examples/new-api-profiler.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\"..\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Now you can get extra information for the profiler if you activate pass verbose= True to optimus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Create optimus\n",
    "from optimus import Optimus\n",
    "op = Optimus(master=\"local[*]\", app_name = \"optimus\" , checkpoint= True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = op.load.csv(\"data/Meteorite_Landings.csv\").h_repartition()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    .data_type {\n",
       "        font-size: 0.8em;\n",
       "        font-weight: normal;\n",
       "    }\n",
       "\n",
       "    .column_name {\n",
       "        font-size: 1.2em;\n",
       "    }\n",
       "\n",
       "    .info_items {\n",
       "        margin: 10px 0;\n",
       "        font-size: 0.8em;\n",
       "    }\n",
       "\n",
       "    .optimus_table tr:nth-child(even) {\n",
       "        background-color: #f2f2f2 !important;\n",
       "    }\n",
       "\n",
       "    .optimus_table tr:nth-child(odd) {\n",
       "        background-color: #ffffff !important;\n",
       "    }\n",
       "\n",
       "    .optimus_table thead {\n",
       "        border-bottom: 1px solid black;\n",
       "    }\n",
       "    .optimus_table{\n",
       "        font-size: 12px;\n",
       "    }\n",
       "\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "<div class=\"info_items\">Viewing 10 of 45716 rows / 10 columns</div>\n",
       "<div class=\"info_items\">32 partition(s)</div>\n",
       "\n",
       "<table class=\"optimus_table\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">name</div>\n",
       "            <div class=\"data_type\">1 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">id</div>\n",
       "            <div class=\"data_type\">2 (int)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">nametype</div>\n",
       "            <div class=\"data_type\">3 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">recclass</div>\n",
       "            <div class=\"data_type\">4 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">mass (g)</div>\n",
       "            <div class=\"data_type\">5 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">fall</div>\n",
       "            <div class=\"data_type\">6 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">year</div>\n",
       "            <div class=\"data_type\">7 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">reclat</div>\n",
       "            <div class=\"data_type\">8 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">reclong</div>\n",
       "            <div class=\"data_type\">9 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">GeoLocation</div>\n",
       "            <div class=\"data_type\">10 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "    </tr>\n",
       "\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Acfer⸱232'>Acfer⸱232</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='240'>240</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H5'>H5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='725.0'>725.0</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1991⸱12:00:00⸱AM'>01/01/1991⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='27.73944'>27.73944</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='4.32833'>4.32833</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(27.739440,⸱4.328330)'>(27.739440,⸱4.328330)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Elephant⸱Moraine⸱90232'>Elephant⸱Moraine⸱90232</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='8641'>8641</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='L6'>L6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='16.9'>16.9</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1990⸱12:00:00⸱AM'>01/01/1990⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-76.28795'>-76.28795</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='156.46841'>156.46841</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-76.287950,⸱156.468410)'>(-76.287950,⸱156.468410)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Grove⸱Mountains⸱020090'>Grove⸱Mountains⸱020090</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='30681'>30681</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Martian⸱(shergottite)'>Martian⸱(shergottite)</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='7.5'>7.5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2003⸱12:00:00⸱AM'>01/01/2003⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-72.99944'>-72.99944</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='75.26111'>75.26111</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-72.999440,⸱75.261110)'>(-72.999440,⸱75.261110)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Northwest⸱Africa⸱891'>Northwest⸱Africa⸱891</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='31912'>31912</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H4'>H4</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='70.8'>70.8</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2001⸱12:00:00⸱AM'>01/01/2001⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='None'>None</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='None'>None</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='None'>None</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Queen⸱Alexandra⸱Range⸱93098'>Queen⸱Alexandra⸱Range⸱93098</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='19187'>19187</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H6'>H6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='1.2'>1.2</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1993⸱12:00:00⸱AM'>01/01/1993⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-84.5757'>-84.5757</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='162.56524'>162.56524</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-84.575700,⸱162.565240)'>(-84.575700,⸱162.565240)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Queen⸱Alexandra⸱Range⸱94691'>Queen⸱Alexandra⸱Range⸱94691</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='20322'>20322</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H6'>H6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='9.6'>9.6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1994⸱12:00:00⸱AM'>01/01/1994⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-84.0'>-84.0</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='168.0'>168.0</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-84.000000,⸱168.000000)'>(-84.000000,⸱168.000000)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Meteorite⸱Hills⸱00977'>Meteorite⸱Hills⸱00977</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='16211'>16211</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H5'>H5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='13.2'>13.2</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2000⸱12:00:00⸱AM'>01/01/2000⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-79.68333'>-79.68333</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='159.75'>159.75</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-79.683330,⸱159.750000)'>(-79.683330,⸱159.750000)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Grove⸱Mountains⸱020114'>Grove⸱Mountains⸱020114</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='46531'>46531</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='L3'>L3</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='1.0'>1.0</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2003⸱12:00:00⸱AM'>01/01/2003⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-72.98194'>-72.98194</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='75.25167'>75.25167</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-72.981940,⸱75.251670)'>(-72.981940,⸱75.251670)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Pecora⸱Escarpment⸱91483'>Pecora⸱Escarpment⸱91483</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='18774'>18774</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H5'>H5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='5.5'>5.5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1991⸱12:00:00⸱AM'>01/01/1991⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-85.55819'>-85.55819</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-68.31586'>-68.31586</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-85.558190,⸱-68.315860)'>(-85.558190,⸱-68.315860)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Ramlat⸱as⸱Sahmah⸱390'>Ramlat⸱as⸱Sahmah⸱390</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='55656'>55656</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H3.8-6'>H3.8-6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='0.69'>0.69</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2010⸱12:00:00⸱AM'>01/01/2010⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='20.0949'>20.0949</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='55.69318'>55.69318</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(20.094900,⸱55.693180)'>(20.094900,⸱55.693180)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "\n",
       "<div class=\"info_items\">Viewing 10 of 45716 rows / 10 columns</div>\n",
       "<div class=\"info_items\">32 partition(s)</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.table(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Profiler dump mode (Faster). It just handle the column data type as present in the dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"title_profiler\">\n",
       "    <h1>Overview</h1>\n",
       "</div>\n",
       "<div class=\"main\">\n",
       "    <div class=\"panel_profiler\">\n",
       "        <h2>Dataset info</h2>\n",
       "        <table>\n",
       "            <tbody>\n",
       "            <tr>\n",
       "                <td>Number of columns</td>\n",
       "                <td>10</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Number of rows</td>\n",
       "                <td>45716</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Total Missing (%)</td>\n",
       "                <td>0.49%</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Total size in memory</td>\n",
       "                <td>31.5 MB</td>\n",
       "\n",
       "            </tr>\n",
       "            </tbody>\n",
       "        </table>\n",
       "    </div>\n",
       "    <div class=\"panel_profiler\">\n",
       "        <h2>Column types</h2>\n",
       "        <table>\n",
       "            <tbody>\n",
       "            <tr>\n",
       "                <td>String</td>\n",
       "                <td>1</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Numeric</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Date</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Bool</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "             <tr>\n",
       "                <td>Array</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Not available</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "            </tbody>\n",
       "        </table>\n",
       "    </div>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>name</h2>\n",
       "                <div>categorical</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 45515</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 99.56</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        45716\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Święcany</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Łowicz</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 064</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 063</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 062</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 061</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 060</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 059</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 058</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 057</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>0</td>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .data_type {\n",
       "        font-size: 0.8em;\n",
       "        font-weight: normal;\n",
       "    }\n",
       "\n",
       "    .column_name {\n",
       "        font-size: 1.2em;\n",
       "    }\n",
       "\n",
       "    .info_items {\n",
       "        margin: 10px 0;\n",
       "        font-size: 0.8em;\n",
       "    }\n",
       "\n",
       "    .optimus_table tr:nth-child(even) {\n",
       "        background-color: #f2f2f2 !important;\n",
       "    }\n",
       "\n",
       "    .optimus_table tr:nth-child(odd) {\n",
       "        background-color: #ffffff !important;\n",
       "    }\n",
       "\n",
       "    .optimus_table thead {\n",
       "        border-bottom: 1px solid black;\n",
       "    }\n",
       "    .optimus_table{\n",
       "        font-size: 12px;\n",
       "    }\n",
       "\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "<div class=\"info_items\">Viewing 10 of 45716 rows / 10 columns</div>\n",
       "<div class=\"info_items\">32 partition(s)</div>\n",
       "\n",
       "<table class=\"optimus_table\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">name</div>\n",
       "            <div class=\"data_type\">1 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">id</div>\n",
       "            <div class=\"data_type\">2 (int)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">nametype</div>\n",
       "            <div class=\"data_type\">3 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">recclass</div>\n",
       "            <div class=\"data_type\">4 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">mass (g)</div>\n",
       "            <div class=\"data_type\">5 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">fall</div>\n",
       "            <div class=\"data_type\">6 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">year</div>\n",
       "            <div class=\"data_type\">7 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">reclat</div>\n",
       "            <div class=\"data_type\">8 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">reclong</div>\n",
       "            <div class=\"data_type\">9 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">GeoLocation</div>\n",
       "            <div class=\"data_type\">10 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "    </tr>\n",
       "\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Acfer⸱232'>Acfer⸱232</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='240'>240</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H5'>H5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='725.0'>725.0</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1991⸱12:00:00⸱AM'>01/01/1991⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='27.73944'>27.73944</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='4.32833'>4.32833</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(27.739440,⸱4.328330)'>(27.739440,⸱4.328330)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Elephant⸱Moraine⸱90232'>Elephant⸱Moraine⸱90232</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='8641'>8641</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='L6'>L6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='16.9'>16.9</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1990⸱12:00:00⸱AM'>01/01/1990⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-76.28795'>-76.28795</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='156.46841'>156.46841</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-76.287950,⸱156.468410)'>(-76.287950,⸱156.468410)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Grove⸱Mountains⸱020090'>Grove⸱Mountains⸱020090</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='30681'>30681</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Martian⸱(shergottite)'>Martian⸱(shergottite)</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='7.5'>7.5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2003⸱12:00:00⸱AM'>01/01/2003⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-72.99944'>-72.99944</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='75.26111'>75.26111</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-72.999440,⸱75.261110)'>(-72.999440,⸱75.261110)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Northwest⸱Africa⸱891'>Northwest⸱Africa⸱891</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='31912'>31912</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H4'>H4</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='70.8'>70.8</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2001⸱12:00:00⸱AM'>01/01/2001⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='None'>None</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='None'>None</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='None'>None</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Queen⸱Alexandra⸱Range⸱93098'>Queen⸱Alexandra⸱Range⸱93098</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='19187'>19187</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H6'>H6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='1.2'>1.2</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1993⸱12:00:00⸱AM'>01/01/1993⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-84.5757'>-84.5757</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='162.56524'>162.56524</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-84.575700,⸱162.565240)'>(-84.575700,⸱162.565240)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Queen⸱Alexandra⸱Range⸱94691'>Queen⸱Alexandra⸱Range⸱94691</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='20322'>20322</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H6'>H6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='9.6'>9.6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1994⸱12:00:00⸱AM'>01/01/1994⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-84.0'>-84.0</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='168.0'>168.0</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-84.000000,⸱168.000000)'>(-84.000000,⸱168.000000)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Meteorite⸱Hills⸱00977'>Meteorite⸱Hills⸱00977</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='16211'>16211</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H5'>H5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='13.2'>13.2</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2000⸱12:00:00⸱AM'>01/01/2000⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-79.68333'>-79.68333</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='159.75'>159.75</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-79.683330,⸱159.750000)'>(-79.683330,⸱159.750000)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Grove⸱Mountains⸱020114'>Grove⸱Mountains⸱020114</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='46531'>46531</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='L3'>L3</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='1.0'>1.0</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2003⸱12:00:00⸱AM'>01/01/2003⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-72.98194'>-72.98194</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='75.25167'>75.25167</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-72.981940,⸱75.251670)'>(-72.981940,⸱75.251670)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Pecora⸱Escarpment⸱91483'>Pecora⸱Escarpment⸱91483</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='18774'>18774</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H5'>H5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='5.5'>5.5</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/1991⸱12:00:00⸱AM'>01/01/1991⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-85.55819'>-85.55819</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='-68.31586'>-68.31586</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(-85.558190,⸱-68.315860)'>(-85.558190,⸱-68.315860)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Ramlat⸱as⸱Sahmah⸱390'>Ramlat⸱as⸱Sahmah⸱390</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='55656'>55656</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Valid'>Valid</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='H3.8-6'>H3.8-6</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='0.69'>0.69</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='Found'>Found</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='01/01/2010⸱12:00:00⸱AM'>01/01/2010⸱12:00:00⸱AM</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='20.0949'>20.0949</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='55.69318'>55.69318</div>\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            <div title='(20.094900,⸱55.693180)'>(20.094900,⸱55.693180)</div>\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "\n",
