04 Dataset env_waspac.ipynb

{
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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "from utils import *\n",
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "import plotly.graph_objects as go"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Siedlungsabfälle nach Abfallbewirtschaftungsmaßnahmen (env_wasmun)\n",
    "\n",
    "[Data Explorere](https://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=env_waspac&lang=de)\n",
    "\n",
    "[Plastikmüll und Recycling in der EU: Zahlen und Fakten](https://www.europarl.europa.eu/news/de/headlines/society/20181212STO21610/plastikmull-und-recycling-in-der-eu-zahlen-und-fakten)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Read in data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "file_packaging_waste = \"data/env_waspac.xls\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "codes = get_header_codes_from_excel(file_packaging_waste)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Category:  WASTE\n",
      "---------\n",
      "W15010401_IBA: Aluminium from incineration bottom ash (IBA)\n",
      "W150107: Glass packaging\n",
      "W150103: Wooden packaging\n",
      "W150104: Metallic packaging\n",
      "W150101: Paper and cardboard packaging\n",
      "W150102: Plastic packaging\n",
      "W15010402: Steel packaging\n",
      "W150199: Other packaging\n",
      "W15010401: Aluminium packaging\n",
      "W15010402_IBA: Ferrous metal from incineration bottom ash (IBA)\n",
      "W1501: Packaging\n",
      "\n",
      "Category:  WST_OPER\n",
      "---------\n",
      "GEN: Waste generated\n",
      "RCV: Recovery\n",
      "RCY_NEU: Recycling outside the EU\n",
      "RCY: Recycling\n",
      "RCV_OTH: Recovery - other\n",
      "RCY_EU_FOR: Recycling in other Member States of the EU\n",
      "RCY_NAT: Recycling in the Member State \n",
      "RPR: Repair\n",
      "RCV_E_PAC: Recovery - energy recovery from packaging waste\n",
      "\n",
      "Category:  UNIT\n",
      "---------\n",
      "T: Tonne\n",
      "PC: Percentage\n",
      "KG_HAB: Kilograms per capita\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print_codes(file_packaging_waste)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "df = get_data_from_excel(file_packaging_waste)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "df.to_parquet(\"data/env_waspac_combined.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "df_packaging_waste = pd.read_parquet(\"data/env_waspac_combined.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>value</th>\n",
       "      <th>waste</th>\n",
       "      <th>wst_oper</th>\n",
       "      <th>unit</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>geo</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>EU27_2020</th>\n",
       "      <td>2009</td>\n",
       "      <td>149.89</td>\n",
       "      <td>W1501</td>\n",
       "      <td>GEN</td>\n",
       "      <td>KG_HAB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EU28</th>\n",
       "      <td>2009</td>\n",
       "      <td>152.78</td>\n",
       "      <td>W1501</td>\n",
       "      <td>GEN</td>\n",
       "      <td>KG_HAB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BE</th>\n",
       "      <td>2009</td>\n",
       "      <td>152.11</td>\n",
       "      <td>W1501</td>\n",
       "      <td>GEN</td>\n",
       "      <td>KG_HAB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BG</th>\n",
       "      <td>2009</td>\n",
       "      <td>40.82</td>\n",
       "      <td>W1501</td>\n",
       "      <td>GEN</td>\n",
       "      <td>KG_HAB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZ</th>\n",
       "      <td>2009</td>\n",
       "      <td>85.63</td>\n",
       "      <td>W1501</td>\n",
       "      <td>GEN</td>\n",
       "      <td>KG_HAB</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>SE</th>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>W150199</td>\n",
       "      <td>RPR</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IS</th>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>W150199</td>\n",
       "      <td>RPR</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LI</th>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>W150199</td>\n",
       "      <td>RPR</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NO</th>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>W150199</td>\n",
       "      <td>RPR</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UK</th>\n",
       "      <td>2018</td>\n",
       "      <td>NaN</td>\n",
       "      <td>W150199</td>\n",
       "      <td>RPR</td>\n",
       "      <td>PC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>98010 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           year   value    waste wst_oper    unit\n",
       "geo                                              \n",
       "EU27_2020  2009  149.89    W1501      GEN  KG_HAB\n",
       "EU28       2009  152.78    W1501      GEN  KG_HAB\n",
       "BE         2009  152.11    W1501      GEN  KG_HAB\n",
       "BG         2009   40.82    W1501      GEN  KG_HAB\n",
       "CZ         2009   85.63    W1501      GEN  KG_HAB\n",
       "...         ...     ...      ...      ...     ...\n",
       "SE         2018     NaN  W150199      RPR      PC\n",
       "IS         2018     NaN  W150199      RPR      PC\n",
       "LI         2018     NaN  W150199      RPR      PC\n",
       "NO         2018     NaN  W150199      RPR      PC\n",
       "UK         2018     NaN  W150199      RPR      PC\n",
       "\n",
       "[98010 rows x 5 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_packaging_waste"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018])"
      ]
     },
     "execution_count": 9,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_packaging_waste.year.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>waste</th>\n",
       "      <th>wst_oper</th>\n",
       "      <th>unit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>98010</td>\n",
       "      <td>98010</td>\n",
       "      <td>98010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>11</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>W1501</td>\n",
       "      <td>GEN</td>\n",
       "      <td>KG_HAB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>8910</td>\n",
       "      <td>10890</td>\n",
       "      <td>32670</td>\n",
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      "text/plain": [
       "        waste wst_oper    unit\n",
       "count   98010    98010   98010\n",
       "unique     11        9       3\n",
       "top     W1501      GEN  KG_HAB\n",
       "freq     8910    10890   32670"
      ]
     },
     "execution_count": 10,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_packaging_waste.describe(include=[\"category\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Packaging waste 2018"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Category:  WASTE\n",
      "---------\n",
      "W15010401_IBA: Aluminium from incineration bottom ash (IBA)\n",
      "W150107: Glass packaging\n",
      "W150103: Wooden packaging\n",
      "W150104: Metallic packaging\n",
      "W150101: Paper and cardboard packaging\n",
      "W150102: Plastic packaging\n",
      "W15010402: Steel packaging\n",
      "W150199: Other packaging\n",
      "W15010401: Aluminium packaging\n",
      "W15010402_IBA: Ferrous metal from incineration bottom ash (IBA)\n",
      "W1501: Packaging\n",
      "\n",
      "Category:  WST_OPER\n",
      "---------\n",
      "GEN: Waste generated\n",
      "RCV: Recovery\n",
      "RCY_NEU: Recycling outside the EU\n",
      "RCY: Recycling\n",
      "RCV_OTH: Recovery - other\n",
      "RCY_EU_FOR: Recycling in other Member States of the EU\n",
      "RCY_NAT: Recycling in the Member State \n",
      "RPR: Repair\n",
      "RCV_E_PAC: Recovery - energy recovery from packaging waste\n",
      "\n",
      "Category:  UNIT\n",
      "---------\n",
      "T: Tonne\n",
      "PC: Percentage\n",
      "KG_HAB: Kilograms per capita\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print_codes(file_packaging_waste)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Question 1:\n",
    "\n",
    "Weniger als ein Drittel der Kunststoffabfälle in Europa wird recycelt. Unsere Infografik enthält interessante Zahlen und Fakten zum Thema Plastikmüll und Recycling in der EU.\n",
    "\n",
    "Die Kunststoffproduktion ist in nur wenigen Jahrzehnten exponentiell gestiegen - weltweit von 1,5 Millionen Tonnen im Jahr 1950 auf 322 Millionen Tonnen im Jahr 2015. Damit ging auch ein Anstieg der Menge anfallenden Plastikmülls einher."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Plastic packaging waste generation for EU28 over the past 10 years'}, xlabel='year', ylabel='waste generation [T]'>"
