{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predicting the loan default risk of Czech bank customers using getML\n",
    "\n",
    "### Introduction to relational learning with getML\n",
    "\n",
    "This notebook demonstrates the application of our relational learning algorithm to predict if a customer of a bank will default on his loan. We train the predictor on customer metadata, transaction history, as well as other successful and unsuccessful loans.\n",
    "\n",
    "Summary:\n",
    "\n",
    "- Prediction type: __Binary classification__\n",
    "- Domain: __Finance__\n",
    "- Prediction target: __Loan default__\n",
    "- Source data: __8 tables, 78.8 MB__\n",
    "- Population size: __682__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Background\n",
    "\n",
    "This notebook features a textbook example of predictive analytics applied to the financial sector. A loan is the lending of money to companies or individuals. Banks grant loans in exchange for the promise of repayment. Loan default is defined as the failure to meet this legal obligation, for example, when a home buyer fails to make a mortgage payment. A bank needs to estimate the risk it carries when granting loans to potentially non-performing customers.\n",
    "\n",
    "The analysis is based on the [financial](https://relational.fit.cvut.cz/dataset/Financial) dataset from the [the CTU Prague Relational Learning Repository](https://arxiv.org/abs/1511.03086) (Motl and Schulte, 2015) (Now residing at [relational-data.org](https://relational-data.org/dataset/Financial).)\n",
    "."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's get started with the analysis and set-up your session:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "getML engine is already running.\n",
      "\n",
      "Connected to project 'loans'\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from pathlib import Path\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from IPython.display import Image, Markdown\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import getml\n",
    "\n",
    "getml.engine.launch(home_directory=Path.home(), allow_remote_ips=True, token='token')\n",
    "getml.engine.set_project(\"loans\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Loading data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1 Download from source\n",
    "\n",
    "Downloading the raw data from the CTU Prague Relational Learning Repository into a prediction ready format takes time. To get to the getML model building as fast as possible, we prepared the data for you and excluded the code from this notebook. It will be made available in a future version."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Loading population_train...\n",
      " 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "\n",
      "Loading population_test...\n",
      " 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "\n",
      "Loading order...\n",
      " 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "\n",
      "Loading trans...\n",
      " 100% |██████████| [elapsed: 00:01, remaining: 00:00]          \n",
      "\n",
      "Loading meta...\n",
      " 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n"
     ]
    }
   ],
   "source": [
    "population_train, population_test, order, trans, meta = getml.datasets.load_loans(roles=True, units=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2 Prepare data for getML\n",
    "\n",
    "The `getml.datasets.load_loans` method took care of the entire data lifting:\n",
    "* Downloads csv's from our servers in python\n",
    "* Converts csv's to getML [DataFrames](https://docs.getml.com/latest/api/getml.data.DataFrame.html#dataframe)\n",
    "* Sets [roles](https://docs.getml.com/latest/user_guide/annotating_data/annotating_data.html#roles) to columns inside getML DataFrames\n",
    "\n",
    "The only thing left is to set [units](https://docs.getml.com/latest/user_guide/annotating_data/annotating_data.html#annotating-units) to columns that the relational learning algorithm is allowed to compare to each other."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Data visualization__\n",
    "\n",
    "To simplify the notebook, original data model (image below) is condensed into 4 tables, by resolving the trivial one-to-one and many-to-one joins:\n",
    "\n",
    "- A population table `population_{train, test}`, consiting of `loan` and `account` tables\n",
    "- Three peripheral tables: `order`, `trans`, and `meta`.\n",
    "- Whereas `meta` is made up of `card`, `client`, `disp` and `district`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {
      "image/png": {
       "width": 500
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(\"assets/loans-schema.png\", width=500)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Population table\n",
    "\n",
    "- Information on the loan itself (duration, amount, date, ...)\n",
    "- Geo-information about the branch where the loans was granted (A**)\n",
    "- Column `status` contains binary target. Levels [A, C] := _loan paid back_ and [B, D] := _loan default_;\n",
    "  we recoded status to our binary target: `default`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "population_train.set_role(\"date_loan\", \"time_stamp\")\n",
    "population_test.set_role(\"date_loan\", \"time_stamp\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  }\n",
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       "  th:nth-child(1) {\n",
       "    text-align: right !important;\n",
       "    border-right: 1px solid LightGray;\n",
       "  }\n",
       "  th.sub-header {\n",
       "    font-weight: normal;\n",
       "    font-style: italic;\n",
       "  }\n",
       "  .join_key,\n",
       "  .numerical,\n",
       "  .target,\n",
       "  .unused_float {\n",
       "    text-align: right !important;\n",
       "  }\n",
       "\n",
       "  .char-align {\n",
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       "  span.left {\n",
       "    text-align: right;\n",
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       "  span.right {\n",
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       "</style>\n",
       "\n",
       "<table class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      \n",
       "        \n",
       "          <th>name</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"time_stamp\">                  date_loan</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"join_key\">account_id</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"target\">default</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"categorical\">frequency         </th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"numerical\"> duration</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"numerical\"> payments</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"numerical\">   amount</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_float\">     loan_id</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_float\"> district_id</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_float\">date_account</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_string\">status       </th>\n",
       "        \n",
       "      \n",
       "    </tr>\n",
       "    \n",
       "      <tr>\n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header\">role</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header time_stamp\">                 time_stamp</th>\n",
       "          \n",
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       "          \n",
       "            <th class=\"sub-header join_key\">  join_key</th>\n",
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       "          \n",
       "            <th class=\"sub-header numerical\">numerical</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header numerical\">numerical</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header numerical\">numerical</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header unused_float\">unused_float</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header unused_float\">unused_float</th>\n",
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       "        \n",
       "          \n",
       "            <th class=\"sub-header unused_float\">unused_float</th>\n",
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       "          \n",
       "            <th class=\"sub-header unused_string\">unused_string</th>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header\">unit</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header time_stamp\">time stamp, comparison only</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header join_key\">          </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header target\">       </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header categorical\">                  </th>\n",
       "          \n",
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       "          \n",
       "            <th class=\"sub-header numerical\">         </th>\n",
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       "          \n",
       "            <th class=\"sub-header numerical\">         </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header numerical\">    money</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header unused_float\">            </th>\n",
       "          \n",
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       "          \n",
       "            <th class=\"sub-header unused_float\">            </th>\n",
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       "          \n",
       "            <th class=\"sub-header unused_string\">             </th>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "  </thead>\n",
       "  <tbody>\n",
       "    \n",
       "      <tr>\n",
       "        <th>0</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1996-04-29</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">19</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK MESICNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">12</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2523</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">30276</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">4961</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">21</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1995</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">B</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1998-10-14</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">37</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK MESICNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">60</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">5308</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">318480</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">4967</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">20</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1997</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">D</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>2</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1998-04-19</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">38</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK TYDNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">48</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2307</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">110736</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">4968</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">19</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1997</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">C</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>3</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1997-08-10</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">97</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK MESICNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">12</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">8573</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">102876</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">4986</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">74</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1996</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">A</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>4</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1996-11-06</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">132</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK PO OBRATU</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">12</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">7370</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">88440</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">4996</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">40</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1996</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">A</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th></th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">...</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>218</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1995-12-04</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11042</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK MESICNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">36</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">6032</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">217152</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">7243</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">72</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1995</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">A</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>219</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1996-08-20</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11054</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK TYDNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">60</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2482</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">148920</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">7246</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">59</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1996</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">C</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>220</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1994-01-31</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11111</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK MESICNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">36</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3004</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">108144</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">7259</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1993</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">A</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>221</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1998-11-22</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11317</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK MESICNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">60</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">5291</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">317460</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">7292</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">50</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1997</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">C</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>222</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1996-12-27</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11362</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align target\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">POPLATEK MESICNE</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">24</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">5392</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">129408</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">7308</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">67</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1995</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">A</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "  </tbody>\n",
       "</table>\n",
