{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f049b286",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Päivitetty 2023-12-10 / Aki Taanila\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "print(f'Päivitetty {datetime.now().date()} / Aki Taanila')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b14a76e",
   "metadata": {},
   "source": [
    "Olen käyttänyt Excelin grafiikan perusasioiden opetuksessa työkirjaa https://taanila.fi/kaavio.xlsx. Toistan tässä työkirjan esimerkit vertailun vuoksi Python-ympäristössä."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f7f01f1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('white')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ecf703e",
   "metadata": {},
   "source": [
    "## Osa 1 - laadukkaista taulukoista laadukkaita kaavioita"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d1a66359",
   "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>Etelä</th>\n",
       "      <th>Keski</th>\n",
       "      <th>Pohjoinen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1. nelj.</th>\n",
       "      <td>120</td>\n",
       "      <td>98</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2. nelj.</th>\n",
       "      <td>130</td>\n",
       "      <td>102</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3. nelj.</th>\n",
       "      <td>167</td>\n",
       "      <td>120</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4. nelj.</th>\n",
       "      <td>210</td>\n",
       "      <td>180</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Etelä  Keski  Pohjoinen\n",
       "1. nelj.    120     98         89\n",
       "2. nelj.    130    102         95\n",
       "3. nelj.    167    120        108\n",
       "4. nelj.    210    180        120"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# luon dataframen\n",
    "df1 = pd.DataFrame({'Etelä':[120, 130, 167, 210],\n",
    "                    'Keski':[98, 102, 120, 180],\n",
    "                    'Pohjoinen':[89, 95, 108, 120]},\n",
    "                    index = ['1. nelj.', '2. nelj.', '3. nelj.', '4. nelj.'])\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0f676973",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b2285a8cd0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.plot(kind='bar', rot=0)    # rot kääntää luokka-akselin nimiöt\n",
    "\n",
    "plt.yticks([0, 50, 100, 150, 200, 250])    # Arvoakselin asteikon arvot\n",
    "plt.ylabel('Myynti miljoonaa euroa')    # Arvoakselin otsikko\n",
    "plt.grid(axis='y')    # Vaakasuuntainen taustaviivoitus\n",
    "plt.legend(loc=(0.15, -0.2), ncol=3)    # Selitteen sijoittelu ja leveys (3 vierekkäin)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f43effdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b2285bc190>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.T.plot(kind='bar', rot=0)    # Äskeinen arvosarjat ja luokat vaihdettuina päittäin\n",
    "\n",
    "plt.yticks([0, 50, 100, 150, 200, 250])\n",
    "plt.ylabel('Myynti miljoonaa euroa')\n",
    "plt.grid(axis='y')\n",
    "plt.legend(loc=(0, -0.2), ncol=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "daba284c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pylväskaavion sijasta voin käyttää myös viivakaaviota\n",
