCIMYAAAAABgEQYwAAAAALAIAxgAAAAAWIQBDAAAAAAswgAGAAAAABZhAAMAAAAAizCAAQAAAIBFGMAAAAAAwCIMYAAAAABgEQYwAAAAALAIAxgAAAAAWIQBDAAAAAAswgAGAAAAABZhAAMAAAAAizCAAQAAAIBFGMAAAAAAwCIMYAAAAABgEQYwAAAAALAIAxgAAAAAWIQBDAAAAAAs4rYBbOXKlapfv778/f01adKkbJf79ttvZbPZFBYW5q4oAAAAAFAouGUAS0tLU0hIiFasWKHw8HCFhoYqPDw803Lnz5/XRx99pDZt2rgjBgAAAAAUKm4ZwLZu3Sp/f3/Vrl1bXl5eCg4O1pIlSzItN2bMGI0aNUrFihVzRwwAAAAAKFTcMoDFxMTI19fXcdnHx0cxMTEZltmxY4eio6P1wAMPuCMCAAAAABQ6nu4oaozJ9DObzeb4/9WrVzV8+HDNmTMn11ozZ87UzJkzJUlxcXEuywgAAAAAVnPLK2A+Pj6Kjo52XD527JiqVavmuHz+/Hnt2bNH99xzj2rVqqXNmzcrKCgoyw/iePrppxUWFqawsDBVqlTJHXEBAAAAwBJuGcACAgIUGRmpw4cPKyUlRQsXLlRQUJDj+rJlyyo+Pl5RUVGKiopS27ZttXTpUrVu3dodcQAAAACgUHDLAObp6akZM2aoS5cuatiwoXr27KnGjRtr7NixWrp0qTt+JQAAAAAUem55D5gkBQYGKjAwMMPPxo8fn+Wy69atc1cMAAAAACg03PZFzAAAAACAjBjAAAAAAMAiDGAAAAAAYBEGMAAAAACwCAMYAAAAAFiEAQwAAAAALMIABgAAAAAWYQADAAAAAIswgAEAAACARRjAAAAAAMAiDGAAAAAAYBEGMAAAAACwCAMYAAAAAFiEAQwAAAAALMIABgAAAAAWYQADAAAAAIswgAEAAACARRjAAAAAAMAiDGAAAAAAYBEGMAAAAACwCAMYAAAAAFiEAQwAAAAALMIABgAAAAAWYQADAAAAAIswgAEAAACARRjAAAAAAMAiDGAAAAAAYBEGMAAAAACwCAMYAAAAAFiEAQwAAAAALMIABgAAAAAWYQADAAAAAIu4bQBbuXKl6tevL39/f02aNCnT9VOmTFGjRo3UrFkz3XfffTpy5Ii7ogAAAABAoeCWASwtLU0hISFasWKFwsPDFRoaqvDw8AzLtGjRQmFhYdq1a5ceffRRjRo1yh1RAAAAAKDQcMsAtnXrVvn7+6t27dry8vJScHCwlixZkmGZe++9VyVKlJAktW3bVseOHXNHFAAAAAAoNNwygMXExMjX19dx2cfHRzExMdku/8UXX6hbt27uiAIAAAAAhYanO4oaYzL9zGazZbns/PnzFRYWpt9++y3L62fOnKmZM2dKkuLi4lwXEgAAAAAs5pZXwHx8fBQdHe24fOzYMVWrVi3TcqtXr9bbb7+tpUuXqmjRolnWevrppxUWFqawsDBVqlTJHXEBAAAAwBJuGcACAgIUGRmpw4cPKyUlRQsXLlRQUFCGZXbs2KF///vfWrp0qSpXruyOGAAAAABQqLhlAPP09NSMGTPUpUsXNWzYUD179lTjxo01duxYLV26VJL00ksv6cKFC3rsscfUvHnzTAMaAAAAANxs3PIeMEkKDAxUYGBghp+NHz/e8f/Vq1e761cDAAAAQKHkti9iBgAAAABkxAAGAAAAABZhAAMAAAAAizCAAQAAAIBFGMAAAAAAwCIMYAAAAABgEQYwAAAAALAIAxgAAAAAWIQBDAAAAAAswgAGAAAAABZhAAMAAAAAizCAAQAAAIBFGMAAAAAAwCIMYAAAAABgEQYwAAAAALAIAxgAAAAAWIQBDAAAAAAswgAGAAAAABZhAAMAAAAAizCAAQAAAIBFGMAAAAAAwCIMYAAAAABgEQYwAAAAALAIAxgAAAAAWIQBDAAAAAAswgAGAAAAABZhAAMAAAAAizCAAQAAAIBFGMAAAAAAwCIMYAAAAABgEQYwAAAAALAIAxgAAAAAWMRtA9jKlStVv359+fv7a9KkSZmuv3z5snr16iV/f3+1adNGUVFR7ooCAAAAAIWCWwawtLQ0hYSEaMWKFQoPD1doaKjCw8MzLPPFF1+ofPnyOnjwoIYPH66XX37ZHVEAAAAAoNBwywC2detW+fv7q3bt2vLy8lJwcLCWLFmSYZklS5ZowIABkqRHH31Ua9askTHGHXEAAAAAoFBwywAWExMjX19fx2UfHx/FxMRku4ynp6fKli2r06dPuyMOAAAAABQKNuOGl50WLVqkVatW6fPPP5ckffXVV9q6daumT5/uWKZx48ZatWqVfHx8JEl16tTR1q1b5e3tnaHWzJkzNXPmTEnS/v371aBBA1fHdau4uDhVqlSp0NRxZS0yWVvHlbUKYyZX1iKTtXVcWaswZnJlLTJZW8eVtQpjJlfWIpO1dVxZi0yFS1RUlOLj43NeyLjBxo0bTefOnR2XJ06caCZOnJhhmc6dO5uNGzcaY4xJTU013t7e5urVq+6Ic121atWqUNVxZS0yWVvHlbUKYyZX1iKTtXVcWaswZnJlLTJZW8eVtQpjJlfWIpO1dVxZi0w3HrecghgQEKDIyEgdPnxYKSkpWrhwoYKCgjIsExQUpLlz50qSvv32W3Xo0EE2m80dcQAAAACgUPB0S1FPT82YMUNdunRRWlqannjiCTVu3Fhjx45V69atFRQUpCeffFL9+/eXv7+/KlSooIULF7ojCgAAAAAUGh7jxo0b547CdevW1XPPPafnn39ed911lyTp3nvvVf369SX9PaT17NlTw4YN01NPPaXy5cu7I0ah0KpVq0JVx5W1yGRtHVfWKoyZXFmLTNbWcWWtwpjJlbXIZG0dV9YqjJlcWYtM1tZxZS0y3Vjc8iEcAAAAAIDM3PIeMAAAAABAZgxghYD9RUhejAQAAABubgxg15kxxvHpjwkJCdc5DW50V69edfy/oAN9+tunr+uqmkB+pe/HgvSmO3occAVX9bhEn6PwcuUxy42GAew6Sj98zZ49W8HBwUpMTMxzHXsDX758ucANnNXOOT87bFfu5K9dp/yuo6vWzV21rly5orS0tHzXunr1qooUKaJDhw5p//79stlsBcpks9l09OhRnT17VkWK5G9XYf/9p0+f1qVLlwr0VROu6nN390F+uKrHpcLZ5/bbGGMc61aQTEWKFNHhw4cVFxenIkWK5Gt72Xv8xIkTOn/+fL573F5LkhITE5WamlrgOvb9QEHcCPvygnDn+hX0/lLQPndVj9truaLPXdXj6WsVtM9vhH15QRTmHi/o8Yr9dq46ZrkRMYAVQEHvaPaD0RkzZmjixIlKTEzMV017A3ft2lVr167N987RfmfYv3+/Xn/9db300ks6duxYnnfY9joRERGaNGmS3nnnHZ04cSLfmWw2m06ePKm9e/dK+nu75XU72TOFh4frzTff1FtvvaWjR4/m68HIXmvfvn2aOHGiJk+erOjo6ALV2rt3r/7973+rV69eOnjwYL63eWRkpG6//XYFBQXl+8HWGONYv8DAQP344495rpE+0/79+zVo0CBFRETkq46dK/rcVT2evlZB+9xVPZ4+kyv7PCIiQh9//LEWLlzoOBjMy4Nk+kwjRozQkCFDCrzNIyMjFRAQoF69eikpKSnPg729x8PDw/XII49ozZo1ec5ybaZ9+/Zp6NChOnr0aL5r2detV69eioqKKnCmiIgIvf/++5o2bZpOnTqV7/3KwYMH9cknn2jevHmKj4/PdyabzabTp0/r5MmT+apxba4DBw7oww8/1Pz58/M1qLiqx9PXKmifu6rHJdf1uSt7XHJNn7uqx9PXKmifF+YeL0zHK+lrueKY5Ub1z1lTN7DZbNq8ebPefPPNPN0u/Z3n+++/15w5cxQWFqY2bdooMjIyX1kuXLig8PBw/f7779qwYYNSUlLyXMO+o3788cdVqVIlpaamqk+fPnl+lsN+Z+/Tp48uXbqk48ePq2PHjjp9+nS+MzVv3lzTpk3T//73P0l5P0AtUqSIjh07pocffljFixfX+fPn1b17d61evVqXL1/Oc6a//vpL/fr1U9myZXXlyhV169ZNK1euzPMzevahYsCAAbr77rtVt25d9e3bV1euXJHk/JBv3+b9+vXTmDFj1KNHD61bt05S3p+dstlsOn/+vB5//HGNGDFC/fr1y9Pt02cKDw/XgAED9Nhjj+m2227LcH1+nukqaJ+7qsfttVzR567qcXstV/Z5ZGSk+vTpo4SEBB04cEAtWrTQ3r1783SAaq8zcOBA+fv7q1ixYgoJCcnzKwT2g8n9+/erX79+evrpp9WsWTP99ddfeaoj/b1tz5w5o+DgYD311FPq0aOH07e9lr0PBg4cqE6dOqlOnToZrs9rn+/fv1+LFy/WnDlzFBUVle8n5ez7g4sXL2rfvn0aNWpUnre5vTeDg4O1b98+bdy4UQMHDszXmRr2A7fGjRvr008/dfzd8sP+6lCPHj10/Phxbd26VW3atNG+ffvydL9xVY+nr1WQPndlj0uu63NX97hU8D53VY/ba7mizwtrjxe24xV7LVcds9yo3PY9YDc7++mDCQkJWr58ue677z55eXnl+ixV+tMOT548qVOnTmnEiBGqVKmSPv30UzVo0ED16tXTr7/+qiJFiqhcuXJOZUlJSdGmTZtUrFgx7dmzR7Vq1VLRokWVnJys4sWLO7VOFy9e1EsvvaRHHnlEQ4cOVZMmTbRjxw6VLFlSJUuWVJkyZRzP8ORWZ/jw4erZs6defPFFBQYGau/evSpXrlymHXdu0tLS9NFHH6lSpUpq1KiRdu7cqRIlSsjX1zfPzwiuX79ex44d00cffaROnTrplltu0Zw5c1S1alXVqVPHqXWzW7hwoby8vDRu3Dj961//0q5du/TZZ5+pefPmqlmzZp5qLViwQB4eHnr99dfVsWNHrV69WmfOnJGXl5cqVqzo1DNCp0+f1tChQzVgwAA988wz+vXXX7V+/Xo9+uij+Xrm9NKlS1q3bp0mTZokSRo3bpyWLFmiIkWKqHTp0ipZsmSuNS5fvqyQkBAlJSXpo48+kiSFhoZqy5Ytqly5ssqWLZun7SSpwH3uqh6X/h4GX3zxRT322GMF6vMrV65o+vTpqlixYoF7XJJ+//13l/X5zJkz5evrq/Hjx+uee+7Rhg0bNG3aNAUGBsrb29vpWp999pmqVaum1157Tc2bN9fWrVt15coVlSxZUuXKlXOqjv00qieeeELPPPOMhg8frrlz52rbtm3q0aNHnrdVbGysNm/erHfffVeSNHXqVK1YsULly5d3+n4n/d0HgwcPVrly5Rz3l59++kmRkZEqX768SpUqlec+j4qK0unTp7VlyxZ17NhRaWlpstlsTmc6e/asnnvuOfXt21fDhw9X+fLldejQIVWvXl2enp4qWbKkU5nOnj2rIUOGaNCgQXr11VfVtm1bbd68WQ0bNlTlypWdXh9JSk5O1rvvvquKFSs6XvGtUqWOZVHkAAAgAElEQVRKvr8DdNmyZbp8+bI+/fRTdevWTcnJyRo/frzuvPNOVa5c2elt7qoelwre567ucck1fe6OHpcK1ueu6nF7LVf0eWHtcVcer4SGhhb4eEWS4uPjFRIS4rJjlhsRA1g+2RvkypUrCg0NVc2aNXM96Eo/fH3wwQdatmyZ+vXrp1tvvVWSdPjwYTVp0kR//vmn3nzzTT322GMqW7Zspjr2O0tKSoo8PDxks9lUtmxZxcbGatiwYYqPj9c333yjyZMn64477lD16tWzzZS+VvHixdW0aVN17txZktSjRw+dO3dOqampeuONN9ShQwdVqlQpxzqpqakqWrSoihcvrh49esjT01M2m01Lly5VYmKi7r777ly3bfpMt9xyixo0aKDevXurSpUq2r17t/bv369ixYqpRo0aWW7ba+tcvnzZsUNeu3atatasqWrVqqlly5ZKTk7WO++8o06dOqlChQq5ZrL/nuPHjys6OlpNmzZVmTJldOrUKcXFxSk0NFTdu3dXmTJlnK519uxZbd++XSdPntRzzz2nEiVKyNPTU59//rn8/Pzk5+eXYx3p7z5s2bKlunbtKklq166dJk+erGLFiql58+ZOb3O7YsWKadGiRbpy5YreffddFS1aVLfeeqtWrlwpT09PNW3aNMdtLv39Zes1a9bUiRMntGHDBn300Uc6efKkoqKiNGnSJHXq1CnbfsoqkzFG5cqVy3Ofp69js9l022235avHr61ljFHJkiXz1efp6xQpUkT169fPV4+nr2W/vkSJEgXuc7vdu3crKSlJ9957r6S/HzTj4uL0ySefqG/fvipRooRTdQ4ePKjo6GgZY/Tcc88pNTVVZ86c0YQJE3Tfffc5vc0vXLig5s2b64EHHpAk3XHHHY4D6Nz2v9dmKlWqlJYsWaIqVapo5MiRjmeDZ8+erdq1a6tWrVpO1UpJSZGXl5euXLmiiIgIvfXWWwoPD9fu3bs1ZswY9ezZM8v9+LV17L//lltu0dGjRzVp0iRt2LBBCxcu1PTp03XPPffI29vbqUzJyclq0qSJ7r//fklSv379dPz4ccXGxmrkyJF65JFHnMp06dIleXl5KTg4WB4eHipRooS++uoreXh4KCAgINss2a1fjRo19Oyzz6py5cpaunSpzpw5o1tvvTXHnsyqliSlpqZq586duv3221WqVCn961//0rlz5zR8+HD17t1bpUuXzrLOtfejvXv3KjExUffdd58k53s8q1p//fWX45S6vPR5+jpJSUlq0aKF42+Xlx7PKlOZMmX0/fffq2rVqnnq8/R1UlNT5eXlpZSUFEVGRuapx6+tZf9/kSJFFB0dnac+T18nJSUl3z1+ba3k5GQVLVpUjz32mDw9PfPU59euW82aNTV06FDdeuutee7xa/92aWlp2r59u9q0aVOgHj9x4oSOHDmiZs2a5fl45dpaZ8+eVVhYmE6dOpWn45VrayUnJ6t169b5Pma5GTCA5cPevXs1YMAAtWrVSrVr11alSpU0bdo0denSJcedtb3xQkNDNXv2bE2fPt0xfEnSjh07NGzYMP3xxx/68ssvVbdu3Uw10p8X/PHHH6tu3bqOO8/8+fNVrVo1tWrVSq+//rq8vb0VFBSkSpUqZfmsRPpaM2bMUMOGDR0747/++ks+Pj5699131bFjRx05ckSLFi1Sz549szzotteZPn26mjVrpkaNGqlYsWKO9Y6Pj1daWpratWunHTt2OIa03NavXr16ql69ujw8POTt7S0fHx/t2bNH+/fvV506dRQVFaVLly5l2rllVads2bLatGmTYmNjVbduXZUqVUotWrTQ0aNHtXbtWseOPLtMkZGR2rx5s+rVq6cSJUro66+/1pYtW/T9999r9erVWrNmjY4eParY2Fi1bt3a6VqlSpXSuXPndOLECcXGxmr58uXq2LGjEhMTNXPmTPXp00ceHh7Z1tm4caOaNWumKlWqSPr7wbJYsWIyxujw4cO67777cnyG69pMfn5+8vDw0IULF7Rz506dP39e//nPf9S+fXtduXJFn3/+uXr16qVbbrkl2zqbNm1SvXr1VLVqVVWtWlVffPGFatWqpc8//1wPPfSQTpw4oW+//TbbZ7uuzeTv7+/o4f/+97+qWrWqU31+baaGDRuqYsWKkvLW41lt80aNGqlWrVp57vOstlPp0qXl6emZpx7PajvVrVtXRYoU0ebNmxUXFyd/f3+n+9y+DocOHVJcXJwqVqyo4sWL65133tH+/fv1448/as2aNfr111918OBBFS9ePMt9VFZ1SpUqpe3bt+vAgQM6d+6cVq1apfvvv1+nTp3S/Pnz1atXr2z7017r1KlT8vPzcwylV65cUfHixXXo0CElJSWpXbt2Ofa5vU58fLy8vb2VkpKivXv3avfu3fLy8tKMGTPUqVMnJSYmatasWerdu3em+921tWJjY1WtWjXVqFFDSUlJ+s9//qPGjRvryy+/1KOPPqojR45o69atjoE/p0z2g/PixYtr/vz5CggIUEBAgF577TWVLl1azz33nLy8vHL928XGxsrHx0eVK1dWkSJFtH37dlWpUkXTp09X165ddejQIW3atMlx4JNTHftBf/HixZWWluZ4n0z58uXVokULhYeHy8vLy3EfyK5WXFycbr31VpUtW1aenp6qVq2afHx8tGzZMp0+fVqtW7fW3r17dcstt2T7GHrt388Yo9DQUCUnJ6tNmzaSpPbt2+vIkSM6cuSI2rVrl6mG/f5y8uRJnT17VlevXpWfn5/Gjx+vffv25anHr62VlpamunXrasuWLdq3b5/TfZ6+TkJCgry8vNSgQQNJee/xazOdO3dO5cqV0549e7Rr1y6n+/zaTB4eHmrTpo0SExP12Wef5anHr8104cIFlSlTJs99fm0mSY6/TV57PKttfvvtt8vT0zNPfZ6+zpkzZ5SSkqLatWvLZrPlucev3U6XLl1S9erVNXfuXCUlJalt27aSnO/x+Ph4x3sHq1atqgULFmjTpk364Ycf8ny8Yq8lST4+PkpISFBMTIzi4uKcOl65ttbFixczPMF4+fJlFS9e3OljlpsF7wFzUvpzW+vVq6eAgAC999576t+/vyIiIuTj4+N478e156/u3r1bq1atclw+fPiwBgwYoGrVqikpKUnGGMcDgZ+fnxYsWKDGjRtnmcN+Dm6XLl1Uo0YN+fj4OK7r0aOHfvrpJ/Xs2VMvvPCCHnjgAc2cOVNnz551qlbVqlUd19WuXVuPPvqo4/Idd9yhGjVqZHmHuLZOxYoVHTvQ9M8MGWP0xx9/6KGHHtLu3budymR/VcO+/evVq6e+ffuqcuXKGjVqlFq3bp3lhzukr+Pr66vq1aurVKlSGjZsmLZt26bPP//ckSEgICDbA5v0g9zDDz/s2PHXqFFDU6dOVXBwsLp27arQ0FBJyvWVr6xq3XrrrXr22Wf1yiuvqEmTJo43OLdr106VK1d2nF+dXZ30f19jjGMwCggI0Ndff63169dne1pAVpnst+/SpYs8PT21Z88ex/o1adJEpUuXVnJyco51zpw5I0ny8PBQ8+bN9eWXX+rjjz92LN+qVSv5+PjkOOikz5T+jcdBQUFavnx5rn2eXSa7vPR4dtu8aNGikpzv8+wy2Wz/9+lPzvZ4VtvJZrM5DmK2bNmiL774wqk+t7t48aL69eun5s2ba9euXWrSpIlCQ0PVokULNW3aVPPmzXPkvXDhglN1du/erbp16+q9997TSy+95DiQkKQ777wzw5NQOdVq2bKlwsPDJf39zLCnp6e8vLzUuXNnTZkyRX/++WeOp7/Y69x2223au3evihUrpoEDB+rYsWMKCwvT77//LunvA5wqVark+P4Ie60WLVpoz549KleunLp27aopU6Y4TreVpAYNGmT7LPW1mcLDwx191K5dO82dO1f9+vXTyJEj1bhxY40YMcJxEJRbpvDwcHl6ekqSWrZsqSeeeMKxXLNmzXJ8ZSB9nb1796pUqVIZnrm+5ZZb5OHhoR07dig4OFgHDhzItVbz5s0d2/zKlSu6evWqAgICHB/oEBISovbt22vnzp1Obavdu3erevXqmjBhgj7//HNNmzbNcV/y9/fP8r076T+M4KGHHtLLL7+s4cOHq0iRIvr666/VsmVLNWnSxKkez6rWiBEjlJiYqPfff18vv/yyYyiUsu