       "\n",
       "  <p>\n",
       "    223 rows x 11 columns<br />\n",
       "    memory usage: 0.02 MB<br />\n",
       "    name: population_test<br />\n",
       "    type: getml.DataFrame<br />\n",
       "    \n",
       "  </p>\n"
      ],
      "text/plain": [
       "name                     date_loan   account_id   default   frequency            ...      amount        loan_id    district_id\n",
       "role                    time_stamp     join_key    target   categorical          ...   numerical   unused_float   unused_float\n",
       "unit   time stamp, comparison only                                               ...       money                              \n",
       "   0                    1996-04-29           19         1   POPLATEK MESICNE     ...       30276           4961             21\n",
       "   1                    1998-10-14           37         1   POPLATEK MESICNE     ...      318480           4967             20\n",
       "   2                    1998-04-19           38         0   POPLATEK TYDNE       ...      110736           4968             19\n",
       "   3                    1997-08-10           97         0   POPLATEK MESICNE     ...      102876           4986             74\n",
       "   4                    1996-11-06          132         0   POPLATEK PO OBRATU   ...       88440           4996             40\n",
       "                               ...          ...       ...   ...                              ...            ...            ...\n",
       " 218                    1995-12-04        11042         0   POPLATEK MESICNE     ...      217152           7243             72\n",
       " 219                    1996-08-20        11054         0   POPLATEK TYDNE       ...      148920           7246             59\n",
       " 220                    1994-01-31        11111         0   POPLATEK MESICNE     ...      108144           7259              1\n",
       " 221                    1998-11-22        11317         0   POPLATEK MESICNE     ...      317460           7292             50\n",
       " 222                    1996-12-27        11362         0   POPLATEK MESICNE     ...      129408           7308             67\n",
       "\n",
       "name   date_account   status       \n",
       "role   unused_float   unused_string\n",
       "unit                               \n",
       "   0           1995   B            \n",
       "   1           1997   D            \n",
       "   2           1997   C            \n",
       "   3           1996   A            \n",
       "   4           1996   A            \n",
       "                ...   ...          \n",
       " 218           1995   A            \n",
       " 219           1996   C            \n",
       " 220           1993   A            \n",
       " 221           1997   C            \n",
       " 222           1995   A            \n",
       "\n",
       "\n",
       "223 rows x 11 columns\n",
       "memory usage: 0.02 MB\n",
       "type: getml.DataFrame"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Peripheral tables\n",
    "\n",
    "- `meta`\n",
    "  - Meta info about the client (card_type, gender, ...)\n",
    "  - Geo-information about the client\n",
    "- `order`\n",
    "  - Permanent orders related to a loan (amount, balance, ...)\n",
    "- `trans`\n",
    "  - Transactions related to a given loan (amount, ...)\n",
    "\n",
    "While the contents of `meta` and `order` are omitted for brevity, here are contents of `trans`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      \n",
       "        \n",
       "          <th>   name</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"time_stamp\">                       date</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"join_key\">account_id</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"categorical\">type       </th>\n",
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       "        \n",
       "          <th class=\"categorical\">k_symbol   </th>\n",
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       "          <th class=\"categorical\">bank       </th>\n",
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       "        \n",
       "          <th class=\"categorical\">operation    </th>\n",
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       "          <th class=\"numerical\">   amount</th>\n",
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       "            <th class=\"sub-header time_stamp\">                 time_stamp</th>\n",
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       "            <th class=\"sub-header join_key\">  join_key</th>\n",
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       "        \n",
       "          \n",
       "            <th class=\"sub-header categorical\">categorical  </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header numerical\">numerical</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header numerical\">numerical</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header unused_float\">unused_float</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header unused_string\">unused_string</th>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header\">   unit</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header time_stamp\">time stamp, comparison only</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header join_key\">          </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header categorical\">           </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header categorical\">           </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header categorical\">           </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header categorical\">             </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header numerical\">         </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header numerical\">    money</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header unused_float\">            </th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header unused_string\">             </th>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "  </thead>\n",
       "  <tbody>\n",
       "    \n",
       "      <tr>\n",
       "        <th>0</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1995-03-24</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">1</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">VKLAD</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1000</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1000</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1995-04-13</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">1</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">AB</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PREVOD Z UCTU</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3679</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">4679</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">41403269.0</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>2</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1995-05-13</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">1</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">AB</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PREVOD Z UCTU</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3679</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">20977</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">6</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">41403269.0</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>3</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1995-06-13</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">1</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">AB</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PREVOD Z UCTU</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3679</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">26835</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">7</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">41403269.0</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>4</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1995-07-13</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">1</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">AB</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PREVOD Z UCTU</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3679</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">30415</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">8</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">41403269.0</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th></th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">...</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1056315</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1998-08-31</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">10451</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">UROK</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">62</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">17300</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">3682983</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1056316</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1998-09-30</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">10451</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">UROK</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">49</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">13442</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">3682984</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1056317</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1998-10-31</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">10451</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">UROK</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">34</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">10118</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">3682985</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1056318</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1998-11-30</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">10451</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">UROK</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">26</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">8398</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">3682986</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1056319</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"time_stamp\">1998-12-31</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">10451</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">PRIJEM</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">UROK</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">42</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">13695</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">3682987</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "  </tbody>\n",
       "</table>\n",
       "\n",
       "  <p>\n",
       "    1056320 rows x 10 columns<br />\n",
       "    memory usage: 67.20 MB<br />\n",
       "    name: trans<br />\n",
       "    type: getml.DataFrame<br />\n",
       "    \n",
       "  </p>\n"
      ],
      "text/plain": [
       "   name                          date   account_id   type          k_symbol      ...   operation          amount     balance\n",
       "   role                    time_stamp     join_key   categorical   categorical   ...   categorical     numerical   numerical\n",
       "   unit   time stamp, comparison only                                            ...                                   money\n",
       "      0                    1995-03-24            1   PRIJEM        NULL          ...   VKLAD                1000        1000\n",
       "      1                    1995-04-13            1   PRIJEM        NULL          ...   PREVOD Z UCTU        3679        4679\n",
       "      2                    1995-05-13            1   PRIJEM        NULL          ...   PREVOD Z UCTU        3679       20977\n",
       "      3                    1995-06-13            1   PRIJEM        NULL          ...   PREVOD Z UCTU        3679       26835\n",
       "      4                    1995-07-13            1   PRIJEM        NULL          ...   PREVOD Z UCTU        3679       30415\n",
       "                                  ...          ...   ...           ...                 ...                   ...         ...\n",
       "1056315                    1998-08-31        10451   PRIJEM        UROK          ...   NULL                   62       17300\n",
       "1056316                    1998-09-30        10451   PRIJEM        UROK          ...   NULL                   49       13442\n",
       "1056317                    1998-10-31        10451   PRIJEM        UROK          ...   NULL                   34       10118\n",
       "1056318                    1998-11-30        10451   PRIJEM        UROK          ...   NULL                   26        8398\n",
       "1056319                    1998-12-31        10451   PRIJEM        UROK          ...   NULL                   42       13695\n",
       "\n",
       "   name       trans_id   account      \n",
       "   role   unused_float   unused_string\n",
       "   unit                               \n",
       "      0              1   NULL         \n",
       "      1              5   41403269.0   \n",
       "      2              6   41403269.0   \n",
       "      3              7   41403269.0   \n",
       "      4              8   41403269.0   \n",
       "                   ...   ...          \n",
       "1056315        3682983   NULL         \n",
       "1056316        3682984   NULL         \n",
       "1056317        3682985   NULL         \n",
       "1056318        3682986   NULL         \n",
       "1056319        3682987   NULL         \n",
       "\n",
       "\n",
       "1056320 rows x 10 columns\n",
       "memory usage: 67.20 MB\n",
       "type: getml.DataFrame"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trans"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3 Define relational model\n",
    "\n",
    "To start with relational learning, we need to specify an abstract data model. Here, we use the [high-level star schema API](https://docs.getml.com/latest/api/getml.data.StarSchema.html) that allows us to define the abstract data model and construct a [container](https://docs.getml.com/latest/api/getml.data.Container.html) with the concrete data at one-go. While a simple `StarSchema` indeed works in many cases, it is not sufficient for more complex data models like schoflake schemas, where you would have to define the data model and construct the container in separate steps, by utilzing getML's [full-fledged data model](https://docs.getml.com/latest/api/getml.data.DataModel.html) and [container](https://docs.getml.com/latest/api/getml.data.Container.html) APIs respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<span style='font-size: 1.2rem; font-weight: 500;'>data model</span>\n",
       "            <div style='margin-top: 15px; margin-bottom: 5px;'>\n",
       "            <div style='margin-bottom: 10px; font-size: 1rem;'>diagram</div>\n",