    "# style määrittää viivan ja havaintopisteen tyylin\n",
    "df1.plot(style='-o')\n",
    "\n",
    "plt.yticks([50, 100, 150, 200, 250])\n",
    "plt.ylabel('Myynti miljoonaa euroa')\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "805159ed",
   "metadata": {},
   "source": [
    "## Osa 2 - vaakapylväskaavio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "095da13a",
   "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>Kotieläimet 1000 kpl</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Siipikarjaa</th>\n",
       "      <td>4056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sikoja</th>\n",
       "      <td>1483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nautakarjaa</th>\n",
       "      <td>915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Poroja</th>\n",
       "      <td>195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lampaita</th>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hevosia</th>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Kotieläimet 1000 kpl\n",
       "Siipikarjaa                  4056\n",
       "Sikoja                       1483\n",
       "Nautakarjaa                   915\n",
       "Poroja                        195\n",
       "Lampaita                      122\n",
       "Hevosia                        59"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.DataFrame({'Kotieläimet 1000 kpl': [4056, 1483, 915, 195, 122, 59]},\n",
    "                    index = ['Siipikarjaa', 'Sikoja', 'Nautakarjaa', 'Poroja', 'Lampaita', 'Hevosia'])\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "718c5370",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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D1bx58xyZlfiPUlJSFBAQoGbNmumtt97SxYsXNXToUL3yyivq06ePnnvuOW3evFlNmjTRnj17tHHjRqdXXQCAGdzd3eXi4qJz587Jz8/P1GkjDMPQ1atX5erqyvQVBURu9KlhGMrMzNS5c+fk6urq9PLx3HJfBrGRI0dmm7xt9erVmj17tr7++mtlZmbqpZdekouLi8qWLatBgwZp4MCBiomJUYcOHTRnzhwdP35cFSpU0Jo1a9S2bVt5eHho9erVatKkiVq0aCFJeuyxx/Tiiy9q2bJlio6Olqenp7Zt26YqVaqoTp06+uSTTxzv5/q9AQMGyGKxyNfX1/FSWElKTk7OlSBWsmRJpxfCent765VXXlGnTp30xhtvaMqUKZo9e7ZGjBihWrVqKTIyUgkJCTleBwDcDYvFovLly+vkyZM6duyYqbUYhqGsrCxHOET+l5t9WqhQIVWoUOGmGSCn3ZdB7HaSkpKUkpKi0NBQx7IbnXHhwgWVLl1a9evX13/+8x9FR0dry5Yt+vjjjyVdf1Hr3//+d6f9lS9fXklJSZKkN998U7NmzdKMGTP00ksvKTg4WKNGjcr2jqsLFy5o/Pjx2r9/v8qXL6/HH39cUu4NZR44cEDr169XTEyM4w9bZmamXF1dlZGRoapVq2rdunWO9QcPHuyoCQDM5Ovrq6pVq97za3nulc1m04EDB+Tv788EvQVEbvWpxWKRm5tbngX2fBfEypQpowoVKujTTz91LLNarbpw4YJKlCghSerYsaOmTJmiUqVK6W9/+5sjSJUrV07Hjx932t+JEyfk5+cnu92u/fv3a8CAARo+fLhOnz6tiRMnatiwYY4gd8OgQYMUHh6uhQsXys3NTRcvXtRHH32Ua+dcrFgxLV++XEWLFlX37t2VnJysqVOnql27dkpKSlJ0dLQ++OAD+fv767PPPtNXX32lVatW5Vo9AHA3LBaL6eHnxjsUvby8TK8FOaOg9Gm+u1m/cePGSktL04IFC5SZmanLly9r6NChGjJkiCO9NmrUSFeuXNG7777reJpQuv4i0i1btmjTpk2y2Wzav3+/5s+fr/bt28vV1VXjxo3Tm2++qatXr6pEiRLy9PRU8eLFs9WQmprq6PiUlBSNGzdOknLtX3xlypTRvHnz9OWXX6p27dpq3769atSooREjRqhmzZqKjY1Vv379FBoaqoULF+qdd9657ZvqAQDA/SHfjYj5+vpqyZIlmjRpkhYsWCC73a6wsDC9/fbbjnXc3NwUGRmpZcuWOU35ULNmTc2cOVNz5szR8OHDVbx4cXXu3Fm9evWSdP3S5NixY1WvXj3Z7XaFhoZq7Nix2WqYOHGiJkyYoEWLFqlo0aJq0aKFAgICdOjQIdWrVy9