Predavanje 3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predavanje 3\n",
    "## Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dohvaćanje podataka"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Na https://www.hnb.hr/temeljne-funkcije/monetarna-politika/tecajna-lista/tecajna-lista kliknuti Pretraživanje, i odabrati:\n",
    "* Mjesečni prosjeci\n",
    "* Sve godine\n",
    "* Svi mjeseci\n",
    "* Sve (valute)\n",
    "* Svi tečajevi\n",
    "* JSON\n",
    "\n",
    "te kliknuti \"Preuzimanje\". Datoteku snimiti u tekući direktorij kao `ProsjeciMjesecni_2011-2018.json`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[CP65001](https://docs.python.org/3.5/library/codecs.html?highlight=cp65001#standard-encodings) je Microsoftova implementacija UTF8. Nažalost ne postoji pod Linuxom, ali nam ni ne treba: automatska detekcija ovdje sasvim lijepo funkcionira."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'read_clipboard',\n",
       " 'read_csv',\n",
       " 'read_excel',\n",
       " 'read_feather',\n",
       " 'read_fwf',\n",
       " 'read_gbq',\n",
       " 'read_hdf',\n",
       " 'read_html',\n",
       " 'read_json',\n",
       " 'read_msgpack',\n",
       " 'read_parquet',\n",
       " 'read_pickle',\n",
       " 'read_sas',\n",
       " 'read_sql',\n",
       " 'read_sql_query',\n",
       " 'read_sql_table',\n",
       " 'read_stata',\n",
       " 'read_table'}"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "{metoda for metoda in dir(pd) if metoda.startswith('read_')}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Država', 'Godina', 'Jedinica', 'Kupovni za devize', 'Mjesec',\n",
       "       'Prodajni za devize', 'Srednji za devize', 'Valuta', 'Šifra valute'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "tečaj = pd.read_json('ProsjeciMjesecni_2011-2018.json')\n",
    "tečaj.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vidimo listu stupaca. Mnoge od njih mogli bismo ljepše prikazati. Za početak pogledajmo stupac 'Mjesec'."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sređivanje datumâ"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       Siječanj\n",
       "1       Siječanj\n",
       "2       Siječanj\n",
       "3       Siječanj\n",
       "4       Siječanj\n",
       "5       Siječanj\n",
       "6       Siječanj\n",
       "7       Siječanj\n",
       "8       Siječanj\n",
       "9       Siječanj\n",
       "10      Siječanj\n",
       "11      Siječanj\n",
       "12      Siječanj\n",
       "13      Siječanj\n",
       "14       Veljača\n",
       "15       Veljača\n",
       "16       Veljača\n",
       "17       Veljača\n",
       "18       Veljača\n",
       "19       Veljača\n",
       "20       Veljača\n",
       "21       Veljača\n",
       "22       Veljača\n",
       "23       Veljača\n",
       "24       Veljača\n",
       "25       Veljača\n",
       "26       Veljača\n",
       "27       Veljača\n",
       "28        Ožujak\n",
       "29        Ožujak\n",
       "          ...   \n",
       "1177    Siječanj\n",
       "1178    Siječanj\n",
       "1179    Siječanj\n",
       "1180    Siječanj\n",
       "1181    Siječanj\n",
       "1182    Siječanj\n",
       "1183    Siječanj\n",
       "1184    Siječanj\n",
       "1185    Siječanj\n",
       "1186    Siječanj\n",
       "1187    Siječanj\n",
       "1188    Siječanj\n",
       "1189    Siječanj\n",
       "1190    Siječanj\n",
       "1191    Siječanj\n",
       "1192     Veljača\n",
       "1193     Veljača\n",
       "1194     Veljača\n",
       "1195     Veljača\n",
       "1196     Veljača\n",
       "1197     Veljača\n",
       "1198     Veljača\n",
       "1199     Veljača\n",
       "1200     Veljača\n",
       "1201     Veljača\n",
       "1202     Veljača\n",
       "1203     Veljača\n",
       "1204     Veljača\n",
       "1205     Veljača\n",
       "1206     Veljača\n",
       "Name: Mjesec, Length: 1207, dtype: object"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj['Mjesec']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Kolovoz',\n",
       " 'Lipanj',\n",
       " 'Listopad',\n",
       " 'Ožujak',\n",
       " 'Prosinac',\n",
       " 'Rujan',\n",
       " 'Siječanj',\n",
       " 'Srpanj',\n",
       " 'Studeni',\n",
       " 'Svibanj',\n",
       " 'Travanj',\n",
       " 'Veljača'}"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hr_mjeseci = set(tečaj['Mjesec'])\n",
    "hr_mjeseci"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dakle, imamo hrvatske nazive mjeseci. Ako bismo željeli to pretvoriti u datume, trebat će nam broj mjeseca. Python [zna](http://strftime.org/) hrvatske nazive za mjesece, samo trebamo prethodno [locale](https://en.wikipedia.org/wiki/Locale_(computer_software%29) podesiti na hrvatski. Nakon toga izgradimo rječnik koji preslikava nazive mjeseci u njihove redne brojeve."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import locale, time\n",
    "#locale.setlocale(locale.LC_ALL, 'hr')\n",
    "#mjesec_broj = {hr_mjesec: time.strptime(hr_mjesec, '%B').tm_mon for hr_mjesec in hr_mjeseci}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nažalost, ovo gore ne radi na računalima u Pr1 jer su iz tko zna kojeg razloga podešena na američki locale (osim za vrstu papira, što nam ne pomaže ovdje:). Konstruirajmo ručno naš rječnik:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "mjesec_broj = {\n",
    " 'Kolovoz': 8,\n",
    " 'Lipanj': 6,\n",
    " 'Listopad': 10,\n",
    " 'Ožujak': 3,\n",
    " 'Prosinac': 12,\n",
    " 'Rujan': 9,\n",
    " 'Siječanj': 1,\n",
    " 'Srpanj': 7,\n",
    " 'Studeni': 11,\n",
    " 'Svibanj': 5,\n",
    " 'Travanj': 4,\n",
    " 'Veljača': 2,\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sada možemo zamijeniti sve vrijednosti u stupcu 'Mjesec' koristeći gornji rječnik. `inplace` služi tome da se zamjena obavi na licu mjesta, unutar samog dataframea `tečaj` (umjesto vraćanja novog dataframea)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "tečaj.replace({'Mjesec': mjesec_broj}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Država</th>\n",
       "      <th>Godina</th>\n",
       "      <th>Jedinica</th>\n",
       "      <th>Kupovni za devize</th>\n",
       "      <th>Mjesec</th>\n",
       "      <th>Prodajni za devize</th>\n",
       "      <th>Srednji za devize</th>\n",
       "      <th>Valuta</th>\n",
       "      <th>Šifra valute</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Australija</td>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>5,504948</td>\n",
       "      <td>1</td>\n",
       "      <td>5,538077</td>\n",
       "      <td>5,521513</td>\n",
       "      <td>AUD</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kanada</td>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>5,554872</td>\n",
       "      <td>1</td>\n",
       "      <td>5,588302</td>\n",
       "      <td>5,571587</td>\n",
       "      <td>CAD</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Češka</td>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>0,301385</td>\n",
       "      <td>1</td>\n",
       "      <td>0,303199</td>\n",
       "      <td>0,302292</td>\n",
       "      <td>CZK</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Danska</td>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>0,989672</td>\n",
       "      <td>1</td>\n",
       "      <td>0,995628</td>\n",
       "      <td>0,992650</td>\n",
       "      <td>DKK</td>\n",
       "      <td>208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mađarska</td>\n",
       "      <td>2011</td>\n",
       "      <td>100</td>\n",
       "      <td>2,676801</td>\n",
       "      <td>1</td>\n",
       "      <td>2,692910</td>\n",
       "      <td>2,684856</td>\n",
       "      <td>HUF</td>\n",
       "      <td>348</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Država  Godina  Jedinica Kupovni za devize  Mjesec Prodajni za devize  \\\n",
       "0  Australija    2011         1          5,504948       1           5,538077   \n",
       "1      Kanada    2011         1          5,554872       1           5,588302   \n",
       "2       Češka    2011         1          0,301385       1           0,303199   \n",
       "3      Danska    2011         1          0,989672       1           0,995628   \n",
       "4    Mađarska    2011       100          2,676801       1           2,692910   \n",
       "\n",
       "  Srednji za devize Valuta  Šifra valute  \n",
       "0          5,521513    AUD            36  \n",
       "1          5,571587    CAD           124  \n",
       "2          0,302292    CZK           203  \n",
       "3          0,992650    DKK           208  \n",
       "4          2,684856    HUF           348  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sada napokon možemo stvoriti stupac 'Datum' (za dan u mjesecu fiksiramo `1`), te obrisati posebne stupce za godinu i mjesec koji nam više ne trebaju."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Država</th>\n",
       "      <th>Jedinica</th>\n",
       "      <th>Kupovni za devize</th>\n",
       "      <th>Prodajni za devize</th>\n",
       "      <th>Srednji za devize</th>\n",
       "      <th>Valuta</th>\n",
       "      <th>Šifra valute</th>\n",
       "      <th>Datum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Australija</td>\n",
       "      <td>1</td>\n",
       "      <td>5,504948</td>\n",
       "      <td>5,538077</td>\n",
       "      <td>5,521513</td>\n",
       "      <td>AUD</td>\n",
       "      <td>36</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Kanada</td>\n",
       "      <td>1</td>\n",
       "      <td>5,554872</td>\n",
       "      <td>5,588302</td>\n",
       "      <td>5,571587</td>\n",
       "      <td>CAD</td>\n",
       "      <td>124</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Češka</td>\n",
       "      <td>1</td>\n",
       "      <td>0,301385</td>\n",
       "      <td>0,303199</td>\n",
       "      <td>0,302292</td>\n",
       "      <td>CZK</td>\n",
       "      <td>203</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Danska</td>\n",
       "      <td>1</td>\n",
       "      <td>0,989672</td>\n",
       "      <td>0,995628</td>\n",
       "      <td>0,992650</td>\n",
       "      <td>DKK</td>\n",
       "      <td>208</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mađarska</td>\n",
       "      <td>100</td>\n",
       "      <td>2,676801</td>\n",
       "      <td>2,692910</td>\n",
       "      <td>2,684856</td>\n",
       "      <td>HUF</td>\n",
       "      <td>348</td>\n",
       "      <td>2011-01-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Država  Jedinica Kupovni za devize Prodajni za devize  \\\n",
       "0  Australija         1          5,504948           5,538077   \n",
       "1      Kanada         1          5,554872           5,588302   \n",
       "2       Češka         1          0,301385           0,303199   \n",
       "3      Danska         1          0,989672           0,995628   \n",
       "4    Mađarska       100          2,676801           2,692910   \n",
       "\n",
       "  Srednji za devize Valuta  Šifra valute      Datum  \n",
       "0          5,521513    AUD            36 2011-01-01  \n",
       "1          5,571587    CAD           124 2011-01-01  \n",
       "2          0,302292    CZK           203 2011-01-01  \n",
       "3          0,992650    DKK           208 2011-01-01  \n",
       "4          2,684856    HUF           348 2011-01-01  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj['Datum'] = pd.to_datetime(dict(year=tečaj['Godina'], month=tečaj['Mjesec'], day=1))\n",
    "del tečaj['Godina'], tečaj['Mjesec']\n",
    "tečaj.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Umjesto beskorisnih rednih brojeva, stavimo datum kao indeks kojim možemo dohvaćati podatke."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "tečaj.set_index('Datum', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Država</th>\n",
       "      <th>Jedinica</th>\n",
       "      <th>Kupovni za devize</th>\n",
       "      <th>Prodajni za devize</th>\n",
       "      <th>Srednji za devize</th>\n",
       "      <th>Valuta</th>\n",
       "      <th>Šifra valute</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Australija</td>\n",
       "      <td>1</td>\n",
       "      <td>5,504948</td>\n",
       "      <td>5,538077</td>\n",
       "      <td>5,521513</td>\n",
       "      <td>AUD</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Kanada</td>\n",
       "      <td>1</td>\n",
       "      <td>5,554872</td>\n",
       "      <td>5,588302</td>\n",
       "      <td>5,571587</td>\n",
       "      <td>CAD</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Češka</td>\n",
       "      <td>1</td>\n",
       "      <td>0,301385</td>\n",
       "      <td>0,303199</td>\n",
       "      <td>0,302292</td>\n",
       "      <td>CZK</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Danska</td>\n",
       "      <td>1</td>\n",
       "      <td>0,989672</td>\n",
       "      <td>0,995628</td>\n",
       "      <td>0,992650</td>\n",
       "      <td>DKK</td>\n",
       "      <td>208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Mađarska</td>\n",
       "      <td>100</td>\n",
       "      <td>2,676801</td>\n",
       "      <td>2,692910</td>\n",
       "      <td>2,684856</td>\n",
       "      <td>HUF</td>\n",
       "      <td>348</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Država  Jedinica Kupovni za devize Prodajni za devize  \\\n",
       "Datum                                                                   \n",
       "2011-01-01  Australija         1          5,504948           5,538077   \n",
       "2011-01-01      Kanada         1          5,554872           5,588302   \n",
       "2011-01-01       Češka         1          0,301385           0,303199   \n",
       "2011-01-01      Danska         1          0,989672           0,995628   \n",
       "2011-01-01    Mađarska       100          2,676801           2,692910   \n",
       "\n",
       "           Srednji za devize Valuta  Šifra valute  \n",
       "Datum                                              \n",
       "2011-01-01          5,521513    AUD            36  \n",
       "2011-01-01          5,571587    CAD           124  \n",
       "2011-01-01          0,302292    CZK           203  \n",
       "2011-01-01          0,992650    DKK           208  \n",
       "2011-01-01          2,684856    HUF           348  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Države, valute i šifre"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sada se bacimo na stupce koji se odnose na valutu. Pretpostavljamo da postoji bijekcija (trijekcija?:) između sljedeća 3 stupca:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Država</th>\n",
       "      <th>Valuta</th>\n",
       "      <th>Šifra valute</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Australija</td>\n",
       "      <td>AUD</td>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Kanada</td>\n",
       "      <td>CAD</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Češka</td>\n",
       "      <td>CZK</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Danska</td>\n",
       "      <td>DKK</td>\n",
       "      <td>208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Mađarska</td>\n",
       "      <td>HUF</td>\n",
       "      <td>348</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Japan</td>\n",
       "      <td>JPY</td>\n",
       "      <td>392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Norveška</td>\n",
       "      <td>NOK</td>\n",
       "      <td>578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Švedska</td>\n",
       "      <td>SEK</td>\n",
       "      <td>752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Švicarska</td>\n",
       "      <td>CHF</td>\n",
       "      <td>756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Velika Britanija</td>\n",
       "      <td>GBP</td>\n",
       "      <td>826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>SAD</td>\n",
       "      <td>USD</td>\n",
       "      <td>840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td></td>\n",
       "      <td>XDR</td>\n",
       "      <td>960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>EMU</td>\n",
       "      <td>EUR</td>\n",
       "      <td>978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Poljska</td>\n",
       "      <td>PLN</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-01</th>\n",
       "      <td>Bosna i Hercegovina</td>\n",
       "      <td>BAM</td>\n",
       "      <td>977</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Država Valuta  Šifra valute\n",
       "Datum                                               \n",
       "2011-01-01           Australija    AUD            36\n",
       "2011-01-01               Kanada    CAD           124\n",
       "2011-01-01                Češka    CZK           203\n",
       "2011-01-01               Danska    DKK           208\n",
       "2011-01-01             Mađarska    HUF           348\n",
       "2011-01-01                Japan    JPY           392\n",
       "2011-01-01             Norveška    NOK           578\n",
       "2011-01-01              Švedska    SEK           752\n",
       "2011-01-01            Švicarska    CHF           756\n",
       "2011-01-01     Velika Britanija    GBP           826\n",
       "2011-01-01                  SAD    USD           840\n",
       "2011-01-01                         XDR           960\n",
       "2011-01-01                  EMU    EUR           978\n",
       "2011-01-01              Poljska    PLN           985\n",
       "2017-12-01  Bosna i Hercegovina    BAM           977"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj[['Država', 'Valuta', 'Šifra valute']].drop_duplicates()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Čini se da je doista tako (u pojedinim stupcima nema duplikata --- što ovdje možemo ustanoviti golim okom, ali kod kompliciranijih podataka, dobro je koristiti `.duplicated` metodu), jedino što [XDR](https://hr.wikipedia.org/wiki/Posebna_prava_vu%C4%8Denja) nema napisanu državu. Kako euro ima EMU, čini se logičnim XDRu staviti MMF. Šifra valute nam svakako više ne treba, jer je u bijekciji s valutom, a nema neku pametnu semantiku ionako."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Država</th>\n",
       "      <th>Valuta</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Australija</td>\n",
       "      <td>AUD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Kanada</td>\n",
       "      <td>CAD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Češka</td>\n",
       "      <td>CZK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Danska</td>\n",
       "      <td>DKK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Mađarska</td>\n",
       "      <td>HUF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Japan</td>\n",
       "      <td>JPY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Norveška</td>\n",
       "      <td>NOK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Švedska</td>\n",
       "      <td>SEK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Švicarska</td>\n",
       "      <td>CHF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Velika Britanija</td>\n",
       "      <td>GBP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>SAD</td>\n",
       "      <td>USD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>MMF</td>\n",
       "      <td>XDR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>EMU</td>\n",
       "      <td>EUR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Poljska</td>\n",
       "      <td>PLN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-01</th>\n",
       "      <td>Bosna i Hercegovina</td>\n",
       "      <td>BAM</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Država Valuta\n",
       "Datum                                 \n",
       "2011-01-01           Australija    AUD\n",
       "2011-01-01               Kanada    CAD\n",