       "<div class=\"info_items\">Viewing 10 of 45716 rows / 10 columns</div>\n",
       "<div class=\"info_items\">32 partition(s)</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "op.profiler.run(df, \"name\", infer=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Profiler smart mode (Slower). It just try to infer the column data type and present extra data acordinly. From example datetype columns get extra histograms about minutes, day, week and month. Also can detect array types on data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
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       "    }\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"title_profiler\">\n",
       "    <h1>Overview</h1>\n",
       "</div>\n",
       "<div class=\"main\">\n",
       "    <div class=\"panel_profiler\">\n",
       "        <h2>Dataset info</h2>\n",
       "        <table>\n",
       "            <tbody>\n",
       "            <tr>\n",
       "                <td>Number of columns</td>\n",
       "                <td>10</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Number of rows</td>\n",
       "                <td>45716</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Total Missing (%)</td>\n",
       "                <td>0.49%</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Total size in memory</td>\n",
       "                <td>95.8 MB</td>\n",
       "\n",
       "            </tr>\n",
       "            </tbody>\n",
       "        </table>\n",
       "    </div>\n",
       "    <div class=\"panel_profiler\">\n",
       "        <h2>Column types</h2>\n",
       "        <table>\n",
       "            <tbody>\n",
       "            <tr>\n",
       "                <td>String</td>\n",
       "                <td>4</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Numeric</td>\n",
       "                <td>4</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Date</td>\n",
       "                <td>1</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Bool</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "             <tr>\n",
       "                <td>Array</td>\n",
       "                <td>1</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Not available</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
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       "</div><style>\n",
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       "        width:100%;\n",
       "        overflow:auto;\n",
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       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
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       "        overflow: auto\n",
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       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>name</h2>\n",
       "                <div>categorical</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 45515</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 99.56</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        45716\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Święcany</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Łowicz</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 064</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 063</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 062</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 061</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 060</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 059</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 058</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Österplana 057</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>0</td>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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AxcXFrF27FoDKykrmzp1LJBJh0qRJtLa20tzczIYNG0gkEkSjUTIzM0kkElRVVZ3+iiRJkiQpTZ1WgFVUVDBnzhwAduzYQSwWAyAWi7Fz504AmpqayMvLa98nNzeXpqamU45LkiRJ0rmq0wF26NAhfv3rX/PXf/3Xn7tdEAQnjEUikVOOH6+srIyCggIKCgrYtWtXZ6crSZIkSd2u0wG2fv16xo0bR3Z2NgDZ2dk0NzcD0NzcTFZWFnD0ylZDQ0P7fo2NjeTk5Jxy/HglJSXU1dVRV1fHgAEDOjtdSZIkSep2nQ6wZ555pv32Q4CioqL2Jxkmk0mmTZvWPr5q1SqCIKCmpoZ+/foRi8UoLCykurqalpYWWlpaqK6uprCw8DSXI0mSJEnpK6MzOx04cIDf/va3/PznP28fW7x4MTNnzqS8vJyBAweyevVqAKZOncq6deuIx+P06tWLFStWABCNRlm6dCkTJkwA4MEHHyQajZ7ueiRJkiQpbUWCk70ZK00VFBRQV1fX3dOQJEk6bYMXP39Gj19feuMZPb6kE32ZXjmtpyBKkiRJkr48A0ySJEmSQmKASZIkSVJIDDBJkiRJCokBJkmSJEkhMcAkSZIkKSQGmCRJkiSFxACTJEmSpJAYYJIkSZIUEgNMkiRJkkJigEmSJElSSAwwSZIkSQqJASZJkiRJITHAJEmSJCkkBpgkSZIkhaRTAdba2sqMGTMYNmwYw4cP55VXXmHv3r0kEgny8/NJJBK0tLQAEAQBd999N/F4nNGjR7Nly5b24ySTSfLz88nPzyeZTHbNiiRJkiQpTXUqwO655x5uuOEG3n77bV5//XWGDx9OaWkpU6ZMIZVKMWXKFEpLSwFYv349qVSKVCpFWVkZCxYsAGDv3r0sW7aMzZs3U1tby7Jly9qjTZIkSZLORR0OsI8++oiXXnqJ+fPnA3DBBRfQv39/KisrKS4uBqC4uJi1a9cCUFlZydy5c4lEIkyaNInW1laam5vZsGEDiUSCaDRKZmYmiUSCqqqqLlyaJEmSJKWXDgfYe++9x4ABA/ibv/kbxo4dyx133MH+/fvZsWMHsVgMgFgsxs6dOwFoamoiLy+vff/c3FyamppOOS5JkiRJ56oOB1hbWxtbtmxhwYIFvPbaa3zta19rv93wZIIgOGEsEomccvx4ZWVlFBQUUFBQwK5duzo6XUmSJElKGx0OsNzcXHJzc5k4cSIAM2bMYMuWLWRnZ9Pc3AxAc3MzWVlZ7ds3NDS079/Y2EhOTs4px49XUlJCXV0ddXV1DBgwoKPTlSRJkqS00eEAu+SSS8jLy+P3v/89ABs3bmTEiBEUFRW1P8kwmUwybdo0AIqKili1ahVBEFBTU0O/fv2IxWIUFhZSXV1NS0sLLS0tVFdXU1hY2IVLkyRJkqT0ktGZnZ566iluu+02Dh06xNChQ1mxYgWfffYZM2fOpLy8nIEDB7J69WoApk6dyrp164jH4/Tq1YsVK1YAEI1GWbp0KRMmTADgwQcfJBqNdtGyJEmSJCn9RIKTvRkrTRUUFFBXV9fd05AkSTptgxc/f0aPX1964xk9vqQTfZle6dTngEmSJEmSOs4AkyRJkqSQGGCSJEmSFBIDTJIkSZJCYoBJkiRJUkgMMEmSJEkKiQEmSZIkSSHp1AcxS5LSi58nJEnS2cErYJIkSZIUEgNMkiRJkkJigEmSJElSSAwwSZIkSQqJASZJkiRJITHAJEmSJCkkBpgkSZIkhaRTnwM2ePBg+vTpQ48ePcjIyKCuro69e/cya9Ys6uvrGTx4ML/61a/IzMwkCALuuece1q1bR69evVi5ciXjxo0DIJlM8qMf/QiABx54gOLi4q5bmSRJkgA/K1BKJ52+AvZf//VfbN26lbq6OgBKS0uZMmUKqVSKKVOmUFpaCsD69etJpVKkUinKyspYsGABAHv37mXZsmVs3ryZ2tpali1bRktLSxcsSZIkSZLSU5fdglhZWdl+Bau4uJi1a9e2j8+dO5dIJMKkSZNobW2lubmZDRs2kEgkiEajZGZmkkgkqKqq6qrpSJIkSVLa6VSARSIRrr/+esaPH09ZWRkAO3bsIBaLARCLxdi5cycATU1N5OXlte+bm5tLU1PTKcclSZIk6VzVqfeAvfzyy+Tk5LBz504SiQTDhg075bZBEJwwFolETjl+vLKysvbI27VrV2emK0mSJElpoVNXwHJycgDIyspi+vTp1NbWkp2dTXNzMwDNzc1kZWUBR69sNTQ0tO/b2NhITk7OKcePV1JSQl1dHXV1dQwYMKAz05UkSZKktNDhANu/fz/79u1r/3t1dTWjRo2iqKiIZDIJHH264bRp0wAoKipi1apVBEFATU0N/fr1IxaLUVhYSHV1NS0tLbS0tFBdXU1hYWEXLk2SJEmS0kuHb0HcsWMH06dPB6CtrY1vf/vb3HDDDUyYMIGZM2dSXl7OwIEDWb16NQBTp05l3bp1xONxevXqxYoVKwCIRqMsXbqUCRMmAPDggw8SjUa7al2SJEmSlHY6HGBDhw7l9ddfP2H84osvZuPGjSeMRyIRli9fftJjzZs3j3nz5nV0CpIkSZJ0Vuqyx9BLkiRJkj6fASZJkiRJITHAJEmSJCkkBpgkSZIkhcQAkyRJkqSQGGCSJEmSFBIDTJIkSZJCYoBJkiRJUkgMMEmSJEkKiQEmSZIkSSExwCRJkiQpJAaYJEmSJIXEAJMkSZKkkBhgkiRJkhQSA0ySJEmSQtLpADty5Ahjx47lpptuAmD79u1MnDiR/Px8Zs2axaFDhwA4ePAgs2bNIh6PM3HiROrr69uP8eijjxKPx7nsssvYsGHD6a1EkiRJktJcpwPsySefZPjw4e1fL1q0iIULF5JKpcjMzKS8vByA8vJyMjMzeeedd1i4cCGLFi0CYNu2bVRUVPDmm29SVVXFXXfdxZEjR05zOZIkSZKUvjoVYI2NjTz//PPccccdAARBwIsvvsiMGTMAKC4uZu3atQBUVlZSXFwMwIwZM9i4cSNBEFBZWcns2bPp2bMnQ4YMIR6PU1tb2xVrkiRJkqS01KkA+8EPfsA//dM/cd55R3ffs2cP/fv3JyMjA4Dc3FyampoAaGpqIi8vD4CMjAz69evHnj17jhk/fh9JkiRJOhd1OMCee+45srKyGD9+fPtYEAQnbBeJRD73e5+3z58rKyujoKCAgoICdu3a1dHpSpIkSVLayOjoDi+//DK//vWvWbduHZ9++ikfffQRP/jBD2htbaWtrY2MjAwaGxvJyckBjl7ZamhoIDc3l7a2Nj788EOi0Wj7+J/8+T5/rqSkhJKSEgAKCgo6u05J6haDFz9/Ro9fX3rjGT2+JEnqWh2+Avboo4/S2NhIfX09FRUVXHfddfzyl7/k2muvZc2aNQAkk0mmTZsGQFFREclkEoA1a9Zw3XXXEYlEKCoqoqKigoMHD7J9+3ZSqRRXXnllFy5NkiRJktJLh6+Ancpjjz3G7NmzeeCBBxg7dizz588HYP78+dx+++3E43Gi0SgVFRUAjBw5kpkzZzJixAgyMjJYvnw5PXr06KrpSJIkSVLaOa0Amzx5MpMnTwZg6NChJ32K4YUXXsjq1atPuv+SJUtYsmTJ6UxBkiRJks4anf4cMEmSJElSxxhgkiRJkhQSA0ySJEmSQmKASZIkSVJIDDBJkiRJCokBJkmSJEkhMcAkSZIkKSQGmCRJkiSFxACTJEmSpJBkdPcEJEmS0sngxc+f0ePXl954Ro8vfRHP8e7lFTBJkiRJCokBJkmSJEkhMcAkSZIkKSQGmCRJkiSFxACTJEmSpJB0OMA+/fRTrrzySq644gpGjhzJQw89BMD27duZOHEi+fn5zJo1i0OHDgFw8OBBZs2aRTweZ+LEidTX17cf69FHHyUej3PZZZexYcOGrlmRJEmSJKWpDgdYz549efHFF3n99dfZunUrVVVV1NTUsGjRIhYuXEgqlSIzM5Py8nIAysvLyczM5J133mHhwoUsWrQIgG3btlFRUcGbb75JVVUVd911F0eOHOna1UmSJElSGulwgEUiEXr37g3A4cOHOXz4MJFIhBdffJEZM2YAUFxczNq1awGorKykuLgYgBkzZrBx40aCIKCyspLZs2fTs2dPhgwZQjwep7a2tqvWJUmSJElpp1PvATty5AhjxowhKyuLRCLBpZdeSv/+/cnIOPq5zrm5uTQ1NQHQ1NREXl4eABkZGfTr1489e/YcM378PpIkSZJ0LupUgPXo0YOtW7fS2NhIbW0tb7311gnbRCIRAIIgOOn3TjV+vLKyMgoKCigoKGDXrl2dma4kSZIkpYXTegpi//79mTx5MjU1NbS2ttLW1gZAY2MjOTk5wNErWw0NDQC0tbXx4YcfEo1Gjxk/fp8/V1JSQl1dHXV1dQwYMOB0pitJkiRJ3arDAbZr1y5aW1sB+OSTT3jhhRcYPnw41157LWvWrAEgmUwybdo0AIqKikgmkwCsWbOG6667jkgkQlFRERUVFRw8eJDt27eTSqW48soru2pdkiRJkpR2Mjq6Q3NzM8XFxRw5coTPPvuMmTNnctNNNzFixAhmz57NAw88wNixY5k/fz4A8+fP5/bbbycejxONRqmoqABg5MiRzJw5kxEjRpCRkcHy5cvp0aNH165OkiRJktJIhwNs9OjRvPbaayeMDx069KRPMbzwwgtZvXr1SY+1ZMkSlixZ0tEpSJIkSdJZqcMBJkmS0t/gxc+fsWPXl954xo4tSee603oIhyRJkiTpyzPAJEmSJCkkBpgkSZIkhcQAkyRJkqSQGGCSJEmSFBIDTJIkSZJCYoBJkiRJUkgMMEmSJEkKiQEmSZIkSSExwCRJkiQpJAaYJEmSJIXEAJMkSZKkkBhgkiRJkhSSjO6egCRJOnsNXvz8GT1+femNZ/T4khS2Dl8Ba2ho4Nprr2X48OGMHDmSJ598EoC9e/eSSCTIz88nkUjQ0tICQBAE3H333cTjcUaPHs2WLVvaj5VMJsnPzyc/P59kMtlFS5IkSZKk9NThAMvIyODHP/4xb731FjU1NSxfvpxt27ZRWlrKlClTSKVSTJkyhdLSUgDWr19PKpUilUpRVlbGggULgKPBtmzZMjZv3kxtbS3Lli1rjzZJkiRJOhd1OMBisRjjxo0DoE+fPgwfPpympiYqKyspLi4GoLi4mLVr1wJQWVnJ3LlziUQiTJo0idbWVpqbm9mwYQOJRIJoNEpmZiaJRIKqqqouXJokSZIkpZfTeghHfX09r732GhMnTmTHjh3EYjHgaKTt3LkTgKamJvLy8tr3yc3Npamp6ZTjkiRJknSu6vRDOD7++GNuvfVWnnjiCfr27XvK7YIgOGEsEomccvx4ZWVllJWVAbBr167OTleSJEmSul2nroAdPnyYW2+9ldtuu41bbrkFgOzsbJqbmwFobm4mKysLOHplq6GhoX3fxsZGcnJyTjl+vJKSEurq6qirq2PAgAGdma4kSZIkpYUOB1gQBMyfP5/hw4dz7733to8XFRW1P8kwmUwybdq09vFVq1YRBAE1NTX069ePWCxGYWEh1dXVtLS00NLSQnV1NYWFhV20LEmSJElKPx2+BfHll1/mF7/4BZdffjljxowB4JFHHmHx4sXMnDmT8vJyBg4cyOrVqwGYOnUq69atIx6P06tXL1asWAFANBpl6dKlTJgwAYAHH3yQaDTaVeuSJEmSpLTT4QC7+uqrT/r+LYCNGzeeMBaJRFi+fPlJt583bx7z5s3r6BQkSdJXjB/4LOlccVpPQZQkSZIkfXkGmCRJkiSFxACTJEmSpJAYYJIkSZIUEgNMkiRJkkJigEmSJElSSAwwSZIkSQqJASZJkiRJIenwBzFLkiRJJ+MHZktfzCtgkiRJkhQSr4BJShv+5lSSJJ3rvAImSZIkSSExwCRJkiQpJN6CKOkrx1sdJUlSdzHAJElpyVCWJJ2LOnwL4rx588jKymLUqFHtY3v37iWRSJCfn08ikaClpQWAIAi4++67icfjjB49mi1btrTvk0wmyc/PJz8/n2Qy2QVLkSRJkqT01uEA++53v0tVVdUxY6WlpUyZMoVUKsWUKVMoLS0FYP369aRSKVKpFGVlZSxYsAA4GmzLli1j8+bN1NbWsmzZsva5D5tKAAAJl0lEQVRokyRJkqRzVYcD7JprriEajR4zVllZSXFxMQDFxcWsXbu2fXzu3LlEIhEmTZpEa2srzc3NbNiwgUQiQTQaJTMzk0QicULUSZIkSdK5pkuegrhjxw5isRgAsViMnTt3AtDU1EReXl77drm5uTQ1NZ1yXJIkSZLOZWf0IRxBEJwwFolETjl+MmVlZZSVlQGwa9eurp2gJEmSJIWoSwIsOzub5uZmYrEYzc3NZGVlAUevbDU0NLRv19jYSE5ODrm5uWzatOmY8cmTJ5/02CUlJZSUlABQUFDQFdOV1AE+iU6SJKnrdMktiEVFRe1PMkwmk0ybNq19fNWqVQRBQE1NDf369SMWi1FYWEh1dTUtLS20tLRQXV1NYWFhV0xFkiRJktJWh6+AzZkzh02bNrF7925yc3NZtmwZixcvZubMmZSXlzNw4EBWr14NwNSpU1m3bh3xeJxevXqxYsUKAKLRKEuXLmXChAkAPPjggyc82EOSJEmSzjUdDrBnnnnmpOMbN248YSwSibB8+fKTbj9v3jzmzZvX0R8vSZIkSWetLrkFUZIkSZL0xQwwSZIkSQqJASZJkiRJITHAJEmSJCkkBpgkSZIkhcQAkyRJkqSQGGCSJEmSFBIDTJIkSZJC0uEPYpaUHgYvfv6MHr++9MYzenxJkqSvIgNMXwlhxYpRJEnSucX/tqureQuiJEmSJIXEAJMkSZKkkHgLoiSpQ87k7TjeiiNJOtcZYJIkhcT3kkiSDDB1K3+TLkmSpK+Sbn8PWFVVFZdddhnxeJzS0tLuno4kSZIknTHdGmBHjhzhb//2b1m/fj3btm3jmWeeYdu2bd05JUmSJEk6Y7r1FsTa2lri8ThDhw4FYPbs2VRWVjJixIjunNZXnu9RkCRJks6Mbg2wpqYm8vLy2r/Ozc1l8+bN3TgjSZIknQ3OxV8Yu6aOOVt/qR8JgiDorh++evVqNmzYwL/9278B8Itf/ILa2lqeeuqp9m3KysooKysD4O2332bYsGHdMleFY9euXQwYMKC7p6GzkOeOOsPzRp3luaPO8Lw599XX17N79+7P3aZbr4Dl5ubS0NDQ/nVjYyM5OTnHbFNSUkJJSUnYU1M3KSgooK6urrunobOQ5446w/NGneW5o87wvBF080M4JkyYQCqVYvv27Rw6dIiKigqKioq6c0qSJEmSdMZ06xWwjIwMfvKTn1BYWMiRI0eYN28eI0eO7M4pSZIkSdIZ0+0fxDx16lSmTp3a3dNQmvB2U3WW5446w/NGneW5o87wvBF080M4JEmSJOmrpFvfAyZJkiRJXyUGmNLG4MGDufzyyxkzZgwFBQXdPR2lsXnz5pGVlcWoUaPax/bu3UsikSA/P59EIkFLS0s3zlDp6GTnzcMPP8w3vvENxowZw5gxY1i3bl03zlDpqKGhgWuvvZbhw4czcuRInnzyScDXHH2xU507vu7IWxCVNgYPHkxdXR1f//rXu3sqSnMvvfQSvXv3Zu7cubzxxhsA/N3f/R3RaJTFixdTWlpKS0sLjz32WDfPVOnkZOfNww8/TO/evbnvvvu6eXZKV83NzTQ3NzNu3Dj27dvH+PHjWbt2LStXrvQ1R5/rVOfOr371K193vuK8AibprHPNNdcQjUaPGausrKS4uBiA4uJi1q5d2x1TUxo72XkjfZFYLMa4ceMA6NOnD8OHD6epqcnXHH2hU507kgGmtBGJRLj++usZP348ZWVl3T0dnWV27NhBLBYDjv5Hb+fOnd08I50tfvKTnzB69GjmzZvnbWT6XPX19bz22mtMnDjR1xx1yJ+fO+DrzledAaa08fLLL7NlyxbWr1/P8uXLeemll7p7SpLOcQsWLODdd99l69atxGIxfvjDH3b3lJSmPv74Y2699VaeeOIJ+vbt293T0Vnk+HPH1x0ZYEobOTk5AGRlZTF9+nRqa2u7eUY6m2RnZ9Pc3Awcve8+Kyurm2eks0F2djY9evTgvPPO48477/R1Ryd1+PBhbr31Vm677TZuueUWwNccfTmnOnd83flqM8CUFvbv38++ffva/15dXX3Mk8qkL1JUVEQymQQgmUwybdq0bp6RzgZ/+h9ogGeffdbXHZ0gCALmz5/P8OHDuffee9vHfc3RFznVuePrjnwKotLCe++9x/Tp0wFoa2vj29/+NkuWLOnmWSldzZkzh02bNrF7926ys7NZtmwZN998MzNnzuT9999n4MCBrF692gcu6BgnO282bdrE1q1biUQiDB48mJ///Oft7+uRAP73f/+Xv/zLv+Tyyy/nvPOO/t76kUceYeLEib7m6HOd6tx55plnfN35ijPAJEmSJCkk3oIoSZIkSSExwCRJkiQpJAaYJEmSJIXEAJMkSZKkkBhgkiRJkhQSA0ySJEmSQmKASZIkSVJIDDBJkiRJCokBJkmSJEkhMcAkSZIkKSQGmCRJkiSFxACTJEmSpJAYYJIkSZIUEgNMkiRJkkJigEmSJElSSAwwSZIkSQqJASZJkiRJITHAJEmSJCkkBpgkSZIkhcQAkyRJkqSQGGCSJEmSFBIDTJIkSZJCYoBJkiRJUkgMMEmSJEkKiQEmSZIkSSExwCRJkiQpJAaYJEmSJIXEAJMkSZKkkBhgkiRJkhQSA0ySJEmSQmKASZIkSVJIDDBJkiRJCokBJkmSJEkhMcAkSZIkKSQGmCRJkiSFxACTJEmSpJAYYJIkSZIUEgNMkiRJkkJigEmSJElSSAwwSZIkSQqJASZJkiRJITHAJEmSJCkkBpgkSZIkhcQAkyRJkqSQGGCSJEmSFBIDTJIkSZJCYoBJkiRJUkgMMEmSJEkKiQEmSZIkSSExwCRJkiQpJAaYJEmSJIXEAJMkSZKkkBhgkiRJkhQSA0ySJEmSQmKASZIkSVJIDDBJkiRJCokBJkmSJEkhMcAkSZIkKSQGmCRJkiSFxACTJEmSpJAYYJIkSZIUEgNMkiRJkkJigEmSJElSSAwwSZIkSQqJASZJkiRJITHAJEmSJCkkBpgkSZIkhcQAkyRJkqSQGGCSJEmSFBIDTJIkSZJCYoBJkiRJUkgMMEmSJEkKiQEmSZIkSSExwCRJkiQpJAaYJEmSJIXEAJMkSZKkkBhgkiRJkhQSA0ySJEmSQmKASZIkSVJIDDBJkiRJCokBJkmSJEkhMcAkSZIkKSQGmCRJkiSFxACTJEmSpJAYYJIkSZIUEgNMkiRJkkJigEmSJElSSAwwSZIkSQqJASZJkiRJITHAJEmSJCkkBpgkSZIkhcQAkyRJkqSQ/H/NIgqOBsLG0wAAAABJRU5ErkJggg==\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>id</h2>\n",
       "                <div>numeric</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 42365</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 92.67</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        45716\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "            <div>\n",
       "                <h3>\n",
       "                    Basic Stats\n",
       "                </h3>\n",
       "\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Mean</td>\n",
       "                    <td>26889.73510368361</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Minimum</td>\n",
       "                    <td>1</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Maximum</td>\n",
       "                    <td>57458</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Zeros(%)</td>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57458</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57457</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57456</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57455</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57454</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57453</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57436</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57435</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57434</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>57433</td>\n",
       "                    <td>1</td>\n",
       "                    <td>0.002%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>0</td>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "        <div class=\"panel_profiler\">\n",
       "\n",
       "\n",
       "            <h3>Quantile statistics</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Minimum</td>\n",
       "                    <td>1</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>5-th percentile</td>\n",
       "                    <td>1.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Q1</td>\n",
       "                    <td>1.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Median</td>\n",
       "                    <td>1.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Q3</td>\n",
       "                    <td>1.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>95-th percentile</td>\n",
       "                    <td>1.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Maximum</td>\n",
       "                    <td>57458</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Range</td>\n",
       "                    <td>57457</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Interquartile range</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Descriptive statistics</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Standard deviation</td>\n",
       "                    <td>16860.683030276334</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Coef of variation</td>\n",
       "                    <td>0.62703</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Kurtosis</td>\n",
       "                    <td>-1.1602608393254068</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Mean</td>\n",
       "                    <td>26889.73510368361</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>MAD</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Skewness</td>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Sum</td>\n",
       "                    <td>1229291130</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Variance</td>\n",
       "                    <td>284282632.2474484</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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vn4KDg9W+fXv16dNHf/3rXxUcHOyPOAAAAAAQEPzyGjBJioiIUERERIHvTZo0yf3/QUFBmj59uqZPn+6vCAAAAAAQUPz2QcwAAAAAgIIoYAAAAADgEAoYAAAAADiEAgYAAAAADqGAAQAAAIBDKGAAAAAA4BAKGAAAAAA4hAIGAAAAAA6hgAEAAACAQyhgAAAAAOAQChgAAAAAOIQCBgAAAAAOoYABAAAAgEMoYAAAAADgEAoYAAAAADiEAgYAAAAADqGAAQAAAIBDKGAAAAAA4BAKGAAAAAA4hAIGAAAAAA6hgAEAAACAQyhgAAAAAOAQChgAAAAAOIQCBgAAAAAOoYABAAAAgEMoYAAAAADgEAoYAAAAADiEAgYAAAAADqGAAQAAAIBDKGAAAAAA4BAKGAAAAAA4hAIGAAAAAA7xWwFbu3at2rZtq9DQUE2dOrXY5ZYuXaqgoCAlJSX5KwoAAAAABAS/FLDc3FyNHTtWa9asUXJyshYtWqTk5ORCy505c0YzZ87U7bff7o8YAAAAABBQ/FLAEhMTFRoaqtatW6tGjRoaNGiQli9fXmi5CRMmaPz48apVq5Y/YgAAAABAQPFLAUtNTVWLFi3cX4eEhCg1NbXAMjt37tSxY8c0cOBAf0QAAAAAgIBTzR9DzazQ94KCgtz/n5eXp3HjxmnevHmlzoqOjlZ0dLQkKT093WcZAQAAAMBpfnkGLCQkRMeOHXN/ffz4cV133XXur8+cOaPdu3erd+/eatWqlbZu3arIyMgi34hj9OjRSkpKUlJSkpo2beqPuAAAAADgCL8UsPDwcB08eFCHDx9Wdna2YmNjFRkZ6b69QYMGysjIUEpKilJSUtSjRw/FxcWpe/fu/ogDAAAAAAHBLwWsWrVqmjVrlvr166d27dopKipKHTp00EsvvaS4uDh//JMAAAAAEPD88howSYqIiFBERESB702aNKnIZRMSEvwVAwAAAAACht8+iBkAAAAAUBAFDAAAAAAcQgEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCEUMAAAAABwCAUMAAAAABxCAQMAAAAAh1DAAAAAAMAhFDAAAAAAcAgFDAAAAAAcQgEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCEUMAAAAABwCAUMAAAAABxCAQMAAAAAh1DAAAAAAMAhFDAAAAAAcAgFDAAAAAAcQgEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCF+K2Br165V27ZtFRoaqqlTpxa6ffr06Wrfvr06deqkO++8U0eOHPFXFAAAAAAICH4pYLm5uRo7dqzWrFmj5ORkLVq0SMnJyQWW6dKli5KSkrRr1y498MADGj9+vD+iAAAAAEDA8EsBS0xMVGhoqFq3bq0aNWpo0KBBWr58eYFl+vTpozp16kiSevTooePHj/sjCgAAAAAEDL8UsNTUVLVo0cL9dUhIiFJTU4tdfu7cuerfv78/ogAAAABAwKjmj6FmVuh7QUFBRS67cOFCJSUladOmTUXeHh0drejoaElSenq670ICAAAAgMP88gxYSEiIjh075v76+PHjuu666wott379ek2ZMkVxcXGqWbNmkbNGjx6tpKQkJSUlqWnTpv6ICwAAAACO8EsBCw8P18GDB3X48GFlZ2crNjZWkZGRBZbZuXOnxowZo7i4ODVr1swfMQAAAAAgoPilgFWrVk2zZs1Sv3791K5dO0VFRalDhw566aWXFBcXJ0n6wx/+oLNnz+rBBx9U586dCxU0AAAAAKhs/PIaMEmKiIhQREREge9NmjTJ/f/r16/31z8NAAAAAAHJbx/EDAAAAAAoiAIGAAAAAA6hgAEAAACAQyhgAAAAAOAQChgAAAAAOIQCBgAAAAAOoYABAAAAgEMoYAAAAADgEAoYAAAAADiEAgYAAAAADqGAAQAAAIBDKGAAAAAA4BAKGAAAAAA4hAIGAAAAAA6hgAEAAACAQyhgAAAAAOAQChgAAAAAOIQCBgAAAAAOoYABAAAAgEMoYAAAAADgEAoYAAAAADiEAgYAAAAADqGAAQAAAIBDKGAAAAAA4BAKGAAAAAA4hAIGAAAAAA6hgAEAAACAQyhgAAAAAOAQChgAAAAAOIQCBgAAAAAOoYABAAAAgEMoYAAAAADgEL8VsLVr16pt27YKDQ3V1KlTC91+4cIFPfTQQwoNDdXtt9+ulJQUf0UBAAAAgIDglwKWm5ursWPHas2aNUpOTtaiRYuUnJxcYJm5c+eqUaNG+vrrrzVu3Dj98Y9/9EcUAAAAAAgYfilgiYmJCg0NVevWrVWjRg0NGjRIy5cvL7DM8uXLNWzYMEnSAw88oA0bNsjM/BEHAAAAAAKCXwpYamqqWrRo4f46JCREqampxS5TrVo1NWjQQJmZmf6IAwAAAAABIcj88LTTkiVLFB8frzlz5kiSFixYoMTERL399tvuZTp06KD4+HiFhIRIktq0aaPExEQFBwcXmBUdHa3o6GhJ0r59+3TLLbf4Oq5fpaenq2nTpgEzx5ezyOTsHF/OCsRMvpxFJmfn+HJWIGby5SwyOTvHl7MCMZMvZ5HJ2Tm+nEWmwJKSkqKMjIySFzI/2LJli/Xt29f99WuvvWavvfZagWX69u1rW7ZsMTOzixcvWnBwsOXl5fkjzhXVrVu3gJrjy1lkcnaOL2cFYiZfziKTs3N8OSsQM/lyFpmcnePLWYGYyZezyOTsHF/OIlPF45dLEMPDw3Xw4EEdPnxY2dnZio2NVWRkZIFlIiMjFRMTI0launSpfvGLXygoKMgfcQAAAAAgIFTzy9Bq1TRr1iz169dPubm5Gj58uDp06KCXXnpJ3bt3V2RkpEaMGKGhQ4cqNDRUjRs3VmxsrD+iAAAAAEDAqDpx4sSJ/hh800036amnntLTTz+tXr16SZL69Omjtm3bSrpU0qKiovS73/1Oo0aNUqNGjfwRIyB069YtoOb4chaZnJ3jy1mBmMmXs8jk7BxfzgrETL6cRSZn5/hyViBm8uUsMjk7x5ezyFSx+OVNOAAAAAAAhfnlNWAAAAAAgMIoYAEkLy/PZ7N4YtMz3E+QfLfvsT0hUHF8ATzHNg5/o4D5SHkObjt27NDZs2dVpUr5fx2HDh1SdnZ2ud9R8vTp0wH9B6i82dLS0pSTk1Pu+ykrK6tcP1+U3Nxcn8+srMp7Uumrfc9X+51U+fe9QOer9fPl/cTxxVmBnM0XfLl+gbK/JCcn68cffyx3Dl+dG0i+Pz/g3KBy8dubcFR28fHxmjt3rtavX6/w8HDVrl27THPWr1+vu+++W+fPny/3W/GvWLFCL7/8ssLCwtS8efMyz1m1apWio6PVs2dP1axZs8xzpEv307Rp0zRw4MByzUlISNDKlSuVnJysm266STVq1CjzrLi4OP3lL39Rp06dyvXBfitXrtRHH32kn/3sZ6patWqZ50jSxx9/rJiYGPXp00dVqlRRXl5embeFLVu26NNPP9V3332n66+/XtWqle3NTrdv366kpCSdOXNGwcHBZZ4jXTrhqlWrlsysXNu4r/Y7yXf7nq/2O8l3+56v9jvJd/veli1b9Mknn+jIkSNq2bKlqlevXuZMJ06cUO3atX1SKhISErRu3TqlpaXp+uuvV82aNcu0/23evFkJCQlKS0tT8+bNVbNmTeXm5pYpI8cXzwTi8cVX23kgbuOSlJiYqKSkJF24cEENGzZU9erVyzRrw4YNWrJkib766it16NChXPf5unXrNHjwYDVo0EDdunUr83HGV+cGku/ODwLx3EDy3fmBr84NKiRHP3WsklizZo117tzZ5syZY4899phNnTrVfVtubq7Xc5555hkbO3as+/tl+UDq3bt3W5s2bezTTz8tdJs3mVavXm1dunSxhISEQrd5mysnJ8eef/55CwoKsldeeaXMc1atWmWdO3e2SZMm2cMPP2yzZs0q86ykpCRr06aNbdq0qdBtZfndffLJJ179+5fLy8uzrKws+81vfmNBQUH25z//2X1bdna21/NWrVplYWFh9tRTT1lUVJQtX768TLni4uKsU6dONmjQIHv00UftvffeK/MHpf/zn/+0evXq2bp168r08y6+2u/yzyrvvuer/c7Md/uer/Y7M9/teytWrLCwsDAbO3asPfbYY/bHP/7RLl686HUeM7Nly5ZZ3bp1bf78+fbjjz+WaYbLxx9/bDfddJONHz/eRo0aZbfddptlZmaamfd/Nzt16mRTpkyxP/3pT/bTn/7UTp065fUcM44vngrE44uvtvNA3MbN/u+48Mwzz9j48ePt4Ycfth9++MHrWStXrrTOnTvb5MmTbejQofbhhx+6b/P2Po+Pj7ewsDB74IEHCmzn3vLVuYGZb84PAvXcwMx35we+OjeoqChgXsrNzbURI0ZYbGysmZnFxsbaCy+8YCtWrLDTp0+7lynNv//9b+vcubMlJiaamdmtt95qr776aplzffLJJzZ06FAzMzt27JjNmjXLJk6caCdOnDAzz/6offPNN3brrbfa5MmTzcwsMzPT1q1bZ+vXr7czZ86Ymfd/iDZt2mTPPPOM9ejRwx5//HEzM8vKyvL455OTk61Xr1722WefmZnZm2++aW+88Ybt37/fzp0753WmxYsXu/9IHzt2zBYsWGBz5szx6mRpz549dvPNN9vs2bPNzOzkyZOWmJhou3btKvPBMj4+3t58801r166d+37y1vbt2y08PNz+/e9/m5nZ+PHjbc6cOZaZmWkXLlzweM7OnTutY8eOtmvXLjMzi4mJsUceeaRMmVJSUqxfv372m9/8xtq3b28bNmwo05y8vDyf7Hdmvt33fLHfmfl+3yvvfmfmu31v7969dtttt9n27dvNzGzz5s02dOhQO3/+vFd5zMy+/fZbe/DBB23kyJE2YMAAW7Rokdfrld+f//xne+ONN9xfP/fccxYaGuo+QfXk95eXl2ejRo2yZcuWmdml+7lr164WFhbm/rvi6Xbgq+2c44tnfHl88dV2HojbuNmlk/7Bgwe776u9e/daly5dbODAgfbf//7X41kXLlywhx56yDZu3GhmZtOmTbM333zTEhMTvd4OPvnkE7v55pttx44dZmbWpk0be//99z362cv54tzAzPfnB4F0bmDmu/MDX50bVGS8BsxLubm5qlWrlr7++mtt3LhRL730ko4ePaolS5aoW7duOnXqlEeXDAQHB2vevHkKDw+XJM2cOVN79uzRkSNHypSrVatWqlGjhg4dOqRBgwYpMzNTR48eVUREhNLS0jx6ardWrVq67777VK1aNcXExCgyMlLz5s3Te++9p8jISJ05c8bjyyFycnJkZqpWrZquueYarV+/Xnv27FFkZKQGDBigc+fOeXTN9zXXXKMZM2bojjvu0MmTJ/XOO+/o008/1YwZM3T33Xfrhx9+8OoSDdflF+fPn9eDDz6o7du3KyEhQeHh4R7/7mrXrq3w8HDl5eXp448/VmRkpF5//XW9+uqrGjt2rM6fP+9xHtc13f/973915swZJSYmasOGDYqMjFRkZKQk6eLFix7NatSokWbOnKkePXooMzNT//jHP7R06VK9+OKLeuKJJzzOVb9+fY0ePVq33nqrJOmhhx7S4cOHtX//fq+v069Xr57GjRunhQsX6o9//KNGjRqlTz75RJJ31/y79ruDBw+Wa7+TpCZNmvhs32vVqpWqV69erv1OkurUqaP77rtPVatWLde+l5eXJzNT1apVy7XfSVLDhg19su/Vr19fY8aMUdeuXSVJd9xxh1JSUrR9+3avt6c6depo3Lhxmj17tsaMGaP33ntPy5YtK/TaD0/nhoaG6ty5c+6vp02bpnvuuUd33323zp07V+rvz/Xv5OTk6Pvvv5ck1axZU/fee69atmyphx9+WBcuXPB4OzAznxxfmjVrFnDHl3r16vns+CLJJ8eXxo0b++z40qBBA59s566/meXdxl23l3cbd3Ft465t6JZbblGfPn1Uv359/elPf/L4dVO5ubk6f/68kpOTtW/fPkVHR2vLli16++23NXDgQK/u82bNmmn+/Pnq0qWLJGnixInav3+lB0tMAAAYb0lEQVS/zp8/7/XrJn1xbiD57vzA9bf89OnTAXNuIPnu/MBX5wYVmtONr6LatGmTpaWlmZlZYmKiDRs2zB544AEbM2aMe5mRI0falClTSpyTkJBgx48fd3/tesQoJSXFIiIiLC4ursD3S8vkegQyIyPD7rnnHnvyyScLPNL51FNPlfq0fEJCgqWmppqZWVpamk2aNMk6depk7777rpldesTqkUcecT8q62kml+HDh5vZpaet69ata/369St1Tv5MLsuXL3dnyM7OtiFDhhS4dKE4J06ccF8mcezYMQsLC7MxY8bYO++8415m9OjRBS71KW6O69Gwb775xh599FFr3769+xG3/fv325AhQ2zz5s0eZ3L9ni9cuOD+PS1fvtxq165tffv2LXWOa5br0XGXDz74wObMmWNmZgcOHLCHH37Y/YijJ+vnusQhOzvbfvzxR7vzzjvt4MGDZnbpUePSLoHInyknJ8f9/ZiYGGvdurWtX7/ezMy2bt1a4qO7p06dsrNnz5rZpUfxyrrfmV16JNK1HeTn7b536tQp96PjJ0+etHvuucfGjh3r9X7n+nnXo77ffvttmfe9/JlcyrLfXZ7JpSz7Xv45ru3FdTnWgw8+aElJSWZm9sUXX5T6CH/+7SD/I9FxcXH285//3D766CMzM9u4cWOh+6GoWa5l9u7da23atHH/vMvIkSOLvEyuOJs2bbKGDRvahAkT3NvomTNnbOTIkXbkyBGP55iV7/hyufIcX1xyc3MtPT29zMeX/FJTU8t1fHHJ/zelrNv55cp6fMnP9QxHWbdzl/x/X8uyjefnuny0rNt4RkaGez9et26dtWnTxqZOnWpPPvmkRUVF2X/+8x8bMWKEe//0ZM6nn35qffr0sV/+8pf2+9//3r3Ow4cPt5iYmFIzpaenu591y2/Hjh3WtWtX+/zzz82s9O08IyPDnfv48ePWuXNnGzVqlNfnBq5ZrkyHDx+2xx57zG655Ravzw/yZzK7dL+4nvny9twgfyaXOXPmeH1ucPks1/6XlZXl9flBRkaG+zic//fj7blBZUAB80B8fLy1atXK/fSt2aUNcO3atfb222+7v/fKK6+UuKO65mzdutX9vfwb4Ny5c+3WW28tUNC8mZWUlGSdO3e2iIgI94z33nvPJkyY4NW6paWluXcCl8cff7zUg1FRmS5cuGDPPPOMvfDCC9a+fXtbuHChdezY0caPH+/VnKKMHTvWFixYUOIyK1eutD59+lj//v3dlwR8+umn1qhRIxs8eLB7uSlTpti0adO8mvP111/b0qVLCyw3ePBgW7VqlUeZIiIibO7cuZadnW2nTp2yxx57zCZPnmzt2rWzBQsWWHBwcIn30+W55s6dW+DEJL8hQ4bYihUrPJ7jOoFwzYuKirL09HT7xz/+Yffee69lZGR4lSknJ8e9rcfExFiHDh3sySeftNtuu61QYXeJi4uzAQMGWM+ePd0HZdd+l/91GqXtd/ln9erVyz788MMC5dfM830v/xzXtufa7wYOHOjxfnf5+rlmpaWlFboevrR97/J1O3XqlHu/e/HFFz3e74qaVVRhNSt938u/bgsXLnQfuF3lafTo0bZ3715bvHix9enTp9htoKhZP/zwQ6ESFhERYcOGDbPQ0NASC0/+WfPnzzczsw0bNljDhg0LnKAOHz68xPWLj4+31157rcD3EhMT7b333rO3337bfQJy3333uU/AvZmVl5fn9XZ++ZzLL5ny9vhyeaYdO3Z4vZ0XNefbb78t8/El/6zs7Gy7ePGi19v55XOK+5vpyfGluFnebuelZfJmGy/qPt+4caPX27jZpdfo3HXXXdazZ0/729/+ZsnJybZjxw6bMGGCTZ482f03tH///u4T8JLm9OrVy95991375ptvzOxSGZg3b557ud/97nf2t7/9zaNMvXr1sujo6ELnCdOnT7e77rrLfYmlJ3P+9re/2ZEjR2z37t3WuHFjGzRokHu50s4Nipp14MABy8zMtH/+858Flivt/ODydduyZYuZXfpdvfrqq16dG1w+K/85Xn6lnRtcPuv99993z3L9/j09Pyhujoun5waVBQWsFGvXrrVOnTq5N5Qff/zR/cdx3759FhwcbNOnT7fp06dbt27dLDk52aM5WVlZhQ6Q2dnZNnTo0EI7rSeZXAf8PXv2WEREhL3wwgv21FNPWadOnew///mPx5mKesHwkiVLrFu3bvb11197nCkrK8t9P61Zs8auvfZaW7x4sZldegTa9QfYkzlFXXu9dOlS69atW4l/9F0v9E1MTLRVq1ZZ7969LT093czMtm3bZu3atbNp06bZiy++aJ07d7Y9e/Z4PKeoPzD//Oc/rWvXrnb48GGPM/Xp08d9oFi4cKE1b97cfT+dPHnSq/Xr06ePnTx5stByy5Ytsy5duhSby5M5w4cPt/vuu8+6du1a7PbkTaaoqChr0qSJffXVV0XOiY+Pt/bt29sXX3xhixcvtl/96lfubeKrr76yxo0b21tvvVXqflfUrP79+7sP2q4DSE5OTqn7XlGZXI+07ty50/r3728TJkwodb8rLpPrYJt/ey9t3ytqjut+Wr58uf3kJz+xJUuWmFnJ+11p91N+pe17nsx56qmnrGfPntatWzfbvXt3mTLlv58effRRa9asmVf3+a9+9Sv361k2btxot9xyiz3//PM2btw4a9eune3fv7/IOZs2bbKmTZta27Zt7bnnniv234uJibGwsLBCz+R7OmvXrl0eb+fFzcl/H3myjZeW6csvv/R4Oy9pjjfbeGmz4uLiPN7Oi5tz+XHPk+OLJ/e5J9t5SXPyP0jkyTZe0v2UkJDg8TZudunZyptvvtm2b99u8fHxNmXKFBs5cqRt27atwHILFiywrl27uo+tpc2ZPHmyjR492rZs2WLJycl2880329y5cy0mJsa6devmdaYxY8bYxx9/7F7m6NGjdv/999sXX3zh8ZzJkyfbiBEjLDk52Xbv3u3xuUFJ99Plb1hT2vlBUXNGjRpl27Zts2XLlnl1blDc/RQfH19gudLODUqalf+BwhEjRpR6fuDJ786s9HODyoQCVopnn33WbrrpJjMz+/77723kyJEWFRVlM2bMsJMnT9q///1vGz16tI0ePbrEE4ni5syaNavAhjZz5sxSH6EsataDDz5oM2bMsLS0NPv+++9t69atFh0dXeJO6kmm2NhYu+2220r8o19SppkzZ1pSUpK7sJR26ZonmWbPnm1dunQpNdPLL7/sfmTnxIkT1rVrVxs5cqTFxMRYenq6ffPNN7Zs2TJ74403bN++fV7NGTVqlC1cuNCdac6cOdaxY8cyZRo1apR9+OGHtnbtWvfv3pN3OSpq1ujRowvkmjFjhrVv377EbbOkOa4XN999993WrFmzErcnTzPt2rXLevXqVewf2JycHJswYYL9/e9/d3/v9ddft+eee859crNx40YbPXq0jRo1qsR1K2mWWcFnoGfMmFHsvlfcnGeffdad6ciRI7Z161Z7//33S7yfPM0UGxtr4eHhxW5TJWXKy8uzCxcuuNentBdae5IpJyfHZs+ebZ07d/Y6k2uO60GZcePGWUhIiB04cKBcmcwuXe7Tr18/27lzp9eznn32WXem5ORkW7p0qb366qslFvoPP/zQoqOjLSMjw37xi1/Ys88+W+DfycnJsU2bNtkvf/nLEjOVNsvs/7bzkSNHlridl5bJ5a233ir1+FJaJk+389Iy5eXlWWxsrHXv3r3Uv5slzcrKyrJjx46ZWenbuSe/u9K2cU9muQqdJ9t5SXNcf1s82cZLm2X2f9v4pEmTStzGzS5dtvrLX/7S/fWhQ4fsnXfesccff9z9rO7KlSutZ8+e9uWXX3o9Z8yYMbZ//35bu3at9e/f3wYPHux+YwdvZr377rv2+OOPFyhc48ePt6NHj3o1Z9asWTZq1ChLS0uzAwcOeHRuUNL65b+fPDk/KG7OE088YStWrLCUlBQz8+zcoKT7yZXJk3OD0ma5yrgn5weeZPrqq69KPDeobILMrpZXu3nn7NmzqlevniRpxIgR2rVrl6pXr67f/OY3atKkibZv365GjRrp+eefV05OjqpWrVrkC1BLm7Njxw4FBwfrueeeK/WzIjzJ1LhxY/3pT38q1xxXpvHjx+vw4cOqWrWqWrZsWeZZTZo00R/+8Afl5eUV+0JWbzIdOnRIVatWVatWrYqcde7cOdWtW9f99fnz53XnnXfqrrvuUo8ePbRp0ybVq1dPEyZMKPF+Km3O5s2bdc011+jPf/6z9u3bp2rVqik0NNTrWbfffrs+//xz1a9fX88//3yJ95O3ufbs2aMaNWropptuKtOc+vXr64UXXtC2bdtUp04d9wtvy5Pp5MmTysvLU5MmTYqdk5mZqSpVqqhhw4aSpAULFmj9+vWaP39+geWthM8O8XTW+fPnVadOnSJneDMnNze31H3Ym/VzfSBoUfuep3Oys7NL/XwdbzIdP35cOTk5Re573szZt2+fpEsv5C9PposXLyooKEjnz5/XNddcU+718+R+kqTMzEwFBwcrJSVFI0eO1K233qr//d//lST3myWcP39ewcHB5ZrlUtx27umckydPqnHjxj5Zv8v39bLOyc7O1qlTp3ThwoVijy8lzerYsaPeeustSZfexKhBgwblznTx4kWlp6crOzvbo+NLSbPy8vJ06NAh5ebmFrmdezrnzJkzqlevns6cOVPqNl7arKysLNWqVavY+0kq+PfwwQcf1A033KBp06ZJuvRB3AsWLFCrVq306KOPut+ApajPhfNkTsuWLTV8+HBlZWWpWrVqxX6WlDeZyrNu8+fP1w033KDhw4eXOMfbTCWdH5Q2Z+HChbrxxhv1yCOPlHpu4E2mks4NvJ1V0vmBJ3NuvPFGDRs2rMRzg0rpyva/wLR69WobMmSI+/IiM7MnnniiwAugN2zYYBERESW+raincwYMGFDqiw19NcubOaW9fa4ns9avX39FMl1+yZPrEVKzS29d62kmT+aU9oJoT2cNHDjQ4+2gvLm8mVPai6u9mVXS7881p6hLR7Zu3ep+sf2HH35oMTExxb52w5tZH330kcXExBT7WT3eZirpM3+8mZX/mZryrpsv7idfZfrwww/tgw8+KHaOt+s3b968Et8e2le/P9ecol5HcejQIbvzzjvtlVdescWLF9trr73m0X3uyazXX3+92Gd1PJ2zZMkSmzp1aonPDnmTqaRZ3t5PnvzuPF2/4p4Z8CbTlClTfJLJNau4N4HwZt1ef/11j/6ulPd3l3+W61i8a9cuGzNmTIHXQK1cudL69u3r0fHFkznenmcUN6tfv35enY+VlKm0t4v3ZlZJx09frZsvM3k76/I3bCrr+nnzxjKVRdk/BrsS279/v5KTk/XJJ58oOztbvXv31jvvvKO8vDz3IxAZGRmqVq2acnJyyj2natWqunjxomrWrOn3Wd7Mcb1FenkyZWZmXpFM69at08WLF/Wzn/1M0qW3mHU9Q+F6JNyTTJ7M8VWmoKAgj7eD8ubyZk5pb+frzSxP9pe1a9cqKyvLPUeSgoKCVKVKFc2bN09vvPGGli1bVuKzTd7OKu6RV1/NKcusQLyf/D2nLLNKekTY19vB+vXrlZOTU2BO69attXr1at144406f/68Nm/e7NF97ums4p7B9NWcK5nJk9+dp7OqV68ecJmKe3be2zme/F3x5XawYcMGValSRT169ND999+vZcuW6amnntLbb7+ts2fPqkaNGiW+Vbg3czw9vpQ2q3r16h4d8zzJ5Okx3ZNZTqybLzN5O6ukjx7wZv1K2p4qKwrY/+f65QcFBally5Zq0qSJ8vLytHbtWjVr1kzXX3+96tSpo+rVq+vdd9/VBx98oL///e/uy+Z8PYdM5c+0cuVKNWnSRM2bNy8wa+7cuZo3b57HmUqbU79+fb9l8mWuQFg/bzNde+21ql27tmrVqqXY2Fjt2bNHy5YtK/KSHl/NIlPFzeTk+uXfxlesWKHq1avrs88+U4cOHbzO5OksMpHJiVlmpmXLluknP/mJwsLC1LRpU73xxhsaMGCAjh49qvnz5xe6DNVXc8jkfKZAXb9Kz8fPqFVY+Z/e/eGHH2zKlCm2f/9+e/31123QoEHWt29fO3HihJ09e9aeffbZYl8s6qs5ZPJtprS0NDtx4oQ9/fTT5crkyZxAnVVRM2VmZlpWVpYNGDCg3Jk8mUWmipvJ6fVzvU1yTExMiW9q4KtZZCKTk7Meeugh69+/v/vzIb/77rtCnznp6zlkcj5ToK5fZUcBs0tvfd6nTx/77rvvzOzS29j27NnTLl68aB999JE1aNDA7r//fvc72BR3jbiv5pDJ95lc7/RT3LX0vpoTqLMqaqZf//rX7ndEKukaeF/NIlPFzeT0+t1///0evVuXr2aRiUxXalZp777oqzlkcj5ToK7f1aDqxIkTJ17pZ+GupPj4eD399NO65ppr1L59e7Vq1Uq1atVSXl6ePv74Y02fPl0vvPCC6tWrp7179+r2228v8hpaX80hk38zFfX6Kl/NCdRZFT3Tvn37dPvtt6t27drlzlTSLDJV3ExXav3279+v8PDwYl9/5KtZZCLTlZx14MAB3XbbbeVev5LmkMn5TIG6fleNK90Ar6Q1a9ZYly5dbPPmzfaXv/zFBg4c6L5t7ty51qZNG/dnGu3bt8/d6v01h0xkuhrWj0xkCtRZZCJTZc9U2dePTBV7/a4mV3UBGzdunCUkJJjZpQ+369Wrl82ZM8d9u+tttIt7K1lfzyETma6G9SMTmQJ1FpnIVNkzVfb1I1PFXr+ryVX5LohxcXE6efKkpk+fLun/Pqz0oYce0uHDh93LXX/99Y7MIROZrob1IxOZAnUWmchU2TNV9vUjU8Vev6vSlW6ATouPj7ewsDCLj48vdNuXX35pzZs3tzVr1jg2h0xk8vUsMpGpsmfy5SwykamyZ/LlLDJV3Ey+nOXLTFerq6qAff7559asWTPbtm2bmZmdPn3aUlJS7MyZM5adnW1mZtHR0TZkyBDLyMjw+xwykelqWD8ykSlQZ5GJTJU9U2VfPzJV7PW7ml1VlyAGBwerevXqOnHihDIzM/XAAw+odu3aqlevnn71q19p6NChuvnmm7V169YSPy3cV3PIRKarYf3IRKZAnUUmMlX2TJV9/chUsdfvqnalG6DTvvzyS7vxxhvt+uuvt+joaMvNzbW5c+faQw89ZCdPnjQzs8zMTMfmkIlMV8P6kYlMgTqLTGSq7Jkq+/qRqWKv39XqqitgZmZ79uyxWbNmFfhev379LCkp6YrMIROZfD2LTGSq7Jl8OYtMZKrsmXw5i0wVN5MvZ/ky09Xoqixgl1u6dKl17drVvv3224CYQyYy+XoWmchU2TP5chaZyFTZM/lyFpkqbiZfzvJlpqvBVV3A8vLybO7cudauXTvbvXv3FZ9DJjL5ehaZyFTZM/lyFpnIVNkz+XIWmSpuJl/O8mWmq0mQmdmVfh3alWJm2rRpk6699lrdcsstV3wOmcjk61lkIlNlz+TLWWQiU2XP5MtZZKq4mXw5y5eZriZXdQEDAAAAACdVudIBAAAAAOBqQQEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCEUMAAAAABwCAUMAAAAABxCAQMAAAAAh1DAAAAAAMAhFDAAAAAAcAgFDAAAAAAcQgEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCEUMAAAAABwCAUMAAAAABxCAQMAAAAAh1DAAAAAAMAhFDAAAAAAcAgFDAAAAAAcQgEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCEUMAAAAABwCAUMAAAAABxCAQMAAAAAh1DAAAAAAMAhFDAAAAAAcAgFDAAAAAAcQgEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCEUMAAAAABwCAUMAAAAABxCAQMAAAAAh1DAAAAAAMAhFDAAAAAAcAgFDAAAAAAcQgEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCEUMAAAAABwCAUMAAAAABxCAQMAAAAAh1DAAAAAAMAhFDAAAAAAcAgFDAAAAAAcQgEDAAAAAIdQwAAAAADAIRQwAAAAAHAIBQwAAAAAHEIBAwAAAACHUMAAAAAAwCEUMAAAAABwCAUMAAAAABxCAQMAAAAAh1DAAAAAAMAhFDAAAAAAcMj/AxlCH3Ax/X+5AAAAAElFTkSuQmCC\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>nametype</h2>\n",
       "                <div>categorical</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 2</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 0.004</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        45716\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Valid</td>\n",
       "                    <td>45641</td>\n",
       "                    <td>99.836%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Relict</td>\n",
       "                    <td>75</td>\n",
       "                    <td>0.164%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>0</td>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>recclass</h2>\n",
       "                <div>categorical</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 444</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 0.971</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        45716\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>L6</td>\n",
       "                    <td>8285</td>\n",
       "                    <td>18.123%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>H5</td>\n",
       "                    <td>7142</td>\n",
       "                    <td>15.623%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>L5</td>\n",
       "                    <td>4796</td>\n",
       "                    <td>10.491%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>H6</td>\n",
       "                    <td>4528</td>\n",
       "                    <td>9.905%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>H4</td>\n",
       "                    <td>4211</td>\n",
       "                    <td>9.211%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>LL5</td>\n",
       "                    <td>2766</td>\n",
       "                    <td>6.05%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>LL6</td>\n",
       "                    <td>2043</td>\n",
       "                    <td>4.469%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>L4</td>\n",
       "                    <td>1253</td>\n",
       "                    <td>2.741%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>H4/5</td>\n",
       "                    <td>428</td>\n",
       "                    <td>0.936%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>CM2</td>\n",
       "                    <td>416</td>\n",
       "                    <td>0.91%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>0</td>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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pUzJlypQsXbq0b5877rgjdXV1mTBhQpYvX9433t7engkTJqSuri6LFi3qG1+3bl2mTZuW+vr6XHrppdm+ffu+WiMAAMB+YbcBVlVVlS996Ut55plnsmrVqtxzzz1Zs2ZNkuSGG27I6tWrs3r16syYMSNJsmbNmrS2tubpp59Oe3t7rr322vT29qa3tzfXXXddli1bljVr1uTBBx/sO87NN9+cG264IV1dXRkxYkQWL15c0pIBAAAGxm4DrKamJqecckqSZOjQoZk4cWK6u7v7PUhbW1tmzZqVQw89NMcdd1zq6urS0dGRjo6O1NXVZfz48TnkkEMya9astLW1pSiKPPbYY7nkkkuSJLNnz86SJUv2wfIAAAD2H2/7HrD169fnqaeeyrRp05Ikd999d04++eTMmTMnW7ZsSZJ0d3dn7NixffvU1tamu7u73/EXXnghw4cPT1VV1S7jAAAAB7O3DLBXXnklF198ce66664MGzYs8+fPz9q1a7N69erU1NTkpptuSpIURfGmfSuVyh6P705zc3MaGhrS0NCQzZs3v6NFAQAA7I/6DbAdO3bk4osvzuWXX56LLrooSTJ69OgMHjw4gwYNyjXXXJOOjo4kb9zB2rBhQ9++GzduzJgxY/odP+qoo7J169bs3Llzl/HdmTdvXjo7O9PZ2ZmRI0f+8SsGAAAYILsNsKIoMnfu3EycODE33nhj33hPT0/f14888khOOumkJElTU1NaW1uzbdu2rFu3Ll1dXTnttNMyderUdHV1Zd26ddm+fXtaW1vT1NSUSqWSs846Kw8//HCSpKWlJeeff/6+XCcAAMCAq9rd4OOPP54HHnggkydPzpQpU5Ikt99+ex588MGsXr06lUol48aNyze+8Y0kyaRJkzJz5syceOKJqaqqyj333JPBgwcneeM9Y9OnT09vb2/mzJmTSZMmJUnuvPPOzJo1K5///OfzwQ9+MHPnzi1jvQAAAAOmUuzuDVn7qYaGhnR2dg70NAbcuAXf2efnWL/ovH1+DgAAOJi8k155209BBAAAYO8QYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACURYAAAACXpN8A2bNiQs846KxMnTsykSZPyla98JUny4osvprGxMfX19WlsbMyWLVuSJEVR5Prrr09dXV1OPvnkPPnkk33HamlpSX19ferr69PS0tI3/qMf/SiTJ09OXV1drr/++hRFsa/WCQAAMOD6DbCqqqp86UtfyjPPPJNVq1blnnvuyZo1a7Jo0aKcc8456erqyjnnnJNFixYlSZYtW5aurq50dXWlubk58+fPT/JGsC1cuDBPPPFEOjo6snDhwr5omz9/fpqbm/v2a29vL2HJAAAAA6PfAKupqckpp5ySJBk6dGgmTpyY7u7utLW1Zfbs2UmS2bNnZ8mSJUmStra2XHXVValUKjn99NOzdevW9PT0ZPny5WlsbEx1dXVGjBiRxsbGtLe3p6enJy+99FLOOOOMVCqVXHXVVX3HAgAAOBi9o/eArV+/Pk899VSmTZuW5557LjU1NUneiLRNmzYlSbq7uzN27Ni+fWpra9Pd3f2W47W1tW8aBwAAOFhVvd0Gr7zySi6++OLcddddGTZsWL/b7e79W5VKZY/H/1Bzc3Oam5uTJJs3b3676QIAAOy33vIO2I4dO3LxxRfn8ssvz0UXXZQkGT16dHp6epIkPT09GTVqVJI37mBt2LChb9+NGzdmzJgxbzm+cePGN43/oXnz5qWzszOdnZ0ZOXLkH7FUAACAgdVvgBVFkblz52bixIm58cYb+8abmpr6PsmwpaUl559/ft/4/fffn6IosmrVqhxxxBGpqanJ9OnTs2LFimzZsiVbtmzJihUrMn369NTU1GTo0KFZtWpViqLI/fff33csAACAg1G/L0F8/PHH88ADD2Ty5MmZMmVKkuT222/PggULMnPmzCxevDjHHHNMHnrooSTJjBkzsnTp0tTV1eXwww/PvffemySprq7OLbfckqlTpyZJvvCFL6S6ujpJ8vWvfz1XX311XnvttZx77rk599xz9+liAQAABlKlOID++FZDQ0M6OzsHehoDbtyC7+zzc6xfdN4+PwcAABxM3kmvvKNPQQQAAOCPJ8AAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABKIsAAAABK0m+AzZkzJ6NGjcpJJ53UN3bbbbfl6KOPzpQpUzJlypQsXbq077E77rgjdXV1mTBhQpYvX9433t7engkTJqSuri6LFi3qG1+3bl2mTZuW+vr6XHrppdm+ffveXhsAAMB+pd8Au/rqq9Pe3v6m8RtuuCGrV6/O6tWrM2PGjCTJmjVr0tramqeffjrt7e259tpr09vbm97e3lx33XVZtmxZ1qxZkwcffDBr1qxJktx888254YYb0tXVlREjRmTx4sX7aIkAAAD7h34D7Mwzz0x1dfU7OkhbW1tmzZqVQw89NMcdd1zq6urS0dGRjo6O1NXVZfz48TnkkEMya9astLW1pSiKPPbYY7nkkkuSJLNnz86SJUv2zooAAAD2U3v8HrC77747J598cubMmZMtW7YkSbq7uzN27Ni+bWpra9Pd3d3v+AsvvJDhw4enqqpql3EAAICD2R4F2Pz587N27dqsXr06NTU1uemmm5IkRVG8adtKpbLH47vT3NychoaGNDQ0ZPPmzXsyXQAAgP3KHgXY6NGjM3jw4AwaNCjXXHNNOjo6krxxB2vDhg19223cuDFjxozpd/yoo47K1q1bs3Pnzl3Gd2fevHnp7OxMZ2dnRo4cuccLBAAA2F/sUYD19PT0ff3II4/0fUJiU1NTWltbs23btqxbty5dXV057bTTMnXq1HR1dWXdunXZvn17Wltb09TUlEqlkrPOOisPP/xwkqSlpSXnn3/+XlwWAADA/qeqvwcuu+yyrFy5Ms8//3xqa2uzcOHCrFy5MqtXr06lUsm4cePyjW98I0kyadKkzJw5MyeeeGKqqqpyzz33ZPDgwUneeM/Y9OnT09vbmzlz5mTSpElJkjvvvDOzZs3K5z//+Xzwgx/M3LlzS1guAADAwKkUu3tD1n6qoaEhnZ2dAz2NATduwXf2+TnWLzpvn58DAAAOJu+kV/b4UxABAAB4dwQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASQQYAABASfoNsDlz5mTUqFE56aST+sZefPHFNDY2pr6+Po2NjdmyZUuSpCiKXH/99amrq8vJJ5+cJ598sm+flpaW1NfXp76+Pi0tLX3jP/rRjzJ58uTU1dXl+uuvT1EU+2J9AAAA+41+A+zqq69Oe3v7LmOLFi3KOeeck66urpxzzjlZtGhRkmTZsmXp6upKV1dXmpubM3/+/CRvBNvChQvzxBNPpKOjIwsXLuyLtvnz56e5ublvvz88FwAAwMGm3wA788wzU11dvctYW1tbZs+enSSZPXt2lixZ0jd+1VVXpVKp5PTTT8/WrVvT09OT5cuXp7GxMdXV1RkxYkQaGxvT3t6enp6evPTSSznjjDNSqVRy1VVX9R0LAADgYLVH7wF77rnnUlNTkySpqanJpk2bkiTd3d0ZO3Zs33a1tbXp7u5+y/Ha2to3jQMAABzMqvbGQXb3/q1KpbLH47vT3Nyc5ubmJMnmzZv/yJkCAAAMnD26AzZ69Oj09PQkSXp6ejJq1Kgkb9zB2rBhQ992GzduzJgxY95yfOPGjW8a35158+als7MznZ2dGTly5J5MFwAAYL+yRwHW1NTU90mGLS0tOf/88/vG77///hRFkVWrVuWII45ITU1Npk+fnhUrVmTLli3ZsmVLVqxYkenTp6empiZDhw7NqlWrUhRF7r///r5jAQAAHKz6fQniZZddlpUrV+b5559PbW1tFi5cmAULFmTmzJlZvHhxjjnmmDz00ENJkhkzZmTp0qWpq6vL4YcfnnvvvTdJUl1dnVtuuSVTp05NknzhC1/o+2CPr3/967n66qvz2muv5dxzz8255567r9cKAAAwoCrFAfQHuBoaGtLZ2TnQ0xhw4xZ8Z5+fY/2i8/b5OQAA4GDyTnplj16CCAAAwLsnwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEoiwAAAAEpSNdATYP83bsF3SjnP+kXnlXIeAAAYKO6AAQAAlESAAQAAlESAAQAAlESAAQAAlESAAQAAlESAAQAAlESAAQAAlESAAQAAlESAAQAAlORdBdi4ceMyefLkTJkyJQ0NDUmSF198MY2Njamvr09jY2O2bNmSJCmKItdff33q6upy8skn58knn+w7TktLS+rr61NfX5+Wlpa9sBwAAID917u+A/af//mfWb16dTo7O5MkixYtyjnnnJOurq6cc845WbRoUZJk2bJl6erqSldXV5qbmzN//vwkbwTbwoUL88QTT6SjoyMLFy7sizYAAICD0V57CWJbW1tmz56dJJk9e3aWLFnSN37VVVelUqnk9NNPz9atW9PT05Ply5ensbEx1dXVGTFiRBobG9Pe3r63pgMAALDfeVcBVqlU8vGPfzynnnpqmpubkyTPPfdcampqkiQ1NTXZtGlTkqS7uztjx47t27e2tjbd3d39jgMAABysqt7NTo8//njGjBmTTZs2pbGxMSeccEK/2xZF8aaxSqXS7/gfam5u7ou8zZs3v5vpAgAA7Bfe1R2wMWPGJElGjRqVCy+8MB0dHRk9enR6enqSJD09PRk1alSSN+5sbdiwoW/fjRs3ZsyYMf2O/6F58+als7MznZ2dGTly5LuZLgAAwH5hjwPs1Vdfzcsvv9z39YoVK3LSSSelqamp75MMW1pacv755ydJmpqacv/996coiqxatSpHHHFEampqMn369KxYsSJbtmzJli1bsmLFikyfPn0vLg0AAGD/sscvQXzuuedy4YUXJkl27tyZT33qU/mLv/iLTJ06NTNnzszixYtzzDHH5KGHHkqSzJgxI0uXLk1dXV0OP/zw3HvvvUmS6urq3HLLLZk6dWqS5Atf+EKqq6v31roAAAD2O3scYOPHj8+Pf/zjN40feeSRefTRR980XqlUcs899+z2WHPmzMmcOXP2dAoAAAAHpL32MfQAAAC8NQEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQEgEGAABQkqqBngDszrgF39nn51i/6Lx9fg4AAPh97oABAACURIABAACURIABAACURIABAACURIABAACURIABAACURIABAACURIABAACUxB9iBg4aZfwB78Qf8QYA3r0BD7D29vZ8+tOfTm9vb/7qr/4qCxYsGOgp8SfIL+4AAJRhQAOst7c31113Xb773e+mtrY2U6dOTVNTU0488cSBnBYAA8j/EAHgYDagAdbR0ZG6urqMHz8+STJr1qy0tbUJMNgHBuKX2jLOOdC/RJe9Rj/HfeNP4ecIwP5hQAOsu7s7Y8eO7fu+trY2TzzxxADOaM/5jyjv1p/CL7UAHNj8ngN7X6UoimKgTv7QQw9l+fLl+eY3v5kkeeCBB9LR0ZGvfvWrfds0Nzenubk5SfLss8/mhBNOeNNxNm/enJEjR5YzaQ56rif2NtcUe5Prib3J9cTe5HpK1q9fn+eff/4ttxnQO2C1tbXZsGGGM7hNAAAGsElEQVRD3/cbN27MmDFjdtlm3rx5mTdv3lsep6GhIZ2dnftkjvzpcT2xt7mm2JtcT+xNrif2JtfTOzOgfwds6tSp6erqyrp167J9+/a0tramqalpIKcEAACwzwzoHbCqqqrcfffdmT59enp7ezNnzpxMmjRpIKcEAACwzwz43wGbMWNGZsyY8Ucd4+1eogh7wvXE3uaaYm9yPbE3uZ7Ym1xP78yAfggHAADAn5IBfQ8YAADAn5IDPsDa29szYcKE1NXVZdGiRQM9HQ5w48aNy+TJkzNlypQ0NDQM9HQ4wMyZMyejRo3KSSed1Df24osvprGxMfX19WlsbMyWLVsGcIYcaHZ3Td122205+uijM2XKlEyZMiVLly4dwBlyoNiwYUPOOuusTJw4MZMmTcpXvvKVJJ6jePf6u6Y8R729A/oliL29vfmzP/uzfPe7301tbW2mTp2aBx98MCeeeOJAT40D1Lhx49LZ2ZmjjjpqoKfCAej73/9+hgwZkquuuio/+clPkiR/93d/l+rq6ixYsCCLFi3Kli1bcueddw7wTDlQ7O6auu222zJkyJB85jOfGeDZcSDp6elJT09PTjnllLz88ss59dRTs2TJktx3332eo3hX+rum/v3f/91z1Ns4oO+AdXR0pK6uLuPHj88hhxySWbNmpa2tbaCnBfyJOvPMM1NdXb3LWFtbW2bPnp0kmT17dpYsWTIQU+MAtbtrCt6NmpqanHLKKUmSoUOHZuLEienu7vYcxbvW3zXF2zugA6y7uztjx47t+762ttYPnj9KpVLJxz/+8Zx66qlpbm4e6OlwEHjuuedSU1OT5I3/WG3atGmAZ8TB4O67787JJ5+cOXPmeMkYe2z9+vV56qmnMm3aNM9R7BW/f00lnqPezgEdYLt79WSlUhmAmXCwePzxx/Pkk09m2bJlueeee/L9739/oKcEsIv58+dn7dq1Wb16dWpqanLTTTcN9JQ4gLzyyiu5+OKLc9ddd2XYsGEDPR0OAn94TXmOensHdIDV1tZmw4YNfd9v3LgxY8aMGcAZcaD73fUzatSoXHjhheno6BjgGXGgGz16dHp6epK88Xr5UaNGDfCMONCNHj06gwcPzqBBg3LNNdd4nuId27FjRy6++OJcfvnlueiii5J4juKP09815TnqrR3QATZ16tR0dXVl3bp12b59e1pbW9PU1DTQ0+IA9eqrr+bll1/u+3rFihW7fPIYvBtNTU1paWlJkrS0tOT8888f4BlxoPvdL8tJ8sgjj3ie4h0piiJz587NxIkTc+ONN/aNe47i3ervmvIc9fYO6E9BTJKlS5fmb//2b9Pb25s5c+bkc5/73EBPiQPUz3/+81x44YVJkp07d+ZTn/qU64k9ctlll2XlypV5/vnnM3r06CxcuDAXXHBBZs6cmV/+8pc55phj8tBDD/lQBd6x3V1TK1euzOrVq1OpVDJu3Lh84xvf6HsPD/TnBz/4QT7ykY9k8uTJGTTojf//fvvtt2fatGmeo3hX+rumHnzwQc9Rb+OADzAAAIADxQH9EkQAAIADiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoiQADAAAoyf8HJFjzhP87TIIAAAAASUVORK5CYII=\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>mass (g)</h2>\n",