      ]
     },
     "execution_count": 13,
     "metadata": {
     },
     "output_type": "execute_result"
    },
    {
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",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "image/png": {
       "height": 440,
       "width": 726
      },
      "needs_background": "light"
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_packaging_waste \\\n",
    "    .query(\"geo == 'EU28' and unit == 'T' and wst_oper == 'GEN' and waste == 'W150102'\") \\\n",
    "    .plot(\n",
    "        x=\"year\",\n",
    "        y=\"value\",\n",
    "        ylabel=\"waste generation [T]\",\n",
    "        title=\"Plastic packaging waste generation for EU28 over the past 10 years\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Plastic packaging waste generation for EU28 over the past 10 years'}, xlabel='year', ylabel='waste generation [KG/person]'>"
      ]
     },
     "execution_count": 14,
     "metadata": {
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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6MB8vr7fzuc654iqOAwAAAAAA1BIvTlqse96fG10+sm973XZ8X5lZiFEBQO0SVKJ5mqTjzKyvpDxJp0v6yjm3OaZON0nLkmnEzHaRtMI5tz6uPEXSbZLaSvomMsGfP/Hfq5KOkvSkpPNJMgMAAAAAgIiPZq3QNa/OiC7vuVNLPXD6QKWmkGQGgIoIKtF8j6TPJE2PKftX5B9/fOR9JH2UZDtHSbrTzL6SNF/SGkntJB0gbzLA5ZL+FFP///xtVkv6XdKNCb6NnOCcm5BkXAAAAAAAoJaZOD9bFz0/RcX+DE59OjTVf0fsrqz01HADA4BaKJBEs3PuSzM7Rl6S10l6zjn3XkyVveUlel9LsqmPJXWXtK+kQZKaS8qR9LOkZyQ97JyLHSt6R/9va0k3lrHfCUnGBQAAAAAAapE5yzfovDGTtKXQ++Fzl5YNNXrUEDXJSg85MgConYLq0Szn3PuS3i9l3ZfyEsPJtjFT0kUVqD8s2TYBAAAAAEDdsjg7VyOenKiNeYWSpNaNM/XMeUPVtklWyJEBQO0VyOR8ZlZkZs8FsS8AAAAAAICqsmbTFp3z1ESt3LhFktQ4M02jzx2irq0ahRwZANRugSSaJW2UtCigfQEAAAAAAARu05ZCnTt6kn5bnSNJykhN0X9H7K6+HZuFHBkA1H5BJZqnSuoT0L4AAAAAAAAClV9YrL88M1kzlqyXJKWY9PDwgdpr51YhRwYAdUNQiea7JR1lZocGtD8AAAAAAIBAFBc7XfnSdH01b3W07PYT+umIvh1CjAoA6pagJgNsK28iwPfM7HVJkyQtl+TiKzrnxgbUJgAAAAAAQJk25BXo6pdm6P2flkfLrjh0F525R5cQowKAuieoRPNoeUllk3SSf5O2TjSbv0yiGQAAAAAAVLmZv6/XBc9N0aLs3GjZiL266uKDuocYFQDUTUElms8NaD8AAAAAAABJcc7p2e8X6ba3Zim/qDhaPnLvbrrhmD4ysxCjA4C6KZBEs3NuTBD7AQAAAAAASMamLYW69tUf9db0pdGyxplpuvvk/jq6P2MyA0BVCapHMwAAAAAAQKhmL9ugC5+bot9W50TL+nRoqsfPGqxurRuFGBkA1H2BJprNrI2kkyX1ltTIOffHmPIdJf3onNscZJsAAAAAAKB+c87pxR8W68Y3ftKWwpKhMs7co4tuPKaPstJTQ4wOAOqHwBLNZnaepIclZalk4r8/+qvbSfpW0vmSngyqTQAAAAAAUL/l5hfq+tdn6tUpv0fLGmak6o4T++mEQR1DjAwA6peUIHZiZodK+o+knyWdKOmJ2PXOuZmSfpJ0QhDtAQAAAAAA/LJio45/9Outksy7tGusNy/alyQzAFSzoHo0/13SMkkHOOc2mNmgBHVmSNoroPYAAAAAAEA99uqUJfrHazO1uaAoWnbqbp106/F91SCDoTIAoLoFlWjeXdJ459yGMuoskdQ+oPYAAAAAAEA9lFdQpJvf/EnjJy2OlmWlp+jW4/vqtN07hxgZANRvQSWaMyTlbKdOc0lF26kDAAAAAACQ0G+rNumC56ZozvKN0bKd2jTSE2ftpp7tm4QYGQAgqETzAkm7bafOHpLmBtQeAAAAAACoR96avlTXvDJDOfklfdiOH7iD7jixnxplBpXeAABUVlBX4jckXW1mpzrnXopfaWbnSuov6R8BtQcAAAAAAOqBLYVFuv3t2Xrmu4XRsoy0FN187K4aPrSzzCzE6AAAEUElmu+RdIakcWZ2iqRmkmRmF0naT9JJkn6R9EhA7QEAAAAAgDpu0ZpcXfD8ZM38vWRKqG6tGurRMwerb8dmIUYGAIgXSKLZObfWzA6QNFbSqTGrHvb/finpTOfc9sZxBgAAAAAA0Pszl+uql6drY15htOyofu1118n91TQrPcTIAACJBDaIkXNukaRhZtZf0l6SWklaL+k759zkoNoBAAAAAAB1V35hse56b46e+np+tCw91XT90X00Yq+uDJUBADVU4KPlO+dmSJoR9H4BAAAAAEDdtmRtri56fqqmLV4XLevUooEeO3OwBnRuHlpcAIDtCzzRbGbpknrLG6d5vaTZzrmCoNsBAAAAAAB1xyezV+iKF6dr/eaSFMKhfdrpvlMGqFlDhsoAgJousESzmbWSdJekMyVlxazKM7PnJV3rnFsdVHsAAAAAAKD2Kygq1n0fztW/P/8tWpaWYrrmyF46b98dGSoDAGqJQBLNZtZO0teSdpLXi3mipOWS2ksaKOk8SQea2T7OuRVBtAkAAAAAAGq35evzdPG4KZq0YG20rEOzLD165mDt1rVFiJEBACoqqB7Nd8hLMj8o6Wbn3IbICjNrKukWSZdK+qekPwbUJgAAAAAAqKW++HmVLnthmrJz8qNlw3q20f2nDVTLRhkhRgYAqIygEs3HSPrSOXdF/Ao/6Xy5me0u6diA2gMAAAAAALVQUbHTgx//rEc/myfnvLIUk648rKf+esDOSklhqAwAqI2CSjQ3kfTVdup8KWlwQO0BAAAAAIBaZuXGPF06bpq+/W1NtKxtk0w9MnyQ9tipVYiRAQCSFVSieY6kDtup00HS3IDaAwAAAAAAtcg3v67WJeOmafWmLdGyfbu31oNnDFTrxpkhRgYACEJQieaHJD1uZg8652bErzSzgZJOk/TXgNoDAAAAAAC1QHGx06OfzdODH/+sYn+oDDPp0oN76OKDeiiVoTIAoE4IKtE8X9JHkiaa2VhJX0haIamdpAMknS3pPUkLzGz/2A2dc18EFAMAAAAAAKhB1mzaostemKYvf1kdLWvdOEMPnTFI+3RvHWJkAICgBZVoniDJSTJJf5R0Xsy6yFeTx/m3eKkBxQAAAAAAAGqIifOzdfG4KVqxoWSojD12bKlHhg9S26ZZIUYGAKgKQSWab5WXaAYAAAAAAPVYcbHTv7/4Tfd9OFdFxSWpggsP3FmXH7KL0lJTQowOAFBVAkk0O+duDmI/AAAAAACg9lqbk68rX5quT+esjJa1aJiuB04fqGE924YYGQCgqlU60Wxml0t6xTm3KMB4AAAAAABALTRl0Vpd9NwULV2fFy3brWsLPTJ8kHZo3iDEyAAA1SGZHs3/knSfmU2X9Kqk151zM4MJCwAAAAAA1AbOOT351Xzd9d4cFcYMlXH+/jvpqsN7Kp2hMgCgXkgm0TxU0kmSTpA3RvMtZvarSpLO3yUfHgAAAAAAqKnWby7Q1S9P1wc/rYiWNWuQrn+dOkCH9GkXYmQAgOpW6USzc+4HST9Ius7Meko6WV7S+WpJV5nZckmv+bcJzrmi5MMFAAAAAAA1wY9L1uuC5ydrcfbmaNmATs306JmD1bllwxAjAwCEIZDfrzjn5jrn7nDODZXURdJlkn6W9GdJH0paaWZjzOx4M8sKok0AAAAAAFD9nHMa++0CnfzEN1slmUfu3U0v/WVvkswAUE8lM3RGQs65JZIekfSImbWSdJykEyWdKukPkjab2QfOuZODbhsAAAAAAFSdjXkFuubVH/XOjGXRsiaZabrnlP46sl+HECMDAIQt8ERzLOfcGklPS3razBpJOkpe0vmoqmwXAAAAAAAEa9bSDbrw+SmavzonWtanQ1M9ftZgdWvdKMTIAAA1QZUmmmM553IkvSTpJTNLr652AQAAAABA5TnnNH7SYt385k/aUlgcLT9rjy664Zg+ykpPDTE6AEBNEXii2cy6SOqWYNVi59x8SXLOFQTdLgAAAAAACFbOlkJd//pMvTb192hZw4xU3XlSPx0/sGOIkQEAappKJ5rNLE3S15I2STrUORf5WvNcSTcm2OQ3M+vtnCusbJsAAAAAAKB6/Lxioy54bormrdwULevZrokeO2uwurdtHGJkAICaKJkezadIGiLplJgkc4RJei5muZmko+WNz/xSEm0CAAAAAIAq9vLkJbrh9ZnaXFAULTtt90665bi+apDBUBkAgG0lk2g+TtJySa8lWOecc2dHFszMJC2SdJJINAMAAAAAUCNtzi/STW/O1Is/LImWZaWn6PYT+umU3TqFGBkAoKZLJtG8m6TPnXNuexWdc87MPpO0ZxLtAQAAAACAKvLrqk268LkpmrN8Y7Rs5zaN9PhZu6ln+yYhRgYAqA2SSTTvIOn1BOXr5fVejrdcUock2gMAAAAAAFXgjWm/67pXf1ROfslQGScO6qjbT+irRpnJpA4AAPVFMq8W6ZLix2aWc+5BSQ8mqF/kbwMAAAAAAGqAvIIi3fb2LD33fUl/sYy0FN163K46fUhneSNhAgCwfckkmrMlda5A/S7+NgAAAAAAIGQL1+Toguem6KelG6Jl3Vo11GNnDdauOzQLMTIAQG2UTKJ5uqSDzCzNOVdYVkUzS5N0oKQZSbQHAAAAAAAC8N6Py3T1yzO0cUvJx/mj+3fQXSf1U5MsfowMAKi4ZBLN70g6XNKVku7eTt0rJLWT9FYS7QEAAAAAgCTkFxbrzvdm6+mvF0TLMlJTdMMxvfWHPbsyVAYAoNKSSTQ/Jenvkm43s0aS7nXObYytYGaNJV0l6TpJS/1tAAAAAABANVucnauLxk3V9MXromWdWzbQY2cOVv9OzUOLCwBQN1Q60eycyzWz0yW9J+kfkq4ws8mSfver7CBpd0kNJOVIOtU5tznJeAEAAAAAQAV9NGuFrnxxmjbklQyVcVifdrr31AFq1oChMgAAyUumR7Occ9+Y2d6SHpE0TNJ+CapNkHSxc+6nZNoCAAAAAAAVU1BUrPs+mKt/f/FbtCwtxXTNkb103r47MlQGACAwSSWaJclPIB9kZjtJ2kdSe3/VcklfO+d+K3VjAAAAAABQJZat36yLnp+qyQvXRst2aJalR88arMFdWoQYGQCgLqp0otnMGjrnciPLfkK5zKSymZ3qnHupsm0CAAAAAIDtmzB3pS5/YZrW5hZEyw7s2Ub3nzZQLRplhBgZAKCuSkli21fMLLW8lc3sOEnPJtEeAAAAAAAoQ6E/VMbIpydFk8ypKaa/H9FLT54zhCQzAKDKJDN0xuGSnpJ0zvYqmtlhkl6UVJREewAAAAAAoBQrN+Tp4nFT9f387GhZu6aZemT4YA3dsWWIkQEA6oNkEs3vS/qDma1wzl1dWiUzGybpNX/x1CTaAwAAAAAACXw9b7UuHT9VqzflR8v269FaD5w+UK0bZ4YYGQCgvkgm0XyKpM8kXWlmy5xzD8RXMLO9JL0lKV3ScOfcO0m0BwAAAAAAYhQVOz366Tw9+MnPcs4rM5MuP2QXXXhgd6WmWLgBAgDqjUonmp1zuWZ2lKSvJd3r92x+PrLezHaT9J6kBpLOcc69knS0AAAAAABAkrR60xZdNn6avpq3OlrWunGmHj5joPbu3jrEyAAA9VEyPZrlnFtjZodL+kbSU2a2yjn3kZn1k/SBpKaSznfOPRdArAAAAAAAQNL3v63RxeOmauXGLdGyPXdqqYeHD1LbJlkhRgYAqK+SSjRLknNuoZkdIelLSa+Y2V8kPSCppaTLnHP/S7YNAAAAAAAgFRc7/d8Xv+q+D+aqOGaojIsO7K5LD+6htNSUcAMEANRbSSeaJck596OZHSdvgsBnJJmka5xzDwexfwAAAAAA6ru1Ofm64sVp+mzuqmhZy0YZeuD0gTpglzYhRgYAQBKJZjPbP0HxvyVdKi/h/F2iOs65LyrbJgAAAAAA9dHkhdm66PmpWrY+L1q2e9cWeuTMQerQrEGIkQEA4EmmR/MESa6UdYf7t3guyTYBAAAAAKg3nHN68qv5uuu9OSosLvkI/ucDdtLfDuupdIbKAADUEMkkfb9Q6YlmAAAAAACQhPW5Bfrby9P10awV0bJmDdJ1/2kDdHDvdiFGBgDAtiqdaHbODQswDgAAAAAA4JuxZJ0ueG6KlqzdHC0b0Lm5HjtzkDq1aBhiZAAAJMYwFgAAAAAA1BDOOY39dqH++c5s5RcVR8tH7bOjrjmylzLSGCoDAFAzkWgGAAAAAKAG2JBXoGtf+VHv/LgsWtYkM033ntpfR/TtEGJkAABsX6USzWZ2mqSZzrlZYWwPAAAAAEBd8tPS9brwuSlasCY3Wta3Y1M9duZgdW3VKMTIAAAon8r+5ma8pFOSaDfZ7QEAAAAAqPWcc3r++0U68fFvtkoyn71nV738l71JMgMAao1khs5wgUUBAAAAAEA9k7OlUNe99qPemLY0WtYoI1V3ntxfxw3YIcTIAACouGQSzTeb2c2V3JYkNQAAAACg3pq7fKMueG6yfl2VEy3r1b6JHjtrsHZu0zjEyAAAqJzKJpq/UPLJ4gVJbg8AAAAAQK3z0g+LdcMbM5VXUBwtO2NIZ9183K7KSk8NMTIAACqvUolm59ywgOMAAAAAAKBO25xfpBvemKmXJy+JljVIT9XtJ/TVybt1CjEyAACSl8zQGQAAAAAAoBzmrdykC5+borkrNkbLurdtrCfOGqwe7ZqEGBkAAMEg0QwAAAAAQBV6Y9rvuvbVH5WbXxQtO2lQR91+Yl81zOBjOQCgbuAVDQAAAACAKpBXUKRb3pqlcRMXRcsy01J0y3G76vQhnWVmIUYHAECwSDQDAAAAABCwBatzdMFzUzRr2YZo2Y6tG+nxsward4emIUYGAEDVINEMAAAAAECA3v1xma5+eYY2bSmMlh3Tv4PuPKmfmmSlhxgZAABVh0QzAAAAAAAB2FJYpDvema0x3y6MlmWkpuiGY3rrD3t2ZagMAECdRqIZAAAAAIAkLc7O1YXPT9GMJeujZV1aNtRjZw5Wv07NQowMAIDqQaIZAAAAAIAkfPjTcv3tpenakFcyVMbhu7bTPacMULMGDJUBAKgfAk00m1lbSbtLaiEpNVEd59zYINsEAAAAACAMBUXFuvu9OfrfV/OjZWkppmuP6q1R+3RjqAwAQL0SSKLZzNIl/Z+kEZJSSqsmyUki0QwAAAAAqNWWrtusi56foimL1kXLOjZvoEfPHKRBXVqEFxgAACEJqkfzbZLOlfSrpOckLZZUWOYWAAAAAADUQp/NXakrXpimtbkF0bKDe7XVv04boOYNM0KMDACA8ASVaD5T0s+SBjnnNge0TwAAAAAAaozComL966Of9cSEX6NlqSmmqw7vqfP320kpKQyVAQCov4JKNLeV9DhJZgAAAABAXbRiQ54uHjdVE+dnR8vaN83SI2cO0pBuLUOMDACAmiGoRPMiSU0D2hcAAAAAADXGV7+s1qXjp2pNTn60bL8erfXg6QPVqnFmiJEBAFBzBJVoHi3pQjNr5pxbH9A+AQAAAAAITVGx08Of/KKHP/1FznllKSZdfsguuvDA7gyVAQBAjKASzXdJGiDpYzO7WtJk59yGgPYNAAAAAEC1WrVxiy57Yaq+nrcmWta6caYeHj5Qe+/cOsTIAAComYJKNEem2jVJH0uSWcJvdp1zLqg2AQAAAAAI3He/rdHF46Zq1cYt0bK9dmqlh4YPVNsmWSFGBgBAzRVU0vdLSS6gfQEAAAAAUO2Ki52e+PxX/evDuSr2P+GaSRcf2F2XHrKLUhkqAwCAUgWSaHbODQtiPwAAAAAAhCE7J1+XvzBNn/+8KlrWslGGHjx9oPbfpU2IkQEAUDswjAUAAAAAoF77YUG2Lh43VcvW50XLhnRroUeGD1b7ZgyVAQBAeQSeaDazdEm9JDWXtF7SbOdcQZkbAQAAAABQzZxz+u+Xv+nu9+eqqLhkNMi/HLCz/nbYLkpLTQkxOgAAapfAEs1m1lTSPZLOlhT7lW+emT0j6Rrn3Lqg2gMAAAAAoLLW5xboypem6+PZK6JlzRqk64HTB+igXu1CjAwAgNopkESzn2T+WtKukjbKmxxwmaQOkgZKOl/Svma2t3NuQxBtAgAAAABQGdMWr9OFz03R7+s2R8sGdWmuR88crI7NG4QYGQAAtVdQPZqvlZdkfkLSP2J7LptZM0m3S7rQr3dtQG0CAAAAAFBuzjmN/maB7nh3tgqKSobKOG/fHfX3I3opI42hMgAAqKygEs0nSfrOOXdh/Arn3HpJF5vZYEkni0QzAAAAAKCabcgr0N9fnqH3Zi6PljXJStO9pwzQEX3bhxgZAAB1Q1CJ5q6SXtlOnc8lXR5QewAAAAAAlMvM39frwuenaOGa3GhZv47N9NiZg9WlVcMQIwMAoO4IKtGcI6ntduq0kZS7nToAAAAAAATCOafnvl+kW9+epfzC4mj5iL266h9H91ZmWmqI0QEAULcElWieJOlUM7vbOfdL/Eoz21nSaZK+Dag9AAAAAABKtWlLoa579Ue9OX1ptKxxZpruOrmfjum/Q4iRAQBQNwWVaL5X0oeSJpnZI5I+k7RMUntJwyRdLKmxpPsCag8AAAAAgITmLN+gC56dot9W50TLerVvosfPGqyd2jQOMTIAAOquQBLNzrlPzOwCSQ9Jus6/RZikAkkXOec+DqI9AAAAAAASefGHxbrh9ZnaEjNUxvChnXXTsbsqK52hMgAAqCpB9WiWc+7fZvaepLMlDZLUTNJ6SVMlPeucWxhUWwAAAAAAxHLO6eY3f9KYb0s+ejZIT9UdJ/XViYM6hRgZAAD1Q2CJZklyzi2S9M8g9wkAAAAAwPb868Oft0oy92jbWI+fNVg92jUJMSoAAOqPQBPNAAAAAABUt9Ffz9ejn82LLh/dr4PuPbW/GmbwkRcAgOpSqVddM9vf/3eicy4vZnm7nHNfVKZNAAAAAADivTl9qW55e1Z0+aBebfXgGQOVnpoSYlQAANQ/lf16d4IkJ6m3pJ9jlsuD2RcAAAAAAEn74udVuvLFaXL+p9HBXZrrsTMHk2QGACAElU003yovsbw6bhkAAAAAgCo3bfE6/eXZySoo8j6K9mjbWE+NHKIGGfRtAgAgDJVKNDvnbi5rGQAAAACAqvLrqk069+mJys0vkiTt0CxLY88bquYNM0KODACA+iuQ3xOZWRcza7qdOk3MrEsQ7QEAAAAA6qfl6/M04smJWptbIElq3jBdY88bqg7NGoQcGQAA9VtQA1fNl3Tpdupc4tcDAAAAAKDC1ucW6JynJur3dZslSQ3SU/X0yCHq3rZJyJEBAICgEs3m3wAAAAAACNzm/CKdN2aS5q7YKElKSzE98YfBGtSlRciRAQAAKbhEc3m0l5RTje0BAAAAAOqAwqJiXfT8FP2wcG207L5TB2hYz7YhRgUAAGJVajJASTKzEXFFAxOUSVKqpC6S/iDpx8q2BwAAAACof5xzuvbVH/XJnJXRshuO6aMTBnUMMSoAABCv0olmSaMlOf9/J+l4/xYvMqRGrqRbkmgPAAAAAFDP3P3+XL00eUl0+a/DdtZ5++4YYkQAACCRZBLN5/p/TdJTkl6X9EaCekWS1kj61jm3Lon2AAAAAAD1yP++/E3/9/mv0eXTdu+kqw/vGWJEAACgNJVONDvnxkT+N7NzJL3unBsbSFQAAAAAgHrttalLdPs7s6PLh/RupztO7Ccz5qEHAKAmSqZHc5Rz7sAg9gMAAAAAwGdzV+qql2ZEl4d0a6FHzxyktNTqnM8eAABUBK/SAAAAAIAaY+qitbrg2SkqLPamBOrZron+N2KIstJTQ44MAACUJZAezZJkZo0kXSDpcEkdJWUmqOacczsH1SYAAAAAoO6Yt3Kjzh09SZsLiiRJHZs30NjzhqpZw/SQIwMAANsTSKLZzJpL+kpSH0kbJDWVtF5ShqQGfrWlkgqCaA8AAAAAULcsXbdZI56cqHW53sfGlo0y9Mx5Q9WuaVbIkQEAgPIIauiM6+Ulmc+T1MIve0BSY0l7S5oi6VdJvQNqDwAAAABQR6zLzdc5T03U0vV5kqSGGal6euQQ7dSmcciRAQCA8goq0XycpC+cc08751yk0Hm+k3SUpF6S/hFQewAAAACAOmBzfpFGjZ6kX1ZukiSlp5r+ffZuGtC5ebiBAQCACgkq0dxZ0uSY5WLFjNHsnFsp6T1JZwTUHgAAAACglisoKtYFz03WlEXrJElm0r9OG6j9erQJNzAAAFBhQSWac+UllyPWS2ofV2eFvEkCAQAAAAD1XHGx099fmaHP5q6Klt10TB8dN2CHEKMCAACVFVSiebG8Xs0RsyTtb2ax+99X0vKA2gMAAAAA1GJ3vT9Hr075Pbp80YHdNXKfHUOMCAAAJCOoRPPnkg4wM/OXX5C0s6R3zexCM3tJ0p6S3g2oPQAAAABALfXvz3/Vf774Lbo8fGhnXXnYLiFGBAAAkpUW0H7GSMqQ1Ele7+b/k3SQpBMkHebX+VrS9QG1BwAAAACohV6evER3vjcnunxYn3a67fi+Kum3BAAAaqNAEs3OuSmS/hqzXCjpJDPbTVJ3SQskTXLOFSfeAwAAAACgrvtk9gr9/ZUZ0eWhO7bUw8MHKS01qB/bAgCAsASSaDaz/SVtcM5Niy13zk2WNDmINgAAAAAAtdfkhdm68PkpKip2kqRe7ZvovyN2V1Z6asiRAQCAIAT1tfFnks4PaF8AAAAAgDrk5xUbNWr0D8or8H7k2rllA40dNVTNGqSHHBkAAAhKUInm1ZI2B7QvAAAAAEAd8fu6zRrx5ESt31wgSWrVKENjR+2htk2zQo4MAAAEKahE8wRJewe0LwAAAABAHZCdk6+zn/xeyzfkSZIaZaRq9LlDtWPrRiFHBgAAghZUovl6ST3N7DYz47dPAAAAAFDP5Wwp1LmjJ+m3VTmSpIzUFP13xO7q16lZyJEBAICqEMhkgJKulTRT0nWSzjOz6ZKWS3Jx9Zxz7ryA2gQAAAAA1ED5hcX663NTNH3xOkmSmfTgGQO1d/fW4QYGAACqTFCJ5pEx/7f3b4k4SSSaAQAAAKCOKi52uurl6fri51XRsluP76uj+nUIMSoAAFDVgko07xjQfgAAAAAAtZRzTre/M1tvTFsaLbv04B46e8+uIUYFAACqQyCJZufcwiD2AwAAAACovZ74/Fc99fX86PJZe3TRZYf0CDEiAABQXYKaDBAAAAAAUI+9OGmx7nl/bnT5qH7tdevxfWVmIUYFAACqS6CJZjM71szGm9l0M5sXU97bzK42s45BtgcAAAAACN9Hs1bomldnRJf32qmVHjh9oFJTSDIDAFBfBDJ0hnlfUY+W9Ae/aLOkBjFV1kq6Q5JJujuINgEAAAAA4Zs4P1sXPT9Fxc5b3nWHpvrPiN2UmZYabmAAAKBaBdWj+QJJZ0t6WlJLSffFrnTOLZf0taSjk23IzO42s0/MbLGZbTazbDObamY3mVmruLrpZnapmT1tZtPMLN/MnJn9Mdk4AAAAAKC+m7N8g84bM0lbCoslSV1bNdToc4eqSVZ6yJEBAIDqFkiPZknnSZou6U/OOWdmLkGdXyQdHkBbl0uaIukjSSslNZK0p6SbJZ3//+3dd5zU1b3/8dfZTll62YUFFJWioMgCxhJjiVHRxEQhlkRjTKJJbm7azc3NTS83N8lNbvo1xV+siSVijFFRY02iRpEFFKQoTVjYpcMuZfv5/THDuLKLAjvLbHk9H495DN/zPfM9n+EhX2ffe+acEMLbYoxrk317AT9N/nkDUAmMSEMNkiRJktStrd26m6t+N4fqmgYABvXO57ZrTmJwYX6GK5MkSZmQrqB5LPCbGGNrAfNeG4HBaRirT4yxZt/GEMJ3gS8D/0lihjXAbmA6sCDGWBFC+CbwjTTUIEmSJEnd1padtXzoxjlsrK4FoDA/h1uumcrIgT0zXJkkScqUdC2d0QAUvEWf4cDOtg7UWsic9Mfk8zHN+tbFGB+KMVa0dVxJkiRJEuysbeDDN7/Ays27AMjLyeK3V03huGF9M1yZJEnKpHQFzYuBM5KbArYQQigAzgLmp2m81rw7+fzSm/aSJEmSJB2S2oZGPn5bGS+V7wAgK8DPL5vEyUcNfItXSpKkri5dS2fcBvwS+EkI4fPNT4QQsoEfA8OAL6VpPEIIXwB6A32BKcBpJELm76drjH3GK9vPqXHtMZ4kSZIkdSRNTZF/++OLPL18c6rtv947kfMmFGewKkmS1FGkK2j+DfAe4NPATKAaIIQwi8RGfcOA+2KMf0jTeABfAIY2O34YuDrGuCmNY0iSJElStxdj5Fv3v8wDL72+KuHnzxnDFSeNzGBVkiSpI0nL0hkxxkbgQuDbQD4wBgjAxUBP4DskAui0iTEWxRgDUJQcZzQwP4QwOZ3jNBuvtLUHsLQ9xpMkSZKkjuKXTyznln++ljq+6uRR/OtZR2ewIkmS1NGka0YzMcYG4JshhG+RCJoHAjuApckgul3EGDcA94YQ5gGvALcCE9prPEmSJEnqTm5/fg3/++grqeMLji/mG+8+jv1s0SNJkrqptAXNe8UYI7As3dc9gHFfCyEsBiaFEAbFGDe/5YskSZIkSfv18KIKvvrnhanjU48eyI/ffwLZWYbMkiTpjdKydEYHMiz53G4zqCVJkiSpO3hu5RY+fecCmmLieOLwvvzmyink52RntjBJktQhpW1GcwjhGOAzwDSgP9Dap48YYzyqDWOMATbEGHfs055FYh3oIcCzMcZthzqGJEmSJHV3L6/fwcdumUtdQxMARw7qxU0fnkrv/LR/KVaSJHURafmUEEI4GXgM6AE0ABuSzy26tnGo6cD3QghPA6uALcBQ4B0kNgOsBD62T21fAsYlDyclnz8cQjgt+eenY4z/r411SZIkSVKXsGbLbj504wtU1yZ+pBtSmM+t10xjUO/8DFcmSZI6snT9Ovp7QD7wceDG5MaA7eEx4GjgNOBEoB+wi8QmgLcBP48xbt3nNeeRCKKbOyX52MugWZIkSVK3t6m6litvfJ7NO2sBKCzI4ZZrpjFiQM8MVyZJkjq6dAXNU4FZMcbfpul6rYoxLgI+dZCvOaN9qpEkSZKkrqO6pp6rb5rDa1t2A5Cfk8XvPjSV8cV9MlyZJEnqDNK1GWAdsCZN15IkSZIkHUa1DY1cd1sZL6+vAiArwC+vmMy0IwdkuDJJktRZpCtofpbEUhaSJEmSpE6ksSnyubsW8OyKLam27108kXOOHZrBqiRJUmeTrqD5y8ApIYQr03Q9SZIkSVI7izHyjb8sYvbCylTbv587lkunjsxgVZIkqTNK1xrNFwFPADeHED4KlAHbW+kXY4zfSdOYkiRJkqQ2+Nnjr/L7515fBfHDpx7BJ884KoMVSZKkzipdQfM3m/357clHayJg0CxJkiRJGfb7517jp4+9mjq+aNIwvnbBsYQQMliVJEnqrNIVNJ+ZputIkiRJktrZ7IUVfO2+Ranj08cM5oczTiAry5BZkiQdmrQEzTHGv6XjOpIkSZKk9vXs8s189s4FxJg4PmFEP371gcnk5aRrCx9JktQd+UlCkiRJkrqJRet2cO1tZdQ1NgEwenAvbrp6Kr3y0/VlV0mS1F2l9dNECOF44ApgPNArxvjOZPsRwDTg0RjjtnSOKUmSJEl6a6s37+Lqm+aws7YBgKI+Bdx6zTQG9MrLcGWSJKkrSFvQHEL4NvBlXp8lHZudzgLuAD4L/CJdY0qSJEmS3trGqhquvPF5Nu+sA6BPQQ63XDONkv49M1yZJEnqKtKydEYI4TLgq8CjwCTge83PxxhXAnOB96RjPEmSJEnSgamqqedDN73A2q17AMjPyeLGq6cytqgww5VJkqSuJF1rNH8aWA5cFGN8Cahrpc8S4Jg0jSdJkiRJegs19Y187Ja5LKmoAiA7K3D9ByYz5YgBGa5MkiR1NekKmicCj8QYWwuY91oPDE3TeJIkSZKkN9HYFPnMnfN5ftXWVNv3L57I2eP9sUySJKVfuoLmADS9RZ+hQE2axpMkSZIk7UeMka/+eSGPvLwh1fal88cxc8qIDFYlSZK6snQFza8Cp+zvZAghCzgNeDlN40mSJEmS9uPHj77CHXPWpo4/etqRXHf66AxWJEmSurp0Bc1/BCaHEP5tP+e/DBwN3J6m8SRJkiRJrbj5mVX84onlqeP3nTicL08fTwghg1VJkqSuLidN1/kpMBP4nxDC+4EIEEL4EfB2YArwHPDbNI0nSZIkSdrH/S+u51sPLE4dnzF2MP8z43iysgyZJUlS+0pL0Bxj3BNCOBP4GfABIDt56vMk1m7+PfCpGGNDOsaTJEmSJL3RP17dxOf/uIAYE8cnjuzH9R+YTG52ur7IKkmStH/pmtFMjHEHcHUI4fPAVGAgsAOYE2PclK5xJEmSJElv9FL5dq67rYz6xkTKfPSQ3tz4oan0zEvbj3ySJElvKu2fOmKMW4FH0n1dSZIkSVJLKzft5OqbXmB3XSMAxX0LuPWaafTvlZfhyiRJUnfid6gkSZIkqZPaUFXDlb+bw9ZddQD065nLbR+ZxrB+PTJcmSRJ6m7SMqM5hHDjAXRrAqqAJcD9McbKdIwtSZIkSd3Rjj31fOjGOazbvgeAHrnZ3Hj1VI4eUpjhyiRJUneUrqUzrgaSW07Q2nbGcZ/2X4YQvhpj/GGaxpckSZKkbqOmvpGP3vICSyurAcjJClz/wclMHtk/w5VJkqTuKl1LZxwF3AdsAb4KnAGMTz5/Ldl+L3AScB2wAfh+COGiNI0vSZIkSd1CQ2MTn7p9Pi+s3pZq++HM4zlz7JAMViVJkrq7dM1ofi/wdmBSjHFds/ZlwN9DCLcC84F/xBh/GkJ4BFgMfIpEQC1JkiRJegsxRr5870IeW7Ih1fbVC8bzvhNLMliVJElS+mY0XwvcvU/InBJjXAvcnexHjHEN8AAwOU3jS5IkSVKX98NHlvHHueWp4+veMZqPvn10BiuSJElKSFfQfASw4y36bAeObHa8GuidpvElSZIkqUu78elVXP/UitTxjNISvnTeuAxWJEmS9Lp0Bc2bgXPeos+7SKzVvFc/3jqcliRJkqRu78/z1/HtBxanjs8eN4TvXzyREFrbi12SJOnwS1fQfA8wOYTw+xDCyOYnQggjQwh/ACYBs5qdKgVeTdP4kiRJktQlPbVsI1+4+8XU8ZRR/fnlFZPJyU7Xj3OSJEltl67NAL9OYjPAK4BLQwjrgA3AUGA4kA0sSPYjhFAM1AO3pWl8SZIkSepy5q/Zxid+P4+GpgjAmKG9+d2HptIjLzvDlUmSJL1RWoLmGGNVCOEU4IvAh4DRwN6ZzSuBW4H/iTHWJPtXAKekY2xJkiRJ6oqWb9zJNTe/wJ76RgCG9+vBrdecRN+euRmuTJIkqaV0zWgmxlgLfAf4TgihEOgDVMUYq9M1hiRJkiR1BxU79nDV755n2+56APr3zOWWa6ZR1Lcgw5VJkiS1Lm1Bc3PJcNmAWZIkSZIO0vbddVz1uzms31EDQM+8bG768DSOHtI7w5VJkiTtn7tHSJIkSVIHsaeukY/cMpdXN+4EICcr8OsPljJpRL/MFiZJkvQWDJolSZIkqQOob2ziX26fR9lr21Jt//v+Ezh9zOAMViVJknRgDJolSZIkKcNijHzpnoU8sXRjqu3rFx7LRZOGZ7AqSZKkA2fQLEmSJEkZ9v2HlnLPvPLU8SfPOIprTjsygxVJkiQdHINmSZIkScqgG/6+kt/8fWXq+NIpI/j3c8dmsCJJkqSDZ9AsSZIkSRlyT1k53529JHV8zrFD+e77JhBCyGBVkiRJBy8n3RcMIfQCxgC9Y4z/SPf1JUmSJKkreHLpRr54z0up42lHDOAXl59ITrbzgSRJUueTtk8wIYSSEMI9wDZgLvBks3OnhRAWhxDOSNd4kiRJktRZlb22jU/8oYzGpgjAuKJCbvjQFApyszNcmSRJ0qFJS9AcQigGngcuAh4A/gk0/67X88AQ4NJ0jCdJkiRJndWrG6q55uYXqKlvAqCkfw9uvWYafXvkZrgySZKkQ5euGc3fIBEknxNjvBh4tPnJGGM98A/g1DSNJ0mSJEmdzvrte7jqxjns2FMPwMBeedz2kZMY0qcgw5VJkiS1TbqC5unAX2KMT75JnzXAsDSNJ0mSJEmdyrZddVz5u+ep2FEDQK+8bG7+8DSOHNQrw5VJkiS1XbqC5qHAq2/Rpx7wE5QkSZKkbmd3XQMfvvkFVmzaBUBuduA3V05hYknfDFcmSZKUHukKmrcCI96izxigMk3jSZIkSVKnUN/YxCf/MI8Fa7cDEAL85NJJnHbMoMwWJkmSlEbpCpqfAd4TQihq7WQI4RjgPODNltaQJEmSpC6lqSnyxVkv8dSyTam2b73nOC483lUFJUlS15KuoPmHQAHwtxDC+UBPgBBCr+Tx/UAT8L9pGk+SJEmSOrQYI9+dvYR7569LtX36rKO56uQjMleUJElSO8lJx0VijM+HEK4DfgU80OxUVfK5AbgmxvhyOsaTJEmSpI7u139bye+eXpU6vnzaSD53zpgMViRJktR+0hI0A8QYbwwh/AP4JPA2YCCwA3gO+GWMcVm6xpIkSZKkjuyPc9fyg4eXpo7PO66I/3rvBEIIGaxKkiSp/aQtaAaIMb4KfC6d15QkSZKkzuSxxRv4zz8tTB2/bfQAfnrZJLKzDJklSVLXlZY1mkMIXw8hnP4Wfd4eQvh6OsaTJEmSpI7ohdVb+Zfb59HYFAEYX9yH3141hYLc7AxXJkmS1L7StRngN4Ez3qLP6cA30jSeJEmSJHUoSyur+MjNL1Db0ATAyAE9ueWaqfQpyM1wZZIkSe0vXUHzgcgFmg7jeJIkSZJ0WJRv282HbpxDVU0DAIN653HbR6YxpLAgw5VJkiQdHoczaJ4MbD6M40mSJElSu9uys5arfjeHDVW1APTOz+HmD09j1MBeGa5MkiTp