       "2011-01-01                Češka    CZK\n",
       "2011-01-01               Danska    DKK\n",
       "2011-01-01             Mađarska    HUF\n",
       "2011-01-01                Japan    JPY\n",
       "2011-01-01             Norveška    NOK\n",
       "2011-01-01              Švedska    SEK\n",
       "2011-01-01            Švicarska    CHF\n",
       "2011-01-01     Velika Britanija    GBP\n",
       "2011-01-01                  SAD    USD\n",
       "2011-01-01                  MMF    XDR\n",
       "2011-01-01                  EMU    EUR\n",
       "2011-01-01              Poljska    PLN\n",
       "2017-12-01  Bosna i Hercegovina    BAM"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj.loc[tečaj['Valuta'] == 'XDR', 'Država'] = 'MMF'\n",
    "del tečaj['Šifra valute']\n",
    "tečaj[['Država', 'Valuta']].drop_duplicates()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Državu zasad ostavimo, ljepše izgleda od troslovne skraćenice valute za kasniju vizualizaciju."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Država                object\n",
       "Jedinica               int64\n",
       "Kupovni za devize     object\n",
       "Prodajni za devize    object\n",
       "Srednji za devize     object\n",
       "Valuta                object\n",
       "dtype: object"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tečajevi kao brojevi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nego, pogledajmo tri stupca sa samim tečajevima. Prvo, maknimo podstring ` za devize` s kraja njihovih naziva. Drugo, pretvorimo ih u brojeve --- samo prethodno moramo decimalni zarez zamijeniti decimalnom točkom (teoretski, o tome bi `locale` trebao voditi računa, ali očito ne funkcionira baš najbolje --- možda jer se ni sami Hrvati ne mogu dogovoriti čime se odvajaju decimale:). I treće, pretvorimo ove retke što imaju `100` u stupcu `Jedinica`, u retke sa 100 puta manjim tečajevima."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Datum\n",
       "2011-01-01      1\n",
       "2011-01-01    100\n",
       "Name: Jedinica, dtype: int64"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj['Jedinica'].drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Država</th>\n",
       "      <th>Kupovni</th>\n",
       "      <th>Prodajni</th>\n",
       "      <th>Srednji</th>\n",
       "      <th>Valuta</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Australija</td>\n",
       "      <td>5.504948</td>\n",
       "      <td>5.538077</td>\n",
       "      <td>5.521513</td>\n",
       "      <td>AUD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Kanada</td>\n",
       "      <td>5.554872</td>\n",
       "      <td>5.588302</td>\n",
       "      <td>5.571587</td>\n",
       "      <td>CAD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Češka</td>\n",
       "      <td>0.301385</td>\n",
       "      <td>0.303199</td>\n",
       "      <td>0.302292</td>\n",
       "      <td>CZK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Danska</td>\n",
       "      <td>0.989672</td>\n",
       "      <td>0.995628</td>\n",
       "      <td>0.992650</td>\n",
       "      <td>DKK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Mađarska</td>\n",
       "      <td>0.026768</td>\n",
       "      <td>0.026929</td>\n",
       "      <td>0.026849</td>\n",
       "      <td>HUF</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Država   Kupovni  Prodajni   Srednji Valuta\n",
       "Datum                                                      \n",
       "2011-01-01  Australija  5.504948  5.538077  5.521513    AUD\n",
       "2011-01-01      Kanada  5.554872  5.588302  5.571587    CAD\n",
       "2011-01-01       Češka  0.301385  0.303199  0.302292    CZK\n",
       "2011-01-01      Danska  0.989672  0.995628  0.992650    DKK\n",
       "2011-01-01    Mađarska  0.026768  0.026929  0.026849    HUF"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj.rename(columns=lambda x: x[:-len(' za devize')] \n",
    "                               if x.endswith(' za devize') else x,\n",
    "             inplace=True)\n",
    "\n",
    "for vrsta in 'Kupovni', 'Prodajni', 'Srednji':\n",
    "    tečaj[vrsta] = pd.to_numeric(tečaj[vrsta].str.replace(',', '.'))\n",
    "    tečaj[vrsta] /= tečaj['Jedinica']\n",
    "\n",
    "del tečaj['Jedinica']\n",
    "tečaj.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Srednji tečaj je dovoljan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f600eb3f4a8>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEKCAYAAAAVaT4rAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzsvXd4VNe1v//uKdKojPqoS0gCdSFEE73ZGHADOy64xeWm2HGccvNLYt8kN/HXiZObOM25cUIc1/hiYhNjOy6xjWOLXgUIhECo9967NDP798ceCQl1kBDlvM/DM9I++5zZI6R11llr7c8SUko0NDQ0NK4edFO9AA0NDQ2Ni4tm+DU0NDSuMjTDr6GhoXGVoRl+DQ0NjasMzfBraGhoXGVohl9DQ0PjKkMz/BoaGhpXGaMafiFErBDiWL9/zUKIb58z53v9jmcKIWxCCB/HsUIhxAnHscOT9UE0NDQ0NMaGGM8GLiGEHigDFkgpi4aZczPwn1LKaxzfFwLzpJS1F75cDQ0NDY0LxTDO+dcCecMZfQd3A1vOf0ng5+cnIyIiLuQSGhoaGlcV6enptVJKy1jmjtfw38UIRl0I4QqsAx7rNyyBT4QQEviLlPL50d4kIiKCw4e1qJCGhobGWBFCjOSQD2DMhl8I4QSsB/5rhGk3A3uklPX9xpZIKcuFEP7AdiHEaSnlziGu/1XgqwDh4eFjXZaGhoaGxjgZT1XP9cARKWXVCHMGPRFIKcsdr9XA20DqUCdKKZ+XUs6TUs6zWMb0tKKhoaGhcR6Mx/CPGLsXQngCK4B3+425CSHMvV8Da4DM81uqhoaGhsZEMKZQjyN2fx3wcL+xRwCklJscQ7cCn0gp2/qdGgC8LYTofa/XpZQfTcC6NTQ0riB6enooLS2ls7NzqpdyyWMymQgNDcVoNJ73NcZVznmxmDdvntSSuxoaVw8FBQWYzWZ8fX1xOIoaQyClpK6ujpaWFiIjIwccE0KkSynnjeU62s5dDQ2NKaezs1Mz+mNACIGvr+8FPxlphl9DQ+OSQDP6Y2Mifk6a4dfQuBRoLoesf071KjSuEjTDr6FxKbDrN/Dm/dDdPtUruWpxd3fv+/rDDz8kOjqa4uLiKVwR/PjHP+bTTz+d8OuOd+euhobGZFC0F5DK8/ebMdWruar597//zTe+8Q0++eSTKd9M+tRTT03KdTWPX0Njqmmvh+os9XVTydSu5Spn165dfOUrX+GDDz5g+vTpADz44IP84x//6JvT+2SQlpbG8uXLufXWW0lISOCRRx7BbrcDsGXLFmbOnElSUhKPP/44AH/+85/5/ve/33edV155hW984xsUFhYSHx/PV77yFRITE1mzZg0dHR1DvvdEoXn8GhpTTcmBs183l03dOi4R/t97J8kqb57QayYEe/CTmxNHnNPV1cWGDRtIS0sjLi5uTNc9ePAgWVlZTJs2jXXr1rFt2zYWL17M448/Tnp6Ot7e3qxZs4Z33nmH22+/nUWLFvGrX/0KgDfeeIMf/vCHAOTk5LBlyxb++te/cuedd/LWW29x3333XdiHHgHN49fQmGqK9oLeCRDQVDrVq7lqMRqNLF68mBdffHHM56SmphIVFYVer+fuu+9m9+7dHDp0iJUrV2KxWDAYDNx7773s3LkTi8VCVFQU+/fvp66ujuzsbJYsWQJAZGQkKSkpAMydO5fCwsLJ+Ih9aB6/hsZUU7wPgudAQ4EW6oFRPfPJQqfT8eabb7J69Wp+/vOf84Mf/AAAg8HQF8KRUtLd3d13zrmllUIIRtoUu3HjRt58803i4uK49dZb+853dnbum6PX6/tCPZOF5vFraEwl3e1QfhSmLQLPUGjSQj1TiaurK++//z6bN2/u8/wjIiJIT08H4N1336Wnp6dv/sGDBykoKMBut/PGG2+wdOlSFixYwI4dO6itrcVms7FlyxZWrFgBwBe+8AXeeecdtmzZwsaNGy/+B3SgefwaGlNJ2WGwWyF8MdTlQfWpqV7RVY+Pjw8fffQRy5cvx8/Pj6985Sts2LCB1NRUrr32Wtzc3PrmLlq0iCeeeIITJ070JXp1Oh2/+MUvWLVqFVJKbrjhBjZs2ACAt7c3CQkJZGVlkZo6pFDxRUHT6tHQmErSfglpv4DHC2HHryD9ZfhBOVxlu1hPnTpFfHz8VC9jXKSlpfHrX/+a999//6K/91A/L02rR0PjcqF4LwQkgYsXeIZATzt0NEz1qjSucDTDr6ExVdh6oOSgiu+DivGDVtlzmbBy5cop8fYnAs3wa2hMFRXHlYcfvohdpbv4/4reRYJm+DUmHc3wa2hMFcV71eu0xbyd+zafVB+iSafTNnFpTDqjGn4hRKwQ4li/f81CiG+fM+d7/Y5nCiFsQggfx7F1QohsIUSuEOKJyfogGhqXHUX7wDsS6R5AepUqF6xwMmm1/BqTzqiGX0qZLaVMkVKmAHOBdlTT9P5znuk357+AHVLKeiGEHngO1ag9AbhbCJEw4Z9CQ+NyQ0q1cWvaYoqai6jvrAegwmzRavk1Jp3xhnquBfKklEUjzOnflD0VyJVS5kspu4G/AxvGv0wNjSuMrHehox6mX9Pn7QNUunlpMf4pQq/Xk5KSQlJSEnfccQft7ecvkf3KK6/w2GOPjTjnn//8J//zP/8z4pzy8nJuv/32817HcIzX8N/FWaM+CEdT9nXAW46hEKD/c2upY0xD4+rF2g2f/gT8EyDxVo5UH8Hb2RsnnROVTi5ajH+KcHFx4dixY2RmZuLk5MSmTZsGHJdS9kk3TATr16/niSdGjn4HBwdPijrnmA2/EMIJWA9sHWHazcAeKWV972lDzBlyx5gQ4qtCiMNCiMM1NTVjXZaGxuXHoRegoRDW/BR0etKr0pkTMIcAtwAqDXqlyW+3TfUqr2qWLVtGbm5un2Tyo48+ypw5cygpKRlSchng5ZdfJiYmhhUrVrBnz56+8ffee48FCxYwe/ZsVq9eTVVVFTDwqeDBBx/km9/8JosXLyYqKqrP2BcWFpKUlDThn288kg3XA0eklFUjzDn3iaAUCOv3fShQPtSJUsrngedB7dwdx7o0NC4f2uthxy9h+rUwYzVVbVWUtZZxb/y9tHS3UNFUAtIGLZVqQ9fVyL+egMoTE3vNwJlw/chhlV6sViv/+te/WLduHQDZ2dm8/PLL/OlPf6K8vHxIyeUFCxbwk5/8hPT0dDw9PVm1ahWzZ88GYOnSpezfvx8hBC+88AK/+tWv+M1vfjPofSsqKti9ezenT59m/fr1kxLi6WU8hr9/7H4QQghPYAXQX0T6EBAthIgEylA3hnvOY50aGlcGu34DXc3K2weOVB8BYE7AHE7Xn+ZA/Rk1r6n06jX8U0RHR0efNPKyZcv40pe+RHl5OdOmTWPhwoUAAySXgT7JZWDA+MaNGzlzRv1flpaWsnHjRioqKuju7iYyMnLI97/lllvQ6XQkJCT0PRVMFmMy/I7Y/XXAw/3GHgGQUvYGwm4FPpFStvXOkVJahRCPAR8DeuAlKeXJCVq7hsblRX0BHPgLpNwLAUp6OL0qHVeDK7HesQS6BVLT3YQVMDSVAAumdLlTxhg984mmN8Z/Lv1F2UbSNjtXormXb3zjG3znO99h/fr1pKWl8eSTTw45r78082RrqI0pxi+lbJdS+kopm/qNbepn9JFSviKlvGuIcz+UUsZIKadLKZ+emGVraFxGdLfBwb/C3zaA3gjX/KjvUHpVOin+KRh0BoLcgrAjqdHrtQTvJcpwkssLFiwgLS2Nuro6enp62Lr1bCq0qamJkBD19Pbqq69O1dIHoMkya2hMFtZu2PkrZfQ7GyFkHqz/A5gDAWjqaiK3MZfrI6+nx2bHRfgCUOHqSZBW0nlJEhQUNKzk8pNPPsmiRYsICgpizpw52Gy2vvE77riDkJAQFi5cSEFBQd/1hntKmGw0w6+hMVkc/AvsfAbiboLF34TwgaGbo9VHAZjjP4fnd+azaW8xhEKlu6+2iWsKaG1tHTQWERFBZmbmgLF77rmHe+4ZnKp86KGHeOihhwaNb9iwoe/m0J+6ujp8fHwAVeEz1FqGev+JQNPq0dCYDDqbVCJ3+jVw1+ZBRh/gSNURjDojMy0z2ZFdQ0ubGYAKVw9NtuEKZ9OmTbzyyiuT2lB9JDTDr6ExGez9o9LVv/bHw05Jr0onyS8JpIFjpY1gd8bV4E6l0VmL8V/hPPLII5w4cYLo6OgpeX/N8GtoTDStNbDvOUjYAMGzh5zS1NVEVl0WcwPmcry0iW6r2hHqYbBQqQfa61Q/Xg2NSUCL8WtcuWS9C+9/B0we4OIDrr6w4GGYce3kvu+u34C1A1b9aNgpzx9/Hpu0cX3k9Ww/Vt837ix8qbAXq2+ay8FvxuSuVeOqRPP4Na5cjjn2GwbPUca/ZD/s/t3kvmdjMRx+EVLuAUvMkFNKmkt4/fTr3Bp9KzHeMRwsqCcmwB0PkwGdzYtKq2MrzKUS5+9qgf+7DUrTR5+rcVmgGX6NKxNrFxTshMRb4PYX4Ytvw5z7oeTA5IZQdvwKELBiePGt3x35HUadka+nfB2bXZJe1MD8CB+CvVywdnvSZG2jXYhLJ85/4h+Q+ymk/XyqV6IxQWiGX+PKpHgf9LTBjNVnx6JWgq1bHZsM7HY49U+YeTt4hQ055Vj1MbYXbeehxIfwd/XnVEUzrV1WUiN9CPFyoc1R2VNpMFw68sxH/qZecz+FmuypXcsk8vTTT5OYmEhycjIpKSkcOHDgvK/l7u4+6pwvf/nLZGVlAXDDDTfQ2Nh43u83XjTDr3Flkvsp6J0gYtnZsfBFoDNCwY7Jec+6HFXGOW3xkIellDxz+Bn8Xfx5IPEBAA4WqPh+aqTy+BualTxApbufChtNNZUnoPwILP8e6J1h/5+nekWTwr59+3j//fc5cuQIx48f59NPPyUsbODNu3dD1kTxwgsvkJCg+lJ9+OGHeHl5Tej1R0Iz/BpXJrn/VobeuZ/n5eQGYamQP0mGv/SQeg2dP+iQlJI3st/geM1xHpv9GK5GV0AZ/lBvF4I8XQjyMtHSqtZbYfaDhpH6HV0kjvxNGfyFj8KsjZDxd6UweoVRUVGBn59fn16On58fwcHBRERE8NRTT7F06VK2bt1KXl4e69atY+7cuSxbtozTp08DUFBQwKJFi5g/fz7//d//3XfdtLQ0Vq5cye23305cXBz33ntvnw7PypUrOXz4MKA2atXW1l60z6tV9WhceTSVQXUWXPfTwcciV0DaL5TxcvWZ2PctOQgmT/A9W5vdZevi/bz3eS3rNfKa8ki2JLN++npA3QwOFdazIlYpOoZ4uSCtHggElS5mqCic2PWNl54OOP4GxN+sflYLH1U3gsMvwfLvTtrb/vLgLzldf3pCrxnnE8fjqY8Pe3zNmjU89dRTxMTEsHr1ajZu3MiKFSsAMJlM7N69G4Brr72WTZs2ER0dzYEDB3j00Uf57LPP+Na3vsXXvvY17r//fp577rkB1z569CgnT54kODiYJUuWsGfPHpYuXTqhn2+8aB6/xpVH3r/Va//4fi9RKwAJhbsm/n1LDylvX6f+rIqai1j31jqe3PckRr2Rny/9Oa+sfQW9Tq+WWdNGXVs3qRHqBhTs5QLo8XTypcLopJK71q6JX+dYOfWeCl3NVWEp/OMhapVqJGPtnrp1TQLu7u6kp6fz/PPPY7FY2LhxY5+MwsaNGwElo7B3717uuOMOUlJSePjhh6moqABgz5493H333QB88YtfHHDt1NRUQkND0el0pKSkUFhYeNE+13BoHr/GlUfOdjAHK0N1LiFzwcldhXsSJrD9c2cTVJ+ChFv6hp498iztPe28sOYFUgNTBwlyHSo8G9+HXsMPbno/KkUnIKGxZOpq+dNfBe9ImNbPO130ddh8O2S9A8l3TsrbjuSZTyZ6vZ6VK1eycuVKZs6c2aek2SvLbLfb8fLyGlK6GYYXXOsvt6zX67FarRO88vGjefwaVxa2HshPU5u0hvpD1Bth2pKJT/CWpQMSwlR8P7M2k+1F23kw8UEWBC0Y0igcKqjHz92JSD9lWALMzugEGKUPlTZHyWlD4cSuc6zU5kLRbpjzxb4nGEB1DvONhv1/mpp1TRLZ2dnk5OT0fX/s2DGmTZs2YI6HhweRkZF9kstSSjIyMgBYsmQJf//73wHYvHnzRVr1+aMZfo0ri9LDqsPVUGGeXqJWQF3uxJZLlhwChHqiQHn73s7e3J94/7CnHCioJzXSp++mYNDrCPAwIa1eVHY1qubUDQXDnj+pHH0NhF41jemPTgdJX4Dyo1dUuKe1tZUHHniAhIQEkpOTycrKGrJhyubNm3nxxReZNWsWiYmJvPvuuwA8++yzPPfcc8yfP5+mpqZB5w3HJSvLLISIBd7oNxQF/FhK+ftz5q0Efg8YgVop5QrHeCHQAtgAq5Ry3oSsXEOjqwXe/0+oyoLFj8HMO1QZp9BD1Eqau5vZXbobdyd3PJ098Xb2JtQcii5SJe3I3wGz7x3xLcZM6UGwxIHJk/0V+9lfsZ/vz/8+bka3IaenFzVQ1tjBwyuiBowHe7nQ0uFBl7GbBicXfKbK489PU2Wpjt4BA/BwtIRsrRp2v8Llxty5c9m7d++g8XPj8ZGRkXz00UeD5kVGRrJv39n9IU88oTbw9YaOevnjH//Y93V/WeaLHfcf1fBLKbOBFAAhhB7VO/ft/nOEEF7An4B1UspiIYT/OZdZJaW8eLVKGlc+Ndnwxn3Kc/eZDu98DT7/OUi7Ktl08eLF9N/xUuZLA067L/4+Hp/3PXD1U+GeiTD8drt60khYj5SSPxz5A4FugdwZO3QMXErJzz7IwmJ25rY5oQOOBXmaKK9xBy+o8A6bGsNv7VZVUQse6RvKa8wjwiNCJabNQWqwpfKKMfwXm+uuu46ZM2cO2393shlvqOdaIE9KeW6B8T3ANillMYCUsnoiFqehMSSZ2+D5VUr2+P5/wmOH4J6t4BGsKmFi1gGwq2wXs/1ns/mGzTx37XPM9p9NWkmaCldErVBe7UT0Nq3LVR22QlP5rPgzTtSe4NFZj+Ksdx5y+gcnKjha3Mh318Tg5jzQ9wrxcqG+WdX4V05VLX/NabXDOWgWAGcaznDru7fyapajbWDvU0BLxcVf2xXC9u3bef3116fs/cdr+O8CtgwxHgN4CyHShBDpQoj+gU0JfOIY/+r5LlRDA1DhmX88pJqVP7wTIpepJG7MGviPj+Hrh2DR16lsqySnIYdVYatItiSzPHQ5ayPWUtpaSmlLqarnb62C2jPjX0Ndnuqj20vpQfUalsoLJ14g0jOSm6ffPOSpnT02fvnRaeICzdw+d7C3HOzlQnenBwCVLh4quTvJjbcHUaESlgSlAPDWmbeQSDaf2kyPvWegxz+BTHaD8SuFifg5jdnwCyGcgPXA1iEOG4C5wI3AWuC/hRC90oRLpJRzgOuBrwshlg9z/a8KIQ4LIQ7X1NSM5zNoXC3Y7bD9x+AZDg+8pzz8/gihFDH1RvaWq3jtkpAlfYcXBi0E4EDFAQhXX1N6eHxr6GqBTUvh5etVCSf0bdxq8wgmqz6LtRFrMeiGjqK+ureQkvoOfnRjAnrd4MResJcL0uaGUedEudEI3S1Km/9iUpGhSl59oui0dvJe/nuEuodS3V7NJ4WfKHlrnQFaJ87wm0wm6urqNOM/ClJK6urqMJlMF3Sd8dTxXw8ckVJWDXGsFJXQbQPahBA7gVnAGSlluWPB1UKIt4FUYOe5F5BSPg88DzBv3jztf19jMFnvQMUxuGUTGEf+xd9dtht/V3+ivc7uoo3yjMLiYuFAxQFum3ErOJmVDs144vyFu6GnXRnHzXfCF7epjVsh88isz8Iu7cyyzBry1Pq2bv74eS6rYi0sjfYbck6QpwkQeDsFUC4c2jANheA29PwLYv8m8AqHuBsGjldkQGAy6HRsL9hOS3cLv135W57e/zSvZb3GDZE3INwDJtTjDw0NpbS0FM3pGx2TyURoaOjoE0dgPIb/boYO8wC8C/xRCGEAnIAFwO+EEG6ATkrZ4vh6DfDUhSxY4yrF1gOf/RT8E0bdOGS1W9lfvp/rIq4bUC4nhGBB0AL2lu/FLkAXnOKovx8HeZ+D0RVufhbefhhe3+jYuLWBjBoVIpnpN3PAKVJK9uXV8btPz9DebeMHNwyxscxBSO8mLl0ApT2OeoiGQgid4GI4KZXM8rmG325TwmxzHwRgW842wsxhpAamcl/8ffzswM84Wn2UOebACY3xG43GKUt0Xo2MKdQjhHAFrgO29Rt7RAjxCICU8hTwEXAcOAi8IKXMBAKA3UKIDMf4B1LKwbVQGhqjceRvUJ8P1/4EHJIHw3G85jgtPS0sCV4y6NjCoIXUd9aT05Cjau4rM8cni5D3mSpzTL4T1v+vQ/pBQuh8MmoyiPKMwtPZE1AG/52jZdzwh93c88IBCmrb+OmGJKIDzMNe3svViItRj97uR2lnzeTV8rfXqVBV5QnV6auX2hzVPSxoFoVNhRyuOswXor+ATui4efrNeDh58FrWayrOP8Exfo2Lx5g8fillO+B7ztimc75/BnjmnLF8VMhHQ+P86W6DHb9Uapsxa0edvrtsN3qhZ2HwwkHHFgQtAGB/xX5iQ+aCvUcZ/9C5o6+jqVRJLzu8YWbfp4TMDmxChs7n+OEnWRW2qm/6tiNl/H9bM4j2d+eXt81kQ0oIJuPINy0hBMFeJuzd3rTa22g0B+A9GSWddXlnv87ZflaPpy+xO4ttOdvQCz0bpitpC1ejK3fE3MHLJ1+m1GsxoUVaVc/lirZzV+PS58AmVYGz+smhZRjOYXfZbmZZZuHh5DHoWKBbIBEeESrB69hlO+ZwT97n6nX6NWfHUr8C30inqKuexq7Gvvh+l9XGb7efISnEg4+/vZyN88NHNfq9BHu50NamtNlLvYInp6SzLle9Glwg55Oz45XHwWCixzuSd/PeZUXoCiyulr7Dd8fdjQ4dm211qpy2p3Pi16Yx6WiGX+PSRko4/IoytuGDPfhzqe2o5VT9KZaGDC97uyBoAYerDtPjZgH3gHEY/s/APXBI8bfe+H6v4X/9QDFljR08vi4O3RDVOyMR7OlCQ5MKB5W6+0yOXk99ntrhPPM2tZ+hV36hIgMCkkir2E19Zz23xdw24LQAtwCum3Yd77bmqzDUBFb2aFw8NMOvcWnTUABNxRB7w5CH85vy2Vm6E7u0AwxZxnkuC4MW0mHt4ERdpvL6x2L47Xa10zdq5ZBPHRk1GZiNZqK8omjtsvLHz3JZPN2XpTPGX40T7OVCXaNqyFLq7KJCTBOti1OXC94REHsjdLdC8V71GSsyIDiFD/I/wN/Ff8g8SaJfIi32Llp0QovzX6Zosswalza93bJ69XX68V7eezy17yk6bZ1EeUbxpZlfIq0kDR+TD3E+cezNq+WXH2Vjdjbg5WrEx82JO+aGMT9wPgLB/or9zAmZA9kfqkSnyXP4dVQeVwnR/mGefmTUZDDTMhOd0PHS7jzq2rr53trY8xLhCvIygXTC29mXUr0AJDSVgO/0cV9rWOry1fUil6sWlTnbVYVPVzMEzSIz72/MC5zX1zugP/6uSpGlRq/HQzP8lyWax69xaVOwU1WQ+J2tx++2dfOz/T/jB7t/QJJfEj9d8lP0Oj0/3P1DthdtZ2nIUnRCx+b9xeRWtdDWbeVkeTN/P1jCrz/JxtPZkwTfBBXnD56jLlp+dOR15H2mXqNWDjrU1tNGbmMusyyzqG/r5vmd+axNDGB2uPd5feTekk4fpyBK7Y4Y+kRW9kipQj2+M1RryoilKs7vSOzW+URQ1V5Fgq/qB9vZY+MHb58gr6YVAIuLivlX6/Wax3+Zonn8Gpcudrsy/DNW94VXWrtbeXj7wxyvPc5DiQ/xzTnfxKAzsGH6BnaW7mRbzjY2xm7EarOzK6eGG2YG8cwdKu7+k3czefNwKd1WOwuDFvLqyVdpXxKLK6hwT9TK4deS/zn4J4I5YNChE7Un+jZu/enzXNq7rXx3Tex5f+y+hiw6f0q6MtXgRMb5WyrUJjQfhzJo9Br46AnIehd0Rk7pVNis1/B/fLKS1w8U09Tew3P3zjnr8RudNb2eyxTN49eYOGw9cPIdZbAnguosaK9V4QgHL2W+xPHa4/x6xa/5zrzv9EkjCCFYEbaCZ695lmRLMsdKGmnutLIy9qxQ7JIZfnT02Dha3EBqYCpWaeVYa7FS9yw7Mvw6utuheD9MX4WUkp8f+DkfF37cdzijWnnKSX5JvHOsjOuTgkas1R8NtXsXDNKPyo4aegymiTX8vRU9vo7OXtFr1OvJdyAggVONqiFJrI+6eW05WAzAvzIrKG1ox89F5S2qXb00j/8yRTP8GhPH4Zdg6wNQkDYx1ytwKHtEqfh+dXt1n2TA2oiR6/nTsmvQ68QAaYQFUb7oBOzJrSXRLxGAk7UnHQneEQx/8V6lVjl9FQVNBWw5vYXv7/y+0q1Bxfene06nqdVIbWs3i6b7Dn+tMWAy6vFzd8LW5Y1EUu4dNsGGX9Xwt3gE0mntVLF+nyhAQtAsTtWfIswchoeTBwW1bezPr+e+heEIIXh1byGuRlfMRjM1zq6ax3+Zohl+jYnBboeDz6uvS8cpgzAcBTuUN+6pdEk2ZWzCKq08NvuxUU/dcaaG2WFeeLoY+8Y8XYwkh3qxJ68OT2dPIjwiyKzNhJA50FIOzcMYsbzPVQI0fDH7KlSzjWivaB7f9Tg7S3dyvPY4s/xnkV6seujOOc/Yfn/CfFxpbVP7EEo9/Cfe49c786X9P+an+3+qxqIdN9KgWWTVZRHvo0pW/36oGL1O8M1rorlhZhB/P1hCa5cVi6uFGqNR8/gvUzTDrzEx5H/uCCGI0ROlY8FmhcI9fWGewqZCtuVs446YOwgzj9z8o6alixNlTayMtQw6tnSGH8dKGmnp7CHJL8lh+B0bucqH8frzPld7CJxc2Vu+l2ke03h53ctEe0Xzrc++RVNXE7MsszhS1Iibk57YwPMP8/QS7uNKdb2jlt/VDPWFEyfPXJ9Pj08kZxpy+Lz4cyW1nLABhJ6moGTKWstI8E2g22rnrfT2QBZBAAAgAElEQVRSronzx9/DxJeWRtLSZeXNQyVYXC1Ua+Wcly2a4deYGA7+FdwsyoAMZ0DHQ/lRJUnsCPP84egfcNY783Dyw6OeuitHKTyuiDm3ERwsnuGLzS45kF9Pkl8S1R3VVHkEKJnhoer5W6qg+iREraLH1sOhykMsDFqI2cnMX677C9M8VEPuFEsKR4obSAn3GlJuebyE+7hSWW/AWe9MSZ88c/0FXxeAulxKvUOxSRstPS0qRzFtETxRxGm9urnE+8bz71NV1LZ2c3equtGmhHkxb5o3L+8twOJioQYrdDWpHIjGZYVm+DUunPoCOPOR0rAJX6jivsOFTcZKb54gYjmZtZlsL9rOA4kP4Osyevw8LbsGP3cnEoMHSzbMCffGZNSxO7eWJL8kADIbc1Vjl5KDgy+W71jH9FUcqzlGh7WDxcGLAfA2efPSupf432v+l0DXcE5XtkxImAeU4bdLHf4uQZTikGeuy7nwC9usUF9Akdmnb2hnmSOX4mzmVN0pAOJ94tlyqIQgT9OAG+iXlkZSUt9BW5sb1bZ2bffuZYpm+DUunEMvKMXMef/Rry7+Ar3+/B0QMBPcfPnTsT/hY/LhgcQHRj3NZpfszKlheYxlSKkEk1HP/Agf9ubVEucTh0EYOFF7AmZcB0V7oPWcrqH5n4OLDwTOYl/5PvRCz/zA+X2HfUw+rAxbSUZJEza7nFDDD+BpCKTU5uj2VZ114RduKgF7D0VOqnIo1juWXaW7+g5n1WcR5BZEa7szu3JquGNe2IAnmDWJgYR6u3CyBKzSTqNOp4V7LkM0w69xYXS3w9HXIP5m1RErcKbSgBmpSmY0ejqU9x21gg5rB/sr9nNz1M24Gd1GPfV4aSON7T2siBkc3+9lyQw/zlS10tQmifGJUXH+mXeoRu0n3z47UUoV349aCTod+8r3kWxJxuw0OIZ/pLgBgNnhXuP9tEMS7qsMvzMWSjuqkU7uSvf/QnFU9BQJG57Ontw8/WZyG3OpaFVPaKfqThHvE8/W9FIA7pw3sOGHXifYkBJMUY0qo1WbuLTKnssNzfBrXBgn3lRyB6mOdspOrkrE7EI8/pKDYOuCyBUcrT5Kj72nT065P509Nn70zgnu3LSPj09WYrdL0rJrEAKWRw9v+Hv1c/bk1TLTbyaZdZnYLTHqCeNEv86i1adUGGP6Kho7GzlZd5JFQYuGvObR4gaiLG54uTqd/+fuR4DZhJNBh+zxoa2njUb/2Ikx/PUOw29tYZrHNJaFLANUY/q2njaKmouI941nx5ka5k3zJtTbddAlQrxcsfeoMFqNQdu9ezmiGX6N86OnQyV0P/uZMpjh/Qxi8GyVnD3fKpReAxc8mwMVBzAIA3MDBurll9S3c/umvfzf/mKK69t5+LV01v5+J9uOljIr1Atvt+ENcEKQB16uRvbk1pHkl0RbTxuFTYWQfIdqo1jvkEfId8gwR63iQOUBJJJFwYMNv5SSI8WNzJ2gMA+ATicI83aho8Mhz+wTBlUnL7yypy4XnNwpaqtgmnkakZ6RhLiHsKt0F6frTyORxHrHc6qimVmhQz+9BHg4I63qqafGyaR5/Jchoxp+IUSsEOJYv3/NQohvDzFvpeP4SSHEjn7j64QQ2UKIXCHEExP9ATQuMtYu2P17+H0yfPhdtfHnlucGKlaGzFFa7edbe95Srurm3fw4WHGQZEsyrsaznudnp6u48Q+7KK5r58UH5rH78VU8e1cKOiEoqe9gdfzgap7+6HSCxdN92ZNbS5KvI8FblwlJDgniE/9Qr3mfq92tXmHsK9+H2WjuSwj3p7Cunfq2buZMmzjDDyrO39CoDGyJuy901A/OQYyXujw6fKOoaq9imsc0hBAsC1nGgcoDHKs+BoBJhtNttZMUMrRoXYCHCWl1ePwunprHfxkyquGXUmZLKVOklCnAXKAdeLv/HCGEF/AnYL2UMhG4wzGuB55DNWpPAO4WQiRM7EfQuKh8/jR8+hMVy3/wQ/iPjyHonCZrF5rgbS4Hj2Cae1rIqs8iNSi179DBgnq+9OphQr1def8by7g2PgCDXseGlBD+9a1lvPP1JXx5WdSob7Fkhh8VTZ3IHgtuRjdO1JxQG8WmLVHhK2uXSvZGKZmGfeX7SA1KxaAzUNHUQZfV1netI0Uqvj9Rid1epvm6UVmnbnilTs5q8EITvHW5FHsFq+t7qlLU5aHL6bB2sOX0FiwuFkod8fvhDL+/hzNIAyadmWpnV83wX4aMN9RzLZAnpTy3JdA9wDYpZTGAlLLXLUkFcqWU+VLKbuDvwIYLWfAVSVUWvP01pXVzKdNeDwdfUInQL26DiCUDPP3s+mxufvtmKtx9QO98/gne5nIwB3Oo8hB2aWdBoIrvSyn5xb9OEWA28Y+vLepLgPai0wlSwrzG1OlqfoQqZzxe0kKib6JK8ALMvB1qz6hKpZ52mL6KouYiytvKWRS0iPZuK9f9did3P7+fti4roBK7ZmcD0f7u5/d5hyHMx5WWTh0+Jl9KheNGM5rhz/4Idjwz9DFrFzSVUOSmblDTzMrwzw+cj0lvoqq9injfeE6WN+PqpCfSb+hkuq+bM3qdwKTzduze1UI9lxvjNfx3AVuGGI8BvIUQaUKIdCHE/Y7xEKCk37xSx5hGfzK2QMbrKoZ7KbP/z9DTBsu+O+Thl0++TGFzIfur0tUTwfnu4HV4/AcqDuBicOnravXxySqOFjfyn9dF4+p0YcKy0y3uuDnpyShtJNEvkdMNp+m2dUPCLaAzwmdPq+qkiGV9Mg2LgxdzIL+e1i4rR4ob+fKrh+nssXGkuJGUcK9xd9oajd6STl/nIEo7a9UGuZEMf08nvP9t9VTWVjf4eEMhSDtFTkrGYv8ZQVp2NSaDqe+pKt4nnsyyJhKCPIbdiKbXCSzuzujtntQI1CY3jcuKMRt+IYQTsB7YOsRhAyoMdCOwFvhvIUQMMNRvzpDZKSHEV4UQh4UQh2tqasa6rCuD0sPq9VI2/J1NcOAvEL8e/OMGHa7tqO1TrOzTvyk/BnbboLkjIqXD8AdxoOIAc/znYNQbsdrs/Orj08zwd+e2OaGjX2cU9DrBzFBPMkoamek3E6vdSnZ9Nrj6KBnonjYInQ8mD/aW7yXEPYQwjzB25tTgbNDxy9tmsr+gjq/87TDZlc0THuaBs4bfTRdAaUupqpYaqbLn6GsO71ue7R/Qn95STqxYXCz87uMinvk4G6CvuifOJ4GsiuZhwzy9qASvB9WyR+0q7moZ/wfUmDLG4/FfDxyRUg51ey8FPpJStkkpa4GdwCzHeH9hlVCgfKiLSymfl1LOk1LOs1iGL8W74rBZz3rGE7FBZ7I4+Fe1PX/50N7+1jNbsdqtTPOYphKlwbOV8awd527TjgawdVHt6kV+U35fGefW9FLya9r43tpYDPqJKUabFeZFVkUzMV4q7XSi9oQ6MPN29Tp9FT12JdPQW82zK6eWBVG+bJwfztO3zGRXTi12yYQnduGs4dfbfKlsq6THEgfVp4eWvbZ2wa7fQtgCcPWF3O2D51QcAwRF3Y2EuIXT3Kka1FQ1d3JT1E08nPwwQU7JtHfbRjX8/h4murvcqbW1YwfN67/MGM9f0N0MHeYBeBdYJoQwCCFcgQXAKeAQEC2EiHQ8MdwF/PNCFnzFUX0SrB3q66rMqV3LcHS3wb7nlILjuYlcoMfWw9bsrSwJWcLq8NWcaThDd8BMdXC8Cd7mMgAO2tVu1QVBC+jotvH7T88wJ9yLNQmDG6GcLymhXvTYJPVNrvi5+J2N88fdBAu+BrO/SGZtJm09bSwOXkxFUwe51a0sc+wDuGdBOE/enEB8kAdzJmjjVn9cnPRYzM70dPogkZR6BaubaeO5KTbgyN9UNdTKJ2D6tZD774E3CCkh8y2IWEpRaxmexuC+Q2nZ1bg7ufPY7MfIqewCIClksNxFfwI8nGlvd8WGpF6n0+L8lxljMvwOY34dsK3f2CNCiEcApJSngI+A48BB4AUpZaaU0go8BnyMuhG8KaW8hOMZU0BvmCdi2aUb6jn8siolHMbb3160nZqOGu6Ju4dEv0QVNtHbwMl9/Aleh8bPgc5KPJw8iPOJ4+W9BVQ1d/HE9fHn1cN2OGaFKWN9vLSJ2f6z2V+xH5vdBkYTXP8/4BnC3vK96ISO1MBUduXUArAs5qzG/4NLIvnXt5ZhNhmHfI8LJdzHldZWlYjOc1aduQaFe6xdsPt3ytuPWgXR16kGNhX9cizlR6Eul6aEm2joasBoVyWvJqOOz06fLRHNLGvC2aBjhmXkRHWA2URbh0r+apu4Lj/GZPillO1SSl8pZVO/sU1Syk39vn9GSpkgpUySUv6+3/iHUsoYKeV0KeXTE7v8K4DSwyppF3s9tNVceJ32RGO3wd7/VfLIYalDTnn99OuEm8NZGrL0bF18/SkISnGEF8ZBcxkSONB4htTAVASCzfuLWRbtR2qkz6inj4cgTxMWszMZJY2sjVhLTUcNh6oODZizr3wfib6JeDp7siunFovZmdgL6K41Xqb5uFJT74VAkIPyxqk+x0E4+n/qSWnF46rKavq1gICcT8/OOfEP0BkpDlZPYtYuX/Q6wfpZwezOqaXbqp4OMsubiA/yGDWcFuBpOrt7V