       "                <div>numeric</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 12497</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 27.336</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>0.29</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>131</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        131\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "            <div>\n",
       "                <h3>\n",
       "                    Basic Stats\n",
       "                </h3>\n",
       "\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Mean</td>\n",
       "                    <td>13278.078548601514</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Minimum</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Maximum</td>\n",
       "                    <td>60000000.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Zeros(%)</td>\n",
       "                    <td>19</td>\n",
       "                </tr>\n",
       "\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>1.3</td>\n",
       "                    <td>171</td>\n",
       "                    <td>0.374%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>1.2</td>\n",
       "                    <td>140</td>\n",
       "                    <td>0.306%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>1.4</td>\n",
       "                    <td>138</td>\n",
       "                    <td>0.302%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>None</td>\n",
       "                    <td>131</td>\n",
       "                    <td>0.287%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>2.1</td>\n",
       "                    <td>130</td>\n",
       "                    <td>0.284%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>2.4</td>\n",
       "                    <td>126</td>\n",
       "                    <td>0.276%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>1.6</td>\n",
       "                    <td>120</td>\n",
       "                    <td>0.262%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>0.5</td>\n",
       "                    <td>119</td>\n",
       "                    <td>0.26%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>1.1</td>\n",
       "                    <td>116</td>\n",
       "                    <td>0.254%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>3.8</td>\n",
       "                    <td>114</td>\n",
       "                    <td>0.249%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>131</td>\n",
       "                    <td>0.29%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "        <div class=\"panel_profiler\">\n",
       "\n",
       "\n",
       "            <h3>Quantile statistics</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Minimum</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>5-th percentile</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Q1</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Median</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Q3</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>95-th percentile</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Maximum</td>\n",
       "                    <td>60000000.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Range</td>\n",
       "                    <td>60000000.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Interquartile range</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Descriptive statistics</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Standard deviation</td>\n",
       "                    <td>574988.8764104729</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Coef of variation</td>\n",
       "                    <td>43.30362</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Kurtosis</td>\n",
       "                    <td>6796.170607910884</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Mean</td>\n",
       "                    <td>13278.078548601514</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>MAD</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Skewness</td>\n",
       "                    <td>19</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Sum</td>\n",
       "                    <td>605281210.638</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Variance</td>\n",
       "                    <td>330612207995.77814</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>fall</h2>\n",
       "                <div>categorical</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 2</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 0.004</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        45716\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Found</td>\n",
       "                    <td>44609</td>\n",
       "                    <td>97.579%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>Fell</td>\n",
       "                    <td>1107</td>\n",
       "                    <td>2.421%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>0</td>\n",
       "                    <td>0.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img src=\"data:image/jpeg;base64,iVBORw0KGgoAAAANSUhEUgAAA2AAAAFoCAYAAAAxXpjgAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAIABJREFUeJzt3XuQ1fV9//HX0Y0ah7sVC7NExGWI4I26CIyOlTgEQYtpg4CNguOFjJpRsUlw0qixTSO1NYn1ltkMI1AtO40zcY3K6nhrOlZC10taJRlXA4bdMApEQFIVWc/vD+v+QG6ayOew9vGYccbzOd9zzvuLn9F9+j3nbKVarVYDAADAXrdfrQcAAAD4v0KAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAUMWrUqDzxxBO1HqOoH//4xxkyZEh69eqVZ599drfHLly4MCeffHL37UqlkpdeemlvjwhAYQIMgD/Y0KFD88gjj2y39sGgeOGFF3Lqqafu9nlWrVqVSqWSrVu37o0x97qFCxfm/PPP77791a9+Nbfeems2b96c0aNH/97Pe/7552fhwoV/+IAA1JwAA+D/jNJh98orr2TUqFFFXxOAfZsAA6CIba+SLV++PI2NjenTp08OO+ywXHXVVUmSU045JUnSr1+/9OrVK0899VTefffdfPvb387hhx+egQMHZtasWdm4cWP38y5evDiHH354DjnkkPzt3/7tdq/zrW99K9OmTcu5556bPn36ZOHChVm+fHnGjx+ffv36ZdCgQfnKV76SLVu2dD9fpVLJ7bffnuHDh6d379655ppr8vLLL2f8+PHp06dPpk+fvt3xO/P222+nV69e6erqynHHHZcjjzwySTJ//vwceeSR6d27d0aOHJkf//jHH98fMAA9ggADoLgrrrgiV1xxRTZt2pSXX34506dPT5L89Kc/TZJs2LAhmzdvzvjx47Nw4cIsXLgwjz/+eH71q19l8+bN+cpXvpIkWbFiRS699NLcfffdWbNmTTZu3JjOzs7tXqulpSXTpk3Lhg0b8qUvfSn7779/vve972XdunV56qmn8uijj+b222/f7jGtra15+umns2zZstx4442ZM2dO7r777qxevTrPP/98lixZstPzev+tggceeGA2b96cJPn5z3+el19+OUly5JFH5t///d+zcePGXHfddTn33HOzZs2aPf55ffCtjQD0XAIMgI/FF77whfTr16/7r0svvXSXx37qU5/KSy+9lHXr1qVXr14ZN27cLo+9++67c9VVV2XYsGHp1atXbrjhhjQ3N2fr1q2555578md/9mc5+eSTc8ABB+Rv/uZvUqlUtnv8+PHj84UvfCH77bdfPv3pT+eEE07IuHHjUldXl6FDh+bLX/5y/u3f/m27x8ybNy99+vTJqFGjcvTRR+fzn/98hg0blr59+2by5Ml7/EKNXTn77LMzePDg7LfffpkxY0aGDx+e5cuX/17PBUDPJMAA+Fjce++92bBhQ/dfH7yqtK0FCxbkxRdfzGc/+9mMGTMm999//y6P/c1vfpPDDz+8+/bhhx+erVu35tVXX81vfvObDBkypPu+gw8+OIcccsh2j9/2/iR58cUXc+aZZ+aP//iP06dPn3zjG9/IunXrtjvmsMMO6/77T3/60zvcfv/q1ke1ePHiHH/88d2R+vzzz+/w2gB8sgkwAIobPnx4lixZktdeey3z5s3LtGnT8rvf/W6Hq1dJMnjw4Lzyyivdt3/961+nrq4uhx12WAYNGpSOjo7u+958882sX79+u8d/8DkvueSSfPazn017e3s2bdqU73znO6lWqx/zGe7olVdeycUXX5xbb70169evz4YNG3L00UcXeW0A9h0CDIDi7rrrrqxduzb77bdf+vXrlyTZf//9c+ihh2a//fbLr371q+5jzznnnHzve9/LypUrs3nz5nzjG9/IjBkzUldXl2nTpuUnP/lJ/uM//iNbtmzJddddt8egeeONN9KnT5/06tUrv/zlL3PHHXfs1XN93/uBeeihhyZJ7rzzzjz//PNFXhuAfYcAA6C41tbWjBo1Kr169coVV1yR5ubmHHTQQTn44IPz13/91znppJPSr1+/LFu2LBdccEHOO++8nHLKKTniiCNy0EEH5ZZbbkny3i93vuWWWzJz5swMGjQovXv3zsCBA3PggQfu8rX/8R//Mf/yL/+S3r175+KLL86MGTOKnPPIkSPzV3/1Vxk/fnwOO+yw/Pd//3dOOumkIq8NwL6jUvXeBwA+ITZv3px+/fqlvb09RxxxRK3HAYAduAIGQI/2k5/8JP/zP/+T3/3ud/nqV7+aY445JkOHDq31WACwUwIMgB6tpaUlgwcPzuDBg9Pe3p7m5uadfpkHAOwLvAURAACgEFfAAAAAChFgAAAAhdTVeoCP4o/+6I98sBoAANgnrVq1KuvWrdvtMT0qwIYOHZq2trZajwEAALCDxsbGPR7jLYgAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAArpUb+IGQCA/1uGXv1ArUdgH7Vq/hm1HuH34goYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCG7DbCurq6MHj06Z555ZpJk5cqVGTt2bIYPH54ZM2Zky5YtSZK33347M2bMSENDQ8aOHZtVq1Z1P8cNN9yQhoaGjBgxIg899FD3emtra0aMGJGGhobMnz9/L5waAADAvmW3AXbzzTfnqKOO6r49b968zJ07N+3t7enfv38WLFiQJFmwYEH69++fl156KXPnzs28efOSJCtWrEhzc3NeeOGFtLa25tJLL01XV1e6urpy2WWXZenSpVmxYkWWLFmSFStW7MXTBAAAqL1dBlhHR0ceeOCBXHTRRUmSarWaxx57LNOmTUuSzJ49O/fee2+SpKWlJbNnz06STJs2LY8++miq1WpaWloyc+bMHHjggTniiCPS0NCQ5cuXZ/ny5WloaMiwYcNywAEHZObMmWlpadnb5woAAFBTuwywK6+8MjfeeGP22++9Q9avX59+/fqlrq4uSVJfX5/Ozs4kSWdnZ4YMGZIkqaurS9++fbN+/frt1rd9zK7WAQAAPsl2GmD3339/Bg4cmBNOOKF7rVqt7nBcpVLZ7X0fdX1nmpqa0tjYmMbGxqxdu3YXpwEAALDvq9vZ4pNPPpn77rsvDz74YN56661s2rQpV155ZTZs2JCtW7emrq4uHR0dGTx4cJL3rmCtXr069fX12bp1azZu3JgBAwZ0r79v28fsav2D5syZkzlz5iRJGhsbP56zBgAAqIGdXgG74YYb0tHRkVWrVqW5uTmf+9zncvfdd2fChAm55557kiSLFi3KWWedlSSZOnVqFi1alCS555578rnPfS6VSiVTp05Nc3Nz3n777axcuTLt7e058cQTM2bMmLS3t2flypXZsmVLmpubM3Xq1EKnDAAAUBs7vQK2K3//93+fmTNn5pvf/GZGjx6dCy+8MEly4YUX5rzzzktDQ0MGDBiQ5ubmJMmoUaMyffr0jBw5MnV1dbntttuy//77J0luvfXWTJo0KV1dXbngggsyatSoj/nUAAAA9i2V6s4+kLWPamxsTFtbW63HAACgkKFXP1DrEdhHrZp/Rq1H2MGH6ZXd/h4wAAAAPj4CDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCECDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUsssAe+utt3LiiSfmuOOOy6hRo3LdddclSVauXJmxY8dm+PDhmTFjRrZs2ZIkefvttzNjxow0NDRk7NixWbVqVfdz3XDDDWloaMiIESPy0EMPda+3trZmxIgRaWhoyPz58/fSKQIAAOwbdhlgBx54YB577LH8/Oc/z3PPPZfW1tYsW7Ys8+bNy9y5c9Pe3p7+/ftnwYIFSZIFCxakf//+eemllzJ37tzMmzcvSbJixYo0NzfnhRdeSGtray699NJ0dXWlq6srl112WZYuXZoVK1ZkyZIlWbFiRZmzBgAAqIFdBlilUkmvXr2SJO+8807eeeedVCqVPPbYY5k2bVqSZPbs2bn33nuTJC0tLZk9e3aSZNq0aXn00UdTrVbT0tKSmTNn5sADD8wRRxyRhoaGLF++PMuXL09DQ0OGDRuWAw44IDNnzkxLS8vePl8AAICa2e1nwLq6unL88cdn4MCBmThxYo488sj069cvdXV1SZL6+vp0dnYmSTo7OzNkyJAkSV1dXfr27Zv169dvt77tY3a1DgAA8Em12wDbf//989xzz6WjoyPLly/PL37xix2OqVQqSZJqtbrT+z7q+gc1NTWlsbExjY2NWbt27e7GBQAA2Kd9qG9B7NevX0499dQsW7YsGzZsyNatW5MkHR0dGTx4cJL3rmCtXr06SbJ169Zs3LgxAwYM2G5928fsav2D5syZk7a2trS1teXQQw/9/c8UAACgxnYZYGvXrs2GDRuSJG+++WYeeeSRHHXUUZkwYULuueeeJMmiRYty1llnJUmmTp2aRYsWJUnuueeefO5zn0ulUsnUqVPT3Nyct99+OytXrkx7e3tOPPHEjBkzJu3t7Vm5cmW2bNmS5ubmTJ06dW+fLwAAQM3U7eqONWvWZPbs2enq6sq7776b6dOn58wzz8zIkSMzc+bMfPOb38zo0aNz4YUXJkkuvPDCnHfeeWloaMiAAQPS3NycJBk1alSmT5+ekSNHpq6uLrfddlv233//JMmtt96aSZMmpaurKxdccEFGjRpV4JQBAABqo1Ld2Yex9lGNjY1pa2ur9RgAABQy9OoHaj0C+6hV88+o9Qg7+DC98qE+AwYAAMAfToABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCECDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEJ2GWCrV6/OhAkTctRRR2XUqFG5+eabkyS//e1vM3HixAwfPjwTJ07M66+/niSpVqu5/PLL09DQkGOPPTbPPPNM93MtWrQow4cPz/Dhw7No0aLu9aeffjrHHHNMGhoacvnll6dare6t8wQAAKi5XQZYXV1dbrrppvziF7/IsmXLctttt2XFihWZP39+TjvttLS3t+e0007L/PnzkyRLly5Ne3t72tvb09TUlEsuuSTJe8F2/fXX52c/+1mWL1+e66+/vjvaLrnkkjQ1NXU/rrW1tcApAwAA1MYuA2zQoEH5kz/5kyRJ7969c9RRR6WzszMtLS2ZPXt2kmT27Nm59957kyQtLS2ZNWtWKpVKxo0blw0bNmTNmjV56KGHMnHixAwYMCD9+/fPxIkT09ramjVr1mTTpk0ZP358KpVKZs2a1f1cAAAAn0Qf6jNgq1atyrPPPpuxY8fm1VdfzaBBg5K8F2mvvfZakqSzszNDhgzpfkx9fX06Ozt3u15fX7/DOgAAwCdV3Z4O2Lx5c774xS/m+9//fvr06bPL43b2+a1KpfKR1z+oqakpTU1NSZK1a9fuaVwAAIB91m6vgL3zzjv54he/mC996Uv5i7/4iyTJYYcdljVr1iRJ1qxZk4EDByZ57wrW6tWrux/b0dGRwYMH73a9o6Njh/UPmjNnTtra2tLW1pZDDz30DzhVAACA2tplgFWr1Vx44YU56qijctVVV3WvT506tfubDBctWpSzzjqre33x4sWpVqtZtmxZ+vbtm0GDBmXSpEl5+OGH8/rrr+f111/Pww8/nEmTJmXQoEHp3bt3li1blmq1msWLF3c/FwAAwCfRLt+C+OSTT+af//mfc8wxx+T4449PknznO9/J1VdfnenTp2fBggX5zGc+kx/96EdJkilTpuTBBx9MQ0NDDj744Nx5551JkgEDBuSaa67JmDFjkiTXXnttBgwYkCS54447cv755+fNN9/M5MmTM3ny5L16sgAAALVUqfagX77V2NiYtra2Wo8BAEAhQ69+oNYjsI9aNf+MWo+wgw/TKx/qWxABAAD4wwkwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCECDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFDILgPsggsuyMCBA3P00Ud3r/32t7/NxIkTM3z48EycODGvv/56kqRarebyyy9PQ0NDjj322DzzzDPdj1m0aFGGDx+e4cOHZ9GiRd3rTz/9dI455pg0NDTk8ssvT7Va3RvnBwAAsM/YZYCdf/75aW1t3W5t/vz5Oe2009Le3p7TTjst8+fPT5IsXbo07e3taW9vT1NTUy655JIk7wXb9ddfn5/97GdZvnx5rr/++u5ou+SSS9LU1NT9uA++FgAAwCfNLgPslFNOyYABA7Zba2lpyezZs5Mks2fPzr333tu9PmvWrFQqlYwbNy4bNmzImjVr8tBDD2XixIkZMGBA+vfvn4kTJ6a1tTVr1qzJpk2bMn78+FQqlcyaNav7uQAAAD6pPtJnwF599dUMGjQoSTJo0KC89tprSZLOzs4MGTKk+7j6+vp0dnbudr2+vn6HdQAAgE+yuo/jSXb2+a1KpfKR13emqakpTU1NSZK1a9f+gZMCAADUzke6AnbYYYdlzZo1SZI1a9Zk4MCBSd67grV69eru4zo6OjJ48ODdrnd0dOywvjNz5sxJW1tb2tracuihh36UcQEAAPYpHynApk6d2v1NhosWLcpZZ53Vvb548eJUq9UsW7Ysffv2zaBBgzJp0qQ8/PDDef311/P666/n4YcfzqRJkzJo0KD07t07y5YtS7VazeLFi7ufCwAA4JNql29BPOecc/LEE09k3bp1qa+vz/XXX5+rr74606dPz4IFC/KZz3wmP/rRj5IkU6ZMyYMPPpiGhoYcfPDBufPOO5MkAwYMyDXXXJMxY8YkSa699truL/a44447cv755+fNN9/M5MmTM3ny5L19rgAAADVVqfagX8DV2NiYtra2Wo8BAEAhQ69+oNYjsI9aNf+MWo+wgw/TKx/pLYgAAAD8/gQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCECDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFBIXa0H6OmGXv1ArUdgH7Zq/hm1HgEAgH1Iza+Atba2ZsSIEWloaMj8+fNrPQ4AAMBeU9MA6+rqymWXXZalS5dmxYoVWbJkSVasWFHLkQAAAPaamgbY8uXL09DQkGHDhuWAAw7IzJkz09LSUsuRAAAA9pqaBlhnZ2eGDBnSfbu+vj6dnZ01nAgAAGDvqemXcFSr1R3WKpXKdrebmprS1NSUJPnlL3+ZxsbGIrNta+3atTn00EN3et8fFZ6FnqWx8bpd3re7fQV/CHuLvcXeYm/Y077ysxa7srufs5La/Dtr1apVezympgFWX1+f1atXd9/u6OjI4MGDtztmzpw5mTNnTunRttPY2Ji2traazsAnj33F3mJvsbfYW+wN9hV7y766t2r6FsQxY8akvb09K1euzJYtW9Lc3JypU6fWciQAAIC9pqZXwOrq6nLrrbdm0qRJ6erqygUXXJBRo0bVciQAAIC9pua/iHnKlCmZMmVKrcfYrVq/BZJPJvuKvcXeYm+xt9gb7Cv2ln11b1WqO/smDAAAAD52Nf0MGAAAwP8lAmwbXV1dGT16dM4888wd7nv77bczY8aMNDQ0ZOzYsR/qKybhfbvbW9/97nczcuTIHHvssTnttNPyyiuv1GBCeqrd7a333XPPPalUKvvkN0Gxb9rTvvrXf/3XjBw5MqNGjcpf/uVfFp6Onmx3e+vXv/51JkyYkNGjR+fYY4/Ngw8+WIMJ6YmGDh2aY445Jscff/xOf2VVtVrN5ZdfnoaGhhx77LF55plnajDl/yfAtnHzzTfnqKOO2ul9CxYsSP/+/fPSSy9l7ty5mTdvXuHp6Ml2t7dGjx6dtra2/Nd//VemTZuWr3/964Wnoyfb3d5KkjfeeCP/9E//lLFjxxacip5ud/uqvb09N9xwQ5588sm88MIL+f73v194Onqy3e2tb3/725k+fXqeffbZNDc359JLLy08HT3Z448/nueee26n/7Nx6dKlaW9vT3t7e5qamnLJJZfUYML/T4D9r46OjjzwwAO56KKLdnp/S0tLZs+enSSZNm1aHn300Z3+Imn4oD3trQkTJuTggw9OkowbNy4dHR0lx6MH29PeSpJrrrkmX//613PQQQcVnIyebE/76oc//GEuu+yy9O/fP0kycODAkuPRg+1pb1UqlWzatClJsnHjxh1+Nyz8vlpaWjJr1qxUKpWMGzcuGzZsyJo1a2o2jwD7X1deeWVuvPHG7Lffzv9IOjs7M2TIkCTvfX1+3759s379+pIj0kPtaW9ta8GCBZk8eXKBqfgk2NPeevbZZ7N69erdvj0RPmhP++rFF1/Miy++mJNOOinjxo1La2tr4Qnpqfa0t771rW/lrrvuSn19faZMmZJbbrml8IT0VJVKJZ///OdzwgknpKmpaYf7t/05Pknq6+vT2dlZcsTtCLAk999/fwYOHJgTTjhhl8fs7GpXpVLZm2PxCfBh9tb77rrrrrS1teVrX/tagcno6fa0t959993MnTs3N910U+HJ6Mk+zL+ztm7dmvb29jzxxBNZsmRJLrroomzYsKHglPREH2ZvLVmyJOeff346Ojry4IMP5rzzzsu7775bcEp6qieffDLPPPNMli5dmttuuy0//elPt7t/X/s5XoDlvX9o9913X4YOHZqZM2fmsccey7nnnrvdMfX19Vm9enWS9/7js3HjxgwYMKAW49KDfJi9lSSPPPJI/u7v/i733XdfDjzwwBpMSk+zp731xhtv5Pnnn8+pp56aoUOHZtmyZZk6daov4mC3Pux/D88666x86lOfyhFHHJERI0akvb29RhPTU3yYvbVgwYJMnz49STJ+/Pi89dZbWbduXS3GpYd5/+2qAwcOzJ//+Z9n+fLl292/7c/xyXtvh63pW1yrbOfxxx+vnnHGGTus33rrrdUvf/nL1Wq1Wl2yZEn17LPPLj0aPdyu9tYzzzxTHTZsWPXFF1+swVR8Euxqb23rT//0T6v/+Z//WWgiPgl2ta+WLl1anTVrVrVarVbXrl1bra+vr65bt670ePRgu9pbp59+evXOO++sVqvV6ooVK6qDBg2qvvvuu4Wno6fZvHlzddOmTd1/P378+OrSpUu3O+b++++vnn766dV33323+tRTT1XHjBlTi1G7uQK2G9dee23uu+++JMmFF16Y9evXp6GhId/97nczf/78Gk9HT7bt3vra176WzZs35+yzz87xxx+fqVOn1ng6erJt9xZ8XLbdV5MmTcohhxySkSNHZsKECfmHf/iHHHLIITWekJ5q271100035Yc//GGOO+64nHPOOVm4cKGPe7BHr776ak4++eQcd9xxOfHEE3PGGWfk9NNPzw9+8IP84Ac/SJJMmTIlw4YNS0NDQy6++OLcfvvtNZ25Uq36Kj8AAIASXAEDAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCECDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCECDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAEAhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCECDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhQgwAACAQgQYAABAIQIMAACgEAEGAABQiAADAAAoRIABAAAUIsAAAAAKEWAAAACFCDAAAIBCBBgAAECyma5RAAAAWUlEQVQhAgwAAKAQAQYAAFCIAAMAAChEgAEAABQiwAAAAAoRYAAAAIUIMAAAgEIEGAAAQCECDAAAoBABBgAAUIgAAwAAKESAAQAAFCLAAAAAChFgAAAAhfw/kfztrrVJGHAAAAAASUVORK5CYII=\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img src=\"data:image/jpeg;base64,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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>year</h2>\n",
       "                <div>date</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 265</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 0.58</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>0.63</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>288</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        45428\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        288\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/2003 12:00:00 AM</td>\n",
       "                    <td>3323</td>\n",
       "                    <td>7.269%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/1979 12:00:00 AM</td>\n",
       "                    <td>3046</td>\n",
       "                    <td>6.663%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/1998 12:00:00 AM</td>\n",
       "                    <td>2697</td>\n",
       "                    <td>5.899%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/2006 12:00:00 AM</td>\n",
       "                    <td>2456</td>\n",
       "                    <td>5.372%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/1988 12:00:00 AM</td>\n",
       "                    <td>2296</td>\n",
       "                    <td>5.022%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/2002 12:00:00 AM</td>\n",
       "                    <td>2078</td>\n",
       "                    <td>4.545%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/2004 12:00:00 AM</td>\n",
       "                    <td>1940</td>\n",
       "                    <td>4.244%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/2000 12:00:00 AM</td>\n",
       "                    <td>1792</td>\n",
       "                    <td>3.92%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/1997 12:00:00 AM</td>\n",
       "                    <td>1696</td>\n",
       "                    <td>3.71%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>01/01/1999 12:00:00 AM</td>\n",
       "                    <td>1691</td>\n",
       "                    <td>3.699%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>288</td>\n",
       "                    <td>0.63%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img src=\"data:image/jpeg;base64,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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>reclat</h2>\n",
       "                <div>numeric</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 13169</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 28.806</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>16.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>7315</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        7315\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "            <div>\n",
       "                <h3>\n",
       "                    Basic Stats\n",
       "                </h3>\n",
       "\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Mean</td>\n",
       "                    <td>-39.1225803114242</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Minimum</td>\n",
       "                    <td>-87.36667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Maximum</td>\n",
       "                    <td>81.16667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Zeros(%)</td>\n",
       "                    <td>6438</td>\n",
       "                </tr>\n",
       "\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>None</td>\n",
       "                    <td>7315</td>\n",
       "                    <td>16.001%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>0.0</td>\n",
       "                    <td>6438</td>\n",
       "                    <td>14.083%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-71.5</td>\n",
       "                    <td>4761</td>\n",
       "                    <td>10.414%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-84.0</td>\n",
       "                    <td>3040</td>\n",