8DnkzQBDCE/s03R1COGMVrpmAyOAUcAdhzqeJEmSJHU0u2obuObmF1i5eRcAedlZ/PaqUiYM75vhyiRJkg6vQw6aeeOazBE4IvnYVxOwBbgL+FwbxpMkSZKkDqOuoYmP/76MF8t3ABAC/PSySZxy1KAMVyZJknT4HXLQHGNMLbsRQmgCvhlj/HZaqpIkSZKkDqypKfKFu1/kH6++vjrgdy6awPSJxRmsSpIkKXPaMqO5uQ8DC9J0LUmSJEnqsGKMfPuBxfzlxfWpts+9cwwffNuoDFYlSZKUWWkJmmOMt+zvXAihP1AXY9yVjrEkSZIkKZOuf2oFNz+7OnV81cmj+PTZR2euIEmSpA4g6627vLUQwlkhhP9Jhsp724aEEP4GbAa2hhB+nI6xJEmSJClT7pyzhh8+six1fMHEYr7x7uMIIWSwKkmSpMxLS9AMfBq4OMa4rVnbj4C3AytIbAb4mRDC+9M0niRJkiQdVo+8XMmX712YOj716IH8+NITyM4yZJYkSUpX0HwC8PTegxBCD2AG8GiMcQwwFlgLfDxN40mSJEnSYfP8yi386x3zaYqJ4wnD+/CbK6eQn5Od2cIkSZI6iHQFzUOA9c2OTwIKgJsBYozVwAMkAmdJkiRJ6jSWVFTx0VvnUtfQBMARA3ty84en0Ts/XXurS5IkdX7pCpprgR7Njt8ORODvzdqqgAFpGk+SJEmS2t3arbu56sY5VNc0ADC4MJ/bPnISg3rnZ7gySZKkjiVdQfMq4Kxmx5cAr8YY1zVrG0FiY0BJkiRJ6vA276zlyt89z6bqWgAK83O45cPTGDGgZ4YrkyRJ6njSFTTfAkwMITwfQvgHMBG4fZ8+xwPLWrxSkiRJkjqY6pp6rr5pDqu37AYgLyeL//ehKRw7rE+GK5MkSeqY0hU0/wq4E5gCnEpiPeYf7D0ZQphAInx+Kk3jSZIkSVK7qG1o5Lrbyli0rgqArAC/uPxETho9MMOVSZIkdVxp2b0ixlgPXBFC+HjiMFbv06USOBFYnY7xJEmSJKk9NDZFPn/Xizy7Ykuq7b/fN5FzjyvKYFWSJEkdX1q3SY4xVu2nfTOuzyxJkiSpA4sx8s2/vMyDCytSbV941xgumzYyg1VJkiR1DulaOkOSJEmSOrWfP76c2557LXV89SlH8C9nHp3BiiRJkjqPtM1oDiH0Aj4JnAsMB/Jb6RZjjEela0xJkiRJSoffP/caP3nsldTxu08YxtcvPJYQQgarkiRJ6jzSEjSHEPoBTwPHAlVAH2AHkAf0SHZbD9SnYzxJkiRJSpeHFlbwtfsWpY7ffswg/nfmCWRlGTJLkiQdqHQtnfFVEiHzR4D+ybafAL2BU4B5wApgfJrGkyRJkqQ2e3bFZj5z5wJiTBwfX9KXX32wlLwcVxmUJEk6GOn69PQe4O8xxpti3PsRLbFORozxOWA6MA74SprGkyRJkqQ2WbRuB9feWkZdYxMAowf14qarp9I7P617pkuSJHUL6QqaRwBlzY6baLZGc4xxI/AQcFmaxpMkSZKkQ/ball1cfdML7KxtAGBon3xuuWYaA3u3ttWMJEmS3kq6gubdJMLlvXYARfv02UBik0BJkiRJypiN1TVc+bs5bN5ZC0CfghxuuWYaIwb0zHBlkiRJnVe6gua1JGY177UYOD2E0Pz6pwGVaRpPkiRJkg5aVU09V9/4Amu27gYgPyeL3109lXFFfTJcmSRJUueWrqD5b8A7Qgh7t2W+CzgKmB1C+JcQwt3A24DZaRpPkiRJkg5KTX0j1946l8UVVQBkZwV+ecVkph4xIMOVSZIkdX7p2uXiFiAPKCExu/nXwFnAe4F3Jfs8A3w1TeNJkiRJ0gFrbIp89s4FPLdya6rtexdP5Jxjh2awKkmSpK4jLUFzjHEe8Ilmxw3AxSGEUuBoYDXwQoyxqfUrSJIkSVL7iDHytfsW8fDLr6/k9x/njeP9U0a8yaskSZJ0MNI1o7lVMcYyoKw9x5AkSZKkN/OTx17l9ufXpI4/ctqRfPwdozNYkSRJUteTljWaQwhXhxCcDiBJkiSpQ7ntn6v5+eOvpo7fd+JwvjJ9PK9vLyNJkqR0SNeM5huBGEJYCTwOPAE8EWPcnKbrS5IkSdJBeeCl9Xz9Ly+njt8xZjD/M+N4srIMmSVJktItLTOagX8B7gX6A9cCdwCVIYQXQwg/DiFcGEIoTNNYkiRJkvSmnn51M5+7awExJo4njejHrz44mdzsdP0IJEmSpObStRngr4BfhcT3zyYBZycfpwETgc8AjSGEuTHGU9IxpiRJkiS15qXy7Vx321zqGxMp81GDe3HT1VPpmdeuW9RIkiR1a2n9dX5MmB9j/FGM8XxgIPA5YBOJUPukdI4nSZIkSc2t2ryLD9/0ArvqGgEo7lvArR85if698jJcmSRJUteW9l/phxCO5vUZzWcCA4AArCCxfrMkSZIkpd2Gqhqu/N3zbNlVB0DfHrnces00hvfrkeHKJEmSur60BM0hhA/werhcQiJYrgAeJrk5YIxxTTrGkiRJkqR97dhTz4dunEP5tj0AFORmcePVUzlmqFvFSJIkHQ7pmtF8GxCBJ4DvA0/GGJem6dqSJEmStF819Y187Ja5LK2sBiA7K3D9ByZTOqp/hiuTJEnqPtIVNNcBecA7gN7AsBDC48CzMca6NI0hSZIkSW/Q0NjEv94xnzmrt6ba/ueS4zlr3NAMViVJktT9pGszwH7AOcCPktf8EoklM7aFEB4NIXwphDA1hBDSNJ4kSZKkbi7GyFfuXcSjizek2r48fRyXlJZksCpJkqTuKS0zmmOMNSSC5ccBQgh9SGwEeFby8d3kYweJzQElSZIkqU1+9Ndl3DV3ber42tNHc+3pR2WwIkmSpO4rXUtnvEGMsSqE8DSQD/QAhgCDgb7tMZ4kSZKk7uWmZ1bxf0+uSB1fPHk4XzpvXAYrkiRJ6t7SFjSHEHoBpwNnJx8TgZB87ADuIznjWZIkSZIO1X0L1vGt+xenjs8aN4QfXHI8WVmu1CdJkpQpaQmaQwj/AKYlrxeAPSRC5SeSz/NijE3pGEuSJElS9xRj5KZnVvPd2UtSbZNH9uP/rphMbna6tp+RJEnSoUjXjOaTgOd5PVj+Z4yxPk3XliRJktTN1TY08tV7F3F3WXmq7Zghvbnx6qn0yMvOYGWSJEmC9AXN/WOMu9J0LUmSJElK2VhVw3W/L2P+mu2pthNG9OOGK0vp1zMvc4VJkiQpJS1BsyGzJEmSpPbw4trtXHdbGZVVNam2i08czn9fPJGCXGcyS5IkdRRp2wxQkiRJktLp3vnl/Mc9C6lrSGz3khXgy9PH85HTjiQEN/6TJEnqSAyaJUmSJHUojU2RHzy8lN/+fWWqrU9BDr+4YjLvGDM4g5VJkiRpfwyaJUmSJHUYO/bU8+k75vO3Vzal2o4e0psbrprCkYN6ZbAySZIkvRmDZkmSJEkdwvKNO7n21rms3Pz6FjBnjxvCTy+bRGFBbgYrkyRJ0lsxaJYkSZKUcU8s3cBn7lhAdW1Dqu2TZxzFv71rLNlZrscsSZLU0Rk0S5IkScqYGCO/+tsKfvjIMmJMtBXkZvHDGSfw7hOGZbY4SZIkHTCDZkmSJEkZsaeukf+45yX+8uL6VNuwvgX89qopTBjeN4OVSZIk6WAZNEuSJEk67NZv38O1t81l0bqqVNvUI/rzqw+WMqh3fgYrkyRJ0qEwaJYkSZJ0WM1dvZWP/76MzTvrUm2XTxvJt95zHHk5WRmsTJIkSYfKoFmSJEnSYXPnnDV87b5F1DcmFmTOyQp84z3HceXbRmW4MkmSJLWFQbMkSZKkdlff2MR3HljMrf98LdU2oFce139gMm8bPTCDlUmSJCkdDJolSZIktautu+r4lz/M458rt6TaxhUVcsNVUxgxoGcGK5MkSVK6GDRLkiRJajdLK6v46C1zKd+2J9U2fWIRP5p5Aj3z/HFEkiSpq/CTnSRJkqR28fCiCj7/xxfZXdeYavv8OWP417OOJoSQwcokSZKUbgbNkiRJktKqqSnys8df5WePv5pq65WXzU8uncS7jivKYGWSJElqLwbNkiRJktJmZ20D//bHBTzy8oZU26iBPbnhqimMGVqYwcokSZLUngyaJUmSJKXFmi27+ditc1m2oTrVdtrRg/jlFSfSr2deBiuTJElSezNoliRJktRmzy7fzCdvn8f23fWptmtOPZIvTx9HTnZWBiuTJEnS4WDQLEmSJOmQxRi55dnVfOfBJTQ2RQDysrP4r/dN4P1TRmS4OkmSJB0uBs2SJEmSDkltQyNf//PL3DV3baptcGE+v/5gKaWj+mewMkmSJB1uBs2SJEmSDtrG6ho+8ft5lL22LdV2QklffnPlFIr6FmSwMkmSJGWCQbMkSZKkg/JS+Xauu62Mih01qbb3nTic7108kYLc7AxWJkmSpEwxaJYkSZJ0wO5bsI4vznqJ2oYmALIC/Of54/no248khJDh6iRJkpQpBs2SJEmS3lJjU+R/HlnKb/62MtVWWJDDL6+YzDvGDM5gZZIkSeoIDJolSZIkvakde+r5zJ3zeWrZplTbUYN7ccNVUxg9uHcGK5MkSVJHYdAsSZIkab9WbNrJx26dy8pNu1JtZ40bwk8vm0SfgtwMViZJkqSOxKBZkiRJUqueXLqRT98xn+rahlTbJ884in9711iys1yPWZIkSa8zaJYkSZL0BjFGfvP3lfzg4aXEmGgryM3if2acwHtOGJbZ4iRJktQhGTRLkiRJSqmpb+Q/7nmJ+xasT7UV9y3ghqumMGF43wxWJkmSpI7MoFmSJEkSABU79nDtrWUsXLcj1TZlVH9+9cFSBhfmZ7AySZIkdXQGzZIkSZIoe20r1902j807a1Ntl08bwbfeM4G8nKwMViZJkqTOwKBZkiRJ6ubuemENX/3zIuobEwsy52QFvvHuY/ng20YRgpv+SZIk6a0ZNEuSJEndVH1jE999cAk3P7s61da/Zy7Xf6CUk48amLnCJEmS1OkYNEuSJEnd0LZddfzL7fN4dsWWVNu4okJuuGoKIwb0zGBlkiRJ6owMmiVJkqRuZmllFR+7dS5rt+5JtZ0/oYgfzTyBXvn+iCBJkqSD56dISZIkqRt5eFEln//jAnbXNabaPn/OGD515tFkZbkesyRJkg6NQbMkSZLUDTQ1RX7+xKv89LFXU2298rL58aWTOPe4ogxWJkmSpK7AoFmSJEnq4nbVNvBvf3yRh1+uTLWNGNCD/3fVVMYWFWawMkmSJHUVBs2SJElSF7Z2624+dutcllZWp9pOOWog/3fFZPr3ystgZZIkSepKDJolSZKkLurZFZv5lz/MY9vu+lTbh089gq9MH09OdlYGK5MkSVJXY9AsSZIkdTExRm7952t8+4HFNDZFAPKys/iv903g/VNGZLg6SZIkdUUGzZIkSVIXUtfQxNfvW8SdL6xNtQ3qnc9vriyldFT/DFYmSZKkrsygWZIkSeoiNlXX8onflzH3tW2ptuNL+vKbK0sp7tsjg5VJkiSpqzNoliRJkrqAheU7uPa2uVTsqEm1vXfSML5/yfEU5GZnsDJJkiR1BwbNkiRJUid334J1fHHWS9Q2NAGQFeBL54/jY28fTQghw9VJkiSpOzBoliRJkjqpxqbIj/66jF89tSLVVliQwy8uP5Ezxg7JYGWSJEnqbrIyXcDBCiH8IITweAhhbQhhTwhhawhhfgjhGyGEgft5zSkhhNnJvntCCC+FED4bQvA7hJIkSeqUqmrq+egtL7whZB49uBd//pdTDZklSZJ02HXGGc2fA+YBjwIbgV7A24BvAteGEN4WY0xtsR1CuAi4B6gB7gK2Au8GfgKcCsw8nMVLkiRJbbVy004+eutcVm7alWo7c+xgfnb5ifQpyM1gZZIkSequOmPQ3CfGWLNvYwjhu8CXgf8EPpls6wPcADQCZ8QY5ybbvwY8AcwIIVwWY7zzcBUvSZIktcVTyzbyr3fMp7qmIdX2iTOO4gvvGkt2lusxS5IkKTM63dIZrYXMSX9MPh/TrG0GMBi4c2/I3OwaX00efiLtRUqSJElpFmPkN39bwTU3v5AKmfNzsvjZZZP4j/PGGTJLkiQpozrjjOb9eXfy+aVmbWclnx9upf/fgd3AKSGE/Bhj7ZtdPIRQtp9T4w6qSkmSJOkg1dQ38p9/Wsi989el2or7FvDbK6cwsaRvBiuTJEmSEjpt0BxC+ALQG+gLTAFOIxEyf79Zt7HJ51f2fX2MsSGEsAo4DhgNLGnXgiVJkqRDULmjhmtvm8tL5TtSbVNG9edXHyxlcGF+BiuTJEmSXtdpg2bgC8DQZscPA1fHGDc1a9s7vWMHrdvb3u+tBosxlrbWnpzpPPmtXi9JkiQdrLLXtvHx35exqfr1L99dNnUE37roOPJzsjNYmSRJkvRGnW6N5r1ijEUxxgAUAReTmJU8P4Rg6CtJkqRO749z13L5b59LhczZWYFvX3Qc37t4oiGzJEmSOpzOPKMZgBjjBuDeEMI8Ektk3ApMSJ7eO2N5fwvX7W3f3m4FSpIkSQehobGJ785ewk3PrE619e+Zy/99YDKnHDUoc4VJkiRJb6LTzmjeV4zxNWAxcFwIYe8n8GXJ5zH79g8h5ABHAg3AysNSpCRJkvQmtu2q40M3zXlDyDyuqJC/fOo0Q2ZJkiR1aF0maE4alnxuTD4/kXw+r5W+pwM9gWdjjLWtnJckSZIOm2WV1Vz0f8/wzPItqbZzjxvKPZ84hREDemawMkmSJOmtdaqgOYQwJoTQYhmMEEJWCOG7wBASwfG25KlZwGbgshDClGb9C4D/Sh7+qp3LliRJkt7UIy9XcvH1z7Bm6+5U2+feOYZffaCUXvmdfrU7SZIkdQOd7VPrdOB7IYSngVXAFmAo8A4SmwFWAh/b2znGWBVC+BiJwPmpEMKdwFbgPcDYZPtdh/UdSJIkSUlNTZFfPLGcnzz2SqqtZ142P37/JM6bUJTByiRJkqSD09mC5seAo4HTgBOBfsAuEpsA3gb8PMa4tfkLYox/DiG8A/gKcAlQACwHPp/sHw9b9ZIkSVLSrtoGvnD3izy0qDLVNmJAD264agrjivpksDJJkiTp4HWqoDnGuAj41CG87hkSs6ElSZKkjFu7dTcfu3UuSyurU22nHDWQ/7tiMv175WWwMkmSJOnQdKqgWZIkdW419Y28umEnSyurWFZZzdLKal7buouRA3py3oRizjuuiMGF+ZkuU2pX/1yxhU/+oYxtu+tTbVefcgRfuWA8udmdagsVSZIkKcWgWZIkpV1TU6R82x6WpALlKpZWVrN68y6aWlm0au3WPTyzfAvfuG8R044cwPSJxZw3oYghhQWHv3ipncQY+f1zr/Gt+xfTkPyHkJsd+K/3TuDSqSMzXJ0kSZLUNgbNkiSpTbbtqmNpZTXLKqtYtqGaJRXVvLKhmt11jQd9raYIz63cynMrt/KNv7zM1CMGMH1CEedPLGZoH0NndV51DU184y8vc8ecNam2Qb3z+c2VkykdNSCDlUmSJEnpYdAsSZIOSG1DIys27kote7EkGS5vqKo94GuEAKMG9GRsUSHjivowrqiQkQN78sKqrcxeVMkLq7eyd5veGGHOqq3MWbWVbz2wmCmj+nP+hGLOn1hEcd8e7fQupfTbvLOWT/y+jBdWb0u1TRzel99cWcqwfv63LEmSpK7BoFmSJL1BjJF12/ewtKKaZRsS6ygvrahi5eZdNLa27sV+DOiVx9ihhYwrLmRcUSFji/owZmhveua1/Phx3LC+XH3qkWysquHhlyuZvbCCOau2ppbZiBFeWL2NF1Zv49sPLKZ0VH/On1DE9InFBnXq0Bat28G1t85l/Y6aVNtFk4bxg0uOpyA3O4OVSZIkSekVYjzwHxjVUgihbPLkyZPLysoyXYokSQdtx556liVnJi9Nbs73SmU11bUNB3yNvJwsjhnSm7FFhYwv6pOYrVxcyODe+YQQDrm2TdW1PPxyJQ8trOC5lVtaXdsZ4MSR/ZienOlc0r/nIY8npdtfXlzPF2e9SE19E5CY0f+l88Zx7emj2/RvQ5IkSWovpaWlzJs3b16MsfRgX2vQ3EYGzZKkzqC+sYmVm3alNuVblpyl3HyW5YEYMaAHY4f2YXxxYXL5i0KOGNiLnOysdqo8YfPOWh55uZKHFlbyz5Vb9juz+oQR/ZienOk8YoChszKjsSnyo78u41dPrUi1FRbk8PPLT+TMsUMyWJkkSZL05toSNLt0hiRJXUiMkcqqGpZWVKc26FtaWc2KTTupbzzwXy737ZGbnKGcWPJibFEiWO6dn5mPDoN65/OBk0bxgZNGsWVnLX9dvIHZCyt4dsUbQ+cX127nxbXb+d5DSzm+pC/nTyjmgonFjBxo6KzDo6qmns/euYAnlm5MtY0e1IsbPjSFowb3zmBlkiRJUvsyaJYkqZPaWduQmJmc3JwvES5XUVVz4Mte5GYHjhrcm/HFr4fJ44v6MLRP25a9aE8De+dz+bSRXD5tJNt21fHXxZXMXljJM8s309AsdH6pfAcvle/gBw8vZcLwPqnQ+YhBvTJYvbqyVZt38dFbXmDFpl2ptjPGDuZnl51I3x65GaxMkiRJan8GzZIkdXANjU2s3rKLJRXJJS+S4XL5tj0HdZ3h/XokN+VLBsrFfThyUC9y23nZi/bUv1cel04dyaVTR7J9dx1/XbyBhxZW8PTyzW+Ywb1oXRWL1lXxw0eWcWxxH6ZPTCyvMdoZpkqTv72yiX+9fd4bftFz3TtG88Vzx5Gd1TF/aSNJkiSlk0GzJEkdRIyRTdW1qSB5aXKW8vJNO6lraDrg6xTm56Q25Btb1IdxRYWMGVrY5WdU9uuZx/unjOD9U0awY3c9jy5JhM7/eHUzdY2v//0trqhicUUVP/rrK4wrKmT6xGKmTyzm6CGGzjp4MUb+3z9W8b2HlqQ2rMzPyeIHlxzPe08cntniJEmSpMPIoFmSpAzYXdfAKxt2srSi2eZ8lVVs211/wNfIyQqMHtyLcck1lMcVFTKuuA/D+hZ02GUvDpe+PXOZUVrCjNISqmrqeWzxBmYvrOTvr2x6Q+i8NDlD/MePvsLYoYWcP7GICyYWc8zQwgxWr86ipr6RL/9pIX+avy7VVtSngN9eVcrxJf0yV5gkSZKUAQbNkiS1o8amyGtbdrGsspolzTbnW7N1N/HA9+ajqE9BcoZyMlAu6sPowb3Iz8luv+K7iD4FuVw8uYSLJ5dQXVPPE0s38uBLFTz1yqY3zBRftqGaZRuq+eljr3LMkN6cPzGxpvOYob27fXCvlip31HDdbXN5sXxHqm3yyH78+spShhQWZLAySZIkKTMMmiVJSpPNO2sTgXJFYnO+ZRuqeWVDNTX1B77sRa+8bMYkg+S96ymPKyqkX8+8dqy8+ygsyOWiScO5aNJwdtY28MTSjcx+qYInl22ktlno/OrGnbz6+Kv8/PFXOWpwLy6YWMz5E4sZV1Ro6CzmrdnGx28rY2N1bart0ikj+PZ7j/OXP5IkSeq2DJolSTpINfWNvLphZ2od5b3LXmzeWXfA18gKcOSgXowr7sO4oa9vzje8Xw+y3DjssOidn8N7ThjGe04Yxq7aBp5ctpHZCyt4YunGN/xyYMWmXfz8ieX8/InljB7Ui+kTizl/YhHHFvcxdO6GZpWV8+U/LUwtwZKdFfj6hcdy1cmj/O9BkiRJ3ZpBsyRJ+9HUFFm7bXdqU75lGxLB8urNu1Kbfh2IwYX5yeUuXt+c7+ghvSnIdeZjR9ErP4cLjx/GhccPY3ddA08u3cTsRRU8sWQje+obU/1Wbt7FL59czi+fXM4RA3umNhI8bpihc1fX0NjEf89eyo3PrEq19euZy/VXTOaUowdlsDJJkiSpYzBoliQJ2LarLrkxXFVyhnJi2YvddY1v/eKkHrnZjBna+w2b840tKmRg7/x2rFzp1jMvhwuOL+aC44vZU9fIU8s2MntRJY8v2fCG/x5Wb9nN9U+t4PqnVjBywN7QuYiJw/saOncx23fX8anb5/P08s2ptrFDC7nhqimMHNgzg5VJkiRJHYdBsySpW6ltaGT5xp2pMDkxW7nqDWutvpUQ4IiBvd6whvK4oj6MHNDTZS+6mB552ZyfXJ+5pr6Rp5Zt4qFFFTy2eAO7moXOa7bu5td/W8Gv/7aCEQN6MH1C4jUnlBg6d3avbKjmY7fO5bUtu1Nt5x43lB+/fxK98v0oLUmSJO3lp2NJUpcUY6R8257U+sl711JeuXkXjQex7sXAXnnJMDmx5MW44kKOGVJIjzyXvehuCnKzOW9CEedNKKKmvpG/v7KJhxZV8tjiDVTXNqT6rd26h9/8fSW/+ftKhvfrwfSJRZw/sZgTR/QzdO5k/vpyJZ+7a8EbfqnwmbOP4TNnH+MvlSRJkqR9GDRLkjq9HXvqWVZZzbLKKpYkA+VXKqvfEP69lfycLI5JLnvx+kzlPgwudNkLtVSQm827jiviXccVUdvQyD9e2czsRRU8ungD1TWv/3e3bvsebvjHKm74xyqG9S3g/OTyGieO6G9Q2YHFGPnlE8v530dfSbX1zMvmf2eewPkTizNYmSRJktRxGTRLkjqNuoYmVm5OLHuxpCIRLC+rrGb9jpqDus7IAT3fuDlfcSFHDOxFtsGfDkF+TjbvPHYo7zx2KLUNjTyzfDOzF1by15crqWoWOq/fUcPvnl7F755eRVGfAs6fWMT0icWUjjR07kh21zXw73e/xIMLK1JtJf17cMNVUxhf3CeDlUmSJEkdm0GzJKnDiTFSsaMmESgnw+RlldWs2LST+sYDX/aiX89cxg4tZHzx65vzjRla6Lqqajf5OdmcNW4oZ40bSt37JvLsis3MXljBXxdvYPvu+lS/yqoabnpmNTc9s5ohhfmcPyEROk85YoC/8Mig8m27+ditZSypqEq1vW30AK7/QCkDeuVlsDJJkiSp4/MnbUlSRlXX1PPKhr2b8lWn1lRuPhP0reRlZ3HUkN6MTy55MbYoES4PKcx3TVxlTF5OFmeMHcIZY4fw3cYm/rliC7MXVvDIy5VsaxY6b6yu5ZZ/vsYt/3yNwYX5nHdcInSedqSh8+H0/MotfOIP89i6qy7V9qGTR/HVC48lNzsrg5VJkiRJnUOI8cBnhqmlEELZ5MmTJ5eVlWW6FEnq0Boam1i1eVdqU769G/SVb9tzUNcZ3q8H44v3Bsp9GF9UyBGDehkEqdOob2zi+ZVbeTAZOjcPNpsb1DuPc48r4oJk6Jzjf+Pt5vfPvcY3//IyDcmNQnOzA9+5aAKXTRuZ4cokSZKkw6u0tJR58+bNizGWHuxrDZrbyKBZkvavsSny91c2cfucNfztlU3UNTQd8GsLC3KS6yj3Sc5QTix7UViQ244VS4dXQ2MTc1a9Hjpv3tl66DywVx7vSobObxtt6JwudQ1NfPP+l7n9+TWptkG98/j1B0uZcsSADFYmSZIkZYZBcwYZNEtSSxuqavjjC2u584W1rNv+5jOWc7ICRw3uzbjkLOW94XJx3wKXvVC30tgUmbNqK7MXVvDQoko276xttV//nrmcm1xe4+SjBjqb/xBt3lnLJ38/jzmrt6baJgzvw2+vnMKwfj0yWJkkSZKUOQbNGWTQLEkJTU2Rv7+6idufX8PjSzfS2NTy/y/FfQsYl1zyYlxRIeOKCxk9qDd5OQZlUnONTZG5q18PnTdWtx469+uZy7uOHcr0icWcevQgQ+cDtGjdDq67rewNvwh7zwnD+MElx9MjLzuDlUmSJEmZZdCcQQbNkrq7jdU13D23nDvmrGl1veX+PXOZOWUEl00dwejBvTNQodS5NTVFytZs48GXKnhoUQUbqloPnfv2yOWcY4dyQTJ09hc4rbv/xfX8+6wXqalPLOUTAnzx3HF8/B2j/RaFJEmSur22BM057VGQJKlra2qKPL18M7c/v4bHlmxIbaDV3ElHDuCKk0Zy3oQi8nOcISgdqqyswNQjBjD1iAF8/cJjmb92Gw++VMlDiyqo2FGT6rdjTz2zysqZVVZOYUFOKnQ+7ZhB/hskcd/630eX8X9Prki1Febn8LPLJ3HWuKEZrEySJEnqGgyaJUkHbFN1LXeXreXOOWtZs3V3i/P9euZyyeQSLp82kqOHOHtZSresrEDpqAGUjhrAVy8Yz4Ly7cx+KbG8RvNlIKprGvjTvHX8ad46CvNzeGdyeY23HzOIgtzuFzpX19TzubsW8NiSjam20YN68durpnivkiRJktLEoFmS9KaamiLPrtjC7XNe468vtz57edoRr89e7o4hlpQJWVmBySP7M3lkf75ywXheLN/B7IUVPPhSxRtD59oG7p2/jnvnr6N3fg5njx/C9InFvGPM4G7x73XV5l187Na5LN+4M9X2jjGD+fnlJ9K3R24GK5MkSZK6FoNmSVKrNu+sZVZZOXfOWcPqLS1nL/ftkcvFk4dzxbSRHDO0MAMVStorhMCkEf2YNKIf/3n+OBau28GDCyuYvbCCtVtfD5131jZw34L13LdgPb3ysjlr/FAumFjEGWOHdMnQ+e+vbOJTt8+jqqYh1Xbd6aP54nnjyM5yPWZJkiQpnQyaJUkpMUb+uWILf5izhr++XEl9Y8vZy1NG9eeKk0YyfWJxlwympM4uhMDxJf04vqQfXzpvHC+vr0qFzq81+6XRrrpG7n9xPfe/uJ6eedmcOW4IF0ws5syxQ+iR17n/bccY+d3Tq/jv2UvY+yWM/JwsfnDJ8bz3xOGZLU6SJEnqogyaJUls3VXHrLK13DFnLas272pxvrAgJ7X28tgiZy9LnUUIgQnD+zJheF++eO5YFldUMXthBbMXVr7h3/ruukYefCmx7EaP3GzOHDeY6ROLOWvcEHrmda6PizX1jXzl3kXcM6881VbUp4DfXlXK8SX9MleYJEmS1MV1rp8cJElpE2PkuZVbuX3OGh5ZVEldY1OLPpNH9uOKk0ZxwcTiTj/DUeruQggcN6wvxw3ryxfeNZalldWJNZ0XVrBy0+uh8576RmYvrGT2wkoKcrM4c+wQzp9YzNnjhtArv2N/dNxQVcN1t5WxYO32VNvkkf349QdLGdKnIHOFSZIkSd1Ax/5pQZKUdtt21XHPvHJun7PmDeHSXoX5Obxv8nCuOGkk44r6ZKBCSe0thMD44j6ML+7D588ZwysbdqaW12i+aV5NfRMPLarkoUWV5OdkccbYxEzns8cPpXcHC53nr9nGdbeVsbG6NtX2/iklfOe9E8jP8RdlkiRJUnvrWD8hSJLaRYyROasSs5cfWtj67OVJI/pxxUkjufD44k73VXlJhy6EwNiiQsYWFfL5c8bw6obqVOj8yobXQ+fahiYeeXkDj7y8gbycLN4xZjDTJxZx9vih9CnIzeA7gHvKyvnPexdS15C4t2VnBb56wXiuPuUIQnDTP0mSJOlwMEmQpC5s++467pm3jjvmrHnDLMW9eufn8N4Th3HFtFEcO8zZy5LgmKGFfHZoIZ995xiWb6xOLqNRwdLK6lSfuoYmHl28gUcXbyAvO4vTxwzi/AnFvPPYofTtcfhC54bGJr730FJ+9/SqVFvfHrlc/4HJnHr0oMNWhyRJkiSDZknqcmKMzH1tG3c8v4YHFlakZvg1d0JJX644aSTvPmGYs5cl7dfRQwr59NmFfPrsY1ixaScPLazgwYWVLKmoSvWpa2zisSUbeWzJRnKzA28/ZjDnTyjiXccW0bdn+4XOO3bX86k75vGPVzen2sYM7c0NV01h1MBe7TauJEmSpNaFGGOma+jUQghlkydPnlxWVpbpUiR1czt21/On+eXcMWfNG77uvlevvGwuOnE4V0wbyYThfTNQoaSuYtXmXcxOLq/x8vqqVvvkZgdOPXoQ0ycU867jhtKvZ17axn91QzUfu3Uuq7fsTrW969ih/PjSSR1u7WhJkiSpMyktLWXevHnzYoylB/tag+Y2MmiWlEkxRuat2c7tz6/hgZfWU9vK7OWJw1+fvWwAIyndXtuyK7W8xsJ1O1rtk5MVOOXoQUyfUMS7jitiQK9DD50fW7yBz961gJ21Dam2T599DJ89+xiyslyPWZIkSWoLg+YMMmiWlAk79tTz5/mJtZebr5u6V8+8bC6alFh7eWKJs5clHR5rt+5OzXR+sbz10Dk7K3DKUQM5f0Ix5x43lIG98w/o2jFGrn9qBT/66zL2fnztkZvNj99/AudPLE7XW5AkSZK6NYPmDDJolnS4xBhZsDYxe/n+l9ZTU99y9vJxw/pwxUkjec8JwygsOHwbcknSvsq37eahhZXMXlTB/DXbW+2TFeBtowcyfWIx500oYtB+QufddQ38+6yXePClilRbSf8e3HDVFMYXu5GpJEmSlC4GzRlk0CypvVXV1HPf/HX84fnWZy/3yM3mPScM44qTRnJ8SV9C8KvjkjqWddv38NDCCh5aVEnZa9ta7ZMVYNqRA7hgYjHnTihiSGFB6rUfu2Uui5ttQPi20QO4/gOlbVqCQ5IkSVJLBs0ZZNAsqT3EGHmpfAe3P7+Gv7y4nj31jS36jC9OzF6+aNIw+jh7WVInUbFjDw8trOShRRXMfW0brX0UDQGmHjGA048ZxE3PrGbLrrrUuatOHsXXLjyW3Oysw1i1JEmS1D20JWh2VyhJ6kB21jbw5/nruP35NW+YvbdXQW4W7z4+MXt50oh+zl6W1OkU9+3BNacdyTWnHcmGqhoeWljB7EWVvLB6ayp0jhHmrNrKnFVbU6/LzQ58+6IJXD5tZIYqlyRJkvRmDJolqQNYWL6D2+e8xn0L1rO7ruXs5XFFhcnZy8Pp28PZy5K6hqF9Crj61CO5+tQj2VhVw8MvVzJ7YQVzVm2lqdlM54G98vj1laVMPWJA5oqVJEmS9KYMmiUpQ3bWNvCXBeu5fc5rLFrXcvZyfk4WFyZnL08e6exlSV3bkD4FXHXyEVx18hFsqq7l4ZcreXzJBnrmZfOVC45leL8emS5RkiRJ0pswaJakw2zRuh3cPmcN981fx65WZi+PGdqbK6aN5H0nltC3p7OXJXU/gwvzufJto7jybaMyXYokSZKkA2TQLEmHwa7aBu5/cT13zFnDi+U7WpzPy8niwonFXHHSSEpH9Xf2siRJkiRJ6lQMmiWpHS1eX8Xtc17jz/PXs7O2ocX5owb34oqTRnHJ5OH065mXgQolSZIkSZLazqBZktJsd10DD7xYwe1z1rBg7fYW5/Nyspg+oYgrThrF1COcvSxJkiRJkjo/g2ZJSpOllVXc/vwa7p23jupWZi+PHtyLK6aN5JLJJfTv5exlSZIkSZLUdRg0S1Ib7Klr5IGXEmsvz1uzvcX5vOwszptQxBUnjeSkIwc4e1mSJEmSJHVJBs2SdAhe2VDN7c+v4U/zyqmqaTl7+chBvbh82ghmlI5ggLOXJUmSJElSF2fQLEkHqKa+kQdfquCOOWuY+9q2FudzswPnHpeYvXzy6IHOXpYkSZIkSd2GQbMkvYXlG6v5w/Nr+NO8dezYU9/i/KiBPbl82khmlJYwqHd+BiqUJEmSJEnKLINmSWpFTX0jDy+q5Pbn1zBn9dYW53Oy3jh7OSvL2cuSJEmSJKn7MmiWpGaWb9zJHXPWcM+8crbvbjl7eeSAnlw2bQQzS0cwuNDZy5IkSZIkSWDQLEnUNrw+e/n5Va3PXj7n2KFccdJITj1qkLOXJUmSJEmS9mHQLKnbWrkpMXt5Vlk521qZvVzSvweXTxvJzCklDCksyECFkiRJkiRJnYNBs6Rupa6hiUdeTsxe/ufKLS3OZ2cF3jl+CFecNIq3H+3sZUmSJEmSpANh0CypW1i9eVdq9vKWXXUtzg/v14PLpo7g/VNHMLSPs5clSZIkSZIOhkGzpC6rrqGJRxdv4PY5r/HM8pazl7MCnD0+sfby6ccMJtvZy5IkSZIkSYfEoFlSl7Nmy25un7OGWWVr2byz5ezlYX0LuHTqSC6dOoKivs5eliRJkiRJaiuDZkldQn1jE48t3sDtc9bwj1c3tzifFeCscUO44qSRvGPMEGcvS5IkSZIkpZFBs6RObe3W3dwxZw1/nFvO5p21Lc4X9Sng0qkjuHTqCIb165GBCiVJkiRJkro+g2ZJnU59YxOPL9mYnL28iRjfeD4EOHPsEC6fNpIzxw4mJzsrM4VKkiRJkiR1EwbNkjqN8m27uXPOWv44dy0bq1vOXh7aJ59Lp4zg0mkjGe7sZUmSJEmSpMPGoFlSh9bQ2MQTSxOzl//2Suuzl98xZjCXTxvJ2eOGOHtZkiRJkiQpAwyaJXVI67bv4a45a7hr7lo2VLWcvTy4MDl7eeoIRgzomYEKJUmSJEmStJdBs6QOo6GxiaeWbeL2OWt4atlGmlqZvfz2YwZzxbQRnD1+KLnOXpYkSZIkSeoQDJolZVzFjj2ptZcrdtS0OD+odz7vn1LC5dNGOntZkiRJkiSpAzJolpQRjU2Rv72ykdufX8MTS1vOXgZ4+zGDuHzaSM451tnLkiRJkiRJHZlBs6TDqnJHDX+cu5a7XljLuu17Wpwf2CuPmVNGcPm0EYwa2CsDFUqSJEmSJOlgGTRLaneNTZG/v7opNXu5sZXpy6cePZDLp43kXccWkZfj7GVJkiRJkqTOxKBZUrvZWJWYvXzHnNZnLw/olcfM0hIumzaSIwc5e1mSJEmSJKmzMmiWlFZNTZF/LN/M7c+/xmNLWp+9fPLogVx+0kjOPW4o+TnZGahSkiRJkiRJ6WTQLCktKnbs4U/z1nHnC2tYu7Xl7OX+PXOZUVrC5dNGMnpw7wxUKEmSJEmSpPZi0CzpkNXUN/LXxRuYVVbO069uopXJy5x05ACuOGkk5x5XREGus5clSZIkSZK6IoNmSQclxshL5Tu4u2wtf1mwnqqahhZ9+vXM5ZLJidnLRw9x9rIkSZIkSVJXZ9As6YBsrK7hz/PXMausnFc27GxxPgQ49ahBzCgt4bwJzl6WJEmSJEnqTgyaJe1XXUMTTyxNLI3x5LJNrW7sN3JAT2aUlnBJaQnD+/XIQJWSJEmSJEnKNINmSS0sXl/F3WVruW/BerbuqmtxvmdeNtMnFjOztIRpRw4ghJCBKiVJkiRJktRRGDRLAmDrrjruW7COu+eWs7iiqtU+044YwIwpJVwwsZhe+d4+JEmSJEmSlGBSJHVjDY1N/O2VTcwqK+exJRuob2y5NMawvgVcUlrCJZNLOGJQrwxUKUmSJEmSpI7OoFnqhpZvrObuueX8af46NlXXtjifn5PFeROKmFk6gpOPGkh2lktjSJIkSZIkaf8MmqVuYseeeu5/cT13l5Xz4trtrfaZNKIfM6eUcOHxw+jbI/fwFihJkiRJkqROy6BZ6sIamyLPLN/MrLJyHnm5ktqGphZ9Bhfmc/Hk4cwsLeHoIYUZqFKSJEmSJEmdnUGz1AWt3ryLWWXl3DOvnIodNS3O52YHzjl2KDNKSzj9mMHkZGdloEpJkiRJkiR1FQbNUhexs7aB2S9VcHfZWl5Yva3VPscN68PM0hIumjSc/r3yDnOFkiRJkiRJ6qoMmqVOrKkp8vyqrcwqK+ehRRXsrmts0WdArzzeO2k4M0pLOHZYnwxUKUmSJEmSpK7OoFnqhMq37eaesnXMmreWtVv3tDifnRU4c+wQZpSWcNa4IeTluDSGJEmSJEmS2o9Bs9RJ7Klr5OGXK5hVVs6zK7YQY8s+Y4b2ZmbpCN574nAGF+Yf/iIlSZIkSZLULRk0Sx1YjJF5a7Yzq2wtD7xYQXVtQ4s+fQpyuGjScGZOKWHi8