5NtuOzQdu5ONWWHIWSeUoeES8/rr89XsgXJG4c8fLLuJBk1GdwVdxc6oSPQLRAfk48Km3hHQFPp+N6vuZwSo5GKjmoWBC2guL6dssYOrpvAEE8vQghmhXpxrLSRFaErcDO68WH+h2eX0t3MidoTLApehN0u2Z1Tw7IZfhP61DEaYT6uVDTaCXEPJaelCLzCB3r8vd5+6HyYfo0ac/NVyfXeOL/dpsI80Wso7FLSzs0tnoT7uHJdQiBt3TYOFdZjt0tOljWPGuaBgZu4qp1dNI//MkMz/FNJR4OqGQ+dBwGOHaGXWoK38rh6DUwedKi9p53nM57HxeDCLTNuAZQxTfJLUi0NPYKgtUolsMdKSzlHPVVyf37gfHbnqvDK4ul+I5113qSEeZJf00ZXj57V4avZXrSdLpvyrA9VqH0Ei4IWcbK8mYb2ngFhnotBuI8rUkKIWyS5jbngnzDQ8O95VilurvyvgbunZ1ynnibb66Fwl+PmfQfFLcUIBFV17kT6ubFkhi9OehXuKa5vp6XLysxRErtwjmyDi6cmzXyZoRn+qaQ3/h06D9z8wM3/0vP4KzNVkxJLbN9QU1cTf8n4C2vfWstnJZ9xX/x9AxQrk3yTyG/Kp83VVyleto0jfNVcToWL8iTDzGHsza0j0MPEdMvoypznQ2+c/0RpEzdE3UBrT2ufTPG+in19+wh25aoS4yUzLq7hn+bYpOZlCKe4uZguS4xyFqzdUHMGdj4DibfCjGsHnjhjNX1lnSe2gpMZYtZR1FREsHswRbXdRPi64epkYEGUD59nV5NZriK5icFjMPxmE6DHVe9JtZOLVtVzmaEZ/qmk9DAgzkocBCReepU9lSfALxYMSjLgQMUB1r61lj8e+yPJlmT+dv3f+Oacbw44JdEvEYkkS++o4R9PU5bmCqqdTPiYfDAII3vzalk8w3fSwivJIcrwZ5Q2siBwAb4mXz7I/wCAveV7SQ1Mxag3sutMLXGBZvzNpklZx3D0lnQ624OxSRsFZn+wW5Xxf+9bYHSBdb8cfGLIHNVH4PT7kPWeks02ulDUUkSgaygdPTYiHTfTa+L8ya9p48MTFTjpdcSMIYfh5WrESa/DWXhTYzBoMf7LDM3wTyVlh8E/nh4nF7V5KCARarLHFxqZbKoy1S5clGTCbw7/Bm9nb7bevJXnrn2O2f6z+6Z2WW28fbSUeB+VrzjZ46gFGI9RaC6nyqAnwDWAU5UqvLJkksI8AJ6uRqL83DhW0ohep+f6yOvZWbqT0/WnKWkpYVGwkmk4XFTP8hE0/icLi9kZZ4OOng6V48jp3bH8yQ+heC+seRrMZ/MfbT1tSltfp1cx/5Nvq/0XM29HSklRcxFmvSrljHJIMqyKVRU+/8qsJDbQjJNhdLMghMDfwxmd3ZNqnVQhPY3LBs3wTxVSKo8/ZC5bs7dy5/t3UuUTDtZOlVC9FGirVUY7UOUfdpXt4lT9KR6e9TBxPoN3727eX8x/vpHByRIbwW7BZLY7DP5YDX9XK3Q1UYUNf1d/9uYq2YHJDq/MCvPiWEkjUkpujLqRbns3P9v/MwAWBS/iQH49PTbJsuiLG+YBZWDDfVypb/TAqDOSY2tVUhL5aaoEePZ9A+Y/sesJ7vrgLqx2qyrrBBVCjFxBXWcdbT1tGGzK0Pdq8UT4uRHl54aUo9fv9yfAQ1X21Mge6G5V/38alwWa4Z8q6vNVbXzofI5UH8Eu7WQ79yowXiJx/krHTtbAmUgp+UvGXwhxD+HGqBsHTbXbJX/bVwhARkkTiX6JZDblqvxA85CbtQfjuEFU2zoJcA1gT14tURY3Aj0nN7wyK9STmpYuKps7SfRNJNwcTkZNBgGuAUR6RLIrpxYng65P2O1iM83XldKGbiI9I8lpyge/aCWCd/OzAxK6J2tPklaSRn1nvaqqmn6tukkk3QZ6A0XNauNXd4cPzgYdgR5nf66r4tTNYCzx/V4CPJzp6nKjztaBFTSv/zJCM/xTRe/GrdB5HK9RlTNn7B3qD/VSSfD25hsCZrK/Yj/Ha4/zH0n/gVE3eLPSjjM1FNa1o9cJjpc2kuSXRFlrGQ3mwLF7/M1ldAlosLXja7JwsKB+UsM8vfQmeDNKGhFC9N3YFgUvQgjBrpwaFkT6jEn1czII83GlpL6daK9oVdmz+km4/SXwnT5g3qaMTZidzOiFnl1lu8DdAl/eDtf8EICCJtVgprHZk0g/twGicjclB+Gk17Ewauw3N3+zifY2NyRQp9XyX1Zohn+qKDsMTu7UuPlS0ab+YM40FajGH5eK4a/MBHMwuPny/PHn8Xfx7yvbPJdX9hbib3bmxplBZJQ2kejriPN7+IzD8FdQrVcx7K4uM+3dNpbM8J2QjzIS8UEeGPWCYyUqJ3FT1E04651ZHb6ayqZOcqpbpyTM00u4jytt3TaC3SKpbKukOXIJxN80YM7JupOklabxQMIDJFuS2V22Wx0ImQvOKlm7o2QH/i7+lNe6DJJcnh3uzcmn1jLDf+yb0wI8TLR3Onbv6rXdu5cTmuGfKkoPQfBsjtcrI+/n4seZhjOOyp5xGP7W6vErYI6VyhMQmER6VTqHqw7zUNJDOOkHtzTMq2llx5ka7ls4jXkR3tS2duFjiEIgyDSZxl7V01xGlUF51eW1TggBC6Mm3/CbjHrigzxIL1Kbm8I9wtl11y5WhK1gV44q41w6Y+qEA3uNtItUqqR5jXmD5vR6+/fE38PSkKVk1WVR21Hbd7yxs5HdZbtZG7GOkvrOIbX2jeMUv+tV6ASoNui1UM9lhGb4pwJrl/KmHWEeg87AjZE3UthcSLd/rBLhGovMbX0B/C4Rjr85OWuszYaAJP56/K/4mHy4Lea2Iae+tq8IJ72Ou1PDSXb0ac2rshLhGcFJnX3sHn9LBVWOGv4zZXqSgj0nrHn5aFwT58/hogYqmzoBcDEoXZxdObX4uTsTF3jxZBrOJdbx3l3t6uaT0zBQ8TSrLou0kjTuT7gfs5OZpSFLAVWO2ssnRZ9glVbm+F6D1S6JGKbJyngY0ILR6Kx5/ENht6tGS02ll1SjJc3wTwW1Z8DeA4EzOVF7gjjvOJL8krBJG/lmh2c5ku56L0deBVv32STsRFKTDXYrDX5R7Cnfw8bYjX3GsD+tXVb+kV7KjclBWMzOxAeZMeoFGaVNRHtFUyA7oat5bBUfzeVUu6obR1aJYPFFCPP0siElBCnhvYyziWi7XbInt5alM3wnvMnKeAj0MGE2GaioM+FmdBtk+P+c8WfMTmbujb8XgDifOHxNvuwu3d0358OCD4n0jETXrZ4aoibE8Dsjre4IdFS7eGiGfyjOfAR/XqQctJ9a4JkZw3dIu4hohn8qcIRyrJZ4MmszSbYkE+MdA8AZg8PAjLaRy9qtxLng/Juaj4TjZpJtUhuIUvxThpz2VnoprV1WHlwcAYCzQU9coAfHSxvxd/Wn2tahOu+MxetvLqPK2QWT3o0eq9NFSez2EunnxqxQT945VtY3llXRTF1bN8uip7Y/hBCCuEAzZ6pameE1g5zGs4b/WPUx0krS+GLCF/t2T+uEjiUhS9hTvger3UpFawXpVencGHkjBXXtAMO2VRwP/h4mQIer3pNaZxdNtmEoKo6B0MGNv1UiekYXOPOvqV6VZvinhKpM0DuTp5d0WDtItiQT7hGOk86JM111anv9aHH+7A+UmqeLNzQUTM4aja5kW1XIKdY7dsDhhrZufrf9DL/+JJuUMK++yhiA5FBPjpc04e/iT4e9h1Yhxmj4K6gyGHDVqcqSsWjGTCQbUkI4Wd5MbrX6zL06QUunMLHbS0yAmezKFmZ4zSC3MRcpJd22bp7c+yRBbkHcn3D/gPnLQpbR3N1MZm0mHxYo4bkbom6goLYVs8mAj9uFh9DMzgZcjHqc8KLaYNBkG4ai5jT4RMH8L8Gq/1Jieh0NU70qzfBPCVVZ4B/H8XolyJbsl4xBZ2C613RyGnNVi72a7JGvcfhl8AxTqpkNhWpD2IVwblenyhPgn0B2wxksLhZ8XVTYpbXLys/ez2LJLz/j2X/nsCDSl9/eObA5y6xQL1q6rGBXhrvaoB89wWvthrZqqoXEiDfOBh1erpOjcT8cN80KQifgnaMq3LMrp4bYADMBHhdXpmEo4gLNNHdaCTBF0NTVRG1HLS9mvkheUx4/Wvgj3IwDPfhFwYvQCR27ynbxYcGHJFuSCTOHUVjbTpSf24RIYAghCHDs3q3VoXn8Q1GTrSRPenHxho7GqVuPA83wTwVVJyEgieM1x/F29ibUrOKu0d7RqrLHzyHENRx1eVCwA+Y8AD7Toaf9wioqGovhmSgl7wvqJuKo6MluyCbW5+wv7i8+PMVLewpYmxjIx99ezgsPzCPqnKYdyWHK4Dc2q5xAld6gukONhMNoVNq7EDZPgjxNF1X+GFRd+pIZfrybUUZHt41DhQ1TWsbZn9hAlUTVW4MAlaz96/G/cn3k9SwPXT5ovqezJ8l+yWzL2caZhjPcGKn2JhTUtk1ImKcXfw8Tth6z2r3b2QQ9HRN27XHR06mKHYr2wZmPVXHCVGPrgbrcAQKHmLygs3Ho9pkXEc3wX2zaapWRC0jkeM1xki3JHCtp5IsvHiDKI5rajlrqvEKVIR/OMzjyqtroNfs+8IlUY/UXEO4p2qsePz99UiWemsugs5Fu/3jyG/P75BkqmzrZeriUu1LD+d3GlL5qk3OZYXHHxainrFaFE6pN7qN7/M3lWIFaaxs9XeZJ3607HLekhFBS38GmHXl0W+2XRJgH6Gv+0t6q8g2/PvRrXI2uPD7/8QHzth0p5b/fUfmhpSFLqe2oRS/0rI1YS2ePjbLGDiL9Ru6uNR4CPEx0dblRb+tUu3enIsH7/n/C0wHwhxR4eR28fieceu/ir+Nc6vOVoJ6ln7yJi7dSrO2e2ub0oxp+IUSsEOJYv3/NQohvnzNnpRCiqd+cH/c7ViiEOOEYPzwZH+KywhG7b/aNJL8pn2RLMv/MKFeyAPYQAHJcHR5ZXe7g863dcHSz6tjlEQTeDsN/IQneigwwuKiw0ec/g3ceBSDf3RertPbF9/+yMw+blHxtxfSRroZBryMpxIPcCvXrVe3qMXqMv7mMOr0eO5K2dneCPAdXEF0M1iQG4GzQ8ee0PJz0OhZEXrzKopHwdDUS6GGiuFaHr0n9v3x33nf7QnCgwnBPvZ/Fa/uLqGruZGmoKutcGLwQXxdfCutUH+MIP9cJW1eA2ZnWNtezu3cvdi1/Vwsce10J0m34E2zcrMbHKhMymdScVq/9PX4XRy5siuP8htEmSCmzgRQAIYQeKAPeHmLqLinlTUOMA6ySUtYOc+zqwmH4Mx0KiDP9ZvLhLuXZd7U7FBiFjYWg4oOh8waef/o91U913kPqe69wVTVwIQneigylwHnLn5W2zrHNgOC0Tm0Mi/WJpaaliy0Hi7l1dghhPqMbjlmhXry2vwhLoifVjKGWv7mib/NWS6sbAdFT4/GbTUZWJwTwwfEKFk/3xcVpamQahiImUCV4l85ZSlN3Exumbxhw/NW9hTS2q1rxHdk13D4vntuib2P99PUAFNYqwx814R6/O65ArV5PwMX2+M98rIQNl38fpi1SYUq9k/obmWpqsgGhQre9uHir145G8J6SVQHjD/VcC+RJKYsmYzFXBVUnwT2A4y2FCAQxXvFklTcDUFKjw8fkoyp7dMah4/yZ21RSN8rRZs/gBB6h5x/qsduh4jgEzVJSvuv/CKlfheg1ZLcUYdKbCDeH88LufLqtdh5dObK330tymBddVjseTn5UGYxjCvVUOasbSneXmaApCvWACvcAU17GeS5xgWZyqlv5f4t/yh9W/WFADqS1y8pfd+WzMtZCoIeJz7Or0QkdTy5+kjkBqt/D0eJG9DrRp8M/Efj368Q1Jbt3M7cpWZGwBep7IcDVT4VUp5qa08oxc+rnKJkuDY9/vIb/LmDLMMcWCSEyhBD/EkIk9huXwCdCiHQhxFeHu7AQ4qtCiMNCiMM1NTXjXNZlRFUm+CdwovYE072mU1Qr6bbZ0Qk4XdlCjHcMZxpzlABXbc7g88vSYdpi0PX7r/Oedv4ef32+ijcGOSpzdDq44Rm4902yG7KJ8Y6hucPG/+0r4qbk4EGJ3OGYFaoSvAbpSY2QKq8xUkKr5ezmLWn1nLIYP8CqWAs/ujGeu1PDpmwNQxETYKbbaqewrm1Q4rvX2//26hhWxlrYnVNLj+3sz9tul/wzo5zl0X64O4/6oD9mBuzeNRgvrlBbZ7PqK5x4y8C/B7dLxfCfGRjfh9aTqq8AACAASURBVLMef+fUVvaM2fALIZyA9cDWIQ4fAaZJKWcB/wu80+/YEinlHOB64OtCiMElCICU8nkp5Twp5TyL5dLytCYMmxVqTiP9E84mdovVL8A1cf59hj+vMQ+b74zBHn9zhfrDcnTs6rR28r0d3+OUh9/5e/wVx9Rr8MANWlJKsuuzifGJ4eU9BbR123jsmhljvmy4jyterkZ6usxUy26V5Gob4YbeXE6VyR2DMCJtrgMkgy82Br2OLy+LumhyEWOlVzYiu3JgYrDX218VayElzIuVsRZauqwcKTrrVR4oqKeiqZNbZodM6JqU4XdHIKh18bi4tfzZH6qd64m3Dhx38xv5d+1iYLepv1/LwP0vl0qMfzwe//XAESnloP9ZKWWzlLLV8fWHgFEI4ef4vtzxWo3KDaRe8KovV+rzwdpJlc80GrsaifeJ52hJI8GeJpbHWGjq6MHfFEGXrYtir2DlxffX9yg/ql6DVderT4o+4aPCj/hcb1MxzbHo+5xLxTGl7X6OZ1LZVklzdzPRXrG8vLeQdYmBY2rJ14sQgpkhnrS0uVFnbXdUfIzgDTZXUGV0wt3gC4gpDfVcqszwd0cnBhv+Xm//W6tVLHnJDD8MOsHn2WeN3z8zynB10nNdQgATib/ZGdBj0nlQ4+x6cWv5T76twp6h/z977xkeV3Xub99rep+RRr3LcpXcLdsYmxKIwdQQAvxJQkIoJwcSQnpIchKSkAZJSHLSkzeF0A4lBAgGbDDNVHfLtlxkq8tqI2nUNdKU9X5YozKWZEsukmXv+7rmkrX32nv2yDPPPPv3tKWx2+2Jk6/x+ysg3EuZM5GbXrqJOzbcwb3v3stvS56k2GSa9Fz+8Rj+jzOKzCOESBHRe08hxLLoeZuFEHYhhDO63Q5cApxmQ2UnkGgbhhKLMmqz4mexo8rPoqw4ZkfztEWfytMusdqUlzzUk6/drtI4o6MQnz6gbr6qddHirePJ7KkrUh1B9bHFUgf8qoDMRiYdgRCXzUsZ96kz4qx0ddmIIGk6Wr/2QLtq16AXmInDoBN4HeZxP9+ZjsWoJ8drjzH8HYFgjLcPKkBdmBPHmwfUkPveUJgXd9VxaUEKNtPJk3kA7GYDTrMBk/BEpZ4J8vh7WuHQa5D/kZhhNMDpofFHCzDfkZ0U+Ypo6Wnh3cPv8v8V/4NfeOOnhscvhLABq4F/D9l2hxDijuiv1wF7hBBFwG+AG6WUEkgG3olu3wy8KKVcdzJfwJSioRiEXg1cAdyGTGr8PSzK8gzkxLe2x6MTOkpE1NMfKvfU7lBVvSYbJf4SdvqUTFMdVtka45Z7pFSGP3XBsF37W/YjEHR3KNmtIG3sI/n6SXZZaO9SgURVvTtKil3leyDDNAiJiHhIdlnQT2JTtNOZWSlOShoGDf/P1h2grSfIV1bHSgoXzlLSYX1bgDcP+GgPhPjIwrRTck2J0epdn46J0/j3v6gaHc69dvg+e4IqauzrmphrGYloKmdZuJN4SzxPXfUUr93wGhdlXUSrwTDpGv+Yvv6llN2A94htfxry798BvxvhuDJguFU5W2kohoSZlLSVke5I51CdGqq+KMuD22ok3WPlUH0v2a5sDvZF3xj9hl9KOLwdZqsKzKcPPI1JZ2JV+ip2NkYloPEGeP0VqtpyBMNf4i8h05lJWWMIs0FHjnf8mSApLgsy2N+v3TC6USh/C6k309jXjivoItmlefujMTPZyfriegLBMHsOt/HIB5XcujKXeRmxfY0unJXI/S/v580DjWw86CPBYWLVKZpdnOy0UB100mQOqXGioT6VbXYqKX5WZcxE410x2KMxwq4mMJ28DKZx4TsArnRKO6qZ5p42sNltdtOu008Nj1/jJNFQDMkFlPhLmBE3gx3VrRj1YmDO6ewUJ/vr28lz51HeUQ3O1MHMntYq9aFKW0R3sJu1ZWtZnbOaeYnzaOn1022LG7/HX1cEQCA5nwe3Phgz4GN/y35mxc9ib107s1OcGMY5pAMg2W1BhtRra7DFHcXwb6Q1q5C+SB89PZNXvDUVmJ3iJCKhuLade57ZRbrHylcvmTls3axkJykuCy/sqmXDvkaunJ92XP+HYyHJZSYQsNMUDhCGU5/S2d0CZW+ooO5IbT3s0S+4ydT5ffuRCTMpbSslzzOYAu02uWkTckpp/BonQqAN2qroTZxFRXsFM+NmsrOqlfxU18As19mpTkp9XWQ6s6npqCGYMGPQ46/drn6mL2Z9xXo6g51cP/P6gT4/1XGZ4/f464pAZ2BzpJOHih/ilnW3cKDlAF3BLqo7qpkVpwx//nHIPBD1+MM29MKAb7S2DZ0+aNhDQzSrqL3TNqmpnKc7M6OS4Lf+vYtSXxc//uhc7COkZwoh+NDsRN491ExfKHLKZB5Qkl5Xt4rl+PW60Q1/oA3WfkX9n58Ibz+o4l9zrwNgY81G7tl4D7esu4Urn72SC7b9iF1m0+Tp/JEINJXQ5M2lo68jxuN3mV30CghoHv9ZQoPqxFnmSiAsw0z3zKSopnUgIAcwO8VFOCKxkkpIhqj2pCvDL6XS9/UmSCrg6ZKnyXPnsThpMZlOlWte4zyOlM66nZA0h32tqjWEUWfktldu4z+l/wEgyZJLa3eQOanHb/hVv/Y4Gk3mkT3+ircBaExQH45Aj3NSUzlPd3K8dkwGHSUNnXx0UToXzkoade0FM9W+bK8t5n12sklymgn2qfqOo87e3f4IbP0b7Hjk+J+s4h14//dQeBukzkdKyQ8/+CHvHH6HiIww3TOdlmC7ypyZLMPfVg3Bbkod6m8+1ON3mdRnqb23bVIurR/N8E8U/Rk90VYNpnAa3X1hFmUN1m3PSVXeXCigblXL7W41vaqzQen7yXPZ317G7qbdXD/reoQQA4a/2mIb33i3gcDuQvY27yXblc1Dax7CarDyk00/ASASUF5i/nEafo/NiMmgw0wcjXrdyMHd8rfA7KLeogzHZBdvne7odYJZyU7ibEa+c8Wco65dOd2L02zghsLMU9rpNNFpJhKN5fhGy96SErY9pP69f+3xPVGgHZ67E+Jy4JIfAlDkK6K+q55vLvsm/7zsnzx4wYMIBC16/eTl8kczekqN6k4sxvCb1d+pra994q9rCJrhnyiqN4E1npKAD7PeTF2TMnSLsgY9sX5vrqVVfRmUR78k8O1XRjptEf8++G/MejNXTlNtkVwmFy6Ti2q9DmRYeRtjof0wdDdD6gL2tewjPz6fTFcm/7j0H6Q70km0JnLYpwJ0s4/T8AshSHFZEGE3DYRUJsORbXvLN0L2ShoCPgQ6ZMih5fAfg59dN5/Hbj/nmCmvTouRjd/4EHcco6neiaKKuJTT4jMYRpZ6Kt+F5oOQVKCqz4+nidr6byvn5qN/Hgjarq9Yj0ln4kOZHwJAr9PjMXtoMRonT+MfyOjpxmVy4bUM5sW4TSrm1R4OTOoMXs3wTwS9nSr9LP9qSvwlTPdMp6i6nXi7iawhDc8Meh0zkx0cagiSZEuiPKIGf3NgnfL80xeztWErhSmFuM2DWRyZzkyqZbT/+FjlnlqVCupPmE5dVx353nwAMpwZPHnlkzx82cPsb+gg22s7oRL/ZJeZUNBFYzj6WoZ6g63Vqqgt93wauxtxGOIAvebxH4M5qa4xx13i7KZTnhqb5DQjw1HDP9rs3a3/AIsbrvm9+n3/i+N7kgPrlES08ouQpfryRGSEVypeYWX6ShymwVYi8ZZ4/Cbr5Ek9TQfAkUxp12HyPHkxd1sDHr9eN6kBXs3wTwT7XlB5xfNvpMRfwsy4meyobmVRpmfYLfisZBf76zvIdedS3lMPRjvs+RcA3UlzKG0tZa537sD6dw81kWpPp7o//XOsAd66IhB69kVt+hzvoGzgNrvJcGawt7b9uGWefpJdFnoDDrojfWoE49AAb/lb6ue0C2joasAi1MjFJKdm+KcSSS4LSAMWnTNavXuEx9/VDPv+A/NvhNSF4J0xvn75vZ3wwhcheS5c+K2BzTsad9DY08ianDUxy+MscTQbjJNn+H0HIHEWZa1lMYFdGOLx63STmsuvGf6JYNcT4MmmKXEGLYEWcpzTKfV1xsyp7WdOqhNfRy+p1izK2yqQCdOVVmmwckAnicgIcxOU4S+qbuWTf91Ee4ebuu5Ggnrz2D3+uiJInMXeNpXCOdTwg+r/UtHcfcKGP8Vlob1T3dU0GvRQs2VwZ/lGVWWZlE9DdwN66SHBYcZk0N6WUwmH2YDdpFfVu0bTcI2/6HHVU2fJZ1T65ZwrVZC2u2VsT/D+71QriCt+CYZBeWtd+TrMejMXZl4YszzeEo9fp5scjV9K8JXQEp+Dv9dPljOXp7dWs25PPTuq/PQE1PW36XSTmst/cuu3NYbTdhjK3oILvkFJq0rNNMsMpOwZMVumv3WDhVQ6g5344heTFK2u3ePfB0CBVzU/fWyT6o4dDMQRlmHq47PIHGvbhtYq8Oaxt3kvGY6MgWyDfg7Uq+DT8aZy9pPittDX68QANKQtZNqG76kP/7l3q79L7vmEZYT6rnocwVxN35+iJLkshCNumnStsW0b+oO6mcshWcmJzL5KjfksWQ8LP370E3c0wLu/gTlXD0g8AOFImFcrX+X8jPOxGWPnQ8RZ4mgRkcnx+LtboLeNUpsbWsDX7OG+dbuGLIjgmi2Ux69JPWcwu58GJMz/f5S0KMPf06UqC/uzeIYyO7qttyea2eOMBobSFrGnaQ9JtiQSbYm0B4K8UKQ8q45OdedQ7U4ee7+eznpwprCved+Avj+U/hkBx5vK2U+yyzKY8XHu51TRzav3wlOfVtcw7QL2+/fTHeom2JV5Wgw21xg/SU4zkaATH2HlaYdVVToV76hJcktuGVyctkj10B9Lds+bP4FwL3z4+zGbtzVsoznQzKU5lw47xGvx0iZDBLub1BfPRBKVWsuid62dHV5MBh0v3LWKv3+mkII0D3ppiWr8k+fxa4b/VCIlFD0BGcvAm0eJv4QkWxKVjQKn2UC6Z3iFaoLDTILDTItfGfPyaEM30hezt3nvgL7/3I7D9ATDTEuw0+RXGQ7VVpcaxH6sAplQL/T4abN6qOmsGSbzAOyt68BjM56wB57iHuzX3tjnh4/9HVbcpTRfgNwL2FS3CYBWf7bm8U9RkqKzd5vCASJI+FUB/G4ZPHO7CuoWXDO4WKdTrUcOvQZ93aOftHE/bH9Y5ex7YzOT1lWsw2qwjjhoPt6iYkVtsg/6Ok/K6xszLWUAlMoAdqOdmmYTeYkO5mW4uWh2supwG7FGPX7N8J+Z1O8C3z5Y8P8ABgK7++vbmZ3qHDW3emayg+omIzaDjXKTGZbfQXvOuVS0V1CQUICUksc+qGJeuptL56ZQ12zCpDNR7Y0ODnn0WpXzPBqdqmvj/uhUwXxvPgcbOggNGdyxt04Fdk80/zvFZQFpwqJz0NDVoD70l/4YrvwVLP0viMthU90mcl3TaO+0ahk9U5Qkp5mubjshIrSecwfMWK0aCibnw+r7wHiEkzPnSgj1QOlro590w/fA5IALYgfKhyIhNlRu4MKMC7EahjtPcRaVDt2s00+83NNSDgjKAj7y3HkcauxkRtJgxpHbaiQUsmvB3TOaoifVCMWCawlGgpS2lTLTM5P9dR0DWv5I5CU6KGvsItedS1lnDVz2AHu7agCY653L9io/Bxo6+OTyLLLjbYQigmRbGtWRXrjhYWjcC098AoKBkZ8gavj3RlT3Ql1fBqt/tZHPP76dvlCEcERyoL79hGUeUH1cAKy6OBq7Gwd3FN4KV/yCvkiQ7Q3bKYhfAqB5/FOUZJeZvt5o9e6yW+Ejv4Mb/gmfelYFdVHDfbY3bCciI5C9Uo0h3DeK3FP+NpSsg1VfBnvswPsNVRvw9/oHZJ62niDvHGzimW01/P6NQ7xcpLx8v143CYa/TDVna68gy5lLdUvPCIbfSpvBqHn8ZyS9nUrfn3kp2OKpaKsgFAmRYM6hozc0oOWPxPQkBx29IdJs2ZS3Kc2wuEkNaS9IKOCxD6pwmA1ctSCNLK8KbHmMqdR01sDMS9TQ9Iq34ZnbBrXWoUSHZezrbSbNnsbBeqWDri9u4HOPbeNAfQeBYOSEM3oAzAY98XYTBumJNfxRinxFBMIBMq3zAbR2DVOUJOeQIq6ekaXGt2re4uZ1N/Ny+ctq/sOcK2Hv86qeYyiRMKz/lhqycs6dMbuae5r56aafMid+DudnKpnnzke3cdPfNvHVp4v4+foDPL9NtUNo0esnvojLX05bfBZNPU249aqP1ozkQcPvsRmRYStteoMW3J2yHN4G92fB2i/Hvnn3vwi/Xw5djbD0NkDJPACyVw1aOZo3nReda2vTpdLQ3UBXsIvi5mIyHBnIsJW1u+v46KJ07GYD2dF2yWYSqe6oRkoJ82+ANfer4Nn7w7plDxTY7O2sZo53Dntq2vDYjPzwIwVs2NfIrQ+plMsTzejpR1V2ukc0/JvqNqETOjw6NQFMk3qmJkkuM5H+2bvdIxv+pw48BcCGyg1qQ7+Es/7bsQt3PAr1u2H1D2IkIiklP3j/B3T2dfKTVT/BqDPS0B7g/bJmbl6RzZtfu5Ad311NJKw+E8rjn+CUzpYyylwqeUOE1LSz6UmDTl6/4W/XCc3jn7KUrFda+vZH4DeLVJHJE59UMovFBbe+AnkXAbCveR8GnQF/qyrgmHWUMYZ5SeqNK/pUk62K9gr2NO1hbsJcntl+mL5QhE8szwKUh2zS65BBLz2hHpoDzeok59wJ3umDXT2H0tlIp9BR2XWYfG8+e2rbmJfu5lMrcrj/2nk0dAQw6sXAF9CJkuIy09frpCnQRCgSeweyqW4TBd4CWjtVZrFm+KcmQz3+pp7hXnZtZy3vHH4Hq8HKu7Xv0hPqUf30z/+qCvQfin4ZBNrh9R9C5jlQEDtk5fnS53mj+g3uXnw30+PU/OcXd9UhJXz63BxyEuzE2U3Y9Q4EOpr1E6zx93ZAl49Ss/qy6uxMwKgXZHsH003dViMyYqMDSSRwGht+IcQsIcTOIY92IcSXjlhzoRCibciae4fsWyOEOCCEOCSE+OapeBGTRvVmVU34xZ2w5GbY+bjKVPjwD+C/N8aUlr9a+SrLUpZR0tBDttc2YivdflJcFuwmPV1dStvcVr+Nuq465ibMZcPeBvJTXQN3DHqdICPeSneXygKq6agZPJE7U/U2OZLOeva5lVcy3T2LkoaOgZkANy7L4o+fXMz/XD7npBVSpbgtdHfbicgILYHBop2uYBd7mvawPHU59W0B3FbjSR8NqDExJLnMII2YdfYR7+yeOfgMQgi+texb9IR6eK/2PbXj3Lshfhq89A2Vbbbx58pLX/PTmF77tZ213L/5fpYkL+GmOTcNbF+7q5Y5qa4YJ8XrsGLESYvBPLGGP5pKXaqTWA1WapvMTEtwYBwyB8FtNSHDViICOk9nj19KeUBKuVBKuRBYAnSjhqYfydv966SU9wEIIfTA71GD2vOBjwshhieNT0UiESX1ZC4FdwZc8SB8ZR98uRhWfSlmhu22hm3UdtVyVd5V7KtXg02OhhCCvCQHDS0O9ELP2jIVAJsTn8+ew20syY6LWZ8db6OlTX0RVHcMkZzcGaMY/kb22dV6UzibYFgyL32w98+aual8ZmXuuP4cR0ONYIxW7w4xCtsathGSIZanLqeuLaDp+1MYp9mA1ajHLDzDPP5gJMizB59lVfoqrsy7EqfJyetVr6udBjNc9nNoKYWXvg4f/BEWfhLSBydrSSm59717kVLy41U/Rq9T6WiHW3vYXtXKlfNTY54v3m5CJx34TZaJ1fijqZxl4U6muadR2tjF9OTYu2a3VUk9AG29k9ehc7wu3cVAqZSycozrlwGHpJRlUso+4AngI+N8ztMT337VOC1j2eA2e8KwDASAtWVrsRlsnJtyIRVNXUfN6OlHZfYEyHRmsq9lHwKBVWbR0RsaNmYv22unzmdBII4w/Jmqb0qoN/bkHfXsNZlItiVT5VNvgaGG/2ST4hrM5a/rGizn31S3CZPOxMLEhTS0BzSZZwojhCCpf/buEcHdjdUb8fX4uH7m9Rh1Ri7MuJA3q98kGIl2p5zxYZh9JWz/p/oiuPjemOPfqH6DTXWb+NKSL5HuSB/Y/uIu1eHzqvmxQ2YSHCZkyEGLwTCxGn+0XUppdwPZzlwqW7pjMnqgX+NXTlB7sH3iC8yijNfw3wj83yj7VgghioQQLwshCqLb0oGhIfua6LZhCCE+K4TYKoTY6vNNUh/t8VCzWf3MXHbUZYFQgPUV6/lw9oepbg4RkWOrhp2e5KCuLUCmMxuAXHcuB+vVB2VBRmyPn6x4G119giRbcqzh90Tz+tsPx568s5FynWS6Zzq7D7fhshjIjD914w6T3RYifQnYDA7u33Q/B1pUv/JNdZtYmLQQi8FCXVtAS+Wc4iQ5zciQc1hw9+mSp0m2JbMqfRUAF2ddTHtfO9satg0uWvNTsCfBRd8BZ8rA5mAkyK+2/Ypcdy7Xz7w+5rxrd9UxP8M9kNnWj9duJhS0Rfv1TKzHH7Al0NDTiEOfgpQwIyn27t5tNUK/x49UzRsngTEbfiGECbgaeHqE3duBbCnlAuC3wHP9h42wdsSvOCnlX6SUhVLKwsTExLFe1uRRvQWs8UqfPApvVL9BV7CLq/OuZn99fxuEo0s9AHmJKsDrMajvybkJc9lV04bNpGf6EV5EToJ648ebUodLPRAr90gJnQ00ESLJlkRxbRtz092ndFBHissCEQufnf4gCLh53c28WPYiB/wHBvR9X0fvsNelMbVIclno63Xg6/Gp7DJUzOm92ve4dsa1GHQqfnNu+rlY9JbB7B5Qgd6v7BuWvvlMyTNUtFfwlSVfGTgeoLK5i101bcNkHoB4h4neXhsthCdY4y+nJj7qbAVVy5UZR0g9Rr0Oi05ta5/Etg3j8fgvA7ZLKYdNWZBStkspO6P/fgkwCiESUB5+5pClGcBxTGA4DanZDBlLRx72PIQXSl8gxZ7C0pSl7KvrwGbSkxlnO+oxwIAR1IdVSliBt4BdNa3MTXMP66+eFa++JGw65fFHZLQCt9/wD0017W4hEgnSHOklzuxlf13HKZV5YEhufjCVxy5/jHRHOt98W8X5l6cu591D6sN5bl7CKb0OjVNLf/VuMBLkRx/8iN9s/w33b74fIQTXzhjM0LEarKxMX8kbVW8MvlcB9LGB/c6+Tv5Y9EcKkwu5IOOCmH1rdynJ8Ir5w2cJe+0mwkEbHYTpm8h+PS3lVDnVe7iry4NeJ8iJplsPxWUe0pp5knL5x2P4P84oMo8QIkVEXUYhxLLoeZuBLcAMIURu9I7hRuA/J3bJpwHdLWoWbubSoy5r6mnivdr3uCL3CnRCx/76dmalONGNYTBGVrwdvU4gAtNItiWzLOUcimvbmZ8x3EhnxlsRAhxyJi2BFn6+5efK43JFVbWhHn9nA36djjCSSMhJXzjC3FNs+PtHMDa0B0ixp/DPNf9kZdpKUu2pFHgLePdQE/F20zGD3hqnN8kuCz0d2WQ4MllXsY6/7fkbb9W8xSXZl5BiT4lZe3HWxTT2NLKnac+o5/v7nr/TEmjha4VfG3ZHunZXHYuzPKP2u5Jh5Tj5CatY3Kkm1AttNVRblaH3tTjI8dpGzIxzR4exTGa/njHlzgkhbMBq4L+HbLsDQEr5J+A64E4hRAjoAW6U6l4vJIS4C1gP6IG/SymLT+5LmAQOR7XJjKPr+y+Xv0xYhrkq7yqklOyr6+DyecNvTUfCZNCRHW/D53ey4aYNFNe20RuKDAvsgqqOTXVZMHYXctOcm3h036PEWeL47PzPgiM5dhxjZz1NBpUV0dGlPjSn2vD3j2Csb1MtJBwmB39a/SeC4SB6oefd0iZW5HnH9IWocfqS5DQTCaTz+/OfYlqiAyklPaGeEfvpnJ9xPgZhYEPVBuYnzh+2v76rnof3PszluZdTkFAQs+9gQwf76tq598qREwTj7SZktIirRa8juatJNYo7lfgrAUm1TuA2uyk/LEet1Ymz2qmTBtWTf5L69YzJ45dSdkspvVLKtiHb/hQ1+kgpfyelLJBSLpBSniOlfG/IupeklDOllHlSyh+f/JcwCVRvBqGD9CVHXfZC6Qvke/PJ8+RR3x6grSc4Jn2/n7wkB4caVd+RXTXqT39kYLefLK+NKn8PX1/6da6cdiW/3fFbVSl5ZEpnZyNNemX4G/xGnGYD2fHHlp5OlGSXmfr22N5BRr2RUl8XDe29rNRknilP/+S0xg6VRSaEwGa0DXjrZb5OVvz0NfYcbsNtdrM0ZSnrytfRG+4ddq7/3f6/SCm5e/HdMdvDEcn/PLcHh9nAlQtGdqK80aweAP9EFXFF2zFXRQKkOzKobB6e0dOPx2ZEF7FOamtmrXL3eKjZDEkF+MI9fOed7/DO4XcGglkA/oCf7777Xfa17OPqvKsB2F/XAYyvv31eooOK5i5C4Qi7alpxW40xVYBDyY63U9ncjU7ouG/lfZyfcT4/+uBHbHS4Yg1/Rz2+qOGvbDRQkO6aEE872WWhsX1407j3StWHcuX04WmwGlOL5GhDvn7DfyQPv19JXVuAf21T78db5t5CXVcd/9jzj5h1Rb4i1pat5eaCm2PSNwH+/k45m8tbuPeq/FFHdCY4zESihr9Zp5uYXP5oDn91n584YxrhiGT6KB6/yuW3TRmNXwNUA6kaVbi1rmIdz5c+z50b7uSml25iY81Gnj34LFc/dzVrS9dy69xbuWHWDYBqcwwwaxw6dl6inWBYUu3voai6jfkZo2ffZHltNHX20tUbwqgz8osLfkGcJY71OqU9DgS4OhtpMqkPzKE6wdy0U3wLHCXFZaG+PRDzBQlqZnC6xxozdF5jajLg8Y/wBd/TF+aZ7crgv1Jcj5SSFWkruCT7Ev66+68DFecRp7wcYgAAIABJREFUGeGBzQ+QaE3k9nm3x5zjQH0HP19/gNX5yVy/JGPU64izDZV69BOTy99STtDsora7HpNUWYmjefxum5Fg2EabXq95/FMG337o64CMZRT5iki2JfO9Fd+jOdDM51/7PPe+dy+57lyeuuopvrzkyxh1qoL3rRIfeYl2XBbjMZ5gkP7MnuLaNkoaOkYM7PbTfydQ1aLygq0GKzmuHGpFRPU974728Omsp8niwGqw0xc0jBgzOBWkuC0EghHaewZ79YQjkvdLm1k53XtK00k1JgaX1YDJoBvR41+7q5aOQIjrl2RQ2xZg92ElXX596dfRCR0PbHkAgBfLXmR3026+uPiLMSMV+0IRvvTkTpwWAz+9dt5R3y8mgw6nyYEO/cS1Zm4pozY+k4iMEOyNRycgN2F4Rg+Ax2oiHLLSrjee3hq/xhCqBwu3inxFLExayHUzr+OFj77AT1b9hJ+d/zMeWvMQM+JmDB7S0s3m8hY+umjE2rVRmRbtP/JCUS2hiGRe+sj6PiipB6CyebAgJMWeQl2kR/3SH+DtaMBntGDTqbYPpzqw20//SMWhOn9xbRvtgRArp2v6/pmAEIJkl5mGETz+xzdXMT3Jwbcun4NeJ1hfrDrEpthTuHPBnbxZ/Sbrytfxq22/Yq53LlflXRVz/P++VsK+unZ+eu08EhzmYec/kkSHBQNOWoyWCdP4q12qqWJ7h5tsrx2LUT/i0v4iLk3jn0rUbAWblwaLnfquehYkLgDAqDNyVd5VXJZ7GToR+2d9doeqnL1mnIbfbTWS6DTz+n7V32ZB5uhGOmvA4+8a2JZqT6Whr50wDOr8nQ00GXSIsBO7SU/uCHnGp4L+dgxDDf+7h9RdyIo8Td8/U0hyWmhsj/X499a2s6OqlY8vyyLebmJ5bjzriwfLgW6acxPT3NO45+178PX4uGfZPTGfoTJfJ39+q4yPLc7gkoLYtNDRiLeb0EWc+E3mUy/1RMLgr6TKqhy1Op99VJkHhrRmFmga/5QhWrhV5NsFwMLEhUddLqXk39trOGdaPBljKNw6kumJDoJhSaLTfNQmZm6rEY/NSMUQjz/VnkpIhlV72qGGX0j6+hzMSZ2YwC4wULT26AeVBIJhQAV2ZyY7Rg3SaUw9kl1mGjtiPf7HN1diMuj42GLl+FxakMKhxs6BjDWj3si3l3+biIxwee7lLEyK/Uw9sG4/ZoOOey6bNebr8DpMyLCDFr3x1Ad322ogEqTaYMBqsFLdpBu4Wx+J/kZtPQL6elpGXXcq0Qz/eAi0q8Kt9CUU+Yow683Mjp991EO2V7VS0dzNtYtHD0Ydjf7e/AuOEtjtJzveRtVQw+9Q6W61Frt6c/Z1Q287vkgfvQE7aSMUv5wqUtwWvnPFHF7d28An/7qJhvYAWypatGrdM4wjPf6u3hDP7ajlynmpeGwmAC4pUNXo/XIPqAruRy9/lO+f+/2Y820ub2F9cQN3XJA3LgfB6zAT7LPSouPUSz39GT2ylxRbOsEw5IySfQeDPfkB2ns1j//0p155+aQtoshXRL43H6P+6MHaf2+vwWLUcdncsd2iHkl/n/H5o+TvDyXLa6fyCKkHoN6ZqDT+zga6hKBHhujusZHkPLZWejK5/bxp/OGTi9l9uI1Lf72RQDCi6ftnGIlOMx29Id4+6GPP4TYe+aCSzt7QwOAggFS3lQWZnhjDD7AgcUFMsVckIvnxi3tJdpm5/byj98Q6Eq+9v19P5NRLPf05/H1teIzqM5d9FAm1X+oBaO+bnNbMmuEfD7U7AOhLymdv894BfX80ekNhXiiq5dKCFJzjyOYZSv/c2yN78I/EjCQHNf4e3ojGBPoNf53Npfr1dDYMFG/19ToGBqFPJJfPS+Xx25cjUENklk+Ln/Br0Dh1TItmsnzqb5u58rfvcP/L+5mV7Bz2/l1TkMKumjYOt/aMeq61u+soqmnja5fMwmoaOVA6Gl67iUjITjdhAl2N0NU8/hczVlrKCOvN1HTXY5IqwNvfOHEk+vP4AdqC3SpGMMFo447GQ+1OcGWwt9dHMBI8puF/fV8j7YHQccs8AMty43n+8yuPmsrZzy0rc3hlbz13PraNR29bTmFOPE6TkzphgYZS6GzAF23XIMPOSdPWC3PieeELq6jx94wrvVXj9GfN3BRe/uJ5+Lv76AyE6AiEWJTlGSZTXlqQzAPr9vNKcT23jDD0pzcU5mfr9jMn1XVcn594h3mwelenI7V6E8y+/Phe1LFoKacxPotgpJdInxeTQUfyUT5bDrMBnYxKPToBgTawTawDpHn846F2B6QtpMhXBHBMw//M9sMkOc2sPIGsFSEECzKHf3BGwmkx8tAty0hzW7n1oS3sq2sn1Z5KnU6owe+tVQMevww5SZxgqWcoGXE2zpmmZfOcaQghmJPq4ty8BC4pSOFjSzJGDHROS3QwM9nBS7vrRjgLPPRuBTX+Hv4nmv45XhLspoGh6y1GM1R/MO5zjBl/BdVudXfd1ekmO9521KQJIQQOoyrkbNPrJyWXXzP8YyXQpsbDRQ1/mj2NOLOXV4rr6eoNDVv+SnE9bx5o5JpF6Rj0E/dnTnCYefi2ZdhMBj71t814jEnUyT618/B2mqKtbyMh54Rr/BoaQ7mhMJMtFX5e2xfb6d3X0ctvXz/ERbOTWDXj+GJA3iEef0vi9MH6m5ONlKods00Z8uY251H1/X7cpqGtmSc+l18z/GOlTnn5pKrA7oLEBbywq5bPPrKNVQ+8zu/fOERHIMjh1h5u/+dWPvvINvISHdyyMmfCLzUjzsYjty2jqzeEr9VKXUilzXF4Kz6rEx0GCNu0NEqNSeXmc3OYkeTg+y8UD6T4Avxi/QECwTDfuWLOcZ87pkOnNwcObx8+grR8I/xxJTScQMPgzkYIdlFlNGLUGanxmUbtpzUUj1XF7tp0OujWDP/pS+1OAOo9aTR2N7IgaQFbK/w4zAYWZcXx8/UHWHn/63z4wbd491AT37psNmvvXkWqe+JSJocyI9lJXpKdvoCb9lA3XUIoqcdsxaJzYzLocVm1EI/G5GHU67jvI3OpbunhD28cAmB3TRtPbavmlpU5R82FPxZxNiNEoh6/MwXCvVC3K3bR5r9Awx54+BpoLj2+J4pm9NQQItWWTiB49FTOfjxWM3ppoc1ghHX3HP/zHyea4R8rtTvAncXOripA6fvbKv0syvLw988s5T93rWTVjARW5yfz6lfO578vyMM4gRLPSKR7rHR2RasJDcrINxmMGKSbRIdZ64+jMemsyPPykYVp/OmtMsqbuvjBC8XE20x84eIZxz74KBj0OjwWBzqM+KPedYzO39sJB1+FGZeCDCvjP7SL7ViJ5vBXhdrxmI6dytmPx2pEhu20531IDXb664eh8v3xP/9xohn+sVK3E9IWUNRYhEVvIcOeR0lDB4uzVJra/AwPf/jkEn7z8UXHVaF7KkjzWPG3qTdhXXQknE8AYdekpHJqaIzE/1w+B7NBx01/3cTWSj9fv3TWScn28trNGHHSHAlAXA5UbxrceXA9hAKw8m646d8qwPrwNdA5zpz/lnKk0FHd3YiFaCrnWAy/zUQkbKXNaITbN6isnoevhl1Pje/5j5NjGn4hxCwhxM4hj3YhxJdGWbtUCBEWQlw3ZFt4yLFTc+xiT6v6Zk9bxC7fLvK9+RQf7iIiYfEY8usni3SPle4e5e3U2VW6WDMhQn12LbCrcdqQ5LLw5dUzOdzaQ36qi+sLM4990Bjw2k2IiBN/wA+Z50DVpsH25HufB3sSZK2AtIXwiSeVx7/unvE9ib+cZk8G3aFuZNCLQSdI8xw7duayGgmFrLT3toM3D257VU30e/VedTdyijmmyCulPAAsBBBC6IHDwLNHrovuewA1ZnEoPVLKoze0Od2JBnaDyXPZV/EYn5zzSbZV+hECFmYeu6J2skj3WJEhJ3qhp95iIwi0RHoRATuJyZrh1zh9+PSKbPzdfVw5P+240jdHIsFh5lC3nZZAC2RdArueAH8FOJKg5BVY+AnQRQvDss+FudfCgZcgEgHdGMWQljKqPWlALT3dHjLirGPK4vNE+/X4A9GhhrZ4+NSzqsLefPyxjbEyXqnnYqBUSlk5wr4vAM8AjSd8Vacb0Yrdg3Y3wUiQAm8B26v8zEhyqBarpymqF48OtzGRWoNRNWsDenrsWkaPxmmFQa/jq5fMGtegomMRbzcR7LMpw5+5XG2s3gQHX1EzKgquiT0g5zyVWtk4jiyflnKq7cr587e5x6Tvw2CjtpiWDQaT8v4ngPEa/huB/ztyoxAiHfgo8KcRjrEIIbYKIT4QQlwzwv7Tn7qd4Mlib5cK/syJz2dHVeuAvn+60t+Ezab3UiciA4Zfy+HXOBvwOkwEAi4auxvpicsBs0sZ/r3Pgy0BslfGHpB7nvpZ/vbYniDQBj0tVJnM6ISOwz7zmFI5YbBfT0ewfdhUuolgzIZfCGECrgaeHmH3r4F7pJQjNZ3IklIWAp8Afi2EGPErTQjx2egXxFafbwJGpY2H2h2Qtoji5mKcJid9gTjaeoKnveFPcJgwGXQYIvHUyyC+pJnA5FftamhMBF6HmXBPFmEZZk/LXshYCmVvQcl6mHPVoMzTjzsD4nKhYoyGv0WlclbrIiRZU+gIjC2jB/oNv42IDNMd6j72ASeZ8Xj8lwHbpZQNI+wrBJ4QQlQA1wF/6PfupZS10Z9lwJvAopFOLqX8i5SyUEpZmJiYOI7LOsX0+JUumLqQ4qZiCrwF7KhSJdaLs09ffR9UaXi6x0o46KGht4WGVXcDyvBrUo/GmY7XbiLcrbqC7mzcCVnnqOr7YPdwmaef3POg4t2xNU7rb8cc6sRrTgPGlsMPg1O4ANp628Z0zMlkPIb/44wg8wBIKXOllDlSyhzgX8DnpJTPCSHihBBmACFEArAS2HuC1zyxRAu3+lLmcrD1IPnefLZX+XFbjUxLOPVBmBMlzWMh0OMiLMPsa9kHgAxNTmdODY2JxGs3QcRGqjWbHY07IHOZ2mHzQvaqkQ/KOR962wZbsB+NaPFWdU8TNqFSOccq9bitJmTkNDf8QggbsBr495Btdwgh7jjGoXOArUKIIuAN4H4p5dQx/JEIbHsIhI6DVgehSGggsLsoyzNh06tOhHSPlbZ2dfu5q2kXZp0TIQzqQ6GhcQbjjc7mTbPOYadvJ5G0xaAzKplHb6CqvYoff/DjWMM7Hp2/pZx2RxKtfW2IUAJCMOYanv7gLkxOT/4xGX4pZbeU0iulbBuy7U9SymHBXCnlZ6SU/4r++z0p5Twp5YLoz7+dvEs/xUgJL38d9j4HH/ofiqOB3SzHLA42dp72+n4/aR4r/qjhL20txYQbr900oY3jNDQmg37nxqufRUdfB+UBH9y6Di7+HgD/KP4HTxx4gs+99jm6g1Gd3ZkC3hlj0/lbyqmOUy2je3viSHNbRx2wfiQmgw4zqrbmsX2P0RMafS7BqUD79I/Ga/fBlr/CuXfDeV9lb/Ne3GY39c1WpGTKGP50j5VIUMUiIjKCiLhI1PR9jbMAt9WIXiewy+kASu7JKARbPKFIiNcqX2OaexrFTcXc/cbd9IajTdxyz1PtE8LDu+7G4C+n2qlai/vbnGTFj69i32NMZZbxk7xZ/Sa3rruVpp5TPCJyCJrhH4l3fg3v/BKW3AKr7wMhKG4eDOwKAQsyjz0Y5XQg3WMFacZuUBW8kaCWyqlxdqDTCeLtJvoCccRb4pXhj7K1YSv+Xj93LbqL+1bex6a6TXztra8RjARVPn9fh0rjHo1gD7Qfptqs5Jq6ZvtRp26NhMtqJC70YX79oV9T2lbKJ178BCX+kuN6rePlzDX8/gp45bsQ6hvncZWw4ftQ8FG44kEQgt5wL4f8hwb0/VnJzuMepTjR9OfyOw2qV09vwK6lcmqcNXjtJpq71LS8/gFKAK9UvILVYGVV+iquzruaby//Nm9Wv8lvtv9GGX44utzjVzWs1TrwWhJo6RRjTuXsx2Mz0tYd5KKsi3hozUOEI2FuX3/7oOx0CjlzDf+r34P3fqOKNcbD3ucACR/+/kCeb0lLCSEZIt+bz87qVhZNEZkHIDXaN8SEuiXtmoQh6xoak4XXYaKlq49FSYuobK+kuadZyTxVr3F+xvkDw90/PvvjXJh5Ia9UvAKOREicc/QAb39GT6SHBMv4Ujn78VhNtPUEAcj35vPYFY9x38r7sBlPfZPHM9PwN+4fNPhb/jq+Y/f8G9KXqG5+UYqbVQm3S5dLRyDEgjHMvz1dMBv0JDrNiJD6sgprUo/GWYTXbqa5s5dFSap8aKdvJ9sattESaOGS7Eti1q5IXUFtVy01HTWQswqqPlAN04IB9YhEBhdHi7eqepux65IByIofn8fvthpp7RlUJFLsKVyYeeFxvMrxc2Ya/rd/AUYbnPdV1YO7fvfYjmsuVbpewUdjNhc3FxNviaeuWXnP86aQ4Qcl9wR71TWrql0tuKtxdpDoNFPfHmCGZxZGnZGixiJeqXgFi97CqvTYXP5lKSrPf0v9Fsg9H4Jd8NN0+HGyevz5PGiPzgj2lxMwu2nsaUIfVgWnY83h78djM9LaHTzxF3kcnHmGv+kQ7HkGlt4G534BDFbYMsYs0r3PqZ/5sVV9e5v3ku/NZ8/hNkwGHTOTT14jqYkgw2OlqyMZgzAS6UvQirc0zhrmZ7gJBCOU+/oo8BawrWEbG6o2cF7GecMklTxPHvGWeDbXb4ZZl8GaB+Die9Xjwm+puOFDl6v2zS1l1HhV++hgII4Ehxm7eXwT7VxWI72hSMzYyYnizDP8bz8IerMy+tY4mPcxNdwgMIbquD3Pqp7YnsF+4D2hHkpbS8n35rOrpo38VNekT9YaL2keCz5fFl+f/SQy5NKkHo2zhiXReRnbKv0sSlrErqZdSubJuWTYWiEES1OWsrl+M1JngHPuUKrBeV+FC7+p2iZ3NcE/Lof6PVRHhxu1tbvGre+D8viBAZ1/IplaFuxYtJTDrieh8BbVcxug8DZ1y1b05NGPbToIDbtVT+4hHGg5QFiGyY8voLi2nflTTOYBJfX0hiKUNao3mJbVo3G2kO6xkuKysLXSz8IkNRbEordwfvr5I65flrKMxu5Gqjqqhu/MXAaffk5N6+qsp8qiNP3GFgdZx2P4rarATDP8J8o7vwSdQRVd9ZO+GNIWqyDv0dqfFj8LCMj/SMzmN6vfBMAhcujsDTE3feoZ/vRoSufO6lYcZgM2kzZkXePsQAjBkpw4tlf6WZC4AGBA5unqDbF2Vy2RyKBdWJqyFEDJPSORvgRuXgveGVTbXDiNTupb9WMat3gk/bM8JkPnP3MMf6ANdj8Diz8NrtTYfUtvh6YDUPHO6Mfv+bcaw+ZKG9j0r5J/8bc9f+Oy3Muoa1Ze8lT1+AF2H27TZB6Ns47C7DgOt/bQ12fj3hX3ctfCuwD4w5uHuOvxHXz3+T0DPfFzXDkkWhPZUrdl9BOmzocvbKVGB0nWdGD8gV2AOLsy/G8f9E14T/4zx/Bb3HDXZrjgG8P3zb1W6f3b/znysY37wLcvRuZ5ufxl7nv/Plalr+LHK3/Mrpo2LEYd0xNP/46cR9Lv8feGIprMo3HWUZiteuJsrfBz/czrmeaZhpSSl3bX4zAbeGxTFT99eT9Sylid/xjGuKqjCqchBRh7H/6hzElxcdncFH77+iG++/weQuHIsQ86SZw5hh/UIIV+bX8oRitM/7Dy+Ef6zyx+DoQO5lwNwFvVb/Htt7/N4uTF/PLCX2LUG9l9uJWCNPeUbG7msRmxmVQxmmb4Nc425qQ6sRr1bKv0D2zbV9dBeVMX3758Dp86J5u/bCzjt68fAmB56nKaA82UtZWNes5gJEhdZx3GiArwHk9wV6cT/P4Ti7njgjwe/aCKWx7aQntgYmSfqWfFxkhnXycvl788+K2dsQw66lQq1pGUvgbpheBMpjXQytfe+hqz4mfxu4t+h9VgJRyR7DnczrwpqO+D0jn75R5tAIvG2YZBr2NhpoetlS0D217aXYdeJ7i0IJkfXF3AtYvS+eWrJfzf5qpj6/xAfWc9IRki1OvFZTHgsR1fm3OdTvDNy2bzs4/N5/3SZq7743t09R6jOdxJ4Iw1/L/b+Tu+sfEbvF/7vtrQP4ShelPswr4uNVoxRxVzbKjaQCAc4HsrvofDpGSdUl8nPcHwlNT3+xkw/FoOv8ZZSGFOHPvqOujqDSGl5MXddZwzLR6vw4xOJ/jZdfNZkOnhn+9VkOHIINWeqgq5RqG6oxqAzk43OQnjl3mO5IalmTx82zLWzE0ddz3A8XBGGn5ft49/lfwLgCcOPKE2Js9V1bw1R/xnVm+GSGhg8PK6inVku7KZHT97YMnuGlUDMJUNf7/On+jQDL/G2ceS7DjCEUlRdeuAzHP5vMEkEINex+o5Seyv78DfHWRpylK21G8hIkfW3fsNv88//nbMo3FuXgJfWT3zpJzrWBzT8AshZgkhdg55tAshvjTK2qVCiLAQ4roh224WQhyMPm4+mRc/Gg8VP0QoEuKynMt4q+Yt6jrrQG9QqVhHevyV7yp9P2s5TT1NbKnfwiXZlyDE4HSt3YfbsJv05E6BUYujkR5t1qZ5/BpnI4uz4xACtlb6eWl3HToBlxakxKxZkacaGW4qa2ZZyjJae1u5+rmrBx7ffvvbBEIBQAV2LXoLdc3G40rlnGyOafillAeklAullAuBJUA38OyR64QQeuABYP2QbfHA94DlwDLge0KIU9rasrmnmacOPMUV067gS0vU99PTJU+rnRlLVd+eviFtTyvfg9QFYHayoXIDERlhTe6amHPuqlGBXf0UGLU4Gv23o/2ev4bG2YTLYmRWsnPA8J8zzUvCEXe/8zM82Ex63itt5qKsi7hm+jXMjp/NzLiZ5LpyWVu2lrtev4vuYDfVHdUk2dIIRTiu4q3JZrxi0sVAqZSycoR9XwCeAZYO2XYp8KqUsgVACPEqsIZRhrafDP6595/0Rfq4fd7tpDnSOD/jfJ45+Ax3LLgDU+ZyJevU7oCclarjXs1WWPZfAKyvWM809zRmeGYMnC8UjlBc285N52SfqkueEC6bm8ozd1qYNgXTUTU0TgZLsuN4cks1oYjk1lW5w/Yb9TqW5sTzflkzTtNcfrjyhzH7Xyh9ge+8+x3u3HAnvh4fcYYsgDPT4z+CGxnBaAsh0oGPAkfO4E0Hqof8XhPddkrwB/w8sf8J1uSsIdet/mNvnHUjLYEWNlRuUB4/DMo9h7dBuBeyV9LY3ci2hm2syVkTI/McbOykNxSZ0vo+gF4nWBLNZ9bQOBspzIkjFJHoBKyZmzLimhV5Xg41dtLYERi276q8q3jgvAco8hVR3VGNiePrynk6MGbDL4QwAVcDT4+w+9fAPVLKI9vMjaSNjFgVIYT4rBBiqxBiq8/nG+tlxfDI3kcIhAJ8dv5nB7atSFtBljNLBXntXvBOHwzwVr6rLjF7Ba9WvopEcmnupTHn3FKhUsCmaiqnhoaGor+Qa3nucJmnn3OjOv/7pc0j7l+Tu4YHL3gQo86IPpiBxaibktXw4/H4LwO2SykbRthXCDwhhKgArgP+IIS4BuXhZw5ZlwHUjnRyKeVfpJSFUsrCxMTEcVyWoqOvg8f3P87q7NXkefIGtuuEjhtm3cCOxh0caDkAmcuVxy+lMvzJBWCNY135OmbGzWSae9rAsZvLW/jJS/uYl+6ekrdzGhoag2TEWblxaSZ3Xpg36pqCNDdOi4EPykY2/AAXZ1/M2ze+jexcTHa8PUYhmCqMx/B/nFG0eSllrpQyR0qZA/wL+JyU8jlUoPcSIURcNKh7CUOCvycTh9HB/37of/n8os8P23fN9Gsw680qyJuxFLqboalEpXJmr6S+q56dvp2syRkM6u6qaeXWh7aQ5rHyj1uWopvCgV0NDQ1VyHj/x+Zz/szRHUu9TrA8N35Uj78fu9FOVXP3lJR5YIyGXwhhA1YD/x6y7Q4hxB1HOy4a1P0hsCX6uK8/0HuyEUKwPHV5jMfej9vsZmXaSlXMlblcbdz0Zwh2Q/a5rK9Q30WX5iiZp6Shg5v/vhm31chjty8f9bZQQ0PjzGNFXgIVzd3UtvaMuiYSkVS1nOGGX0rZLaX0Sinbhmz7k5TyyGAuUsrPSCn/NeT3v0spp0cf/zg5l31sIhHJocbOgd8XJi2kqqOKZkcimF2w8zG1I3slb9e8zYy4GWS5sujpC/Opv23CqNfx+H8tJ9WtpT9qaJxNrJh2dJ0foKEjQG8oclzN2U4HzsjKXYA/byxj9a/eYs9h9V3VP4RhV/MeyCiEUAASZhK0eijyFQ3M23zjQCMN7b384voFU/Y/VUND4/iZneIkzmbk/aPo/JXNqhbojPb4pxpdvSH+srEUKeGR91XJQb43H4POwE7fTtWwDSB7JcXNxQTCAQqTCwFYu6uWBIeZldMTJuvyNTQ0JhGdTnDONC/vlzaP2pq5srkLmJo5/DD+Aq4pwaMfVOLvDrIoy8PzRYf59uVzcNvM5Mfns7NxJ8z8jFqYs4qtDVsBWJK8hM7eEK/vb+SGwswpXaWroaFxYqzI8/Lynno+99j2gVbsCzLc3LYqFyEElc3dGHSCVPfU7HZ7xnn83X0h/rKxjPNmJPCja+YSCEZ4epuqIVuQtIDi5mKC2Svhxsch/xq21m9lumc6cZY4XtvXQCAY4cr5acd4Fg0NjTOZ1fnJFKS5OFDfQfHhNnZU+fnRi/u49/liIhFJZXM3mfG2KTmfA85Aj//xTVU0d/XxpQ/PoCDNzZLsOB79oJJbV+ayIHEBj+x9hAOtJcydfQWhSIgdjTu4Ku8qAF4oqiPFZaEw+5S2E9LQ0DjNSXVbefHu8wZ+l1Jy/8v7+fPGMnpDYcqbuk5aV87JYGp+XY1CIBjmT2+VsXK6d6A9wadXZFPR3M2QidtTAAAK/klEQVQ7h5oGhi3vbNwJwP6W/XSHuilMLqStJ8jGEh+Xz0vVcvY1NDRiEEINTLn74hk8tbWGvXXtxzV163ThjDL8j2+qoqmzl7svGmyytmZuCl67iYffryTFnkKqPVUFeIGt9YP6/qt7G+gLR7hyQeqI59bQ0Di7EULwldUz+fqlswCYnjR1Gx6eMVKP8vZLOWdaPMujebgAZoOeG5dl8sc3S6nxd7MgccGg4W/YSrYrm0RbImt3bSbdY2VRpmeyXoKGhsYU4PMfms75MxKZkTx1Df8Z4/ELAXdckMdXL5k1bN8nlquWyo9vqmJh0kLqu+qp7axle8N2CpML8Xf18c7BJq5ckDol+25oaGhMLPMy3FiM+sm+jOPmjPH4zQb9iD22QQ0fOTcvgdf3N/JgoSrkerrkaTqCHSxJXsL64npCEclVWjaPhobGWcAZ4/Efi8KcOA40dJBmy8Wit/Dk/ifV9uRCNuxrICveRkGaa5KvUkNDQ+PUc9YY/iXZcUgJew53UZBQQEewg3RHOkm2FDaVt3BunleTeTQ0NM4KzhrDvzDTgxCwrdLPwkQl9yxJXsL++nY6AiGWT9OmU2loaJwdnDWG3xkdtryt0j/QsK0wuZBNZapL9PJc79EO19DQ0DhjOGsMPyi5Z2dVKytSz+WepfewJncNm8qbyYy3kubR2i9raGicHZx1hr+jN0RFUy835d+EWWdhc3mL5u1raGicVRzT8AshZgkhdg55tAshvnTEmo8IIXZF928VQqwasi885Nj/nIoXMVaWRHvwbKv0A3CwsRN/d5DluZq+r6GhcfZwzDx+KeUBYCGAEEIPHAaePWLZa8B/pJRSCDEfeAqYHd3XI6VcePIu+fjJirfhtZvYVunnE8uz2FSuBi2cM03z+DU0NM4exlvAdTFQKqWsHLpRStk55Fc7MPL0gklGCMHi7Di2VymPf1NZC6luCxlxmr6voaFx9jBejf9G4P9G2iGE+KgQYj/wInDrkF2WqPzzgRDimuO8zpPGkuw4ypu6aOrsZVN5M8tz47X8fQ0NjbOKMRt+IYQJuBp4eqT9UspnpZSzgWuAHw7ZlSWlLAQ+AfxaCJE3yvk/G/2C2Orz+cb8AsZLv87/zLYamjr7Yhq6aWhoaJwNjMfjvwzYLqVsONoiKeVGIE8IkRD9vTb6swx4E1g0ynF/kVIWSikLExMTx3FZ42NeuhujXvDXd8oBtMCuhobGWcd4DP/HGV3mmS6ieokQYjFgApqFEHFCCHN0ewKwEth7Ypd8YliMegrS3Pg6ekl0mslNmJrDkjU0NDSOlzEFd4UQNmA18N9Dtt0BIKX8E/Ax4NNCiCDQw//f3t3GyFWWYRz/X7JbaUtpCxatFln6wSoqLiU2KEgaKwYUi34wqNFAguGLJgIhpsaowWhCjVFjGkUCvgSlBgHf+sGASCNGo5bS2q0lEmmFSuk2Gij4Upbu7YfnWR3X7nTHfc7O057rl5zM2Zkz97l29uy95zw7cw5cnt/h8yrga5LGSX9kboyIvjZ+yB/kevwpj++bWStNq/FHxN+BUyfdd1PH/Hpg/RGe90vgtTPMWNy5Zyzm1l/s9vi+mbVSqz65O2H1iiVcdcGZvONsX2bRzNrnuLkQSy/mzRngE5ee1e8YZmZ90co9fjOzNnPjNzNrGTd+M7OWceM3M2sZN34zs5Zx4zczaxk3fjOzlnHjNzNrGUXUd80USQeAzou9LASenubTXw48Ns1lp1u3l/W3PWtT63dWZ3XW7jXPiIjpndo4IqqfgJt7WPZA6bo9rr/VWRtcv7M6q7NOs+bRpmNlqOfHPSz7VAN1e1l/27M2tX5nbWb9ztrM+vudtasqh3pmQtKWSFf8qp6zNsNZm+GszehH1mNlj78XN/c7QA+ctRnO2gxnbcasZz3u9vjNzKy743GP38zMuqi+8Us6XdL9knZJ2inpI/n+UyTdK+mRfLs43/9KSb+SdEjS9ZNqfV3SqKSRmrNOVafSrCdK+o2k7bnODbVm7ah3gqSHJG2qOaukPZJ2SNomaUvlWRdJulPSw7neG2rMKmlFfj0npoOSrqkxa37s2lxjRNJGSScWCVnq7UFNTcBSYGWeXwD8ATgL+BywLt+/Dlif508DXg98Frh+Uq0LgZXASM1Zp6pTaVYBJ+X5QeDXwHk1Zu2odx1wO7Cp1m0gP7YHeFET22oDWb8FfDDPzwEW1Zq1o+YJwJOk979XlxV4GbAbmJu/vgO4skTG6vf4I2JfRGzN888Au0gvyGWkjY18+868zGhE/BYYO0KtnwN/rT1rlzo1Zo2IeDZ/OZinov84KrkNSFoGvB24pWTGJrI2rVRWSSeTdqpuzcs9FxG9vFV51rJOsgb4Y0T8qcsy/c46AMyVNADMA54okbH6xt9J0hBwDmmv8sURsQ/SC036q1mNUlkn1WnETLPmoZNtwChwb0RUmxX4EvBRYLyhiP9WIGsA90h6UNLVTeWEGWddDhwAvpGH0G6RNL/SrJ3eA2wsna/TTLJGxJ+Bz5M+1bsPeDoi7imR65hp/JJOAu4CromIg/3O002prLPxPZdYR0QcjohhYBmwStJrSmacMNOski4FRiPiweLh/nddJX5250fESuAS4EOSLiwWsEOBrAOkIdSvRsQ5wN9IQxnFFfzdmgOsBb5XKtsR1jHT7XUx6SjhTOClwHxJ7y+R7Zho/JIGSS/gdyLi7nz3fklL8+NLSXubfVcq6xR1qsw6IR/ebwYuLhy1VNbzgbWS9gDfBd4s6duVZiUinsi3o8D3gVWVZt0L7O040ruT9IegxqwTLgG2RsT+0jlzlhJZ3wLsjogDETEG3A28sUS+6hu/JJHGDndFxBc6HvoRcEWevwL44Wxnm6xU1i51asy6RNKiPD+XtLE+XGPWiPhYRCyLiCHSYf7PIqLIHlTprJLmS1owMQ+8FSj6brSCr+uTwOOSVuS71gC/rzFrh/fS0DBPwayPAedJmpdrriH9v2Dmev1v8GxPwAWksc7fAdvy9DbgVOA+4JF8e0pe/iWkPZCDpHNg7AVOzo9tJI2VjeX7r6ox61R1Ks16NvBQrjMCfLLmbaCj5mqaeVdPqdd1ObA9TzuBj9eaNT82DGzJtX4ALK446zzgL8DC0q9pA1lvIO1IjQC3AS8skdGf3DUza5nqh3rMzKwsN34zs5Zx4zczaxk3fjOzlnHjNzNrGTd+axVJh/NZGXcqnVH0Okldfw8kDUl632xlNGuaG7+1zT8iYjgiXg1cRHp/9aeO8pwhwI3fjhtu/NZakU6FcDXwYSVDkh6QtDVPEx+PvxF4Uz5SuFbSlZI2TNSRtEnS6jz/rKT1+cRqP5W0StJmSY9KWjvr36TZEbjxW6tFxKOk34PTSOdOuSjSidEuB76cF1sHPJCPFL54lJLzgc0RcS7wDPAZ0pHFu4BPN/AtmPVsoN8BzCqgfDsIbJA0DBwGXvF/1HoO+Eme3wEciogxSTtIQ0ZmfefGb60maTmpyY+Sxvr3A68jHQX8c4qnPc9/Hy13Xg5vLP5zHpRx4BBARIzni2mY9Z2Heqy1JC0BbgI25Ga9ENgXEePAB0iX5oM0ZLOg46l7gGFJL5B0Og2cLtmsSd4DsbaZm68WNkjac78NmDh17leAuyS9G7ifdEERSGdZfF7SduCbpKt47SYN5YwAW2ctvVkBPjunmVnLeKjHzKxl3PjNzFrGjd/MrGXc+M3MWsaN38ysZdz4zcxaxo3fzKxl3PjNzFrmX+6xtFvJ8daOAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600eba8d68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "tečaj[tečaj['Valuta'] == 'EUR'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Iz grafa zaključujemo da su kupovni, srednji i prodajni tečajevi vrlo slični, te nam vjerojatno ne trebaju sva tri podatka (iz bilo kojeg možemo zaključiti ostala dva). Kako XDR nema kupovni i prodajni tečaj, želimo srednji tečaj proglasiti osnovnim, a kupovni i prodajni računati iz njega."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Država</th>\n",
       "      <th>Kupovni</th>\n",
       "      <th>Prodajni</th>\n",
       "      <th>Srednji</th>\n",
       "      <th>Valuta</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>MMF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.575765</td>\n",
       "      <td>XDR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01</th>\n",
       "      <td>MMF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.486219</td>\n",
       "      <td>XDR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-03-01</th>\n",
       "      <td>MMF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.351255</td>\n",
       "      <td>XDR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-01</th>\n",
       "      <td>MMF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.158269</td>\n",
       "      <td>XDR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-05-01</th>\n",
       "      <td>MMF</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.214160</td>\n",
       "      <td>XDR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Država  Kupovni  Prodajni   Srednji Valuta\n",
       "Datum                                                \n",
       "2011-01-01    MMF      NaN       NaN  8.575765    XDR\n",
       "2011-02-01    MMF      NaN       NaN  8.486219    XDR\n",
       "2011-03-01    MMF      NaN       NaN  8.351255    XDR\n",
       "2011-04-01    MMF      NaN       NaN  8.158269    XDR\n",
       "2011-05-01    MMF      NaN       NaN  8.214160    XDR"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj[tečaj['Valuta'] == 'XDR'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Prva, relativno očita, hipoteza je da \"srednji\" tečaj doista znači sredinu, konkretno aritmetičku sredinu."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.00000002290335e-07"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(tečaj[['Kupovni', 'Prodajni']].mean(axis=1) - tečaj['Srednji']).abs().max()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Odstupanje od $5\\cdot10^{-7}$ je očito samo posljedica zaokruživanja (jer su tečajevi zaokruženi na 6 decimala).\n",
    "\n",
    "Ipak, to nije dovoljno da rekonstruiramo i kupovni i prodajni tečaj iz srednjeg --- moramo ustanoviti kolika je razlika. Apsolutna razlika vjerojatno nema smisla, između ostalog jer su neki tečajevi bili dijeljeni sa 100. Pogledajmo relativnu razliku, odnosno omjer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Kupovni</th>\n",
       "      <th>Prodajni</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.121000e+03</td>\n",
       "      <td>1.121000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>9.970000e-01</td>\n",
       "      <td>1.003000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>4.673557e-07</td>\n",
       "      <td>4.681532e-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>9.969968e-01</td>\n",
       "      <td>1.002997e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>9.969999e-01</td>\n",
       "      <td>1.003000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>9.970000e-01</td>\n",
       "      <td>1.003000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>9.970001e-01</td>\n",
       "      <td>1.003000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.970032e-01</td>\n",
       "      <td>1.003002e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Kupovni      Prodajni\n",
       "count  1.121000e+03  1.121000e+03\n",
       "mean   9.970000e-01  1.003000e+00\n",
       "std    4.673557e-07  4.681532e-07\n",
       "min    9.969968e-01  1.002997e+00\n",
       "25%    9.969999e-01  1.003000e+00\n",
       "50%    9.970000e-01  1.003000e+00\n",
       "75%    9.970001e-01  1.003000e+00\n",
       "max    9.970032e-01  1.003002e+00"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame({vrsta: tečaj[vrsta] / tečaj['Srednji'] for vrsta in ['Kupovni', 'Prodajni']}).describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "std (standardna devijacija) od $<5\\cdot10^{-7}$ pokazuje da su stupci zapravo konstantni. Vidimo da je razlika 0.3% u svakom smjeru: kupovni je 0.3% manji, a prodajni 0.3% veći od srednjeg. Iz toga slijedi da ih lako možemo rekonstruirati, te ih ne moramo pamtiti kao zasebne stupce u tablici."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "del tečaj['Prodajni'], tečaj['Kupovni']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Država</th>\n",
       "      <th>Srednji</th>\n",
       "      <th>Valuta</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Australija</td>\n",
       "      <td>5.521513</td>\n",
       "      <td>AUD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Kanada</td>\n",
       "      <td>5.571587</td>\n",
       "      <td>CAD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Češka</td>\n",
       "      <td>0.302292</td>\n",
       "      <td>CZK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Danska</td>\n",
       "      <td>0.992650</td>\n",
       "      <td>DKK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>Mađarska</td>\n",
       "      <td>0.026849</td>\n",
       "      <td>HUF</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Država   Srednji Valuta\n",
       "Datum                                  \n",
       "2011-01-01  Australija  5.521513    AUD\n",
       "2011-01-01      Kanada  5.571587    CAD\n",
       "2011-01-01       Češka  0.302292    CZK\n",
       "2011-01-01      Danska  0.992650    DKK\n",