       "            <div style=\"height:320px;width:660px;position:relative;\"><svg height=\"310\" width=\"650\"><rect y=\"0\" x=\"0\" rx=\"10\" ry=\"10\" width=\"150\" height=\"90\" style=\"fill:#6829c2;stroke-width:0;\" /><text y=\"73.8\" x=\"75.0\" dominant-baseline=\"middle\" text-anchor=\"middle\" fill=\"white\">trans</text><rect x=\"51\" y=\"10\" rx=\"4\" ry=\"4\" width=\"48\" height=\"48\" style=\" fill:#6829c2;stroke:#ffffff;stroke-width:3;\" /><line x1=\"67.0\" y1=\"10\" x2=\"67.0\" y2=\"58\" style=\"stroke:white;stroke-width:3\" /><line x1=\"83.0\" y1=\"10\" x2=\"83.0\" y2=\"58\" style=\"stroke:white;stroke-width:3\" /><line x1=\"51\" y1=\"26.0\" x2=\"99\" y2=\"26.0\" style=\"stroke:white;stroke-width:3\" /><line x1=\"51\" y1=\"42.0\" x2=\"99\" y2=\"42.0\" style=\"stroke:white;stroke-width:3\" /><rect y=\"110\" x=\"0\" rx=\"10\" ry=\"10\" width=\"150\" height=\"90\" style=\"fill:#6829c2;stroke-width:0;\" /><text y=\"183.8\" x=\"75.0\" dominant-baseline=\"middle\" text-anchor=\"middle\" fill=\"white\">order</text><rect x=\"51\" y=\"120\" rx=\"4\" ry=\"4\" width=\"48\" height=\"48\" style=\" fill:#6829c2;stroke:#ffffff;stroke-width:3;\" /><line x1=\"67.0\" y1=\"120\" x2=\"67.0\" y2=\"168\" style=\"stroke:white;stroke-width:3\" /><line x1=\"83.0\" y1=\"120\" x2=\"83.0\" y2=\"168\" style=\"stroke:white;stroke-width:3\" /><line x1=\"51\" y1=\"136.0\" x2=\"99\" y2=\"136.0\" style=\"stroke:white;stroke-width:3\" /><line x1=\"51\" y1=\"152.0\" x2=\"99\" y2=\"152.0\" style=\"stroke:white;stroke-width:3\" /><rect y=\"220\" x=\"0\" rx=\"10\" ry=\"10\" width=\"150\" height=\"90\" style=\"fill:#6829c2;stroke-width:0;\" /><text y=\"293.8\" x=\"75.0\" dominant-baseline=\"middle\" text-anchor=\"middle\" fill=\"white\">meta</text><rect x=\"51\" y=\"230\" rx=\"4\" ry=\"4\" width=\"48\" height=\"48\" style=\" fill:#6829c2;stroke:#ffffff;stroke-width:3;\" /><line x1=\"67.0\" y1=\"230\" x2=\"67.0\" y2=\"278\" style=\"stroke:white;stroke-width:3\" /><line x1=\"83.0\" y1=\"230\" x2=\"83.0\" y2=\"278\" style=\"stroke:white;stroke-width:3\" /><line x1=\"51\" y1=\"246.0\" x2=\"99\" y2=\"246.0\" style=\"stroke:white;stroke-width:3\" /><line x1=\"51\" y1=\"262.0\" x2=\"99\" y2=\"262.0\" style=\"stroke:white;stroke-width:3\" /><rect y=\"220\" x=\"500\" rx=\"10\" ry=\"10\" width=\"150\" height=\"90\" style=\"fill:#6829c2;stroke-width:0;\" /><text y=\"293.8\" x=\"575.0\" dominant-baseline=\"middle\" text-anchor=\"middle\" fill=\"white\">population</text><rect x=\"551\" y=\"230\" rx=\"4\" ry=\"4\" width=\"48\" height=\"48\" style=\" fill:#6829c2;stroke:#ffffff;stroke-width:3;\" /><line x1=\"567.0\" y1=\"230\" x2=\"567.0\" y2=\"278\" style=\"stroke:white;stroke-width:3\" /><line x1=\"583.0\" y1=\"230\" x2=\"583.0\" y2=\"278\" style=\"stroke:white;stroke-width:3\" /><line x1=\"551\" y1=\"246.0\" x2=\"599\" y2=\"246.0\" style=\"stroke:white;stroke-width:3\" /><line x1=\"551\" y1=\"262.0\" x2=\"599\" y2=\"262.0\" style=\"stroke:white;stroke-width:3\" /><line x1=\"150\" y1=\"43.0\" x2=\"573.0\" y2=\"43.0\" style=\"stroke:#808080;;stroke-width:4\" /><line x1=\"573.0\" y1=\"41.0\" x2=\"573.0\" y2=\"210\" style=\"stroke:#808080;;stroke-width:4\" /><polygon points=\"573.0, 220 567.0, 210 579.0, 210 \" style=\"fill:#808080;;stroke-width:0;\" /><rect y=\"10.0\" x=\"249.0\" rx=\"10\" ry=\"10\" width=\"150\" height=\"70\" style=\"fill:#6829c2;stroke-width:0;\" /><text dominant-baseline=\"middle\" text-anchor=\"middle\" fill=\"white\"><tspan y=\"40.0\" x=\"324.0\" font-size=\"7pt\" >account_id = account_id</tspan><tspan y=\"50.0\" x=\"324.0\" font-size=\"7pt\" >date &lt;= date_loan</tspan></text><line x1=\"150\" y1=\"153.0\" x2=\"573.0\" y2=\"153.0\" style=\"stroke:#808080;;stroke-width:4\" /><line x1=\"573.0\" y1=\"151.0\" x2=\"573.0\" y2=\"210\" style=\"stroke:#808080;;stroke-width:4\" /><polygon points=\"573.0, 220 567.0, 210 579.0, 210 \" style=\"fill:#808080;;stroke-width:0;\" /><rect y=\"120.0\" x=\"249.0\" rx=\"10\" ry=\"10\" width=\"150\" height=\"70\" style=\"fill:#6829c2;stroke-width:0;\" /><text dominant-baseline=\"middle\" text-anchor=\"middle\" fill=\"white\"><tspan y=\"155.0\" x=\"324.0\" font-size=\"7pt\" >account_id = account_id</tspan></text><line x1=\"150\" y1=\"263.0\" x2=\"490\" y2=\"263.0\" style=\"stroke:#808080;;stroke-width:4\" /><polygon points=\"500, 263.0 490, 257.0 490, 269.0 \" style=\"fill:#808080;;stroke-width:0;\" /><rect y=\"230.0\" x=\"249.0\" rx=\"10\" ry=\"10\" width=\"150\" height=\"70\" style=\"fill:#6829c2;stroke-width:0;\" /><text dominant-baseline=\"middle\" text-anchor=\"middle\" fill=\"white\"><tspan y=\"265.0\" x=\"324.0\" font-size=\"7pt\" >account_id = account_id</tspan></text></svg></div>\n",
       "            </div>\n",
       "\n",
       "            <div style='margin-top: 15px;'>\n",
       "            <div style='margin-bottom: 10px; font-size: 1rem;'>staging</div>\n",
       "            <style>\n",
       "  th {\n",
       "    text-align: left !important;\n",
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       "  td {\n",
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       "  th:nth-child(1) {\n",
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       "\n",
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       "        \n",
       "          <th class=\"str\">data frames</th>\n",
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       "          <th class=\"str\">staging table              </th>\n",
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       "  <tbody>\n",
       "    \n",
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       "        <th>0</th>\n",
       "          \n",
       "            \n",
       "              <td class=\"str\">population</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"str\">POPULATION__STAGING_TABLE_1</td>\n",
       "            \n",
       "          \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1</th>\n",
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       "              <td class=\"str\">META__STAGING_TABLE_2</td>\n",
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       "      <tr>\n",
       "        <th>2</th>\n",
       "          \n",
       "            \n",
       "              <td class=\"str\">order</td>\n",
       "            \n",
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       "            \n",
       "              <td class=\"str\">ORDER__STAGING_TABLE_3</td>\n",
       "            \n",
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       "    \n",
       "      <tr>\n",
       "        <th>3</th>\n",
       "          \n",
       "            \n",
       "              <td class=\"str\">trans</td>\n",
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       "          \n",
       "            \n",
       "              <td class=\"str\">TRANS__STAGING_TABLE_4</td>\n",
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       "  td.float {\n",
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       "    \n",
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       "  <tbody>\n",
       "    \n",
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       "        <th>0</th>\n",
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       "              <td class=\"int\">1056320</td>\n",
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       "            \n",
       "              <td class=\"str\">DataFrame</td>\n",
       "            \n",
       "          \n",
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       "    \n",
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       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"int\">6471</td>\n",
       "            \n",
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       "            \n",
       "              <td class=\"str\">DataFrame</td>\n",
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       "          \n",
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       "        <th>2</th>\n",
       "          \n",
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       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"int\">5369</td>\n",
       "            \n",
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       "            \n",
       "              <td class=\"str\">DataFrame</td>\n",
       "            \n",
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       "</div>\n",
       "</div>"
      ],
      "text/plain": [
       "data model\n",
       "\n",
       "  population:\n",
       "    columns:\n",
       "    - frequency: categorical\n",
       "    - account_id: join_key\n",
       "    - duration: numerical\n",
       "    - payments: numerical\n",
       "    - amount: numerical\n",
       "    - ...\n",
       "\n",
       "    joins:\n",
       "    - right: 'trans'\n",
       "      on: (population.account_id, trans.account_id)\n",
       "      time_stamps: (population.date_loan, trans.date)\n",
       "      relationship: 'many-to-many'\n",
       "      lagged_targets: False\n",
       "    - right: 'order'\n",
       "      on: (population.account_id, order.account_id)\n",
       "      relationship: 'many-to-many'\n",
       "      lagged_targets: False\n",
       "    - right: 'meta'\n",
       "      on: (population.account_id, meta.account_id)\n",
       "      relationship: 'many-to-many'\n",
       "      lagged_targets: False\n",
       "\n",
       "  trans:\n",
       "    columns:\n",
       "    - type: categorical\n",
       "    - k_symbol: categorical\n",
       "    - bank: categorical\n",
       "    - operation: categorical\n",
       "    - account_id: join_key\n",
       "    - ...\n",
       "\n",
       "  order:\n",
       "    columns:\n",
       "    - bank_to: categorical\n",
       "    - k_symbol: categorical\n",
       "    - account_id: join_key\n",
       "    - amount: numerical\n",
       "    - account_to: unused_float\n",
       "    - ...\n",
       "\n",
       "  meta:\n",
       "    columns:\n",
       "    - type_disp: categorical\n",
       "    - type_card: categorical\n",
       "    - gender: categorical\n",
       "    - A3: categorical\n",
       "    - account_id: join_key\n",
       "    - ...\n",
       "\n",
       "\n",
       "container\n",
       "\n",
       "  population\n",
       "      subset   name               rows   type     \n",
       "  0   train    population_train    459   DataFrame\n",
       "  1   test     population_test     223   DataFrame\n",
       "\n",
       "  peripheral\n",
       "      name       rows   type     \n",
       "  0   trans   1056320   DataFrame\n",
       "  1   order      6471   DataFrame\n",
       "  2   meta       5369   DataFrame"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "star_schema = getml.data.StarSchema(\n",
    "    train=population_train, test=population_test, alias=\"population\"\n",
    ")\n",
    "\n",
    "star_schema.join(\n",
    "    trans,\n",
    "    on=\"account_id\",\n",
    "    time_stamps=(\"date_loan\", \"date\"),\n",
    ")\n",
    "\n",
    "star_schema.join(\n",
    "    order,\n",
    "    on=\"account_id\",\n",
    ")\n",
    "\n",
    "star_schema.join(\n",
    "    meta,\n",
    "    on=\"account_id\",\n",
    ")\n",
    "\n",
    "star_schema"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
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       "          <th class=\"join_key\">account_id</th>\n",
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       "        \n",
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       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_float\">  birth_date</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_float\"> district_id</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_string\">card_id      </th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_string\">issued       </th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"unused_string\">A2             </th>\n",
       "        \n",
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       "    </tr>\n",
       "    \n",
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       "        \n",
       "          \n",
       "            <th class=\"sub-header\">role</th>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <th class=\"sub-header join_key\">  join_key</th>\n",
       "          \n",
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       "          \n",
       "            <th class=\"sub-header categorical\">categorical</th>\n",
       "          \n",
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       "            <th class=\"sub-header categorical\">categorical</th>\n",
       "          \n",
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       "            <td class=\"join_key\">1</td>\n",
       "          \n",
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       "          \n",
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       "          \n",
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       "            <td class=\"categorical\">F</td>\n",
       "          \n",
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       "            <td class=\"categorical\">south Bohemia</td>\n",
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       "              \n",
       "          \n",
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       "              <span class=\"left\">65</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
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       "          \n",
       "            <td class=\"char-align numerical\">\n",
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       "              ><span class=\"right\" style=\"width: 0ch\"\n",
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       "          \n",
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       "              \n",
       "              \n",
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       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2</span\n",
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       "          \n",
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       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3</span\n",
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       "              >\n",
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       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
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       "              ><span class=\"right\" style=\"width: 0ch\"\n",
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       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1740</span\n",
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       "              >\n",
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       "          \n",
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       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1910</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
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       "              \n",
       "          \n",
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       "              ><span class=\"right\" style=\"width: 0ch\"\n",
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       "              \n",
       "              \n",
       "          \n",
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       "              \n",
       "              \n",
       "          \n",
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       "              <span class=\"left\">18</span\n",
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       "            <td class=\"categorical\">M</td>\n",
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       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
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       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
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       "              \n",
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       "            <td class=\"char-align numerical\">\n",