/za+u8+uqrevXVV7V9+3ZJylOPX1vrlVde0bhx43To0CENGjRIMTEx2rZtW659nlWmkSNHat++ferWrZs+/PBDTZs2zbF8Tj2eVaY33nhD27Ztk/T3PnfOnDm59nlWmV577TXHdspLj2e3fvZa9u2bW59ntW6jR4921DHGON3jWfXTq6++qtOnT2vixIn68ssvNXXqVKd73P6hKwMHDtRLL72kkydP6pNPPlFwcLACAwPzdLySvtaoUaO0f/9+DR06VK+88opuu+22XI9Xsqo1aNAgjR49Wr/99puk/3scdeaY5aZi4LRff/3VvPfeeyYsLMwYY8y5c+fM2rVrTdeuXU3VqlVNjx49Mt0mJSXFLF261MTGxpqjR48aY4x5++23zTPPPJNhuVWrVplt27aZEydO5Jpj8uTJ5rXXXjPGGJOWlmYOHTpkDh48aBISEoy/v7+ZOHGi47r9+/fnqdZff/1l9uzZk2GZTZs2mRYtWpiffvopT3X27t3ruH7evHnG39/ftGrVyixfvjzPmdLXMsaYWbNmmdKlS5sff/zR6TqRkZHm1KlT5ty5c2bo0KGmb9++pn///qZ27drm+++/z7bOkSNHTOPGjc20adMctc6fP28uX76cYblff/3VNGrUyKxduzZPtZKSksz58+dNWlqa6d+/vxk2bJgZO3asadasmfnhhx+cqnP16lVHnfTeeecd06tXL3Pp0qU8Zbpw4YIxxpikpCQzefJk88QTT5g+ffqYhg0bmu+++87pTBcvXjRJSUkZltu4caNp3rx5jv2U3fqlpqaamJgYU6dOHfPOO+848mbX59nVSUxMzLCcMz2eXS37tjLGmK+++irXPnemjjHO9Xh2vWmMMSdPnjRDhgwx/fr1c6rP7d555x3TuXNnU65cObNx48ZM12/YsME0aNDAbNq0yek6mzdvNsYYc+LECdO+fXvz+uuvmxkzZpjmzZubJUuWOJ2pfPnyZsuWLcaYv7eb3SuvvGJeffXVTPdJZ9YtKirKhISEmOeff94MHTrUNGzYMM/byb4trly54rh+69atpnnz5mbVqlV5Xrft27cbb29vM2HCBGOMMampqWbHjh1OZ0pfK71t27aZFi1a5CuT3fTp003z5s1Ny5Ytc+zNnGql/9tNnTrVlChRwixdutTpWun/fjt37jRdu3Y1Q4YMMcOHDzf+/v7Z5jp06JAJCAgw//3vf01CQoIZNGhQvns8q1r29UtMTDTt27c3o0ePzrXPr63zxBNPmK1bt2ZazpkezyqTfR3i4uJMSEiIGTZsWK59nlUd+304PWd6PKv1s2+nAwcOGG9vb/PWW28ZY3Luc2e3kzM97kwtZ/rc2UzO9HhOvXnw4EHTtWtX88wzz+Ta43/99Zdp2rSp+e6770xERIR5++23zXvvvZdpOWeOV7KqNXnyZGOMMQkJCaZPnz5m+PDhuR6vZFVr4sSJjlppaWmO5Zw5ZrlZMIDlwv5AsWXLFtO0aVPHQfuUKVNMXFycMebvRty9e7fp169fhuEl/YPMkSNHTHBwsFm8eLE5e/as8fPzM6+//rr566+/zNy5c42fn59jQMtNaGio44G5Q4cOpnfv3qZp06bm/fffz/J356VWnz59TPPmzc2LL75ojPn7YLlDhw6OB4/s6uZWZ+vWraZatWq5PvA7U+vq1avmySefNKGhoY7LWeXKbju9/fbbxhhjIiIizFdffeV4gMpu3ZYsWWI6dOhgNm3aZOLj483AgQNNr169zKBBg8zs2bONMX8fWPbp08d88803Oa5bdrUGDBhgli1bZuLj482MGTPM6NGjzS+//JJtrpwyzZkzx7HcH3/8kWl4dbbW448/br799ltjjDHnz583v/zyi9m1a1eBMu3cudN06dLFLF68ONs6OdXq37+/WblypWO53PrcmUwbNmxwqsed6YMtW7aY6tWr59jnzmRKS0szgwcPzrXHs6rVs2dP8/jjjzvW58CBA071eWpqqjHGmC+//NJs2rTJzJ8/31SoUMEsW7bMfPnll45a3bt3z7HPs6uzZMkSs2LFChMREWFGjhxpnnvuObNixYo8Z/L29jY//vijY5vbt8POnTvzlWnx4sUmKSnJ7N+/3yxcuDDLIcHZ7WTPtHHjRvOvf/0rx+EyuzqLFy82ixcvNmfOnMkxR163088//2zatm2b50z2OvYe+O6770yFChUc+6eCZEpMTDTBwcHm66+/dqxrVuub07b66aefzOnTp80vv/xipk6d6jigzKrOd999Z+bOneu43LRpU9O9e3czevRox88PHjyYa4/nVOvVV181P//8s4mOjjajRo0yzz77bI59nlOmefPmOX6eW4/nVOuVV14xy5YtM8b8/biXW587k2nLli259rgzmZKTk7PNkddMq1evzrXHc6tl//kPP/xgypcvn2OfO5Pp4sWLTvV4Tttp5cqVJikpyaxZsybXHl+0aJF5+eWXHZfXrFlj7rjjDpOYmGiuXr1q0tLSzPHjx01wcHCuPZ5Vrfbt25uzZ88aY4yJjIw006dPN6+99lqOxys51bI/GWq/XVhYWK7HLDcLBjAnbNu2zdx7773mjz/+MMb8fUcZMWKE+eCDD0xsbKxjuYcffjjLZzj+/PNPc+LECfP555+bQYMGmbVr15rTp0+boKAg88QTT5iOHTtmetXJzv7MQPpnVn/++WfTsWNHM3fuXMeAcfz4cePn5+e4k6d/RiGvtU6cOGHq1Kljli5das6dO2cOHjxojPm/O0he6/zwww8mNjbWbN++PUOd/NRatGiRMeb/HpDtO7O81PHz88vxGW57LfvvMMaY+fPnOwbBkSNHmp07d5pvv/3WdO/e3Rw4cMBcuXLFsVPKav2cqfXAAw+YI0eOuCRTTjuwvNQKCgoy4eHhLskUGRlpzp49aw4fPlyg7RQUFOS4v1zb53nNdOjQIZOQkJCpx/NTKyIiwpw4ccKxn7j2/uJsHfv2vrbH81rrwQcfNAcOHMjqT5ehVvr7jDHGrF+/3gwePNgYY8zYsWONzWZzvGJ//vx5x6v0Oe0Psqvz1FNPZcqf2/4gt0wFXbd///vf2dbJb6YTJ0447oN52U5jxozJkOnKlStO78tzyxQTE5PpCZT81Dl48KD5/fffM9TJa60hQ4YYY/4+Q+TcuXOOWvnJ9fTTT2faPtdmSt9v9rqvvvqqGTZsmNm/f79ZvHixCQwMNPv37zdJSUmZejwvtX744QfTpUsXEx0