       "2011-01-01    Mađarska  0.026849    HUF"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Grafovi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pogledajmo primjer grafičkog prikaza: kretanje tečaja švicarskog franka kroz praćeno razdoblje. Jasno se vidi ogromni skok početkom 2015. godine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f600c0ecef0>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600c0ff860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tečaj.loc[tečaj['Valuta'] == 'CHF', 'Srednji'].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Možemo napraviti i grafove za svaku pojedinu valutu:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600c032390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600bf72b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600bf60ef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600be9c860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAEWCAYAAABmE+CbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3Xd8XOWV8PHfmVHvvTdbkm3cizAtlGAgQAgOCTWEkLIhpL2QTt59lyRs2A3ZBDZZyCYQAgESElpCc0IvgRiwbMu9ybZsdcnqvT7vH3NHHssqI2lGM5o5389HH4/ufe6dM7I0Z54uxhiUUkopm68DUEop5R80ISillAI0ISillLJoQlBKKQVoQlBKKWXRhKCUUgrQhKCUUsqiCUEpi4i8KSL/4us4lPIVTQhKKaUATQhKnUREEkXkBRFpFJEW63GOy/k3ReQ/ReQDEWkTkWdFJMnl/JMiUmede1tElrice1hE7hORF0WkQ0TeF5HC2X6NSo1FE4JSJ7MBDwH5QB7QA9w7qsxngM8DWcAg8EuXc38DioE0YAvwh1HXXgf8CEgEyoE7PRu+UtMjupaRUg4i8ibwmDHmt6OOrwTeMMYkupR7zxhzm/X9YqAMiDTGDI26NgFoARKMMW0i8jAwaIz5F+v8pcDdxphF3nxtSrlDawhKjSIiUSLyGxE5IiLtwNtAgojYXYpVujw+AoQCKSJiF5GfiMhB69oKq0yKS/k6l8fdQIznX4VSU6cJQamTfQtYCJxmjIkDzrGOi0uZXJfHecAAcAz4FLAeuACIBwrGuFYpv6QJQamTxeLoN2i1Oot/MEaZT4vIYhGJAu4AnrKai2KBPqAJiAL+Y5ZiVmrGNCEodSID/DcQieMT/3vA38co9yjwMI7mnwjg/1jHH8HRhFQN7LauV2pO0E5lpSwisgW4wxjz10nKvckYnc9KzXVaQ1AKsOYKnAJs9XUsSvmKJgQV9ETkLuBl4HvGmCO+jkcpX9EmI6WUUoDWEJRSSllCfB3AVKSkpJiCggJfh6GUUnPK5s2bjxljUicrN6cSQkFBAaWlpb4OQyml5hQRcatvTJuMlFJKAZoQlFJKWTQhKKWUAjQhKKWUsmhCUEopBWhCUEopZdGEoJRSCtCEEBRau/t5ZGMFzV39vg5FKeXHNCEEgTtf3MPtz+7i7Lte52cv7aOte8DXISml/JAmhABX3tDJ01uqWL8yi/MWpnHvG+V86Kev87cdtb4OTSnlZzQhBLi7X9lHZKid2y9bzH3Xr+Zvt5xNSkw49//jkK9DU0r5GU0IAWxHVRsbdtTxhbPnkxwTDsApmXGcVZTMwYZOdOlzpZQrTQgB7Kcv7SUxKpQvnj3vhONFqTG09w7S2Nnno8iUUv5IE0KA2niwiX8cOMZXzisiNiL0hHOFaTEAHGzo8kVoSik/pQkhQP385X1kxEVwwxn5J50rshJCeWPnbIellPJjmhACUEfvAKVHWvjUaXlEhNpPOp8RF0F0mJ2DDZoQlFLHaULwM3/fWcu2ytYZ3WN/veONfnFm3JjnRYTCtBgOag1BKeVCE4IfMcbwvad38IvXDszoPvvrOwBYmBE7bpnC1BitISilTqAJwY80dfXT1jMw8oY+XfvqOogKs5OdEDlumcLUaGraeunqG5zRcymlAocmBD/i/MRe1dJD5wzeqPfXd1CcHovNJuOWcXYsH2rUkUZKKQdNCH7koMub84EZ1BL213ewMD1mwjKFqdbQU+1HUEpZNCH4Edc35wP103ujPtbZx7HOfhakj99/AJCfHI3dJpRrP4JSyuJWQhCRi0Vkn4iUi8htY5wPF5E/W+ffF5EC6/j1IlLm8jUsIiutc29a93SeS/PkC5uLDjZ2sigjlohQG/umWUNwp0MZICzERn5SlNYQlFIjQiYrICJ24D7gQqAK2CQizxljdrsU+wLQYowpEpFrgbuAa4wxfwD+YN1nGfCsMabM5brrjTGlHnotc97Bxk5W5iYSardNu2N5f52VECapIYBjxrLWEJRSTu7UENYC5caYQ8aYfuBPwPpRZdYDv7cePwWsE5HRPZrXAY/PJNhA1jswRFVLD4Wp0RSnx0w7Ieyr7yQhKpTU2PBJyxamxlDR1MXg0PC0nkspFVjcSQjZQKXL91XWsTHLGGMGgTYgeVSZazg5ITxkNRf92xgJBAARuUlESkWktLGx0Y1w56bDx7owxvEmvTA9lvr2vmltZLO/voMF6bGM8+M8QVFaDANDhqPN3dMJWSkVYNxJCGO9s4xeN3nCMiJyGtBtjNnpcv56Y8wy4Gzr64axntwYc78xpsQYU5KamupGuHOTsy2/MDWGBVb7//6GqdUSjDHsr+twq7nI8VzR1nPr0FOllHsJoQrIdfk+B6gZr4yIhADxQLPL+WsZVTswxlRb/3YAf8TRNBW0DjZ0IQLzUqJHRgjtq5taQqht66Wjb3AkoUzGueqp9iMopcC9hLAJKBaReSIShuPN/blRZZ4DbrQeXwm8bqzdV0TEBlyFo+8B61iIiKRYj0OBy4CdBLGDjZ1kJ0QSGWYnKz6CmPCQKc9FcI5McreGEBcRSlpsuI40UkoBbowyMsYMisjXgJcAO/A7Y8wuEbkDKDXGPAc8CDwqIuU4agbXutziHKDKGOO6Z2M48JKVDOzAq8ADHnlFc9TBxs6RyWIiQnF6zJSHnjpHGC2YZFKaqyIdaaSUskyaEACMMRuADaOO3e7yuBdHLWCsa98ETh91rAtYM8VYA9bwsOFQYxenzTveD78wPZaXd9dP6T776ztJjwsnISrM7WsKU2P4a1k1xhi3OqKVUoFLZyr7gdr2XnoGhihMix45tiA9luaufo5NYZtL5wijqShKi6Gjd5DGDt1OU6lgpwnBDzgXtStKPd7U43xj3+9mx/LQsOFAg/sjjJyci9y9f7h5kpJKqUCnCcEPONvwnaN+ABZkOB67O0Gtsrmb3oFht0cYOZ1akMTC9Fj+/YXdtHb3T+lapVRg0YTgBw42dhIfGUpy9PG2/9SYcBKiQtnn5iJ3Ux1h5BQWYuPnV6+guauf25/dNaVrlVKBRROCH3CMMIo+oVNXRFiQHut2DcHZtFSU5v4II6el2fHcsq6Y57bV8OL22ilfr5QKDJoQ/MDBxq6RIaeuFloJwZrSMaEjzd1kxEUQHe7WwLGTfPm8QlbkxPP//rqDho7ead1DKTW3aULwsbaeARo7+k7oP3BakO4YAVTXPvkbdFVLN9mJ42+ZOZkQu42fX72S7v4hvv/0DreSkFIqsGhC8LFDLmsYjeY8dtiNtYaqW3sm3EPZHUVpMXznIwt5bW8DT22umtG9lFJzjyYEH3MuLOdcaM5VlvUGX9M2cQ1haNhQ29pLzgxqCE6fP2sea+clccfzu6lp7Znx/ZRSc4cmBB/bXtVKVJidvKSok85lxEcAUDvJG3NDRy+Dw2ZGTUZONpvwsytXMGQM33t6uzYdKRVENCH42AeHm1mTn0iI/eT/iohQO8nRYZPWEKpaHAljpk1GTnnJUfzfS0/hHweO8Yf3j3rknkop/6cJwYdau/vZW9fBafOSxi2TmRBBbdvENYRqKyF4osnI6frT8ji7OIX/2LCHo026gY5SwUATgg99YC0XsXbe6M3ljsuKj5y0Lb/aOp/loRoCOOZB/OSTy+nuH+L57aO3v1BKBSJNCD70weFmwkJsLM+JH7dMVkIkta2TNxklR4cRFTa9OQjjyU6IJDk6bKRJSikV2DQh+NAHFc2syk0gItQ+bpnM+Ag6+gbp6B1/f+WZzkGYSHZi5EgNRCkV2DQh+Ehn3yA7q9sm7D8AyLSagWon6Fj2xByE8WQnRFLdon0ISgUDTQg+svlIC8Nm4v4DgCxr6Ol4/QjGGGq8nRBae3T4qVJBQBOCj3xwuIkQm7A6P2HCcpPVEJq6+ukdGPboCCNX2YmR9A4M09ylS2MrFeg0IfjIB4ebWZodP2lHcHpsODYZv4YwMgch8eSJbZ7grHloP4JSgU8Tgg/0DgyxrXLy/gNwLDqXHhdBzTgjjao9PCltNGdndbWONFIq4GlC8IGyylb6h4ZZ60ZCAMdIo/Emp1W3Ojp8vTXKKCchynoeTQhKBTpNCLOgvKGTv2ytoqd/CHA0F4lASb6bCSEhctw+hOqWHmIjQoiPDPVYvK7iIkOICQ/RuQhKBQHPzmRSJ+kfHOamR0s51NjFDyN3c+2pubx/uJlFGXHER7n3Jp4VH8Gru+sxxpywqxo4+hC81VwEjhnLzpFGSqnApjUEL3tkYwWHGrv43sWLOKsomd++c5iyyla3+g+cMuMj6RscpqX75Mlp1a09Xhth5JSdGKl9CEoFAa0heFFjRx+/ePUA5y1M5cvnFQKO0UIvbK/h0mWZbt8nK+H4XISk6LATzlW39EwpuUxHdkIkm4+0ePU5lFK+pzUEL/rZS/voGRji3y5bPHIsKyGSm84pJGcKw0RHNsoZ1WzT1jNAR9+g1zqUnbITI2nrGaCzb9Crz6OU8i1NCF6yvaqVJzZX8vkPzRtze8ypyIwfe3JalbWkxFSSy3SMzEXQZiOlApomBC8wxvDD53aRHB3O188vmvH9kqPDCLPbqBk19NTbcxCcRuYitOqaRkoFMk0IXrCzup0tR1u59YJiYiNmPhzUZhMy4iNOWgbbOfLH201GOVpDUCooaELwgkPHOgE82tmbGR9xUh9CdUsPEaE2kkd1NHtaSkw4YXYbVTr0VKmA5lZCEJGLRWSfiJSLyG1jnA8XkT9b598XkQLr+PUiUubyNSwiK61za0Rkh3XNL2X0APs5rOJYNyKQm+S5tv2sMSanOecgePtHZ7MJWQkRWkNQKsBNmhBExA7cB1wCLAauE5HFo4p9AWgxxhQB9wB3ARhj/mCMWWmMWQncAFQYY8qsa/4XuAkotr4u9sDr8QtHmrrIjIuYcOObqcqMj6CuvZeh4ePLUFe39nhtUbvRdKMcpQKfOzWEtUC5MeaQMaYf+BOwflSZ9cDvrcdPAevG+MR/HfA4gIhkAnHGmI3GsdD+I8DHp/ka/E5FUxf5ydEevWdWQiRDw4bGjr6RY97cGGc0x0Y5mhCUCmTuJIRsoNLl+yrr2JhljDGDQBsweueXa7ASglW+apJ7AiAiN4lIqYiUNjY2uhGu7x1p6qYgxbOf3Ecmp1kjjbr7B2nu6vf6LGWn7IQoGjr66BscmpXnU0rNPncSwlgN1KO3z5qwjIicBnQbY3ZO4Z6Og8bcb4wpMcaUpKamuhGub7X3DtDU1e/xGsLIXARrpNHPX94PwPKceI8+z3icI5lGj3RSSgUOdxJCFZDr8n0OUDNeGREJAeKBZpfz13K8duAsnzPJPeeko02OsfoFyR6uIcQfn6381OYqHnznMJ89s4Czi2cnSepGOUoFPnfWMtoEFIvIPKAax5v7p0aVeQ64EdgIXAm8bvUNICI24CrgHGdhY0ytiHSIyOnA+8BngP+Z4WvxCxVNXQAeryHERYYQFWbn1T31bK1s5czCZP71o6d49DkmkqMb5SgV8CZNCMaYQRH5GvASYAd+Z4zZJSJ3AKXGmOeAB4FHRaQcR83gWpdbnANUGWMOjbr1l4GHgUjgb9bXnHfEqiHke7iGICJkxkfw/uFmcpMiue9Tqwm1z940koz4CGyCzkVQKoC5tdqpMWYDsGHUsdtdHvfiqAWMde2bwOljHC8Flk4h1jmh4lgXabHhk+6VPB15SVHUtvXywGdKSPTyZLTRQq2tPLWGoFTg0uWvPexIUzcFHm4ucvrh5UvoGRhiUUacV+4/GcdGObqekVKBSpeu8DDHHATvTBbLT472WTIAnZymVKDThOBB3f2DNHT0UZDinRqCr2UnRFLbeuJsaaVU4NCE4EHe6lD2F5nxEQwOG5q7+n0dilLKCzQheNARa8ipt/oQfC01NhyAhg6dnKZUINKE4EEVVg0hL0BrCKmxjuUzGlzWU1JKBQ5NCB50pKmL5Ogw4jywKY4/SrNqCI3tmhCUCkSaEDyo4lh3wPYfgDYZKRXoNCF40JGmroDtPwCICLUTHxmqTUZKBShNCB7SOzBETVuvx9cw8jepseEn7MmglAocmhA8pLLZWuXUw/sg+Ju02HCtISgVoDQheEjFyByEwK4hOBKC9iEoFYg0IXiIcw7CvEBPCHERNLT3Ya1urpQKIJoQPKSiqYuEqFDiowJzyKlTWmw4fYPDtPcO+joUpZSHaULwkIpj3eQnBXb/ARwfetqozUZKBRxNCB5gjGFnTRunZPpuJdLZcnwugnYsKxVoAj4hGGN4fW897xw45rXnqGjqprV7gJW5CV57Dn+RZi1foUNPlQo8Ab9Bjojwnxv2khgVxoeKU7zyHFuPtgCwKi/RK/f3J2lxVg1Bl69QKuAEfA0B4LLlWWw60kxtm3c2d9l6tJWY8BCK0mK8cn9/EhseQkSoTYeeKhWAgiMhrMjEGHhxe61X7l9W2crynHjsNvHK/f2JiJCqk9OUCkhBkRAKU2NYnBnHC15ICL0DQ+ypbWdVXuD3HzilxUZok5FSASgoEgLAx1ZkUVbZOrLEhKfsrG5jcNiwMjfw+w+c0mLDaezUhKBUoAmahHDZ8kwAj9cSth5tBQiKEUZOabHhNLRrH4JSgSZoEkJuUhQrchN4YXuNR++7tbKFnMTIkfH5wSAtLoL23kF6B4Z8HYpSyoOCJiEAfGx5Jrtq2jnU2Omxe5YdbQ2K4aauUmOcs5W12UipQBJUCeGjHm42qm/vpaatl1VB1FwEkBqnO6cpFYiCKiFkxkeytiDJY81GI/0HQTTCCI7vrawjjdRseLK0krf2N/o6jKAQVAkBHHMS9td3sqe2fcb32lrZQpjdxpKswF/DyNXI8hU60kh52aaKZr7z1HZu/N0HfPUPW6jXwQxeFfBLV4x22fIsfvziHh577wh3XrFsRvfaerSVU7LiCA+xeyi6uSEpOgy7TbSGoLxqeNjwo+d3kRkfwXVr87j3jXLe3t/ITefMx2YTqlt7qGnt4cML07jxzAJfhxsQgi4hJEWH8fGVWTyzpZrvfmTRtPcvGBwaZkdVG9ecmuvhCP2f3SYkR4dpH4Lyqqc2V7Gzup1fXLuS9SuzuXxFFv/27E5+/sp+wPG3LMDmihauLsklMiy4Pph5Q9AlBIAbzyzgidIqniit5IvnzJ/WPfbVd9AzMBRUM5RdpcXp8hXKezp6B/jpS3spyU/k8hVZABSkRPPI59dS29ZLYlQYkWF2Nh5s4roH3uPl3XWsX5nt46jnPrf6EETkYhHZJyLlInLbGOfDReTP1vn3RaTA5dxyEdkoIrtEZIeIRFjH37TuWWZ9pXnqRU1mSVY8a+cl8fuNFQwNT28ryI0HmwBYkx9cQ06ddPkK5U3/83o5TV39/OBjSxA5vkaYiJCVEDlSGzhtXhLZCZE8tbnKV6EGlEkTgojYgfuAS4DFwHUisnhUsS8ALcaYIuAe4C7r2hDgMeBmY8wS4DxgwOW6640xK62vhpm+mKn43JkFVLX08Nqe+mldv2FHLYsz48hJDPxd0saSpgvcKS851NjJQ+8e5qo1OSzLiZ+wrM0mfHJNDu+UH/PaasbBxJ0awlqg3BhzyBjTD/wJWD+qzHrg99bjp4B14kjrFwHbjTHbAIwxTcYYv5jeeuHidLLiI3j4nxVTvraurZctR1u5dFmG5wObI9Jiw2nu6pt2DUup8fzh/aOICN/+yEK3yn9ydTbGwF+2Vns5ssDnTkLIBipdvq+yjo1ZxhgzCLQBycACwIjISyKyRUS+O+q6h6zmon8T13qhCxG5SURKRaS0sdFzY5FD7DY+fUY+/zzYxL66jild+/edjoltlyzL9Fg8c01qbDjDBpp06KnysA8ON7M6L2FkePNk8pOjWVuQxFObqzBGP6DMhDsJYaw36tE/9fHKhAAfAq63/r1CRNZZ5683xiwDzra+bhjryY0x9xtjSowxJampqW6E675rT80jPMQ25VrChp11LEyPpTA18DfEGU+q9ceqzUbKkzp6B9hV08bagqQpXXflmhwONXaxtbLVS5EFB3cSQhXgOrYyBxg91XekjNVvEA80W8ffMsYcM8Z0AxuA1QDGmGrr3w7gjziapmZVUnQYF5ySzttTmAXZ0NHLpopmLgni5iJw2UpTh54qD9pytJVhA2vnJU/pukuWZRARauNp7VyeEXcSwiagWETmiUgYcC3w3KgyzwE3Wo+vBF43jrrbS8ByEYmyEsW5wG4RCRGRFAARCQUuA3bO/OVM3fzUaGrbehgYGnar/Eu76jEGLg3i5iLQ5SuUd3xwuAm7TaY8nDs2IpRLlmby/LYaXYV3BiZNCFafwNdwvLnvAZ4wxuwSkTtE5HKr2INAsoiUA98EbrOubQHuxpFUyoAtxpgXgXDgJRHZbh2vBh7w6CtzU25SFMMGalrdG6Hwtx21FKZGUxwE+ydPxLnctzYZKU/adLiFpdnxRIdPfYrUJ1Zn0947yDsHjnkhsuDg1k/dGLMBR3OP67HbXR73AleNc+1jOIaeuh7rAtZMNVhvyLWGjR5t7iY/OXrCsk2dfbx/uJkvn1vIOH3gQSM8xE5CVKg2GSmP6R0YoqyqlRvPyJ/W9autZej31XdwweJ0T4YWNIJucbvR8pIdCaGyefIawiu76xkaNkHff+CUnRBJVYuO/Vaesb2qjf7B4Sn3HzhFh4eQFR/BgfqpjRpUxwV9QsiIiyDULlS2TL7X8os7aslPjmJxZnCtbjqevKQojnp4j2oVvDZVNANQMoPZ/4VpMZR7cAOsYBP0CcFuc0yFn+yN7cXttfzjwDGuWJUd9M1FTnlJUVQ19+jkNOUR7x9uZmF6LInRYdO+R1FaDAcbuhjW38lpCfqEAM43tvETwr66Dr7z1DZW5yXwlfOKZjEy/5aXHEX/0LCuUa9mbHBomC1HWjh13szWBitKi6FnYIgaXcZiWjQhADmJUVSO0xbe1jPAlx4tJTo8hP/99BrCQvRH5pSXdLxDXqmZ2FPbQWff4LT7D5yKrMmi5Q3abDQd+u6G442tuaufzr7BE44PDxu++ecyqlp6+NX1q0mPc28qfbDIT3KMyjrapAlBzcwHVv/BVGcoj1acHgtoQpguTQhAblIkAJWjPuk+vukor+1t4PaPLebUGf6iBqLMhAjsNtEagpqxDw43kZcURUb8zD50JUWHkRQdxkHtWJ4WTQiM3/Tx9v5G8pOjuOH06Y2LDnShdhtZCRGaENSMGGPYVNHisQ9dRakxHKjXhDAdmhA4PjltdA2hrLKVVbkJOqpoAvlJ0RzRhKBm4EhTN81d/ZQUeGazKefQ0+mufNrRO8Ddr+wPyiUwNCEACVGhxISHnDDJqq6tl/r2PlbkBucWme7KTYo6KZEqNRU7qtsAWJY98WY47ipKi6G1e4Cmrv5pXf/Xshp++doBNh5q8kg8c4kmBBzb8uWOmmRVVtkCwEpNCBNydsh39A5MXlipMeysaSPMbmOB1SE8U0VpMxtp9NY+x+aNFce6PBLPXKIJwZKbGHnCJ92yyjZC7cIpOit5QvnJOvRUzcyu6nYWZsR6bEh38QwSQt/gEP+09ks/rAkheOUlRVHZ0j3S7lhW2cLizDgiQu0+jsy/OTvktdlITYcxhh3VbSzN9twHr8z4CKLD7NNKCKUVLXT3D2G3iSaEYJabFEXvwDCNnY59gndUtWn/gRuciwMe0bkIahqqWnpo6xlgqYf6D8DRBFyYFjOthPDmvgbC7DbOX5SmCSGYHf+k28PBxk66+odYkaMJYTJxEaEkRIVqk5Galp1Wh/LSLM8lBHAMPZ1OQnhrfyNr5yWxJCuO6tYe+gaDa6SRJgSL6+S0sqOOfVlXTnHXpmClq56q6dpZ00aITViY4ZkOZafCtBjq2nunNNihprWH/fWdnLsglXkp0RgTfLPwNSFYclzmIpRVtRIbEcK8STbMUQ6aENR07axupzg91uN9dc6RRgcb3W/2eXOfY2/18xY6EgLAoSBrNtKEYIkItZMWG05li6OGsCInAZtNJ6S5Iy8piuqWHgbd3JdaKXB0KO+sbmNpludH8k020qihvZc39jacMHntrf0NZCdEUpQWQ4GVEIJt6KkmBBe5SVHsr+9kX32Hzj+YgvzkKAaHDbVtx5fBburso1H3W1YTqGvvpamrn2U5nu0/AMeHlDC77aSE0D84zP1vH+TDP3uTzz28iR+/uAdjDP2Dw7xb3sQ5C1IREeIiQkmJCQu6juWp72QdwPKSovjL1moAHWE0Bbkua0HlJkUxNGz41APvEx1u55mvnOXj6JS/2lndDsASD3coA4TYbRSkRFHe0EF77wAN7b3sr+/kZy/v41BjF+cvSiM9LoIH3zlMV98gl6/IorNvkPMWpo7coyA5WhNCMMtNjBx5vCLX87+kgcp1ccCzgOe31bCvvgO7TejqGyQ6XH/N1Ml2VLdhE7y2JW1RWgwbdtSx/IcvjxzLT47id58t4fxF6RhjSI4O4943ynl5dz2hduGsopSRsvNSonlrf6NXYvNX+pfqwvlJNzshkrRY3fvAXZnxkYTahSNN3QwODfPfr+4nKsxOd/8Q2ypbOdPlj0wpp13VbRSlxRAZ5p3Jn186p5DshEhSY8NJj4sgIy6ClXkJhIc4nk9E+PZHFhIVbuenf9/HGfOTiXH58FKQEs2Tm6uC6kNNcLxKNzkTgtYOpsZuE8euc83dPLOlmoqmbn521Qq+89Q2So+0aEJQY9pZ08ZZhd773ViRm+BW0+9XzivilMy4E1oIAOZbHcuHj3V5dOKcP9NOZRfOoWar8zyzDG8wyUuK4mBjJ7947QDLc+L55OpsFqbHssnaCUspVw0djtWEl/jJG+2HF6ZRlHbiXIh5qccTQrDQGoKL9LgInvjSGSz3wqiHQJeXFDXS3nrnFUsREdbkJ/JsWQ1Dwwa7DuFVLnZZHcqeWvLaG5xbxAbT0FOtIYyydl6SLmg3Dc6O5ZL8RM5d4BipUVKQSGffIPvqOnwZmvJDziUrFnthDoKnRIbZyYqPCKoagiYE5RGnZMYhAt+6aOHIDnMl+Y4tEUuPaLOROq5/cJgXd9RSlBZzQieuPypIieZwkyYA2qYtAAAdX0lEQVQEpabkrKJk3v+/6zijMHnkWE5iJOlx4ZRWtPgwMuVv7n2jnL11HXznIwt9Hcqk5qUE11wETQjKI0TkpKG6IkJJfhKbj2hCUA47qtq4741yrliVzUeWZPg6nEnNS4mmtXuAlmluxznXaEJQXlVSkEh1aw81rT2TF1YBY3jY8PXHt/KlR0s5UO/oQ+obHOJbT5aREhPGDz+2xMcRusc58jBYmo3casATkYuBXwB24LfGmJ+MOh8OPAKsAZqAa4wxFda55cBvgDhgGDjVGNMrImuAh4FIYANwi3FdaUoFhOP9CC1cnhA5SWkVKB76ZwXPb6shPMTGK7vruWpNLqEhwv76Th763KnER4X6OkS3OBe5O9zYFRTD0SetIYiIHbgPuARYDFwnIotHFfsC0GKMKQLuAe6yrg0BHgNuNsYsAc4DnAuU/y9wE1BsfV080xej/M8pmbFEhdnZrPMRgkZ5Qyc//fte1i1KY+P31/HZM+fxzNYqHnvvKNeU5PLhhWm+DtFtuYlR2G1ChdYQRqwFyo0xhwBE5E/AemC3S5n1wA+tx08B94pjqMlFwHZjzDYAY0yTdY9MIM4Ys9H6/hHg48DfZvqClH8JsdtYlZdAqfYjBIXBoWG+9UQZUWF2/vOTy0iKDuP2jy3mc2cV8LedtXzqtHxfhzglYSE2chIjg2ZfBHf6ELKBSpfvq6xjY5YxxgwCbUAysAAwIvKSiGwRke+6lK+a5J4AiMhNIlIqIqWNjcG10FSgWJOfxJ7adjr7Bn0divKyX715kG1Vbdx5xbITBhnkJkVx0zmFfj/MdCzFabG8W36MQ41T35JzrnEnIYw1xXR0W/94ZUKADwHXW/9eISLr3Lyn46Ax9xtjSowxJampqWMVUX6uJD+RYQNbj2otIVC19QzwyMYKfvnaAdavzOLSZZm+Dsljvn/pIuwifPq371Md4IMj3EkIVUCuy/c5QM14Zax+g3ig2Tr+ljHmmDGmG0fn8WrreM4k91QBYlVeAjZB5yMEoO1VrXzjz2WsvfNVbn92F0uy4rjj8qW+DsujClNjeOQLa+noG+T6B96joaN38ovmKHcSwiagWETmiUgYcC3w3KgyzwE3Wo+vBF63Rgy9BCwXkSgrUZwL7DbG1AIdInK61dfwGeBZD7we5YdiI0JZmBGn8xECTHf/INf85j1e3VPPVSU5PPe1s/jrV8+aMyOIpmJJVjwPf+5U6tv7+MyDH9DWMzD5RXPQpAnB6hP4Go439z3AE8aYXSJyh4hcbhV7EEgWkXLgm8Bt1rUtwN04kkoZsMUY86J1zZeB3wLlwEG0QzmgleQnsvVoi+67HEC2Hm2lZ2CIX163ih9/fBnLcxJGli0JRGvyk/jNDWvYW9fB05urJr9gDnKrh8cYswFHc4/rsdtdHvcCV41z7WM4hp6OPl4KBFbdUo2rpCCRR987wt66jqBZWz7QfXC4GRFYkx/44/OdzlmQSlpsODusxfkCjc5UVrPC+aahzUaBY1NFM6dkxBEXEXhNRBNZlh2vCUGpmchOiCQjLkLnI3jQwNAwf99Zx4APmuEGhobZerSVtfOSZv25fW1pdjwHGzvpCsBh1JoQ1KwQEdYUJOqMZQ/pGxziK3/Yws2PbeaNvQ2z/vw7q9voGRgKyoSwPCceY2B3bbuvQ/E4TQhq1pTkJ1LT1qsL3c1Q78AQNz2ymVd21wNwoGH2J0w5t0Y9tSD4EoJzl7ftVYHXbKQJQc0a14Xu1PR09w/y+Yc38faBRn7yiWVkxkdw0AczaD843MK8lGhSY8Nn/bl9LS0ugrTY8JFd3wKJJgQ1a3Shu5n75p+38d6hJu6+egXXrs2jMDWGg42zu87O8LCh9EgzpxYEz+ii0ZbnBGbHsiYENWtC7DZW5iaw2WUJC2MML26vpa4tcGd/ekpjRx8v767jS+cWcsUqx0T/wtRoDjV0Mpsrx5c3dtLaPRCUzUVOgdqxrAlBzaqS/ET21HaM/CH97t0KvvrHLXzryTIfR+b//razlmEDV6w6vg7k/NQYOvoGaezom7U4PjjsqOEFY4ey07JsR8fyrprA6ljWhKBm1ZqCJIaGDWWVrby2p54fv7ibrPgI3i1v4t3yY74Oz689v62GhemxLEiPHTlWmBoDOD61z5ZNFc2kxYaTlxQ1a8/pb5wdy4HWbKQJQc2qVXkJiMAf3z/K1x/fytKseDbccjZZ8RH89KV9s9r0MZfUtvWwqaKFy5afuIpoYZpjR6/Z7EfYdLiZU+clBfQyFZNJi4sgPS7wOpY1IahZFRcRysL0WF7cUUt8ZCi/vbGEhKgwbrmgmG2VrSNDKdWJXtxeC8BlK7JOOJ4RF0FUmJ2DszT0tKqlm5q2XtYGcf+BUyDOWNaEoGbdmYUpRIXZ+e2NJaTHOTZR+eTqHOanRPPzl/czNOyoJRhjeLf82Mgm7cHs+e21LMmKG9n03UlErJFG3ksIvQND1LT2sKe2nb9sqQaCc/7BaM6O5UDa+GnubV+k5rzvXryQm8+dT1rc8R21Quw2vnnRAr72x608W1ZNVFgI975xgJ3V7USE2vj5VSv56PLA2XRlKiqbu9lW2cptlywa83xhajSbvLTXRGVzNxfe8xa9A8eXx0iODmNhRuwEVwUHZ8fy7pr2gOlg14SgZl1EqJ2IUPtJxy9dmsnizIN868ltGAMFyVHcecVS/rKlmq/+cQv764u5ZV0xNltwtV0/v92xd9RHx9mFrDA1hr+W1dDTP0Rk2Mk/15l4srSS/sFh/v3jS0mJDiMuMpT5qdHYg+z/YCyuHcuaEJTyMJtN+NH6Jdz98n6uXZvLR5dlEmK3ceWaHP71Lzv5xWsH2F/fwZ1XODZvDxYvbKtlZW4CueOM6plvjTQ6dKyTJVmeW1p8aNjw1OYqzi5O5YbT8z1230ARiB3L2oeg/MqpBUk8ftPprF+ZTYjd8esZHmLnv65czr9eegov7arj3J++wX1vlNPdHzhtt+M52NjJ7tr2k0YXufLWSKN3y49R09bL1SW5kxcOUsuy4yk90kxtW2Csz6UJQc0JIsIXz5nPS7eew+mFyfzXS/s497/e5Lltgb0V99931gFM2H9SkByNCB4fafREaSUJUaFcsDjNo/cNJB9dnkllcw9n/eR1Pv/wJv6+s25O7wqoCUHNKcXpsTzwmRKeuvkMshIiueVPW3lz3+wv/zxbXttTz7LseDLjI8ctExFqJzcxyqMjjVq7+3l5dz0fX5lNeIhn+yUCyRWrcnj7Ox/mK+cVsaumjZsf28ytfy6bdD5Ne+8A971RPqszzN2hCUHNSSUFSTz+xdNYlBHH1x/fyiEfrPjpbcc6+9ha2cr5iyb/hF6YGu3RJqPnttXQPzjMVSU5HrtnoMpLjuLbH1nIu987n1svKOaF7bU8+M7hccv3Dw7z5cc2818v7eOzD31AR+/ALEY7MU0Ias6KCgvh/hvWEGq38cVHSmn3oz8sT3hzXyPGwAWnpE9atjA1hkONnQwPe2am9xOllSzJivNoJ3WgC7HbuGVdMRcvyeA//7aXjQebTipjjOH7z+zg3fImPnNGPvvqOrj5sc30DQ75IOKTaUJQc1puUhS/un41R5q6ufVPZSOT2gLBa3vqSY8LZ2l23KRlC9Ni6BscptoDmw/trmlnZ3U7V63R2sFUiQj/ddVyCpKj+PrjW07qbP7Fawd4eksVt6wr5o71S7nrk8t5t7yJbz+53WPJfCZ02Kma806fn8wPPraYf3t2F8+WVfOJ1XP/jaxvcIi39zdy+cpst9YMmp/iHGnUOe7wVHcYY/jdu4cJs9tYvzJ78gvUSWIjQvnNDWtYf++7fO6hTZxdnEJYiI3O3kF+v/EIn1ydw60XFAPwyTU5NHb28ZO/7SUrIYLvX3KKT2PXGoIKCJ8+PZ+Y8BDKKlt9HYpHfHC4ma7+Ida50X8AjhoCzGzoae/AEN/4cxlPba7i+tPzSAyiuR6eVpQWyz3XrKSpq59H3zvCr986xO83HmHdojT+8xPLTkjyXzpnPp9Ylc1D71T4fH8FrSGogCAiLEiPYW9dYKx79NqeBsJDbJxVlOJW+eToMOIjQ6fdud7Q3ssXH93MtspWvn3RAr764aJp3Ucdd9GSDC5akjHy/dCwGXOGt4hw9am5PLO1mrf3N3LJODPSZ4PWEFTAWJgRx766jjm/hLYxhlf31POhohS3l6JwLHIXPa2hp1Ut3Vx+77scqO/g159ew9fOLw7qpa29ZaLlPkryE0mICvX5ar+aEFTAWJQRS1vPAPXt/jW2Gxzj+t0dc36goZOqlh7OP2VqE8IWZsSxq7qd/sGpTYz67T8O09TVx5M3n8HFSzMmv0B5XIjdxvkL03h9X4NPJ7ZpQlABw7kC5946/9rW0BjDjb/7gC8+UupW+Vf3OD4lrls0+XBTV+cvSqOjb3Bki8vRMfQOnDy0sbt/kKc3V3HpskwdYupjFy5Op7V7gNIj3lm51h2aEFTAWDSSEPyrH+Hl3fVsq2pjb127W0MLX9vTwNLsODLiIyYt6+pDRSlEhNp4eXfdSeceereCtXe+Ss2oYanPltXQ0Teoi9f5gXMWpBIWYjup2cgYM2t7LmhCUAEjISqMjLgI9vkgIRhj+N07h09aRmN42HDPK/sB6B0Ypra9d8L7DA4Ns62y1e3OZFeRYXbOLk7l1d31J/SjGGP4/cYK2nsH+Y8Ne044/sjGIyzKiGVNfuKUn095VnR4CGcVJvPKqP+/x947wkfueXtWFtDThKACysKM2FmvIRhjuOOF3dzxwm5uenTzCUNfN+ysZW9dB9etzQMmX4CuvqOPwWFDQXL0hOXGc+HidGraetlVc7zZ7L1DzRxp6mZpdhwvbK/lnwePAbDlaAt7atu54Yx87UT2ExcsTudoczf76x2/J/vqOvjxi3soSoshPXZqNcbp0ISgAsqijFgONnQyMEsdc85k8NC7FXzqtDzSYsP50qOlNLT3MjRs+O9XD1CcFjMyEWmyYaFVzd0A5CSOv5jdRNYtSsMmjmYqpydKK4kND+HRz59GblIkP3xuFwNDwzy68Qix4SF8XCeg+Q3nMiWv7K6jd2CIrz++hdiIUH521YpZ2RjKrYQgIheLyD4RKReR28Y4Hy4if7bOvy8iBdbxAhHpEZEy6+vXLte8ad3TeU7X2FUztjAjlv6hYSqOeXZvgLEYY/jR845k8IUPzePOjy/lgc+U0NE7yE2PbubpzVWUN3Ry6wULSIsNJzY8hEOTxFXV4mgWyEmc3mzj5JhwSvKTeHmXox+hrWeADTtquXxlFonRYdx+2RL213dyzyv72bCjjk+uySE6XKcj+Yv0uAhW5Cbwyp4G7nxxD/vrO/n51StIjQ2fleefNCGIiB24D7gEWAxcJyKLRxX7AtBijCkC7gHucjl30Biz0vq6edR117ucC9w1jNWsWTiLHcv3vLKfh//pSAb/76OnICKckhnH3VevoKyyle89s51FGbFcsjQDEWF+ajSHJplJ7EwIWQnTbx64cHE6e+s6qGzu5rltNfQNDnPNqY5Nbi44JY3zFqbyqzcP0j80zKdPz5v28yjvuPCUNLZVtvLoe0f44tnzOHdB6qw9tzs1hLVAuTHmkDGmH/gTsH5UmfXA763HTwHrRBsllQ8UpcVgt8mEHctNnX38z2sHZrTC5Avba/jl6+VcXZIzkgycLl6aya0XFGMMfOuihSNVfeeKpBOpaukmPS58RnsQXLjY2exQzxObKlmUETuy/6+I8IOPLSHMbuP0+UkUpcVO+3mUd1y42DEXZGl2HN/5yKJZfW536orZQKXL91XAaeOVMcYMikgbkGydmyciW4F24P8ZY/7hct1DIjIEPA382IwxxVREbgJuAsjL008zamLhIXbmpURPOBfhgX8c5tdvHSQyzM6/nD1/ys+xs7qNbz+5jTX5ifz7x5eO2SF7y7piri7JJSvheF/A/NRontlaTXf/IFFhY//pVbX0TLu5yKkgJZritBh+9+5hqlp6+MHHFp8Q47yUaP7wxdPIiPN+J6WaugXpMfzkE8s42xqGOpvcebaxPumPfuMer0wtkGeMWQV8E/ijiDjX8r3eGLMMONv6umGsJzfG3G+MKTHGlKSmzl7VSc1diyYYaTQ4NMwzW6oA+J/Xy2nrntoeCsc6+7jpkVISo8L49afXjPtJXkROSAYA81MdC9BN1GxU1do97Q5lVxctSaeqpYcwu23MTuNTC5JmtCqq8h4R4dq1eWQnzPz3YKrcSQhVgOsu2znA6I1sR8qISAgQDzQbY/qMMU0AxpjNwEFggfV9tfVvB/BHHE1TSs3YooxYqlp6xpzM848Dx2jo6OOWdcW09w7wqzfL3b5va3c/X3p0M83d/TzwmZIpd/TNT3UMJR2vY3lwaJja1l6PJARns8NHlmboqqXKbe4khE1AsYjME5Ew4FrguVFlngNutB5fCbxujDEikmp1SiMi84Fi4JCIhIhIinU8FLgM2Dnzl6OUY00fYMx+hCdKK0mKDuOrHy7iE6tyeOifFVS1dE96z61HW/joL99he1Urd1+9kqXZU1/moSA5GpHxh5465yDMtMkIYHl2PN+4YAHfsIa7KuWOSROCMWYQ+BrwErAHeMIYs0tE7hCRy61iDwLJIlKOo2nIOTT1HGC7iGzD0dl8szGmGQgHXhKR7UAZUA084MHXpYKYcwmL0QmhuaufV/fUc8WqbMJCbHzrogUA/Pzl/ePeyxjDg+8c5urfbEQEnv7ymVw6zeWJI0LtZCdEjrtnwUznILiy2YRbLigeaaZSyh1uDUA2xmwANow6drvL417gqjGuexpHh/Ho413AmqkGq5Q7shMiiQ6zs29Ux/KzZdUMDJmRjeOzEiL5/Fnz+PVbB/nCh+ad9Kl/YGiY7z61nb9srebCxen87MoVxEeFzii2iUYazXQOglIzpTOVVcCx2YQFY3QsP1FaxbLseBZlHN+j+CsfLiQxKpT/8/hWdlS1jRzvHRjiy49t5i9bq/nWhQu4/4Y1M04G4OhHOHysa8w9GzwxB0GpmdCEoALSooxYdla38feddQwNG3ZWt7Gntp2rS07cbzkuIpT7rl9NV/8gV/zqXe55ZT+t3f187qFNvLqngX9fv4Svr/PchjHzU2Po7h+iboxF7jwxB0GpmdA56yogXX9aPu+UH+PmxzYzLyWa1NhwwkJsXL7i5CGYZxam8PKt5/LD53fxi9cO8Ju3DzIwZLjnmhVcsSpnjLtPX2GKNdKosYvM+BP7CjwxB0GpmdAaggpIS7PjeeNb53Hvp1YRGxHCB4ebuXhJxrjNPvFRodxzzUp+/ek1FKfF8r/Xr/Z4MoDjcxHG2urSU3MQlJourSGogBVit3HZ8iw+uiyTndXt5LkxEevipRle3UYyPS6c6DD7SZPTRuYgrNCEoHxHE4IKeCLCshz/2B7SschdzEk1BE/OQVBqurTJSKlZNtaqp56cg6DUdGlCUGqWzU+Joaath57+46ut6hwE5Q80ISg1y+anRmMMHHZZ00jnICh/oAlBqVnmXOTOdYlunYOg/IEmBKVm2cL0WHKTInno3YqRGcs6B0H5A00ISs2yELuNr59fzI7qNl7d49g5VucgKH+gCUEpH/jEqmzyk6O4+5X9DHhwHwSlZkITglI+EGK3ccu6YvbUtvPIxiM6B0H5BU0ISvnI5SuymJ8azc9f3gfoHATle5oQlPIRZy2h25qPoDUE5WuaEJTyocuWZ1Gc5ljwTucgKF/TtYyU8iG7TbjryuW8f6hZ5yAon9OEoJSPrc5LZHVeoq/DUEqbjJRSSjloQlBKKQVoQlBKKWXRhKCUUgrQhKCUUsqiCUEppRSgCUEppZRFE4JSSikAxLlBx1wgIo3AEZdD8UCbm5fnAUfdLOvufafy/Bqrxqqxzp1YvfX8voo13xiTOumdjDFz9gu4fwplGz193yk+v8aqsWqscyRWLz6/T2Od7GuuNxk9P4WyrV6471SeX2PVWDXWuROrt57f17FOaE41Gc2EiJQaY0p8HYc7NFbv0Fi9Q2P1Dl/EOtdrCFNxv68DmAKN1Ts0Vu/QWL1j1mMNmhqCUkqpiQVTDUEppdQENCEopZQC5nBCEJFcEXlDRPaIyC4RucU6niQir4jIAevfROv4IhHZKCJ9IvLtUff6nYg0iMhOf451vPv4aawRIvKBiGyz7vMjf43V5X52EdkqIi/4c6wiUiEiO0SkTERK/TzWBBF5SkT2Wvc7wx9jFZGF1s/T+dUuIrf6Y6zWuW9Y99gpIo+LiGf2X/XU+NXZ/gIygdXW41hgP7AY+Clwm3X8NuAu63EacCpwJ/DtUfc6B1gN7PTnWMe7j5/GKkCM9TgUeB843R9jdbnfN4E/Ai/46++Ada4CSPHG76oXYv098C/W4zAgwV9jdbmnHajDMZnL72IFsoHDQKT1/RPAZz0R45ytIRhjao0xW6zHHcAeHD+o9Th+CbH+/bhVpsEYswkYGONebwPN/h7rBPfxx1iNMabT+jbU+vLoCAZP/g6ISA7wUeC3nozRG7F6m6diFZE4HB+2HrTK9RtjpjJnYdZiHWUdcNAYc2SCMr6ONQSIFJEQIAqo8USMczYhuBKRAmAVjk+h6caYWnD8B+DIsn7DU7GOuo9XzDRWqwmmDGgAXjHG+G2swH8D3wWGvRTiCA/EaoCXRWSziNzkrThhxrHOBxqBh6ymuN+KSLSfxurqWuBxT8fnaiaxGmOqgZ/hWNaiFmgzxrzsibjmfEIQkRjgaeBWY0y7r+OZiKdinY3X7InnMMYMGWNWAjnAWhFZ6skYnWYaq4hcBjQYYzZ7PLiTn8sT/3dnGWNWA5cAXxWRczwWoAsPxBqCoyn2f40xq4AuHE0iHufBv60w4HLgSU/FNsZzzPT3NRFHrWIekAVEi8inPRHbnE4IIhKK4wf7B2PMM9bhehHJtM5n4vh06nOeinWc+/hlrE5WM8GbwMUeDtVTsZ4FXC4iFcCfgPNF5DE/jRVjTI31bwPwF2Ctn8ZaBVS51AyfwpEg/DFWp0uALcaYek/HacXiiVgvAA4bYxqNMQPAM8CZnohvziYEEREcbZN7jDF3u5x6DrjRenwj8Oxsxzaap2Kd4D7+GGuqiCRYjyNx/BLv9cdYjTHfN8bkGGMKcDQXvG6M8cgnLk/HKiLRIhLrfAxcBHh0dJwHf651QKWILLQOrQN2+2OsLq7DS81FHoz1KHC6iERZ91yHoz9i5qbaC+0vX8CHcLSlbgfKrK9LgWTgNeCA9W+SVT4DxyeWdhyLRlUBcda5x3G0xQ1Yx7/gj7GOdx8/jXU5sNW6z07gdn/+HXC553l4Z5SRp36u84Ft1tcu4F/9NVbr3Eqg1LrXX4FEP441CmgC4j39M/VCrD/C8QFrJ/AoEO6JGHXpCqWUUsAcbjJSSinlWZoQlFJKAZoQlFJKWTQhKKWUAjQhKKWUsmhCUAoQkSFrlctd4lih9ZsiMuHfh4gUiMinZitGpbxNE4JSDj3GmJXGmCXAhTjGh/9gkmsKAE0IKmBoQlBqFONYEuIm4GviUCAi/xCRLdaXc5mAnwBnWzWLb4jIZ0XkXud9ROQFETnPetwpIndZC9K9KiJrReRNETkkIpfP+otUagyaEJQagzHmEI6/jzQca8tcaBwLyl0D/NIqdhvwD6tmcc8kt4wG3jTGrAE6gB/jqIlcAdzhhZeg1JSF+DoApfyYWP+GAveKyEpgCFgwjXv1A3+3Hu8A+owxAyKyA0fTk1I+pwlBqTGIyHwcb/4NOPoS6oEVOGoNveNcNsiJtW7XbQ0HzPF1YoaBPgBjzLC1yYlSPqdNRkqNIiKpwK+Be6038Xig1hgzDNyAY4tFcDT9xLpcWgGsFBGbiOTihWWplfIm/WSilEOktbtbKI5P+o8CziWKfwU8LSJXAW/g2OgFHKtWDorINuBhHLuuHcbRJLQT2DJr0SvlAbraqVJKKUCbjJRSSlk0ISillAI0ISillLJoQlBKKQVoQlBKKWXRhKCUUgrQhKCUUsry/wF60mlOyutaNQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600be38860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600bd65f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600bd29630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600bc60dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600bb95d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600bb73b70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600bdce828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600ba8b710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600b99dbe0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600ba09198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f600b9ef978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for država, podokvir in tečaj.groupby('Država'):\n",