Xzrt27dpasWLFTds6d+6szp0758pxAQBA7uGl3ybhpd8FCy+ILnjo04KF/ix4zOpTXvoNAABQQBDEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACT5LtXHBU0lUv6yNXD7rTMv9S9z9QLAADufwQxk03uUPOmr0iw2Q1ZXF1MqAgAAOQVLk2azGaz3XQ5IQwAgIKPIAYAAGASghgAAIBJCGIAAAAmIYgBAACYhCAGAABgEoIYAACASQhiAAAAJiGIAQAAmIQgBgAAYBKCGAAAgEkIYgAAACYhiAEAAJiEIAYAAGASghgAAIBJCGIAAAAmIYgBAACYhCAGAABgEoIYAACASQhiAAAAJiGIAQAAmIQgBgAAYBKCGAAAgEkIYgAAACYhiAEAAJiEIAYAAGASghgAAIBJCGIAAAAmIYgBAACYhCAGAABgEoKYySwWy11vY7MbuVAJAADIa25mF/CgG7pqj45dtt/x+v6lfDXz2aBcrAgAAOQVgpjJfj6fpv+dzzK7DAAAYAIuTQIAAJiEIAYAAGASghgAAIBJCGIAAAAmIYgBAACYhCAGAABgEoJYAZKSkqKIiAjFx8c7lm3evFlt27ZVcHCwwsPDNXv2bNnt1+ctMwxDc+bMUXh4uIKDg9W6dWt9+umnZpUPAMADh3nE7sKxY8dUqVIls8u4qZ07d2rYsGE6fvy4Y9nevXsVGxurN998Uw0bNtQvv/yiXr16qVChQnrhhRe0dOlSrV69WvPnz1flypX11VdfafDgwXr44Yf1xBNPmHg2AAA8GEwZEatevbrTqM39qmXLllq7dq0kafny5Xr99ddNrujm1qxZo5dffllDhgxxWp6UlKRnn31WjRs3lqurq6pUqaKIiAjt2LFDknT58mX1799fVapUkYuLi8LDw1WlShXt2rXLjNMAAOCBw4jYbWzYsMHxfUpKiomV3F69evXUunVrubm5OYWxZs2aqVmzZo7PGRkZ+vrrr9W6dWtJ0sCBA532c/ToUR0+fFiPPfZY3hQOAMAD7r67RywzM1OTJ09W8+bNFRQUpDp16mjs2LEyjOsvuo6KitJbb72lzp07KzAwUG3atNGPP/6omJgYx31QX3/9tSQpPj5eDRo00MyZMxUWFqawsDCNHz9emZmZkiSr1aq4uDg1bdpUgYGBql+/vt555x1HLeHh4Vq9erXWrFmjefPmKSEhQSEhIZKuh5bevXurUaNGeuKJJ9SiRQt99dVXefvD+v/8/Pzk5nb7TG21WtW/f395eXkpOjo6W/uNy5Zt2rRRaGhoLlUKAAB+774LYkuXLtW2bdu0dOlSJSYmau7cuVqxYoW2b9/uWOfDDz/U2LFj9cMPP6hIkSLq0qWLmjdvrvj4eDVr1kxjx451rHv27Fn98ssv+vLLL/Xhhx/q66+/1ty5cyVJ06ZN08mTJ7Vq1SolJiYqLi5OM2bM0K+//upUU7t27dS7d2+FhIQoISFBkjRgwABVq1ZNn3/+uRISElSvXj2NGjUq939Af8HPP/+sZ599VteuXdN7770nX19fp/YtW7bomWeeUdOmTTV+/HiTqgQA4MFz312a7NSpk9q1a6eHHnpIycnJysjIkI+Pj86ePetYp1mzZvL395ckhYSE6PLly3rqqackSQ0aNNDixYsd67q4uGjkyJHy9fWVr6+vevbsqXnz5mnw4MEaMGCALBaLfH19debMGXl6ekqSkpOTVbFixdvWOW/ePJUuXVqGYSgpKUlFihRxqvF+sXXrVr300kvq1KmTYmJiso2czZkzRwsWLNCYMWMclywBAEDeuO+CWHp6usaMGaMdO3aoTJkyCggIkGEYjikXJKlYsWKO7y0Wi4oWLer47Orq6riMKUlFixZV8eLFHZ/Lli2r5ORkSdKFCxc0fvx47d+/X+XLl9fjjz8uSU7HupUDBw6oX79+OnfunKpUqaISJUo4Hfd+sHv3bvXv31+jRo1Shw4dsrUvXrxYixcv1vLlyxUQEGBChQAAPNjuuyAWFxenokWL6ttvv5Wnp6fsdnu2e5ZcXFzueH+pqalKT0+Xt7e3JOnkyZN6+OGHJUmDBg1SeHi4Fi5cKDc3N128eFEfffTRn+7z7NmzGjRokGbPnq3w8HBJ1+fr+uyzz+64rrzwzjvv6Nq1axo/frzTJcdatWpp/vz5mjNnjtLT09W1a1en7Xr37q0+ffrkdbkAADxwTAtiKSkpOnPmjNOykiVLymq1qlSpUnJ1dZXVatXs2bNltVqVlZX1l45js9k0efJkvfrqq0pKStLChQv1zDPPSLoe0ry8vGSxWJSSkuIIKzc7lqenp6xWqwzDUFpammw2myPcHTlyRHPmzJF0/WEDDw+Pv1RrTjh48KDj+98/eHAzN+53AwAA5jDtZv3BgwerYcOGTl+//vqr4uLidODAAdWuXVtPP/20rFar6tevr0OHDv3lYxUtWlRNmjTRc889p3bt2qlnz56SpIkTJ2rjxo0KDg5WZGSkSpcurYCAgJseq3Hjxrp06ZJq1aqlkiVLKjY2Vq+88opq1aqlQYMGqX379nJ3d7+nOgEAwIPFxbjfbmzKQfHx8XruueecRonuF1arVbVq1VLlXrP0v/N3Ptr32MNFtGFg/VysDH+FzWbT7t27FRgYKIvFYnY5yAH0acFCfxY8ZvXpjd/fO3fuzDYLwV9x301fAQAA8KAgiAEAAJikQAexsLCw+/KyJAAAgFTAgxgAAMD9jCAGAABgEoIYAACASQhiAAAAJiGIAQAAmOS+e9fkg6ZySR+5evz5S8Zv8C9175PHAQCA+wNBzGSTO9S865l5bXZDFtc7f/E5AAC4P3Fp0mQ2m+2utyGEAQBQMBDEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACTEMQAAABMQhADAAAwCUEMAADAJAQxAAAAkxDEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACTEMQAAABMQhADAAAwCUEMAADAJAQxAAAAkxDEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEDOZxWLJ8X3a7EaO7xMAAOQ8N7MLeNANXbVHxy7bc2x//qV8NfPZoBzbHwAAyD0EMZP9fD5N/zufZXYZAADABFyaBAAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACTEMQeMCkpKYqIiFB8fLxj2datW/XPf/5TQUFBatOmjT7//HOnbZo3b66aNWsqKCjI8XX06NG8Lh0AgAKHCV0fIDt37tSwYcN0/Phxx7J9+/apf//+GjlypNq1a6fdu3frxRdfVJEiRRQWFiar1apffvlFX375pcqVK2di9QAAFDz5dkQsPDxcNWrUcIzQBAYGql69epo8ebLs9px7ZdANI0aM0IgRI3J8v3llzZo1evnllzVkyBCn5Zs2bVJwcLA6duwoNzc3hYSEqHXr1vrggw8kSXv37lWxYsUIYQAA5IJ8PSI2evRoRUZGOj4fPHhQ0dHR8vb21sCBA3P0WGPGjMnR/eW1evXqqXXr1nJzc3MKYzabTYUKFXJa19XVVT///LMk6aeffpK3t7e6deumw4cPq1y5chowYIAaN26cp/UDAFAQ5dsRsZupXr26QkNDtX//fmVkZGjKlClq2LChQkNDFRUVpR9//NFp3XHjxiksLEx9+vSRJH3xxReKjIxUcHCwmjVrpiVLljhG14YNG6Zhw4ZJkjIzMzV58mQ1b95cQUFBqlOnjsaOHSvDMPL+pO+Qn5+f3Nyy5+6IiAh9++232rx5s65du6adO3dq48aNunr1qiTJxcVFNWrU0Lhx47Rt2zZFR0drwIAB2r17dx6fAQAABU++HhH7vaysLO3atUvbt2/XgAEDNGrUKO3fv1/vvfeeypYtqw8++EDR0dFav369Hn74YUnS8ePH9fXXXysrK0vbt2/X4MGDNWXKFDVt2lQHDx5Uv379JEnR0dFOx1q6dKm2bdumpUuXqlSpUkpMTFS3bt301FNPqU6dOnl96vckODhYU6ZM0ezZszVixAjVqlVLkZGRSkhIkCT17NnTaf02bdpo/fr12rx5swIDA02oGACAgiNfj4iNHj1aISEhCgkJcYxKde/eXR07dtT69esVExOjihUrysPDQ88//7wqV66s9evXO7Zv1aqVvL29VaRIEa1evVpNmjRRixYt5Obmpscee0wvvviiVqxYke24nTp10pIlS+Tn56fk5GRlZGTIx8dHZ8+ezcvTzxGXLl1S1apVtW7dOsXHx2vu3Lk6ffq0Hn/8cUnSwoUL9f333zttk5mZKU9PTzPKBQCgQMnXI2IjR450ukfshuTkZGVlZal8+fJOy8uXL6+TJ086PpcqVcrx/YULF/T3v/892/pJSUnZ9p+enq4xY8Zox44dKlOmjAICAmQYRq48JJDbfv31V0VHR+uDDz6Qv7+/PvvsM3311VdatWqVJOn06dNauXKl5s+fr7Jly+o///mPEhMTNXr0aJMrBwAg/8vXQexWSpYsKU9PT504cUJVqlRxLD9+/LjCw8Mdn11cXBzflytXzmlaB0k6ceKE/Pz8su0/Li5ORYsW1bfffitPT0/Z7XaFhobmwpnkvpo1ayo2Nlb9+vXTxYsXVblyZb3zzjuqWrWqJCk2Nlaurq7q0qWLUlNT5e/vr3fffVcVK1Y0uXIAAPK/AhnEXF1d1b59e73xxht69NFHHfeIHTlyRNOnT7/pNu3bt1fXrl21adMmxz1i8+fPV6dOnbKta7VaVapUKbm6uspqtWr27NmyWq3KysrK7VPLEQcPHnT63LlzZ3Xu3Pmm63p4eGj48OEaPnx4XpQGAMADJV/fI3Y7sbGxqlevnqKjoxUWFqZNmzZp4cKFevTRR2+6fs2aNTVz5kzNnz9fISEh+te//qXOnTs7nqj8vbi4OB04cEC1a9fW008/LavVqvr16+vQoUO5fVoAAKAAybcjYlu2bLltu7e3t2JjYxUbG3vT9j+OCklSkyZN1KRJk5uub7fbHdM/PP7441q9evVdVgwAAOCswI6I5aRLly7p+PHjKlmypNmlAACAAoQg9icuX76sxo0bKzU19aZPaAIAAPxV+fbSZF4pUqSIEhMTzS4DAAAUQIyIAQAAmIQgBgAAYBKCGAAAgEkIYgAAACYhiAEAAJiEpyZNVrmkj1w9cu5l4f6lfHNsXwAAIHcRxEw2uUNN+frmbHiy2Q1ZXF3+fEUAAGAqLk2azGaz5fg+CWEAAOQPBDEAAACTEMQAAABMQhADAAAwCUEMAADAJAQxAAAAkxDEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACTEMQAAABMQhADAAAwCUEMAADAJAQxAAAAkxDEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACTEMQAAABMQhADAAAwCUEMAADAJAQxAAAAkxDETGaxWMwuAX/CZjfMLgEAUEC5mV3Ag27oqj06dtludhm4Bf9Svpr5bJDZZQAACiiCmMl+Pp+m/53PMrsMAABgAi5NAgAAmIQgBgAAYBKCGAAAgEkIYgAAACYhiAEAAJiEIAYAAGASghgAAIBJ7ssgduzYMbNLAG7r6NGj6tGjh0JCQtSoUSO98847studJ+ZNTExUjRo1sm3bvHlz1axZU0FBQY6vo0eP5lXpAID7yF0FserVq+vFF1+UYTi/8mX16tUKDw/PkYK2bNmiHj163FVN8fHxOXLsnj176p133smRfaHgSktLU8+ePVW2bFl98803Wr58uT799FOtWbNGkmQYhlatWqUXXnhBmZmZTttarVb98ssv2rhxoxITEx1fVapUMeNUAAAmu+sRsa1bt2rBggW5UYsk6dKlS9mCXl5ZsGCB+vTpY8qxkX/s3LlTFy5c0IgRI1SoUCGVK1dOvXv31hdffCHDMDR8+HCtXLlSAwcOzLbt3r17VaxYMZUrV86EygEA95u7DmJRUVGaOXOmdu3adct1tmzZomeffVZ16tRRzZo11a1bN8flxpuNnkVFRWnWrFmKj4/XyJEjderUKQUFBens2bM6e/asBg8erPDwcNWsWVNNmjTRqlWrbnrc1atXKzQ0VDt27LijOiIjI/XCCy8oJCRE69atc9QhXR+5iIuLU9OmTRUYGKj69es7jZYdPXpUvXv3VqNGjfTEE0+oRYsW+uqrr+72x4l8yG63y93dXe7u7o5lLi4u+u2333T58mUNGjRIH374oQICArJt+9NPP8nb21vdunVTWFiYIiMj+XMDAA+wuw5iEREReuaZZ/TSSy/p0qVL2drPnDmjQYMG6cUXX9T333+vr7/+WoZhaM6cOX+677CwMI0ePVoPP/ywEhMTVbp0acXFxcnd3V0bNmzQrl271K1bN40dO1ZpaWlO265cuVJTp07VokWLFBoaekd17Nu3T61bt9Z3332niIgIp/1NmzZNJ0+e1KpVq5SYmKi4uDjNmDFDv/76qyRpwIABqlatmj7//HMlJCSoXr16GjVq1N3+OJEPBQcHy8vLS9OnT1d6erqSkpK0ePFiSdLVq1dVpkyZW27r4uKiGjVqaNy4cdq2bZuio6M1YMAA7d69O4+qBwDcT/7SS7+HDh2qxMREDRs2TG+//bZTW4kSJbRhwwZVqFBBVqtVZ86cUfHixXX27Nm/VOC4cePk4+Mjd3d3nTp1Sj4+PsrIyNBvv/0mHx8fSddD2Pr16/XRRx85bo6+kzrc3d3Vtm1bubpmz6MDBgyQxWKRr6+vzpw5I09PT0lScnKyKlasqHnz5ql06dIyDENJSUkqUqTIXz5H5C9FihTR/PnzNXHiRDVq1EgVKlRQmzZt9NNPP6lw4cK33bZnz55On9u0aaP169dr8+bNCgwMzMWqAQD3o78UxDw8PPTmm2+qXbt2WrRokYoXL+5oc3d31/r167VixQq5uLioWrVqslqtcnP7S4fSiRMnNGXKFB07dkyVKlVSxYoVJcnpCbVdu3bJ399fH3/8sZ544ok7rsPPz++mIUySLly4oPHjx2v//v0qX768Hn/8cafjHjhwQP369dO5c+dUpUoVlShRwrR725C3MjMzde3aNb333ntycXGRJC1fvlzlypWTt7f3bbdduHChAgICVKdOHaf93Qj6AIAHy1+evqJChQoaO3asZsyY4XRZZdOmTXr//fe1bNkybd26VfPnz3e6V8bV1TXbk2QXL1686TGysrLUu3dvtW3bVvHx8froo4/0/PPPZ1tvzJgxmjJlij7++GN98803d1SHJMcv0ZsZNGiQHn/8cX3//fdas2aNXnrpJUfb2bNnNWjQIA0ZMkTbt2/X8uXL1apVq1v/sFDg9OjRQ6tWrZJhGNq7d6/mzZun5s2b/+l2p0+f1ujRo3XixAldu3bNcem7Xbt2eVA1AOB+c0/ziLVo0ULt27fXhx9+6FiWmpoqV1dXeXl5yTAMffPNN/rPf/6jrKwsSVKVKlV0/vx5bd++XYZh6JNPPnGaQ8nT01Pp6em6du2asrKylJGRIS8vL7m4uOjUqVOaOnWqJDn2J10f/QoICNCLL76o1157Tb/99tuf1vFnUlNT5eXlJYvFopSUFI0bN85x3LS0NNlsNsfox5EjRxz3nv0xZKLg8fDw0Ny5c/XBBx8oODhYgwcPVo8ePe5oCpfY2Fg1aNBAXbp0UUhIiFasWKF3333XMdILAHiw/LXrhb8zfPhw7dmzR5cvX5YktWvXTjt37lTLli1lsVhUuXJlPf/881q+fLkyMzNVo0YN9e3bV8OGDVNaWpqeeuopNWvWzLG/0NBQPfTQQwoNDdWKFSs0YcIEzZw5U+PGjdNDDz2kTp066ciRIzp06JAeffRRp1r69u2rL7/8UqNHj9akSZNuW8efmThxoiZMmKBFixapaNGiatGihQICAnTo0CHVq1dPsbGxeuWVV5Senq4yZcqoU6dOmjp1qg4dOuS4jImCKzQ0VKtXr3Z8ttls2W64DwsL08GDB52WeXh4aPjw4Ro+fHhelAkAuM+5GNzY5NC1a1c9+eST6t+/f64fy2q1qlatWqrca5b+d/7ORumQ9x57uIg2DKz/p+vdCGKBgYGyWCx5UBlyG31asNCfBY9ZfXrj9/fOnTvl6+t7z/u75xGxgsBut+vixYs6ffq0SpYsaXY5AADgAXFfvmsyrx05ckTh4eHy8/PLNp8YAABAbmFETFK1atW0Z88es8sAAAAPGEbEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJ01eYrHJJH7l62M0uA7fgX+reZ00GAOBWCGImm9yhZo68IgG5x2Y3ZHF1MbsMAEABxKVJk9lsNrNLwJ8ghAEAcgtBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACTEMQAAABMQhADAAAwCUEMAADAJAQxAAAAkxDEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACTEMQAAABMQhADAAAwCUEMAADAJAQxAAAAkxDEAAAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEANyiLe3t9klAADyGTezC3jQWSwWs0tADrBYLAoICDC7jFxlsxuyuLqYXQYAFCgEMZMNXbVHxy7bzS4DuC3/Ur6a+WyQ2WUAQIFDEDPZz+fT9L/zWWaXAQAATMA9YgAAACYhiAEAAJiEIAYAAGASghgAAIBJCGIAAAAmIYgBAACYhCAGAABgEoIYgHuWkpKiiIgIxcfHZ2tLTk7Wk08+qdWrVzuW2e12zZgxQw0aNFCtWrXUqVMn/fDDD472pKQk9enTR6GhoQoJCVG/fv104sSJPDkXAMhLBDEA92Tnzp165plndPz48WxtdrtdL7/8si5evOi0fMWKFfriiy+0cuVK7dixQy1atFDv3r119epVSdKAAQNUqlQpbdu2Tdu2bZOPj49effXVPDkfAMhLBSKI/fbbbxo1apQaNmyowMBA1atXT0OHDtWZM2ckSS1bttTatWslSVFRUZo1a9ZdH+PUqVMKCgrSqVOncrR2ID9bs2aNXn75ZQ0ZMuSm7XPmzFGZMmVUtmxZp+U///yz7Ha77Ha7DMOQi4uLvLy8HO0ffPCBXn/9dXl5eclqtSotLU0lSpTI1XMBADMUiFccDRkyRIULF9aqVavk5+en8+fPa/z48erevbvWrVunDRs23PMxHn74YSUmJuZAtUDBUa9ePbVu3Vpubm7Zwtj27du1YcMGffzxx2rdurVT27PPPqsvv/xSjRo1ksVikaenp9599115enpKkuO/MTEx2rBhg/z8/LRkyZI8OScAyEsFYkRs586dioiIkJ+fnySpZMmSGj58uGrWrKnLly8rPDzc6f6UG/bv369//OMfjr/gL168qNdff1316tVTWFiYevfurWPHjkmSTp48qerVq+