L6EEDJQqSRJkiRJkrozg2apA9pQVcM988qZVVbOyk27WpwPAd5+zGBmlpZwzrFDKcjNzkCVkiRJkiRJUoJBs9RB1DY08ujiDcwqK+fvr2yiqZWlMY4c1IsZpSVcPHk4xX17HP4iJUmSJEmSpFYYNEsZFGNk0boq7i5by30L1rNjT32LPr3zc7jw+GJmlJZQOqq/S2NIkiRJkiSpwzFoljJg885a/jx/HbPKyllaWd1qn5NHD2TmlBLOm1BEzzz/qUqSJEmSJKnjMr2SDpP6xiaeWLqRWWXlPLl0Iw2trI1R0r8HM0pLuGRyCSMG9MxAlZIkSZIkSdLBM2iW2tnSyirunlvOn+evY8uuuhbne+Rmc/7EImaUlvC2IweSleXSGJIkSZIkSepcDJqldrB9dx33LVjPrLJyFq7b0WqfKaP6M3NKCdMnFlNYkHuYK5QkSZIkSZLSx6BZSpOGxib+8epmZpWV8+jiDdQ1NrXoU9SngEtKh3PJ5BJGD+6dgSolSZIkSZKk9DNoltpoxaad3D23nHvnl7OhqrbF+bycLN517FBmThnBaUcPItulMSRJkiRJktTFGDRLh6Cqpp4HXqxgVtla5q3Z3mqfE0r6MmPKCN5z/DD69nRpDEmSJEmSJHVdBs3SAWpqivxz5RbunruWh1+upKa+5dIYg3rnc/Hk4cwoLWHM0MIMVClJkiRJkiQdfgbN0ltYs2U3s8rWcs+8dazbvqfF+ZyswNnjhzCzdATvGDuY3OysDFQpSZIkSZIkZY5Bs9SKXbUNzF5Ywayycp5ftbXVPuOL+zCztISLJg1jYO/8w1yhJEmSJEmS1HEYNEtJMUZeWL2Nu+eu5cGFFeyua2zRp3/PXC6alFgaY8LwvhmoUpIkSZIkSep4DJrV7a3fvod7ysqZNa+c17bsbnE+K8AZY4cws7SEs8YPIT8nOwNVSpIkSZIkSR2XQbO6pZr6Rh55uZJZZeU8vXwzMbbsc9TgXsycMoKLTxzOkD4Fh79ISZIkSZIkqZMwaFa3EWNkwdrt3F1Wzv0vrqe6pqFFn8KCHN59wjBmlpYwaUQ/QggZqFSSJEmSJEnqXAya1eVtrKrhT/PXMausnOUbd7Y4HwKcdvQgZpSWcO5xRRTkujSGJEmSJEmSdDAMmtUl1TY08sSSjdxdVs7fXtlEY1PLtTFGDezJjMklXFxawvB+PTJQpSRJkiRJktQ1GDSrS1m0bgezysq5b8E6tu2ub3G+Z142F0wsZuaUEUw9or9LY0iSJEmSJElpYNCsTm/Lzlr+vGA9s8rKWVJR1Wqfk44cwMwpIzh/QhG98v3PXpIkSZIkSUonEzd1SvWNTfxt2SbuLlvLE0s3Ut/YcmmM4f16cMnk4VxSWsKogb0yUKUkSZIkSZLUPRg0q1N5ZUM1d89dy73z17N5Z22L8/k5WZw/oYiZU0Zw8uiBZGW5NIYkSZIkSZLU3gya1eHt2F3PX15cx6yycl4s39Fqn8kj+zGjdAQXnlBMn4Lcw1yhJEmSJEmS1L0ZNKtDamyKPL18M3fPXctfF2+grqGpRZ8hhflcPLmEGaUlHD2kdwaqlCRJkiRJkgQGzepgVm7ayayycv40bx2VVTUtzudlZ3HOsUOZMaWEtx89iJzsrAxUKUmSJEmSJKk5g2ZlXHVNPQ++VMGssnLmvrat1T4Th/dlRmkJ7zlhGP175R3mCiVJkiRJkiS9GYNmZURTU+S5VVuYNbechxZVsqe+sUWfgb3yeO+Jw5lRWsL44j4ZqFKSJEmSJEnSgTBo1mG1dutuZpWVc8+8csq37WlxPicrcOa4IcwsLeHMcUPIdWkMSZIkSZIkqcMzaFa7213XwEMLK5lVVs4/V25ptc/YoYXMnFLCe08czqDe+Ye5QkmSJEmSJEltYdCsdhFjpOy1bdw9t5wHF1aws7ahRZ++PXK5aNIwZpaOYMLwPoQQMlCpJEmSJEmSpLYyaFZaVezYw5/mrWNWWTmrNu9qcT4rwOljBjOjtIR3jh9KQW52BqqUJEmSJEmSlE4GzWqzmvpGHl28gbvLynn61U00xZZ9Rg/qxYwpJVx8YglFfQsOf5GSJEmSJEmS2o1Bsw5JjJGXyndwd9la/rJgPVU1LZfG6J2fw7tPKGZG6Qgmj+zn0hiSJEmSJElSF2XQrIOysbqGP89PLI3xyoadrfY55aiBzJxSwnnHFdMjz6UxJEmSJEmSpK7OoFkHLMbIxdc/S/m2PS3OjRjQgxmTR3BJ6XBK+vfMQHWSJEmSJEmSMsWgWQcshMB7ThjG9U+tAKBHbjbTJxYzc0oJ044YQFaWS2NIkiRJkiRJ3ZFBsw7KjNISXli9lZmlI5h+fDG98/1PSJIkSZIkSeruTAl1UEYP7s3dHz8l02VIkiRJkiRJ6kCyMl2AJEmSJEmSJKlzM2iWJEmSJEmSJLWJQbMkSZIkSZIkqU0MmiVJkiRJkiRJbWLQLEmSJEmSJElqE4NmSZIkSZIkSVKbGDRLkiRJkiRJktrEoFmSJEmSJEmS1CYGzZIkSZIkSZKkNjFoliRJkiRJkiS1iUGzJEmSJEmSJKlNOlXQHEIYGEL4aAjh3hDC8hDCnhDCjhDC0yGEj4QQWryfEEJhCOG7IYSlIYSaEMK2EMIjIYSzM/EeJEmSJEmSJKmrycl0AQdpJvAroAJ4ElgDDAUuBv4fcH4IYWaMMQKEEPoDTwPHAi8DvwZ6AxcBj4UQPhpj/N1hfxeSJEmSJEmS1IV0tqD5FeA9wIMxxqa9jSGELwNzgEtIhM73JE99k0TI/Cfg0hhjQ7P+c4FfhBAeiTGWH7Z3IEmSJEmSJEldTKdaOiPG+ESM8f7mIXOyvZLEbGWAM5qdel/y+et7Q+Zk/43Aj4EewDXtV7EkSZIkSZIkdX2dbUbzm6lPPjc0aytKPq9spf/etrOBb7/VxUMIZfs5Ne6AqpMkSZIkSZKkLqpTzWjenxBCDnBV8vDhZqc2J5+PbOVlo5PPY9urLkmSJEmSJEnqDrrKjObvAxOA2THGR5q1Pwh8FPhWCOGyGGMjQAhhMPC5ZJ/+BzJAjLG0tfbkTOfJh1q4JEmSJEmSJHV2nT5oDiF8Gvg3YClw5T6nvw6cC8wAFoQQHgd6ARcB64CRQBOSJEmSJEmSpEPWqZfOCCF8CvgZsBg4M8a4tfn5GGMFMBX4P6AQ+CRwAXAXMDPZbeNhK1iSJEmSJEmSuqBOO6M5hPBZ4CfAIuDsGGOrgXGMcQPwqeSj+evPSv7xhXYsU5IkSZIkSZK6vE45ozmE8B8kQuYFJGYyH8qs5L2bB96errokSZIkSZIkqTvqdEFzCOFrJDb/KyMxk3nzm/TNCiH0bqX9ShJB87PAn9upVEmSJEmSJEnqFjrV0hkhhA8B3wYagX8Anw4h7NttdYzx5uSfewIbQgiPAitIbPx3KnAysASYGWN0M0BJkiRJkiRJaoNOFTQDRyafs4HP7qfP34Cbk3+uBe4ETgPOSba9CnwF+GmMcXe7VClJkiRJkiRJ3UinCppjjN8EvnkQ/euBj7RXPZIkSZIkSZKkTrhGsyRJkiRJkiSpYzFoliRJkiRJkiS1iUGzJEmSJEmSJKlNDJolSZIkSZIkSW1i0CxJkiRJkiRJapMQY8x0DZ1aCGFLjx49BowfPz7TpUiSJEmSJEnSIVuyZAl79uzZGmMceLCvNWhuoxDCKqAPsDrDpUgdwbjk89KMViGps/HeIelged+QdCi8d0g6WN3xvnEEUBVjPPJgX2jQLCltQghlADHG0kzXIqnz8N4h6WB535B0KLx3SDpY3jcOjms0S5IkSZIkSZLaxKBZkiRJkiRJktQmBs2SJEmSJEmSpDYxaJYkSZIkSZIktYlBsyRJkiRJkiSpTUKMMdM1SJIkSZIkSZI6MWc0S5IkSZIkSZLaxKBZkiRJkiRJktQmBs2SJEmSJEmSpDYxaJYkSZIkSZIktYlBsyRJkiRJkiSpTQyaJUmSJEmSJEltYtAsSZIkSZIkSWoTg2apmwkhDAwhfDSEcG8IYXkIYU8IYUcI4ekQwkdCCK3eF0IIp4QQZocQtiZf81II4bMhhOxW+vYLIfx7COEPIYTFIYSGEEIMIbzzLWrLDiF8LnntPcmxZocQTknX+5d0aDrivSMknBdC+EUIYUEIYVsIoSaEsCyE8NMQwtB0/z1IOnAd8b6xn/EGhRAqkq97ui3vWVLbdfR7RwihKITwk+TnjT3Jzx/zQgjfT8f7l3TwOvJ9I4RwZAjh1yGEpSGE3SGEDSGEf4YQrg0h5KXr76CjCDHGTNcg6TAKIXwc+BVQATwJrAGGAhcDfYF7gJmx2c0hhHBRsr0GuAvYCrwbGAvMijHO3GeMScD85GE5kJsc45wY42P7qSsAfwRmAMuA+4EBwKVAAXBJjPG+tr17SYeqI947QggFwB6gDvg78CKQDZwFHA9sAN4eY3y1zX8Bkg5aR7xv7KfOe4B3Ab2BZ2KMpx3C25WUJh353hFCOBV4AOgJzCbxc0sP4GjguBjjEYf+ziUdqo563wghTE3W0wN4GFgE9EmOMxz4K3Be7ErhbIzRhw8f3ehBIoB5N5C1T3sRiZtxJBHq7m3vA2wEaoEpzdoLgGeT/S/b51r9gbOBAcnjm5P93vkmdV2e7PMMUNCsfWpy7I1AYab//nz46K6PjnjvIPHh7itA/33as4BfJ197f6b/7nz46K6PjnjfaKXGq5L9P5F8fjrTf28+fHT3R0e9dyTH3wysBsa0cj430393Pnx010cHvm88mOzzoX3aewEvJ8+dnum/v3Q+XDpD6mZijE/EGO+PMTbt015JIpgBOKPZqRnAYODOGOPcZv1rgK8mDz+xz7W2xRgfjzFuPYjS9l7jq8lr773WCyR+uzg4WYukDOiI944YY32M8bsxxm37tDcB326lJkmHUUe8bzQXQhgJ/Bz4HfDQwb5eUvvowPeOLwMDgY/HGF9ppe76g7iWpDTqwPeN0cnnv+xzrV3A48nDwQdxvQ7PoFlSc3s/HDU0azsr+fxwK/3/DuwGTgkh5B/qoMmvv5+SvNY/Wumy94e/s1o5JynzMnLvOISaJHUcGb1vJJfsuhnYAXy+rdeTdNhk8t5xObANeCSEcGwI4V9DCP8RQpgRQujdxmtLaj+ZvG+8nHy+oHljCKFnsobdwD/bOEaHYtAsCYAQQg6Jr4/CG2+2Y5PPrf3WvgFYBeTw+m/qDsVRJNZVXZm85r72rq86pg1jSGoHGb53vJlrWqlJUgfQQe4bnyUxs+kjMcaqNFxPUjvL5L0jhHAkMAhYDvyERHj0c+D7wN3A6hDC9EO9vqT20QE+c3yVxLrRN4cQ/hJC+H4I4XpgKYk9qWbEGNe3cYwOxaBZ0l7fByYAs2OMjzRr75t83rGf1+1t79eGsQ/HGJLaRybvHa1KbrrxDaCa17/6JqnjyOh9I4RwLPDfwK/jAW4YKKlDyOS9Y0jyeTJwLfCpZNsw4IvJGu4JIYxvwxiS0i+jnzlijEtJ7Dv1LIk1pP+DxJIcRcDvgefacv2OyKBZEiGETwP/RuK3aldmuBxJnURHvHeEEMYA95PYKPCDMcYVGS5JUjOZvm+EEHKB20jMLvri4R5f0qHJ9L2D17OTbODbMcb/izFuijFWxBh/SGJ2cwGJb0tI6gA6wH2DEMKJJELmHsDbgUJgBPB1Ekt3PR9C6Lv/K3Q+Bs1SNxdC+BTwM2AxcGYrC9vv/U3e/m5+e9u3t6GMwzGGpDTqIPeOfWsaAzxJ4mtol8UY//IWL5F0GHWQ+8Z/AicCH44x7mzDdSQdJh3k3tH8tfe2cn5v27Q2jCEpTTrCfSO5bMcfSWz29+4Y49Mxxp0xxvIY4/eBXwDHAJ871DE6IoNmqRsLIXyWxM1tEYmbb2Ur3ZYln1usj5y8cR5JYlH9lW0oZQXQCIxOXnNfxySfW6yfJOnw60D3jubXHA88RWL9xJkxxnvScV1J6dGB7huTgQA8FUKIex8k1mIEODXZtr0NY0hKkw5071jB6xuJbW/l/Lbkc482jCEpDTrQfWMccDSwZD81PJl8Lm3DGB2OQbPUTYUQ/oPERhYLSNx8N+6n6xPJ5/NaOXc60BN4NsZYe6i1xBhrSHydpCeJr5Ps6/x9apGUIR3p3tGspokkQuYBwMUxxvvaek1J6dPB7huPAr9r5XFX8vyG5PGtbRhDUhp0pHtHjLEO+EfycEIrXfa2rWrlnKTDpCPdN4D85POg/ZwfnHyua8MYHY5Bs9QNhRC+RmJR/DLg7Bjj5jfpPgvYDFwWQpjS7BoFwH8lD3+VhrL2XuO/ktfeO85U4FJgE+AMRSmDOuK9I4QwicRsgELgohjjg229pqT06Wj3jeS6qh/d9wF8KdllebLt020ZR1LbdLR7R9Ivks/fDiH0ajZOP+BrycM70jCOpEPQAe8bi0h8A2JkCOGj+9TaD/hC8vDxNo7ToYQYY6ZrkHQYhRA+BNxMYqmKX9D6LqurY4w3N3vNe0nciGuAO4GtwHuAscn298d9biYhhB/x+m/uTgOOAv5KYvMdgD/HGP/crH8gsX7RDBKL9d8PDCQRMhcAlzhLUcqcjnjvCCH0B5aTmMn8OPD0fsr/aYxx+wG+VUlp0hHvG29S6xEkZiI+E2M87cDeoaT20JHvHSGEG4EPk7hfPERic8ALgeEkJsW8P8bYdNBvWlKbdNT7RrKum0gs2/U4MB/onxxnMPAccEY6vuXZURg0S91MCOGbwDfeotvfYoxn7PO6U4GvACeTCH6XAzcCP48xNrYyzmpg1JuM8a0Y4zf3eU0O8K/ANSTWMqoB/gn8V4zx2beoWVI76oj3jmbB0Fs5Msa4+gD6SUqjjnjfeJNaj8CgWeoQOvK9Izk55iPAdcCxJMKjxSSCpF8ZMkuZ0cHvG6cDn02OMQioJbFG9N0kJsTUvEXdnYpBsyRJkiRJkiSpTVyjWZIkSZIkSZLUJgbNkiRJkiRJkqQ2MWiWJEmSJEmSJLWJQbMkSZIkSZIkqU0MmiVJkiRJkiRJbWLQLEmSJEmSJElqE4NmSZIkSZIkSVKbGDRLkiRJkiRJktrEoFmSJEmSJEmS1CYGzZIkSZIkSZKkNjFoliRJkiRJkiS1iUGzJEmSJEmSJKlNDJolSZIkSZIkSW1i0CxJkiRJkiRJahODZkmSJEmSJElSmxg0S5IkSWkWQhgXQoghhCffpM/CEEJ9CKG4Wdu5IYTZIYTNIYTaEMKKEMIPQwj9Wnn9mSGE34YQFocQqkIIe0IIi0II3wghFLTS/5vJms4IIVwRQng+hLAzhLA6Xe9bkiRJ3VdOpguQJEmSupoY49JkyHxmCGFMjPGV5udDCKcAE4B7YowVybZvAN8EtgIPABuB44EvANNDCCfHGKuaXeY/gHHAs8CDQAFwavIaZ4QQ3hljbGylvH8DzgHuB54E+qblTUuSJKlbM2iWJEmS2sf1wJnAtSTC4uauTT7/BhKzk0kExP8EpscYt+/tGEK4GrgJ+BbwuWbX+CSwKsYYm184hPAd4KvADOCuVuo6Czg5xjj/EN6TJEmS1CqXzpAkSZLax5+BCuDqEEL+3sbkMhjvB1YAjyWbP518/ljzkBkgxngzsAD4wD7tK/cNmZN+knw+dz91/daQWZIkSenmjGZJkiSpHcQYG0IINwBfBy4Bbk+euhLoQSLw3RsUnwzUAzNDCDNbuVweMDiEMDDGuAUghNAL+AzwPmAMUAiEZq8Zvp/S5hz6u5IkSZJaZ9AsSZIktZ/fAl8BruP1oPlaoI7Echh7DSTx2fwbb3G93sCWEEIu8AQwDVhEYomMTSTCapLXyW/1ClB5cG9BkiRJemsGzZIkSVI7iTGuCyH8BXhfCGEcMIDEJoB3xRg3Neu6A8iKMQ44wEtfRCJkvjnG+OHmJ0IIxbx5YN3achuSJElSm7hGsyRJktS+rk8+X8c+mwA28xzQP4Rw3AFe8+jk859aOfeOgytPkiRJajuDZkmSJKl9PQ68AnyIxCaAy2KMT+7TZ+8GfjeEEIbte4EQQq8QwtuaNa1OPp+xT7/RwA/SULMkSZJ0UFw6Q5IkSWpHMcYYQvg18ONk029b6fN4COFLwPeAV0MIs4FVJNZkHkVilvLTwHnJl9wPLAc+H0KYCMwHRgIXAg8m/yxJkiQdNs5oliRJktrfzUATUAPc0lqHGOMPgNNJBMWnAp8FZgLDSYTTX23WdxdwFokNBo8DPg0cD3wH+GD7vAVJkiRp/0KM7gUiSZIktacQwhnAk8DvY4xXZrYaSZIkKf2c0SxJkiS1vy8mn3+Z0SokSZKkduIazZIkSVI7SK6dfCFQCpwPPBBjfD6zVUmSJEntw6BZkiRJah+lwH8DVcDdwCczW44kSZLUflyjWZIkSZIkSZLUJq7RLEmSJEmSJElqE4NmSZIkSZIkSVKbGDRLkiRJkiRJktrEoFmSJEmSJEmS1CYGzZIkSZIkSZKkNjFoliRJkiRJkiS1iUGzJEmSJEmSJKlNDJolSZIkSZIkSW1i0CxJkiRJkiRJahODZkmSJEmSJElSmxg0S5IkSZIkSZLaxKBZkiRJkiRJktQmBs2SJEmSJEmSpDb5/872FSzv5PDxAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "execution_count": 14,
     "metadata": {
      "image/png": {
       "height": 440,
       "width": 717
      },
      "needs_background": "light"
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_packaging_waste \\\n",
    "    .query(\"geo == 'EU28' and unit == 'KG_HAB' and wst_oper == 'GEN' and waste == 'W150102'\") \\\n",
    "    .plot(\n",
    "        x=\"year\",\n",
    "        y=\"value\",\n",
    "        ylabel=\"waste generation [KG/person]\",\n",
    "        title=\"Plastic packaging waste generation for EU28 over the past 10 years\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": "<html>\n<head><meta charset=\"utf-8\" /></head>\n<body>\n    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n        <script src=\"https://cdn.plot.ly/plotly-2.1.0.min.js\"></script>                <div id=\"39cb3e37-0191-462c-b806-9a2749ca1d82\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"39cb3e37-0191-462c-b806-9a2749ca1d82\")) {                    Plotly.newPlot(                        \"39cb3e37-0191-462c-b806-9a2749ca1d82\",                        [{\"alignmentgroup\":\"True\",\"hovertemplate\":\"waste=Paper and cardboard packaging<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Paper and cardboard packaging\",\"marker\":{\"color\":\"#636efa\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Paper and cardboard packaging\",\"offsetgroup\":\"Paper and cardboard packaging\",\"orientation\":\"v\",\"showlegend\":true,\"textposition\":\"auto\",\"type\":\"bar\",\"x\":[2009,2010,2011,2012,2013,2014,2015,2016,2017,2018],\"xaxis\":\"x\",\"y\":[59.39,62.12,63.26,62.48,63.87,67.14,68.48,69.35,70.68,71.53],\"yaxis\":\"y\"},{\"alignmentgroup\":\"True\",\"hovertemplate\":\"waste=Plastic packaging<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Plastic packaging\",\"marker\":{\"color\":\"#EF553B\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Plastic packaging\",\"offsetgroup\":\"Plastic packaging\",\"orientation\":\"v\",\"showlegend\":true,\"textposition\":\"auto\",\"type\":\"bar\",\"x\":[2009,2010,2011,2012,2013,2014,2015,2016,2017,2018],\"xaxis\":\"x\",\"y\":[29.12,29.44,29.78,29.93,29.65,30.34,31.27,31.91,32.84,33.45],\"yaxis\":\"y\"},{\"alignmentgroup\":\"True\",\"hovertemplate\":\"waste=Wooden packaging<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Wooden packaging\",\"marker\":{\"color\":\"#00cc96\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Wooden packaging\",\"offsetgroup\":\"Wooden packaging\",\"orientation\":\"v\",\"showlegend\":true,\"textposition\":\"auto\",\"type\":\"bar\",\"x\":[2009,2010,2011,2012,2013,2014,2015,2016,2017,2018],\"xaxis\":\"x\",\"y\":[22.72,23.57,24.11,23.32,23.41,25.39,26.28,27.29,28.5,26.94],\"yaxis\":\"y\"},{\"alignmentgroup\":\"True\",\"hovertemplate\":\"waste=Metallic packaging<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Metallic packaging\",\"marker\":{\"color\":\"#ab63fa\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Metallic packaging\",\"offsetgroup\":\"Metallic packaging\",\"orientation\":\"v\",\"showlegend\":true,\"textposition\":\"auto\",\"type\":\"bar\",\"x\":[2009,2010,2011,2012,2013,2014,2015,2016,2017,2018],\"xaxis\":\"x\",\"y\":[9.06,9.06,9.18,9.04,8.92,8.91,8.96,8.9,9.21,9.06],\"yaxis\":\"y\"},{\"alignmentgroup\":\"True\",\"hovertemplate\":\"waste=Aluminium packaging<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Aluminium packaging\",\"marker\":{\"color\":\"#FFA15A\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Aluminium packaging\",\"offsetgroup\":\"Aluminium packaging\",\"orientation\":\"v\",\"showlegend\":true,\"textposition\":\"auto\",\"type\":\"bar\",\"x\":[2009,2010,2011,2012,2013,2014,2015,2016,2017,2018],\"xaxis\":\"x\",\"y\":[null,null,null,null,null,null,null,null,null,null],\"yaxis\":\"y\"},{\"alignmentgroup\":\"True\",\"hovertemplate\":\"waste=Aluminium from incineration bottom ash (IBA)<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Aluminium from incineration bottom ash (IBA)\",\"marker\":{\"color\":\"#19d3f3\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Aluminium from incineration bottom ash (IBA)\",\"offsetgroup\":\"Aluminium from incineration bottom ash (IBA)\",\"orientation\":\"v\",\"showlegend\":true,\"textposition\":\"auto\",\"type\":\"bar\",\"x\":[2009,2010,2011,2012,2013,2014,2015,2016,2017,2018],\"xaxis\":\"x\",\"y\":[null,null,null,null,null,null,null,null,null,null],\"yaxis\":\"y\"},{\"alignmentgroup\":\"True\",\"hovertemplate\":\"waste=Steel packaging<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Steel packaging\",\"marker\":{\"color\":\"#FF6692\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Steel packaging\",\"offsetgroup\":\"Steel 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packaging<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Glass packaging\",\"marker\":{\"color\":\"#FF97FF\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Glass packaging\",\"offsetgroup\":\"Glass packaging\",\"orientation\":\"v\",\"showlegend\":true,\"textposition\":\"auto\",\"type\":\"bar\",\"x\":[2009,2010,2011,2012,2013,2014,2015,2016,2017,2018],\"xaxis\":\"x\",\"y\":[31.94,31.63,32.2,31.18,30.98,30.99,31.16,31.83,32.15,33.12],\"yaxis\":\"y\"},{\"alignmentgroup\":\"True\",\"hovertemplate\":\"waste=Other packaging<br>year=%{x}<br>value=%{y}<extra></extra>\",\"legendgroup\":\"Other packaging\",\"marker\":{\"color\":\"#FECB52\",\"pattern\":{\"shape\":\"\"}},\"name\":\"Other packaging\",\"offsetgroup\":\"Other packaging\",\"orientation\":\"v\",\"showlegend\":true,\"textposition\":\"auto\",\"type\":\"bar\",\"x\":[2009,2010,2011,2012,2013,2014,2015,2016,2017,2018],\"xaxis\":\"x\",\"y\":[null,null,0.57,0.41,null,null,null,null,null,null],\"yaxis\":\"y\"}],                        {\"barmode\":\"relative\",\"legend\":{\"title\":{\"text\":\"waste\"},\"tracegroupgap\":0},\"margin\":{\"t\":60},\"template\":{\"data\":{\"bar\":[{\"error_x\":{\"color\":\"#2a3f5f\"},\"error_y\":{\"color\":\"#2a3f5f\"},\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"bar\"}],\"barpolar\":[{\"marker\":{\"line\":{\"color\":\"#E5ECF6\",\"width\":0.5},\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"barpolar\"}],\"carpet\":[{\"aaxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"baxis\":{\"endlinecolor\":\"#2a3f5f\",\"gridcolor\":\"white\",\"linecolor\":\"white\",\"minorgridcolor\":\"white\",\"startlinecolor\":\"#2a3f5f\"},\"type\":\"carpet\"}],\"choropleth\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"choropleth\"}],\"contour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"contour\"}],\"contourcarpet\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"contourcarpet\"}],\"heatmap\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmap\"}],\"heatmapgl\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"heatmapgl\"}],\"histogram\":[{\"marker\":{\"pattern\":{\"fillmode\":\"overlay\",\"size\":10,\"solidity\":0.2}},\"type\":\"histogram\"}],\"histogram2d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2d\"}],\"histogram2dcontour\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"histogram2dcontour\"}],\"mesh3d\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"type\":\"mesh3d\"}],\"parcoords\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"parcoords\"}],\"pie\":[{\"automargin\":true,\"type\":\"pie\"}],\"scatter\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter\"}],\"scatter3d\":[{\"line\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatter3d\"}],\"scattercarpet\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattercarpet\"}],\"scattergeo\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergeo\"}],\"scattergl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattergl\"}],\"scattermapbox\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scattermapbox\"}],\"scatterpolar\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolar\"}],\"scatterpolargl\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterpolargl\"}],\"scatterternary\":[{\"marker\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"type\":\"scatterternary\"}],\"surface\":[{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"},\"colorscale\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"type\":\"surface\"}],\"table\":[{\"cells\":{\"fill\":{\"color\":\"#EBF0F8\"},\"line\":{\"color\":\"white\"}},\"header\":{\"fill\":{\"color\":\"#C8D4E3\"},\"line\":{\"color\":\"white\"}},\"type\":\"table\"}]},\"layout\":{\"annotationdefaults\":{\"arrowcolor\":\"#2a3f5f\",\"arrowhead\":0,\"arrowwidth\":1},\"autotypenumbers\":\"strict\",\"coloraxis\":{\"colorbar\":{\"outlinewidth\":0,\"ticks\":\"\"}},\"colorscale\":{\"diverging\":[[0,\"#8e0152\"],[0.1,\"#c51b7d\"],[0.2,\"#de77ae\"],[0.3,\"#f1b6da\"],[0.4,\"#fde0ef\"],[0.5,\"#f7f7f7\"],[0.6,\"#e6f5d0\"],[0.7,\"#b8e186\"],[0.8,\"#7fbc41\"],[0.9,\"#4d9221\"],[1,\"#276419\"]],\"sequential\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]],\"sequentialminus\":[[0.0,\"#0d0887\"],[0.1111111111111111,\"#46039f\"],[0.2222222222222222,\"#7201a8\"],[0.3333333333333333,\"#9c179e\"],[0.4444444444444444,\"#bd3786\"],[0.5555555555555556,\"#d8576b\"],[0.6666666666666666,\"#ed7953