    "    podokvir.plot(title=država, legend=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Odnos dviju stranih valuta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Da bismo pratili relativni tečaj dviju valuta od kojih nijedna nije kuna, potrebno je različite valute dobiti kao stupce. Jednostavan način da se to učini je staviti valutu u indeks (maknut ćemo državu da nam ne smeta), i onda pozvati `unstack` metodu."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Srednji</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th>Valuta</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"14\" valign=\"top\">2011-01-01</th>\n",
       "      <th>AUD</th>\n",
       "      <td>5.521513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAD</th>\n",
       "      <td>5.571587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZK</th>\n",
       "      <td>0.302292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DKK</th>\n",
       "      <td>0.992650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HUF</th>\n",
       "      <td>0.026849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPY</th>\n",
       "      <td>0.067089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NOK</th>\n",
       "      <td>0.945634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEK</th>\n",
       "      <td>0.829051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHF</th>\n",
       "      <td>5.794304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GBP</th>\n",
       "      <td>8.724773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>USD</th>\n",
       "      <td>5.537878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XDR</th>\n",
       "      <td>8.575765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EUR</th>\n",
       "      <td>7.396420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLN</th>\n",
       "      <td>1.900072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"6\" valign=\"top\">2011-02-01</th>\n",
       "      <th>AUD</th>\n",
       "      <td>5.469563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAD</th>\n",
       "      <td>5.492327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CZK</th>\n",
       "      <td>0.305517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DKK</th>\n",
       "      <td>0.994092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HUF</th>\n",
       "      <td>0.027346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPY</th>\n",
       "      <td>0.065763</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Srednji\n",
       "Datum      Valuta          \n",
       "2011-01-01 AUD     5.521513\n",
       "           CAD     5.571587\n",
       "           CZK     0.302292\n",
       "           DKK     0.992650\n",
       "           HUF     0.026849\n",
       "           JPY     0.067089\n",
       "           NOK     0.945634\n",
       "           SEK     0.829051\n",
       "           CHF     5.794304\n",
       "           GBP     8.724773\n",
       "           USD     5.537878\n",
       "           XDR     8.575765\n",
       "           EUR     7.396420\n",
       "           PLN     1.900072\n",
       "2011-02-01 AUD     5.469563\n",
       "           CAD     5.492327\n",
       "           CZK     0.305517\n",
       "           DKK     0.994092\n",
       "           HUF     0.027346\n",
       "           JPY     0.065763"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj.set_index([tečaj.index, 'Valuta'], inplace=True)\n",
    "del tečaj['Država']\n",
    "tečaj.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"15\" halign=\"left\">Srednji</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Valuta</th>\n",
       "      <th>AUD</th>\n",
       "      <th>BAM</th>\n",
       "      <th>CAD</th>\n",
       "      <th>CHF</th>\n",
       "      <th>CZK</th>\n",
       "      <th>DKK</th>\n",
       "      <th>EUR</th>\n",
       "      <th>GBP</th>\n",
       "      <th>HUF</th>\n",
       "      <th>JPY</th>\n",
       "      <th>NOK</th>\n",
       "      <th>PLN</th>\n",
       "      <th>SEK</th>\n",
       "      <th>USD</th>\n",
       "      <th>XDR</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>5.521513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.571587</td>\n",
       "      <td>5.794304</td>\n",
       "      <td>0.302292</td>\n",
       "      <td>0.992650</td>\n",
       "      <td>7.396420</td>\n",
       "      <td>8.724773</td>\n",
       "      <td>0.026849</td>\n",
       "      <td>0.067089</td>\n",
       "      <td>0.945634</td>\n",
       "      <td>1.900072</td>\n",
       "      <td>0.829051</td>\n",
       "      <td>5.537878</td>\n",
       "      <td>8.575765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01</th>\n",
       "      <td>5.469563</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.492327</td>\n",
       "      <td>5.710786</td>\n",
       "      <td>0.305517</td>\n",
       "      <td>0.994092</td>\n",
       "      <td>7.410873</td>\n",
       "      <td>8.753128</td>\n",
       "      <td>0.027346</td>\n",
       "      <td>0.065763</td>\n",
       "      <td>0.945485</td>\n",
       "      <td>1.889289</td>\n",
       "      <td>0.842513</td>\n",
       "      <td>5.431365</td>\n",
       "      <td>8.486219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-03-01</th>\n",
       "      <td>5.338322</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.415269</td>\n",
       "      <td>5.746383</td>\n",
       "      <td>0.303387</td>\n",
       "      <td>0.991520</td>\n",
       "      <td>7.393749</td>\n",
       "      <td>8.546276</td>\n",
       "      <td>0.027285</td>\n",
       "      <td>0.064709</td>\n",
       "      <td>0.944455</td>\n",
       "      <td>1.843635</td>\n",
       "      <td>0.832785</td>\n",
       "      <td>5.285354</td>\n",
       "      <td>8.351255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-01</th>\n",
       "      <td>5.386425</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.324651</td>\n",
       "      <td>5.671406</td>\n",
       "      <td>0.303116</td>\n",
       "      <td>0.987303</td>\n",
       "      <td>7.362212</td>\n",
       "      <td>8.340644</td>\n",
       "      <td>0.027759</td>\n",
       "      <td>0.061243</td>\n",
       "      <td>0.942367</td>\n",
       "      <td>1.852690</td>\n",
       "      <td>0.820994</td>\n",
       "      <td>5.105235</td>\n",
       "      <td>8.158269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-05-01</th>\n",
       "      <td>5.499733</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.323025</td>\n",
       "      <td>5.882541</td>\n",
       "      <td>0.303557</td>\n",
       "      <td>0.991288</td>\n",
       "      <td>7.391226</td>\n",
       "      <td>8.407499</td>\n",
       "      <td>0.027741</td>\n",
       "      <td>0.063371</td>\n",
       "      <td>0.942421</td>\n",
       "      <td>1.877661</td>\n",
       "      <td>0.825230</td>\n",
       "      <td>5.142271</td>\n",
       "      <td>8.214160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-06-01</th>\n",
       "      <td>5.463301</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.265003</td>\n",
       "      <td>6.121611</td>\n",
       "      <td>0.305374</td>\n",
       "      <td>0.993951</td>\n",
       "      <td>7.412196</td>\n",
       "      <td>8.368008</td>\n",
       "      <td>0.027805</td>\n",
       "      <td>0.063943</td>\n",
       "      <td>0.946782</td>\n",
       "      <td>1.869097</td>\n",
       "      <td>0.815349</td>\n",
       "      <td>5.148899</td>\n",
       "      <td>8.236234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-01</th>\n",
       "      <td>5.586135</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.427585</td>\n",
       "      <td>6.288996</td>\n",
       "      <td>0.304951</td>\n",
       "      <td>0.995140</td>\n",
       "      <td>7.419738</td>\n",
       "      <td>8.367082</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>0.065324</td>\n",
       "      <td>0.953285</td>\n",
       "      <td>1.858853</td>\n",
       "      <td>0.812134</td>\n",
       "      <td>5.193281</td>\n",
       "      <td>8.283039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-01</th>\n",
       "      <td>5.466704</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.305947</td>\n",
       "      <td>6.657745</td>\n",
       "      <td>0.307502</td>\n",
       "      <td>1.000725</td>\n",
       "      <td>7.454965</td>\n",
       "      <td>8.505480</td>\n",
       "      <td>0.027409</td>\n",
       "      <td>0.067407</td>\n",
       "      <td>0.957383</td>\n",
       "      <td>1.813037</td>\n",
       "      <td>0.814209</td>\n",
       "      <td>5.192441</td>\n",
       "      <td>8.342176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-09-01</th>\n",
       "      <td>5.575827</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.432720</td>\n",
       "      <td>6.250744</td>\n",
       "      <td>0.305516</td>\n",
       "      <td>1.005435</td>\n",
       "      <td>7.486844</td>\n",
       "      <td>8.578141</td>\n",
       "      <td>0.026403</td>\n",
       "      <td>0.070620</td>\n",
       "      <td>0.970303</td>\n",
       "      <td>1.732927</td>\n",
       "      <td>0.820237</td>\n",
       "      <td>5.420572</td>\n",
       "      <td>8.540190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-01</th>\n",
       "      <td>5.518712</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.345578</td>\n",
       "      <td>6.085039</td>\n",
       "      <td>0.301705</td>\n",
       "      <td>1.005341</td>\n",
       "      <td>7.483324</td>\n",
       "      <td>8.602293</td>\n",
       "      <td>0.025281</td>\n",
       "      <td>0.071396</td>\n",
       "      <td>0.964879</td>\n",
       "      <td>1.718539</td>\n",
       "      <td>0.820534</td>\n",
       "      <td>5.467645</td>\n",
       "      <td>8.598491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-11-01</th>\n",
       "      <td>5.573647</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.378559</td>\n",
       "      <td>6.082743</td>\n",
       "      <td>0.294278</td>\n",
       "      <td>1.006383</td>\n",
       "      <td>7.487735</td>\n",
       "      <td>8.721751</td>\n",
       "      <td>0.024205</td>\n",
       "      <td>0.071202</td>\n",
       "      <td>0.962638</td>\n",
       "      <td>1.692721</td>\n",
       "      <td>0.819930</td>\n",
       "      <td>5.512767</td>\n",
       "      <td>8.619486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-01</th>\n",
       "      <td>5.758831</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.559832</td>\n",
       "      <td>6.112429</td>\n",
       "      <td>0.294873</td>\n",
       "      <td>1.009852</td>\n",
       "      <td>7.507179</td>\n",
       "      <td>8.883743</td>\n",
       "      <td>0.024681</td>\n",
       "      <td>0.073068</td>\n",
       "      <td>0.969097</td>\n",
       "      <td>1.675588</td>\n",
       "      <td>0.831527</td>\n",
       "      <td>5.688661</td>\n",
       "      <td>8.794582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-01</th>\n",
       "      <td>6.073910</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.768345</td>\n",
       "      <td>6.231979</td>\n",
       "      <td>0.295560</td>\n",
       "      <td>1.015017</td>\n",
       "      <td>7.546707</td>\n",
       "      <td>9.062576</td>\n",
       "      <td>0.024559</td>\n",
       "      <td>0.075958</td>\n",
       "      <td>0.982265</td>\n",
       "      <td>1.723388</td>\n",
       "      <td>0.852955</td>\n",
       "      <td>5.846617</td>\n",
       "      <td>8.980310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-02-01</th>\n",
       "      <td>6.148260</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.747129</td>\n",
       "      <td>6.279834</td>\n",
       "      <td>0.302710</td>\n",
       "      <td>1.019586</td>\n",
       "      <td>7.579384</td>\n",
       "      <td>9.056639</td>\n",
       "      <td>0.026075</td>\n",
       "      <td>0.073301</td>\n",
       "      <td>1.001840</td>\n",
       "      <td>1.810179</td>\n",
       "      <td>0.859164</td>\n",
       "      <td>5.733239</td>\n",
       "      <td>8.885371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-03-01</th>\n",
       "      <td>6.024449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.746059</td>\n",
       "      <td>6.251841</td>\n",
       "      <td>0.305572</td>\n",
       "      <td>1.014048</td>\n",
       "      <td>7.539590</td>\n",
       "      <td>9.029432</td>\n",
       "      <td>0.025834</td>\n",
       "      <td>0.069328</td>\n",
       "      <td>1.002743</td>\n",
       "      <td>1.823356</td>\n",
       "      <td>0.848646</td>\n",
       "      <td>5.709035</td>\n",
       "      <td>8.795810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-04-01</th>\n",
       "      <td>5.888507</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.728512</td>\n",
       "      <td>6.234184</td>\n",
       "      <td>0.302470</td>\n",
       "      <td>1.007404</td>\n",
       "      <td>7.494357</td>\n",
       "      <td>9.102995</td>\n",
       "      <td>0.025386</td>\n",
       "      <td>0.069884</td>\n",
       "      <td>0.990552</td>\n",
       "      <td>1.795660</td>\n",
       "      <td>0.846429</td>\n",
       "      <td>5.691287</td>\n",
       "      <td>8.782991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-05-01</th>\n",
       "      <td>5.868946</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.824643</td>\n",
       "      <td>6.268465</td>\n",
       "      <td>0.298041</td>\n",
       "      <td>1.012824</td>\n",
       "      <td>7.528940</td>\n",
       "      <td>9.359736</td>\n",
       "      <td>0.025706</td>\n",
       "      <td>0.073592</td>\n",
       "      <td>0.994298</td>\n",
       "      <td>1.758317</td>\n",
       "      <td>0.837405</td>\n",
       "      <td>5.870676</td>\n",
       "      <td>8.977813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-06-01</th>\n",
       "      <td>5.997273</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.863707</td>\n",
       "      <td>6.284864</td>\n",
       "      <td>0.294551</td>\n",
       "      <td>1.015416</td>\n",
       "      <td>7.546585</td>\n",
       "      <td>9.365869</td>\n",
       "      <td>0.025620</td>\n",
       "      <td>0.076227</td>\n",
       "      <td>1.000331</td>\n",
       "      <td>1.751013</td>\n",
       "      <td>0.848979</td>\n",
       "      <td>6.026710</td>\n",
       "      <td>9.133588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-07-01</th>\n",
       "      <td>6.260851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.997593</td>\n",
       "      <td>6.241017</td>\n",
       "      <td>0.294473</td>\n",
       "      <td>1.007610</td>\n",
       "      <td>7.494496</td>\n",
       "      <td>9.489191</td>\n",
       "      <td>0.026139</td>\n",
       "      <td>0.077085</td>\n",
       "      <td>1.004560</td>\n",
       "      <td>1.786904</td>\n",
       "      <td>0.874998</td>\n",
       "      <td>6.089386</td>\n",
       "      <td>9.173819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-08-01</th>\n",
       "      <td>6.336171</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.082778</td>\n",
       "      <td>6.234162</td>\n",
       "      <td>0.299211</td>\n",
       "      <td>1.005625</td>\n",
       "      <td>7.486777</td>\n",
       "      <td>9.489612</td>\n",
       "      <td>0.026897</td>\n",
       "      <td>0.076854</td>\n",
       "      <td>1.021260</td>\n",
       "      <td>1.831579</td>\n",
       "      <td>0.904138</td>\n",
       "      <td>6.042111</td>\n",
       "      <td>9.141598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-09-01</th>\n",
       "      <td>6.010115</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.910138</td>\n",
       "      <td>6.145893</td>\n",
       "      <td>0.300599</td>\n",
       "      <td>0.996427</td>\n",
       "      <td>7.426569</td>\n",
       "      <td>9.310771</td>\n",
       "      <td>0.026156</td>\n",
       "      <td>0.073992</td>\n",
       "      <td>1.005044</td>\n",
       "      <td>1.795046</td>\n",
       "      <td>0.874748</td>\n",
       "      <td>5.787501</td>\n",
       "      <td>8.897525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-10-01</th>\n",
       "      <td>5.962364</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.868991</td>\n",
       "      <td>6.200713</td>\n",
       "      <td>0.300724</td>\n",
       "      <td>1.005722</td>\n",
       "      <td>7.500421</td>\n",
       "      <td>9.306267</td>\n",
       "      <td>0.026601</td>\n",
       "      <td>0.073328</td>\n",
       "      <td>1.013000</td>\n",
       "      <td>1.825608</td>\n",
       "      <td>0.871788</td>\n",
       "      <td>5.783514</td>\n",
       "      <td>8.908779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-11-01</th>\n",
       "      <td>6.116261</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.896474</td>\n",
       "      <td>6.254353</td>\n",
       "      <td>0.297418</td>\n",
       "      <td>1.010459</td>\n",
       "      <td>7.536449</td>\n",
       "      <td>9.378519</td>\n",
       "      <td>0.026697</td>\n",
       "      <td>0.072661</td>\n",
       "      <td>1.027117</td>\n",
       "      <td>1.823028</td>\n",
       "      <td>0.876198</td>\n",
       "      <td>5.876333</td>\n",
       "      <td>8.982806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-01</th>\n",
       "      <td>6.019501</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.808641</td>\n",
       "      <td>6.228983</td>\n",
       "      <td>0.298751</td>\n",
       "      <td>1.009275</td>\n",
       "      <td>7.529460</td>\n",
       "      <td>9.276943</td>\n",
       "      <td>0.026424</td>\n",
       "      <td>0.068924</td>\n",
       "      <td>1.023597</td>\n",
       "      <td>1.838537</td>\n",
       "      <td>0.869956</td>\n",
       "      <td>5.747093</td>\n",
       "      <td>8.838613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>5.987356</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.751224</td>\n",
       "      <td>6.166394</td>\n",
       "      <td>0.296583</td>\n",
       "      <td>1.014281</td>\n",
       "      <td>7.567746</td>\n",
       "      <td>9.115161</td>\n",
       "      <td>0.025765</td>\n",
       "      <td>0.064257</td>\n",
       "      <td>1.025649</td>\n",
       "      <td>1.830966</td>\n",
       "      <td>0.878060</td>\n",
       "      <td>5.701444</td>\n",
       "      <td>8.753616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-02-01</th>\n",
       "      <td>5.846483</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.622783</td>\n",
       "      <td>6.161676</td>\n",
       "      <td>0.297918</td>\n",
       "      <td>1.016386</td>\n",
       "      <td>7.582399</td>\n",
       "      <td>8.790390</td>\n",
       "      <td>0.025931</td>\n",
       "      <td>0.060886</td>\n",
       "      <td>1.021279</td>\n",
       "      <td>1.817114</td>\n",
       "      <td>0.890298</td>\n",
       "      <td>5.664825</td>\n",
       "      <td>8.650024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-03-01</th>\n",
       "      <td>6.042051</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.704623</td>\n",
       "      <td>6.185597</td>\n",
       "      <td>0.295891</td>\n",
       "      <td>1.017536</td>\n",
       "      <td>7.585782</td>\n",
       "      <td>8.819467</td>\n",
       "      <td>0.025069</td>\n",
       "      <td>0.061767</td>\n",
       "      <td>1.013480</td>\n",
       "      <td>1.826196</td>\n",
       "      <td>0.908675</td>\n",
       "      <td>5.846774</td>\n",