dneH2Od2Hc8pk/5sVZP1++OEH07Vr1zzty3PKFBERYWJjYzP1eF4zdevWzezevTvD7fKbKTIy0pw8eTLLJwnzs35RUVGZ+jyvdfbs2WPS0tJy7HFn/3YREREmK1nVOX78uElLSzOpqanm1KlTJjAw0DHo2s+0SJ8pr7Xsr05ltW/Kby57nn8SBjAnbNiwwRQvXtyMHj3a8bPFixebIUOGmEmTJplLly6Z6Oho06ZNG7N//35H4129etWcP3/etG7d2nz22WfGGGNmz55tBgwYkOFZlewaz14nPDzcjBw50owZM8axw3vttddMyZIlzYwZMxzLv/3229k+85OfWlm9nOyqOq5cP3dup9GjRzsetBYvXmzGjx/vWPbixYumZ8+e2R7kuqpWXuv06tWr0GXq2bNntqcJ5mf9snowyk+mffv2uWw7ZVWrMP7tsqo1duxY8+eff5pz586ZhIQEM2zYMBMVFWVuv/128+ijjxovLy/HYFnQOvYnYlxRK6vTlVxVJ7+17Keo34yZsqqT31pW98Hrr79udu7c6ThF9/jx445lL168aHr37p3rgJKXWs7sD/Jb53pnyu4JvpslU1ZPiN8o/bRr164Mb0W4dOmSufvuu01qaqpZv369GTp0qElISChwrd9++80MHTrUxMfHZ3rVK7+54uPjs9xeN6t/wLvc8s78/zf7JyUlKSkpSe3bt9ePP/6opUuX6tNPP5Ukde/eXR07dlRQUJCKFSsmHx8frVy5UvXr13e8eXD37t0qVaqUQkNDFRoaqo0bNyo4OFgdOnTQrFmztGjRIknK9g2sRYoU0fHjx3XffffJz89Pp06d0meffaaJEyfq7bff1rBhw/TFF19o27ZtWrZsmebNm5ft903kp1ZWHwXrqjquXD93bqe4uDh99tlneuutt9SpUyeNGTPGseyhQ4cUGRmZ5ZtOXVkrr3UiIiIKXabIyMhsP9QgP+uXmprqkkzXfmCOq2sVxr9dVrVOnjypOXPmaMqUKSpatKg8PDzk5+enhx9+WIsWLdLkyZMVHx/vkjpxcXEuyxQbG+u2OvmtldUXcd8smbL7kvEboQ9iY2M1Z84cvffeezp9+rSqVq3qeKz/66+/tH//fqf3B87Uymp/56o61zuTMVl/4e7NkslVda5HP82ePVvvvfee4wM7Ll++rMqVK2vevHl69tln9cADDzh1HJVbreeee04PPPCAvL29M31wVX5z5fQ1Gzel6zL2FWL2SX7x4sUmKCjIdOnSxfFm+vXr15uAgADz4YcfZriN/TQJ+21TU1PNrl27jM1mM08++aT5/vvvzeLFi80HH3xgUlNTzcmTJ82CBQsyPMuRnV27dpkBAwY46v/6669m+PDhjvcxTZ8+3bz11lvmwQcfzPEDBFxZ65+Yyf7Kmv185R9++ME0a9Ys1zeOu6oWmchkRa0XX3zRvPHGG2b16tXm559/znSbrM7vd1UdMpHJivUbNWpUhvvLggULTNOmTfN1f8lPLTKRyd2ZXnrpJTNmzBjH2yLuuOMOU6NGjVzfg19Ya92sGMCysGLFCtOqVStz7Ngx8+STT5ry5cubBQsWGGP+/uSYpk2bmiNHjmR7/qv952PHjjWvvPKKefTRR03Xrl1N9+7dHaddXHtue3bs7+2yf2iBMcasXbvWPP/88xk+bcf+SXM5vZHVVbX+qZlefPFFs2HDBmOMMTNmzHAMclbUIhOZrKj166+/mpdfftmsX7/e8bPc9lWuqkMmMrm6ljP3lylTpjg+oKKg9z1napGJTFZkGjlypKNOSEiI4/MBclJYa92s+CLmLKxfv16DBg1SRESEli9frhdffFEjRozQrbfeqoceekjBwcGqUqVKppddjTH6/fff9eCDD+ruu+92vPw8YcIEnTp1Sj/88IPWr1+vJ598UkWKFMn1S+auXr2qMmXKqHLlylq6dKm8vb1Vs2ZN+fr66tdff9WOHTvUrVs3SX9/X4jNZsvxCxpdUeufnGn16tXavXu3unXrpttvv11169bN9C3x7qhFJjJZVatGjRpatWqV9u7d6/gS05y+j8VVdchEJqvW79r7S7t27VSvXj2X3Pdyq0UmMlmV6ZdfftHOnTsVGBiowMBANW7cON+ZrmetmxkDmOT442/fvl0eHh664447VLp0ab322muaNGmSHnjgAW3btk3ff/+9evXqleE81fSNY7PZVLNmTdlsNi1fvlySNHfuXKWlpemll15SYGCg+vbtq3LlyjnVbPZlvL29de7cOS1fvlyenp5q0KCBbDab/vjjD3Xp0kW33HJLrvVcVeufniksLEydO3fOdZBzZS0ykcnKWkWKFFFYWJjjPpMTV9UhE5msXD+bzaZt27a57L7nbC0ykcnKTH/88Yc6derkOPYp6HHU9ah1U7PqpbbCbuXKlcbPz89s3brV8VJvSEiImTJlilm9erUZMGBAll9saTdr1izzwgsvmFGjRpnjx4+bmJgYs2DBAtO2bVtTsWJFs3r16jxnSv+Sc3R0tPnqq69M3bp1zZAhQ0zFihWd+gJTV9ciE+tHphs7kytrkYlMhbUWmchEphv7PnyzsxmTzUfH/IMcPXpUDz/8sKZMmaK77rrL8ekz8+bNU1hYmFatWqUPP/xQ999/f5a3/+KLLzRr1iy99NJL+uOPPzR79mytW7dO9evX186dO/XWW29p2rRpql69eo45TBYvw6ampmZ4pi8qKkpRUVEqU6aMWrZsme1Lt66qRSbWj0w3dqabff3IdONmutnXj0xkutkzubrWPwkDmKS4uDgNHz5c8+fPlyQlJyerWLFiSkhIUIUKFXTs2DH5+PhkuE1aWpo8PDwkSaNGjVKbNm30yCOPSJI+/PBDfffdd1q6dKkqVKiQqRGzYm/Gn376SZs3b9alS5c0YcIEFStWzHH7q1ev5nr+vCtrkYn1I9ONnelmXz8y3biZbvb1IxOZbvZMrq71j2P+gewvj9q/FO7y5cumZcuWZtKkSY5l1q5da5577jlz+fLlDLdNfxrizp07jTHGjBgxwowaNcrx84sXL5onnnjC8Y3jzvrxxx9Ny5YtzbZt28ztt99u2rZt6/jUvmu/Ld2qWmSyvhaZyFRYa5GJTIW1FpnIRCbrM7m61j/JP24kNf9/Wl+5cqUee+wxvfrqq5o7d66+//57zZ49W88//7xmzZqlF154QR06dJCXl1eG248dO1YtW7aUJK1du1aSFBISonnz5undd9/VxYsX9f3332v37t1KTk52OtelS5e0bNkyzZ07V8eOHVOpUqVUpUoVtWjRQpcuXZKnp6fltcjE+pHpxs50s68fmW7cTDf7+pGJTDd7JlfX+se53hOgu2X13Qnr1683zZs3N9u2bTPPP/+8ueeee4wxxkRFRZmRI0eaN9980/HFcFnd/v777ze33XabeeSRR8y5c+eMMcZERESYbt26md69e5v27dubPXv25DlbQkKCiYyMNAEBAebUqVPGGGMqVu6KEb0AAA9HSURBVKxomjdvbq5evZrjd0q4qhaZWD8y3diZbvb1I9ONm+lmXz8ykelmz+TqWv9kN/1oarPZdOLECR06dEjt27eXzWbT2bNn9eGHH+r8+fPauHGjFi1aJEkqWrSo3n///Uy3t7Ofx/rjjz9qwIABWr9+vcqUKSNJqlu3ru6//36lpaVp6tSpqly5slPZfv/9d50+fVoVKlTQXXfdpeTkZDVs2FAXL17Uli1bNGTIEHXu3DnXNyu6qhaZWD8y3diZbvb1I9ONm+lmXz8ykelmz+TqWv9o13sCtMKCBQvMvn37TGJiorl06ZJZtmyZqVy5smnZsqU5e/asMcaYn3/+2Tz77LO51kpLSzPGGLNmzRpTqlQp07lzZ8fvqFixotm7d6/TuX7//XdTrVo1M2LECNO0aVPz6aefGmOMGTx4sBk0aJCpWrWq4+Prc3sGwVW1yMT6kenGznSzrx+ZbtxMN/v6kYlMN3smV9f6J/tHDGDGGJOYmGj69u1rFi9ebFJTU83LL79sOnbsaBISEszq1auNv7+/ef75583GjRtNVFRUrvUSEhLM5s2bTadOnUzJkiVN7dq1HR/K4YywsDDz8ssvm59//tkYY8zGjRuNv7+/+eabb4wxxhw4cMD88ccfltYiE+tHphs7082+fmS6cTPd7OtHJjLd7JlcXeuf7h8xgG3atMmkpKSY//znP2bQoEHmxx9/NIcPHzajR482d999t+natauZN2+eWbZsmencubM5ceJEnuo/9dRTZseOHU4ta38F7eX/1979xlRdvw0cvw5iHRZTqRFIRVhJx3TQYm1oqyQYzYnwQGtTIcvNZqwta4h/1khb9ofVqjW3HiizB0ROKQqiCcjIhGnMEW62iDG2iDwDIf4l/7l+D7zhnre/O8m+53v4fHy/Hul3dvm+NnpwcfCcXbs0Pj5ejxw5omNjY6p65Qs5KipKDx486OosmtiPJrObbN+PJnObbN+PJppsb3J6Fq6Yt2/fvn3B/jHIQNH/ecfDt956S44fPy4HDhyQzs5Oqa2tlaioKHnxxRclJydHNmzYIElJSXLnnXfK+vXrJTIyclbzJycnJSQkRNatWyfR0dGzahkYGBCv1ytpaWkyODgodXV1kpiYKHfccYfExsbKqlWr5Pbbb5e4uLiAz6KJ/Wgyu8n2/Wgyt8n2/WiiyfYmp2fhalYfYM3NzRIdHS3JycnS0tIiHo9Hnn32WWlvb5eKigq59dZbZenSpRIaGioej0e8Xq+EhYXNev5sP1hu+s07KisrpaCgQH799VcJCQmR7Oxs+fnnn+X48ePi8/kkMjJSYmNjJS4u7v/9lHCnZtHEfjSZ3WT7fjSZ22T7fjTRZHuT07PwX9zQ62ZzyMTExDXPpqamtLe3VyMjI3X9+vVaVlamu3fv1vfff3/mzxQWFur58+cD0jT9jw6nX7JVVa2pqdEVK1ZoU1OTpqena3p6uhYXF6uq6s6dOzUrK2vmg6EDMYsm9qPJ7Cbb96PJ3Cbb96OJJtubnJ6F6zP6begnJydl06ZN8tFHH0loaKgMDg7KfffdJ319fRIRESGvvfaaNDY2isfjkaamJvnpp58kLCxMcnNzZefOnQHr8ng84vf7pbq6WlJSUuSuu+6Ss2fPSnFxsfj9funu7paNGzfK559/LvPmzZPCwkJpbW2V8PDwgM2iif1oMrvJ9v1oMrfJ9v1oosn2JqdnYRaCfQH+W42NjXrixAl96KGH9NixY/rLL79oZmamFhUVaWdnpz722GNaV1enDQ0NGh8frytXrlS/3x/wt8asrq7WzMxMPXTokA4MDOj4+Lj29fVpRkaGdnV1qapqcnKybtmyRTs7O12ZRRP70WR2k+370WRuk+370UST7U1Oz8LfM/oVMBGR0dFReeWVVyQ/P182bNggIyMjcuDAAdmyZYvccsst8tRTT0lRUZF89tlnUlJSIvPnz5eoqKiAd6Wlpcn4+LgUFxfL5OSkZGVlyW233SZtbW1y7tw5Wbp0qUREREheXp7ExMS4Mosm9qPJ7Cbb96PJ3Cbb96OJJtubnJ6F6wj2BXijpl/BKioq0ldffXXm2blz57S8vFw/+OAD3bFjh77xxhs6f/58raysdLVrWl1dnW7cuFE//fRTnZiY0NLSUl2+fLkmJibqV1995cosmtiPJrObbN+PJnObbN+PJppsb3J6FmbHo6oa7CPw3/j+++9l7969UlBQIEePHpXh4WFpbm6W9PR0+eOPP+Ttt9+WPXv2yPbt2yU1NdWVpqqqKqmqqpIlS5ZIVlaWXLp0Sd577z1JSUmRnJwc+euvv+Ty5csSGxt73XeMcWoWTexHk9lNtu9Hk7lNtu9HE022Nzk9C9c3u/dRn8MeffRReeaZZ2TXrl0yMDAgubm5Ul9fLy+88IKEh4fLAw88IMeOHZPU1FQJ5K05PfvChQuyf/9+WbRokXR0dEhGRoZ4vV7Jy8uT7777To4cOSIRERESGxsrIvJfv4CdmkUT+9FkdpPt+9FkbpPt+9FEk+1NTs/CP3QDr5rNST09PVf9vq6uTletWqWdnZ0Bf8ONaQ0NDbp8+XL94osvZp4dPnxY165dqxMTE1peXq5NTU2uzqKJ/Wgyu8n2/Wgyt8n2/WiiyfYmp2dh9qw5wKaNjY3pt99+qwkJCVpRUeHa39vU1KStra26ePFiXbNmzczz7u5u3bRp0zUHohuzaGI/msxucnIWTTTN1Vk00UST2f8P45+z6gAbGxvT06dPa2pqqn7zzTeu/b3Nzc2alJSkly5d0v7+fo2JidHc3FwdGRnRxsZGvf/++7WlpcXVWTSxH01mN9m+H03mNtm+H0002d7k9Cz8c1YdYKpXjrCLFy+q6rXv6hIILS0tumzZMj18+PDMs56eHr3nnnvU5/NpQUGB1tTUuDqLJvajyewm2/ejydwm2/ejiSbbm5yehRtj3QHmtuHhYc3KylKfz6cTExMzz/v6+nTFihX6/PPPzzy73kHo1Cya2I8ms5ts348mc5ts348mmmxvcnoWbgwH2D80/YXY3Nys1dXV6vf7tb+/X7dt26Zr167V0dHRmT/7559/6sKFCzU/Pz+gs2hiP5rMbrJ9P5rMbbJ9P5posr3J6VlwBgfYDSgrK9OHH35YX375ZU1JSdGqqiodGhrSl156SZ988smrvpD7+vq0tbU14LNoYj+azG6yfT+azG2yfT+aaLK9yelZ+Pc4wGZp+rsHFy9e1HXr1ml/f79++eWXmpiYqN3d3aqqOjg4qFu3btUff/xRVfWql3UDMYsm9qPJ7Cbb96PJ3Cbb96OJJtubnJ4FZ3GAXcfly5dnft3V1aUTExOal5ene/bs0ZUrV2pbW5uqqp48eVJ7enr+9mdlnZpFE/vRZHaT7fvRZG6T7fvRRJPtTU7PQmBwgP2NqakpLS8v1/3792ttba1mZ2dre3u7vv7665qYmKgNDQ2qeuVDnx988EE9f/58wGfRxH40md1k+340mdtk+3400WR7k9OzEDgcYNcxNTWlSUlJumDBAj179qyqXvmOwbZt2/S5557T3bt3q8/n0/Lyctdm0cR+NJndZPt+NJnbZPt+NNFke5PTsxAY8/bt27dPcA1VFY/HI8PDw9LU1CRer1d+//13ycjIkCVLlojP55OYmBjxer2ydetWSU1NnflvAjWLJvajyewm2/ejydwm2/ejiSbbm5yehQC7sbvNbtM/C/v111/rwYMHta+vT8fHxzUrK0uzs7NVVbWtrU3PnDnj2iya2I8ms5ts348mc5ts348mmmxvcnoWAo8DTFUnJyeveVZZWakJCQl68uTJmWd+v18zMzP1iSee0ISEBD116lTAZtHEfjSZ3WT7fjSZ22T7fjTRZHuT07Pgvpv6AJuamtKjR49qV1fXVc8nJyc1JydHS0tLdWhoSCsqKjQ/P1+rq6t1dHRUP/nkE/3hhx8CMosm9qPJ7Cbb96PJ3Cbb96OJJtubnJ6F4PGoqgb7xyCD5fTp07JgwQKJioqS0tJSCQ8Pl0WLFklmZqa8+eab0t7eLm1tbZKcnCwdHR0SHR0tH374YUBn0cR+NJndZPt+NJnbZPt+NNFke5PTsxA8ocEOCJZTp07JwoULJTw8XB5//HF5+umnxev1SklJiVy4cEHWrFkjvb29snjxYklISJAzZ87Ijh07xO/3S1RU1FX/YNGpWTSxH01mN9m+H03mNtm+H0002d7k9CwEWbBfggumkZERXb16tR46dGjmWUdHh6alpWlBQcHMsxMnTqjP59OKioqAz6KJ/Wgyu8n2/Wgyt8n2/WiiyfYmp2cheG7qA2x4eFg3b96sQ0NDM79XVf3tt9/07rvv1pKSEh0dHdV3331Xq6qqXJlFE/vRZHaT7fvRZG6T7fvRRJPtTU7PQvDc1AdYb2+vLlu27KrvDoyOjqqq6jvvvKOFhYWq+r9f3G7Moon9aDK7yfb9aDK3yfb9aKLJ9ianZyF4buoPYg4LC5PQ0FCprq6We++9V6Kjo0VEJCQkROrr62V4eFhWr14tISEh1/25Wadm0cR+NJndZPt+NJnbZPt+NNFke5PTsxBEwb4Ag62rq0v37t2r27dv15qaGlVVra+v17i4OK2trQ3KLJrcn0UTTXN1Fk00zdVZNNFEk/tNTs9CcNz0B5jqlQ+p+/jjjzU+Pl43b96sjzzyiJaVlQV1Fk3uz6KJprk6iyaa5uosmmiiyfxZcN9N/Tlg/5ff7xcRkZGREYmLixNVveGXb52aRZP7s2iiaa7OoommuTqLJppoMn8W3MMBBgAAAAAuCQl2AAAAAADcLDjAAAAAAMAlHGAAAAAA4BIOMAAAAABwCQcYAAAAALiEAwwAAAAAXMIBBgAAAAAu4QADAAAAAJdwgAEAAACASzjAAAAAAMAlHGAAAAAA4BIOMAAAAABwCQcYAAAAALiEAwwAAAAAXMIBBgAAAAAu4QADAAAAAJdwgAEAAACASzjAAAAAAMAlHGAAAAAA4BIOMAAAAABwCQcYAAAAALiEAwwAAAAAXMIBBgAAAAAu4QADAAAAAJdwgAEAAACASzjAAAAAAMAlHGAAAAAA4BIOMAAAAABwCQcYAAAAALiEAwwAAAAAXMIBBgAAAAAu4QADAAAAAJdwgAEAAACASzjAAAAAAMAlHGAAAAAA4BIOMAAAAABwCQcYAAAAALiEAwwAAAAAXMIBBgAAAAAu+Q90bkQaXKxHrgAAAABJRU5ErkJggg==">
</div>
</td>
</tr>
</table>
</div><style>
.data_type {
font-size: 0.8em;
font-weight: normal;
}
.column_name {
font-size: 1.2em;
}
.info_items {
margin: 10px 0;
font-size: 0.8em;
}
.optimus_table tr:nth-child(even) {
background-color: #f2f2f2 !important;
}
.optimus_table tr:nth-child(odd) {
background-color: #ffffff !important;
}
.optimus_table thead {
border-bottom: 1px solid black;
}
.optimus_table{
font-size: 12px;
}
</style>
<div class="info_items">Viewing 10 of 45716 rows / 10 columns</div>
<div class="info_items">32 partition(s)</div>
<table class="optimus_table">
<thead>
<tr>
<th>
<div class="column_name">name</div>
<div class="data_type">1 (string)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">id</div>
<div class="data_type">2 (int)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">nametype</div>
<div class="data_type">3 (string)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">recclass</div>