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       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">100</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">12541</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.2</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.43</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">167</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">85677</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">99107</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">2</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">2</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1945</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Hl.m. Praha</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>2</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">2</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">DISPONENT</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\"></td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">F</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">Prague</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1204953</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">100</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">12541</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.2</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.43</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">167</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">85677</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">99107</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">3</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">3</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1940</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Hl.m. Praha</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>3</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">3</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">OWNER</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\"></td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">M</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">central Bohemia</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">95616</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">65</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">30</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">4</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">6</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">51</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.4</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">9307</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.8</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">4</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.43</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">118</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2616</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3040</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">4</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">4</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1956</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Kolin</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>4</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">3</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">DISPONENT</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\"></td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">F</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">central Bohemia</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">95616</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">65</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">30</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">4</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">6</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">51</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.4</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">9307</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.8</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">4</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.43</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">118</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2616</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3040</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1960</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Kolin</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th></th>\n",
       "        \n",
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       "            <td class=\"join_key\">...</td>\n",
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       "            <td class=\"categorical\">...</td>\n",
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       "            <td class=\"categorical\">...</td>\n",
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       "            <td class=\"categorical\">...</td>\n",
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       "            <td class=\"categorical\">...</td>\n",
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       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
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       "          \n",
       "            \n",
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       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
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       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
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       "            \n",
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       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
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       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
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       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
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       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
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       "            </td>\n",
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       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
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       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">...</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">...</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">...</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>5364</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11349</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">OWNER</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\"></td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">F</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">Prague</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1204953</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">100</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">12541</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.2</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.43</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">167</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">85677</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">99107</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13647</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13955</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1945</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Hl.m. Praha</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>5365</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11349</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">DISPONENT</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\"></td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">M</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">Prague</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1204953</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">100</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">12541</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.2</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.43</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">167</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">85677</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">99107</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13648</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13956</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1943</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Hl.m. Praha</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>5366</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11359</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">OWNER</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">classic</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">M</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">south Moravia</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">117897</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">139</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">28</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">6</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">53</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.8</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">8814</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">4</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.7</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.74</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">107</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2112</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2059</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13660</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13968</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1968</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">61</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">1247.0</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">1995-06-13</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Trebic</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>5367</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11362</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">OWNER</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\"></td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">F</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">north Moravia</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">106054</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">38</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">25</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">6</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">2</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">6</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">63</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.1</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">8110</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.7</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">6</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.55</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">109</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3244</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">3079</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13663</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13971</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1962</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">67</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Bruntal</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>5368</th>\n",
       "        \n",
       "          \n",
       "            <td class=\"join_key\">11382</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">OWNER</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\"></td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">F</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"categorical\">north Moravia</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">323870</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">0</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">1</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">100</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">10673</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">4</span\n",
       "              ><span class=\"right\" style=\"width: 1ch\"\n",
       "                >.7</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "            \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">5</span\n",
       "              ><span class=\"right\" style=\"width: 2ch\"\n",
       "                >.44</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">100</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">18782</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align numerical\">\n",
       "              <span class=\"left\">18347</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13690</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">13998</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">1953</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            \n",
       "              \n",
       "              \n",
       "          \n",
       "            <td class=\"char-align unused_float\">\n",
       "              <span class=\"left\">74</span\n",
       "              ><span class=\"right\" style=\"width: 0ch\"\n",
       "                >&nbsp;</span\n",
       "              >\n",
       "            </td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">NULL</td>\n",
       "          \n",
       "        \n",
       "          \n",
       "            <td class=\"unused_string\">Ostrava - mesto</td>\n",
       "          \n",
       "        \n",
       "      </tr>\n",
       "    \n",
       "  </tbody>\n",
       "</table>\n",
       "\n",
       "  <p>\n",
       "    5369 rows x 25 columns<br />\n",
       "    memory usage: 1.05 MB<br />\n",
       "    name: meta<br />\n",
       "    type: getml.DataFrame<br />\n",
       "    \n",
       "  </p>\n"
      ],
      "text/plain": [
       "name   account_id   type_disp     type_card     gender        ...     birth_date    district_id   card_id      \n",
       "role     join_key   categorical   categorical   categorical   ...   unused_float   unused_float   unused_string\n",
       "   0            1   OWNER                       F             ...           1970             18   NULL         \n",
       "   1            2   OWNER                       M             ...           1945              1   NULL         \n",
       "   2            2   DISPONENT                   F             ...           1940              1   NULL         \n",
       "   3            3   OWNER                       M             ...           1956              5   NULL         \n",
       "   4            3   DISPONENT                   F             ...           1960              5   NULL         \n",
       "              ...   ...           ...           ...                          ...            ...   ...          \n",
       "5364        11349   OWNER                       F             ...           1945              1   NULL         \n",
       "5365        11349   DISPONENT                   M             ...           1943              1   NULL         \n",
       "5366        11359   OWNER         classic       M             ...           1968             61   1247.0       \n",
       "5367        11362   OWNER                       F             ...           1962             67   NULL         \n",
       "5368        11382   OWNER                       F             ...           1953             74   NULL         \n",
       "\n",
       "name   issued          A2             \n",
       "role   unused_string   unused_string  \n",
       "   0   NULL            Pisek          \n",
       "   1   NULL            Hl.m. Praha    \n",
       "   2   NULL            Hl.m. Praha    \n",
       "   3   NULL            Kolin          \n",
       "   4   NULL            Kolin          \n",
       "       ...             ...            \n",
       "5364   NULL            Hl.m. Praha    \n",
       "5365   NULL            Hl.m. Praha    \n",
       "5366   1995-06-13      Trebic         \n",
       "5367   NULL            Bruntal        \n",
       "5368   NULL            Ostrava - mesto\n",
       "\n",
       "\n",
       "5369 rows x 25 columns\n",
       "memory usage: 1.05 MB\n",
       "type: getml.DataFrame"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Predictive modeling\n",
    "\n",
    "We loaded the data, defined the roles, units and the abstract data model. Next, we create a getML pipeline for relational learning."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1 getML Pipeline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!-- #### 2.1.1  -->\n",
    "__Set-up of feature learners, selectors & predictor__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "mapping = getml.preprocessors.Mapping(min_freq=100)\n",
    "\n",
    "fast_prop = getml.feature_learning.FastProp(\n",
    "    aggregation=getml.feature_learning.FastProp.agg_sets.All,\n",
    "    loss_function=getml.feature_learning.loss_functions.CrossEntropyLoss,\n",
    "    num_threads=1,\n",
    ")\n",
    "\n",
    "feature_selector = getml.predictors.XGBoostClassifier(n_jobs=1)\n",
    "\n",
    "# the population is really small, so we set gamma to mitigate overfitting\n",
    "predictor = getml.predictors.XGBoostClassifier(gamma=2, n_jobs=1,)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Build the pipeline__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "pipe = getml.pipeline.Pipeline(\n",
    "    data_model=star_schema.data_model,\n",
    "    preprocessors=[mapping],\n",
    "    feature_learners=[fast_prop],\n",
    "    feature_selectors=[feature_selector],\n",
    "    predictors=predictor,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Model training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking data model...\n",