       "      <td>8.788637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-04-01</th>\n",
       "      <td>6.073394</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.738285</td>\n",
       "      <td>6.234325</td>\n",
       "      <td>0.294276</td>\n",
       "      <td>1.019776</td>\n",
       "      <td>7.602485</td>\n",
       "      <td>8.937617</td>\n",
       "      <td>0.025445</td>\n",
       "      <td>0.059816</td>\n",
       "      <td>1.008648</td>\n",
       "      <td>1.837236</td>\n",
       "      <td>0.901713</td>\n",
       "      <td>5.845017</td>\n",
       "      <td>8.792672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-05-01</th>\n",
       "      <td>5.790835</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.719164</td>\n",
       "      <td>6.104171</td>\n",
       "      <td>0.292351</td>\n",
       "      <td>1.015400</td>\n",
       "      <td>7.568123</td>\n",
       "      <td>8.924146</td>\n",
       "      <td>0.025871</td>\n",
       "      <td>0.057850</td>\n",
       "      <td>1.001166</td>\n",
       "      <td>1.815279</td>\n",
       "      <td>0.882926</td>\n",
       "      <td>5.828459</td>\n",
       "      <td>8.737063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-06-01</th>\n",
       "      <td>5.376424</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.523467</td>\n",
       "      <td>6.084023</td>\n",
       "      <td>0.291561</td>\n",
       "      <td>1.005788</td>\n",
       "      <td>7.500346</td>\n",
       "      <td>8.801832</td>\n",
       "      <td>0.025367</td>\n",
       "      <td>0.058384</td>\n",
       "      <td>0.973363</td>\n",
       "      <td>1.754321</td>\n",
       "      <td>0.866091</td>\n",
       "      <td>5.687173</td>\n",
       "      <td>8.611107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-01</th>\n",
       "      <td>4.765329</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.091709</td>\n",
       "      <td>6.942959</td>\n",
       "      <td>0.279877</td>\n",
       "      <td>1.015223</td>\n",
       "      <td>7.574467</td>\n",
       "      <td>10.364283</td>\n",
       "      <td>0.024205</td>\n",
       "      <td>0.056137</td>\n",
       "      <td>0.814340</td>\n",
       "      <td>1.796225</td>\n",
       "      <td>0.805873</td>\n",
       "      <td>6.745421</td>\n",
       "      <td>9.480873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-10-01</th>\n",
       "      <td>4.888398</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.183148</td>\n",
       "      <td>7.006613</td>\n",
       "      <td>0.281373</td>\n",
       "      <td>1.021851</td>\n",
       "      <td>7.622835</td>\n",
       "      <td>10.392797</td>\n",
       "      <td>0.024507</td>\n",
       "      <td>0.056511</td>\n",
       "      <td>0.820466</td>\n",
       "      <td>1.795134</td>\n",
       "      <td>0.815649</td>\n",
       "      <td>6.780515</td>\n",
       "      <td>9.539132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-11-01</th>\n",
       "      <td>5.050875</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.329308</td>\n",
       "      <td>7.016779</td>\n",
       "      <td>0.281113</td>\n",
       "      <td>1.018581</td>\n",
       "      <td>7.598376</td>\n",
       "      <td>10.750593</td>\n",
       "      <td>0.024351</td>\n",
       "      <td>0.057696</td>\n",
       "      <td>0.819756</td>\n",
       "      <td>1.788498</td>\n",
       "      <td>0.815592</td>\n",
       "      <td>7.063317</td>\n",
       "      <td>9.752016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-01</th>\n",
       "      <td>5.098144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.148764</td>\n",
       "      <td>7.049754</td>\n",
       "      <td>0.282652</td>\n",
       "      <td>1.023288</td>\n",
       "      <td>7.634682</td>\n",
       "      <td>10.554799</td>\n",
       "      <td>0.024323</td>\n",
       "      <td>0.057725</td>\n",
       "      <td>0.809859</td>\n",
       "      <td>1.780026</td>\n",
       "      <td>0.826140</td>\n",
       "      <td>7.034940</td>\n",
       "      <td>9.747479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-01-01</th>\n",
       "      <td>4.937558</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.951244</td>\n",
       "      <td>7.004027</td>\n",
       "      <td>0.283337</td>\n",
       "      <td>1.025618</td>\n",
       "      <td>7.652777</td>\n",
       "      <td>10.149827</td>\n",
       "      <td>0.024322</td>\n",
       "      <td>0.059622</td>\n",
       "      <td>0.797414</td>\n",
       "      <td>1.739975</td>\n",
       "      <td>0.825211</td>\n",
       "      <td>7.041467</td>\n",
       "      <td>9.730927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-02-01</th>\n",
       "      <td>4.908655</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.976686</td>\n",
       "      <td>6.925609</td>\n",
       "      <td>0.282561</td>\n",
       "      <td>1.023313</td>\n",
       "      <td>7.636668</td>\n",
       "      <td>9.867520</td>\n",
       "      <td>0.024628</td>\n",
       "      <td>0.059796</td>\n",
       "      <td>0.799420</td>\n",
       "      <td>1.735803</td>\n",
       "      <td>0.812218</td>\n",
       "      <td>6.882671</td>\n",
       "      <td>9.590942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-01</th>\n",
       "      <td>5.095151</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.145003</td>\n",
       "      <td>6.930301</td>\n",
       "      <td>0.279847</td>\n",
       "      <td>1.014694</td>\n",
       "      <td>7.566498</td>\n",
       "      <td>9.692216</td>\n",
       "      <td>0.024343</td>\n",
       "      <td>0.060457</td>\n",
       "      <td>0.801724</td>\n",
       "      <td>1.761361</td>\n",
       "      <td>0.814597</td>\n",
       "      <td>6.827044</td>\n",
       "      <td>9.522787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-04-01</th>\n",
       "      <td>5.068793</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.143247</td>\n",
       "      <td>6.858715</td>\n",
       "      <td>0.277368</td>\n",
       "      <td>1.006970</td>\n",
       "      <td>7.494619</td>\n",
       "      <td>9.455753</td>\n",
       "      <td>0.024064</td>\n",
       "      <td>0.060211</td>\n",
       "      <td>0.803683</td>\n",
       "      <td>1.742605</td>\n",
       "      <td>0.814043</td>\n",
       "      <td>6.612791</td>\n",
       "      <td>9.316050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-01</th>\n",
       "      <td>4.855564</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.126689</td>\n",
       "      <td>6.783124</td>\n",
       "      <td>0.277404</td>\n",
       "      <td>1.007427</td>\n",
       "      <td>7.494223</td>\n",
       "      <td>9.609321</td>\n",
       "      <td>0.023842</td>\n",
       "      <td>0.060881</td>\n",
       "      <td>0.805481</td>\n",
       "      <td>1.701641</td>\n",
       "      <td>0.807486</td>\n",
       "      <td>6.615648</td>\n",
       "      <td>9.336993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-01</th>\n",
       "      <td>4.939507</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.184768</td>\n",
       "      <td>6.888549</td>\n",
       "      <td>0.277882</td>\n",
       "      <td>1.010112</td>\n",
       "      <td>7.511915</td>\n",
       "      <td>9.533886</td>\n",
       "      <td>0.023951</td>\n",
       "      <td>0.063181</td>\n",
       "      <td>0.804885</td>\n",
       "      <td>1.708288</td>\n",
       "      <td>0.805879</td>\n",
       "      <td>6.687416</td>\n",
       "      <td>9.410964</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-07-01</th>\n",
       "      <td>5.095732</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.196875</td>\n",
       "      <td>6.892748</td>\n",
       "      <td>0.277106</td>\n",
       "      <td>1.006805</td>\n",
       "      <td>7.489517</td>\n",
       "      <td>8.912073</td>\n",
       "      <td>0.023810</td>\n",
       "      <td>0.065066</td>\n",
       "      <td>0.800139</td>\n",
       "      <td>1.702209</td>\n",
       "      <td>0.791452</td>\n",
       "      <td>6.766731</td>\n",
       "      <td>9.407829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-08-01</th>\n",
       "      <td>5.087716</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.133501</td>\n",
       "      <td>6.878600</td>\n",
       "      <td>0.276802</td>\n",
       "      <td>1.005008</td>\n",
       "      <td>7.477713</td>\n",
       "      <td>8.756782</td>\n",
       "      <td>0.024099</td>\n",
       "      <td>0.065848</td>\n",
       "      <td>0.802279</td>\n",
       "      <td>1.737718</td>\n",
       "      <td>0.787874</td>\n",
       "      <td>6.670247</td>\n",
       "      <td>9.335079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-01</th>\n",
       "      <td>5.071550</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.108462</td>\n",
       "      <td>6.857253</td>\n",
       "      <td>0.277321</td>\n",
       "      <td>1.005821</td>\n",
       "      <td>7.490070</td>\n",
       "      <td>8.795602</td>\n",
       "      <td>0.024272</td>\n",
       "      <td>0.065566</td>\n",
       "      <td>0.813478</td>\n",
       "      <td>1.732805</td>\n",
       "      <td>0.783654</td>\n",
       "      <td>6.683380</td>\n",
       "      <td>9.350946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-10-01</th>\n",
       "      <td>5.180651</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.140420</td>\n",
       "      <td>6.893958</td>\n",
       "      <td>0.277822</td>\n",
       "      <td>1.008377</td>\n",
       "      <td>7.502932</td>\n",
       "      <td>8.417464</td>\n",
       "      <td>0.024453</td>\n",
       "      <td>0.065619</td>\n",
       "      <td>0.833846</td>\n",
       "      <td>1.742061</td>\n",
       "      <td>0.774453</td>\n",
       "      <td>6.797877</td>\n",
       "      <td>9.382797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-11-01</th>\n",
       "      <td>5.240763</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.169131</td>\n",
       "      <td>6.986309</td>\n",
       "      <td>0.278071</td>\n",
       "      <td>1.009765</td>\n",
       "      <td>7.513263</td>\n",
       "      <td>8.637247</td>\n",
       "      <td>0.024350</td>\n",
       "      <td>0.064406</td>\n",
       "      <td>0.827292</td>\n",
       "      <td>1.713480</td>\n",
       "      <td>0.762676</td>\n",
       "      <td>6.950066</td>\n",
       "      <td>9.485565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-01</th>\n",
       "      <td>5.251182</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.349959</td>\n",
       "      <td>7.003823</td>\n",
       "      <td>0.278839</td>\n",
       "      <td>1.013179</td>\n",
       "      <td>7.534257</td>\n",
       "      <td>8.918689</td>\n",
       "      <td>0.024136</td>\n",
       "      <td>0.061595</td>\n",
       "      <td>0.835121</td>\n",
       "      <td>1.697625</td>\n",
       "      <td>0.775051</td>\n",
       "      <td>7.136544</td>\n",
       "      <td>9.613394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-01-01</th>\n",
       "      <td>5.280477</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.368499</td>\n",
       "      <td>7.030407</td>\n",
       "      <td>0.278953</td>\n",
       "      <td>1.013439</td>\n",
       "      <td>7.534989</td>\n",
       "      <td>8.749881</td>\n",
       "      <td>0.024385</td>\n",
       "      <td>0.061642</td>\n",
       "      <td>0.836467</td>\n",
       "      <td>1.723164</td>\n",
       "      <td>0.792263</td>\n",
       "      <td>7.103393</td>\n",
       "      <td>9.601413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-02-01</th>\n",
       "      <td>5.360187</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.344355</td>\n",
       "      <td>6.991528</td>\n",
       "      <td>0.275864</td>\n",
       "      <td>1.002132</td>\n",
       "      <td>7.450718</td>\n",
       "      <td>8.740565</td>\n",
       "      <td>0.024147</td>\n",
       "      <td>0.061910</td>\n",
       "      <td>0.840732</td>\n",
       "      <td>1.729072</td>\n",
       "      <td>0.786856</td>\n",
       "      <td>6.999946</td>\n",
       "      <td>9.487741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-01</th>\n",
       "      <td>5.294459</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.192864</td>\n",
       "      <td>6.932323</td>\n",
       "      <td>0.274671</td>\n",
       "      <td>0.997948</td>\n",
       "      <td>7.419710</td>\n",
       "      <td>8.570487</td>\n",
       "      <td>0.023965</td>\n",
       "      <td>0.061479</td>\n",
       "      <td>0.817947</td>\n",
       "      <td>1.728611</td>\n",
       "      <td>0.778806</td>\n",
       "      <td>6.946884</td>\n",
       "      <td>9.411210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-04-01</th>\n",
       "      <td>5.242195</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.184009</td>\n",
       "      <td>6.943622</td>\n",
       "      <td>0.277260</td>\n",
       "      <td>1.000525</td>\n",
       "      <td>7.441166</td>\n",
       "      <td>8.764501</td>\n",
       "      <td>0.023905</td>\n",
       "      <td>0.063074</td>\n",
       "      <td>0.810151</td>\n",
       "      <td>1.755259</td>\n",
       "      <td>0.776296</td>\n",
       "      <td>6.951871</td>\n",
       "      <td>9.462911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-05-01</th>\n",
       "      <td>5.005306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.948983</td>\n",
       "      <td>6.823126</td>\n",
       "      <td>0.279438</td>\n",
       "      <td>0.999182</td>\n",
       "      <td>7.433633</td>\n",
       "      <td>8.709807</td>\n",
       "      <td>0.023987</td>\n",
       "      <td>0.059991</td>\n",
       "      <td>0.791149</td>\n",
       "      <td>1.768549</td>\n",
       "      <td>0.766221</td>\n",
       "      <td>6.734946</td>\n",
       "      <td>9.261577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-01</th>\n",
       "      <td>4.979518</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.950714</td>\n",
       "      <td>6.811871</td>\n",
       "      <td>0.281835</td>\n",
       "      <td>0.995718</td>\n",
       "      <td>7.405667</td>\n",
       "      <td>8.444707</td>\n",
       "      <td>0.024040</td>\n",
       "      <td>0.059512</td>\n",
       "      <td>0.780189</td>\n",
       "      <td>1.761354</td>\n",
       "      <td>0.758895</td>\n",
       "      <td>6.598044</td>\n",
       "      <td>9.130642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-01</th>\n",
       "      <td>5.012121</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.055595</td>\n",
       "      <td>6.710868</td>\n",
       "      <td>0.283903</td>\n",
       "      <td>0.995866</td>\n",
       "      <td>7.405674</td>\n",
       "      <td>8.367511</td>\n",
       "      <td>0.024129</td>\n",
       "      <td>0.057252</td>\n",
       "      <td>0.786601</td>\n",
       "      <td>1.748852</td>\n",
       "      <td>0.771847</td>\n",
       "      <td>6.445860</td>\n",
       "      <td>8.991664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-08-01</th>\n",
       "      <td>4.965026</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.977469</td>\n",
       "      <td>6.495135</td>\n",
       "      <td>0.283444</td>\n",
       "      <td>0.994767</td>\n",
       "      <td>7.398765</td>\n",
       "      <td>8.137790</td>\n",
       "      <td>0.024330</td>\n",
       "      <td>0.057075</td>\n",
       "      <td>0.793987</td>\n",
       "      <td>1.734904</td>\n",
       "      <td>0.774446</td>\n",
       "      <td>6.269399</td>\n",
       "      <td>8.848272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-01</th>\n",
       "      <td>4.983603</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.081359</td>\n",
       "      <td>6.494259</td>\n",
       "      <td>0.285689</td>\n",
       "      <td>1.001408</td>\n",
       "      <td>7.450196</td>\n",
       "      <td>8.298461</td>\n",
       "      <td>0.024183</td>\n",
       "      <td>0.056498</td>\n",
       "      <td>0.798618</td>\n",
       "      <td>1.745218</td>\n",
       "      <td>0.782099</td>\n",
       "      <td>6.248933</td>\n",
       "      <td>8.875585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-10-01</th>\n",
       "      <td>4.970688</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.074534</td>\n",
       "      <td>6.504182</td>\n",
       "      <td>0.290986</td>\n",
       "      <td>1.007866</td>\n",
       "      <td>7.501332</td>\n",
       "      <td>8.421898</td>\n",
       "      <td>0.024206</td>\n",
       "      <td>0.056486</td>\n",
       "      <td>0.798722</td>\n",
       "      <td>1.757951</td>\n",
       "      <td>0.780921</td>\n",
       "      <td>6.377096</td>\n",
       "      <td>8.986162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-11-01</th>\n",
       "      <td>4.904225</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.041424</td>\n",
       "      <td>6.483424</td>\n",
       "      <td>0.295334</td>\n",
       "      <td>1.013827</td>\n",
       "      <td>7.544639</td>\n",
       "      <td>8.492068</td>\n",
       "      <td>0.024202</td>\n",
       "      <td>0.057005</td>\n",
       "      <td>0.786431</td>\n",
       "      <td>1.784340</td>\n",
       "      <td>0.766922</td>\n",
       "      <td>6.431025</td>\n",
       "      <td>9.063290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-01</th>\n",
       "      <td>4.866181</td>\n",
       "      <td>3.856288</td>\n",
       "      <td>4.988267</td>\n",
       "      <td>6.456522</td>\n",
       "      <td>0.294242</td>\n",
       "      <td>1.013573</td>\n",
       "      <td>7.543915</td>\n",
       "      <td>8.551135</td>\n",
       "      <td>0.024079</td>\n",
       "      <td>0.056504</td>\n",
       "      <td>0.766766</td>\n",
       "      <td>1.794140</td>\n",
       "      <td>0.758966</td>\n",
       "      <td>6.378575</td>\n",
       "      <td>9.025915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-01-01</th>\n",
       "      <td>4.853165</td>\n",
       "      <td>3.804115</td>\n",
       "      <td>4.911962</td>\n",
       "      <td>6.346387</td>\n",
       "      <td>0.292240</td>\n",
       "      <td>0.999275</td>\n",
       "      <td>7.440202</td>\n",
       "      <td>8.420160</td>\n",
       "      <td>0.024068</td>\n",
       "      <td>0.055033</td>\n",
       "      <td>0.770258</td>\n",
       "      <td>1.786485</td>\n",
       "      <td>0.757620</td>\n",
       "      <td>6.110671</td>\n",
       "      <td>8.793069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-02-01</th>\n",
       "      <td>4.744075</td>\n",
       "      <td>3.801014</td>\n",
       "      <td>4.795058</td>\n",
       "      <td>6.437374</td>\n",
       "      <td>0.293786</td>\n",
       "      <td>0.998515</td>\n",
       "      <td>7.434137</td>\n",
       "      <td>8.415267</td>\n",
       "      <td>0.023872</td>\n",
       "      <td>0.055658</td>\n",
       "      <td>0.768404</td>\n",
       "      <td>1.785897</td>\n",
       "      <td>0.749566</td>\n",
       "      <td>6.011575</td>\n",
       "      <td>8.727280</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>86 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Srednji                                                    \\\n",
       "Valuta           AUD       BAM       CAD       CHF       CZK       DKK   \n",
       "Datum                                                                    \n",
       "2011-01-01  5.521513       NaN  5.571587  5.794304  0.302292  0.992650   \n",
       "2011-02-01  5.469563       NaN  5.492327  5.710786  0.305517  0.994092   \n",
       "2011-03-01  5.338322       NaN  5.415269  5.746383  0.303387  0.991520   \n",
       "2011-04-01  5.386425       NaN  5.324651  5.671406  0.303116  0.987303   \n",
       "2011-05-01  5.499733       NaN  5.323025  5.882541  0.303557  0.991288   \n",