<div class="data_type">4 (string)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">mass (g)</div>
<div class="data_type">5 (double)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">fall</div>
<div class="data_type">6 (string)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">year</div>
<div class="data_type">7 (string)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">reclat</div>
<div class="data_type">8 (double)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">reclong</div>
<div class="data_type">9 (double)</div>
<div class="data_type">
nullable
</div>
</th>
<th>
<div class="column_name">GeoLocation</div>
<div class="data_type">10 (string)</div>
<div class="data_type">
nullable
</div>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
Acfer⸱232
</td>
<td>
240
</td>
<td>
Valid
</td>
<td>
H5
</td>
<td>
725.0
</td>
<td>
Found
</td>
<td>
01/01/1991⸱12:00:00⸱AM
</td>
<td>
27.73944
</td>
<td>
4.32833
</td>
<td>
(27.739440,⸱4.328330)
</td>
</tr>
<tr>
<td>
Elephant⸱Moraine⸱90232
</td>
<td>
8641
</td>
<td>
Valid
</td>
<td>
L6
</td>
<td>
16.9
</td>
<td>
Found
</td>
<td>
01/01/1990⸱12:00:00⸱AM
</td>
<td>
-76.28795
</td>
<td>
156.46841
</td>
<td>
(-76.287950,⸱156.468410)
</td>
</tr>
<tr>
<td>
Grove⸱Mountains⸱020090
</td>
<td>
30681
</td>
<td>
Valid
</td>
<td>
Martian⸱(shergottite)
</td>
<td>
7.5
</td>
<td>
Found
</td>
<td>
01/01/2003⸱12:00:00⸱AM
</td>
<td>
-72.99944
</td>
<td>
75.26111
</td>
<td>
(-72.999440,⸱75.261110)
</td>
</tr>
<tr>
<td>
Northwest⸱Africa⸱891
</td>
<td>
31912
</td>
<td>
Valid
</td>
<td>
H4
</td>
<td>
70.8
</td>
<td>
Found
</td>
<td>
01/01/2001⸱12:00:00⸱AM
</td>
<td>
None
</td>
<td>
None
</td>
<td>
None
</td>
</tr>
<tr>
<td>
Queen⸱Alexandra⸱Range⸱93098
</td>
<td>
19187
</td>
<td>
Valid
</td>
<td>
H6
</td>
<td>
1.2
</td>
<td>
Found
</td>
<td>
01/01/1993⸱12:00:00⸱AM
</td>
<td>
-84.5757
</td>
<td>
162.56524
</td>
<td>
(-84.575700,⸱162.565240)
</td>
</tr>
<tr>
<td>
Queen⸱Alexandra⸱Range⸱94691
</td>
<td>
20322
</td>
<td>
Valid
</td>
<td>
H6
</td>
<td>
9.6
</td>
<td>
Found
</td>
<td>
01/01/1994⸱12:00:00⸱AM
</td>
<td>
-84.0
</td>
<td>
168.0
</td>
<td>
(-84.000000,⸱168.000000)
</td>
</tr>
<tr>
<td>
Meteorite⸱Hills⸱00977
</td>
<td>
16211
</td>
<td>
Valid
</td>
<td>
H5
</td>
<td>
13.2
</td>
<td>
Found
</td>
<td>
01/01/2000⸱12:00:00⸱AM
</td>
<td>
-79.68333
</td>
<td>
159.75
</td>
<td>
(-79.683330,⸱159.750000)
</td>
</tr>
<tr>
<td>
Grove⸱Mountains⸱020114
</td>
<td>
46531
</td>
<td>
Valid
</td>
<td>
L3
</td>
<td>
1.0
</td>
<td>
Found
</td>
<td>
01/01/2003⸱12:00:00⸱AM
</td>
<td>
-72.98194
</td>
<td>
75.25167
</td>
<td>
(-72.981940,⸱75.251670)
</td>
</tr>
<tr>
<td>
Pecora⸱Escarpment⸱91483
</td>
<td>
18774
</td>
<td>
Valid
</td>
<td>
H5
</td>
<td>
5.5
</td>
<td>
Found
</td>
<td>
01/01/1991⸱12:00:00⸱AM
</td>
<td>
-85.55819
</td>
<td>
-68.31586
</td>
<td>
(-85.558190,⸱-68.315860)
</td>
</tr>
<tr>
<td>
Ramlat⸱as⸱Sahmah⸱390
</td>
<td>
55656
</td>
<td>
Valid
</td>
<td>
H3.8-6
</td>
<td>
0.69
</td>
<td>
Found
</td>
<td>
01/01/2010⸱12:00:00⸱AM
</td>
<td>
20.0949
</td>
<td>
55.69318
</td>
<td>
(20.094900,⸱55.693180)
</td>
</tr>
</tbody>
</table>
<div class="info_items">Viewing 10 of 45716 rows / 10 columns</div>
<div class="info_items">32 partition(s)</div>
</body></html>
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