      "Staging... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "Preprocessing... 100% |██████████| [elapsed: 00:01, remaining: 00:00]          \n",
      "Checking... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "\n",
      "OK.\n",
      "Staging... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "Preprocessing... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "FastProp: Trying 808 features... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "FastProp: Building features... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "XGBoost: Training as feature selector... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "XGBoost: Training as predictor... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "\n",
      "Trained pipeline.\n",
      "Time taken: 0h:0m:0.970731\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre>Pipeline(data_model='population',\n",
       "         feature_learners=['FastProp'],\n",
       "         feature_selectors=['XGBoostClassifier'],\n",
       "         include_categorical=False,\n",
       "         loss_function='CrossEntropyLoss',\n",
       "         peripheral=['meta', 'order', 'trans'],\n",
       "         predictors=['XGBoostClassifier'],\n",
       "         preprocessors=['Mapping'],\n",
       "         share_selected_features=0.5,\n",
       "         tags=['container-6Bk0Du'])</pre>"
      ],
      "text/plain": [
       "Pipeline(data_model='population',\n",
       "         feature_learners=['FastProp'],\n",
       "         feature_selectors=['XGBoostClassifier'],\n",
       "         include_categorical=False,\n",
       "         loss_function='CrossEntropyLoss',\n",
       "         peripheral=['meta', 'order', 'trans'],\n",
       "         predictors=['XGBoostClassifier'],\n",
       "         preprocessors=['Mapping'],\n",
       "         share_selected_features=0.5,\n",
       "         tags=['container-6Bk0Du'])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.fit(star_schema.train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Model evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Staging... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "Preprocessing... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "FastProp: Building features... 100% |██████████| [elapsed: 00:00, remaining: 00:00]          \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       "  th {\n",
       "    text-align: left !important;\n",
       "  }\n",
       "  td {\n",
       "    text-align: left !important;\n",
       "  }\n",
       "  th:nth-child(1) {\n",
       "    text-align: right;\n",
       "    border-right: 1px solid LightGray;\n",
       "  }\n",
       "  th.float {\n",
       "    text-align: right !important;\n",
       "  }\n",
       "  td.float {\n",
       "    text-align: right !important;\n",
       "  }\n",
       "  th.int {\n",
       "    text-align: right !important;\n",
       "  }\n",
       "  td.int {\n",
       "    text-align: right !important;\n",
       "  }\n",
       "</style>\n",
       "\n",
       "<table class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      \n",
       "        \n",
       "          <th class=\"int\"> </th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"datetime\">date time          </th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"str\">set used</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"str\">target </th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"float\">accuracy</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"float\">    auc</th>\n",
       "        \n",
       "      \n",
       "        \n",
       "          <th class=\"float\">cross entropy</th>\n",
       "        \n",
       "      \n",
       "    </tr>\n",
       "    \n",
       "  </thead>\n",
       "  <tbody>\n",
       "    \n",
       "      <tr>\n",
       "        <th>0</th>\n",
       "          \n",
       "            \n",
       "              <td class=\"datetime\">2024-02-21 15:01:29</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"str\">train</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"str\">default</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"float\">0.9978</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"float\">0.9999</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"float\">0.06221</td>\n",
       "            \n",
       "          \n",
       "      </tr>\n",
       "    \n",
       "      <tr>\n",
       "        <th>1</th>\n",
       "          \n",
       "            \n",
       "              <td class=\"datetime\">2024-02-21 15:01:29</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"str\">test</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"str\">default</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"float\">0.9596</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"float\">0.9314</td>\n",
       "            \n",
       "          \n",
       "            \n",
       "              <td class=\"float\">0.1415</td>\n",
       "            \n",
       "          \n",
       "      </tr>\n",
       "    \n",
       "  </tbody>\n",
       "</table>"
      ],
      "text/plain": [
       "    date time             set used   target    accuracy       auc   cross entropy\n",
       "0   2024-02-21 15:01:29   train      default     0.9978    0.9999         0.06221\n",
       "1   2024-02-21 15:01:29   test       default     0.9596    0.9314         0.1415 "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.score(star_schema.test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.4 Studying features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Visualizing the learned features__\n",
    "\n",
    "The feature with the highest importance is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "```sql\n",
       "DROP TABLE IF EXISTS \"FEATURE_1_29\";\n",
       "\n",
       "CREATE TABLE \"FEATURE_1_29\" AS\n",
       "SELECT Q1( t2.\"balance\" ) AS \"feature_1_29\",\n",
       "       t1.rowid AS rownum\n",
       "FROM \"POPULATION__STAGING_TABLE_1\" t1\n",
       "INNER JOIN \"TRANS__STAGING_TABLE_4\" t2\n",
       "ON t1.\"account_id\" = t2.\"account_id\"\n",
       "WHERE t2.\"date\" <= t1.\"date_loan\"\n",
       "GROUP BY t1.rowid;\n",
       "```"
      ],
      "text/plain": [
       "'DROP TABLE IF EXISTS \"FEATURE_1_29\";\\n\\nCREATE TABLE \"FEATURE_1_29\" AS\\nSELECT Q1( t2.\"balance\" ) AS \"feature_1_29\",\\n       t1.rowid AS rownum\\nFROM \"POPULATION__STAGING_TABLE_1\" t1\\nINNER JOIN \"TRANS__STAGING_TABLE_4\" t2\\nON t1.\"account_id\" = t2.\"account_id\"\\nWHERE t2.\"date\" <= t1.\"date_loan\"\\nGROUP BY t1.rowid;'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "by_importances = pipe.features.sort(by=\"importances\")\n",
    "by_importances[0].sql"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Feature correlations__\n",
    "\n",
    "We want to analyze how the features are correlated with the target variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "names, correlations = pipe.features[:50].correlations()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(20, 10))\n",
    "\n",
    "ax.bar(names, correlations)\n",
    "\n",
    "ax.set_title(\"feature correlations\")\n",
    "ax.set_xlabel(\"feature\")\n",
    "ax.set_ylabel(\"correlation\")\n",
    "ax.tick_params(axis=\"x\", rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Feature importances__\n",
    "\n",
    "Feature importances are calculated by analyzing the improvement in predictive accuracy on each node of the trees in the XGBoost predictor. They are then normalized, so that all importances add up to 100%."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "names, importances = pipe.features[:50].importances()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(20, 10))\n",
    "\n",
    "ax.bar(names, importances)\n",
    "\n",
    "ax.set_title(\"feature importances\")\n",
    "ax.set_xlabel(\"feature\")\n",
    "ax.set_ylabel(\"importance\")\n",
    "ax.tick_params(axis=\"x\", rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Column importances__\n",
    "\n",
    "Because getML uses relational learning, we can apply the principles we used to calculate the feature importances to individual columns as well.\n",
    "\n",
    "As we can see, a lot of the predictive power stems from the account balance. This is unsurprising: People with less money on their bank accounts are more likely to default on their loans."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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nZTVeozZnzpxap/U8/vjjY9SoUbF8+fIoKSmJSy+9NE488URRZSs75ZRT4vHHH4/bbrut1lkpmjdvHg888ED07t07w+kar4svvjiuvfbauOKKK+KII46oWW/evHnceOON9ktGPujMIf951hCysXTp0hgzZoyg0siIKhS0Qw45JG6++ea46KKLIuL9bxbV1dVx6aWXxmc+85mMp2vcXnzxxZg8eXLND1d69+4dY8eOjd122y3jyRqviy66KCZMmBA33XSTb+YFYONvQ5aVlcWwYcP8QLjADB06NC688ML47W9/GxHvf39ZvHhxnHPOOWJXhs4444z45je/GW3atIlddtklDj/88Ih4/7Rgn/zkJ7MdrhF78sknY/DgwdGqVavo379/RLx/2o8f/ehH8cADD8QBBxyQ8YSNy4gRIyIiYtddd42DDjoomjdvnvFERPz7lHkjR46Mq666Ktq1a5fxRGzUpUuXeO2116JHjx4R8f61B957772afbT77rvHqlWrshyxUZoyZUrcfffdMXjw4Pg//+f/xHe/+92sRyIixo0bF0ceeWSccMIJcdRRR8XEiRN9nykAHTt2jEsvvTSOPPLITd7/z3/+M4466qitPBUbDR48OJ588sma7zM0Di5UT0H7xz/+EUceeWQccMAB8Ze//CWGDh0a//znP2PVqlXx6KOP+gF+Ru6///4YOnRo9OnTp+ZUU48++mjMmzcv7rnnnvjsZz+b8YSN0/777x8vvvhi5PP5KCsrq/OP3zlz5mQ0GRERGzZs2ORF6z7xiU9kNFHjVlFREccee2w8+eSTsWbNmth5551j2bJlMXDgwLj33ntjhx12yHrERmv27NmxePHi+OxnP1tzhNe0adOiQ4cOcdBBB2U8XeN0yCGHRM+ePeO6666rOU3Le++9FyeffHIsXLgw/vrXv2Y8YeNVXV0dCxYs2OT3l0MPPTSjqaCwnHHGGTFjxoy47LLLoqioKC666KLI5/M1Iez++++P0047LRYsWJDxpI3T0qVLY/jw4dGiRYv41a9+FaWlpTFv3jxHRGTsrbfeitNOOy3mzp0bt956axxwwAExd+5c+yUjgwcPjkMOOSTOPffcTd4/b9682H///ev8W4Ct4/rrr48LL7wwRo4cGZ/85Cfr/Cxm6NChGU3Gx0lUoeBVVFTE1VdfHfPmzYu33norDjjggDjttNNip512ynq0Rmv//fePwYMHx6RJk2qtjxs3Lh544AE/vM/IBRdc8IH3bzxygq3rhRdeiFGjRsVjjz1Wa33jIdpVVVUZTUZExMyZM+Ppp5+u+f4yaNCgrEdq1C688MI466yz6hxt9/bbb8dll13m4psZadWqVTz11FOx11571Vr/17/+Ff369Yt169ZlNFnj9re//S2OP/74ePnll+ucDsT3l+ysXbs2Jk2aFDNmzNhk7Fq4cGFGkzVeb731Vpx00knxu9/9LqqqqmLgwIFxyy23xK677hoR71/Hs6KiIr72ta9lPGnjlc/nY9KkSfGTn/wkVq5cGU8//bQf3heI22+/Pc4444xYuXJlPPPMM/ZLRu6+++5Yu3ZtnHDCCZu8/80334w//vGPNUezsnU1adJks/f5N9n2S1QBtljLli3jmWeeid13373W+vPPPx/77rtvvPPOOxlNBoXn4IMPjmbNmsW4ceNip512qnOu2/322y+jyaDwNG3aNF577bXo0qVLrfU33ngjunTp4n9IMlJSUhK//vWv43Of+1yt9fvvvz+GDx8ey5cvz2iyxq1Pnz6xxx57xAUXXLDJ7y+ud5ON4447Lh5++OH41re+tcn9Mnbs2Iwm45133on33nuv1nXuKCyzZ8+OmTNnxvDhw6NDhw5Zj8P/98orr8Ts2bNj0KBBjuYG+P9cU4WC9qtf/SratGlT57eG7rzzzli3bp0Kn5HOnTvH3Llz60SVuXPn1vlBGFvf7Nmza11IeP/99894osZt7ty5MXv27Dq/4U32ZsyYET/+8Y9rvl569eoVZ5xxhqNVMrS5i2zOmzcvOnbsmMFEREQMGzYsTjrppLj88strTsH26KOPxtlnnx3HHXdcxtM1Xi+88EJMnTo1evbsmfUo/If77rsvpk2bVnOKXArHpq5vl8/nY/r06XH99dfH1KlTM5iK/9S3b9/o27dv1mPwX7p37x7du3ePfD4f9913n68XgIjY/PFJUAAmTpwYnTp1qrPepUuXuPjiizOYiIiI0aNHxymnnBKXXHJJPPLII/HII4/EpEmT4tvf/naMHj066/EarRUrVsQRRxwRBx54YIwZMybGjBkTffv2jSOPPDJWrlyZ9XiNVu/eveP111/Pegz+y89+9rP4/Oc/H23bto2xY8fG2LFjo127dvHFL34xrrnmmqzHa3Q6dOgQHTt2jFwuF3vssUd07Nix5lZcXByf/exn4+tf/3rWYzZal19+eXzlK1+J4cOHR1lZWZSVlcWJJ54Yxx57bFxyySVZj9doDRgwwDUgCtDGv88obC+99FKcd9558YlPfCKOOeYYR9oXoCVLlsSoUaOyHoPw9bIt8PWSvYcffjiOOuqo6NmzZ/Ts2TOGDh0ajzzySNZj8TFy+i8KWsuWLeO5556LsrKyWuuLFi2KXr16xdtvv53NYI1cPp+PyZMnxxVXXBGvvvpqRETsvPPOcfbZZ8eYMWM2+VvGfPyGDRsWCxcujJtvvjl69eoVEe+f737EiBHRs2fP+M1vfpPxhI3TX/7ylzj33HPj4osv3uRF69q1a5fRZI1b9+7dY9y4cfHd73631vo111wTF198cSxdujSjyRqnm266KfL5fIwaNSomT55c67RFLVq0iLKyshg4cGCGExIRsW7dunjxxRcjImK33Xarc+0btq677747zj333Dj77LM3+f1l3333zWiyxu2WW26JP/zhD3HTTTf5Gikw69evj6lTp8b1118fM2fOjKqqqrj88svjpJNO8u+xAjRv3rw44IADnPozI75eti2+XrJ1yy23xMiRI+MrX/lKzZGqjz76aNx9991x4403xvHHH5/xhHwcRBUK2ic+8Ym4+uqrY+jQobXW//CHP8Rpp50Wr7zySkaTsdGaNWsiIqJt27YZT0JxcXH8+c9/jgMPPLDW+hNPPBGf+9znYvXq1dkM1shtvGjdf8dGF6rPVps2bWLu3Ll1TpvzwgsvxP777x9vvfVWRpM1bg8//HAcdNBBdX44TOFYsmRJRESUlpZmPAmbuihqLpfz/SVj+++/f7z44ouRz+ejrKyszt9nc+bMyWiyxmv27Nlx/fXXx29+85vo2bNnfOtb34phw4ZF9+7dY968eS68nZE//vGPH3j/woUL43vf+56/y7YyXy+FyddLYevVq1eccsopceaZZ9Zav/LKK+O6666rOd002xfXVKGgHXfccTFmzJho27ZtHHrooRHx/g9cxo4dG9/4xjcyno4VK1bE/PnzIyJir732is6dO2c8UeNWXV29yR9ENm/ePKqrqzOYiIiIBx98MOsR2IShQ4fG3XffHWeffXat9T/84Q/xpS99KaOpOOyww6K6ujqef/75WLFiRZ2/uzb+W4Ct67333osLLrggfvKTn9QExzZt2sTpp58e559/vgiWkZdeeinrEdiEo48+OusR+C8DBgyI008/Pf72t7/FnnvumfU4/D/27juqqit/G/hzL0iRohAkakSBgAr23mKM0QQlEQ2xYsUSSxQLEo2Z2DVWLNHERJplghLFCWbsSiwkVqqAgmBBB2yIiqgI3PcPx/t6ARXnF+7eeJ7PWrOW95wzaz1rmH33Pfu7y3/16tVLWwh+Ee6AoH9sL3Jie5Fbeno6evToUeK6h4cHZsyYISAR6QOLKiS1efPm4dKlS+jSpQsMDZ/+37WoqAhDhgzhmSoC3b9/H+PGjUNoaKh2wMvAwAD9+vXD2rVrdbZtIf358MMPMXHiRISGhqJmzZoAgGvXrmHy5Mno0qWL4HTK1alTJ9ERqBSurq5YsGAB/vjjD+22UsePH0dUVBR8fX2xevVq7bM+Pj6iYirO8ePH4eXlhcuXL5d4aeTMe3EmTJiA8PBwLFmyRNte/vrrL8yePRu3b9/Gjz/+KDihMtWpU0d0BCrFrFmzREegYrp06YLAwEDcuHEDgwcPhpubGwcfJVCjRg388MMP6NmzZ6n3Y2NjeWi9AGwvcmJ7kZudnR0OHjxYYheEAwcOcHX3G4zbf1GFkJKSgri4OJiamqJRo0Z8iRSsX79+iImJwffff68zuDJx4kQ0bdoUW7ZsEZxQmTIyMuDh4YHExERtx52RkYGGDRsiIiICtWrVEpxQmY4cOfLS+5x5L4aDg0OZnlOpVEhPTy/nNPRM06ZNUbduXcyZMwc1atQo8RLPor0YVapUwZYtW9C9e3ed67t27cKAAQNw9+5dQcmUbePGjS+9P2TIED0lIZJfRkYGgoODERwcjIcPH6Jfv3744YcfEB8frz2LkPTLw8MDTZs2xdy5c0u9HxcXh2bNmnHFvQBsL/Jhe5Hbjz/+iEmTJmH48OFo3749gKdnqoSEhGDVqlUYPXq04IRUHlhUIaLXZmZmhr179+K9997TuX706FF069YNDx48EJSMNBoNDhw4gHPnzgF4urdn165dBadSthftef8MZ94T/X9mZmaIi4srMcuLxLK1tcXhw4dLDKQkJyfj/fffx82bNwUlUzYrKyudz0+ePEFeXh6MjIxQuXJlZGdnC0qmbGq1+qWzutnvi7d//34EBwdjx44dsLOzQ+/evdG7d280b95cdDRFOXr0KB48eIBu3bqVev/Bgwc4ffo0V30LxvYiB7YX+e3YsQPLly/Xnp/i4uICPz+/F64uooqPRRWSWmFhIUJCQnDw4MFS91Y/dOiQoGTKVrt2bfz73/9Go0aNdK7Hx8fD3d0dV69eFZSMSD7FZ3A/efIEMTEx+Pbbb7FgwQJuzSZIZGQkOnfuLDoGFfPhhx/iq6++euELI4kxd+5cnDt3DsHBwTA2NgYAPH78GCNGjICzszO3O5JIamoqxo4dCz8/P7i5uYmOo0i//fabzudn/f6GDRswZ84cjBgxQlAyKu7OnTvYvHkzgoKCEB8fz4IX0UuwvRAR6WJRhaQ2fvx4hISE4JNPPil1G5AVK1YISqZsP//8M3799Vds2rQJ1atXBwBkZWVh6NCh8PT05NJGPVq9ejW++OILmJiY6JwBURqeCyGXw4cPY8qUKThz5ozoKIpkbGyMWrVqwdvbG0OHDuVet5LYsWMH/vGPf8DPzw+NGjUqcQB648aNBSVTHk9PT53PBw4cgLGxMZo0aQLg6TYT+fn56NKlC8LDw0VEpBc4ffo0Bg0apF21SnL45ZdfsHXr1hJFF5JDdHQ0Z95LRKPRYM+ePQgMDMS2bdtEx6Fi2F7kwvZCJAaLKiQ1GxsbbNy4Ee7u7qKjKF6zZs10ilqpqal4/PgxateuDQC4cuUKjI2N4ezsjOjoaFExFcfBwQGnT5/GW2+99dIzInguhHzOnTuHli1bIjc3V3QURbp16xY2bdqEDRs2IDExER9++CFGjBiBXr16wcjISHQ8xXrRdnkajYYH1euZt7d3mZ8NDg4uxyT0umJjY/H+++/j3r17oqPQc9LT09G4cWP2+0QvcfHiRQQFBSEkJAQ3b95E165d8fvvv4uORSQlthexrK2tkZKSAhsbG1hZWb10609uyfpmMhQdgOhljIyMuK+6JHr16iU6ApXi4sWLpf6b5BEfH6/zWaPRIDMzE4sWLULTpk3FhCLY2Nhg8uTJmDx5MqKjoxEcHIxx48Zh3Lhx8PLywogRI7Qz8kl/+D0mDxZK5BcREaHz+Vn/smbNGnTo0EFQKirNw4cPsXr1arzzzjuio1ApXFxckJKSwsK9II8fP8a2bdsQGBiIY8eOobCwEMuWLcOIESNgaWkpOh4Vw/YiFtuLPFasWAELCwvtv19WVKE3E1eqkNSWL1+O9PR0rFmzhl9QRK8wd+5cTJ06FZUrV9a5/vDhQyxduhQzZ84UlEzZnh1YW7y7bdu2LYKCglC/fn1Byeh5//nPf/Dzzz9j0aJFMDQ0xKNHj9CuXTusW7cODRo0EB2PiKiE4iu7VCoVqlWrhg8//BDLly9HjRo1BCVTtuKzVTUaDe7fv4/KlStj8+bN8PDwEJiOSvOvf/0Ld+/exdChQ0VHUZQzZ84gMDAQoaGhcHJywuDBg9GvXz/UqlULcXFxcHV1FR2RSsH2IgbbC5F8WFQhqX322WeIjIyEtbU1GjRoUGJvde7hLV5ubi6Kiop0rnGGhBgGBgbIzMyEra2tzvXbt2/D1taWs4kEuXz5ss5ntVqNatWqwcTERFAieubJkyf47bffEBQUhP3796Nly5YYMWIEBgwYgJs3b+If//gHoqOjkZSUJDqqomzatAnr1q3DxYsX8ddff6FOnTpYuXIlHBwc0LNnT9HxFOn27duYOXMmIiMjcePGjRL9Prc0IPr/NmzYoPP5Wb/fpk0bWFlZCUpFJB9DQ0NMmDABY8aMQb169bTXK1WqxEFiomLYXuTGsRhl4vZfJLWqVavis88+Ex2Dirl48SLGjx+PP/74A48ePdJe5573Yj3737+4uLg4WFtbC0hEAFCnTh3REagUEyZMQGhoKDQaDQYPHowlS5agYcOG2vtmZmZYtmwZatasKTCl8vz444+YOXMmJk2ahAULFmj7k6pVq2LlypUsqggyePBgXLhwASNGjMDbb7/N1cMSejZPjn8b8Th7m6hsunTpgsDAQNy4cQODBw+Gm5sbv8OIXoDtRW4vWq/w+PFjntf5BmNRhaTG/bzlNGjQIGg0GgQFBXFwRQLPtplQqVSoW7euzt+jsLAQubm5GDNmjMCEdPjwYSxbtgzJyckAAFdXV/j5+aFjx46CkylXUlISvv/+e3h6esLY2LjUZ2xsbBAZGannZMr2/fffY/369ejVqxcWLVqkvd6yZUtMnTpVYDJlO3r0KI4dO8ZzhiS0ceNGLF26FKmpqQCAunXrws/PD4MHDxacTNlycnIQGBio7fcbNGiA4cOHo0qVKoKT0bZt2xAWFoYrV64gPz9f5150dLSgVMq0d+9eZGRkIDg4GGPHjsXDhw/Rr18/ACwQy4LtRR5sL3JavXo1gKd/g4CAAJibm2vvFRYW4siRI9zu+w3G7b+I6LWZm5vjzJkzOstOSZwNGzZAo9Fg+PDhWLlypc4Lu5GREezt7dGuXTuBCZVt8+bN8Pb2hqenp/bg4KioKOzYsQMhISHw8vISnFCZjhw5gvbt28PQUHd+SUFBAf7880+8//77gpIpm6mpKc6dO4c6derAwsICcXFxcHR0RGpqKho3boyHDx+KjqhIrVq1wvfff4+2bduKjkLP8ff3x7fffovx48dr+5djx45h7dq1mD9/PiZPniw4oTKdPn0abm5uMDU1RevWrQEAp06dwsOHD7Fv3z40b95ccELlWr16Nb755hsMGzYMP//8M7y9vZGWloZTp07hyy+/xIIFC0RHVLT9+/cjODgYO3bsgJ2dHXr37o3evXuzzQjC9iI3thc5ODg4AHi65XetWrVgYGCgvfdsLGbu3Llo06aNqIhUjlhUIelxdoR8OnfujG+++QZdu3YVHYWec/jwYbRv377E2UMklouLC7744osSg1v+/v5Yv369dhYr6Rf3vZWTq6srvvvuO/Ts2VOnqPL9998jODiY/b4gp06dwvTp0zFz5kw0bNiwRD/Ds9TEcHBwwJw5czBkyBCd6xs2bMDs2bNx8eJFQcmUrWPHjnBycsL69eu1hfuCggKMHDkS6enpOHLkiOCEylW/fn3MmjULAwYM0OljZs6ciezsbKxZs0Z0RAJw584dbN68GUFBQYiPj+dvMkHYXioGthc5dO7cGeHh4Tw7TWFYVCGpcXaEnNLS0jBmzBgMGjSo1MGVxo0bC0pGzzx69KhEEZKDXmIYGxsjMTERTk5OOtcvXLiAhg0b6pxLRPqjVqtx/fp1VKtWTed6SkoKWrZsiXv37glKpmwBAQGYPXs2li9fjhEjRiAgIABpaWn47rvvEBAQgP79+4uOqEipqanw8vIqUdTiWWpimZiY4OzZsyX6l9TUVDRq1Ij9iyCmpqaIiYkpsd1HUlISWrZsiby8PEHJqHLlykhOTkadOnVga2uL/fv3o0mTJkhNTUXbtm1x+/Zt0RGpmOjoaM68F4TtpeJheyHSL56pQlL74Ycf8PPPP2PAgAEICQnBV199pTM7gsS4efMm0tLS4O3trb2mUqk4uCJYXl4evvrqK4SFhZX6I5d/FzHs7Oxw8ODBEoNeBw4cgJ2dnaBUyuXp6Qng6XfWsGHDdM5TKSwsRHx8PNq3by8qnuKNHDkSpqam+Mc//oG8vDx4eXmhZs2aWLVqFQsqAg0cOBCVKlXCL7/8wrPUJOLk5ISwsDDMmDFD5/rWrVvh7OwsKBVZWlriypUrJYoqGRkZsLCwEJSKAKB69erIzs5GnTp1ULt2bRw/fhxNmjTBxYsXX3jIMInFAWJx2F4qHrYXsa5evYqIiIhSd9nx9/cXlIrKE4sqJLUrV65oB7dMTU1x//59AMDgwYPRtm1bLjkVZPjw4WjWrBlCQ0M5uCIRPz8/REZG4scff8TgwYOxdu1aXLt2DT/99JPOgc+kX76+vvDx8UFsbKz2+ywqKgohISFYtWqV4HTK8+zMIY1GAwsLC5iammrvGRkZoW3bthg1apSoeISnA/gDBw5EXl4ecnNzS2zRRvp39uxZxMTE8Cw1ycyZMwf9+vXDkSNHdM7sOnjwIMLCwgSnU65+/fphxIgRWLZsmU6/7+fnhwEDBghOp2wffvghIiIi0KxZM3h7e2Py5MnYtm0bTp8+rZ10QfJwcXFBSkoKJ4YJwvZSsbC9iHXw4EF4eHjA0dER586dQ8OGDXHp0iVoNBoWu95g3P6LpObo6Ijt27ejWbNmaNmyJUaNGoXRo0dj37596N+/P1erCGJmZoa4uLgSM+9JrNq1a2Pjxo344IMPYGlpiejoaDg5OWHTpk0IDQ3Frl27REdUrB07dmD58uXa81NcXFzg5+eHnj17Ck6mXHPmzMHUqVNhZmYmOgqR9N5//33MnDmTZ6lJ6MyZM1ixYoVO/+Lr64tmzZoJTqZc+fn58PPzw7p161BQUAAAqFSpEsaOHYtFixbprJAk/SoqKkJRUZH2rJstW7bgzz//hLOzM0aPHg0jIyPBCel5//rXv3D37l0MHTpUdBRFYnupWNhexGrdujW6d++OOXPmaM8gsrW1xcCBA9GtWzeMHTtWdEQqByyqkNRGjhwJOzs7zJo1C2vXroWfnx86dOignR0RGBgoOqIi9ejRA8OGDcPnn38uOgo9x9zcHElJSahduzZq1aqF8PBwtG7dGhcvXkSjRo2Qm5srOiIR0Uvdvn0bM2fORGRkJG7cuIGioiKd+5xMIcavv/6K2bNnw8/PD40aNeJZakRlkJeXh7S0NADAu+++i8qVKwtORFeuXIGdnV2JVfYajQYZGRmoXbu2oGRE8mF7ISo7CwsLxMbG4t1334WVlRWOHTuGBg0aIC4uDj179sSlS5dER6RywO2/SGo///yzdkDlyy+/xFtvvYU///wTHh4eGD16tOB0ytWjRw9MnjwZCQkJpQ6ueHh4CEqmbI6Ojrh48SJq166N+vXrIywsDK1bt8bOnTtRtWpV0fEIQG5ubolBYktLS0FpqDQzZsxAVlYWgoKCREdRpMGDB+PChQsYMWIEt5eUSL9+/QA83f7zGZ6lJo8bN26UWoRksUusypUro1GjRqJj0HMcHByQmZlZYlvJ7OxsODg48LuM6DlsL0RlZ2Zmpj1HpUaNGkhLS0ODBg0AALdu3RIZjcoRiyokNbVaDbVarf3cv39/HlQrgTFjxgAA5s6dW+IeB1fE8fb2RlxcHDp16oTp06ejR48eWLNmDZ48ecKD0QS6ePEixo8fjz/++AOPHj3SXudgpJyuXbuGjIwM0TEU6+jRozh27BiaNGkiOgo95+LFi6IjUCnOnDmDoUOHIjk5ucShwexfxHn06BG+//77F664i46OFpSMnv32Ki43NxcmJiYCEtEz27ZtQ1hYWKkHPLPNiMH2Ii+2F/m0bdsWx44dg4uLC9zd3eHr64uEhASEh4ejbdu2ouNROWFRhaQTHx9f5mc5A0+M4i+HJIfJkydr/921a1ecO3cOZ86cgZOTE9uKQIMGDYJGo0FQUBBn3lcAGzZsEB1B0erXr4+HDx+KjkHF2NjY8PwhCQ0fPhx169ZFYGAg+xeJjBgxAvv27UPv3r3RunVr/l0kMGXKFABPi43ffvutzlZshYWFOHHiBJo2bSooHa1evRrffPMNhg0bht9++w3e3t5IS0vDqVOn8OWXX4qOpzhsL3Jje5GTv7+/drv1OXPmIDc3F1u3boWzszMnuL7BeKYKSUetVmu3lHgZzsATJz09HY6OjqJj0HOePHmCbt26Yd26dXB2dhYdh55jbm6OM2fOoF69eqKj0Cvk5ORwqzzBTp06henTp2PmzJlo2LBhie0luV2eGObm5ujbty+GDx+O9957T3Qc+i8LCwvExMTAyclJdBR6TpUqVbBr1y506NBBdBT6r86dOwMADh8+jHbt2ukcsG1kZAR7e3tMnTqVv6EFqV+/PmbNmoUBAwZoD3h2dHTEzJkzkZ2djTVr1oiOqChsL3Jje5FPYWEhoqKi0LhxY75LKgxXqpB0uMWE/JycnNCpUyeMGDECvXv35vJfCVSqVOm1VnmR/rRq1QoZGRksqkhm8eLFsLe3154V0bdvX2zfvh3Vq1fHrl27uP2UIFWrVsW9e/fw4Ycf6lzndnlibd68GSEhIfjwww9hb2+P4cOHY8iQIahZs6boaIrWpUsXxMXFsagimXfeeQcWFhaiY9BzIiMjATzdKnfVqlUs0EvmypUraN++PQDA1NQU9+/fB/D0nLW2bdtykFjP2F7kxvYiHwMDA3z88cdITk5mUUVhWFQh6dSpU0d0BHqF6OhoBAcHY8qUKRg/fjz69euHESNGoHXr1qKjKdqgQYMQGBiIRYsWiY5CzwkICMCYMWNw7dq1Umfec2s2MdatW4d//vOfAID9+/dj//792L17N8LCwuDn54d9+/YJTqhMAwcORKVKlfDLL79wOyOJ9OrVC7169cLNmzexadMmhISE4Ntvv4WbmxuGDx8ODw8PGBrytULfAgICMHToUJw9e7bU/sXDw0NQMmVbvnw5pk2bhnXr1vG9RjLBwcEAgAsXLiAtLQ3vv/8+TE1NX3h2BOlH9erVkZ2djTp16qB27do4fvw4mjRpgosXL75y9woqP2wvcmJ7kVPDhg2Rnp4OBwcH0VFIj7j9F1UISUlJpR7CxZdFsQoKChAREYGQkBDs2bMHdevWxfDhwzF48GBUq1ZNdDzFmTBhAjZu3AhnZ2e0aNGixP733MtTjOPHj8PLywuXLl3SXnu2xSFn3otjamqKlJQU2NnZYeLEiXj06BF++uknpKSkoE2bNrhz547oiIpUuXJlxMTEcGVXBfD999/Dz88P+fn5sLGxwZgxYzB9+nSdvdepfO3cuRODBw/GvXv3Stxj/yLOzZs30bdvXxw5cgSVK1cuUezKzs4WlIyys7PRp08fREZGQqVSITU1FY6Ojhg+fDisrKywfPly0REVaeTIkbCzs8OsWbOwdu1a+Pn5oUOHDjh9+jQ8PT0RGBgoOqIisb3Iie1FTnv27MHXX3+NefPmlToWwxVfbyYWVUhq6enp+Oyzz5CQkKBzzsqzmRF8WZTD48eP8cMPP+Drr79Gfn4+jIyM0LdvXyxevBg1atQQHU8xnu1/WxqVSoVDhw7pMQ094+rqChcXF3z11VelzrznLFYxatasiW3btqF9+/aoV68e5s+fjz59+uD8+fNo1apVqYOUVP7ef/99zJw5E127dhUdhUpx/fp1bNiwASEhIbh8+TI+++wzjBgxAlevXsXixYtRs2ZNrvLSI3t7e3z66af49ttv8fbbb4uOQ//VtWtXXLlyBSNGjCi13x86dKigZDRkyBDcuHEDAQEBcHFx0Z5FsHfvXkyZMgWJiYmiIypSUVERioqKtCset2zZgj///BPOzs4YPXq0zpkepD9sL3Jie5GTWq3W/vv5fp8TKd9sLKqQ1Hr06AEDAwMEBATAwcEBJ0+exO3bt+Hr64tly5ahY8eOoiMq2unTpxEUFIQtW7bAzMwMQ4cO1Q6uzJkzB/fu3cPJkydFxyQSyszMjHveS2j8+PH4/fff4ezsjJiYGFy6dAnm5ubYsmULlixZgujoaNERFenXX3/F7Nmz4efnh0aNGnG7PEmEh4cjODgYe/fuhaurK0aOHIlBgwbp7BudlpYGFxeXEquKqfxYWFggNjYW7777rugo9JzKlSvjr7/+4tlcEqpevTr27t2LJk2a6BzwnJ6ejsaNGyM3N1d0REW6cuUK7OzsShQgNRoNMjIyULt2bUHJlI3tRU5sL3I6fPjwS+936tRJT0lIn7j5MUntr7/+wqFDh2BjYwO1Wg21Wo333nsP3333HXx8fBATEyM6oiL5+/sjODgY58+fh7u7OzZu3Ah3d3dtdd7BwQEhISGwt7cXG1ShuO+tXD788EMWVSS0YsUK2NvbIyMjA0uWLIG5uTkAIDMzE+PGjROcTrn69esHABg+fLj2GrfLE8/b2xv9+/dHVFQUWrVqVeozNWvWxDfffKPnZMrm6emJyMhIFlUkU79+fTx8+FB0DCrFgwcPSt2iMDs7G8bGxgISEfD03TEzMxO2trY617Ozs+Hg4MC+XxC2FzmxvciJRRNlYlGFpFZYWAgLCwsAgI2NDf7zn/+gXr16qFOnDs6fPy84nXL9+OOPGD58OIYNG/bC7b1sbW25n6ee3b59G3379i2x7+2IESO4761APXr0wOTJk5GQkFDqzHueDSVGpUqVMHXq1BLXJ0+eLCANPXPx4kXREagUmZmZrzwrxdTUFLNmzdJTIgKAunXr4uuvv8axY8dK7V98fHwEJVO2RYsWwdfXFwsWLCj178J91cXp2LEjNm7ciHnz5gF4WrQvKirCkiVLXrqNLpWvF00Ay83NhYmJiYBEBLC9yIrtRU5Hjhx56f33339fT0lIn7j9F0mtY8eO8PX1Ra9eveDl5YU7d+7gH//4B37++WecOXMGZ8+eFR2RSBrc91ZOz++vWhxn3ouVmpqKyMhI3LhxA0VFRTr3Zs6cKSiVsj148KDEwY4kXnR0NCpVqoRGjRoBAH777TcEBwfD1dUVs2fP5v7dgjg4OLzwnkqlQnp6uh7T0DPP+v3StmZhvy/W2bNn0aVLFzRv3hyHDh2Ch4cHEhMTkZ2djaioKK760rMpU6YAAFatWoVRo0bpFO8LCwtx4sQJGBgYICoqSlRERWN7kQvbi9xKe+d//ncA+/43E1eqkNT+8Y9/4MGDBwCAuXPn4tNPP0XHjh3x1ltvYevWrYLTKdeePXtgbm6O9957DwCwdu1arF+/Hq6urli7di2srKwEJ1Smffv2Ye/evahVq5bOdWdnZ1y+fFlQKio+WE9yWL9+PcaOHQsbGxtUr15d50evSqViUUWQt99+G3379sXw4cO1fQyJN3r0aEyfPh2NGjVCeno6+vfvj88++wy//vor8vLysHLlStERFYkru+QUGRkpOgK9QMOGDZGSkoI1a9bAwsICubm58PT0xJdffvnC1fdUfp5t5a3RaJCQkKBToDcyMkKTJk1KXVVM+sH2Ihe2F7nduXNH5/OTJ08QExODb7/9FgsWLBCUisobV6pQhZOdnQ0rKyueESFQo0aNsHjxYri7uyMhIQGtWrXClClTEBkZifr16yM4OFh0REWysLBAdHQ0nJ2ddQ4TPH36NNzc3HD79m3REYmkUadOHYwbNw7Tpk0THYWe869//QshISHYtWsX7O3tMXz4cAwZMgQ1a9YUHU3RqlSpgujoaLz77rtYvHgxDh06hL179yIqKgr9+/dHRkaG6IhERFRBeXt7Y9WqVdwaj6gM2F4qlsOHD2PKlCk4c+aM6ChUDlhUoQrj2Qu7nZ2d4CRkbm6Os2fPwt7eHrNnz8bZs2exbds2REdHw93dHVlZWaIjKpK7uztatGiBefPmwcLCAvHx8ahTpw769++PoqIibNu2TXRExXrw4AEOHz6MK1euID8/X+ce97wXw9LSErGxsXB0dBQdhUpx8+ZNbNq0CSEhIUhOToabmxuGDx8ODw8PGBpyobW+WVpa4syZM3B2dsZHH32ETz/9FBMnTsSVK1dQr149Hsot0NWrVxEREVFq/+Lv7y8oFQFAXl5eqX+Xxo0bC0pEAPDo0SPEx8eXuvUnz7kT68KFC0hLS8P7778PU1PTF54dQfrD9iIvtpeK4dy5c2jZsiVyc3NFR6FywKIKSa2goABz5szB6tWrtV9C5ubmmDBhAmbNmlXi4EfSD2traxw7dgyurq547733MGTIEHzxxRe4dOkSXF1dkZeXJzqiInHfWznFxMTA3d0deXl5ePDgAaytrXHr1i1UrlwZtra23PNekBEjRqBVq1YYM2aM6Cj0Ct9//z38/PyQn58PGxsbjBkzBtOnT3/lwen09/nwww9hZ2eHrl27YsSIEUhKSoKTkxMOHz6MoUOH4tKlS6IjKtLBgwfh4eEBR0dHnDt3Dg0bNsSlS5eg0Wi0vwVI/27evAlvb2/s3r271PvcV12cPXv2YMiQIbh161aJezzvRpzs7Gz06dMHkZGRUKlUSE1NhaOjI4YPHw4rKyssX75cdERFYnuRE9uLnOLj43U+azQaZGZmYtGiRSgoKMCxY8cEJaPy9OLTc4kkMGHCBPz8889YsmQJYmJiEBMTgyVLliAwMJCzuwV67733MGXKFMybNw8nT57EJ598AgBISUkpcZ4H6c+zfW/fe+899OzZEw8ePICnpydiYmJYUBFo8uTJ6NGjB+7cuQNTU1McP34cly9fRosWLbBs2TLR8RTLyckJ3377LYYNG4bly5dj9erVOv8hsa5fv44lS5bA1dUV06dPR+/evXHw4EEsX74c4eHh6NWrl+iIirJy5UpER0dj/Pjx+Oabb+Dk5AQA2LZtG9q3by84nXJ9/fXXmDp1KhISEmBiYoLt27cjIyMDnTp1Qp8+fUTHU6xJkyYhJycHJ06cgKmpKfbs2YMNGzbA2dkZERERouMp2oQJE9CnTx9kZmaiqKhI5z8cIBZn0qRJqFSpEq5cuaIzYaJfv37Ys2ePwGTKxvYiJ7YXOTVt2hTNmjVD06ZNtf92d3dHfn4+AgICRMejcsKVKiS1KlWqYMuWLejevbvO9V27dmHAgAG4e/euoGTKduXKFYwbNw4ZGRnw8fHBiBEjADwdPC4sLOSAJNFzqlatihMnTqBevXqoWrUq/vrrL7i4uODEiRMYOnQozp07JzqiIjk4OLzwnkql4goiQcLDwxEcHIy9e/fC1dUVI0eOxKBBg1C1alXtM2lpaXBxcSmxpQ7p36NHj2BgYKBdORwaGgoPDw+YmZkJTqYMFhYWiI2NxbvvvgsrKyscO3YMDRo0QFxcHHr27MkVRILUqFEDv/32G1q3bg1LS0ucPn0adevWRUREBJYsWcLZqgJZWlpyspGEqlevjr1796JJkyY650Kmp6ejcePG3DZHELYXObG9yOny5cs6n9VqNapVqwYTExNBiUgfuCk1Sc3Y2Bj29vYlrjs4OMDIyEj/gQgAULt2bfz+++8lrq9YsULn86JFizBmzBidwTAqX3fu3EFgYCCSk5MBAK6urvD29oa1tbXgZMpVqVIlqNVPF4ba2triypUrcHFxQZUqVXi4s0AXL14UHYFK4e3tjf79+yMqKgqtWrUq9ZmaNWvim2++0XMyKk3xF8XRo0ejTZs2PKtIT8zMzLTFxRo1aiAtLQ0NGjQAgFK3ayH9ePDgAWxtbQEAVlZWuHnzJurWrYtGjRohOjpacDpl6927N/744w8OEkvmwYMHpW7pmZ2dDWNjYwGJCGB7kRXbi5zq1KkjOgIJwKIKSW38+PGYN28egoODtR3E48ePsWDBAowfP15wOnqVhQsXom/fviyq6MmRI0fQo0cPVKlSBS1btgQArF69GnPnzsXOnTvx/vvvC06oTM2aNcOpU6fg7OyMTp06YebMmbh16xY2bdqEhg0bio5HJJXMzMxXnpViamqKWbNm6SkRvQ4ugNevtm3b4tixY3BxcYG7uzt8fX2RkJCA8PBwtG3bVnQ8xapXrx7Onz8Pe3t7NGnSBD/99BPs7e2xbt061KhRQ3Q8RVuzZg369OmDo0ePolGjRiXO5+T20mJ07NgRGzduxLx58wA8XTFcVFSEJUuWoHPnzoLTKRfbi5zYXuTxOju0sL28mbj9F0nH09NT5/OBAwdgbGyMJk2aAADi4uKQn5+PLl26IDw8XEREKqPnl6NS+WvUqBHatWuHH3/8EQYGBgCeHoY6btw4/Pnnn0hISBCcUJlOnz6N+/fvo3Pnzrhx4waGDBmCP//8E87OzggKCtJ+t5H+Xb16FREREbhy5UqJraT8/f0FpaJnHj16VOLvYmlpKSgNlQX7ff1KT09Hbm4uGjdujAcPHsDX11fbv/j7+3PWpCCbN29GQUEBhg0bhjNnzqBbt27Izs6GkZERQkJC0K9fP9ERFSswMBBjxoyBiYkJ3nrrLahUKu09bv0pztmzZ9GlSxc0b94chw4dgoeHBxITE5GdnY2oqCiulBCE7UVObC/yKL6d9M2bN5GXl6edVJyTk4PKlSvD1taW7eUNxaIKScfb27vMzwYHB5djEvq/4uCKfpmamiI2Nhb16tXTuX7+/Hk0bdoUDx8+FJSMSD4HDx6Eh4cHHB0dce7cOTRs2BCXLl2CRqPRvqSQ/j148ADTpk1DWFgYbt++XeI+D0aVG/t9opLy8vJw7tw51K5dGzY2NqLjKFr16tXh4+OD6dOna7dmJTncvXsXa9asQVxcHHJzc9G8eXN8+eWXXN0lENuLvNhe5PPLL7/ghx9+QGBgoHY85vz58xg1ahRGjx6NgQMHCk5I5YFFFSIqNxxc0a8OHTrAz88PvXr10rn+r3/9C4sWLcLx48fFBCOSUOvWrdG9e3fMmTNH+11la2uLgQMHolu3bhg7dqzoiIr05ZdfIjIyEvPmzcPgwYOxdu1aXLt2DT/99BMWLVrEFxLJsd8nIplZW1vj1KlTnMlNVAZsL0Rl9+6772Lbtm1o1qyZzvUzZ86gd+/ePM/zDcUzVYiI3hA+Pj6YOHEiLly4oN1L/fjx41i7di0WLVqE+Ph47bONGzcWFZP+a8aMGcjKykJQUJDoKIqUnJyM0NBQAIChoSEePnwIc3NzzJ07Fz179mRRRZCdO3di48aN+OCDD+Dt7Y2OHTvCyckJderUwT//+U8WVYjKYOjQocjIyOCKO8n89ttvuHv3LoYMGSI6imINHToUW7duxYwZM0RHoWIePXqE+Ph43LhxA0VFRTr3PDw8BKVSNrYXebG9yCczMxMFBQUlrhcWFuL69esCEpE+sKhCFRIHI4lKGjBgAADgq6++KvWeSqWCRqOBSqXiFjoSuHbtGjIyMkTHUCwzMzPteR01atRAWloaGjRoAAC4deuWyGiKlp2drV3lYGlpiezsbADAe++9x0KXpJ71KwBQp06dEgfZUvnQaDTIyMiAra0tTExMdO6988473KpFQtOmTUNqaiqLKgIVFhZiyZIl2Lt3Lxo3blzi+4rnqYmxZ88eDBkypNTfX3xvEYftRU5sL3Lq0qULRo8ejYCAADRv3hzA01UqY8eORdeuXQWno/LCogpVSByMlNfDhw9hamoKAOjYsaP231T+uKS0YtmwYYPoCIrWtm1bHDt2DC4uLnB3d4evry8SEhIQHh6uXelF+ufo6IiLFy+idu3aqF+/PsLCwtC6dWvs3LlTe+gj6d/SpUvh5+dX4nphYSEGDRqkXfV19uxZfUdTLI1GAycnJyQmJsLZ2Vnn3sKFCwWlopc5d+6c6AiKl5CQoN2apfj31fOHcJN+TZgwAX369MHMmTPx9ttvi45D/8X2Iie2FzkFBQVh6NChaNmypbYAWVBQADc3NwQEBAhOR+WFZ6oQ0Wvz8fHB6tWrS1x/8OABPv30U0RGRgpIRVRx5OTkcIBYsPT0dOTm5qJx48Z48OABfH198eeff8LZ2Rn+/v6oU6eO6IiKtGLFChgYGMDHxwcHDhxAjx49oNFo8OTJE/j7+2PixImiIyqSra0tvvvuO4wYMUJ7rbCwEP3798fZs2eRnJwsMJ1yNWjQAIGBgSwEE1GFZmlpiZiYGJ7dQVQGbC9yS01N1f4url+/PurWrSs4EZUnFlWowuFgpHjvvvsuBg0ahDlz5mivPXjwAN26dQMAHD16VFQ0xUtLS8PKlSu1HbmrqysmTpzIH10CLV68GPb29ujXrx8AoG/fvti+fTuqV6+OXbt2oUmTJoITKk9hYSGioqLQuHFj9ieSu3TpEqKjo+Hk5MSzoAQ6deoUPv74Y6xfvx69e/dGQUEB+vbti3PnzuHQoUOoXr266IiKtHPnTixZsgQ//vgjGjZsKDoOPScnJwcnT54sdb97bv9FpGv48OHo0KGDTuGeiErH9kIkDxZVSGocjJRTWloaOnbsiK+++gqTJk3C/fv34ebmBkNDQ+zevRtmZmaiIyrS3r174eHhgaZNm6JDhw4AgKioKMTFxWHnzp346KOPBCdUJgcHB/zzn/9E+/btsX//fvTt2xdbt25FWFgYrly5gn379omOqEgmJiZITk6Gg4OD6ChEFcKhQ4fQq1cvbN68GYGBgbhw4QIOHTrErScEsrKyQl5eHgoKCmBkZFRiy9VnZxKRfu3cuRMDBw5Ebm4uLC0tdbbJUalU/LsQFZOXl4c+ffqgWrVqaNSoUYmzO3x8fAQlI5IP20vF8ttvv+Hu3bucUPGGYlGFpMbBSHnFx8ejc+fOmDVrFkJDQ2FsbIx///vfLKgI1KxZM7i5uWHRokU616dPn459+/YhOjpaUDJlMzU1RUpKCuzs7DBx4kQ8evQIP/30E1JSUtCmTRvcuXNHdERFatmyJRYvXowuXbqIjkLFHDx4ECtWrNCuuHNxccGkSZN4yKME/vWvf6FPnz5wcXHBoUOHYGNjIzqSor3qbK6hQ4fqKQk9r27dunB3d8fChQtRuXJl0XGIpBcYGIgxY8bAxMQEb731VolCZHp6usB0RHJhe6lY6tevj9TUVBQWFoqOQuWARRWSGgcj5fbXX3/ho48+Qps2bfD777/zUHrBTExMkJCQUOLA2pSUFDRu3BiPHj0SlEzZatasiW3btqF9+/aoV68e5s+fjz59+uD8+fNo1aoV7t27JzqiIu3Zswdff/015s2bhxYtWpQoCFtaWgpKpmw//PADJk6ciN69e6Ndu3YAgOPHj2Pbtm1YsWIFvvzyS8EJlcPT07PU68ePH4eTk5NOQSU8PFxfsYikZ2ZmhoSEBDg6OoqOQlQhVK9eHT4+Ppg+fTrUarXoOERSY3shkoeh6ABEL2NlZYWMjAzY2dlhz549mD9/PgBAo9Gw0qtnzZo105kF8YyxsTH+85//aLebAsAVEYJUq1YNsbGxJYoqsbGxsLW1FZSKPD094eXlBWdnZ9y+fRvdu3cHAMTExMDJyUlwOuVyd3cHAHh4eOh8t2k0GqhUKvYxgixcuBArVqzA+PHjtdd8fHzQoUMHLFy4kEUVPapSpUqp193c3PSchF4mLS0NwcHBSEtLw6pVq2Bra4vdu3ejdu3aaNCggeh4iuTm5obTp0+zqEJURvn5+ejXrx8HiInKgO2FSB4sqpDUOBgpj169eomOQK8watQofPHFF0hPT0f79u0BPD1TZfHixZgyZYrgdMq1YsUK2NvbIyMjA0uWLIG5uTkAIDMzE+PGjROcTrkiIyNFR6BS5OTkoFu3biWuf/zxx5g2bZqARMoVHBwsOgK9wuHDh9G9e3d06NABR44cwYIFC2Bra4u4uDgEBgZi27ZtoiMq0ieffAI/Pz8kJSWVut+9h4eHoGTKtHr16tf+73h7e8PCwqIc0lBphg4diq1bt2LGjBmioyge24v82F7klZOTg5MnT+LGjRsoKirSucczVd5M3P6LpPbkyROsWrUKGRkZGDZsGJo1awbg6SClhYUFRo4cKTghkTw0Gg1WrlyJ5cuX4z//+Q+Ap1tP+fn5wcfHp9SVRkRKdeXKFdjZ2ZVoFxqNBhkZGahdu7agZMrm5eWFZs2awc/PT+f6smXLcPr0aWzZskVQMiL5tGvXDn369MGUKVNgYWGBuLg4ODo64uTJk/D09MTVq1dFR1Skl80e5kpI/VOr1ahVqxYMDAzK9HxGRgZSUlK40kiPfHx8sHHjRjRp0gSNGzcuUYj09/cXlEx52F7kx/Yip507d2LgwIHIzc2FpaVlibNusrOzBaaj8sKiChHRG+j+/fsAwFlDkkhNTUVkZGSps1ZmzpwpKJWyGRgYIDMzs8TWeLdv34atrS0HvQSZP38+li1bhg4dOuicqRIVFQVfX1+ds258fHxExaT/mjFjBrKyshAUFCQ6iiKZm5sjISEBDg4OOkWVS5cuoX79+jxLjQhPB4mzsrLKvBXu822J9KNz584vvKdSqXDo0CE9plE2thf5sb3IqW7dunB3d8fChQtRuXJl0XFIT7j9F0mPg5EVx9ChQ5GRkcGOXAIspshj/fr1GDt2LGxsbFC9evUSs1b4PSbGs7NTisvNzYWJiYmARAQAgYGBsLKyQlJSEpKSkrTXq1atisDAQO1nlUrFoooErl27hoyMDNExFKtq1arIzMyEg4ODzvWYmBi88847glIRyWXWrFnarVfLYsaMGbC2ti7HRFQct2SVB9uL/Nhe5HTt2jX4+PiwoKIwXKlCUnvVYCQPRNe/Z1vj2Nralhh4nDFjBjIzM7kPu2Q4k1isOnXqYNy4cTwPQhLPzhdatWoVRo0apfPDt7CwECdOnICBgQGioqJERSQiKpOpU6fixIkT+PXXX1G3bl1ER0fj+vXrGDJkCIYMGYJZs2aJjqhYhw8fxrJly5CcnAwAcHV1hZ+fHzp27Cg4GREREf3dPD090b9/f/Tt21d0FNIjFlVIahyMlE9RURFMTEyQmJgIZ2dn0XGoDLiCSCxLS0vExsZyWbwkni2ZP3z4MNq1awcjIyPtPSMjI9jb22Pq1Kn8fiN6hZycHFStWlV0DEXLz8/Hl19+iZCQEBQWFsLQ0BCFhYXw8vJCSEhImffEp7/X5s2b4e3tDU9PT3To0AEAEBUVhR07diAkJAReXl6CE1Jx8fHxaNmyJfLz80VHIZIe2wtRSYGBgZg7dy68vb3RqFGjEmfdeHh4CEpG5YlFFZIaByPl1KBBAwQGBqJt27aioxBJb8SIEWjVqhXGjBkjOgo9x9vbG6tWrdI5o4Pk9dtvv+Hu3bsYMmSI6CiKtHjxYtjb26Nfv34AgL59+2L79u2oXr06du3ahSZNmghOqGxXrlzB2bNnkZubi2bNmrEoLJiLiwu++OILTJ48Wee6v78/1q9fr129QvKIi4tD8+bNeZ4aURmwvRCVpFarX3hPpVKxvbyhWFQhqXEwUk47d+7EkiVL8OOPP6Jhw4ai49BLcCaxeN999x38/f3xySeflDprhedCEL1a/fr1kZqayhcSQRwcHPDPf/4T7du3x/79+9G3b19s3boVYWFhuHLlCvbt2yc6IpE0jI2NkZiYCCcnJ53rFy5cQMOGDfHo0SNByehFOEhMVHZsL0RET/GgepKak5MTvv32Wxw/fpyDkRIZMmQI8vLy0KRJExgZGcHU1FTnfnZ2tqBkysaZxHL6+eefYW5ujsOHD+Pw4cM693jYNlHZnDt3TnQERcvKyoKdnR0A4Pfff0ffvn3x8ccfw97eHm3atBGcTlmenQtVFv7+/uWYhF7Ezs4OBw8eLFFUOXDggLYdEREREVHFxqIKSY2DkXJauXKl6AhUinXr1uGf//wnAGD//v3Yv38/du/ejbCwMPj5+XEmsSAXL14UHYGI6P/EysoKGRkZsLOzw549ezB//nwAgEaj4UxVPYuJidH5HB0djYKCAtSrVw8AkJKSAgMDA7Ro0UJEPALg6+sLHx8fxMbGon379gCenqkSEhKCVatWCU6nTPfu3Xvp/fv37+spCT2zevXq1/7veHt7w8LCohzS0PPYXuTD9lIxHD58GMuWLdNu8+nq6go/Pz907NhRcDIqL9z+i4joDWFqaoqUlBTY2dlh4sSJePToEX766SekpKSgTZs2uHPnjuiIRESvlJOTg5MnT+LGjRsoKirSucczVcQYP348fv/9dzg7OyMmJgaXLl2Cubk5tmzZgiVLliA6Olp0REXy9/fHH3/8gQ0bNsDKygoAcOfOHXh7e6Njx47w9fUVnFC5duzYgeXLl2sHVlxcXODn54eePXsKTqZMarUaKpXqhfc1Gg33vNcztVqNWrVqwcDAoEzPZ2RkICUlhWet6gHbi3zYXuS3efNmeHt7w9PTEx06dADwdELFjh07EBISAi8vL8EJqTywqEJE/5O0tDQEBwcjLS0Nq1atgq2tLXbv3o3atWujQYMGouMpUs2aNbFt2za0b98e9erVw/z589GnTx+cP38erVq1euWsIyo/V69eRUREBK5cuYL8/Hyde9yehej/27lzJwYOHIjc3FxYWlrqvNSrVCpuLynIkydPsGrVKmRkZGDYsGFo1qwZAGDFihWwsLDAyJEjBSdUpnfeeQf79u0r8bvr7Nmz+Pjjj/Gf//xHUDIiuRTf8eBFOnXqVM5J6Bm1Wo2srCzY2tqW6XkLCwvExcVxkFgP2F7kw/YiPxcXF3zxxReYPHmyznV/f3+sX79eO8mC3izc/oukx8FI+Rw+fBjdu3dHhw4dcOTIESxYsAC2traIi4tDYGAgtm3bJjqiInl6esLLywvOzs64ffs2unfvDuDpViHF9/Um/Tl48CA8PDzg6OiIc+fOoWHDhrh06RI0Gg2aN28uOp6icOm8/Hx9fTF8+HAsXLgQlStXFh2H/qtSpUqYOnVqievFXxxJv+7du4ebN2+WuH7z5k1uz0L0nLIM/rJor1+zZs2Cubl5mZ+fMWMGrK2tyzERPcP2Ih+2F/mlp6ejR48eJa57eHhgxowZAhKRPnClCkntVYORhw4dEh1Rkdq1a4c+ffpgypQpOrMgTp48CU9PT1y9elV0REXiTGI5tW7dGt27d8ecOXO07cXW1hYDBw5Et27dMHbsWNERFYNL5+VnZmaGhIQE/m8uodTUVERGRpa6LdvMmTMFpVK2IUOG4OjRo1i+fDlat24NADhx4oR2/+4NGzYITqgc1tbWSElJgY2NDaysrF66dQ4HI+Wyb98+BAQEYOfOnXj48KHoOERSY3shKp2TkxP8/PwwevRonevr1q3D8uXLkZqaKigZlSeuVCGpff3115g6dap2MHL79u06g5EkRkJCAn755ZcS121tbXHr1i0BiQjgTGJZJScnIzQ0FABgaGiIhw8fwtzcHHPnzkXPnj1ZVNGz06dPv9bSedIvNzc3nD59mkUVyaxfvx5jx46FjY0NqlevXmJbNhZVxFi3bh2mTp0KLy8vPHnyBMDTfmbEiBFYunSp4HTK8mwCy7N/v6yoQuJdvnwZQUFB2LBhA+7cuYPu3btj48aNomNRMfHx8WjZsmWJ3SpIv9heKga2F7F8fX3h4+OD2NhYtG/fHsDTM1VCQkKwatUqwemovLCoQlLjYKScqlatiszMTDg4OOhcj4mJwTvvvCMoFQGcSSwjMzMz7Y/bGjVqIC0tTbv/PYuQ+sWl8/L75JNP4Ofnh6SkJDRq1AiVKlXSue/h4SEombLNnz8fCxYswLRp00RHof8qLCzE6dOnsWDBAixduhRpaWkAgHfffRdmZmaC0ynP0KFDtf8eNmyYuCD0Qvn5+QgPD0dAQACioqLQtWtXXL16FTExMWjUqJHoeFQKjUbDw9AFYXupeNhexBo7diyqV6+O5cuXIywsDMDTc1a2bt2Knj17Ck5H5YVFFZIaByPl1L9/f0ybNg2//vorVCoVioqKEBUVhalTp2LIkCGi4ykWZxLLqW3btjh27BhcXFzg7u4OX19fJCQkIDw8HG3bthUdT1FmzZr1Ws9//fXX5ZSEXmTUqFEAgLlz55a4p1Kp+LIoyJ07d9CnTx/RMeg5BgYG+Pjjj5GcnAwHBwc0btxYdCT6LwMDA2RmZpZYFXn79m3Y2trye0yACRMmIDQ0FM7Ozhg0aBC2bt2Kt956C5UqVSrzlqBESsH2QvS/+eyzz/DZZ5+JjkF6xKIKSY2DkXJauHAhvvzyS9jZ2aGwsBCurq4oLCyEl5cX/vGPf4iOp1icSSwnf39/5ObmAgDmzJmD3NxcbN26Fc7OzvD39xecjorj0nmxiq+wIzn06dMH+/btw5gxY0RHoec0bNgQ6enpJVYOk1gvOrL08ePHMDIy0nMaAoAff/wR06ZNw/Tp07m1J9ErsL0QEZUNiyokNQ5GysnIyAjr16/Ht99+i7NnzyI3NxfNmjWDs7Oz6GiKxpnE8iksLMTVq1e1M4jNzMywbt06wanoZbh0nqgkJycnfPvttzh+/Hip27L5+PgISqZs8+fPx9SpUzFv3jy0aNGixLZflpaWgpIp0+rVqwE8XVUXEBCgs91kYWEhjhw5gvr164uKp2ibNm1CUFAQatSogU8++QSDBw9G9+7dRcdSvHv37r30/v379/WUhJ7H9iInthf5WFtbIyUlBTY2NrCysnrpeWrZ2dl6TEb6otK8aCoNkWCFhYWIiopC48aNUbVqVdFxiKQ3YsQItGrVijOJJWNiYqLdnoXkFxcXh+bNm7OwItDhw4exbNkyJCcnAwBcXV3h5+eHjh07Ck6mXC/7/lKpVEhPT9djGnpGrVZr//38i7xGo+F2eQI8ayeXL19GrVq1dLbJMTIygr29PebOnYs2bdqIiqh4Fy9eREhICEJCQpCXl4fs7Gxs3boVvXv3Fh1NkdRq9UsHIfldJhbbi1zYXuSzYcMG9O/fH8bGxggJCXnp3+f5s9fozcGiCkmNg5HymDJlSpmf5SoiMb777jv4+/vjk08+4UxiibRs2RKLFy9Gly5dREehMmBRRazNmzfD29sbnp6e6NChAwAgKioKO3bsQEhICLy8vAQnJJLH4cOHX3q/U6dOekpCz+vcuTPCw8NhZWUlOgq9gEajwb59+xAYGIiIiAjY2NjA09NTu9qI9ONV32HP8LtMLLYXObC9EMmHRRWSGgcj5dG5c2edz9HR0SgoKEC9evUAACkpKTAwMECLFi1w6NAhEREVjzOJ5bRnzx58/fXX3J5FEq9aOh8fH49OnTqxqCKIi4sLvvjiC0yePFnnur+/P9avX69dvUJERPR3yM7OxsaNGxESEoLY2FjRcaiY7OxsWFtbi45B/8X2Ije2F3EMDAyQmZkJW1tbneu3b9+Gra0t3y3fUDxThaTGvaLlERkZqf23v78/LCwssGHDBu0svDt37sDb25vbswh08eJF0RGoFO7u7gAADw8Pbs8igapVq5Zp6TyJkZ6ejh49epS47uHhgRkzZghIRM9cvXoVERERuHLlCvLz83XucYWqODk5OQgMDNQWHBs0aIDhw4ejSpUqgpMpG9tLxWFtbY2OHTviwIEDoqPQc/bt24eAgADs3LkTDx8+FB2H/ovtRU5sL+K9aL3C48ePYWRkpOc0pC8sqpDUOBgpp+XLl2Pfvn062xpYWVlh/vz5+Pjjj+Hr6yswHZFcni9Iknj8e8jNzs4OBw8ehJOTk871AwcOwM7OTlAqOnjwIDw8PODo6Ihz586hYcOGuHTpEjQaDZo3by46nmKdPn0abm5uMDU1RevWrQE8HbBfsGAB9u3bx7+NIGwvctq7dy/2798PIyMjjBw5Uvv3mT59Onbu3Ak3NzfRERXv8uXLCAoKwoYNG3Dnzh10794dGzduFB1Lkdhe5Mf2Iodn2+CpVCoEBATA3Nxce6+wsBBHjhxB/fr1RcWjcsaiCkmNg19yunfvHm7evFni+s2bN3H//n0BiegZzoyUj4ODA+zs7EqsftBoNMjIyBCUSrnKss9wdna2HpJQaXx9feHj44PY2Fi0b98ewNMzVUJCQrBq1SrB6ZTr66+/xtSpUzFnzhxYWFhg+/btsLW1xcCBA9GtWzfR8RRr8uTJ8PDwwPr162Fo+PS1rqCgACNHjsSkSZNw5MgRwQmVie1FPoGBgRg1ahSsra1x584dBAQEwN/fHxMmTEC/fv1w9uxZuLi4iI6pSPn5+QgPD0dAQACioqLQtWtXXL16FTExMWjUqJHoeIrE9iIvthf5rFixAsDTd/t169bBwMBAe8/IyAj29vZYt26dqHhU3jREErt8+bKmqKioxPWioiLN5cuXBSQijUajGTx4sMbe3l6zfft2TUZGhiYjI0Ozbds2jYODg2bIkCGi4ynWgQMHNJUrV9Y0bNhQY2hoqGnatKmmatWqmipVqmg6d+4sOp5iqdVqzfXr10tcv3XrlkatVgtIRC+yd+9eTZ8+fTQmJiaioyhaeHi4pkOHDhpra2uNtbW1pkOHDpp//etfomMpmrm5uebChQsajUajqVq1qubs2bMajUajiY2N1dSpU0dgMmUzMTHRJCcnl7iemJioMTU1FZCINBq2Fxk1atRIs2TJEo1Go9Fs27ZNo1KpNO3atdNkZGQITqZs48eP17z11luatm3batasWaO5deuWRqPRaAwNDTWJiYmC0ykX24uc2F7k9sEHH2iys7NFxyA940oVkpqDg0Ophz1lZ2fDwcGB238Jsm7dOkydOhVeXl548uQJAMDQ0BAjRozA0qVLBadTLs6MlJPmBWd05ObmwsTEREAieh6Xzsvns88+w2effSY6Bj3HzMxMu/qxRo0aSEtLQ4MGDQAAt27dEhlN0SwtLXHlypUS20pkZGTAwsJCUCpie5FPWloa+vTpAwDw9PSEoaEhli5dilq1aglOpmw//vgjpk2bhunTp/M7SyJsL3Jie5Ebd9lRJhZVSGocjJRPYWEhTp8+jQULFmDp0qVIS0sDALz77rswMzMTnE7ZkpOTERoaCuBpkevhw4cwNzfH3Llz0bNnT4wdO1ZwQmWZMmUKgKf7q3777beoXLmy9l5hYSFOnDiBpk2bCkqnbFw6T/R62rZti2PHjsHFxQXu7u7w9fVFQkICwsPD0bZtW9HxFKtfv34YMWIEli1bprNdnp+fHwYMGCA4nXKxvcjn4cOH2t9hKpUKxsbGqFGjhuBUtGnTJgQFBaFGjRr45JNPMHjwYHTv3l10LMVje5ET24v8uBW78rCoQlLiYKS8DAwM8PHHHyM5ORkODg5o3Lix6Ej0X5wZKZeYmBgAT4vDCQkJMDIy0t4zMjJCkyZNMHXqVFHxFGvChAkIDQ2Fs7MzBg0ahK1bt+Ktt95CpUqVdPbAJf2xtrZGSkoKbGxsYGVlVepkimd43o0Y/v7+yM3NBQDMmTMHubm52Lp1K5ydnfmSKNCyZcugUqkwZMgQFBQUAAAqVaqEsWPHYtGiRYLTKRfbi5yeP0C4oKAAISEhsLGx0XnGx8dHRDTFGjBgAAYMGICLFy8iJCQEX375JfLy8lBUVISkpCS4urqKjqhYbC/yYXuR28GDB+Hh4QFHR0ecO3cODRs2xKVLl6DRaNC8eXPR8aicqDQajUZ0CKLiOnfuDAA4fPgw2rVrV2Iw0t7eHlOnToWzs7OoiIrWsmVLLF68GF26dBEdhZ7Tq1cvfPLJJxg1ahSmTp2K3377DcOGDUN4eDisrKxw4MAB0REVydvbG6tWrYKlpaXoKISnq7hKWzpfqVIlxMXF8YVEgA0bNqB///4wNjZGSEjIS4sqQ4cO1WMyAp5OZomKikLjxo1RtWpV0XGoFHl5eTorh5+fjEREgL29/Uv7FuDpZL709HQ9JaLSaDQa7Nu3D4GBgYiIiICNjQ08PT2xevVq0dEUhe2lYmB7kUvr1q3RvXt37VbscXFxOluxc9eQNxOLKiQ1DkbKac+ePfj6668xb948tGjRosS2X/x7iZGeno7c3Fw0btwYDx48gK+vL/7880/tzMg6deqIjkgkXGhoKIKCgvDXX3/pLJ03MTFhUYXoBUxMTLQrVImIiMpbdnY2Nm7ciJCQEMTGxoqOQyQ1thfxLCwsEBsbi3fffRdWVlY4duwYGjRogLi4OPTs2ROXLl0SHZHKAbf/IqkFBweLjkClcHd3BwB4eHjozGJ5dgZOYWGhqGiKVVhYiKtXr2q3YzMzM8O6desEpyKSD5fOy83AwACZmZmwtbXVuX779m3Y2tqyfxGkYcOGSE9PZ1GF6AVetXXh87iNIdGrWVtbo2PHjlxpT1QGbC/icSt2ZWJRhYheW2RkpOgIVMzzZ91wexaiV3NwcMCcOXMwe/Zs7dL5QYMGYdKkSVw6L9CLFlA/fvxYZytQ0q/58+dj6tSpXKFK9AIrV64UHYFewt3dHaGhoahSpQoAYNGiRRgzZoz2N/Pt27fRsWNHJCUlCUypTHv37sX+/fthZGSEkSNHas8jmD59Onbu3Ak3NzfRERWH7UVebC/yatu2LY4dOwYXFxe4u7vD19cXCQkJCA8PR9u2bUXHo3LC7b+IiN4QPOuG6P+GS+fFeVbEmjx5MubNm6c9HBV4uhLvyJEjuHTpEmJiYkRFVDS1Wq39N1eoElFFU3wVpKWlJWJjY+Ho6AgAuH79OmrWrMnvMj0LDAzEqFGjYG1tjTt37uCtt96Cv78/JkyYgH79+mHixIlwcXERHVNx2F7kxPYiN27FrkxcqUJE/5OcnBwEBgYiOTkZANCgQQMMHz5cO6OF9I8ziYn+b7h0XpwVK1YAeDpIv27dOhgYGGjvGRkZwd7enlsaCsQVqkRld+XKlZfer127tp6S0DPF55FyXqkcVq1ahcWLF8PPzw/bt29Hnz598MMPPyAhIQG1atUSHU+x2F7kxPYit2dFR4BbsSsJV6oQ0Ws7ffo03NzcYGpqitatWwMATp06hYcPH2Lfvn1o3ry54ITKxJnE8vhfto7y9vaGhYVFOaSh4sqydH7Xrl2iYypS586dER4eDisrK9FR6DlXrlyBnZ1diTMjNBoNMjIyOEisR+xf5KdWq196vgp/j+mfWq1GVlaWdua9hYUF4uLiOPNeMDMzMyQmJsLe3h4ajQbGxsaIjIxEhw4dREdTNLYXObG9EMmHK1VIOnxZlN/kyZPh4eGB9evXw9Dw6ddIQUEBRo4ciUmTJuHIkSOCEyoTZxLLY9KkSahVq5bObPuXycjIwKeffsrvMT0ovnQ+ICBAZ+n82bNnuXReIH6PycnBwUFnK5BnsrOz4eDgwIEVPWL/Ir/i2xQ+efIEMTEx8Pf3x4IFCwSlUjaVSlWi0PWywhfpx8OHD1G5cmUAT/8exsbGqFGjhuBUxPYiJ7YX+VhZWZW5bWRnZ5dzGhKBRRWSDl8W5Xf69GmdggoAGBoa4quvvkLLli0FJlM2BweHl84kJv06ffp0iQHIF+H3l/5w6bz8rl69ioiICFy5cgX5+fk69/z9/QWlUrZnKx6Ly83NhYmJiYBEysb+RW5NmjQpca1ly5aoWbMmli5dCk9PTwGplE2j0WDYsGEwNjYGADx69AhjxozRbpX7+PFjkfEULSAgQHuOWkFBAUJCQmBjY6PzjI+Pj4hoisX2Ii+2F7msXLlSdAQSjNt/kXSKLzd9leLLUan8vf3229i0aRM+/vhjnet79+7FkCFDcP36dUHJlK34oYLP3L59G7a2tpxJrEdz5syBn5+fdjbRq3z33XcYO3YsqlatWr7BiEvnJXfw4EF4eHhot2Rr2LAhLl26BI1Gg+bNm+PQoUOiIyrKlClTADwtRo4aNUrnO62wsBAnTpyAgYEBoqKiREVUHPYvFdeFCxfQpEkTPHjwQHQUxfH29i7Tc8HBweWchJ5nb2//ylneKpUK6enpekpEANuLrNheiOTDogpJhy+L8vPx8cGOHTuwbNkytG/fHgAQFRUFPz8/fP7556zYC6JWq3H9+nVUq1ZN5/rly5fh6urKl3givHqfaBKrdevW6N69O+bMmaP929ja2mLgwIHo1q0bxo4dKzqionTu3BkAcPjwYbRr1w5GRkbae0ZGRrC3t8fUqVPh7OwsKiKRdO7du6fzWaPRIDMzE7Nnz8a5c+cQGxsrJhgRERGViytXrrz0Ps8ffDOxqEJEry0/Px9+fn5Yt24dCgoKAACVKlXC2LFjsWjRIu1SYdIPziSumOLj49GyZcsS2xtR+VKr1Zg/f7526fy0adPg5+fHpfOSsLCwQGxsLN59911YWVnh2LFjaNCgAeLi4tCzZ09cunRJdERF8vb2xqpVq2BpaSk6CpUB+xexSjuoXqPRwM7ODlu2bEG7du0EJSMiIqLyUFrf/zzuGvJm4pkqVCHxZVEsIyMjrFq1Ct999x3S0tIAAO+++26ZVxfR3+vZgagajQYJCQklZhI3adIEU6dOFRWPXkCj0fDHlQC1a9fG+vXrtZ+rV6+OTZs26TyjUqlYVBHEzMxM27fXqFEDaWlpaNCgAQDg1q1bIqMpGrf4qFjYv4gVGRmp81mtVqNatWpwcnLSOY+Q9Kes59iEh4eXcxJ6nru7O0JDQ1GlShUAwKJFizBmzBjtDhS3b99Gx44dkZSUJDCl8rC9yIntRW7PxmSeefLkCWJiYuDv748FCxYISkXljb/qqELiy6IcKleujEaNGomOoXjPXt45k5jo1bjSQW5t27bFsWPH4OLiAnd3d/j6+iIhIQHh4eFo27at6HhERK/UqVMn0RGomGeDkM/88ssv6NGjBywsLAQlIuDpeZzPH3q+cOFC9O3bVztIXFBQgPPnzwtKp1xsL3Jie5FbkyZNSlxr2bIlatasiaVLl5a5WEkVC4sqRERvCM4kJqKKzt/fH7m5uQCenrGWm5uLrVu3wtnZGf7+/oLTERGVzfnz5/H9998jOTkZAODi4oLx48ejfv36gpMpU/HfyNu2bcOSJUt4nppgxXei5870cmB7kRPbS8VUr149nDp1SnQMKicsqhAREZWD4gfVFnf//n09JaHncem83J5/YTczM8O6desEpiGSE/sXuW3fvh39+/dHy5YtteenHD9+HI0aNcKWLVvw+eefC05IREREf6fiv800Gg0yMzMxe/ZsODs7C0pF5Y1FFZISXxaJqKKrWrXqSw+r02g0L71P5YNL54moomP/IrevvvoKX3/9NebOnatzfdasWfjqq69YVCH6L5VKVeK7it9dRKVje5Fbab/NNBoN7OzssGXLFkGpqLyxqEJS4ssiEVV0xQ+qJTlw6bx8rKysytynZ2dnl3Maemb16tWv/d/x9vbmnut6wP5FbpmZmRgyZEiJ64MGDcLSpUsFJCKSk0ajwbBhw2BsbAwAePToEcaMGQMzMzMA0JkEQ6R0bC9yK/7bTK1Wo1q1anBycoKhIYfe31T8y5KU+LIoHw6uEL2eshxUywFiImDlypWiI1ApJk2ahFq1asHAwKBMz2dkZODTTz9lv68H7F/k9sEHH+Do0aNwcnLSuX7s2DF07NhRUCpli4iI0PlcVFSEgwcP4uzZszrXPTw89BlL8YYOHarzedCgQSWeKa1ASeWL7UVObC9yK8tvM3rzqDScokkVVHZ2NqytrUXHUAy1Wv3agyspKSk80K6csdhVMe3btw8BAQHYuXMnHj58KDqOohgYGCArKwvVqlUDAFhYWCA+Ph4ODg4AgOvXr6NmzZooLCwUGZNIOLVajaysLNja2pbpeQsLC8TFxbHfF4z9i3jr1q3DzJkz0bdvX7Rt2xbA0zNVfv31V8yZMwc1a9bUPstBSf1Qq9WvfEalUrHvJwLbC9H/6vz58/j++++RnJwMAHBxccH48eNRv359wcmovLCoQhUOXxbF4OCKnFjsqjguX76MoKAgbNiwAXfu3EH37t3x+eefo0+fPqKjKYparUb37t21S+d37tyJDz/8UGfp/J49e/iiKMiVK1deer927dp6SkJz5syBn58fKleuXKbnv/vuO4wdO1Z7PhHpD/sXuZRlQBLgoCQREdGbYvv27ejfvz9atmyJdu3aAXg6oeLUqVPYsmULz1N7Q7GoQhUCXxbF4+CKnFjsklt+fj7Cw8MREBCAqKgodO3aFbt370ZMTAwaNWokOp4ieXt7l+m54ODgck5CpVGr1S89X4UDkERPsX8hen2PHz9GQUGBdiIFieXp6Vmm58LDw8s5CZWG7UUubC9ye/fddzFw4EDMnTtX5/qsWbOwefNmpKWlCUpG5YlnqpC0SntZvHr1Kl8WBZk1a9ZrPf/111+XUxJ63qxZs2Bubl7m52fMmMFt8/RkwoQJCA0NhbOzMwYNGoStW7firbfeQqVKlcq8soj+fiyWyC0mJkbn85MnTxATEwN/f38sWLBAUCp6kfj4eLRs2RL5+fmioygK+xei13Pz5k0MGTIEBw4cQFFREVq1aoXNmzeXOPeG9KtKlSo6n3/55Rf06NGD2xQLxvYiJ7YXuWVmZpZ6ps2gQYOwdOlSAYlIH7hShaRU/GWxf//+2pfFuLg4uLq6io5IpeDgCtH/Z2hoiGnTpmH69Ok6P3b5PUb0+v79739j6dKl+OOPP0RHoefExcWhefPmXEGkZ+xf5Hf48GEsW7ZMu6+6q6sr/Pz8eFC9IMOHD8fu3bvh4+MDExMT/PTTT6hRowYiIyNFR6PncEW9HNheKga2F7m4u7ujT58+JXZFCA4OxpYtW7B3715Byag8caUKSenHH38s9WWR5KbRaDiwIiEWu8TYtGkTgoKCUKNGDXzyyScYPHgwunfvLjqW4nHpfMVUr149nDp1SnQMIimwf5Hb5s2b4e3tDU9PT/j4+AAAoqKi0KVLF4SEhMDLy0twQuXZv38/QkJC4ObmBgD49NNP4eLigsePH2vPWCOip9heiF6fh4cHpk2bhjNnzqBt27YAnp6p8uuvv2LOnDmIiIjQeZbeDFypQlIKDQ1FUFAQ/vrrL52XRRMTE87AkxhnrMqJfxexLl68iJCQEISEhCAvLw/Z2dnYunUrevfuLTqaIhWfPfSipfPcJkyMe/fu6XzWaDTIzMzE7Nmzce7cOcTGxooJRqVi/yIW+xc5ubi44IsvvsDkyZN1rvv7+2P9+vXa1SukPwYGBrh27RqqV6+uvWZmZobExETY29uLC0Y6OPNeDmwvFQPbi1zUanWZnlOpVPzd/AZhUYWkxpfFioWDK3Li30UOGo0G+/btQ2BgICIiImBjYwNPT0+sXr1adDRF4wuJXEo7qF6j0cDOzg5btmxBu3btBCVTpuJFruLi4+PRqVMn9i+CsX+Ri7GxMRITE0ucP3DhwgU0bNgQjx49EpRMuQwMDJCVlYVq1appr1laWiIuLg4ODg4Ck9Hz+JtMDmwvFQPbC5F43P6LpObg4IA5c+Zg9uzZ2pfFQYMGYdKkSXxZFOBVgyv379/XUxKiikelUsHNzQ1ubm7Izs7Gxo0bERISIjoWkVSK79etVqtRrVo1ODk5wdCQP1v1rWrVqiWKXM/TaDQvvU/6wf5FLnZ2djh48GCJosqBAwdgZ2cnKJWyaTQa1K1bV+f7Kjc3F82aNdOZXZydnS0inmI9vx0OABQVFeHgwYM4e/asznVulaNfbC9yYnshkg/fTqlC4MuiHDi4IicWuyoea2trdOzYEQcOHBAdhUgqnTp1Eh2BnsNDaSse9i/i+fr6wsfHB7GxsWjfvj2Ap2eqhISEYNWqVYLTKRO39JRTr169SlwbPXq0zmdulaN/bC9yYnuR3+HDh7Fs2TLtNp+urq7w8/NDx44dBSej8sKiClU4fFkUh4MrcmKxS1579+7F/v37YWRkhJEjR8LR0RHnzp3D9OnTsXPnTu0BkET0/50/fx7ff/+99oXExcUF48ePR/369QUnU56yFLk4U1UM9i/yGjt2LKpXr47ly5cjLCwMwNPvsa1bt6Jnz56C0ynT0KFDRUegUhQVFYmOQKVge5ET24vcNm/eDG9vb3h6esLHxwfA0wkVXbp0QUhICLy8vAQnpPLAM1VIWmV5Wdy1a5fomFRMdnY2rK2tRcdQlMOHD5fpOc4A16/AwECMGjUK1tbWuHPnDt566y34+/tjwoQJ6NevHyZOnAgXFxfRMRWn+NL5AQMGYOXKlXj77bd1rnPpvBjbt29H//790bJlS+35KcePH8epU6ewZcsWfP7554IT0jP79u1DQEAAdu7ciYcPH4qOoyjsX4joTfL48WMUFBTAzMxMdBQi6bG9yMnFxQVffPEFJk+erHPd398f69ev104WozcLiyokJb4sVjwcXJEbi13617hxYwwePBh+fn7Yvn07+vTpg7Zt2yIsLAy1atUSHU+xnt8L+kW4dF6cd999FwMHDsTcuXN1rs+aNQubN29GWlqaoGQEAJcvX0ZQUBA2bNiAO3fuoHv37vj888/Rp08f0dEUhf1LxXD69GmdLUBatGghOJFyWVlZlWnVNlfe6dfNmzcxZMgQHDhwAEVFRWjVqhU2b95c4jwi0i+2FzmxvcjN2NgYiYmJJf4eFy5cQMOGDfHo0SNByag8sahCUuLLYsXAwRX5sdgljpmZGRITE2Fvbw+NRgNjY2NERkaiQ4cOoqMRSaty5cqIj48v8UKSmpqKJk2aIC8vT1Ay5crPz0d4eDgCAgIQFRWFrl27Yvfu3YiJiUGjRo1Ex1Mk9i9yu3r1KgYMGICoqChUrVoVAJCTk4P27dtjy5YtfJcRYMOGDWV6jtse6dfw4cOxe/du+Pj4wMTEBD/99BNq1KjBLacFY3uRE9uL3JycnODn51finJt169Zh+fLlSE1NFZSMyhPPVCEppaWlaQfmPT09YWhoiKVLl/IlRAKlDa5cvXqVgysSKa3YtXHjRtGxFOfhw4eoXLkygKcrH4yNjVGjRg3BqegZLp2X0wcffICjR4+WKKocO3aMhzwKMGHCBISGhsLZ2RmDBg3C1q1b8dZbb6FSpUowMDAQHU+x2L/IbeTIkXjy5AmSk5NRr149AE/PivL29sbIkSOxZ88ewQmVh4O/ctq/fz9CQkK0Z0B9+umncHFxwePHj2FsbCw4nXKxvciJ7UVuvr6+8PHxQWxsLNq3bw/g6ZkqISEhWLVqleB0VF5YVCEp8WVRThxckReLXXIKCAiAubk5AKCgoAAhISGwsbHReebZQXakH1w6LzcPDw9MmzYNZ86cQdu2bQE8PVPl119/xZw5c3TOxOG5N+Xvxx9/xLRp0zB9+nRYWFiIjkPPYf8ir8OHD+PPP//UFlQAoF69evj+++9ZHJZUZmYmFixYgDVr1oiOoij/+c9/0KRJE+1nZ2dnGBsbIzMzE/b29uKC0UuxvYjB9iK3sWPHonr16li+fDnCwsIAPD1nZevWrejZs6fgdFReuP0XSUmtVmP+/Pnal8Vp06bBz8+PL4uCGRoaljq4UqlSJcTFxcHV1VVgOuUqXuzq37+/ttjFv4s49vb2r9yPWKVSIT09XU+JCODSedmV5cwbgOfe6EtoaCiCgoLw119/4ZNPPsHgwYPRvXt3mJiYsH8RiP2L3OrWrYvNmzejdevWOtdPnjwJLy8vXLhwQVAyZUtMTERkZCSMjIzQt29fVK1aFbdu3cKCBQuwbt06ODo6IjExUXRMRTEwMEBWVhaqVaumvWZpaYm4uDg4ODgITEZsL/JheyGSD4sqJCW+LMqJgytyYrGLqOzs7OwQEBCgXTqfmpoKFxcXPHjwgEvniV7g4sWLCAkJQUhICPLy8pCdnY2tW7eid+/eoqMRSee3337DwoULsXbtWrRs2RLA00PrJ0yYgGnTpqFXr15iAypQREQEevfujYKCAgCAo6Mj1q9fj759+6JFixaYNGkSunXrJjil8qjValSpUkXnvT8nJweWlpY6kyx4ILp+sb3Iie2lYjh9+jSSk5MBAK6urmjRooXgRFSeWFQhotfGwRW5sNhFVHYGBga4du0aqlevrr32/KHPRPRiGo0G+/btQ2BgICIiImBjYwNPT0+sXr1adDQiaVhZWSEvLw8FBQUwNHy62/azfxc/x4uDX/rRunVrdOjQAfPmzUNAQACmTJmCBg0aICgoCK1atRIdT7F4ILqc2F7kxPYit6tXr2LAgAGIiopC1apVATwterVv3x5btmzh+dBvKBZViOh/xsEVubDYJRd3d3eEhoaiSpUqAIBFixZhzJgx2h9Zt2/fRseOHZGUlCQwpfJw6bz8Dh8+jGXLlunM8vLz8+NZBJLJzs7Gxo0bERISgtjYWNFxFIX9i9zKOvAFcPBLX6pUqYIzZ87AyckJhYWFMDY2xp49e9C1a1fR0Yikw/ZC9Pq6deuGnJwcbNiwQXum2vnz5+Ht7Q1LS0vs2bNHcEIqDyyqkJT4sljxcHBFHix2ycHAwACZmZmwtbUF8HTgPjY2Fo6OjgCA69evo2bNmjwXQs+4dF5umzdvhre3Nzw9PdGhQwcAQFRUFHbs2IGQkBB4eXkJTkjPO3PmDGbNmoXff/9ddBRFYf9C9HrUajWysrK0bcbCwgJxcXHaNkNE/x/bC9HrMzU1xZ9//olmzZrpXD9z5gw6duyIvLw8QcmoPBmKDkBUmr179+Lx48fazwsXLtQekAY8XUJ//vx5QemoNNbW1ujYsSMOHDggOoriqVQquLm5wc3NTafYRfpVfM4C5zDIITg4WHQEeokFCxZgyZIlmDx5svaaj48P/P39MW/ePBZVBNi7dy/2798PIyMjjBw5Eo6Ojjh37hymT5+OnTt3as8nIv1h/0L0+vbu3audsFdUVISDBw/i7NmzOs94eHiIiKZYVlZWrzxHFeBEFxHYXuTD9iI3Ozs7PHnypMT1wsJC1KxZU0Ai0gcWVUhKfFmUFwdXKhYWu4h0casVuaWnp6NHjx4lrnt4eGDGjBkCEilbYGAgRo0aBWtra9y5cwcBAQHw9/fHhAkT0K9fP5w9exYuLi6iYxIRvVLx/n/06NE6n1UqFVd36dnKlStFR6AXYHuRD9uL3JYuXYoJEyZg7dq1aNmyJYCnh9ZPnDgRy5YtE5yOyguLKkRUZhxckReLXfJRqVQlZhOVZXYRkZLZ2dnh4MGDcHJy0rl+4MAB2NnZCUqlXKtWrcLixYvh5+eH7du3o0+fPvjhhx+QkJDAAzcFYv9C9HqKiopER6BScKKLnNhe5MT2Irdhw4YhLy8Pbdq0gaHh06H2goICGBoaYvjw4Rg+fLj2Wa4menOwqEJS4suinDi4IicWu+Sk0WgwbNgwGBsbAwAePXqEMWPGwMzMDAB0tjgk/eHSebn5+vrCx8cHsbGxaN++PYCnZ6qEhIRg1apVgtMpT1paGvr06QMA8PT0hKGhIZYuXco+XzD2L0SkBJmZmViwYAHWrFkjOgqR9NhexOJKImXiQfUkJbVaje7du2tfFnfu3IkPP/xQ52Vxz549XHKqZ2ZmZkhMTIS9vT00Gg2MjY0RGRmpPUyYxGjcuDEGDx6sU+xq27YtwsLCOPAlkLe3d5me4xkf+rVhw4YyPcfZYOLs2LEDy5cvR3JyMgDAxcUFfn5+6Nmzp+BkysPDauXE/oXo9YwbNw5LliyBubk5ACA0NBQeHh7ad8ucnBx4eXlh165dImMqUmJiIiIjI2FkZKQ9Q/XWrVtYsGAB1q1bB0dHRyQmJoqOqShsL/JieyGSC4sqJCW+LMqJgytyYrGLiIjKg1qtxvz587UDK9OmTYOfnx9sbGx0nvPx8RERj0gazZs3f63nVSoVIiIi8M4775RTInqegYEBMjMzte8wlpaWiI2N1b7DXL9+HTVr1uSEPT2LiIhA7969UVBQAABwdHTE+vXr0bdvX7Ro0QKTJk1Ct27dBKdUHrYXObG9EMmHRRUiKjMOrsiJxS6ivw+Xzsvh9OnT2pUqrq6uaNGiheBEymRvb//K7fJUKhXS09P1lIhITmq1Gr6+vtrfyC+j0WiwaNEiJCUl8beanrzqtzIHicVo3bo1OnTogHnz5iEgIABTpkxBgwYNEBQUhFatWomOp1hsL3JieyGSD4sqRFRmHFyRE4tdcvL09CzTc+Hh4eWchIrj0nl5Xb16FQMGDEBUVBSqVq0K4Ok2E+3bt8eWLVu4pSER2L/IqPgg5KtwAox+cZBYTlWqVMGZM2fg5OSEwsJCGBsbY8+ePejatavoaIrG9iInthci+fCgepISXxbldOnSJdERqBS1a9fG+vXrtZ+rV6+OTZs26TyjUqlYVNGzKlWq6Hz+5Zdf0KNHD1hYWAhKREDJpfNLlizRWTq/Y8cOLp0XaOTIkXjy5AmSk5NRr149AMD58+fh7e2NkSNHYs+ePYITEonH/kU+Fy9eRLVq1cr8fFJSEmrWrFmOiYjkd//+fVhaWgJ4uuWUqakpC41EL8D2QiQfrlQhKRU/U+VFL4s8U4WIKgrOSpUDl87LzdTUFH/++SeaNWumc/3MmTPo2LEj8vLyBCVTJnd3d4SGhmoH8RctWoQxY8ZoVxHdvn0bHTt2RFJSksCUxP6F6OXUajW++OILVK5cGQCwdu1aDBo0SPvdlpeXh/Xr13PmvZ6p1Wps2LBB+3cYMGAAVq5cibffflvnOQ8PDxHxFIvtRU5sL0TyYVGFKgS+LMqBgytE/zt+j8mBS+flVrduXWzevBmtW7fWuX7y5El4eXnhwoULgpIpEw+rrRjYv8jhypUrZXqudu3a5ZyEivvggw9euYUxAERGRuohDT2jVqtf+YxKpWIfo2dsL3Jie5FP8+bNX+t5lUqFiIgIvPPOO+WUiPSN238RUZnt3bsXjx8/1n5euHCh9jwCACgoKMD58+cFpVMuFruIyo5L5+W2dOlSTJgwAWvXrkXLli0BPD20fuLEiVi2bJngdMpTfO4V52IRvdiLzh7UaDTa6yqVSrv9JOnPH3/8IToClaKoqEh0BCoF24uc2F7kExsbC19fX+3Zti+j0WiwaNEinfE0qvhYVCGiMuPgipxY7CJ6PXv37tUWIYuKinDw4EGcPXtW5xkunRdj2LBhyMvLQ5s2bWBo+PRnakFBAQwNDTF8+HAMHz5c+2x2draomEREJcTExJR6XaPRYMuWLVi9enWZBl6ofNy7dw8nTpxAfn4+Wrdu/Vpn4BApDdsLUdn4+flpV3S/yvLly8s5DekbiypERBUci11yioiI0PnMwXt5DB06VOfz6NGjdT5z6bw4K1euFB2BnqNSqUrMvC/LliBUvti/yKlJkyYlrh04cADTp09HSkoKvvrqK/j6+gpIRrGxsXB3d0dWVhaAp1vmhYWFwc3NTXAyZRs3bhyWLFmiLTaGhobCw8MDZmZmAICcnBx4eXlh165dImMqDtuLnNhe5HPx4sXXKjgmJSWhZs2a5ZiI9I1nqpCUir8s8hAuORgYGCArK0vbcVhYWCA+Ph4ODg4AuLe6KGq1GllZWdoZEsX3VuffRQzue0tEFZ1arUb37t1hbGwMANi5cyc+/PBD7Qv848ePsWfPHn6P6Rn7F/lFR0dj2rRpOHr0KEaOHImZM2eWeSYr/f3c3NyQm5uLZcuWwcTEBPPmzUNCQgJSU1NFR1M0ntslJ7YXObG9EMmHK1VISr169SpxjTOJxdNoNBg2bJh2cOXRo0cYM2aMzuAK6R9nEsuJ+94SUUVXfFXXoEGDSjwzZMgQfcWh/2L/Iq+0tDTMmDED27dvR9++fZGUlMRzuyRw5swZ7Nu3T3uocFBQEKytrXHv3j3tOWukf1xtLye2FzmxvcjpypUrZXqudu3a5ZyERGBRhaTEl0U5cXBFTix2ye3x48coKCjQ/j1ILC6dJyq74OBg0RHoJdi/yGXcuHEIDAxE586dcfr0aTRt2lR0JPqv7Oxs1KpVS/u5atWqMDMzw+3btzlITFQM2wtR2dnb25c6oVWj0Wivq1QqFBQU6Dsa6QGLKiQ1vizKhYMrcmKxS043b97EkCFDcODAARQVFaFVq1bYvHkznJycREdTtJ9++gmzZ8/WFlVGjx6NNm3aaGcSP378GHv37hUZkYjopdi/yGndunUwMTHBjRs3MHz48Bc+Fx0drcdU9ExSUpL2jAjg6YBXcnIy7t+/r73WuHFjEdGIpMP2QlQ2MTExpV7XaDTYsmULVq9erX3vpDcPiyokJb4sEpUdi11ymjZtGmJjYzF37lyYmJjgp59+wqhRoxAZGSk6mqJx6TxR2Xl6epbpufDw8HJOQs9j/yKnWbNmiY5AL9GlS5cSff6nn34KlUqlnVHMraX1b+bMmahcuTIAID8/HwsWLECVKlUAAHl5eSKjKRrbi5zYXuTTpEmTEtcOHDiA6dOnIyUlBV999RV8fX0FJCN94EH1JKXhw4dj9+7d8PHx0b4s1qhRgy+LgnFwhajs7OzsEBAQADc3NwBAamoqXFxc8ODBA+1WbaR/arUaWVlZ2kMeLSwsEBcXx0MeiUrh7e2t8/mXX35Bjx49YGFhoXOdxX39Yv9C9HouX75cpufq1KlTzknoeR988EGZzoHkGIB+sb3Iie1FftHR0Zg2bRqOHj2KkSNHYubMmdp3TnozsahCUuLLopw4uCInFrvkZGBggGvXrqF69eraa2ZmZkhMTIS9vb24YArHoop8nh2EWlYqlQoRERF45513yikRvUjx9kJisH+RX3x8PFJSUgAAdevW5TY5REREb6i0tDTMmDED27dvR9++fTF//nz+VlYIbv9FUvrPf/6js4zO2dkZxsbGyMzM5MuiQMWLJdu2bcOSJUvYYQj2bMnvMy8qdpH+GRgYlPjMuQzicem8XGJjY+Hr61um/YY1Gg0WLVqEx48f6yEZkbzYv8jp5MmTGDFiBJKSkrR/D5VKhQYNGiAwMBCtWrUSnFB54uPj0bBhQ6jV6jI9n5iYiHr16sHQkEMl+nDv3j2cOHEC+fn5aN26NapVqyY6kqKxvciN7UU+48aNQ2BgIDp37ozTp0+jadOmoiORHnGlCknJwMAAWVlZOp2EpaUl4uLi4ODgIDAZPY8zVuXEv4sc1Go1qlSporNMOycnB5aWljovKtnZ2SLiKRaXzsun+OqhV+F3nDj8314O7F/klJSUhDZt2sDFxQWTJ0+Gi4uL9vqKFStw/vx5HD9+HK6uroKTKktp75UvY2lpidjYWH7P6UFsbCzc3d21B6JbWFggLCxMu1sF6R/bi7zYXuSkVqthYmKC+vXrv/S56OhoPSUifWI5maSk0WhQt25dnZfF3NxcNGvWjC+LRFQhcBs8Of3xxx+iI1AxFy9efK2ZdklJSahZs2Y5JiKSG/sXOc2ePRsfffQRtm/frvMO07RpUwwYMACenp6YPXs2wsLCBKZUHo1Gg2+//Va7QvVV8vPzyzkRPTNt2jQ4ODhg+/btMDExwbx58zB+/HikpqaKjqZYbC/yYnuR06xZs0RHIIG4UoWktGHDhjI9N3To0HJOQi/DGaty4t+F6OW4dJ6obCIiInQ+DxgwACtXrsTbb7+tc93Dw0OfsYikVK1aNezevRstW7Ys9f6pU6fg7u6Omzdv6jmZspV1herzfvnlF9SoUaOcEtEzNjY22Ldvn/ZstZycHFhbW2tX3pH+sb3Ii+2FSD4sqhBRmXFwpWJgUYXoxbh0Xk5Xrlwp03O1a9cu5yT0vLLsqa5SqVBYWKiHNERyMzExQWpqKuzs7Eq9n5GRAWdnZzx69EjPyYjkVNr2nxYWFoiPj+eW30TFsL3ILz4+HikpKQCAunXronHjxoITUXnj9l9EVGa9evUqcW306NE6nzm4on/Fi11FRUU4ePAgzp49q3OdxS79srKyKtNML25jqF9cOi8ne3v7UtuLRqPRXlepVCgoKNB3NEUrKioSHYFKwf5FTnXq1MHJkydfWFQ5ceIE6tSpo+dURHJLSkrSTnQBnvb7ycnJuH//vvYaByaJnmJ7kdPJkycxYsQIJCUl4dm6BZVKhQYNGiAwMBCtWrUSnJDKC1eqkJT4skhUdpxJLCduYygnLp2XU1xcXKnXNRoNtmzZgtWrV8Pc3Bw3btzQczICgMePH6OgoABmZmaioxDYv8hq1qxZCAkJwb///W80bNhQ515CQgJ69OiBIUOGYO7cuYISEslFrVZDpVKhtCGpZ9f5DkP0FNuLnJKSktCmTRu4uLhg8uTJcHFx0V5fsWIFzp8/j+PHj8PV1VVwUioPLKqQlPiyKDcOrhBRRcWl8xXHgQMHMH36dKSkpGDKlCnw9fWFhYWF6FiKcvPmTQwZMgQHDhxAUVERWrVqhc2bN8PJyUl0NCLpPHr0CF26dMGJEyfw0UcfwcXFRTuL+MCBA2jdujUOHToEExMT0VGJpHD58uUyPccVXkRsL7Lq27cvCgoKsH379hITwzUaDTw9PVGpUiWEhYUJSkjliUUVIiozDq7IjcWuiiUzMxMLFizAmjVrREdRFLVajUOHDsHa2lp7rX379ggLC0OtWrW017h0Xpzo6GhMmzYNR48exciRIzFz5kydIhjpz/Dhw7F79274+PjAxMQEP/30E2rUqIHIyEjR0egl2L+Ik5+fjxUrViA0NFRnX/X+/ftj8uTJMDY2FpyQiIiI/i7VqlXD7t270bJly1Lvnzp1Cu7u7rh586aek5E+sKhCFRJfFsXg4IqcWOySV2JiIiIjI2FkZIS+ffuiatWquHXrFhYsWIB169bB0dERiYmJomMqCpfOyystLQ0zZszA9u3b0bdvX8yfPx+Ojo6iYymanZ0dAgIC4ObmBgBITU2Fi4sLHjx4wMFhwdi/EFFFFh8fj4YNG5ZpG2Pg6XdevXr1YGjIY4FJedhe5GViYoLU1NQXnqeWkZEBZ2dnPHr0SM/JSB9YVCFp8WVRPhxckROLXXKKiIhA7969tQdrOzo6Yv369ejbty9atGiBSZMmoVu3boJTKg+Xzstp3LhxCAwMROfOnbFo0SI0bdpUdCQCYGBggGvXrqF69eraa2ZmZkhMTIS9vb24YArH/oWIKjoDAwNkZWWhWrVqZXre0tISsbGxnGxBisT2Iq969eph4cKF+Pzzz0u9v23bNnzzzTc4f/68npORPrCoQlLiy6KcOLgiJxa75NS6dWt06NAB8+bNQ0BAAKZMmYIGDRogKCgIrVq1Eh2PSCpqtRomJiaoX7/+S5+Ljo7WUyICSn+Jt7S0RFxcHM8gEoj9i5ysrKxK7KdemuzsbD2kIZKbWq3GF198gcqVK5fp+R9++AFJSUkcJCZFYnuR16xZsxASEoJ///vfaNiwoc69hIQE9OjRA0OGDMHcuXMFJaTyxKIKSYkvi3Li4IqcWOySU5UqVXDmzBk4OTmhsLAQxsbG2LNnD7p27So6mmJx6by85syZU6bnZs2aVc5J6HlqtRpVqlTRGSjOycmBpaWlTjviILF+sX+R04YNG8r03NChQ8s5CZH8PvjggzIVIZ/3yy+/oEaNGuWUiEhebC/yevToEbp06YITJ07go48+gouLCzQaDZKTk3HgwAG0bt0ahw4dgomJieioVA5YVCEp8WVRThxckROLXXJSq9XIysrSHrBtYWGBuLg4zhgSiEvniV4PB4nlxP5FTkeOHEH79u1ZiCciIlKQ/Px8rFixAqGhoUhJSQEA1K1bF/3798fkyZO5e8gbjL/4SEr379+HpaUlgKeDYKampnxRlEBwcLDoCFQKjUaDunXr6hS7cnNz0axZMxa7BNu7dy+qVKkCACgqKsLBgwdx9uxZnWc8PDxERFMkjUaDb7/9tsxL5/Pz88s5EZUmPj5e54WkcePGghMpF4sl8mL/Ip/OnTsjMzNTW+wiIiKiN5+RkRGmTZuGadOmiY5CesaVKiQltVqNDRs2aF8WBwwYgJUrV+Ltt9/WeY4vi0ScSSyrsmwxpVKpUFhYqIc0BHDpvOxOnjyJESNGICkpCc9+nqpUKjRo0ACBgYHc/pPov9i/yKn4CiIiIiIienOxqEJS4ssiERGRciQlJaFNmzZwcXHB5MmT4eLior2+YsUKnD9/HsePH4erq6vgpMrCg7eJyk6tVuP69etl3mKSiIiIKjb+VlY2FlWIqMzYYRARUXno27cvCgoKsH379hL9jEajgaenJypVqoSwsDBBCZWJKyGJyk6tVqN79+6v3Ds9PDxcT4mIiIioPPG3srLxTBUiKrOVK1eKjkClYLFLTuPGjcOSJUtgbm4OAAgNDYWHhwfMzMwAADk5OfDy8sKuXbtExiSSQmRkJHbv3l3qd5lKpcKMGTPg7u4uIJmy8QVQTuxf5GVhYQFTU1PRMYiIiEgPHBwc0L59exgacnhdibhShaTEl0WisuPsCDkZGBjoHFhraWmJ2NhYODo6AgCuX7+OmjVrchtDIgAmJiZITU2FnZ1dqfczMjLg7OyMR48e6TkZvUxmZiYWLFiANWvWiI6iKOxf5MQzVYiIiJSl+G8yUhaW0khKP/30E2bPnq0tqowePRpt2rTRviw+fvwYe/fuFRmRSsHBFTFYLJFT8TkLnMNA9GJ16tTByZMnX1hUOXHiBOrUqaPnVAQAiYmJiIyMhJGREfr27YuqVavi1q1bWLBgAdatW6f9bUb6w/5FTmVZNUxERERvDv4GU7ZXnwZOJABfFuWVmJiINWvW4Oeff0ZOTg4A4NatW5g8eTIcHR0RGRkpNiCVkJmZifHjx4uOQUT0Qv3798eUKVNw9uzZEvcSEhIwdepU9OvXT0AyZYuIiECzZs3g4+ODMWPGoGXLloiMjISLiwuSk5OxY8cOJCYmio5JJIVXva8kJydj6tSpekpDRERE+sBJFcrFlSpEVGYRERHo3bs3CgoKAABLlizB+vXr0bdvX7Ro0QI7duxAt27dBKdUJs4kJqKK7Ouvv8aBAwfQtGlTfPTRR3BxcYFGo0FycjIOHDiA1q1bY8aMGaJjKs78+fPx5ZdfYt68eQgICMCUKVPg4+ODXbt2oVWrVqLjEUklMjIS1tbWOtcePHiALVu2IDAwEMePH4erqyuWLVsmKCERERH93YYNGwZjY+OXPhMeHq6nNKRPPFOFpFR8T2ILCwvExcVxr2jBWrdujQ4dOugMrjRo0ABBQUEcXBGoeLHL0dFRp9g1adIkFrsEUKvV+OKLL1C5cmUAwNq1azFo0CBUqVIFAJCXl4f169fze4zov/Lz87FixQqEhoYiJSUFAFC3bl30798fkydPfuXLCv39qlSpgjNnzsDJyQmFhYUwNjbGnj170LVrV9HRFI39i/yioqIQGBiIsLAwPHz4EJMnT8bIkSNRv3590dGIiIjob6JWq9G3b1+Ympq+9Lng4GA9JSJ9YlGFpMSXRTlxcEVOLHbJ6YMPPijTUmBumUdEsnrVJBcSg/2LnG7cuIGQkBAEBQXh7t27GDBgALy8vNCuXTvExcXB1dVVdEQiIiL6GxX/rUzKwqIKSYkvi3Li4IqcWOwiIqLyoFarsWHDBu2klgEDBmDlypV4++23dZ7z8PAQEY9IKqampujduzcGDRqEjz76CGr10+NLK1WqxKIKERHRG8jAwACZmZksqigUz1QhKf3xxx+iI9AL7N27Vzu4UlRUhIMHD5Y4WJiDK/p1//59WFpaAnjaqZuamrLQJYl79+7hxIkTyM/PR+vWrVGtWjXRkYikZGVlVabJFNnZ2XpIQ88bOnSozufRo0frfFapVFw5LAD7F/nUqVMHx44dQ+3atVGnTh1u9UVERPSGe9U6heTkZAQGBvI8tTcUiyokLb4syomDK3JisUs+sbGxcHd3R1ZWFoCnK7vCwsLg5uYmOBmRfFauXCk6ApWiqKhIdAQqBfsXOZ07d057lkqrVq1Qt25dDBo0CADKVDQmIiKiiiUyMhLW1tY61x48eIAtW7YgMDAQx48fh6urK4sqbyhu/0VS4ssiUdk9217iZVjs0j83Nzfk5uZi2bJlMDExwbx585CQkIDU1FTR0Yikc+TIEbRv3x6GhpzvQ/Qq7F/kl5ubi9DQUAQHB+P48ePo1KkTvLy80KtXL04UIyIiegM9m1gRFhaGhw8fYvLkyRg5ciRXrr7BWFQhKfFlkYgqOhsbG+zbtw/NmzcHAOTk5MDa2ho5OTna7dqI6CnuRyyncePGYcmSJTA3NwcAhIaGwsPDA2ZmZgCefq95eXlh165dImMqDvuXiuXZ1h+bNm1CdnY2njx5IjoSERER/Q1u3LiBkJAQBAUF4e7duxgwYAC8vLzQrl07nqemACyqkJT4signDq4QlZ1arUZWVpbOILGFhQXi4+Ph4OAgMBmRfEprLyRe8WKXpaUlYmNjted2Xb9+HTVr1uRKSD1j/1IxFRQUICIiAp6enqKjEBER0d/A1NQUvXv3xqBBg/DRRx9pdxGpVKkSiyoK8Oo9Y4gEyM7ORq1atbSfq1atCjMzM9y+fVtgKvrpp5+Ql5en/Tx69Ghcv35d+/nx48fYu3eviGiKNm7cOOTm5mo/h4aG4sGDB9rPOTk5cHd3FxFN8ZKSkhAfH6/9j0ajQXJyss41InqKZw7Ip/jcK87Fkgf7l4rnwoULmD59uugYRERE9DepU6cOjh07hiNHjiAlJUV0HNIzblxN0kpKStKeqQJA+7J4//597bXGjRuLiKZYHFyR008//YTZs2drVxCNHj0abdq00c4kZrFLnC5dupRoJ59++ilUKhU0Gg3PuiF6zrBhw2BsbPzSZ8LDw/WUhkhu7F8qnsePHyMtLU10DCIiIvqbnDt3TnuWSqtWrVC3bl0MGjQIACeMKQGLKiQtviwSlQ2LXXK6ePGi6AhEFYqFhQVMTU1FxyCSHvsXIiIiIjl06NABHTp0wOrVqxEaGorg4GAUFhZi3Lhx8PLyQq9evVCtWjXRMakcsKhCUuLLIhFVdHXq1BEdgahCWb16Nc9UkdDMmTNRuXJlAEB+fj4WLFiAKlWqAIDOlqCkP+xfiIiIiORibm6OUaNGYdSoUUhOTkZgYCD+8Y9/YNy4cXjy5InoeFQOWFQhKfFlUV4cXCF6tfj4eDRs2FB7UN2rJCYmol69ejA0ZLdMysTl8XJ6//33cf78ee3n9u3bIz09vcQzpD/sX4iIiIjk5uLigmXLlmHRokWIiIgQHYfKiUrDfWJIMnxZlNcHH3xQpoGvyMhIPaShZ9RqNb744gttsWvt2rUYNGiQTrFr/fr13C5PjwwMDJCVlVXmZb6WlpaIjY3VnoNDpDRqtRpZWVkvXKnybLbXsmXL9JyMSC7sX+RlZWX10t/JBQUFePDgAX+PERERKcS5c+fg4eHBQ+zfUByFJuk0a9bstV4W27Vrx5dFPfnjjz9ER6BScCaxfDQaDb799lttoetV8vPzyzkRkdwiIyNhbW2tc+3BgwfYsmULAgMDcfz4cbi6urKoIsC9e/dw4sQJ5Ofno3Xr1twTWjD2L/JauXKl6AhEREQkkcePHyMtLU10DConLKqQdPiyKDcOrsiHxS75FC90vUq7du14QDcpWqdOnbT/joqKQmBgIMLCwvDw4UNMnjwZQUFBqF+/vsCEyhQbGwt3d3dkZWUBACwsLBAWFgY3NzfByZSL/Yu8hg4dKjoCEREREekJt/8i6ZR1i6nn/fLLL6hRo0Y5JaJnOLgiLxa7iKgiu3HjBkJCQhAUFIS7d+9iwIAB8PLyQrt27RAXFwdXV1fRERXJzc0Nubm5WLZsGUxMTDBv3jwkJCQgNTVVdDQi6dy7d6/U62ZmZjAwMNBzGiIiIhItLi4OzZs359afbygWVYiozDi4IicWu4ioojM1NUXv3r0xaNAgfPTRR9pz1SpVqsSiikA2NjbYt28fmjdvDgDIycmBtbU1cnJyYGlpKTgdkVzUanWpE8MMDAzg4OCAqVOnYtSoUQKSERERkQgsqrzZuP0XEZXZmTNndAZXgoKCYG1tjXv37nFwRaBp06bBwcEB27dv1xa7xo8fz2IXEVUYderUwbFjx1C7dm3UqVOHW31JIjs7G7Vq1dJ+rlq1KszMzHD79m32+0TFREZGlno9JycHZ86cgZ+fHwwNDeHt7a3nZERERFQerKysXrrTTkFBgR7TkL6xqEJEZcbBFTmx2EVEFd25c+e0Z6m0atUKdevWxaBBgwDgtbcEpb9XUlKSdiUk8PTsu+TkZNy/f197rXHjxiKiEUnl+bOhiuvZsyfs7e3x/fffs6hCRET0hli5cqXoCCQQt/8iojJTq9U4dOgQrK2ttdfat2+PsLAwnWILB1f0S61WIysrC7a2ttprFhYWiI+Ph4ODg8BkRESvLzc3F6GhoQgODsbx48fRqVMneHl5oVevXjwvSs+ebWdU2uvCs+sqlYpbGhCVQVpaGpo1a/bCs1eIiIiIqOJgUYWIyoyDK3JisYuI3lTJyckIDAzEpk2bkJ2djSdPnoiOpCiXL18u03N16tQp5yREFV90dDR69uyJjIwM0VGIiIjob/CiiRJmZmYwMDDQcxrSNxZViKjMOLgiJxa7iOhNV1BQgIiICHh6eoqOQkT02p48eYIhQ4bgyZMn2LZtm+g4RERE9Dd4NhZTnIGBARwcHDB16lSMGjVKQDLSB56pQkRlxmKJnC5evCg6AhFRubpw4QKmT5/OoooexcfHo2HDhlCr1WV6PjExEfXq1YOhIV8vSJle9P109+5dJCYmQqVS4ejRo3pORUREROUlMjKy1Os5OTk4c+YM/Pz8YGhoyPPU3lBcqUJEZcLBFSIiEiUuLg7Nmzfnijs9MjAwQFZWVpnPsbG0tERsbCwcHR3LORmRnF40YGJpaYl69eph4MCBqFKlip5TERERkShBQUFYs2YNoqOjRUehcsCiChGVCQdX5MRiFxEpAYsq+qdWq/HFF1+gcuXKZXr+hx9+QFJSEvt9IiIiIiIAaWlpaNas2QvPXqGKjaNqRFQmGo0G3377bZkHV/Lz88s5EQFAs2bNXqvY1a5dOxa7iIjold5//32cP3++zM+3a9cOpqam5ZiISH7Hjx/Hzp07kZ+fjy5duqBbt26iIxEREZEgd+/e5SrVNxiLKkRUJhxckROLXUREVB7++OMP0RGIKpRt27ahX79+MDU1RaVKleDv74/Fixdj6tSpoqMRERGRnj158gRLly5FmzZtREehcsLtv4iIKrAPPvgAKpXqtf47v/zyC2rUqFFOiYiIXp+VldVLv8sKCgrw4MEDbv9FRNJq0aIFWrVqhbVr18LAwADfffcdli5diuzsbNHRiIiIqBx4enqWev3u3btITEyESqXC0aNH4eTkpOdkpA8sqhARERGRUBs2bCjTc0OHDi3nJERE/xtzc3PExsZqB07y8/NhZmaGa9euwdbWVnA6IiIi+rt5e3uXet3S0hL16tXDwIEDuf3XG4xFFSIiIiIiIqL/A7VajaysLJ0CioWFBeLi4niWHREREdEbhmeqEBEREZFQ9+7dK/W6mZkZDAwM9JyGiOh/ExAQAHNzc+3ngoIChISEwMbGRnvNx8dHRDQiIiIqB8ePH8fOnTuRn5+PLl26oFu3bqIjkZ5wpQoRERERCaVWq0s9U8XAwAAODg6YOnUqRo0aJSAZEVHZ2Nvbv/KcO5VKhfT0dD0lIiIiovK0bds29OvXD6ampqhUqRLu3buHxYsXY+rUqaKjkR6wqEJEREREQh0+fLjU6zk5OThz5gxWr16NFStWvHDfYiIiIiIiIn1q0aIFWrVqhbVr18LAwADfffcdli5diuzsbNHRSA9YVCEiIiIiqQUFBWHNmjWIjo4WHYWIiIiIiAjm5uaIjY2Fk5MTACA/Px9mZma4du2azhlr9GZSiw5ARERERPQynTp1woULF0THICJ6qYKCAixduhTNmzeHubk5zM3N0bx5cyxbtgxPnjwRHY+IiIj+Rnl5ebC0tNR+NjIygomJCXJzcwWmIn3hQfVEREREJLW7d++iSpUqomMQEb3Qw4cP8dFHH+Gvv/5C165d8f777wMAkpOTMW3aNERERGDfvn0wMTERnJSIiIj+LgEBATA3N9d+LigoQEhICGxsbLTXfHx8RESjcsbtv4iIiIhIWk+ePMGQIUPw5MkTbNu2TXQcIqJSzZo1CyEhIdi5cycaN26scy8uLg4eHh7w9vbG7NmzxQQkIiKiv5W9vT1UKtVLn1GpVEhPT9dTItInFlWIiIiISChPT89Sr9+9exeJiYlQqVQ4evSodr9iIiLZ1KtXDwsXLsTnn39e6v1ff/0V33zzDVJSUvScjIiIiIj+btz+i4iIiIiEetHWXnZ2dvj8888xcOBAbv9FRFK7fPkyWrdu/cL7bdu2xZUrV/SYiIiIiIjKC4sqRERERCRUcHCw6AhERP8nlpaWuHHjBuzs7Eq9n5WVBQsLCz2nIiIiovJUUFCAFStWIDQ0VLsatW7duvDy8sLEiRNRqVIlwQmpvHD7LyIiIiIS7vjx49i5cyfy8/PRpUsXdOvWTXQkIqIy69evHwoKCrB9+/ZS73/++ecwMDBAWFiYnpMRERFReXj48CE++ugj/PXXX+jatStcXFwAAMnJyThw4AA6dOiAffv2wcTERHBSKg8sqhARERGRUNu2bUO/fv1gamqKSpUq4d69e1i8eDGmTp0qOhoRUZkkJSWhTZs2aNCgAaZMmYL69etDo9EgOTkZK1asQFJSEo4fP44GDRqIjkpERER/g1mzZiEkJAQ7d+5E48aNde7FxcXBw8MD3t7emD17tpiAVK5YVCEiIiIioVq0aIFWrVph7dq1MDAwwHfffYelS5ciOztbdDQiojI7fvw4RowYgeTkZKhUKgCARqNB/fr1ERgYiHbt2glOSERERH+XevXqYeHChfj8889Lvf/rr7/im2++0W4LRm8WFlWIiIiISChzc3PExsbCyckJAJCfnw8zMzNcu3YNtra2gtMREb2e2NhYnX3VmzZtKjYQERER/e1MTEyQmpr6wvPUMjIy4OzsjEePHuk5GekDD6onIiIiIqHy8vJgaWmp/WxkZAQTExPk5uayqEJEFca9e/dw4sQJ5Ofno3PnzqhWrZroSERERFROLC0tcePGjRcWVbKysmBhYaHnVKQvLKoQERERkXABAQEwNzfXfi4oKEBISAhsbGy013x8fEREIyJ6pdjYWLi7uyMrKwsAYGFhgbCwMLi5uQlORkREROWhc+fOWLhwIbZv317q/UWLFqFz5856TkX6wu2/iIiIiEgoe3t77fkDL6JSqZCenq6nREREr8fNzQ25ublYtmwZTExMMG/ePCQkJCA1NVV0NCIiIioHSUlJaNOmDRo0aIApU6agfv360Gg0SE5OxooVK5CUlITjx4+jQYMGoqNSOWBRhYiIiIiIiOj/wMbGBvv27UPz5s0BADk5ObC2tkZOTo7O9oZERET05jh+/DhGjBiB5ORk7SQxjUaD+vXrIzAwEO3atROckMoLiypERERERERE/wdqtRpZWVk650BZWFggPj4eDg4OApMRERFReYuNjUVKSgoAoG7dumjatKnYQFTueKYKEREREQlXUFCAFStWIDQ0VOeFxMvLCxMnTkSlSpUEJyQiermkpCTtmSoAtFuA3L9/X3utcePGIqIRERFRObh37x5OnDiB/Px8dO7cGdWqVRMdifSEK1WIiIiISKiHDx/io48+wl9//YWuXbvCxcUFAJCcnIwDBw6gQ4cO2LdvH/5fe3cXYmW1uAH82XuM5oMZzRQZsDL7ULHMhKypCLGLAbEIhIrCTALrwhC6SCQmhKGYIvoACSKEUPBCEbrwJkkiIjIK2mrOYCaDBTUIyuAomOnsc/GnfY7HkfP+T828k+f3u9p7vWu/+5m5mj3PXms1NzeXnBRgbNVqNZVKJWN9vP5jvFKp5OLFiyWkAwD+arVaLStWrGh8oaK9vT07d+5Md3d3ycmYCFaqAABQqr6+vvz888/57rvvLvsW94EDB/Loo4+mr68vmzdvLicgwH8wODhYdgQAYAJt3LgxN998c3bv3p3m5ub09vZm/fr1OXr0aNnRmABWqgAAUKp58+bl9ddfz6pVq8a8vmvXrrzyyiuNbcEAAADKNGPGjOzduzdLlixJkgwPD2f69OkZHh5OR0dHyekYb9WyAwAA8L/t+PHjWbp06RWv33ffffnpp58mMBFAcQcPHszo6Gjh+YcPH86FCxfGMREAMN5OnTqV2bNnN55PmzYtbW1tOXnyZImpmCi2/wIAoFQdHR05ceJEbrjhhjGvDw0Npb29fYJTARRz9913Z2hoqPDhtF1dXanVapk7d+44JwMAxlN/f3/jTJUkqdfrGRgYyMjISGPs37c35upg+y8AAEr1xBNP5MKFC9m9e/eY11etWpWmpqbs3LlzgpMB/GfVajXr1q1La2trofnvv/9++vv7lSoA8DdWrVZTqVQy1r/W/xivVCq5ePFiCekYb0oVAABK1d/fn3vvvTcLFy7MSy+9lPnz5ze+5fXOO++kv78/+/fvz8KFC8uOCnCZZcuWpVKp/L9es2PHjnR2do5TIgBgvB0/frzQvJtuummck1AGpQoAAKXbv39/nnvuuQwMDDT+OVmv1zN//vxs3bo1XV1dJScEAAAApQoAAJNIrVbLDz/8kCS5/fbbs3jx4nIDAQAA/IuDBw/mjjvuSLVaLTT/8OHDmTdvXqZMcbz51UKpAgBA6U6fPp2vv/4658+fz9KlSwsf+AwAADCRmpqaMjQ0VPgzS0dHR2q1mvPUriLqMQAASlWr1bJixYoMDQ0lSdrb27Nz5850d3eXnAwAAOBS9Xo9PT09aW1tLTT//Pnz45yIiWalCgAAperu7s6ZM2fy1ltvpbm5Ob29vTl06FCOHj1adjQAAIBLLFu2rHEOZFE7duxIZ2fnOCVioilVAAAo1YwZM7J3794sWbIkSTI8PJzp06dneHg4HR0dJacDAACAfyp2mg4AAIyTU6dOZfbs2Y3n06ZNS1tbW06ePFliKgAAALicM1UAAChdf39/40yV5P/2KR4YGMjIyEhjbNGiRWVEAwAAgAbbfwEAUKpqtZpKpZKx/iz9Y7xSqeTixYslpAMAAIB/slIFAIBSDQ4Olh0BAAAACrFSBQAAAAAAoAAH1QMAUJqDBw9mdHS08PzDhw/nwoUL45gIAAAArsxKFQAAStPU1JShoaHMnDmz0PyOjo7UarXMnTt3nJMBAADA5ZypAgBAaer1enp6etLa2lpo/vnz58c5EQAAAFyZUgUAgNI89NBDOXLkSOH5XV1daWlpGcdEAAAAcGW2/wIAAAAAACjAQfUAAAAAAAAFKFUAAAAAAAAKUKoAAAAAAAAUoFQBAAAAAAAoQKkCAAAAAABQgFIFAAC4aj377LN57LHHyo4BAABcJZQqAAAAAAAABShVAAAAAAAAClCqAAAAk9ro6GjefPPN3Hrrrbn22mtz44035rXXXkuSHDp0KMuXL09LS0uuv/76rFu3LmfOnLnivebMmZN33333krHFixdn8+bNjeeVSiUffPBBVq5cmdbW1ixYsCBfffVVfvzxxyxbtixtbW25//77c+zYscZrNm/enMWLF2f79u2ZM2dOpk6dmieffDIjIyN/6e8CAAAol1IFAACY1DZt2pS+vr709PSkv78/O3bsyKxZs3L27Nl0d3fnuuuuyzfffJNdu3bl008/zfr16//0e/b29uaZZ55JrVbL/Pnz89RTT+X555/Ppk2b8u2336Zer1/2PseOHcvHH3+cPXv2ZM+ePfn888/T19f3p7MAAACTx5SyAwAAAFzJyMhI3nvvvWzZsiVr1qxJktxyyy158MEH8+GHH+bcuXPZtm1b2trakiRbtmzJI488kjfeeCOzZs36r9937dq1efzxx5MkGzduTFdXV3p6etLd3Z0k2bBhQ9auXXvJa0ZHR/PRRx+lvb09SbJ69ers27evsaoGAAD4+7NSBQAAmLQGBgby22+/5eGHHx7z2l133dUoVJLkgQceyOjoaI4cOfKn3nfRokWNx3+UM3feeeclY+fOncvp06cbY3PmzGkUKknS2dmZEydO/KkcAADA5KJUAQAAJq2Wlpa/9H7VajX1ev2Ssd9///2yeddcc03jcaVSueLY6OjomK/5Y86/XgcAAP7+lCoAAMCkddttt6WlpSX79u277NqCBQty4MCBnD17tjH25ZdfplqtZt68eWPeb+bMmfn1118bz0+fPp3BwcG/PjgAAHBVUqoAAACTVnNzczZu3JiXX34527Zty7Fjx7J///5s3bo1Tz/9dJqbm7NmzZp8//33+eyzz/Liiy9m9erVVzxPZfny5dm+fXu++OKLHDp0KGvWrElTU9ME/1QAAMDflYPqAQCASa2npydTpkzJq6++ml9++SWdnZ154YUX0tramk8++SQbNmzIPffck9bW1qxatSpvv/32Fe+1adOmDA4OZuXKlZk6dWp6e3utVAEAAAqr1P99Q2EAAAAAAAAuY/svAAAAAACAApQqAAAAAAAABShVAAAAAAAAClCqAAAAAAAAFKBUAQAAAAAAKECpAgAAAAAAUIBSBQAAAAAAoAClCgAAAAAAQAFKFQAAAAAAgAKUKgAAAAAAAAUoVQAAAAAAAAr4BwRU7KJhCLc+AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "names, importances = pipe.columns.importances()\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(20, 10))\n",
    "\n",
    "ax.bar(names, importances)\n",
    "\n",
    "ax.set_title(\"column importances\")\n",
    "ax.set_xlabel(\"column\")\n",
    "ax.set_ylabel(\"importance\")\n",
    "ax.tick_params(axis=\"x\", rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most important feature looks as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "```sql\n",
       "DROP TABLE IF EXISTS \"FEATURE_1_29\";\n",
       "\n",
       "CREATE TABLE \"FEATURE_1_29\" AS\n",
       "SELECT Q1( t2.\"balance\" ) AS \"feature_1_29\",\n",
       "       t1.rowid AS rownum\n",
       "FROM \"POPULATION__STAGING_TABLE_1\" t1\n",
       "INNER JOIN \"TRANS__STAGING_TABLE_4\" t2\n",
       "ON t1.\"account_id\" = t2.\"account_id\"\n",
       "WHERE t2.\"date\" <= t1.\"date_loan\"\n",
       "GROUP BY t1.rowid;\n",
       "```"
      ],
      "text/plain": [
       "'DROP TABLE IF EXISTS \"FEATURE_1_29\";\\n\\nCREATE TABLE \"FEATURE_1_29\" AS\\nSELECT Q1( t2.\"balance\" ) AS \"feature_1_29\",\\n       t1.rowid AS rownum\\nFROM \"POPULATION__STAGING_TABLE_1\" t1\\nINNER JOIN \"TRANS__STAGING_TABLE_4\" t2\\nON t1.\"account_id\" = t2.\"account_id\"\\nWHERE t2.\"date\" <= t1.\"date_loan\"\\nGROUP BY t1.rowid;'"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipe.features.to_sql()[pipe.features.sort(by=\"importances\")[0].name]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.5 Productionization\n",
    "\n",
    "It is possible to productionize the pipeline by transpiling the features into production-ready SQL code. Please also refer to getML's `sqlite3` and `spark` modules."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creates a folder named loans_pipeline containing\n",
    "# the SQL code.\n",
    "pipe.features.to_sql().save(\"loans_pipeline\", remove=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creates a folder named baseball_pipeline_spark containing\n",
    "# the SQL code.\n",
    "pipe.features.to_sql(dialect=getml.pipeline.dialect.spark_sql).save(\"loans_pipeline_spark\", remove=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By applying getML to the PKDD'99 Financial dataset, we were able to show the power and relevance of Relational Learning on a real-world data set. Within a training time below 1 minute, we outperformed almost all approaches based on manually generated features. This makes getML the prime choice when dealing with complex relational data schemes. This result holds independent of the problem domain since no expertise in the financial sector was used in this analysis.\n",
    "\n",
    "The present analysis could be improved in two directions. By performing an extensive hyperparameter optimization, the out of sample AUC could be further improved. On the other hand, the hyperparameters could be tuned to produce less complex features that result in worse performance (in terms of AUC) but are better interpretable by humans."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " ## References\n",
    "\n",
    "Schulte, Oliver, et al. \"A hierarchy of independence assumptions for multi-relational Bayes net classifiers.\" 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). IEEE, 2013."
   ]
  }
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