       "                    <td>6.65%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-72.0</td>\n",
       "                    <td>1506</td>\n",
       "                    <td>3.294%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-79.68333</td>\n",
       "                    <td>1130</td>\n",
       "                    <td>2.472%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-76.71667</td>\n",
       "                    <td>680</td>\n",
       "                    <td>1.487%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-76.18333</td>\n",
       "                    <td>539</td>\n",
       "                    <td>1.179%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-84.21667</td>\n",
       "                    <td>263</td>\n",
       "                    <td>0.575%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-86.36667</td>\n",
       "                    <td>226</td>\n",
       "                    <td>0.494%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>7315</td>\n",
       "                    <td>16.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "        <div class=\"panel_profiler\">\n",
       "\n",
       "\n",
       "            <h3>Quantile statistics</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Minimum</td>\n",
       "                    <td>-87.36667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>5-th percentile</td>\n",
       "                    <td>-87.36667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Q1</td>\n",
       "                    <td>-87.36667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Median</td>\n",
       "                    <td>-87.36667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Q3</td>\n",
       "                    <td>-87.36667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>95-th percentile</td>\n",
       "                    <td>-87.36667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Maximum</td>\n",
       "                    <td>81.16667</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Range</td>\n",
       "                    <td>168.53334</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Interquartile range</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Descriptive statistics</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Standard deviation</td>\n",
       "                    <td>46.37851135669318</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Coef of variation</td>\n",
       "                    <td>-1.18547</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Kurtosis</td>\n",
       "                    <td>-1.4768000635301335</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Mean</td>\n",
       "                    <td>-39.1225803114242</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>MAD</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Skewness</td>\n",
       "                    <td>6438</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Sum</td>\n",
       "                    <td>-1502346.2065390009</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Variance</td>\n",
       "                    <td>2150.966315662918</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>reclong</h2>\n",
       "                <div>numeric</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 13795</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 30.175</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>16.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>7315</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        7315\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "            <div>\n",
       "                <h3>\n",
       "                    Basic Stats\n",
       "                </h3>\n",
       "\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Mean</td>\n",
       "                    <td>61.07431852623698</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Minimum</td>\n",
       "                    <td>-165.43333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Maximum</td>\n",
       "                    <td>354.47333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Zeros(%)</td>\n",
       "                    <td>6214</td>\n",
       "                </tr>\n",
       "\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>None</td>\n",
       "                    <td>7315</td>\n",
       "                    <td>16.001%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>0.0</td>\n",
       "                    <td>6214</td>\n",
       "                    <td>13.593%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>35.66667</td>\n",
       "                    <td>4985</td>\n",
       "                    <td>10.904%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>168.0</td>\n",
       "                    <td>3040</td>\n",
       "                    <td>6.65%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>26.0</td>\n",
       "                    <td>1506</td>\n",
       "                    <td>3.294%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>159.75</td>\n",
       "                    <td>657</td>\n",
       "                    <td>1.437%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>159.66667</td>\n",
       "                    <td>637</td>\n",
       "                    <td>1.393%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>157.16667</td>\n",
       "                    <td>542</td>\n",
       "                    <td>1.186%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>155.75</td>\n",
       "                    <td>473</td>\n",
       "                    <td>1.035%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>160.5</td>\n",
       "                    <td>263</td>\n",
       "                    <td>0.575%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>7315</td>\n",
       "                    <td>16.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "        <div class=\"panel_profiler\">\n",
       "\n",
       "\n",
       "            <h3>Quantile statistics</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Minimum</td>\n",
       "                    <td>-165.43333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>5-th percentile</td>\n",
       "                    <td>-165.43333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Q1</td>\n",
       "                    <td>-165.43333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Median</td>\n",
       "                    <td>-165.43333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Q3</td>\n",
       "                    <td>-165.43333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>95-th percentile</td>\n",
       "                    <td>-165.43333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Maximum</td>\n",
       "                    <td>354.47333</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Range</td>\n",
       "                    <td>519.90666</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Interquartile range</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Descriptive statistics</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Standard deviation</td>\n",
       "                    <td>80.64729807908505</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Coef of variation</td>\n",
       "                    <td>1.32048</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Kurtosis</td>\n",
       "                    <td>-0.7312421386000167</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Mean</td>\n",
       "                    <td>61.07431852623698</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>MAD</td>\n",
       "                    <td>0.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Skewness</td>\n",
       "                    <td>6214</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Sum</td>\n",
       "                    <td>2345314.9057260263</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Variance</td>\n",
       "                    <td>6503.986687456795</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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A/x0aPxtd4XlTw/q5MBMAAACg6tADBgAAAABuQgEGAAAAAG5CAQYAAAAAbkIBBgAAAABuQgEGAAAAAG5CAQYAAAAAbkIBBgAAAABuQgEGAAAAAG5CAQYAAAAAblLuAiwoKEj16tVT69atnWmnT5+Wv7+/fH195e/vr6ysLEmSmWny5Mny8fFR27ZttXPnTmeeyMhI+fr6ytfXV5GRkS5oCgAAAABUb+UuwMaNG6e4uLhC08LCwtSzZ0+lpKSoZ8+eCgsLkyTFxsYqJSVFKSkpCg8P1+OPPy7pSsEWGhqqHTt2KCkpSaGhoU7RBgAAAAA/V+UuwH7/+9/L09Oz0LSoqCgFBgZKkgIDA7V69Wpn+tixY+Xh4aGuXbvqzJkzyszMVHx8vPz9/eXp6ak6derI39//mqIOAAAAAH5uXPIM2LFjx+Tl5SVJ8vLy0vHjxyVJGRkZatCggfM5b29vZWRkFDsdAAAAAH7OavyUwc3smmkeHh7FTi9KeHi4wsPDJUknTpxwbYIAAAAA4EYu6QG79dZblZmZKUnKzMxUvXr1JF3p2UpLS3M+l56ervr16xc7vSjjx49XcnKykpOTVbduXVekCwAAAABVwiUFWP/+/Z2RDCMjIzVgwABn+pIlS2Rm2r59u2rXri0vLy/17t1bCQkJysrKUlZWlhISEtS7d29XpAIAAAAA1Va5b0EcMWKENm/erJMnT8rb21uhoaF69tlnFRAQoIiICDVs2FArV66UJPXt21cxMTHy8fFRzZo1tXjxYkmSp6enQkJC1LlzZ0nS7NmzrxnYAwAAAAB+bspdgC1fvrzI6YmJiddM8/Dw0KJFi4r8fFBQkIKCgsr79QAAAABw3XLJLYgAAAAAgNJRgAEAAACAm1CAAQAAAICbUIABAAAAgJtQgAEAAACAm5R7FESgqjV+NrrC86aG9XN5HAAAAKCs6AEDAAAAADehAAMAAAAAN+EWRMAFuJ0RAAAAZUEPGAAAAAC4CT1gQDVT0d40etIAAACqP3rAAAAAAMBNKMAAAAAAwE0owAAAAADATSjAAAAAAMBNKMAAAAAAwE0YBRH4meJvkwEAAFQ/FGAASuWqofEpCgEAwH87CjAA1yVXFXMUhQAAwJ2q/BmwuLg4NWvWTD4+Pgoh/YtPAAAgAElEQVQLC6vqdAAAAADgJ1OlPWC5ubmaOHGi1q9fL29vb3Xu3Fn9+/dXy5YtqzItAKgQetMAAEBpqrQAS0pKko+Pj5o0aSJJGj58uKKioijAAPxXc2UhR1EIAED1UqUFWEZGhho0aOC89vb21o4dO6owIwBAUaprUVgdB4ipjs8nkpN7c6pMLHKqWCxy+uljXQ85XS88zMyq6stXrlyp+Ph4vfvuu5KkpUuXKikpSa+//rrzmfDwcIWHh0uS9u3bp+bNm1dJrhV14sQJ1a1bt9rEcWUscnJvHFfGqo45uTIWObk3jitjVcecXBmLnNwbx5WxqmNOroxFTu6N48pY5FS9pKam6uTJkyV/yKrQZ599Zr169XJev/jii/biiy9WYUau16lTp2oVx5WxyMm9cVwZqzrm5MpY5OTeOK6MVR1zcmUscnJvHFfGqo45uTIWObk3jitjkdP1p0pHQezcubNSUlJ06NAhZWdna8WKFerfv39VpgQAAAAAP5kqfQasRo0aeuONN9S7d2/l5uYqKChIrVq1qsqUAAAAAOAnc8PcuXPnVmUCvr6+mjRpkqZMmaLf//73VZnKT6ZTp07VKo4rY5GTe+O4MlZ1zMmVscjJvXFcGas65uTKWOTk3jiujFUdc3JlLHJybxxXxiKn60uVDsIBAAAAAP9NqvQZMAAAAAD4b0IBBregoxXSz3c9yG/Xz7V91ZGrl3V1+u2qUy4/pf+WduL6wToJd6EA+xlZv369Fi5cWNVpFHLhwgVJkoeHRxVnUpgrd7L/LTvsyrRz165dunjxYrVbD/JV9jc8cuSIpOq3nkvVb/10VT55eXkuibt3715dunSpWv12ly9fruoUflIXL16U5Jrt5auvvnK2P1cws2q3zUjVbzuuTly9DlQ3WVlZOnfunEtjumJ9yt+OK+vAgQM6deqUS2JdTyjAKshVO8Pdu3dr79692rt3b6XiJCQkKDg4WNHR0UpLS3NJbpW1Zs0aBQcHa/jw4YqJianUDnLz5s3OH+yurH/+85/69NNPJUm5ubnVIpYr25eVlXXNyWlFJCUlaceOHdqxY4ekip8sJSQkKDAwUIcOHap0Tq505MiRQoVTRZdZfHy87rjjDn344YeuTE9S5dapS5cuSXJ9UVjRfd8XX3yh77//Xh4eHpXefyYmJurxxx/X4sWLtWbNGkmqUNz4+Hj94Q9/qDb7TEnasGGDRo8erdmzZ2vp0qWVirV+/Xo9+uijev7557Vly5ZKxTp69KhzQa0yoqOj9dhjj2nYsGH69NNPlZOTU+FY8fHxeuCBB7Rp0yZJldte1q9fr6ioKGd7qeg66qrlJEkHDx7UmTNndObMmUrto67mqvOXysTZs2ePMjIyKp2DK9eBjRs3asqUKYqIiNBXX31Vqby++uor7dq1SwcOHKhUnNjYWPXr10+PPPKInn/++UrFkqT9+/dLqvxxIS4uTq+99pp++OGHSsfp06eP9u3bJ6ny52TXFbf8tbGfmby8POffW7dutW3bttl3331X7jgxMTHm7e1tTzzxhLVq1cree++9CuUTFxdnHTt2tKVLl9qIESNs1apV1+RZHhs3brTZs2dbVFSU/etf/6pQjG+//dbq169v27ZtswULFtgf//hHmzx5su3bt6/cseLi4qxDhw72ySefFJqem5tboVgeHh7WvXv3cs/7U8VyZfvWrl1rgwYNsjNnzlQ6J29vb5s6daq1b9/e5syZU6E4UVFR1rlzZ9uxY4eZVaxNV+f1xBNP2Jtvvuksr4qs57GxsdamTRsbPnx4oT/wWN5YsbGx5ufnZ48++qiFhobapUuXKtXGhIQEe/nll23evHkVjmFmFh0dbePHj7dHH33Ujh8/bmYV3x98/vnnFh8fb+vXr69wPvnbSo8ePez777+vVD6bNm2ypk2b2vvvv29Lly613r172yuvvFLuOGvWrDE/Pz/7/PPPK5TH1VyxbsbExFiLFi1s8eLF9vbbb9vo0aNt9+7dFconJibG2rVrZ3/9619t9uzZNn369ArFMTNbt26d9e3bt0LHuYJiY2OtefPmtmXLFgsJCbGhQ4fayZMnKxQrPj7eOnfubMOHDzd/f/8K55SXl2dnzpyx3/72t+bh4WEff/yx8155t2VXLSezK8uqdevW9uyzz1rXrl3tq6++cvItL1dsw66MExsbaz4+Pvb111870yrSLletA/k5tWrVyhYuXGgPPPCALVy4sMKx1qxZYx06dLAHHnjAgoODbfXq1RWK88knn1irVq0sNjbWPvvsMxs/fnyh98u7zBISEuzXv/61LV68uEL55IuJibG2bdvapk2brnmvPDnl/37du3e3Pn36VCqn6xEFWCW88sor1r17dwsMDLQBAwbYF198Uab58vLy7Pz583b//fdbVFSUmV3ZsTVt2tTeeuutcuWQnp5u3bt3ty1btpiZWWRkpLVu3dpSU1PL15j/3/r1661JkyY2d+5cmz59unXv3t3WrVtX7jhffvmlBQQEOK+/+OIL+9Of/mRTp061tLS0MsfZunWr3XTTTc5JyNmzZ+3s2bPlzsfsysGxa9eutn79erv//vvtgw8+qFAcV8ZyZftiY2Otffv2tnnz5grNb3Zl3fzxxx9t6NChtmzZMjMzO3LkiLVt29Zmz55d7nh9+/Y1X19fMzM7deqUhYSE2B/+8AfbsGGDnThxolyxtm7dar6+vvb666/b/PnzrUmTJrZ8+XIn77LavHmz3XnnnbZx40YzMxsyZIgdPnzYeb+ssT755BNr3769bd++3Q4cOGBt27at1ElSfHy8tWrVyt5//31r06aNLViwwHmvPCeC69ats3bt2tn69ett0KBBNnLkyHLnki86Otratm1r06dPt759+9ratWud98raxvPnz9uzzz5rK1eutKCgIOvTp49duHChXDEKevfdd+3tt982M7OLFy/aU089ZU2bNrWwsLAyx7h06ZL17NnTfve735mZ2cmTJ+3VV1+16dOn29dff22XL18uV06uWDdPnTplI0eOtPj4eOf1iBEjbM2aNeXKxcwsLS3NBg8e7OwLVq1aZUOHDrX169fbp59+Wq5YMTEx1qZNG9u2bVu58yjo4sWLFhQUZB9++KEzbeTIkfaXv/yl3LE+/fRT8/b2tqSkJDMze+CBB+zPf/5zpfKLiIiwqVOnWu3atS0yMrLc87tqOZmZHTp0yNq1a2dbt241M7N58+ZZrVq1nPaWZ3/gim3YlXE2btxovr6+zrr5448/mtl/2lTWWK5aB/Ly8uzQoUPm5+dniYmJZma2bNkyCwoKsm3bttk333xTrniff/65tWjRwr766iu7ePGizZ8/32bOnFnuvMzMPv74Y3vxxRfNzGzPnj3WvHlzmzt3rv3xj38sd6zY2Fhr166djR492l566SUzq9j+95tvvrE77rjD3nzzTTO7su/8+uuvbdeuXc5nyhL3k08+scaNG1tycrKZXTkOr1y5ssJ5XY8owCpo9+7dNmDAADMzmzVrlj3wwAOWm5tr2dnZZY4REhJiS5cudeb55z//aY0bN7b333+/TPOfP3/ezMy5wn358mW7cOGCTZo0yf7xj3+YWfmv4L311lv2wgsvOPE/+ugja9WqlUVHR5crTnZ2tvn5+TkbqZlZcnKyTZ8+3dnJlWUj27VrlzVr1sw+/PBD+/77761Xr142ZMgQ6969u+3Zs6fMcVJTU+2ee+6xDRs2mNmV4nnWrFllnv+niuWq9h0+fNg6derk7FhPnTply5cvt9jY2Ar1Yr7yyiu2aNEi5+CYlpZmrVq1stDQ0HLH6tGjh/3mN7+xHj162Kuvvmpz5syx0aNHOwfwsi6zFStW2OTJk53XmzZtsjp16tiKFSvKNH9eXp5lZ2fb3//+d+fE5sCBA+bp6WmTJk2ywYMH26lTp8qc0+rVq+2f//yn83rWrFn24IMP2rlz58qUT0GXLl2yAQMGOIX8qlWrbNGiRRYbG+t8pizb8tmzZ+3BBx905vvqq69s5MiRtmjRIjt48KDT+1QWX3zxhXXq1Mk+++wzMzP74x//aOvWrXP2N2alL6ecnBwzu9Ijnl/UDBs2zPr06VOh5WRmtmjRImvZsqUzf0hIiC1cuNACAgLKta5nZGTYkCFDbMiQIfb73//e5s2bZxMnTjR/f3/buXNnuXKq7LqZb/v27ZaZmen81i+88IKFhISUK0a+/ItwJ06csI4dO9ro0aPtlVdesbZt2xY6eS7JsWPHrFevXvbEE0+YmVlWVpa9+eab9v7771eo0Dh48KCdPXvWWRdeeOGFQr3rZS18T5w4Ueg3ev/9923ixInO6/Lsh/PX0TfeeMM+/vhjS0pKstq1a9szzzxjzzzzjJmVvu25ejmdPHnSgoKCnP3v+fPn7Te/+Y01a9bMvv322zLHccU27Mo4ly5dsscee8xGjx5teXl5lp6ebhMmTLDp06dbaGioZWVllbltrlwHzP6zvWRkZJi3t7cFBQXZo48+ao8++mi5evw2btxo8+fPd15/9dVXds8999jx48fLfT728ccfW/v27W3+/PnWqFEjmzVrln322WfWsmXLQvub0mzatMnat29vycnJlpmZabfeeqtzHlZeX375pU2cONHeeustW7dund17770WEBBgvXr1skcffbTMcfbs2eMUXz/88IOFhITYtGnTKpTT9YoCrIyu3phTUlJs8uTJNmnSJLv//vvt0qVLZnblKtjFixfLFHPRokU2bty4Qj0en3zyiXXq1MkOHjxY4rz/+Mc/bOzYsYUO1vnmzZtn3bp1K1MOV1u8eHGhniszs48++sj8/f1t7969ZYqRfxCNi4uzwMBA+9vf/ua899JLL9nDDz9caozNmzc7vXpffvmldejQwW666SZ74403LDs725599ln73e9+V6Yd2g8//GBmV3as+b744gvz9vZ2iqiyclUsV7Yv35w5c+y5556zpUuXWseOHW3cuHH28MMPW79+/ZwdXVktW7bMBg0aVKidqampdtdddzmFYWnyT2zMzLp3717oKmD+CXN5DpIJCQk2atSoQtM2bdpkd955Z4VuI/v+++/t6aeftueff94uXbpk48ePL3Q7Ylnlr+/79u2zwMBA54ppeXpR8vLybMaMGbZw4UJLTEy022+/3R5++GHz8/OzESNGlCuf/J7FkydPWoMGDWzq1Kk2adIkCw4OdpZTWZb7jh07nBOuU6dOmZeXlz344IM2atQomzJlSqnzr1692iZOnOj0dhVcl/OLMLMrPXalXeDZs2ePxcTEWGZmppmZTZo0yXx8fGzcuHHWrVs3O3v2rD388MOWkJBQal4FHT161O6++257/vnnnWkzZ860cePGlStOZdbNffv22ZYtW5wLagX95S9/sT/84Q9mdmWfX9py2r17t23atKnQ8WPfvn2F5luwYIFzka0sFi9ebLNmzbIXXnjB2rdvbxMmTLCnn37aWrduXe6TuKu3iRUrVthzzz1nZldONuPj40tcN6OjowvdzpW/Tn333XfWvHlzCw8PL3MuV5/s//vf/3YKqD//+c9Wo0aNQif0pXHFcjp//rxdvnzZ6aENDQ213bt324wZM+zVV1+1l19+2caNG2fZ2dlu2YZdHcfsShE+YcIEmzJlijVr1sxefvlli4iIsKeeesqeeuopy8nJcds6kJycbMuXL7f9+/c7cY4cOeL00h47dswmT55sERERpcY6ffq08+/8bTknJ8cyMzPtvvvuc84LC95tUZR9+/bZJ5984uw3V65caX/7298K3cmwf/9+GzNmTJkv+K9du9a2b9/uvF6wYIEFBQWV626bghfvdu/ebVOnTi1019bRo0etV69eRd6WWNCGDRuccx+z//x+qamp5u3tbR999FGZc7reUYCVQcGdwfnz5+3SpUuWl5dnY8eOtXvuuceOHj1qZmbvvPOOdezYsdRbqwrGCwgIsBEjRtiZM2ecjenhhx+2Q4cOFTv/1q1brUWLFiVelenXr1+hW5jK46677rLHHnvMeZ2VlWWTJk0qscAoeLKd7/Tp07ZkyRIbO3asvfbaa2ZmtmTJEgsMDHSu7BUlISHB6tatawEBAc4OYteuXYV608yutLG0nVlcXJwFBQU5O8S8vDxng3/jjTcsODi4zFfdXBXLle0zK3xiGxoaah07dix0e8C0adMK3fZTVpMnTzZ/f39LT093fq+goKByPZNScL3Iy8tz1v3IyEh79NFHy9VjbGbm7+9/zYnuvHnzSr0FNCEhwYKDgy00NLTQLZrp6emFPjdo0KBit9+C221xJwgjR4600aNHl5hLQQXXl6ioKJswYYL16NHDJk2a5Ezv1KmTs/0U55///Kdt2rTJedYuLy/PLl686PT0mV35PfNPMEty7NgxJ4bZlZPmhQsXOj3zhw8ftt///veFDqJX27Bhg7Vs2fKanpaCy+3RRx+1Bg0a2B133FHiVf2YmBhr1aqVBQQE2O9+9ztnm1i/fr1t377dWYemTZtmS5cuLbV9V8t/XjI/t7/+9a82Y8aMcl9Br8i6uXbtWmvVqpX16tXL+vfv79zGnt+m1atX2/z58y0hIcE6d+5sKSkpxcbKv0UsICDARo0a5dwOe7U5c+aU6Xmwgu2PjIy0++67z15//XVn2ssvv1zoSn9pMYqybNkye+aZZ+zvf/+73XnnnbZ///5iPxsdHW0+Pj7XnKDl7/+ioqJs2LBhZXr+Kjo62gYOHGhjxoyxTZs2WW5urh06dMiCg4Pt73//u7Vo0cLmzZtnHh4ehS4gltbGii4nsyvHlx49ethjjz1ma9assaNHj9qwYcNswoQJ9tBDD1l2drbt37+/TAWPK7ZhV8bJlx/n4MGDNm7cOFu0aJHzXmxsbKkFryvXgaioKGvRooUNGTLE7rvvvmKfRZw5c6bNnTu3UP5F5TVw4EAbPXr0NQXIjz/+6Fxsyj//Ka7wKbg/6Nevn3OsTU1NLfRs97vvvmv33Xefc0G4OAVvCzT7z3L6/PPPrX///s7jIKVd6F23bp2NGTPGHnroIadHd9euXdc82zZu3LhCx5yrrVmzxpo3b37NfPnnCW+//bbNmDHDsrOzK/28+PWAAqwUBTe4P//5zzZgwAC7//777eTJk7Zt2zYLDg624cOH24wZM6xly5bFHvT27dtnn332mWVnZ19zFXDYsGE2btw4e/vtt+2NN96wJk2alPic1FtvveXcapaenm5RUVG2devWQjudV1991Z577jmnZ64s8jeC06dP23333Vfogc+JEycW+4zFxo0b7cUXXyyyqDp9+rQlJiZax44dbciQIdawYcMST+DzBxSZP3++DR8+3A4cOOC8V/C3+PDDD61jx47OLWNFSUhIsDvuuMNiYmIKTS+4Exo8eHCpvY2ujOXK9hWVh5ldczCcPHlyiScAV+/oChZFkydPtiFDhtjLL79sr7zyit1xxx0lXhwoytUHrfDwcOvUqVOZbhfLn7dgjn5+fjZy5Egnz+eee67EE8rSBiPI/46lS5daly5dii2iS+rZzs/vzJkz9pvf/KZMPTHR0dE2YMAAGz58uC1fvtzJIzo6utCAPC+88IK9++67xcbJH9ggJCTEfvGLXxQ7mMu7775rM2bMKLFnLjo62nr27GnBwcH23nvvOQf4qw/0QUFBJfbsvPTSS04bMjMzbcuWLbZv375Cg8N88MEHVqdOnWL3mWZXLjY1bdrU+a7hw4c7gyQUbEdERIQ1atSo2BP4Q4cO2YULFwpdpS7Ke++9Z506dSoxJ7PC62NF183t27dbs2bNnN7pp59+2gYPHlzoMxs3brT/9//+n911110lbi+bN2+2Nm3aOLfEDh8+3NavX3/Ntrds2TLr0KFDqXcz5M9XcP6rT+ZmzpxZ4rMt27dvL/X2u/xBAbp161ZoQIarZWdn28CBA53n486fP2/Hjx8vtA78+9//trvvvrvUHse1a9c6z1fNmTPHBg8e7PyGISEhVqtWLedZlK1bt5Zp4KjKLCezK79zy5Yt7W9/+5u99957NmPGDDP7zzqevz698847NnDgQLtw4UKJxYArtmFXxcl39TNeZ86cKXR+EhERYQMGDLDvv/++yLa5ch1IT0+3bt262ZdffmlmV87BYmJi7OzZs4WOf5GRkda2bdsSLxBdvT4NGTKk0D7hhx9+sMGDB9uUKVOsffv2xe5bStsfPPHEE9aoUSObMmWKtWnTptR9VFxcnDVs2NC+/vrrIo+j+WMXlObqgXMGDx7sFKsFl9VHH31kfn5+xZ4fXLhwwe677z7n/OSHH364ptd/27Zt1rx58xIvxPycUICVUWJionXr1s327t3rdL1mZWXZsWPH7IMPPrCIiIhir05+9NFH1qxZM7v33nttzJgx9tprr11zBSQiIsL+9Kc/2dChQ0vdsN566y1nQIS7777bRo0aZePGjbOhQ4c6V/SPHDlS6mAX33333TVXffI31KysLOvatas99NBDNnnyZPPx8SlyJxQTE2ONGzd2dor5cnNzC23sOTk5lpKS4lxRK8rXX39td911l/OQ+Pjx4+3+++8vtDPOycmxDz74wJo3b17qcgoLC3MGkjh+/Lh9+eWX15x4DBs2zAYOHFio7T9VLFe279KlS9cU10WdWC9fvtzatWtn//73v4uMk5iYaCEhIfb+++8X2ukVjP3RRx/Z66+/buPGjSv2JGnNmjX26quvFptvfn4HDhywESNGOAe+4uzcubPQ7Y9mhXvT+vbta6NGjbLRo0dbixYtis2rLIMRnDt3zt577z1r3bp1sXESEhJs4MCB9vzzzxe6laOg3NxcO3/+vM2bN6/E9dzsyoAbzZo1s61bt9rChQstKCjI2X/ExsZa586d7R//+IfNnz/f2rRpU+wJc/4zhPlXXZ9//nnbsGGD0yuf791337UOHTqUuE7lP6S9ZcsWZwS+gutU/nr68ccfm5+fX5ED/eR/Zvr06TZ//nzLzc213/72tzZ48GAbPny4TZ8+3U6ePGmnTp2yGTNmlHo768GDB53f7ujRo1avXj0bOHCgjR071t5++227ePGipaSk2Lhx44ptW0xMjHXu3NkeeeQRe/rppwv1cBa8sr9r1y4bMGBAqetmQkKC0wOQv4+ryLqZnJxc6HnfCxcu2IMPPljoVp8tW7bYbbfdVuz2m2/Hjh3OHQonTpywBg0a2P33329PPvmks13GxcUVGk2vKEVtd0Xty/ILueKKk7i4uEInk8XFS0lJsVatWpW6L//xxx+tb9++lpqaaufOnbM+ffpYr169bOrUqYUGiVqwYEGJyyonJ8fGjBnj9MwePHjQ7r33XgsJCbGNGzfaxo0bnf1gUXd1XK3gMa4iyynfO++8Y3/961/N7Mpv3rlzZ3v99dedkfjy8vJs2bJldvvtt5dYiLtiG3ZlnLS0tDJdRHzzzTdL3T+5ah0wu1L85Q+CdvbsWbvtttts4MCBNmjQIFu0aJFz4biki+pmxa9Pc+bMsY0bNzrnYB07djRfX98SC7kvvvii0OAv+fuDgs/K/uMf/7CPP/64xJ5ws//s8/KLnaLODY4dO2aDBg0qcVCe4gbOKXisz8vLs/fee886duxY4rp59uxZ6969u509e9ZOnjxpgwYNsj59+ticOXMKHQfmzp1bruccr2cUYGWwadMmGzRoUKHnBKZNm2a+vr7XHKyulp2dbQEBAc6VwFWrVtnTTz9tM2fOLHKo8OJuzdu8ebNzID98+LC1atXKBg0aZO+8846ZXSm4Jk2a5IyqWJrVq1dbt27drEuXLk5hka/gxvrxxx/bkiVLijwBvHTpkj3xxBPO8wX5BWn+CU7+TrpgL09pChYBaWlpNnbs2EJXs86dO2cffvhhma5KvvDCCzZjxgw7cuSIdejQwYKDg83b27vQTu7s2bN25MgRt8VyRftWrVplQ4YMMX9/f1u3bl2hq/oFTwLWrFlT4snNli1bzNPT095++20bNGiQPfnkk4Xun7/69sDiTkjyH1qvVatWiaNQ5R+kS7ttIi4uzrp06VJk3gVz2r59u0VFRZV6MCppMILo6Gi7cOGCvfTSS8UWOYmJiebj42NLliyxUaNGXTNqW/5JWP7/S+p1zh8I5A9/+EOhXq7AwMBCo0wuXLjQJk+ebIMHDy7yBD7/d969e7czClh6errVqlXLxo0bZ+3atbMlS5aY2ZXRwnr16lXswTEvL88uX75s48ePd7blQ4cOWadOney5556zZcuWOctwwYIF1r59+yJj5eTkOG3fvXu39ezZ04YNG+YUGdu2bbOgoCDnpLykHsXNmzdf8x2vvfaa8+zS8uXLbfDgwc4JTlHPT5ld+e3atm1r27Zts88++8wCAwML7Xfzl2P+YAKlDQyyfv168/T0tF/84hfXXKUt67oZGxvrnDDm97ZevnzZTp48ae3bt3cuouXf0VDSLe35t8QXbM/s2bPtL3/5i+Xm5lpUVJSNHDnSWU4l3ZpV0nZXUGJiov3ud78r9nOff/653Xbbbc4oo/m/Tf7vnX98yb9SXtIyL3hi/8orr9jEiRNt+PDhtnTpUjty5Ii9/PLLNmXKlHIN6JL/O2VlZVmTJk3sj3/8o82fP9+mTZvmPOtz+fLlYi/IffbZZ84Il2bF375V2nIq6J133rHbb7/dli5darfffrtNnz7dPvzwQ7v77rudO082bdpU7LHUVduwq+KYXelBa926tU2YMMHuv//+QheECy7bkydP2sCBA4uN48p1IDc31zmOvfPOO9a9e3fz8/Nz9ivLli2z4cOHO7c5l+VWxqLWp1dffdWefPJJZ316++23r+kZzffNN9/Yd999Z3l5eU4bitofHDt2rNTnivPy8iwnJ8e6detm/fr1M7Mrx4U5c+bY008/bTExMc6+7uzZszZt2rRS21jawDlmVy4AFddrVTD+3JIJzzcAACAASURBVLlzbf78+RYQEGCLFy+2L7/80h577DFnELP/NhRgRbh6x5uammrjx4+3ESNGFLp9bsKECdaqVSu7fPlysTvh7Oxs69Onj/N3F3Jzc23z5s02ffp05+HFHTt2OPf+F7XTX7t2rTVr1szWrl3rvL9hwwbz9fUtdM/0448/7gzPXJKkpCRr166d/etf/7J169bZ3XffXeERyZ566imLjIy0tLQ08/Pzs7Fjx5q3t7dTcB469P