       "2011-06-01  5.463301       NaN  5.265003  6.121611  0.305374  0.993951   \n",
       "2011-07-01  5.586135       NaN  5.427585  6.288996  0.304951  0.995140   \n",
       "2011-08-01  5.466704       NaN  5.305947  6.657745  0.307502  1.000725   \n",
       "2011-09-01  5.575827       NaN  5.432720  6.250744  0.305516  1.005435   \n",
       "2011-10-01  5.518712       NaN  5.345578  6.085039  0.301705  1.005341   \n",
       "2011-11-01  5.573647       NaN  5.378559  6.082743  0.294278  1.006383   \n",
       "2011-12-01  5.758831       NaN  5.559832  6.112429  0.294873  1.009852   \n",
       "2012-01-01  6.073910       NaN  5.768345  6.231979  0.295560  1.015017   \n",
       "2012-02-01  6.148260       NaN  5.747129  6.279834  0.302710  1.019586   \n",
       "2012-03-01  6.024449       NaN  5.746059  6.251841  0.305572  1.014048   \n",
       "2012-04-01  5.888507       NaN  5.728512  6.234184  0.302470  1.007404   \n",
       "2012-05-01  5.868946       NaN  5.824643  6.268465  0.298041  1.012824   \n",
       "2012-06-01  5.997273       NaN  5.863707  6.284864  0.294551  1.015416   \n",
       "2012-07-01  6.260851       NaN  5.997593  6.241017  0.294473  1.007610   \n",
       "2012-08-01  6.336171       NaN  6.082778  6.234162  0.299211  1.005625   \n",
       "2012-09-01  6.010115       NaN  5.910138  6.145893  0.300599  0.996427   \n",
       "2012-10-01  5.962364       NaN  5.868991  6.200713  0.300724  1.005722   \n",
       "2012-11-01  6.116261       NaN  5.896474  6.254353  0.297418  1.010459   \n",
       "2012-12-01  6.019501       NaN  5.808641  6.228983  0.298751  1.009275   \n",
       "2013-01-01  5.987356       NaN  5.751224  6.166394  0.296583  1.014281   \n",
       "2013-02-01  5.846483       NaN  5.622783  6.161676  0.297918  1.016386   \n",
       "2013-03-01  6.042051       NaN  5.704623  6.185597  0.295891  1.017536   \n",
       "2013-04-01  6.073394       NaN  5.738285  6.234325  0.294276  1.019776   \n",
       "2013-05-01  5.790835       NaN  5.719164  6.104171  0.292351  1.015400   \n",
       "2013-06-01  5.376424       NaN  5.523467  6.084023  0.291561  1.005788   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2015-09-01  4.765329       NaN  5.091709  6.942959  0.279877  1.015223   \n",
       "2015-10-01  4.888398       NaN  5.183148  7.006613  0.281373  1.021851   \n",
       "2015-11-01  5.050875       NaN  5.329308  7.016779  0.281113  1.018581   \n",
       "2015-12-01  5.098144       NaN  5.148764  7.049754  0.282652  1.023288   \n",
       "2016-01-01  4.937558       NaN  4.951244  7.004027  0.283337  1.025618   \n",
       "2016-02-01  4.908655       NaN  4.976686  6.925609  0.282561  1.023313   \n",
       "2016-03-01  5.095151       NaN  5.145003  6.930301  0.279847  1.014694   \n",
       "2016-04-01  5.068793       NaN  5.143247  6.858715  0.277368  1.006970   \n",
       "2016-05-01  4.855564       NaN  5.126689  6.783124  0.277404  1.007427   \n",
       "2016-06-01  4.939507       NaN  5.184768  6.888549  0.277882  1.010112   \n",
       "2016-07-01  5.095732       NaN  5.196875  6.892748  0.277106  1.006805   \n",
       "2016-08-01  5.087716       NaN  5.133501  6.878600  0.276802  1.005008   \n",
       "2016-09-01  5.071550       NaN  5.108462  6.857253  0.277321  1.005821   \n",
       "2016-10-01  5.180651       NaN  5.140420  6.893958  0.277822  1.008377   \n",
       "2016-11-01  5.240763       NaN  5.169131  6.986309  0.278071  1.009765   \n",
       "2016-12-01  5.251182       NaN  5.349959  7.003823  0.278839  1.013179   \n",
       "2017-01-01  5.280477       NaN  5.368499  7.030407  0.278953  1.013439   \n",
       "2017-02-01  5.360187       NaN  5.344355  6.991528  0.275864  1.002132   \n",
       "2017-03-01  5.294459       NaN  5.192864  6.932323  0.274671  0.997948   \n",
       "2017-04-01  5.242195       NaN  5.184009  6.943622  0.277260  1.000525   \n",
       "2017-05-01  5.005306       NaN  4.948983  6.823126  0.279438  0.999182   \n",
       "2017-06-01  4.979518       NaN  4.950714  6.811871  0.281835  0.995718   \n",
       "2017-07-01  5.012121       NaN  5.055595  6.710868  0.283903  0.995866   \n",
       "2017-08-01  4.965026       NaN  4.977469  6.495135  0.283444  0.994767   \n",
       "2017-09-01  4.983603       NaN  5.081359  6.494259  0.285689  1.001408   \n",
       "2017-10-01  4.970688       NaN  5.074534  6.504182  0.290986  1.007866   \n",
       "2017-11-01  4.904225       NaN  5.041424  6.483424  0.295334  1.013827   \n",
       "2017-12-01  4.866181  3.856288  4.988267  6.456522  0.294242  1.013573   \n",
       "2018-01-01  4.853165  3.804115  4.911962  6.346387  0.292240  0.999275   \n",
       "2018-02-01  4.744075  3.801014  4.795058  6.437374  0.293786  0.998515   \n",
       "\n",
       "                                                                         \\\n",
       "Valuta           EUR        GBP       HUF       JPY       NOK       PLN   \n",
       "Datum                                                                     \n",
       "2011-01-01  7.396420   8.724773  0.026849  0.067089  0.945634  1.900072   \n",
       "2011-02-01  7.410873   8.753128  0.027346  0.065763  0.945485  1.889289   \n",
       "2011-03-01  7.393749   8.546276  0.027285  0.064709  0.944455  1.843635   \n",
       "2011-04-01  7.362212   8.340644  0.027759  0.061243  0.942367  1.852690   \n",
       "2011-05-01  7.391226   8.407499  0.027741  0.063371  0.942421  1.877661   \n",
       "2011-06-01  7.412196   8.368008  0.027805  0.063943  0.946782  1.869097   \n",
       "2011-07-01  7.419738   8.367082  0.027778  0.065324  0.953285  1.858853   \n",
       "2011-08-01  7.454965   8.505480  0.027409  0.067407  0.957383  1.813037   \n",
       "2011-09-01  7.486844   8.578141  0.026403  0.070620  0.970303  1.732927   \n",
       "2011-10-01  7.483324   8.602293  0.025281  0.071396  0.964879  1.718539   \n",
       "2011-11-01  7.487735   8.721751  0.024205  0.071202  0.962638  1.692721   \n",
       "2011-12-01  7.507179   8.883743  0.024681  0.073068  0.969097  1.675588   \n",
       "2012-01-01  7.546707   9.062576  0.024559  0.075958  0.982265  1.723388   \n",
       "2012-02-01  7.579384   9.056639  0.026075  0.073301  1.001840  1.810179   \n",
       "2012-03-01  7.539590   9.029432  0.025834  0.069328  1.002743  1.823356   \n",
       "2012-04-01  7.494357   9.102995  0.025386  0.069884  0.990552  1.795660   \n",
       "2012-05-01  7.528940   9.359736  0.025706  0.073592  0.994298  1.758317   \n",
       "2012-06-01  7.546585   9.365869  0.025620  0.076227  1.000331  1.751013   \n",
       "2012-07-01  7.494496   9.489191  0.026139  0.077085  1.004560  1.786904   \n",
       "2012-08-01  7.486777   9.489612  0.026897  0.076854  1.021260  1.831579   \n",
       "2012-09-01  7.426569   9.310771  0.026156  0.073992  1.005044  1.795046   \n",
       "2012-10-01  7.500421   9.306267  0.026601  0.073328  1.013000  1.825608   \n",
       "2012-11-01  7.536449   9.378519  0.026697  0.072661  1.027117  1.823028   \n",
       "2012-12-01  7.529460   9.276943  0.026424  0.068924  1.023597  1.838537   \n",
       "2013-01-01  7.567746   9.115161  0.025765  0.064257  1.025649  1.830966   \n",
       "2013-02-01  7.582399   8.790390  0.025931  0.060886  1.021279  1.817114   \n",
       "2013-03-01  7.585782   8.819467  0.025069  0.061767  1.013480  1.826196   \n",
       "2013-04-01  7.602485   8.937617  0.025445  0.059816  1.008648  1.837236   \n",
       "2013-05-01  7.568123   8.924146  0.025871  0.057850  1.001166  1.815279   \n",
       "2013-06-01  7.500346   8.801832  0.025367  0.058384  0.973363  1.754321   \n",
       "...              ...        ...       ...       ...       ...       ...   \n",
       "2015-09-01  7.574467  10.364283  0.024205  0.056137  0.814340  1.796225   \n",
       "2015-10-01  7.622835  10.392797  0.024507  0.056511  0.820466  1.795134   \n",
       "2015-11-01  7.598376  10.750593  0.024351  0.057696  0.819756  1.788498   \n",
       "2015-12-01  7.634682  10.554799  0.024323  0.057725  0.809859  1.780026   \n",
       "2016-01-01  7.652777  10.149827  0.024322  0.059622  0.797414  1.739975   \n",
       "2016-02-01  7.636668   9.867520  0.024628  0.059796  0.799420  1.735803   \n",
       "2016-03-01  7.566498   9.692216  0.024343  0.060457  0.801724  1.761361   \n",
       "2016-04-01  7.494619   9.455753  0.024064  0.060211  0.803683  1.742605   \n",
       "2016-05-01  7.494223   9.609321  0.023842  0.060881  0.805481  1.701641   \n",
       "2016-06-01  7.511915   9.533886  0.023951  0.063181  0.804885  1.708288   \n",
       "2016-07-01  7.489517   8.912073  0.023810  0.065066  0.800139  1.702209   \n",
       "2016-08-01  7.477713   8.756782  0.024099  0.065848  0.802279  1.737718   \n",
       "2016-09-01  7.490070   8.795602  0.024272  0.065566  0.813478  1.732805   \n",
       "2016-10-01  7.502932   8.417464  0.024453  0.065619  0.833846  1.742061   \n",
       "2016-11-01  7.513263   8.637247  0.024350  0.064406  0.827292  1.713480   \n",
       "2016-12-01  7.534257   8.918689  0.024136  0.061595  0.835121  1.697625   \n",
       "2017-01-01  7.534989   8.749881  0.024385  0.061642  0.836467  1.723164   \n",
       "2017-02-01  7.450718   8.740565  0.024147  0.061910  0.840732  1.729072   \n",
       "2017-03-01  7.419710   8.570487  0.023965  0.061479  0.817947  1.728611   \n",
       "2017-04-01  7.441166   8.764501  0.023905  0.063074  0.810151  1.755259   \n",
       "2017-05-01  7.433633   8.709807  0.023987  0.059991  0.791149  1.768549   \n",
       "2017-06-01  7.405667   8.444707  0.024040  0.059512  0.780189  1.761354   \n",
       "2017-07-01  7.405674   8.367511  0.024129  0.057252  0.786601  1.748852   \n",
       "2017-08-01  7.398765   8.137790  0.024330  0.057075  0.793987  1.734904   \n",
       "2017-09-01  7.450196   8.298461  0.024183  0.056498  0.798618  1.745218   \n",
       "2017-10-01  7.501332   8.421898  0.024206  0.056486  0.798722  1.757951   \n",
       "2017-11-01  7.544639   8.492068  0.024202  0.057005  0.786431  1.784340   \n",
       "2017-12-01  7.543915   8.551135  0.024079  0.056504  0.766766  1.794140   \n",
       "2018-01-01  7.440202   8.420160  0.024068  0.055033  0.770258  1.786485   \n",
       "2018-02-01  7.434137   8.415267  0.023872  0.055658  0.768404  1.785897   \n",
       "\n",
       "                                          \n",
       "Valuta           SEK       USD       XDR  \n",
       "Datum                                     \n",
       "2011-01-01  0.829051  5.537878  8.575765  \n",
       "2011-02-01  0.842513  5.431365  8.486219  \n",
       "2011-03-01  0.832785  5.285354  8.351255  \n",
       "2011-04-01  0.820994  5.105235  8.158269  \n",
       "2011-05-01  0.825230  5.142271  8.214160  \n",
       "2011-06-01  0.815349  5.148899  8.236234  \n",
       "2011-07-01  0.812134  5.193281  8.283039  \n",
       "2011-08-01  0.814209  5.192441  8.342176  \n",
       "2011-09-01  0.820237  5.420572  8.540190  \n",
       "2011-10-01  0.820534  5.467645  8.598491  \n",
       "2011-11-01  0.819930  5.512767  8.619486  \n",
       "2011-12-01  0.831527  5.688661  8.794582  \n",
       "2012-01-01  0.852955  5.846617  8.980310  \n",
       "2012-02-01  0.859164  5.733239  8.885371  \n",
       "2012-03-01  0.848646  5.709035  8.795810  \n",
       "2012-04-01  0.846429  5.691287  8.782991  \n",
       "2012-05-01  0.837405  5.870676  8.977813  \n",
       "2012-06-01  0.848979  6.026710  9.133588  \n",
       "2012-07-01  0.874998  6.089386  9.173819  \n",
       "2012-08-01  0.904138  6.042111  9.141598  \n",
       "2012-09-01  0.874748  5.787501  8.897525  \n",
       "2012-10-01  0.871788  5.783514  8.908779  \n",
       "2012-11-01  0.876198  5.876333  8.982806  \n",
       "2012-12-01  0.869956  5.747093  8.838613  \n",
       "2013-01-01  0.878060  5.701444  8.753616  \n",
       "2013-02-01  0.890298  5.664825  8.650024  \n",
       "2013-03-01  0.908675  5.846774  8.788637  \n",
       "2013-04-01  0.901713  5.845017  8.792672  \n",
       "2013-05-01  0.882926  5.828459  8.737063  \n",
       "2013-06-01  0.866091  5.687173  8.611107  \n",
       "...              ...       ...       ...  \n",
       "2015-09-01  0.805873  6.745421  9.480873  \n",
       "2015-10-01  0.815649  6.780515  9.539132  \n",
       "2015-11-01  0.815592  7.063317  9.752016  \n",
       "2015-12-01  0.826140  7.034940  9.747479  \n",
       "2016-01-01  0.825211  7.041467  9.730927  \n",
       "2016-02-01  0.812218  6.882671  9.590942  \n",
       "2016-03-01  0.814597  6.827044  9.522787  \n",
       "2016-04-01  0.814043  6.612791  9.316050  \n",
       "2016-05-01  0.807486  6.615648  9.336993  \n",
       "2016-06-01  0.805879  6.687416  9.410964  \n",
       "2016-07-01  0.791452  6.766731  9.407829  \n",
       "2016-08-01  0.787874  6.670247  9.335079  \n",
       "2016-09-01  0.783654  6.683380  9.350946  \n",
       "2016-10-01  0.774453  6.797877  9.382797  \n",
       "2016-11-01  0.762676  6.950066  9.485565  \n",
       "2016-12-01  0.775051  7.136544  9.613394  \n",
       "2017-01-01  0.792263  7.103393  9.601413  \n",
       "2017-02-01  0.786856  6.999946  9.487741  \n",
       "2017-03-01  0.778806  6.946884  9.411210  \n",
       "2017-04-01  0.776296  6.951871  9.462911  \n",
       "2017-05-01  0.766221  6.734946  9.261577  \n",
       "2017-06-01  0.758895  6.598044  9.130642  \n",
       "2017-07-01  0.771847  6.445860  8.991664  \n",
       "2017-08-01  0.774446  6.269399  8.848272  \n",
       "2017-09-01  0.782099  6.248933  8.875585  \n",
       "2017-10-01  0.780921  6.377096  8.986162  \n",
       "2017-11-01  0.766922  6.431025  9.063290  \n",
       "2017-12-01  0.758966  6.378575  9.025915  \n",
       "2018-01-01  0.757620  6.110671  8.793069  \n",
       "2018-02-01  0.749566  6.011575  8.727280  \n",
       "\n",
       "[86 rows x 15 columns]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj.unstack('Valuta')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"15\" halign=\"left\">Srednji</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Valuta</th>\n",
       "      <th>AUD</th>\n",
       "      <th>BAM</th>\n",
       "      <th>CAD</th>\n",
       "      <th>CHF</th>\n",
       "      <th>CZK</th>\n",
       "      <th>DKK</th>\n",
       "      <th>EUR</th>\n",
       "      <th>GBP</th>\n",
       "      <th>HUF</th>\n",
       "      <th>JPY</th>\n",
       "      <th>NOK</th>\n",
       "      <th>PLN</th>\n",
       "      <th>SEK</th>\n",
       "      <th>USD</th>\n",
       "      <th>XDR</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Datum</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-01-01</th>\n",
       "      <td>5.521513</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.571587</td>\n",
       "      <td>5.794304</td>\n",
       "      <td>0.302292</td>\n",
       "      <td>0.992650</td>\n",
       "      <td>7.396420</td>\n",
       "      <td>8.724773</td>\n",
       "      <td>0.026849</td>\n",
       "      <td>0.067089</td>\n",
       "      <td>0.945634</td>\n",
       "      <td>1.900072</td>\n",
       "      <td>0.829051</td>\n",
       "      <td>5.537878</td>\n",
       "      <td>8.575765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-02-01</th>\n",
       "      <td>5.469563</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.492327</td>\n",
       "      <td>5.710786</td>\n",
       "      <td>0.305517</td>\n",
       "      <td>0.994092</td>\n",
       "      <td>7.410873</td>\n",
       "      <td>8.753128</td>\n",
       "      <td>0.027346</td>\n",
       "      <td>0.065763</td>\n",
       "      <td>0.945485</td>\n",
       "      <td>1.889289</td>\n",
       "      <td>0.842513</td>\n",
       "      <td>5.431365</td>\n",
       "      <td>8.486219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-03-01</th>\n",
       "      <td>5.338322</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.415269</td>\n",
       "      <td>5.746383</td>\n",
       "      <td>0.303387</td>\n",
       "      <td>0.991520</td>\n",
       "      <td>7.393749</td>\n",
       "      <td>8.546276</td>\n",
       "      <td>0.027285</td>\n",
       "      <td>0.064709</td>\n",
       "      <td>0.944455</td>\n",
       "      <td>1.843635</td>\n",
       "      <td>0.832785</td>\n",
       "      <td>5.285354</td>\n",
       "      <td>8.351255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-04-01</th>\n",
       "      <td>5.386425</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.324651</td>\n",
       "      <td>5.671406</td>\n",
       "      <td>0.303116</td>\n",
       "      <td>0.987303</td>\n",
       "      <td>7.362212</td>\n",
       "      <td>8.340644</td>\n",
       "      <td>0.027759</td>\n",
       "      <td>0.061243</td>\n",
       "      <td>0.942367</td>\n",
       "      <td>1.852690</td>\n",
       "      <td>0.820994</td>\n",
       "      <td>5.105235</td>\n",
       "      <td>8.158269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-05-01</th>\n",
       "      <td>5.499733</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.323025</td>\n",
       "      <td>5.882541</td>\n",
       "      <td>0.303557</td>\n",
       "      <td>0.991288</td>\n",
       "      <td>7.391226</td>\n",
       "      <td>8.407499</td>\n",
       "      <td>0.027741</td>\n",
       "      <td>0.063371</td>\n",
       "      <td>0.942421</td>\n",
       "      <td>1.877661</td>\n",
       "      <td>0.825230</td>\n",
       "      <td>5.142271</td>\n",
       "      <td>8.214160</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Srednji                                                        \\\n",
       "Valuta           AUD BAM       CAD       CHF       CZK       DKK       EUR   \n",
       "Datum                                                                        \n",
       "2011-01-01  5.521513 NaN  5.571587  5.794304  0.302292  0.992650  7.396420   \n",
       "2011-02-01  5.469563 NaN  5.492327  5.710786  0.305517  0.994092  7.410873   \n",
       "2011-03-01  5.338322 NaN  5.415269  5.746383  0.303387  0.991520  7.393749   \n",
       "2011-04-01  5.386425 NaN  5.324651  5.671406  0.303116  0.987303  7.362212   \n",
       "2011-05-01  5.499733 NaN  5.323025  5.882541  0.303557  0.991288  7.391226   \n",
       "\n",
       "                                                                        \\\n",
       "Valuta           GBP       HUF       JPY       NOK       PLN       SEK   \n",
       "Datum                                                                    \n",
       "2011-01-01  8.724773  0.026849  0.067089  0.945634  1.900072  0.829051   \n",
       "2011-02-01  8.753128  0.027346  0.065763  0.945485  1.889289  0.842513   \n",
       "2011-03-01  8.546276  0.027285  0.064709  0.944455  1.843635  0.832785   \n",
       "2011-04-01  8.340644  0.027759  0.061243  0.942367  1.852690  0.820994   \n",
       "2011-05-01  8.407499  0.027741  0.063371  0.942421  1.877661  0.825230   \n",
       "\n",
       "                                \n",
       "Valuta           USD       XDR  \n",
       "Datum                           \n",
       "2011-01-01  5.537878  8.575765  \n",
       "2011-02-01  5.431365  8.486219  \n",
       "2011-03-01  5.285354  8.351255  \n",
       "2011-04-01  5.105235  8.158269  \n",
       "2011-05-01  5.142271  8.214160  "
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tečaj = tečaj.unstack('Valuta')\n",
    "tečaj.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sada možemo grafički prikazati recimo kretanje tečaja €/\\$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5b0e1d1a58>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5b0e524128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(tečaj['EUR'] / tečaj['USD']).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Domaća zadaća"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Proučite malo podatke iz https://nyu.data-bootcamp.com/data/. Inspirirajte se za 1. zadaću."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}