\"],[0.7777777777777778,\"#fb9f3a\"],[0.8888888888888888,\"#fdca26\"],[1.0,\"#f0f921\"]]},\"colorway\":[\"#636efa\",\"#EF553B\",\"#00cc96\",\"#ab63fa\",\"#FFA15A\",\"#19d3f3\",\"#FF6692\",\"#B6E880\",\"#FF97FF\",\"#FECB52\"],\"font\":{\"color\":\"#2a3f5f\"},\"geo\":{\"bgcolor\":\"white\",\"lakecolor\":\"white\",\"landcolor\":\"#E5ECF6\",\"showlakes\":true,\"showland\":true,\"subunitcolor\":\"white\"},\"hoverlabel\":{\"align\":\"left\"},\"hovermode\":\"closest\",\"mapbox\":{\"style\":\"light\"},\"paper_bgcolor\":\"white\",\"plot_bgcolor\":\"#E5ECF6\",\"polar\":{\"angularaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"radialaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"scene\":{\"xaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"yaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"},\"zaxis\":{\"backgroundcolor\":\"#E5ECF6\",\"gridcolor\":\"white\",\"gridwidth\":2,\"linecolor\":\"white\",\"showbackground\":true,\"ticks\":\"\",\"zerolinecolor\":\"white\"}},\"shapedefaults\":{\"line\":{\"color\":\"#2a3f5f\"}},\"ternary\":{\"aaxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"baxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"},\"bgcolor\":\"#E5ECF6\",\"caxis\":{\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\"}},\"title\":{\"x\":0.05},\"xaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2},\"yaxis\":{\"automargin\":true,\"gridcolor\":\"white\",\"linecolor\":\"white\",\"ticks\":\"\",\"title\":{\"standoff\":15},\"zerolinecolor\":\"white\",\"zerolinewidth\":2}}},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"year\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"value\"}}},                        {\"responsive\": true}                    ).then(function(){\n                            \nvar gd = document.getElementById('39cb3e37-0191-462c-b806-9a2749ca1d82');\nvar x = new MutationObserver(function (mutations, observer) {{\n        var display = window.getComputedStyle(gd).display;\n        if (!display || display === 'none') {{\n            console.log([gd, 'removed!']);\n            Plotly.purge(gd);\n            observer.disconnect();\n        }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n    x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif (outputEl) {{\n    x.observe(outputEl, {childList: true});\n}}\n\n                        })                };                            </script>        </div>\n</body>\n</html>"
     },
     "execution_count": 17,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ = df_packaging_waste.query(\"geo == 'EU28' and unit == 'T' and wst_oper == 'GEN' and waste != 'W1501'\").replace(codes[\"WASTE\"])  # compare with KG_HAB\n",
    "\n",
    "px.bar(df_, x=\"year\", y=\"value\", color=\"waste\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# task: use plotly express animation feature to show this for different countries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Question 2:\n",
    "![](https://www.europarl.europa.eu/resources/library/images/20181130PHT20668/20181130PHT20668-cl.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "df_packaing_waste_2016 = df_packaging_waste.query(\"geo != 'EU27_2020' and year == 2016 and waste in ['W150102'] and unit in ['T', 'KG_HAB'] and wst_oper in ['GEN']\").reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": "<html>\n<head><meta charset=\"utf-8\" /></head>\n<body>\n    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n        <script src=\"https://cdn.plot.ly/plotly-2.1.0.min.js\"></script>                <div id=\"c36a194c-bde0-4c3f-9e89-c36953ac5ba3\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"c36a194c-bde0-4c3f-9e89-c36953ac5ba3\")) {                    Plotly.newPlot(                        \"c36a194c-bde0-4c3f-9e89-c36953ac5ba3\",                        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     },
     "execution_count": 26,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig = px.bar(\n",
    "    df_packaing_waste_2016,\n",
    "    x=\"geo\",\n",
    "    y=\"value\",\n",
    "    color=\"unit\",\n",
    "    facet_col=\"unit\",\n",
    "    title=\"Plastic waste generation in EU for 2016 by Tonne and Kilograms per person.\",\n",
    ")\n",
    "\n",
    "fig.update_yaxes(matches=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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\"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Plastic waste generation for EU28 in 2016\"}, \"xaxis\": {\"anchor\": \"y\", \"categoryarray\": [\"IE\", \"EE\", \"LU\", \"IS\", \"DE\", \"DK\", \"NO\", \"PT\", \"IT\", \"UK\", \"AT\", \"ES\", \"FR\", \"MT\", \"EU28\", \"HU\", \"BE\", \"NL\", \"PL\", \"SE\", \"LT\", \"SI\", \"CZ\", \"FI\", \"SK\", \"LI\", \"LV\", \"CY\", \"RO\", \"EL\", \"BG\", \"HR\"], \"categoryorder\": \"array\", \"domain\": [0.0, 0.94], \"tickangle\": 0}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0]}, \"yaxis2\": {\"anchor\": \"x\", \"overlaying\": \"y\", \"side\": \"right\"}},                        {\"responsive\": true}                    ).then(function(){\n                            \nvar gd = document.getElementById('390247fd-906e-4ebd-8819-bcd726ff5e32');\nvar x = new MutationObserver(function (mutations, observer) {{\n        var display = window.getComputedStyle(gd).display;\n        if (!display || display === 'none') {{\n            console.log([gd, 'removed!']);\n            Plotly.purge(gd);\n            observer.disconnect();\n        }}\n}});\n\n// Listen for the removal of the full notebook 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     },
     "execution_count": 120,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "\n",
    "df1 = df_packaing_waste_2016.query(\"unit == 'T'\")\n",
    "df2 = df_packaing_waste_2016.query(\"unit == 'KG_HAB'\")\n",
    "sorting_order = df2.sort_values(\"value\", ascending=False).geo.tolist()\n",
    "\n",
    "\n",
    "# Create figure with secondary y-axis\n",
    "fig = make_subplots(specs=[[{\"secondary_y\": True}]])\n",
    "\n",
    "\n",
    "fig.add_trace(\n",
    "    go.Bar(\n",
    "        x = df1.geo,\n",
    "        y = df1.value,\n",
    "        name = \"Tonne\",\n",
    "        offsetgroup=1,\n",
    "        marker_color=\"darkgreen\"\n",
    "    )\n",
    " )\n",
    "\n",
    "fig.add_trace(\n",
    "    go.Bar(\n",
    "        x = df2.geo,\n",
    "        y = df2.value,\n",
    "        name = \"Kg/person\",\n",
    "        offsetgroup=2,\n",
    "        marker_color=\"orange\"\n",
    "    ),\n",
    "    secondary_y=True\n",
    " )\n",
    "\n",
    "# Add figure title\n",
    "fig.update_layout(\n",
    "    title_text=\"Plastic waste generation for EU28 in 2016\",\n",
    "    barmode='group',\n",
    "    xaxis_tickangle=0,\n",
    "    bargap=0.1, # gap between bars of adjacent location coordinates.\n",
    "    bargroupgap=0.1, # gap between bars of the same location coordinate.\n",
    "    xaxis={'categoryorder': 'array', 'categoryarray': sorting_order}\n",
    ")\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "df_packaging_waste_rcy_rate = df_packaging_waste.query(\"geo != 'EU27_2020' and year == 2016 and waste=='W150102' and wst_oper == 'RCY' and unit == 'PC'\").reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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waste recycling rate in the EU for 2016\"},\"xaxis\":{\"anchor\":\"y\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"geo\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"value\"}}},                        {\"responsive\": true}                    ).then(function(){\n                            \nvar gd = document.getElementById('af4f51d8-8a29-4b11-9708-27cf55f5367d');\nvar x = new MutationObserver(function (mutations, observer) {{\n        var display = window.getComputedStyle(gd).display;\n        if (!display || display === 'none') {{\n            console.log([gd, 'removed!']);\n            Plotly.purge(gd);\n            observer.disconnect();\n        }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n    x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = gd.closest('.output');\nif 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     },
     "execution_count": 29,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "px.bar(\n",
    "    df_packaging_waste_rcy_rate.sort_values(\"value\"), \n",
    "    x=\"geo\", y=\"value\",\n",
    "    color=\"value\",\n",
    "    color_continuous_scale=px.colors.diverging.curl[::-1],\n",
    "    color_continuous_midpoint=df_packaging_waste_rcy_rate.query(\"geo == 'EU28'\").value[0],\n",
    "    title=\"Plastic waste recycling rate in the EU for 2016\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# TODO: map"
   ]
  }
 ],
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   "display_name": "Python 3 (system-wide)",
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