+1d+4BNWXtH9/e+b0zY94ZYzA/5tK4DSVRksowGrfQqJBQSmqky4QMaTCT3KLchVwmNSIkQxfVicoliWHcL4NxCw1FknQ/398f/fZ6zzmds8+pdkfM8/lnRp3W2WvvtZ+1nrWe5/vcho2NDQoLCwVPmJTdv5KSEkycOBG+vr5qP8tz+fJltnuSnZ2NmTNnIjAwkMXkSyQStG/fXiOVMzHbEqt/f/75J/T09JCVlYXo6GhYW1tj9erVKo2fYo6TLNHR0Wxyz83NRUxMDDw9PeXC3U6cOMGepeLz4/8dFxcHiUSCu3fvQk9PT2mo6t27dzF58mS19ckSEhLQrVs3wfcBqOkcKlJbMQJl7fGT2bx589hGR3JyMuzs7BAVFSUXZih0nxTbBKoX1bIT6ubNm1nYkSb9VNxVLi0tRUREBNtFP3z4MN5//31cvHgRxcXFgvedvyZ+YVJQUAATExPMnz+fCQvwE+6BAweU7i4fOHAAjo6OciFCv/76K7p27Son+ODo6Ci3eFVGQkICOnfurFapz8bGpka4pWyfpFIpgoKC2HN68OABOnToAC8vLyxYsICNsatXr2LOnDlqFSJ5ef8TJ04gJCSE5dgKhfAqcujQITRr1gzt2rWTW1iWl5ejpKQE/fv3B1D9bjo5ObFEfGUkJCTA3t4ew4cPlyuBojj+hg8fLqfWqaotTd47fryqOuG9ffs2li1bhnHjxuHChQu4c+cOHBwc4OHhgdGjR7Oxc+fOHdjY2AjOOwkJCXJ5MGfPnoW/vz/MzMxYO0+ePMGAAQM0CiNXhqzt3rBhA1xcXAQ/L5FI8N5778HOzk5us0rxfqm7T0BNYZnQ0FCsX78e3333HfvMwYMHMX36dLX9EOMdFrOdGzduoGfPnixawN3dHe3atatRD5LfwFa1aSXmGNi3bx/Gjx+PCRMmsIiBgoIC+Pj4yJ2gffvtt0hJSRFsSxWK48nZ2Vnw88nJybCwsKixUVNWVlbDHri4uAjaA+C/9zUvLw+mpqZwdXXF119/jZCQEMyaNQtTp07Frl275E7+1SEknLN3794a0U+yxMfHw8nJiW0o79+/H56enhg6dCh7N+7cuYN+/fqJUjvvdYMcMAUUTxCSkpKQlZWFsrIyeHl5Ye7cuXJOmLpQI6A6ZMXa2polJ1ZWVmLHjh1wcHDAy5cvsXLlSmaEFXn69Cl69+7N/ra8vJxN8HFxcdDT00NISAg2bdoEY2NjtacBALB7925MmDABQPVRvLm5Odzc3LB161ZmxBISEthiTpGbN2/i5MmTKCkpwdatWxEYGIilS5cy4YdNmzahTZs2LAyqLs4d/xz4GlSyctyq2L9/P3R1dZnRf/HiBTw9PdGrVy8EBwczQ+Lt7a1WsVDMtpQtZurSP6B691VW4TIrKwuTJk3C2rVr2X2Oj4+XS25WhB8/sbGx0NPTYwvBZ8+eYffu3Zg+fTru3buHqqoqbNiwoUY4Gw8fRltZWcmM57Vr16Cnp8dql8h+ThPFJTc3N1Y3rKioCP7+/nBzc0N8fDw7OUtPT0doaKjKE7naiBHMnDkTgLDTtGnTJnz88cfYs2cPPvzwQ/zwww/w8fHB5MmTmcy40H3iOXr0KEJDQ5UW5YyPj2fqoLt27cKOHTtQVVWl9LpSUlLw9ddfY8qUKXKnZvzz5//Gy8tL7eYAf0182QoeWRsXGxsrqAqYmJgIIyMjJCUlYePGjRg4cCCAatWsVatW4ZtvvsGGDRtYOJbQQkmZvVMWFbBnzx4YGRmpjEDg30/ZfJNRo0YhJCQEx44dw+rVqzFu3DgUFRXh4cOHasOkHj16JLdw27x5MwYNGlQjryUjI0Pl2ORzEePj4xEYGMiEBGQdODc3N0yfPh0mJiaC4Zn8Pc/MzMT8+fPRv39/pYvYffv2wcTERDBSQyqVwt3dXaP3bvXq1So3iFJSUjBgwACcOXMGYWFhcHV1xWeffYY1a9bg5MmTCAoKgqWlJRunQvPCuXPn0L59+xr5rEePHsWwYcPg5eWF3NxcJCYmMolvof6p+pmsMFBUVBQmTJggeEK/fv16LF68mBU6V+aEZWRkYNWqVYIbabLCMn379mWRE2fPnsXQoUPZqeHq1atha2vLhL+UIcY7LGY7QPWJ8sSJE9m6pri4mOWB86e+169fh62trcp8NjHHAF9DKzk5GVu3bkXXrl0RHh4OqVSKffv24ccff8Thw4cRFxeH7t27C0ayiDWeEhMTYWBgwCIYlKGpPQCqN90WLFjARH/y8vLQq1cvphcAVOsYKBZz1qR/sigK56hac548eRLt2rWrUZc0KioKffv2RUhICAoLC5GYmIiBAweq3Zx9EyEHTAF+8K1fvx5GRkaYM2cO9PT0EBwcjNLSUnz//ff44Ycf2HG5JkpZJSUlCA0Nhbu7u5wxsbCwUJtsmJeXhwEDBgCoXgSMHz8eNjY22LBhA3Jzc3Hr1i0EBgbip59+UitqwC8QL168CDs7O7i6uqJ9+/ZYuHAh9u/fDxcXF6xbtw5A9U6msmvjd0otLCzg5uYGiUSCwYMHo0ePHnKnCxMnTlSb6C3rTCqDX0T5+flh1apVgrs1f/31l1x+Fb8YKSkpgZ+fHzw9PbF+/Xr88ssvaN++vWCharHaUpZPUdf+8c9OKpVi4sSJ2L17N1vkHT9+HEOHDmU7UXfu3FE5ruLi4mBqasr6FBAQAB8fH3adubm5GDJkiNr6Renp6fjmm2/kFI/4679y5QqTA965cyc8PT3Vnljxu5lVVVWYMmUKzMzMYGpqipCQEISGhsLCwgKxsbHsXqhShxRLjODAgQNyJ5Nr1qzB3Llz4e3tDaB6Qb9o0SKNi//yiczLli3De++9x5TV+OuKj4+Ht7c39u7dC319fZWTWmpqKrp27Yr4+HgkJCTA3d1dbqHHP4Po6GgYGhoKLiRUXRMP3+727dsxcuRIpQulgoICeHl5sXCzM2fOwNLSEqGhoSy09syZM/D09MTUqVPVLiL43Wyg2t45OTnBxsYG69evx82bN1FeXo6tW7eyQqfK4PMaIyIi5O6jbFjvhQsX4OTkpJEKZ2lpKaRSaQ0nbciQITUENnJzc5WOzbt372LUqFHsfVm4cCF69+7Nfl9RUYGqqip07doVn3zyiWAOS2lpKdzd3dmmze3btzFkyBAEBATgxIkTLGQxNDQUBgYGgvMCf+pXUlKCadOm1fm9k0gkMDQ0hI6ODisSu2bNGjkHJScnB66urhoJQyUmJrKFYk5ODsLDw7FmzRqUlJTg8uXLWLx4MaysrDBgwACVoV2AZkIgQHVetVAOC29/+VqfRUVF2LlzJzw8PGpEnagaAzzKhGVkUwf8/f3xxRdfICAgAF27dhUUJxHjHRazHR6+xl5YWBiys7MREBCAgIAATJ48We6UUUg1WKwxAFTbhOHDh7N/p6enY+jQodixYwdu3LiBn376CYMGDZKrv6kMscbTy5cvmYo2UL0ZsWDBAvzwww9sQ7eiogL6+vpq7QFQ/f517NgRwcHB+PDDD5lQ0cuXL+Xy8SMiIjBp0iSV76CYwjmRkZGsrtf9+/cRGxvLruvw4cOYO3curKys0LdvX7XP702FHLD/5+7du+x499GjR/jmm29YPZ+nT5+iQ4cO2L59Ox4+fIhp06aplZpX5OnTp1i3bh2GDh2KTZs2ITIyEvr6+iqPXWUnex8fH2zYsAEjRozAL7/8gqSkJLi6uqoVPZAlKSkJ9vb2uH37NsrLy3Hy5Ens2LEDNjY27DNpaWno37+/SqN4/Phx6Orqsl31yZMnw8/PDwUFBRgwYAD8/f1x7NgxbNu2Dbq6uoInAvv374ejoyNGjx6N1NRUud1QRcOelpamNrfq0aNHzLD/9ddf+O677zB79mwm352amorFixdj0qRJgkZDrLY0zafQpH/8s7tx4waqqqoQGhqKGTNmICMjgy0gIyMjYW9vLyjvL5FI0LNnTxgZGbE8prNnz2LOnDnw9vZmORmBgYEICQmR281TZM2aNejSpQtsbGyY48fnDwDVE8o777yD1q1bayRq0LJlSxb6yIdmyhZ93rFjB6ytrQX7B4gjRnDgwAHo6+uzyYLn+PHjsLKyYs5qSEgIXF1d1dbk4cNG+evavHkzli9fjvPnz7Pn98cff+Cjjz5Cv379lF6XVCplMfu8s/PHH39AV1cXK1euRHBwMPtcRESEWmGDGzduqLwm2Y2AtWvXCi4kpFIp2+V+9uwZ+vTpw8JYO3TowMIIVZ3mKUPR3iUnJ8PV1RVr166FVCpFWlqayiRtZXmNsgtkfiGya9cuDBgwQK0qYkpKCpYuXSq3YOE3PtLT0+Hh4cHaENpAqaysrPFdsqVC+OuKiYlh844y+HvIO07Pnj2DgYEB28RxdnZmJ6wJCQmCbaWkpCA4OFhO3a4u793BgwfRsWNHXLp0idWvOn36NAur5Nm+fTssLCw0KtVx6dIlTJo0Cbdv34aZmRkCAgJgbW2N/v37s3k6Pz9fZe4f3z91QiClpaW4du0aRo0apdJOydpfWQoLCxEdHQ0PDw+WK61JDSNVwjJOTk4s1HnLli0IDw8XzAW+fv26KO+wWO0ocuTIEXh6esLV1ZXVFs3NzZUrtqvMJvDvghhjgIef07OyslifDh06hC5durAol+fPnwuehIs1nniuXr2KH3/8ESNHjoSxsTECAwOxZMkStGvXjoVEamIPnj9/DmtrazZfbdq0CevWrcPx48fl3r8NGzYIPj+xhHNk02T40G4TExNMmTIFVlZW6N27t1zNNU2Vnt9EyAFDdZLg1KlTsWzZMvYyjx49Wu4UIS4ujuVo1LZ2EU9ZWRnS09MxduxYuLi4qAwPSkxMhKenJwvViYqKgre3N0aMGMEG7vHjxzFgwACNwrqys7Oho6OjtBjk1KlTWT2xuLg4WFlZqTRox48fZ7lsQHWYgWyiZ1BQEObOnYthw4YJLv5+//13GBoa4syZM0hISEC/fv0QEBBQY9dQXbyzLHfu3MGQIUNw/vx5uLu7Y9GiRYiLi8OgQYPkEkbVLeDFaEvTfApN+qfs2b148QILFy7EtGnTmNDCr7/+CmdnZ5WLwLS0NHTp0gVHjhyBRCJhxV2BaicsMDAQHTt2hJ+fH1q1aqVW5OTkyZNM9MXKygpnz56VGzeZmZlo3bq1WmeXV9tydnaWyxVSvLcRERGYOHGiyv6JKUYwe/Zs5jjk5+fj8uXLKCgoQGlpKRYsWICBAwdiwYIF6NSpk+DkKAt/H3JycvDee+/Bzc0NX331FRYvXoznz5/j/v370NfXV7u44cfM06dPYWVlBX9/fyQnJ2PMmDGsdl9cXJzafIiKigqV17Ro0SL8/fffePDgAezt7ZVek7Id1IcPH7IcD6B6ITd27Fi1eQZJSUlyJyVC9k5dOHN0dDRzRpXlNVZWVmLZsmUaLSSTkpLQvXt3lYVFHzx4AFNT0xr1+2Q5dOgQQkNDWb4v8F8HLjw8vEZNJyEnNS0tDUFBQXLfV1VVJRcitnbtWtjb26t1dlX1rbKyUu55qXvvgOqFGx8twOfU8CHQ/HVs3rwZhoaGGm1ISaVS5OTk4Ntvv4Wfn59cCBVf8kUdmgqB8PZAlSCM0NwJVDvAhw4dQq9evdCsWTPBRbc6YZno6GjY2tqqFfbikUql9XqHxW5HsU0eWVu+YcMG2NjYoKSkROkYzcjIQGpqKsrLy/HgwYN6jYGLFy/ijz/+YLbwp59+gq+vL/766y+5ulNTp05VW3NKrPGkaDf//PNPODo6MpsFVDvffNFlTTet5syZAx8fH5w4cQLvv/8+3Nzc0K1bNyxcuJCdyFpbW6scn2IK5/BcvHgR3bp1w8yZM+U2wUaNGsXUPf/pkAOG6kksKioK06dPZ7uss2bNgomJCXtR165dC0dHR0F1JE0REu3IzMysYfBLS0uxevVquck+Pj4ew4cP12j3JyoqioWFPHjwAImJiUyZLCgoCGPHjoWtrS169OghWKOrsrJSLu8nJycHRkZGbAecnzjUORZ79uyRC0MICwuDkZERtmzZwu6LujwfoPoUzcvLiz2PJUuWQEdHR66I9KlTp2qIXDRkW7XJp1DXP6Dms4uLi8O+fftQVVWFyMhIjB8/HhYWFjAwMFDp0L98+RJLlixBVlYWa6dt27Y18sQkEgkSExPVhjvw/bKzs8Ply5exa9cumJubw9DQEH///TeqqqqQkJCgNh8xIyMDRkZGOH36NB4/fozWrVsrTejlazOpmvzFFCMAquPu16xZg/z8fJiZmWHEiBHo27cv9uzZgytXrmD9+vUICAhQG2IbFxeH0aNHy/3s7NmzTP3w6tWrMDExYTkXqnIFjh07huXLl0MikbCc0/LycrncgZMnT7LwSCFycnLk1Mh4+XXFa4qPjweg3NGKjY1Fjx49mMCLKnsYFhYm904po7S0FHZ2dvj3v//Nwp5KSkoQHByMr776qtb2bv/+/SrzGu/fv4+ysjJ4eHioXUhevnwZ7dq1Y3mw+fn5uHbtWo0FTGxsLCwtLZXWLkpKSoKBgQFWrFiBgQMHss0Snrt376JDhw5ym1qqSE1NRefOnbF582Z88MEHNerCyYaIfffdd4KbhJr2Td17pwh/DcnJyXIn3y9evICfn5/gZsXBgwdrhPIdOnQIenp6GDNmDBv3oaGhcotVZdRFCETVGFU2d8oq3wLVJ+GffPKJ4GZTbYRl1IWA/fnnn8yWA3V7h8VsRxn8WDh06BC8vLxQVFSEbdu24dNPP1XphCcnJ+PTTz/FoUOH2N+npqZCT08P9vb2tRoD8fHx6NGjB4YPHw5XV1ekp6ejpKQELi4umD59Ott4WL9+Pdzd3QXbEms8KdpNHsXNwHXr1smtO1Tx999/s9PkrKwsTJs2DUOGDGECGVeuXMFXX33FTsRVzS9iCedkZmaycGWeuLg4/Oc//5GbmwIDAzUSi/sn8I92wK5fv852+qVSKeLj4+Hl5cUmJk9PT/Tu3RseHh4wMjJSu5svBqtXr2YhIA8fPsShQ4eYsYiNjYWPjw+GDx+OXr16aRw3m5GRAW9vbyah7u/vjx49erD8kfPnz2Pv3r21UpKqqKhAUVERy9eIiorC5MmTBaWleccsOzsb7u7uTJ1s8eLFcHNzQ58+fdjkoy6OPiUlBQYGBjXCxAIDA9GkSRO2+N+0aROsrKwET77EakusfApZlD07IyMjuLm5sc+cP39erRgMf838woxXJ8rJydE4j5GHr1Lv4uKC0tJSHDlyBC1btoSZmZncCYg6Dhw4IFdTKzQ0FK6urnLJuFevXsWkSZNU7tyJKUbAk5WVhVmzZsHLy4uFBG3evBmWlpZsslS3YyqRSKCvr4+ePXuy4t3K7rO/v79cjRVFkpOToa+vj1mzZmHw4MFKBTyAamfH2toaL1++VPk8k5OT0b17d9jb27PcA2UIXdOff/6JXr16wczMDF9//TW7n4rfGRUVBRMTE41OPCIiIuDo6IgOHTqwTYHi4mJERUXB19dXrb1TXFjMmzdPaV4jr76oyXg/ffo0e/7JyckYOHAgxowZg0GDBsHHx4d9rqCgQGkIzcuXL2FlZcUWrxs2bEBkZGSNArERERFwc3NTuTiSSqUoLi7Gt99+y5Lrd+/ejbCwsBriP1u2bNHIYdKkbzdu3BB879Tx888/IygoiO2cC70v6enpaNGiBdq3by93Cg5U2z9LS0ssWLAAM2bMUBtaK6YQCP/9iva3Z8+eGDt2LPvM8uXL5TZ+FBFLWAaotpm6uroYPHgwDAwMVH5OnV0Rqx0hbty4ATMzMxaWmZmZqXRzTyqVoqioCFZWViwXrrCwkM2n586dw+DBgzF//nyNxsCJEydYjujLly+xfPly/PjjjwCqNw5/+uknuLq6YvDgwejatavgprNY40mV3VTk119/hbGxsUZFlnv16oWJEyfKqWZu27YNgYGBzJ7MmjVL8IRerP4lJyejefPm6Nu3b43NIV7QbNOmTZg/fz66d++udvPyn8I/1gHLz89HkyZN8PHHH2PdunUICwtjJ2Hz5s1jHnp2dnYNOeuG5LfffsPixYtRVFSEHj16wMvLixVE5rl69aqg4g8AuRyJc+fOwdraGosWLZLLG+vVq5egWp4muLi44Mcff4SxsbHgZJ2SkoKQkBBUVlaiuLgYgYGBcHBwwLBhw2BlZQWg2sGRVXUTYv78+YiJiQFQHQqZlZUll5vTu3dvzJgxA926dVPrOIvRllj5FIBmz87MzIzlj9SFK1euwMbGhu2ACi2QkpOT4efnV2NS2Lx5M8aNG4cvvvgC27Ztw/bt2zFmzBgUFRUJLnIVwxv57z558iSsra3lRE2qqqpUyoOLKUYgy61bt+Dr64uvvvpKTglUtqCzUP9SU1PRvXt3SCQSrFixgu1IKrJt2zYYGBioFEw5f/48DAwM5IQbFi1ahPv377P3v7S0FJs3b1a7QZSeng5dXV0WYmJra6u0Lo+6a7p+/TrLT+A3GWSdMKlUimPHjgnW9eHhF+fx8fHYvn07Ll68iM6dO2PKlCmYPn06c6SF7J2ysSmU16guF0323cvMzISvry86dOiAsLAwSKVS3Lt3DwMHDpQTn1FGWVkZJk6ciL179+LMmTNo164dxowZg6+//pqFbQPV91MTJd3AwEAEBgYiLS0NLVq0wKRJk6Cnpwd/f3+UlJTg/PnzGDt2rKAN1rRvfJ6MOll+IWJjY9GnTx+Nihlv3LgRW7ZswZ07d2Bubo5FixbJ/f7KlSs4fPgwVqxYIXg6L5YQiCb219zcHKtWrVLbN0AcYRmg+j3o0aMHO8W3s7NTGiqu7h0Wqx11PH78WM65UbfxMXXqVDx79gxPnz7FoEGDMG7cODg5ObEIiYyMDKxcuVJthEZ6ejqWL1/O/n3p0iX07duXRepUVFTg2bNnyMzMFCzTIqawjDq7CVTbLXXvMPDf3LWUlBT89ddfcHBwYJFJFy9ehKenJ0JDQ7Fu3Tp06tRJ5f0So3/8tQcFBWHx4sXIzMyEjY1NDSfsxIkT2LlzJ+bOnUvOlwz/WAcMqI6pb9KkCdauXQt3d3eMHj0aEydOxOTJkzFq1CiEhYVplDNUX7Kzs5kIw7Fjx9CjRw8sWrSI7b4DQJ8+fWqEsKgiISEBTZs2xbhx49jPwsLC0L59e/j4+LAThuDgYLlisLVBKpWirKwMHTp0gI6OjqBRVJZvUFpairy8PJw7d46dyixdulSu2LUQnp6eCA4OxosXL/DVV19hxIgRGDZsGHNKLl68iMuXLwuqHfJ4eXnVqy0x8yka8tnxjg6/KAoODkbXrl0F5V9Pnz6Npk2bwtbWFosXL5ZbIKSlpWHw4MHshOfJkydqRQ2U9U92kebm5ianVqUK/jSV/299xAhk4SeUR48ewdvbG7Nnz0Z4eDhiYmLQpUsXtXLeBQUF8PDwYPWpLl68iDZt2sjVmXn+/LnaItk8fEL0w4cP8emnn8LOzg4uLi74/vvvcfPmTdy+fRu2traCCdFlZWWIjo5mTsPNmzfRqlUrTJ06FQ4ODmxX87ffflN5TbLCCbKn3NOmTYOpqSlbyPCLNaHcVMWFfU5ODhsPq1evxttvv41JkyYJ3heg5tiUdfjOnTtX67xGfmzKnm6cPHmyxsm4i4tLjZMsZWzZsgWjR4+Gubm5nPBAnz59WAi4EOfOnWP3NTY2FrNmzcLAgQNZW48fP0b37t3ZvCDkMNWmb3w+V33hRZ9UITtn8A72+fPnYW5ujoULF7LfqSvcDognBNJQ9rc+wjI8Dx8+hKurK65fv468vDw0b94c48aNg4WFBc6ePYvS0lLs27dPrV0Rqx0xkA1TnzBhAsaNGwdfX19ERETg2rVriIyMxOjRozUSPZOde/hQ5YqKCuTm5mLQoEHMbqkT9ALEG0+a2k3+XRA6kZVKpXj58iVWrFjB1LQvX76Mzz//HPPmzWPpEdu2bcP06dMxcuRIlZtyYvVPNiS8sLAQpaWlSEhIgI2NjZwjRyjnH+2AAf+NMS4rK8O9e/cQGRmJoUOHokWLFmoXp2KQlJSENm3a4PDhw2xhzi9CZE9P5syZw05phHjx4gWGDBmCTZs2wcXFBQ4ODux3fBjVqlWrEBAQAD09vXrvRkRERAgaaWX5BleuXFGajNy1a1fBhfK5c+eYwb548SLc3NwwYcIENhHu378fo0aN0qgWmiz1aUvMfAptPLv09HRMnjwZFRUVyM/Px/Tp0wUnt0uXLuG3337DqVOnWCFq2T5oEkapqn/jx49nv+M3OvLy8jBy5EiVBXaB6sljyZIlchOFVCqtkxiBIryTevr0adja2kIikTDpZHUS6vx38SFp/MZCaGgoAgIC5PJybty4odKZO3/+fI2QprS0NCbkcOnSJUyYMIGF8NZGrKa4uBi+vr4IDAxEcXGxnBTyzZs3lV7TgQMHmEobv8kg6zRPmzYN/fv3x9KlS/HNN98IOuGJiYlwdnbGmDFjkJmZiZKSEjx//hw+Pj6IioqCvr4+li5dilatWtXItVFE2dhUfO9SUlKQkJCgdtdc6N2TXTjFxsbCxMRE6WZMRkaGnJw4UD0Gtm/fzjYpgOqwoOjoaMHrSU5OxpdfflnDXuzfvx8rV65kY3/BggVqFzpi9K02aPLOpaSkoEmTJkqVfM+ePQtzc3OEhYUhLi4OoaGhapVGebtgNgAAIABJREFUxRACEdP+iiksw8Nv7owfP57V/wSqRYMsLCxQUVGBW7duqQ2zfv78OTw8PODk5FSvduoLPwb406ri4mI4OzujW7duzKbl5ubC0dER+fn5gm0ps1E8paWlGDp0KIBq58TFxUWteJkY40lMuyn7vfznnj9/jgkTJmDu3Lm4ceMGrKysMGrUKPZ5oY0LMfrHz8OK809xcTHi4+NhY2OD/fv3Iy4uDnv37q2VEu4/hX+8AwZULwo6derEFk5Pnz7Fo0ePBHfv6otUKsXff/8NMzMzpkIou4MZERGBLl26YNeuXQgODka3bt3U7pDxPHjwAEVFRcjLy4OdnZ3cbt6xY8cQHx+PuXPnqt0R1rQfQmiSb1BWVoZ58+YJxmLv27cPZmZmOHr0KKRSKfLy8rB8+XKYmJhg2bJl7HP29vY1FkGKXL58Wc6gP378GMuXL0evXr1q3ZbY+RQN+ez4mPw9e/YA+K+ErRAVFRXMkJ88eRJ+fn5yz4p3KjQ1rIr9k3XCgOp3YNasWSoLk/PFbBWLOwKQE8jRRIxAFdevX4epqalcQVJ1u/Dp6ekwNzdnoRqyE61EIoG5ublaZ5UPA/vwww8xZswYuQR5Rdzd3VmYh6p7f/DgQXh6emLRokXsxKaqqqrGDrCNjY3KjaaEhAQYGhri6NGjmDdvHuzs7JSGq5qamuLjjz8WdFL5WkNHjhzBzz//jNGjR7P3cOHChXj33XdZjmR2drbazQ9VY5N/z2ojGgDUHJu8EhlPZGQkTExMlG6iHDx4EM2aNYOOjk4NUY3Y2Fh88sknOHLkCDZu3AgjIyNBW56eno5OnTqxMc47SVKpFKdOnYKdnR22b9+O5cuXQ09PTyNbUJ++iU1SUhJ69+6N2bNnw93dXWm5kkePHqFly5Zo3rx5rU5h6iMEAohjf8UUlklJSWGnZxcuXEBVVRVu3bqFiRMnys0nQ4YMERxTBw8ehJeXFxYtWoQrV66goKAAd+7cgaura63aEQvFMcDnIp89exb6+vrM+d29ezd69+4tqFqrzkaVlJRg1KhRmDZtGoyMjLQynsS0m0DN+YWPrpH9/idPnsDJyYnZRE3m5Lr2T9k8LPt9xcXFOHnyJDp27IhmzZppRT/hdYQcsP8nKSkJnTp1UrvTIiYvXrxgYgoPHz6Eo6MjXF1dERwcjOfPn+PIkSP45Zdf4OPjo3EIlSL5+fkYNWoUm0jOnz8vGPcsFrXNpRAyFvfu3YOxsTETbOA/W1hYiMDAQDg6OiI0NBQxMTEwMDAQXOgeOHAATZo0wbRp0+SM+q1btzB//nyMHz9eo7a0kU8h9rOTjclXJw0ui+yzycrKwsyZM7FmzRrMnDkT9vb2agUpVMH3j3fCfv/9d+Tm5qps78qVK2jZsiU7pczLy8Pt27drOLaaihGooi73KTg4GE2aNEHv3r3l8gB5fH19MWLECI1Cmp2cnLBgwQJ4e3vLFW7n2bVrF7p164a//vpLZRv8BLlhwwbMnj2bJaHzyOZ89e7dW6kDVlFRAWdnZ6bcduvWLQwYMADz5s1Deno6WzifPn0a3bp1E9xgePnyJdzc3OQS+h0dHdnud2FhITul0iRvSLEfgPzYnDFjBkaPHi3a2OTVL1Xd8+DgYISHh+P06dMwNDSs4YSFhIRg7NixsLa2FhyXZWVl8PT0hJOTE6RSKe7fvw9vb2/4+flh8eLFqKiowC+//AI/Pz+MGDGiTvNCbfsmJr///jsTzSkqKsLgwYPZHCD7rHbv3g0dHZ16LdxqIwSijPrY3/oKywDVBZs7deqE0NBQhISEoH379uzkdNGiRYiIiMDDhw+xd+9eGBgYqMyTlLUFP/74o5wtqE07YqFsDMjauadPn8LOzg4eHh5q7bg6G8XnuRobG6NTp071ci41HU9i2k0eZfMLbyd5GxgeHo7+/ftrpIxdn/5pOg+vW7eu3u/wmw45YDLs378fRkZGdZ60a0tVVRX69++PoKAgjB8/Hps2bcLu3btZ1XixyMvLw8SJE9G5c2d07NhRLvm+IahNvoHQLj/PjRs3YGlpCaDaGfPx8YGbmxv27duH4uJi/P7773B3d4e3t7fgTlJhYSH8/PywYsUKjB8/Hv7+/nJO2N9//43Tp0+rbUub+RTafnbKUMwdu3fvHvr16wcdHR1B9S9N4Punq6urtn+XLl3CDz/8gCVLliAtLQ2DBg2Cs7MzdHV1WX228+fPMzldbXL9+nVs3boVU6dOha6uLgD5CSw7OxtTpkxRG+MPgO1Ur1ixAtOnT0dERAR2796N8vJy7NixA7q6uoK7uPfu3YOtrS1b1OzatQuOjo7IyMhgiffPnz9HREQEDAwMBNviTxALCgrQoUMHzJkzBytWrICvry/Cw8MBqA5dVOTWrVsoLCxkE/zixYvl7Bzf/9qEqWhjbHbu3BmdOnUSLCxfWVnJQnkPHjwIQ0NDdn9k0eRU7tatW/D29sa0adOgq6vLnLtp06bJCbrU9oRPltr0TUyOHj0q924GBwejZ8+eNTY+169fX++FW22EQFRRW/srhrAMz65duzB16lT274yMDHz00UdITEzEpUuXMHToUNjZ2QmeXCqzBQ4ODsjIyMC1a9dw8eJFjdoRE2VjwNjYuEYo/MuXLzWqc6qJjdq4caPGqtGqqM14EtNuAsLzy8uXL7F161YYGhrW653RtH+azMNAtRqtupO9fzrkgClQ192D2sK/PCdOnICLiwuGDRvGfnfw4EE4OTmJ+n0rV66UO2JuKBoi3+DFixfw8vLCmTNnMGLECKxYsQI7duzAl19+yRLQq6qqNDKM/GLz8ePHsLW1hb+/f43FR2Vlpcq2tJ1PAWjv2QmRnp4ODw8PSKVSJCcno2nTpqIlaNemf7zCXcuWLbFu3ToA1eqH7du3R3Z2NsrLy2uVEyUGfP4Zr273/fffQ0dHB23btkVxcTEqKytRXl6u9nSddzz4mHkA8PDwwHvvvcfClh4/fqzRmOLFMPLy8mBkZAQHBwcEBQWhW7duSEtLQ2FhIRYuXFirPELZOnMbNmyQq+WnCYqnibt27WIOxW+//QaJRFKnHIFXPTaVXXNqaioMDQ2RmJiI5ORkREZGarSxx7fFh5nJqtQmJyfDy8urDr1Qzqu0K/xYKCoqgoeHBxOpqY+zpAx1QiCaoMl9EktYRpbU1NQaIdppaWno1KkTbt68iby8PNy/f1+t86zMFixevBgGBgY4e/Ysnj59qlE7YqNqDNRnY0HRRjk7O9fvIhWoy3iqr90Uml9KS0tx9epVeHt7i3LSpGn/hOZhdQqxxH8hB+wVU1BQgMjISOjo6LBwnJiYGAwdOlQ0ARBe1lVbuxENkW8wdepUWFlZYfr06exnKSkpsLW11SisS3aRJKt0Z2NjA39/fwDVTpNscVtVaDOfQtvPThl87hifn5OTk6NRsWZN0LR/ss/vwoULLLyDX9R6eHgwxcBXBT+Orl27ho8++ghffPFFndpJT0/HzJkzkZKSgnbt2sHV1RXu7u4anaYqOgOXLl2SK/4aHByMpUuXAlC+0FHmTMieTPH/HxUVhQkTJgjmxqlzpqKjo+Hv74+YmBh07ty5TnLXr2psauIoXrhwAe+//z6aN29eq1BBvu1nz57JPaPw8HDY2toqLfpcWxqDXeGZM2cO7OzsRG1TrGR/Te6TmMIyigwePLiGE7Zw4UJERUWp/Vt1tmDp0qXMFrxqajMGxLRRmqJuPGnjmoTml/r2UdP3RZN5uL6RB/8kyAHTEqdPn1YZY19cXIz09HT069ePhWOJHQoghhGqC/XNN5B94Z2dnWFoaMhCCXbs2IGxY8cK7pqq2nXmd98eP34MZ2dn9OvXD23btq21uIU28ile1bPjkc2JaojwXFX9U/wu2RMUWXGN3bt3w9jYWJTTxvowe/ZsjBgxAp06dUJaWhomTJgAc3Nzje6Z7Gfy8vLg5OQEHR0dJCYmorCwEGvXrhVlh/rnn39mp06Kk252djYrhC5EWFgYjI2NBW2UJm2lpqaiVatWsLCwqPPu7asYm5rep507d+Lzzz8X7FtmZqZG6rYbNmxAjx49RJUF14ZdUXwmyjbCAMDAwKDWzom2ELpPYgvL8MjeNxMTEzg6OjKbN3v2bPj5+Qn+vSYL6p9//pnVf2pIxBwDYtoosdDWNSmbX0xNTRtcXfB1m4dfJ8gB0wIpKSno2LGj3C4avysi++JUVlbi1q1bGhXmfJ2oTb5BeXl5DeU6WQfr+++/x7Rp0zBhwgSYmJgI7kympqayejvKFme8IQkODkaLFi3qvLh5VfkUbzJpaWn4+eefERkZKXcyImv8KyoqsH37dkGpXLEpKyurcXLEj62LFy/CzMxMLhdQVYx/VlYWkpOTmZS8ImFhYXIKU0JhOcreGWVER0ejR48eSjcZUlJSoKurq/QUkbdRpaWluHbtGkaNGqW26Lq6toDq0ytt1BoSE036VllZiaqqKsyfP1+wbykpKTA0NGTiQjyKC6r8/HyNCls3NjIyMhAUFIQ9e/bIbUjJ9o237du2bWtw2XOxaQhhGdl5SvZvrKysMH78eDg5OaFLly6C9Z00yXUSsgViIuYYENNGiYXY1yTW/CIWjXUeflMgB6yBSU9Px5dffon09HQA/80T4o0OP5BfhbiCNtEkjn7//v1wdHTE6NGjkZqaKidYILvAvHPnDjIzMwXVDg8ePIgWLVqgadOmgqFNjx8/xtSpU+udoNsY8rTeFI4cOYIWLVpg48aNGDlyJHx9feVq6shO3unp6bh165ZWris2NhZ2dnYYPHgwEhMTa9RtKSkpYfL5QvL8Bw4cQPfu3eHn5wcrKyu5UgeKk686x0ronZH97oSEBJiamiqdIE+cOIE2bdowG8XnwfK2StFGyeY61rUtPs9A0xpIjYHa9k2IY8eOoVmzZizkuaioSO5Z88+OX2DVJy/mVZCeng4dHR2Eh4dj8uTJ8Pb2xs6dO9nvZZ1VQPzcL20hhrBMVlaW3L2RdcJkx0R2djbi4uJUnqIdOHAAbdu2VVo6RVNbICZijgExbZRYiH1NYs0vYtFY5+E3CXLAGphZs2Zh3LhxePHiBe7evYtJkyZhypQp8Pf3Z/V4/vzzT0yePBkvXrx4IwvVaRJH//vvv8PQ0BBnzpxBQkIC+vXrh4CAgBpOlib5XomJiTA0NMSJEycQEhKC1atXA6h5CqZMLrwuNKZ8ijeB6OholpuQm5uLmJgYeHp6srpXQPXkd/LkSa1d059//gk9PT1kZWUhOjoa1tbWWL16da3zls6cOYOePXsy9c+5c+ciLi6uxql3Zmam2kW3pu8MP+6V1dK5ffs2li1bxpQj79y5AwcHB3h4eGD06NFsB//OnTuwsbHB8+fPVdqourT1ulDbvhUWFgqGREokEnz99dc4cOAACgoKYG1tjfHjx+Prr79m6njXrl2Dra3tazUvSKVSVFZWYv78+UztLTc3F8OGDYO1tTUTTQKqlWP58MvXpX+K1FdYRiKR4L333oOdnZ3KxS2gfiOmqKgIFhYWOHToEIDqxb6yBb+QLRALsceAmDZKLMS+JrHmFzFpjPPwm8a/OKJBuHTpEvfHH39wzs7OXOvWrblZs2ZxlpaWnL6+PtenTx/unXfe4YKCgrjy8nKuTZs2XHBwMPef//yHa9Kkyau+dNH56KOPuISEBK579+4qP3Pnzh3OyMiIMzY25oYPH845ODhw8fHxXGpqKieVSjmO47iMjAxuy5YtXGVlpcp2Hj9+zMXExHCrV6/mzM3NuebNm3OJiYmcVCrl/vWvf3EAOI7juMOHD3NbtmzhqqqquHfffbfB+0eop6KiguM4jnv77be5yMhI7u7du1ybNm04S0tLrn///tzly5e5nJwcTiqVcmfPnuU+//xzrV3bkydPuNatW3O9e/fmHBwcuNmzZ3OXLl3ikpKSuKKiIo7jOC4hIYHbvHmzYDuVlZXcunXruN69e3NPnz7ltm7dym3ZsoWbMWMGN2XKFI7jOK6kpITLyMjg8vLyBNvS9J0JDQ3lAHCtW7eW+3uJRMJ999133IABAzgLCwtu1apVXJ8+fThzc3POzc2NMzY25nx8fLiioiKubdu23Pbt27kPPvhAqY2qa1uvA3XpW7Nmzbh//Uv19GphYcEFBgZyoaGh3BdffMENHDiQW7t2Lde1a1fu22+/5TiO43R1dbnIyMjXal5o0qQJ99Zbb3EfffQRFxcXx+Xm5nJt2rThdHV1OQMDA+7y5ctceXk5B4DLzc3l+vbty/7udYCfP3jeeustuX9LpVJOKpVye/bs4X788UeuY8eOgn27efMmN3fuXM7NzY07ffo0t2XLFo7jqu+H7Fy1ceNGwXmvSZMm3Pvvv88NHDiQe/r0Kefs7MyNGTOGCwoK4k6cOMHaUWULxETMMSCmjRKLhrgmseYXMWjM8/Abxyt0/t5YkpKSYGBggOHDh2P8+PH4448/MHXqVCbXCVQf79ZWlvZNhJcMz87Ohru7O8uJWbx4Mdzc3NCnTx+W4JqbmysYdlhaWgqpVIonT57I/XzIkCE1kpbVtUVol7i4OJiamrJTn4CAAPj4+LAQrNzcXAwZMgS7du3S6nXx+XxSqRQTJ07E7t27WajM8ePHMXToUEgkEgDVu52qdixlC4DyOULr1q1jOYo5OTn45ptvcOTIEUilUsHTLzHeGYlEAkNDQ+jo6LBE/DVr1sjtwufk5MDV1VXtSZyYbTU2GrJvJSUlSEpKkmsLAEaNGsVOwV6nk6EDBw7A19cXQHVo3uzZs9GjRw+4ubnB0tISOTk5MDMzQ0ZGxqu90DoiprAMb1eqqqpQXl6OoqIi7Ny5Ex4eHti4caPcZ4XmKtlTLh8fH8yePRv29vb49ddfkZmZiYCAAFab6cGDBw0+54k5BhqjXRH7msSaX8Sisc7DbyrkgIlMRkYGOnXqxI5lra2tcerUKZSWlsoZy23btmHYsGFaOS5vrKSkpCAkJASVlZUoLi5GYGAgHBwcMGzYMFhZWQEANm3apFFR6pSUFCxdulTO6PGGjK8TxMdUK4aNEK8WiUSCnj17wsjICCtXrgTw3zoj3t7eLKcmMDAQISEhNcRrGoqkpCTY29vjxo0bqKqqQmhoKGbMmIGMjAwWEhQZGQl7e3vB0Fi+cDdfF4hH8W/c3NzULvDEeGcOHjyIjh074tKlSygrK8PAgQNx+vRplJeXy4Xjbt++HRYWFigoKNBKW40NbfVNtobUtm3bYGpq+lrdJ6B64a2vry8nEFBcXIyEhATEx8ezsT5z5kxWFPh1QkxhGVm7IkthYSGio6Ph4eGB3377Ddu2bWP1AFVdU0hICNuQOXr0KH744QdYWFiw8Xn+/HlYWlrWKHLcEIg5BhqjXRH7msSaX8Sisc7DbzLkgInMlStXWFJmbm4u2rRpA2tra3h4eCAiIgIVFRVYv3696JLCrxtJSUno3r273E5YaWkp8vLycO7cOWaAli5digULFtS6LVkePHgAU1NTVsyWaDykpaWhS5cuOHLkCCQSCTw8PNjvzp49i8DAQHTs2BF+fn5o1apVg6t28WRnZ0NHRwdpaWnsZy9evMDChQsxbdo0lsfw66+/wtnZWaVTr1i4W7amj2zS+d69e9UW7hbrnUlJSWE1xQoKCuDj48MK/vIT6ubNmzVStRKzrcZGQ/aN//uMjAx4eXnhxYsX2LZtG/T19V+7+wRUS2TzNYHy8vJw9erVGgvQTZs2oXPnzq9dsr6YwjLK7Iosz549w6FDh9CrVy80a9ZMpaiTMltQUlKCXbt2wdzcnOWhJSQkYNCgQTUEHRoCMcdAY7QrYl6TWPOLWDTWefhNhxywBmTRokVYuHAhAGDr1q0YM2YMrl+/DhcXl9dOUlhMLl++jHbt2mHTpk0AqmWWr1y5UuOerFmzBl27dhUsYqqsrWvXrtWYuGJjY2FpaSlKEVNCHF6+fIklS5YwQYoHDx6gbdu2bFLjkUgkSExMFK3AriZERUWxEJMHDx4gLi4O+/btQ1VVFSIjIzF+/HhYWFjAwMAAf/zxh2BbioW7ZZ2w8vJyrFu3Tm19GDHfGR4+IT85OVlOwfPFixfw8/OrVfFgMdtqbDRU3/gi0vwpx9q1a1/bhY2bmxvWrFmD/Px8mJmZYcSIEejTpw9iYmJQXl6OK1euwMzM7LWb98QWllG0K4mJiTVqX4WEhOCTTz5RGcKoyhbw15KVlQVvb28MHz4cvXr1YnXyGpqGGAON0a6IcU1izi/1pTHPw286TQCFrFKiwRg6dCi3YcMGrkOHDq/6Ul4pZ86c4cLDwzljY2Pu888/55YvX861bNmSe/r0Kaenp8eFhoZy5eXlXFBQEDdy5EjO0NCwXm1xHMc9e/aMk0qlXIsWLbTVTUIDysrKuHfeeYerqKjg/v3vf3MJCQlcTEwMt2TJEu6zzz57Zcn5hw8fZon0tra2nKWlJSeRSDhjY2MuPDyc4ziOu3DhAtemTRvuf//3fzVu98mTJ9zkyZO5pk2bctu3b+euXbvGSSQS7ttvv+W+/PJLlX8n5jujjICAAK5p06bcrFmzuLfeeouJ1tQFMdtqbIjZt7y8PO7hw4fsWfHvwOvIiRMnuP3793NFRUWcsbExN2nSJC48PJzbuXMnt2PHDq5169bc8+fPuWbNmr3qS9UYiUTChYSEcMuWLeNOnTrFnTp1iktNTeVmzZrFmZubc2lpadzhw4e52NhY7oMPPuCKiorUCssosyuHDh3ivvzyS27Xrl0cx3HcihUruP79+3PGxsZK21BlC/Lz8zkjIyNuxYoVHMdx3P3797n333+fa968ubg3RgUNPQYao12p6zU11PxSVxrrPPzG86o9wDcVxVOW2NhYGBsb/6OL9MoKEWRmZsLX1xcdOnRAWFgYpFIp7t27h4EDB+Lo0aMAhBPQa9sW8Xpw5coV2NjYsN04ISlvsZEdU+fOnYO1tTUWLVqEFStWsJ+bmZmxsgZ1RbFwN1/bRd011fedESI2NhZ9+vQRpR6TmG01Nhqib2/CifytW7fg6+uLr776ip3MAICdnR0Lk3ud+imm2IImdsXc3ByrVq3SuB0hW/CqRE4aegw0RrtSm2vS1vwiBq9yHv4nQQ5YA1NaWopffvkF+vr6r134hZjwQgRjx45lPzt58qRcwi4AuLi4sJdejLZOnDghwtUTDQlv3PlJLDg4GF27dsWzZ8+0dg3KhDLCwsLQvn17+Pj4sGsJDg7G1q1b6/19mhTuFvOd0QR7e3uNighru63Gxpvct7rAL6ofPXoEb29vzJ49G+Hh4YiJiUGXLl2YgtrrgphiC2LZlcY+52lrDDTGd0+Ta9L2/FIXGsM8/E+DHLAGpry8HAcOHHhtY/vFQFGIwMHBgf1OVhkyNjZWrRCBmG0RjYf09HRMnjwZFRUVyM/Px/Tp07Wi3AUIj6nNmzfD0tISq1atQkBAAPT09HD16tV6fZ8mhbu1Oc7FPJl4nU45asub3Lf6wC/cTp8+DVtbW0gkEkyePBkuLi6vZXF6scQWxLIrr8Oc19BjoDG+e5pek7bnl/rwKufhfyLkgBFaQVGIwNHRUe73kZGRMDEx0eiUUMy2iFcPL0awZ88eANUTm7pkdrFRHFOyO5XHjh1DfHw85s6dK9pGiuxOuqbXROOcaKxcv34dpqam2LdvH/uZJmO8MSOG2IJYduV1sAVv4hgQC23PL3WhMczD/zRIhIPQOopCBFevXuUyMjK4oUOH1lqgRMy2iFeDrBhBVVUV99Zbb73S6+HH1Ntvv83t3LmTu3DhAteyZUvus88+e+XXROOcaIw0tndYbMQQgBDLrjRWW/CmjwGxaIzzC8fR83sVkANGvBLy8/M5Pz8/LisriwPAHTlyhPvkk09eeVsEwXHyY6qqqoo7fPgw9/nnnzeaa6JxThDaY+/evdyqVau4w4cPc//zP/9T53bEsitkC15vGuP8QmifN0MbmHjtaNWqFde9e3eusLCQ27t3b70mDzHbIgiOkx9T+/btaxSTI41zgng12NnZcZ9++il3//79erUjll0hW/B60xjnF0L71H0rhyDqQUFBAZeUlMSlpqZy3bp1azRtEQTHNc4x1RiviSDedABwTZo04WJiYurdlljvMNmC1xt6fgTHUQgi8QopLS3l3n333UbXFkFwXOMcU43xmgiC0Byx3mGyBa839PwIcsAIgiAIgiAIgiC0BOWAEQRBEARBEARBaAlywAiCIAiCIAiCILQEOWAEQRAEQRAEQRBaghwwgiAIgiAIgiAILUEOGEEQBEEQBEEQhJYgB4wgCIIgCIIgCEJLkANGEARBEARBEAShJcgBIwiCIAiCIAiC0BLkgBEEQRAEQRAEQWgJcsAIgiAIgiAIgiC0BDlgBEEQBEEQBEEQWoIcMIIgCIIgCIIgCC1BDhhBEARBEARBEISWIAeMIAiCIAiCIAhCS5ADRhAEQRAEQRAEoSXIASMIgiAIgiAIgtAS5IARBEEQBEEQBEFoCXLACIIgCIIgCIIgtAQ5YARBEARBEARBEFqCHDCCIAiCIAiCIAgtQQ4YQRAEQRAEQRCEliAHjCAIgiAIgiAIQkuQA0YQBEEQBEEQBKElyAEjCIIgCIIgCILQEuSAEQRBEARBEARBaAlywAiCIAiCIAiCILQEOWAEQRAEQRAEQRBaghwwgiAIgiAIgiAILUEOGEEQBEEQBEEQhJYgB4wgCIIgCIIgCEJLkANGEARBEARBEAShJcgBIwiCIAiCIAiC0BLkgBEEQRAEQRAEQWgJcsAIgiAIgiAIgiC0BDlgBEEQBEEQBEEQWoIcMIIgCIIgCIIgCC1BDhhBEARBEARBEISWIAeMIAiCIAiCIAhCS5ADRhAEQRAEQRAEoSXIASMIgiAIgiAIgtAS5IARBEEQBEEQBEFoCXLACIIgCIIgCIKDiNeCAAAAsElEQVQgtAQ5YARBEARBEARBEFqCHDCCIAiCIAiCIAgtQQ4YQRAEQRAEQRCEliAHjCAIgiAIgiAIQkuQA0YQBEEQBEEQBKElyAEjCIIgCIIgCILQEuSAEQRBEARBEARBaAlywAiCIAiCIAiCILQEOWAEQRAEQRAEQRBaghwwgiAIgiAIgiAILUEOGEEQBEEQBEEQhJYgB4wgCIIgCIIgCEJLkANGEARBEARBEAShJf4PENoZf0uKNNQAAAAASUVORK5CYII=\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
       "        margin-right:2%;\n",
       "        float:left;\n",
       "        padding-bottom:2%;\n",
       "    }\n",
       "    .title_profiler{\n",
       "        padding:20px;\n",
       "        background-color: #eeeeee\n",
       "    }\n",
       "    .info{\n",
       "        overflow: auto\n",
       "    }\n",
       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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hLfoiZgAAAKAtxGS/Z+xY5Tm3GzsWcClcAQMAAAAAQwgwAAAAADCEAAMAAAAAQwgwAAAAADCEAAMAAAAAQwgwAAAAADCEAAMAAAAAQwgwAAAAADCEAAMAAAAAQwgwAAAAADCEAAMAAAAAQwgwAAAAADCEAAMAAAAAQwIGWGZmpiIiIjR06NALnlu9erVsNpuOHj0qSbIsSwsWLJDL5dLw4cO1d+9e/7b5+flyu91yu93Kz8/3j+/Zs0fDhg2Ty+XSggULZFlWW54XAAAAALQ7AQNszpw5Ki4uvmC8oqJC77//vvr37+8f27Jli7xer7xer3JzczV//nxJ0vHjx7V8+XLt3r1bJSUlWr58uWpqaiRJ8+fPV25urn+/5o4FAAAAAFeTgAE2btw4ORyOC8YXLlyo559/XjabzT9WVFSk2bNny2azacyYMaqtrVVVVZW2bt2q5ORkORwOhYWFKTk5WcXFxaqqqtLJkyc1duxY2Ww2zZ49W4WFhVfmDAEAAACgnWjRZ8A2bdqkfv366cYbb2wy7vP5FB0d7X/sdDrl8/kuOu50Oi8YBwAAAICrmf1yNzxz5oxWrFihbdu2XfBcc5/fstlsLR5vTm5urnJzcyVJ1dXVlztdAAAAAGh3LvsK2IEDB1RWVqYbb7xRMTExqqys1KhRo/T3v/9dTqdTFRUV/m0rKysVFRV10fHKysoLxpuTlZUlj8cjj8ej8PDw1pwjAAAAALQLlx1gw4YN05EjR1ReXq7y8nI5nU7t3btXffv2VUpKitavXy/LsrRr1y717NlTkZGRmjx5srZt26aamhrV1NRo27Ztmjx5siIjI9W9e3ft2rVLlmVp/fr1mjZt2pU8TwAAAAAIuoABNnPmTI0dO1afffaZnE6n8vLyAr7I1KlTNXDgQLlcLt1///165ZVXJEkOh0NLly5VYmKiEhMTtWzZMv+NPV599VXNmzdPLpdLN9xwg6ZMmdLGpwYAAAAA7YvN6kBfwJWQkCCPxxPsaQAAAOAHisl+z9ixynNuN3Ys/LhdTq+06C6IAAAAAIDWI8AAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwJCAAZaZmamIiAgNHTrUP/aLX/xCgwcP1vDhw3XXXXeptrbW/9zKlSvlcrk0aNAgbd261T9eXFysQYMGyeVyKScnxz9eVlampKQkud1uzZgxQ/X19W19bgAAAADQrgQMsDlz5qi4uLjJWHJysvbt26e//OUv+od/+AetXLlSklRaWqqCggLt379fxcXFevDBB9XY2KjGxkY99NBD2rJli0pLS/XWW2+ptLRUkrRo0SItXLhQXq9XYWFhysvLu4KnCQAAAADBFzDAxo0bJ4fD0WRs0qRJstvtkqQxY8aosrJSklRUVKT09HR16dJFsbGxcrlcKikpUUlJiVwulwYOHKjOnTsrPT1dRUVFsixLO3bsUGpqqiQpIyNDhYWFV+ocAQAAAKBdaPVnwH77299qypQpkiSfz6fo6Gj/c06nUz6fL+D4sWPHFBoa6o+578YBAAAA4Gpmb81OK1askN1u16xZsyRJlmVdsI3NZtPZs2ebHQ+0fXNyc3OVm5srSaqurm7NdAEAAACgXWhxgOXn5+vdd9/V9u3b/dHkdDpVUVHh36ayslJRUVGS1Ox47969VVtbq4aGBtnt9ibbny8rK0tZWVmSpISEhJZOFwAAAADajRa9BbG4uFirVq3Spk2b1LVrV/94SkqKCgoKVFdXp7KyMnm9Xo0ePVqJiYnyer0qKytTfX29CgoKlJKSIpvNpvHjx2vjxo2SzkXdtGnT2vbMAAAAAKCdCRhgM2fO1NixY/XZZ5/J6XQqLy9PDz/8sE6dOqXk5GSNGDFCDzzwgCQpPj5eaWlpGjJkiG677TatXbtWnTp1kt1u15o1azR58mTFxcUpLS1N8fHxkqRVq1bp17/+tVwul44dO6a5c+eaOWMAAAAACBKb1dwHstqphIQEeTyeYE8DAAAAP1BM9nvGjlWec7uxY+HH7XJ6pdV3QQQAAAAAtAwBBgAAAACGEGAAAAAAYAgBBgAAAACGEGAAAAAAYAgBBgAAAACGEGAAAAAAYAgBBgAAAACGEGAAAAAAYAgBBgAAAACGEGAAAAAAYAgBBgAAAACGEGAAAAAAYAgBBgAAAACGEGAAAAAAYAgBBgAAAACGEGAAAAAAYAgBBgAAAACGBAywzMxMRUREaOjQof6x48ePKzk5WW63W8nJyaqpqZEkWZalBQsWyOVyafjw4dq7d69/n/z8fLndbrndbuXn5/vH9+zZo2HDhsnlcmnBggWyLOtKnB8AAAAAtBsBA2zOnDkqLi5uMpaTk6OJEyfK6/Vq4sSJysnJkSRt2bJFXq9XXq9Xubm5mj9/vqRzwbZ8+XLt3r1bJSUlWr58uT/a5s+fr9zcXP9+5x8LAAAAAK42AQNs3LhxcjgcTcaKioqUkZEhScrIyFBhYaF/fPbs2bLZbBozZoxqa2tVVVWlrVu3Kjk5WQ6HQ2FhYUpOTlZxcbGqqqp08uRJjR07VjabTbNnz/a/FgAAAABcrVr0GbDDhw8rMjJSkhQZGakjR45Iknw+n6Kjo/3bOZ1O+Xy+i447nc4LxgEAAADgamZvixdp7vNbNputxePNyc3NVW5uriSpurr6B84UAAAAAIKnRVfA+vTpo6qqKklSVVWVIiIiJJ27glVRUeHfrrKyUlFRURcdr6ysvGC8OVlZWfJ4PPJ4PAoPD2/JdAEAAACgXWnRFbCUlBTl5+crOztb+fn5mjZtmn98zZo1Sk9P1+7du9WzZ09FRkZq8uTJevLJJ/033ti2bZtWrlwph8Oh7t27a9euXUpKStL69ev185//vO3PDgAAtJmY7PeMHas853ZjxwIAkwIG2MyZM/Xhhx/q6NGjcjqdWr58ubKzs5WWlqa8vDz1799fGzZskCRNnTpVmzdvlsvlUteuXbVu3TpJksPh0NKlS5WYmChJWrZsmf/GHq+++qrmzJmjr7/+WlOmTNGUKVOu9LkCAAAAQFDZrA70BVwJCQnyeDzBngYAAD9KXAFDW2I94Wp0Ob3Sos+AAQAAAABajwADAAAAAEMIMAAAAAAwhAADAAAAAEMIMAAAAAAwhAADAAAAAEMIMAAAAAAwhAADAAAAAEMIMAAAAAAwhAADAAAAAEMIMAAAAAAwhAADAAAAAEMIMAAAAAAwhAADAAAAAEMIMAAAAAAwhAADAAAAAEMIMAAAAAAwhAADAAAAAENaFWAvvPCC4uPjNXToUM2cOVPffPONysrKlJSUJLfbrRkzZqi+vl6SVFdXpxkzZsjlcikpKUnl5eX+11m5cqVcLpcGDRqkrVu3tskJAQAAAEB71eIA8/l8eumll+TxeLRv3z41NjaqoKBAixYt0sKFC+X1ehUWFqa8vDxJUl5ensLCwvTFF19o4cKFWrRokSSptLRUBQUF2r9/v4qLi/Xggw+qsbGxbc8OAAAAANqRVl0Ba2ho0Ndff62GhgadOXNGkZGR2rFjh1JTUyVJGRkZKiwslCQVFRUpIyNDkpSamqrt27fLsiwVFRUpPT1dXbp0UWxsrFwul0pKStrotAAAAACg/WlxgPXr109PPPGE+vfvr8jISPXs2VM33XSTQkNDZbfbJUlOp1M+n0/SuStm0dHRkiS73a6ePXvq2LFjTcbP3wcAAAAArkYtDrCamhoVFRWprKxMhw4d0unTp7Vly5YLtrPZbJIky7KafS7Q+Plyc3OVkJCghIQEVVdXt3S6AAAAANButDjAPvjgA8XGxio8PFzXXHON7r77bv35z39WbW2tGhoaJEmVlZWKioqSdO7KVkVFhaRzb108ceKEHA5Hk/Hz9/m+rKwseTweeTwehYeHt+okAQAAAKA9aHGA9e/fX7t27dKZM2dkWZa2b9+uIUOGaPz48dq4caMkKT8/X9OmTZMkpaSkKD8/X5K0ceNGTZgwQTabTSkpKSooKFBdXZ3Kysrk9Xo1evToNjw1AAAAAGhf7C3dISkpSampqRo1apTsdrtGjhyprKws3X777UpPT9eSJUs0cuRIzZ07V5I0d+5c3XfffXK5XHI4HCooKJAkxcfHKy0tTUOGDJHdbtfatWvVqVOntj07AAAAAGhHbFZzH8ZqpxISEuTxeII9DQAAfpRist8zdqzynNuNHQvBwXrC1ehyeqVVt6EHAAAAALQcAQYAAAAAhhBgAAAAAGAIAQYAAAAAhhBgAAAAAGAIAQYAAAAAhhBgAAAAAGAIAQYAAAAAhhBgAAAAAGAIAQYAAAAAhhBgAAAAAGAIAQYAAAAAhhBgAAAAAGAIAQYAAAAAhhBgAAAAAGAIAQYAAAAAhhBgAAAAAGAIAQYAAAAAhrQqwGpra5WamqrBgwcrLi5OO3fu1PHjx5WcnCy3263k5GTV1NRIkizL0oIFC+RyuTR8+HDt3bvX/zr5+flyu91yu93Kz89vmzMCAAAAgHbK3pqdHnnkEd12223auHGj6uvrdebMGT333HOaOHGisrOzlZOTo5ycHK1atUpbtmyR1+uV1+vV7t27NX/+fO3evVvHjx/X8uXL5fF4ZLPZdNNNNyklJUVhYWFtfY5XVEz2e8aOVZ5zu7FjAQAAAGh7Lb4CdvLkSf3P//yP5s6dK0nq3LmzQkNDVVRUpIyMDElSRkaGCgsLJUlFRUWaPXu2bDabxowZo9raWlVVVWnr1q1KTk6Ww+FQWFiYkpOTVVxc3IanBgAAAADtS4sD7Msvv1R4eLj+6Z/+SSNHjtS8efN0+vRpHT58WJGRkZKkyMhIHTlyRJLk8/kUHR3t39/pdMrn8wUcBwAAAICrVYsDrKGhQXv37tX8+fP18ccf6/rrr1dOTk7A7S3LumDMZrMFHD9fbm6uEhISlJCQoOrq6pZOFwAAAADajRYHmNPplNPpVFJSkiQpNTVVe/fuVZ8+fVRVVSVJqqqqUkREhH/7iooK//6VlZWKiooKOH6+rKwseTweeTwehYeHt3S6AAAAANButDjA+vbtq+joaH322WeSpO3bt2vIkCFKSUnx38kwPz9f06ZNkySlpKRo/fr1sixLu3btUs+ePRUZGanJkydr27ZtqqmpUU1NjbZt26bJkye34akBAAAAQPvSqrsgvvzyy5o1a5bq6+s1cOBArVu3TmfPnlVaWpry8vLUv39/bdiwQZI0depUbd68WS6XS127dtW6deskSQ6HQ0uXLlViYqIkadmyZXI4HG10WgAAydydWrlLKwAAl6dVATZixAh5PJ4Lxrdv337BmM1m09q1a5t9nczMTGVmZrZmCgAAAADQ4bTqi5gBAAAAAC1HgAEAAACAIQQYAAAAABhCgAEAAACAIQQYAAAAABhCgAEAAACAIQQYAAAAABhCgAEAAACAIQQYAAAAABhCgAEAAACAIQQYAAAAABhCgAEAAACAIQQYAAAAABhCgAEAAACAIQQYAAAAABhCgAEAAACAIQQYAAAAABjS6gBrbGzUyJEjdccdd0iSysrKlJSUJLfbrRkzZqi+vl6SVFdXpxkzZsjlcikpKUnl5eX+11i5cqVcLpcGDRqkrVu3/rAzAQAAAIB2rtUB9uKLLyouLs7/eNGiRVq4cKG8Xq/CwsKUl5cnScrLy1NYWJi++OILLVy4UIsWLZIklZaWqqCgQPv371dxcbEefPBBNTY2/sDTAQAAAID2q1UBVllZqffee0/z5s2TJFmWpR07dig1NVWSlJGRocLCQklSUVGRMjIyJEmpqanavn27LMtSUVGR0tPT1aVLF8XGxsrlcqmkpKQtzgkAAAAA2qVWBdijjz6q559/XiEh53Y/duyYQkNDZbfbJUlOp1M+n0+S5PP5FB0dLUmy2+3q2bOnjh071mT8/H0AAAAA4GrU4gB79913FRERoZtuusk/ZlnWBdvZbLaLPnexfb4vNzdXCQkJSkhIUHV1dUunCwAAAADthr2lO/zpT3/Spk2btHnzZn3zzTc6efKkHn30UdXW1qq9R6Q/AAANfUlEQVShoUF2u12VlZWKioqSdO7KVkVFhZxOpxoaGnTixAk5HA7/+He+v8/3ZWVlKSsrS5KUkJDQ2vMEAAAAgKBr8RWwlStXqrKyUuXl5SooKNCECRP05ptvavz48dq4caMkKT8/X9OmTZMkpaSkKD8/X5K0ceNGTZgwQTabTSkpKSooKFBdXZ3Kysrk9Xo1evToNjw1AAAAAGhfWnwFLJBVq1YpPT1dS5Ys0ciRIzV37lxJ0ty5c3XffffJ5XLJ4XCooKBAkhQfH6+0tDQNGTJEdrtda9euVadOndpqOgAAAADQ7vygALv11lt16623SpIGDhzY7F0Mr732Wm3YsKHZ/RcvXqzFixf/kCkAAAAAQIfR6u8BAwAAAAC0DAEGAAAAAIYQYAAAAABgCAEGAAAAAIYQYAAAAABgCAEGAAAAAIYQYAAAAABgCAEGAAAAAIYQYAAAAABgCAEGAAAAAIYQYAAAAABgCAEGAAAAAIYQYAAAAABgCAEGAAAAAIYQYAAAAABgCAEGAAAAAIYQYAAAAABgCAEGAAAAAIa0OMAqKio0fvx4xcXFKT4+Xi+++KIk6fjx40pOTpbb7VZycrJqamokSZZlacGCBXK5XBo+fLj27t3rf638/Hy53W653W7l5+e30SkBAAAAQPvU4gCz2+3653/+Z/31r3/Vrl27tHbtWpWWlionJ0cTJ06U1+vVxIkTlZOTI0nasmWLvF6vvF6vcnNzNX/+fEnngm358uXavXu3SkpKtHz5cn+0AQAAAMDVqMUBFhkZqVGjRkmSunfvrri4OPl8PhUVFSkjI0OSlJGRocLCQklSUVGRZs+eLZvNpjFjxqi2tlZVVVXaunWrkpOT5XA4FBYWpuTkZBUXF7fhqQEAAABA+/KDPgNWXl6ujz/+WElJSTp8+LAiIyMlnYu0I0eOSJJ8Pp+io6P9+zidTvl8voDjAAAAAHC1srd2x6+++krTp0/Xb37zG/Xo0SPgdpZlXTBms9kCjp8vNzdXubm5kqTq6urWThcAAAAAgq5VV8C+/fZbTZ8+XbNmzdLdd98tSerTp4+qqqokSVVVVYqIiJB07spWRUWFf9/KykpFRUUFHD9fVlaWPB6PPB6PwsPDWzNdAAAAAGgXWhxglmVp7ty5iouL02OPPeYfT0lJ8d/JMD8/X9OmTfOPr1+/XpZladeuXerZs6ciIyM1efJkbdu2TTU1NaqpqdG2bds0efLkNjotAAAAAGh/WvwWxD/96U/63e9+p2HDhmnEiBGSpOeee07Z2dlKS0tTXl6e+vfvrw0bNkiSpk6dqs2bN8vlcqlr165at26dJMnhcGjp0qVKTEyUJC1btkwOh6OtzgsAAAAA2p0WB9gtt9zS7Oe3JGn79u0XjNlsNq1du7bZ7TMzM5WZmdnSKQAAAABAh/SD7oIIAAAAALh8BBgAAAAAGEKAAQAAAIAhBBgAAAAAGEKAAQAAAIAhBBgAAAAAGEKAAQAAAIAhBBgAAAAAGEKAAQAAAIAh9mBPAMD/Lyb7PWPHKs+53dixAAAAcA5XwAAAAADAEAIMAAAAAAwhwAAAAADAEAIMAAAAAAwhwAAAAADAEAIMAAAAAAwhwAAAAADAEAIMAAAAAAwJ+hcxFxcX65FHHlFjY6PmzZun7OzsYE8JAAAAQCvFZL9n5DjlObcbOU5bC+oVsMbGRj300EPasmWLSktL9dZbb6m0tDSYUwIAAACAKyaoAVZSUiKXy6WBAweqc+fOSk9PV1FRUTCnBAAAAABXTFADzOfzKTo62v/Y6XTK5/MFcUYAAAAAcOUE9TNglmVdMGaz2Zo8zs3NVW5uriTp008/VUJCgpG5XY7q6mqFh4cbO15CwlPGjgXzWE9oS9+tp96Gjsd6urqZXk8Sa+pqx995VzfTf/eYXk8XU15efsltghpgTqdTFRUV/seVlZWKiopqsk1WVpaysrJMT+2yJCQkyOPxBHsauEqwntCWWE9oS6wntDXWFNpSR1tPQX0LYmJiorxer8rKylRfX6+CggKlpKQEc0oAAAAAcMUE9QqY3W7XmjVrNHnyZDU2NiozM1Px8fHBnBIAAAAAXDFB/x6wqVOnaurUqcGeRqu017dGomNiPaEtsZ7QllhPaGusKbSljraebFZzd8IAAAAAALS5oH4GDAAAAAB+TAiwy1BRUaHx48crLi5O8fHxevHFFyVJx48fV3Jystxut5KTk1VTUxPkmaIjCLSeNmzYoPj4eIWEhHSoO/kg+AKtqV/84hcaPHiwhg8frrvuuku1tbVBnik6gkDraenSpRo+fLhGjBihSZMm6dChQ0GeKTqCQOvpO6tXr5bNZtPRo0eDNEN0JIHW069+9Sv169dPI0aM0IgRI7R58+Ygz/TieAviZaiqqlJVVZVGjRqlU6dO6aabblJhYaHeeOMNORwOZWdnKycnRzU1NVq1alWwp4t2LtB6stlsCgkJ0c9+9jOtXr26XX3nHdq3QGuqsrJSEyZMkN1u16JFiySJP6NwSYHWk9PpVI8ePSRJL730kkpLS/Xaa68FebZo7wKtpyFDhqiiokLz5s3Tp59+qj179qh3b5PfNIeOKNB6+v3vf69u3brpiSeeCPYULwtXwC5DZGSkRo0aJUnq3r274uLi5PP5VFRUpIyMDElSRkaGCgsLgzlNdBCB1lNcXJwGDRoU5NmhIwq0piZNmiS7/dy9lsaMGaPKyspgThMdRKD19F18SdLp06dls9mCNUV0IIHWkyQtXLhQzz//PGsJl+1i66kjIcBaqLy8XB9//LGSkpJ0+PBhRUZGSjq3II4cORLk2aGj+f56AtpCoDX129/+VlOmTAnSrNBRnb+eFi9erOjoaL355pt6+umngzw7dDTfX0+bNm1Sv379dOONNwZ7Wuigzv/zac2aNRo+fLgyMzPb/ceCCLAW+OqrrzR9+nT95je/afJ/AoHWYD2hrQVaUytWrJDdbtesWbOCODt0NM2tpxUrVqiiokKzZs3SmjVrgjxDdCTfX092u10rVqwg4tFq5//5NH/+fB04cECffPKJIiMj9fjjjwd7ihdFgF2mb7/9VtOnT9esWbN09913S5L69OmjqqoqSefekxoRERHMKaIDaW49AT9EoDWVn5+vd999V2+++SZv88Flu9SfUffcc4/+8z//MwgzQ0d0/no6cOCAysrKdOONNyomJkaVlZUaNWqU/v73vwd7qugAAv2bvFOnTgoJCdH999+vkpKSIM/y4giwy2BZlubOnau4uDg99thj/vGUlBTl5+dLOvePnGnTpgVriuhAAq0noLUCrani4mKtWrVKmzZtUteuXYM4Q3QkgdaT1+v1//emTZs0ePDgYEwPHUxz62nYsGE6cuSIysvLVV5eLqfTqb1796pv375Bni3au0B/Pn13QUSS3n77bQ0dOjQY07ts3AXxMvzv//6vfvKTn2jYsGEKCTnXrM8995ySkpKUlpamv/3tb+rfv782bNggh8MR5NmivQu0nurq6vTzn/9c1dXVCg0N1YgRI7R169YgzxYdQaA1tWDBAtXV1alXr16Szt2Ig7vW4VICrae8vDx99tlnCgkJ0YABA/Taa6+pX79+QZ4t2rtA62nq1Kn+bWJiYuTxeLgLIi4p0Hp666239Mknn8hmsykmJkb/8i//4r9PQ3tEgAEAAACAIbwFEQAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwBACDAAAAAAMIcAAAAAAwJD/D60iMhoUBZkLAAAAAElFTkSuQmCC\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .data_type {\n",
       "        font-size: 0.8em;\n",
       "        font-weight: normal;\n",
       "    }\n",
       "\n",
       "    .column_name {\n",
       "        font-size: 1.2em;\n",
       "    }\n",
       "\n",
       "    .info_items {\n",
       "        margin: 10px 0;\n",
       "        font-size: 0.8em;\n",
       "    }\n",
       "\n",
       "    .optimus_table tr:nth-child(even) {\n",
       "        background-color: #f2f2f2 !important;\n",
       "    }\n",
       "\n",
       "    .optimus_table tr:nth-child(odd) {\n",
       "        background-color: #ffffff !important;\n",
       "    }\n",
       "\n",
       "    .optimus_table thead {\n",
       "        border-bottom: 1px solid black;\n",
       "    }\n",
       "    .optimus_table{\n",
       "        font-size: 12px;\n",
       "    }\n",
       "\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "<div class=\"info_items\">Viewing 10 of 45716 rows / 10 columns</div>\n",
       "<div class=\"info_items\">32 partition(s)</div>\n",
       "\n",
       "<table class=\"optimus_table\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">name</div>\n",
       "            <div class=\"data_type\">1 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">id</div>\n",
       "            <div class=\"data_type\">2 (int)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">nametype</div>\n",
       "            <div class=\"data_type\">3 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">recclass</div>\n",
       "            <div class=\"data_type\">4 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">mass (g)</div>\n",
       "            <div class=\"data_type\">5 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">fall</div>\n",
       "            <div class=\"data_type\">6 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">year</div>\n",
       "            <div class=\"data_type\">7 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">reclat</div>\n",
       "            <div class=\"data_type\">8 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">reclong</div>\n",
       "            <div class=\"data_type\">9 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">GeoLocation</div>\n",
       "            <div class=\"data_type\">10 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "    </tr>\n",
       "\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Acfer⸱232\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            240\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            725.0\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1991⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            27.73944\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            4.32833\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (27.739440,⸱4.328330)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Elephant⸱Moraine⸱90232\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            8641\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            L6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            16.9\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1990⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -76.28795\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            156.46841\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-76.287950,⸱156.468410)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Grove⸱Mountains⸱020090\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            30681\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Martian⸱(shergottite)\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            7.5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2003⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -72.99944\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            75.26111\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-72.999440,⸱75.261110)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Northwest⸱Africa⸱891\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            31912\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H4\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            70.8\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2001⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            None\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            None\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            None\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Queen⸱Alexandra⸱Range⸱93098\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            19187\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            1.2\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1993⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -84.5757\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            162.56524\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-84.575700,⸱162.565240)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Queen⸱Alexandra⸱Range⸱94691\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            20322\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            9.6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1994⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -84.0\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            168.0\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-84.000000,⸱168.000000)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Meteorite⸱Hills⸱00977\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            16211\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            13.2\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2000⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -79.68333\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            159.75\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-79.683330,⸱159.750000)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Grove⸱Mountains⸱020114\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            46531\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            L3\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            1.0\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2003⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -72.98194\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            75.25167\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-72.981940,⸱75.251670)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Pecora⸱Escarpment⸱91483\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            18774\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            5.5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1991⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -85.55819\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -68.31586\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-85.558190,⸱-68.315860)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Ramlat⸱as⸱Sahmah⸱390\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            55656\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H3.8-6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            0.69\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2010⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            20.0949\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            55.69318\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (20.094900,⸱55.693180)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "\n",
       "<div class=\"info_items\">Viewing 10 of 45716 rows / 10 columns</div>\n",
       "<div class=\"info_items\">32 partition(s)</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "op.profiler.run(df, \"*\",infer=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot profile for a specific column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       "    .main{\n",
       "        width:100%;\n",
       "        overflow:auto;\n",
       "        border-bottom:1px solid #eeeeee;\n",
       "        padding: 10px 0;\n",
       "    }\n",
       "    .panel_profiler{\n",
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       "    }\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"title_profiler\">\n",
       "    <h1>Overview</h1>\n",
       "</div>\n",
       "<div class=\"main\">\n",
       "    <div class=\"panel_profiler\">\n",
       "        <h2>Dataset info</h2>\n",
       "        <table>\n",
       "            <tbody>\n",
       "            <tr>\n",
       "                <td>Number of columns</td>\n",
       "                <td>10</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Number of rows</td>\n",
       "                <td>45716</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Total Missing (%)</td>\n",
       "                <td>0.49%</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Total size in memory</td>\n",
       "                <td>66.6 MB</td>\n",
       "\n",
       "            </tr>\n",
       "            </tbody>\n",
       "        </table>\n",
       "    </div>\n",
       "    <div class=\"panel_profiler\">\n",
       "        <h2>Column types</h2>\n",
       "        <table>\n",
       "            <tbody>\n",
       "            <tr>\n",
       "                <td>String</td>\n",
       "                <td>1</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Numeric</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Date</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Bool</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "             <tr>\n",
       "                <td>Array</td>\n",
       "                <td>0</td>\n",
       "\n",
       "            </tr>\n",
       "            <tr>\n",
       "                <td>Not available</td>\n",
       "                <td>0</td>\n",
       "\n",
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       "            </tbody>\n",
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       "</div><style>\n",
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       "\n",
       "\n",
       "\n",
       "</style>\n",
       "\n",
       "<div class=\"main\">\n",
       "    <div class=\"info\">\n",
       "\n",
       "        \n",
       "\n",
       "        <div class=\"panel_profiler\">\n",
       "            <div>\n",
       "                <h2>reclat</h2>\n",
       "                <div>categorical</div>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>Unique</td>\n",
       "                    <td> 12140</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Unique (%)</td>\n",
       "                    <td> 26.555</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing</td>\n",
       "                    <td>16.0</td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>Missing (%)</td>\n",
       "                    <td>7315</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            <div>\n",
       "                <h3>\n",
       "                    Datatypes\n",
       "                </h3>\n",
       "            </div>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        String\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Integer\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Float\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Bool\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Date\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Missing\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        0\n",
       "                    </td>\n",
       "                </tr>\n",
       "                <tr>\n",
       "                    <td>\n",
       "                        Null\n",
       "                    </td>\n",
       "                    <td>\n",
       "                        7315\n",
       "                    </td>\n",
       "\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "            \n",
       "\n",
       "        </div>\n",
       "        <div class=\"panel_profiler\">\n",
       "            <h3>Frequency</h3>\n",
       "            <table>\n",
       "                <tbody>\n",
       "                <th>Value</th>\n",
       "                <th>Count</th>\n",
       "                <th>Frecuency (%)</th>\n",
       "                \n",
       "                <tr>\n",
       "                    <td>None</td>\n",
       "                    <td>7315</td>\n",
       "                    <td>16.001%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>0.0</td>\n",
       "                    <td>6438</td>\n",
       "                    <td>14.083%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-71.5</td>\n",
       "                    <td>4761</td>\n",
       "                    <td>10.414%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-84.0</td>\n",
       "                    <td>3040</td>\n",
       "                    <td>6.65%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-72.0</td>\n",
       "                    <td>1506</td>\n",
       "                    <td>3.294%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-79.68333</td>\n",
       "                    <td>1130</td>\n",
       "                    <td>2.472%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-76.71667</td>\n",
       "                    <td>680</td>\n",
       "                    <td>1.487%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-76.18333</td>\n",
       "                    <td>539</td>\n",
       "                    <td>1.179%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-84.21667</td>\n",
       "                    <td>263</td>\n",
       "                    <td>0.575%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>-86.36667</td>\n",
       "                    <td>226</td>\n",
       "                    <td>0.494%</td>\n",
       "                </tr>\n",
       "\n",
       "                \n",
       "                <tr>\n",
       "                    <td>\"Missing\"</td>\n",
       "                    <td>7315</td>\n",
       "                    <td>16.0%</td>\n",
       "                </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </div>\n",
       "        \n",
       "\n",
       "        \n",
       "    </div>\n",
       "    <table>\n",
       "        \n",
       "        <tr>\n",
       "\n",
       "            <td>\n",
       "\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "            </td>\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        <tr>\n",
       "            <td>\n",
       "                <div>\n",
       "                    <img 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\">\n",
       "                </div>\n",
       "\n",
       "            </td>\n",
       "\n",
       "        </tr>\n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "        \n",
       "\n",
       "    </table>\n",
       "</div><style>\n",
       "    .data_type {\n",
       "        font-size: 0.8em;\n",
       "        font-weight: normal;\n",
       "    }\n",
       "\n",
       "    .column_name {\n",
       "        font-size: 1.2em;\n",
       "    }\n",
       "\n",
       "    .info_items {\n",
       "        margin: 10px 0;\n",
       "        font-size: 0.8em;\n",
       "    }\n",
       "\n",
       "    .optimus_table tr:nth-child(even) {\n",
       "        background-color: #f2f2f2 !important;\n",
       "    }\n",
       "\n",
       "    .optimus_table tr:nth-child(odd) {\n",
       "        background-color: #ffffff !important;\n",
       "    }\n",
       "\n",
       "    .optimus_table thead {\n",
       "        border-bottom: 1px solid black;\n",
       "    }\n",
       "    .optimus_table{\n",
       "        font-size: 12px;\n",
       "    }\n",
       "\n",
       "</style>\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "<div class=\"info_items\">Viewing 10 of 45716 rows / 10 columns</div>\n",
       "<div class=\"info_items\">32 partition(s)</div>\n",
       "\n",
       "<table class=\"optimus_table\">\n",
       "    <thead>\n",
       "    <tr>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">name</div>\n",
       "            <div class=\"data_type\">1 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">id</div>\n",
       "            <div class=\"data_type\">2 (int)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">nametype</div>\n",
       "            <div class=\"data_type\">3 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">recclass</div>\n",
       "            <div class=\"data_type\">4 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">mass (g)</div>\n",
       "            <div class=\"data_type\">5 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">fall</div>\n",
       "            <div class=\"data_type\">6 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">year</div>\n",
       "            <div class=\"data_type\">7 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">reclat</div>\n",
       "            <div class=\"data_type\">8 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">reclong</div>\n",
       "            <div class=\"data_type\">9 (double)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "        <th>\n",
       "            <div class=\"column_name\">GeoLocation</div>\n",
       "            <div class=\"data_type\">10 (string)</div>\n",
       "            <div class=\"data_type\">\n",
       "                \n",
       "                nullable\n",
       "                \n",
       "            </div>\n",
       "        </th>\n",
       "        \n",
       "    </tr>\n",
       "\n",
       "    </thead>\n",
       "    <tbody>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Acfer⸱232\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            240\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            725.0\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1991⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            27.73944\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            4.32833\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (27.739440,⸱4.328330)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Elephant⸱Moraine⸱90232\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            8641\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            L6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            16.9\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1990⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -76.28795\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            156.46841\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-76.287950,⸱156.468410)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Grove⸱Mountains⸱020090\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            30681\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Martian⸱(shergottite)\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            7.5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2003⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -72.99944\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            75.26111\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-72.999440,⸱75.261110)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Northwest⸱Africa⸱891\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            31912\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H4\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            70.8\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2001⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            None\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            None\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            None\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Queen⸱Alexandra⸱Range⸱93098\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            19187\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            1.2\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1993⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -84.5757\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            162.56524\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-84.575700,⸱162.565240)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Queen⸱Alexandra⸱Range⸱94691\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            20322\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            9.6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1994⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -84.0\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            168.0\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-84.000000,⸱168.000000)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Meteorite⸱Hills⸱00977\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            16211\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            13.2\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2000⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -79.68333\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            159.75\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-79.683330,⸱159.750000)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Grove⸱Mountains⸱020114\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            46531\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            L3\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            1.0\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2003⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -72.98194\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            75.25167\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-72.981940,⸱75.251670)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Pecora⸱Escarpment⸱91483\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            18774\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            5.5\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/1991⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -85.55819\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            -68.31586\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (-85.558190,⸱-68.315860)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    <tr>\n",
       "        \n",
       "        <td>\n",
       "            Ramlat⸱as⸱Sahmah⸱390\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            55656\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Valid\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            H3.8-6\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            0.69\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            Found\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            01/01/2010⸱12:00:00⸱AM\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            20.0949\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            55.69318\n",
       "        </td>\n",
       "        \n",
       "        <td>\n",
       "            (20.094900,⸱55.693180)\n",
       "        </td>\n",
       "        \n",
       "    </tr>\n",
       "    \n",
       "    </tbody>\n",
       "</table>\n",
       "\n",
       "<div class=\"info_items\">Viewing 10 of 45716 rows / 10 columns</div>\n",
       "<div class=\"info_items\">32 partition(s)</div>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "op.profiler.run(df, \"reclat\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Output a json file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot histagram for multiple columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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BTJIkSZI6MZBJkiRJUiczCmRJFiW5LMkNSa5P8uIkhybZnOSm9npIG5skH0yyLcm3krxw6Dzr2vibkqyb6ZeSJEmSpLlgpnfIPgD8z6r6TeC3geuBDcBVVbUCuKptAxwHrGg/64HzAJIcCpwBvAg4CjhjX4iTJEmSpPls5ECW5EnAS4ELAKrqgaraA6wBLmrDLgJObO/XABfXwDXAoiSHA8cCm6tqV1XtBjYDq0ftS5IkSZLmipncIXsGsBP4yyTfSPKRJE8EnlZVdwC016e28UuA7UPH72i1/dUlSZIkaV6bSSBbCLwQOK+qXgD8iF9MT5xMJqnVFPUHnyBZn2RLki07d+58uP1KkiRJ0liZSSDbAeyoqmvb9mUMAtqdbSoi7fWuofHLho5fCtw+Rf1Bqur8qlpZVSsXL148g9YlSZIkqb+RA1lVfR/YnuTZrXQ08F1gE7BvpcR1wOXt/SbglLba4irg7jal8XPAMUkOaYt5HNNqkiRJkjSvLZzh8W8CPpbkIOBm4I0MQt6lSU4FbgNOamOvBI4HtgH3tbFU1a4k7wGua+PeXVW7ZtiXJEmSJI29GQWyqvomsHKSXUdPMraA0/Zzno3Axpn0IkmSJElzzUx/D5kkSZIkaUQGMkmSJEnqxEAmSZIkSZ0YyCRJkiSpEwOZJEmSJHViIJMkSZKkTgxkkiRJktSJgUySJEmSOjGQSZIkSVInBjJJkiRJ6sRAJkmSJEmdGMgkSZIkqRMDmSRJkiR1YiCTJEmSpE4MZJIkSZLUiYFMkiRJkjoxkEmSJElSJwYySZIkSerEQCZJkiRJnRjIJEmSJKkTA5kkSZIkdWIgkyRJkqRODGSSJEmS1ImBTJIkSZI6MZBJkiRJUicGMkmSJEnqZMaBLMmCJN9I8pm2fUSSa5PclOQTSQ5q9ce27W1t//Khc5ze6jcmOXamPUmSJEnSXDAbd8jeDFw/tH02cE5VrQB2A6e2+qnA7qp6FnBOG0eSI4G1wHOB1cC5SRbMQl+SJEmSNNZmFMiSLAVOAD7StgO8HLisDbkIOLG9X9O2afuPbuPXAJdU1f1VdQuwDThqJn1JkiRJ0lww0ztk7wfeBvy8bT8F2FNVe9v2DmBJe78E2A7Q9t/dxv9TfZJjJEmSJGneGjmQJXklcFdVfW24PMnQmmbfVMdM/Mz1SbYk2bJz586H1a8kSZIkjZuZ3CH7XeDVSW4FLmEwVfH9wKIkC9uYpcDt7f0OYBlA2/9kYNdwfZJjfklVnV9VK6tq5eLFi2fQuiRJkiT1N3Igq6rTq2ppVS1nsCjHF6rqtcDVwGvasHXA5e39prZN2/+FqqpWX9tWYTwCWAF8ddS+JEmSJGmuWDj9kIft7cAlSd4LfAO4oNUvAD6aZBuDO2NrAapqa5JLge8Ce4HTqupnj0BfkiRJkjRWZiWQVdUXgS+29zczySqJVfUT4KT9HH8mcOZs9CJJkiRJc8Vs/B4ySZIkSdIIDGSSJEmS1ImBTJIkSZI6MZBJkiRJUicGMkmSJEnqxEAmSZIkSZ0YyCRJkiSpEwOZJEmSJHUyK78YWpI03pZvuKJ3CwDcetYJvVuQJGmseIdMkiRJkjoxkEmSJElSJwYySZIkSerEQCZJkiRJnRjIJEmSJKkTA5kkSZIkdWIgkyRJkqRODGSSJEmS1ImBTJIkSZI6Wdi7AUnSgWv5hit6t8CtZ53QuwVJ0gHMO2SSJEmS1ImBTJIkSZI6MZBJkiRJUicGMkmSJEnqxEAmSZIkSZ0YyCRJkiSpEwOZJEmSJHUyciBLsizJ1UmuT7I1yZtb/dAkm5Pc1F4PafUk+WCSbUm+leSFQ+da18bflGTdzL+WJEmSJI2/mdwh2wv8aVU9B1gFnJbkSGADcFVVrQCuatsAxwEr2s964DwYBDjgDOBFwFHAGftCnCRJkiTNZyMHsqq6o6q+3t7/ELgeWAKsAS5qwy4CTmzv1wAX18A1wKIkhwPHApuraldV7QY2A6tH7UuSJEmS5opZeYYsyXLgBcC1wNOq6g4YhDbgqW3YEmD70GE7Wm1/dUmSJEma12YcyJIcDHwSeEtV3TPV0ElqNUV9ss9an2RLki07d+58+M1KkiRJ0hiZUSBL8hgGYexjVfWpVr6zTUWkvd7V6juAZUOHLwVun6L+IFV1flWtrKqVixcvnknrkiRJktTdTFZZDHABcH1VvW9o1yZg30qJ64DLh+qntNUWVwF3tymNnwOOSXJIW8zjmFaTJEmSpHlt4QyO/V3g9cC3k3yz1d4BnAVcmuRU4DbgpLbvSuB4YBtwH/BGgKraleQ9wHVt3LuratcM+pIkSZKkOWHkQFZVX2by578Ajp5kfAGn7edcG4GNo/YiSZIkSXPRrKyyKEmSJEl6+AxkkiRJktTJTJ4hk+aN5Ruu6N0Ct551Qu8WJEmS9CjzDpkkSZIkdWIgkyRJkqRODGSSJEmS1ImBTJIkSZI6MZBJkiRJUieusqhHnSsaSpIkSQPeIZMkSZKkTgxkkiRJktSJgUySJEmSOjGQSZIkSVInBjJJkiRJ6sRAJkmSJEmdGMgkSZIkqRMDmSRJkiR1YiCTJEmSpE4W9m5AkiRNbfmGK3q3wK1nndC7BUmal7xDJkmSJEmdGMgkSZIkqRMDmSRJkiR14jNk85zPHUiSJEnjyztkkiRJktSJgUySJEmSOnHK4ixyeqAkSZKkh2NsAlmS1cAHgAXAR6rqrM4tSZKkOcT/MSppLhqLQJZkAfBh4F8BO4Drkmyqqu/27UySdKDxL/WSpEfTWAQy4ChgW1XdDJDkEmANYCDTAWsc/1I4Dj2Bf1mVJEnzx7gs6rEE2D60vaPVJEmSJGneSlX17oEkJwHHVtUftO3XA0dV1ZsmjFsPrG+bzwZufFQb1Tg5DPhB7yY0J3ntaFReOxqF141G5bUz9/16VS2ebtC4TFncASwb2l4K3D5xUFWdD5z/aDWl8ZVkS1Wt7N2H5h6vHY3Ka0ej8LrRqLx2DhzjMmXxOmBFkiOSHASsBTZ17kmSJEmSHlFjcYesqvYm+RPgcwyWvd9YVVs7tyVJkiRJj6ixCGQAVXUlcGXvPjRnOHVVo/La0ai8djQKrxuNymvnADEWi3pIkiRJ0oFoXJ4hkyRJkqQDjoFMYy/JSUm2Jvl5kpUT9p2eZFuSG5McO1Rf3Wrbkmx49LvWuPGa0FSSbExyV5LvDNUOTbI5yU3t9ZBWT5IPtmvpW0le2K9z9ZZkWZKrk1zf/lv15lb3+tF+JXlckq8m+bt23byr1Y9Icm27bj7RFrsjyWPb9ra2f3nP/jW7DGSaC74D/BvgS8PFJEcyWJHzucBq4NwkC5IsAD4MHAccCZzcxuoA5TWhh+BCBv8eGbYBuKqqVgBXtW0YXEcr2s964LxHqUeNp73An1bVc4BVwGnt3y9eP5rK/cDLq+q3gecDq5OsAs4GzmnXzW7g1Db+VGB3VT0LOKeN0zxhINPYq6rrq2qyXwK+Brikqu6vqluAbcBR7WdbVd1cVQ8Al7SxOnB5TWhKVfUlYNeE8hrgovb+IuDEofrFNXANsCjJ4Y9Opxo3VXVHVX29vf8hcD2wBK8fTaH987+3bT6m/RTwcuCyVp943ey7ni4Djk6SR6ldPcIMZJrLlgDbh7Z3tNr+6jpweU1oFE+rqjtg8Jdu4Kmt7vWkSbVpZC8ArsXrR9Nos3q+CdwFbAb+HthTVXvbkOFr45+um7b/buApj27HeqSMzbL3OrAl+V/Ar06y651Vdfn+DpukVkz+PxpcTvTAtr9rRRqF15MeJMnBwCeBt1TVPVPcvPD6EQBV9TPg+UkWAX8NPGeyYe3V62YeM5BpLFTVK0Y4bAewbGh7KXB7e7+/ug5MU10r0v7cmeTwqrqjTSm7q9W9nvRLkjyGQRj7WFV9qpW9fvSQVNWeJF9k8AzioiQL212w4Wtj33WzI8lC4Mk8eJq15iinLGou2wSsbSsPHcHgAemvAtcBK9pKRQcxWPhjU8c+1Z/XhEaxCVjX3q8DLh+qn9JWy1sF3L1vapoOPO05nguA66vqfUO7vH60X0kWtztjJHk88AoGzx9eDbymDZt43ey7nl4DfKH8ZcLzhr8YWmMvyb8G/huwGNgDfLOqjm373gn8PoNVrt5SVZ9t9eOB9wMLgI1VdWaP3jU+vCY0lSQfB14GHAbcCZwBfBq4FPg14DbgpKra1f4C/iEGqzLeB7yxqrb06Fv9Jfk94H8D3wZ+3srvYPAcmdePJpXktxgs0rGAwQ2SS6vq3UmewWDhqUOBbwCvq6r7kzwO+CiDZxR3AWur6uY+3Wu2GcgkSZIkqROnLEqSJElSJwYySZIkSerEQCZJkiRJnRjIJEmSJKkTA5kkSZIkdWIgkyRJkqRODGSSJEmS1ImBTJIkSZI6+f/WpH0dHKwjDgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plots.hist([\"id\", \"reclong\"], 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plots.frequency([\"id\", \"reclong\"], 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x207ba241470>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9o6q+3Pv838CjvHB1LE2JoXvCKMu4SaeV3psMLgUenG4lepahe8KGl2iTZlmS84C/At5bVf817Xq0wtA9YZRl3KTTQpKzWQncP6+qz067Hp1g6J4wyjJu0szrvS7mz4BHq+rWadej5zN0e3qv2tgD3MXKjYdPV9Wh6VbVPUnuAO4HvjfJYpLrp11TB10O/AzwE0m+0tveOO2itMIpY5LUkD1dSWrI0JWkhgxdSWrI0JWkhgxdSWrI0JWkhgxdSWro/wFSnTGHqUkw1gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.correlation([\"id\",\"mass (g)\", \"reclat\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.        , -0.01888518,  0.25706522],\n",
       "       [-0.01888518,  1.        ,  0.02892697],\n",
       "       [ 0.25706522,  0.02892697,  1.        ]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.correlation([\"id\",\"mass (g)\", \"reclat\"], output=\"array\")"
   ]
  }
 ],
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