vkyZOSpF27dum5555TvXr1VKNGDUVGRmr37t15cbrAfcPPz09ubtn/PXfhwgUNHz5c06ZNk4+PT7b2rKws1a5dW5s2bdKuXbvUs2dPDRw4UOfOnXNab/z48dq1a5eaN2+u5557Tqmpqbl2LgBghgIRxFq2bKmRI0dq1KhR2rhxo5KSkuTn56dJkybd8nLG3r179cILLygmJkbR0dGSpIEDB+r48eNas2aNtm7dqsqVKys6OlpWq9Vp24yMDPXt21fNmjXTN998o/j4eFWoUEFTpkzJ7VMF7nuGYSg2NlZRUVF6/PHHb7pObGysGjRooMqVK8vLy0v9+/dX4cKF9emnnzqt5+XlpUKFCmno0KG6cuWKtm/fnhenAAB5pkAEsXHjxmnEiBE6ffq0RowYofDwcEVERDjuC/ujffv2qXv37urRo4c6duwoSTpx4oR++OEHvf766/Lz85OXl5defvllXbt2TVu3bnXa3t3dXR9++KG6dOmizMxMJSUlqVixYjp79myunytwvzt9+rR++OEHzZkzRyEhIQoJCdGpU6c0evRo9e7dW9L1ey4zMzOdtnNzc5O7u7syMjLUrFkz/fjjj442m80mu92uokWL5um5AEBuKxD3iLm6uqpt27Zq27atDMPQ0aNH9cknnyg2NtZxufL3vvvuOwUFBWn9+vV6/vnn5eHhofPnz0uSHnnkEcd6FotFZcuWVVJSkmrWrOm0PD4+Xr169dKVK1fk7+8vNzc3GYaR+ycL3Ocefvhh/fTTT07LwsPD9a9//UuRkZGOz2+//bZCQkJUpkwZ/fvf/9a5c+fUuHFjeXl5yd/fX1OnTtXMmTPl6empiRMnqlKlSgoMDDThjAAg9+T7EbFt27YpKChIly5dkiS5uLjI399fMTExCggI0P79+7NtEx0drblz5yo1NdXxBGW5cuUkyekRfJvNplOnTmULc3v27NHYsWM1Y8YM/fe//9XSpUtVt27dXDpDoOAZNWqUGjRooK5du+rJJ5/U559/roULF6p06dKSpIkTJ+qRRx5Ry5YtFRERofT0dM2fP18eHh4mVw4AOSvfj4iFhobqoYce0quvvqrBgwercuXKunr1qrZs2aJjx46pUaNGWr58udM27u7u8vHx0fjx49WzZ081btxYwcHBatiwocaNG6dp06apcOHCmjlzpmw2mxo3bux0n1hqaqpcXV0dj9vv3r1b7733nq5du5an5w7cTw4ePHjLti1btjh99vHxUVxcnOLi4m66fpEiRTRhwoQcrQ8A7kf5fkTMy8tL//73v+Xn56e+ffsqJCREjRo10tq1a7V48WJVqVLlltvWqVNHHTt2dNwIPGXKFD3yyCNq166dnnzySR08eFBLly5VsWLFnLarW7euunTpoq5duyo0NFSjR49WVFSUUlJSHJc4AQAA/oyLwY1Nd+TEiRN66qmn9PXXX2ebnPKvsFqtqlWrlir3mqX/nc/KgQqB3PPYw0W0YWB9s8vIUzabTbt371ZgYKAsFovZ5eAe0Z8Fj1l9euP3986dO+Xr63vP+8v3I2J54erVqzp48KAsFku20TEAAIC/Kt/fI5YXZs+ereXLl6tXr17y9vY2uxwAAFBAEMTuQExMjGJiYswuAwAAFDBcmgQAADAJQQwAAMAkBDEAAACTEMQAAABMQhADAAAwCU9NmqxySR+5etjNLgO4Lf9S9z5pIQAgO4KYySZ3qJkjM/MCuc1mN2RxdTG7DAAoULg0aTKbzWZ2CcgBNptN+/fvL9D9SQgDgJxHEANySHp6utklAADyGYIYAACASQhiAAAAJiGIAQAAmIQgBgAAYBKCGAAAgEkIYgAAACYhiAEAAJiEIAYAAGASghgAAIBJCGIAAAAmIYgBAACYhCAGAABgEoIYAACASQhiAAAAJiGIAQAAmIQgBgAAYBKCGAAAgEkIYgAAACYhiAEAAJiEIAYAAGASghgAAIBJCGIAAAAmIYgBAACYhCAGAABgEoIYAACASQhiAAAAJiGIAQAAmIQgBuQQb29vs0tADqNPCxb6s+ApCH3qZnYBDzqLxWJ2CcgBFotFAQEBZpeBHESfFiz0Z8Fzuz612Q1ZXF3yuKK/hiBmsqGr9ujYZbvZZQAAUCD4l/LVzGeDzC7jjhHETPbz+TT973yW2WUAAAATcI8YAACASQhiAAAAJiGIAQAAmIQgBgAAYBKCGAAAgEkIYgAAACYhiAEAAJiEecQAAMADwWazKTo6WuXKldOkSZMkSXv27NG4ceN05MgRFS9eXH379lXHjh0d2zRv3lynTp2Sq+v1sSvDMBxtdrtdc+fO1cqVK3X58mX5+/tr+PDhCgq68wllc3VE7LffftOoUaPUsGFDBQYGql69eho6dKjOnDkjSWrZsqXWrl0rSerZs6feeeedO9pvUFCQEhISJEnh4eFavXp1jtQ7YsQIjRgxIkf2BQAA7i+zZ8925Afpek558cUX9c9//lM7duzQ+PHjNXHiRP3444+SJKvVql9++UUbN25UYmKiEhMT9e233zq2nzt3rtavX68lS5YoISFBERER6tOnjzIzM++4plwdERsyZIgKFy6sVatWyc/PT+fPn9f48ePVvXt3rVu3Ths2bHCsu2DBgjveb2JiYm6UqzFjxuTKfgEAgLm+//57ffbZZ2ratKlj2WeffaZixYqpa9eukqQ6deqodevWWr58uZ544gnt3btXxYoVU7ly5bLtz2azaenSpXrzzTf16KOPSpJ69OihOnXq3FVduToitnPnTkVERMjPz0+SVLJkSQ0fPlw1a9bU5cuXnUazoqKiNGvWLEnSsGHDNHz4cD333HMKDAxU8+bN9cUXXzj2W716dcXHx2c73rZt21SrVi1t2rRJkrRr1y4999xzqlevnmrUqKHIyEjt3r1bkhQfH6+GDRsqJiZGISEhevfddzVs2DANGzZMkpSZmanJkyerefPmCgoKUp06dTR27FjHkOTZs2c1ePBghYeHq2bNmmrSpIlWrVqVOz9IAADwl124cEGvvfaapk+fLm9vb8fyw4cPq1q1ak7r+vv768CBA5Kkn376Sd7e3urWrZvCwsIUGRmpb775RpJ0/PhxXb58WZcvX1ZkZKTCwsLUs2dPeXp6ysPD445ry9Ug1rJlS40cOVKjRo3Sxo0blZSUJD8/P02aNEklSpS47bZr1qzRs88+q4SEBPXu3VuDBw/W0aNHb7n+1q1b9dJLL+mNN95Q8+bNlZGRob59+6pZs2b65ptvFB8frwoVKmjKlCmObc6cOaPKlSvr+++/V5cuXZz2t3TpUm3btk1Lly5VYmKi5s6dqxUrVmj79u2SpLi4OLm7u2vDhg3atWuXunXrprFjxyotLe0efmIAACAn2e12vfLKK+revbv+9re/ObWlpaU5BTNJ8vLy0pUrVyRJLi4uqlGjhsaNG6dt27YpOjpasbGxkq5f1pSkZcuWadasWdq6dasee+wx9ejRQ6mpqXdcX64GsXHjxmnEiBE6ffq0RowYofDwcEVERDjuC7udRo0aqUWLFnJzc9M///lPPf7449q4ceNN1926dav69++v0aNHq2HDhpIkd3d3ffjhh+rSpYsyMzOVlJSkYsWK6ezZs07bdujQQe7u7vL19XVa3qlTJy1ZskR+fn5KTk5WRkaGfHx8HNuPGzdOI0eOlLu7u06dOiUfHx9lZGQ4OgYAAJhv3rx58vDwUFRUVLY2b29vZWRkOC278fteun7/+ltvvaVKlSrJw8NDbdq0Ue3atSXJMer1r3/9S+XKlZOXl5deeuklWa1W7dq1647ry9V7xFxdXdW2bVu1bdtWhmHo6NGj+uSTTxQbG+u4XHkrlSpVcvpctmxZnTt37qbrfv/993rssce0Zs0atWjRQpJksVgUHx+vXr166cqVK/L395ebm5vT0w6SVKpUqZvuMz09XWPGjNGOHTtUpkwZBQQEyDAM2e12SdKJEyc0ZcoUHTt2TJUqVVLFihUlydEOAADM98knnyg5OVkhISGS5AheX3zxhWJjY/Xf//7Xaf0jR46oatWqkqSFCxcqICDA6b6vrKwsSVKFChXk5ubmdGO+YRiOrzuVayNi27ZtU1BQkC5duiTp+vCev7+/YmJiFBAQoP379992+z+OXJ08eVJly5a96boxMTF66623lJiYqBUrVki6/jjq2LFjNWPGDP33v//V0qVLVbdu3Wzburi43HSfcXFx8vb21rfffqt169Zp4sSJjpCVlZWl3r17q23btoqPj9dHH32k559//rbnAwAA8t6nn36qXbt2KSEhQQkJCWrVqpVatWrleMrx/PnzWrJkibKysrR9+3atW7dO7du3lySdPn1ao0eP1okTJ3Tt2jWtWrVKe/bskST5+vqqVatWmjhxok6ePKnMzExNmzZNRYoU0T/+8Y87ri/XglhoaKgeeughvfrqqzp48KCysrJktVq1du1aHTt2TI0aNbrt9p9//rm+++47x4kfOnRIrVq1uum67u7uKl26tF599VVNnjxZx48fV2pqqlxdXeXl5SVJ2r17t9577707fqTUarXK09NTrq6uslqtmjJliqxWq7KyspSVlaWMjAx5eXnJxcVFp06d0tSpUyX9X1IGAAD3t+LFi2vRokX69NNPFRYWpri4OMXFxTmCVGxsrBo0aKAuXbooJCREK1as0FtvveXYfuzYsWratKmee+45hYWFae/evVq4cKEje9yJXLs06eXlpX//+9+aPXu2+vbtqwsXLsjd3V2BgYFavHixqlSpctvtQ0JCNH/+fP3rX/9SpUqV9O677+qRRx657Tbt27fX5s2bNXToUL3//vvq0qWLunbtKrvdrvLlyysqKkrTp0/X+fPn/7T+uLg4jRgxQrVr15aPj48aNWqk+vXr69ChQypUqJAmTJigmTNnaty4cXrooYfUqVMnHTlyRIcOHXI8xgoAAO4vNyZyvaFGjRqOq2l/5OHhoeHDh2v48OGOZVar1ak9JiZGMTExf7keF+NuLmTmkRtTSPzxh5XbYmNj5ebmpgkTJuT6saxWq2rVqqXKvWbpf+cZRQMAICc89nARbRhYP9f2f+P3986dO7M96PdX8K7J/+/SpUs6fvy4SpYsaXYpAADgAUEQk3T58mU1btxYqampioyMNLscAADwgLgvX/qd15ckixQpkmuvTQIAALgVRsQAAABMQhADAAAwCUEMAADAJAQxAAAAkxDEAAAATEIQAwAAMMl9OX3Fg6RySR+5etjNLgMAgALBv9S9z3aflwhiJpvcoWaOvCIBAABcZ7Mbsri6mF3GHeHSpMlsNpvZJSAH2Gw27d+/n/4sQOjTgoX+LHhu16f5JYRJBDEgx6Snp5tdAnIYfVqw0J8FT0HoU4IYAACASQhiAAAAJiGIAQAAmIQgBgAAYBKCGAAAgEkIYgAAACYhiAEAAJiEIAYAAGASghgAAIBJCGIAAAAmIYgBAACYxM3sAh5UhmFIkqxWqywWi8nV4F7ZbDZduXKF/ixA6NOChf4seMzqU6vVKun/fo/fK4KYSdLS0iRJ4eHhJlcCAADuVlpamgoXLnzP+3ExcirS4a7Y7XYlJyfLx8dHLi4uZpcDAADugGEYSktLU6lSpeTqeu93eBHEAAAATMLN+gAAACYhiAEAAJiEIAYAAGASghgAAIBJCGIAAAAmIYgBAACYhCAGAABgEoJYHrtw4YL69eunkJAQhYWFafz48bp27ZrZZeEmUlJSFBERofj4eMeyPXv2qGPHjgoKClJ4eLhWrlzptM2aNWsUERGhwMBARUZGKjEx0dFms9k0efJkPfnkkwoKClLfvn2VnJycZ+fzIDtw4IC6d++u2rVrq27duoqNjVVKSook+jQ/+v7779WxY0cFBwerbt26Gjt2rDIyMiTRn/mZzWZTVFSUhg0b5lj2QPSngTzVrVs3IyYmxrhy5Ypx/Phxo2XLlsb8+fPNLgt/kJCQYDz11FNGtWrVjO3btxuGYRiXLl0yateubbz//vtGVlaW8d133xlBQUHGnj17DMMwjO3btxtBQUFGQkKCkZmZaSxevNgICwszrly5YhiGYcyaNcto3bq1cerUKSM1NdUYPHiw0atXL9PO8UGRnp5u1K1b15g5c6Zx9epVIyUlxejVq5fRu3dv+jQfunDhglGjRg3j448/Nmw2m3H27FmjVatWxsyZM+nPfO7NN980/va3vxlDhw41DOPB+TuXIJaHjh07ZlSrVs04c+aMY9mGDRuMRo0amVgV/mj16tVGo0aNjA0bNjgFsY8++sho2rSp07ojRowwYmNjDcMwjJiYGCMuLs6p/emnnzZWrVplGIZhNGjQwFi7dq2j7dy5c0b16tWN48eP5+bpPPCOHj1q9OjRw7h27Zpj2RdffGEEBwfTp/lUamqqYRiGYbfbjYMHDxoRERHGsmXL6M987LvvvjNatGhhDBw40BHEHpT+5NJkHjp8+LCKFSum0qVLO5ZVqVJFp06d0uXLl02sDL9Xr149ff7552rRooXT8sOHD6tatWpOy/z9/XXgwAFJ0pEjR27ZnpqaqjNnzji1lyxZUkWLFtXBgwdz6UwgSZUrV9aCBQtksVgcyzZv3qzHHnuMPs2nfH19JUkNGzZU69at5efnp8jISPozn7pw4YJee+01TZ8+Xd7e3o7lD0p/EsTyUFpamtMfMkmOz1euXDGjJNyEn5+f3Nzcsi2/Wf95eXk5+u527WlpaZKkQoUKZWu/0YbcZxiGZsyYoa+++kqvvfYafZrPffbZZ/rmm2/k6uqqgQMH0p/5kN1u1yuvvKLu3bvrb3/7m1Pbg9KfBLE8VKhQIaWnpzstu/HZx8fHjJJwF7y9vR03BN+QkZHh6Lvbtd/4y+KP/f/77ZG7rFarBg4cqHXr1un9999X9erV6dN8zsvLS6VLl9Yrr7yibdu20Z/50Lx58+Th4aGoqKhsbQ9KfxLE8lDVqlV16dIlnT9/3rHs6NGjKlOmjAoXLmxiZbgT1apV0+HDh52WHTlyRFWrVpV0vX9v1V60aFGVLl1aR44ccbSdO3dOly5dyja0jpx3/PhxtW/fXlarVatWrVL16tUl0af50a5du/T0008rMzPTsSwzM1Pu7u7y9/enP/OZTz75RD/88INCQkIUEhKi9evXa/369QoJCXlg/v8kiOWhSpUqqVatWpowYYKsVqtOnDihuXPnqkOHDmaXhjsQERGh8+fPa8mSJcrKytL27du1bt06tW/fXpLUoUMHrVu3Ttu3b1dWVpaWLFmiCxcuKCIiQpIUGRmpt99+WydOnJDVatWECRNUu3ZtVahQwczTKvB+++03Pf/88woODtbChQtVokQJRxt9mv9Ur15dGRkZmj59ujIzM5WUlKTJkyerQ4cOatasGf2Zz3z66afatWuXEhISlJCQoFatWqlVq1ZKSEh4cP7/NPtpgQfNuXPnjAEDBhi1a9c2/vGPfxiTJk1yepoL95ffPzVpGIbx448/Gs8884wRFBRkNGnSxPj444+d1v/Pf/5jNGvWzAgMDDQ6dOhg7N6929GWmZlpTJ061ahfv74RHBxs9O3b1zh//nyencuDatGiRUa1atWMmjVrGoGBgU5fhkGf5keHDx82unfvboSEhBiNGzc23njjDePq1auGYdCf+d3QoUMdT00axoPRny6GYRhmh0EAAIAHEZcmAQAATEIQAwAAMAlBDAAAwCQEMQAAAJMQxAAAAExCEAMAADAJQQwAAMAkBDEAAACTEMQAAABMQhADAAAwCUEMAADAJAQxAAAAk/w/NUQKGmYt9TwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df2.plot(kind='barh')\n",
    "\n",
    "plt.xticks([0, 1000, 2000, 3000, 4000])\n",
    "plt.grid(axis='x')\n",
    "\n",
    "# lukuarvot pylväiden viereen\n",
    "for container in ax.containers:\n",
    "    plt.bar_label(container, padding=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ce6e97a",
   "metadata": {},
   "source": [
    "## Osa 3 - histogrammi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bf5b036e",
   "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>Henkilöä</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0-1600</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1601-2100</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2101-2600</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2601-3100</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3101-3600</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3601-</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Henkilöä\n",
       "0-1600            5\n",
       "1601-2100        19\n",
       "2101-2600        25\n",
       "2601-3100        20\n",
       "3101-3600         8\n",
       "3601-             5"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = pd.DataFrame({'Henkilöä': [5, 19, 25, 20, 8, 5]},\n",
    "                    index = ['0-1600', '1601-2100', '2101-2600', '2601-3100', '3101-3600', '3601-'])\n",
    "df3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "35092e91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# width=1: pylväät kiinni toisissaan\n",
    "ax = df3.plot(kind='bar', legend=False, edgecolor='white', width=1, rot=45)\n",
    "\n",
    "plt.ylabel('Henkilöä')\n",
    "plt.ylim(0, 30)\n",
    "plt.grid(axis='y')\n",
    "\n",
    "# lukuarvot pylväiden yläpuolelle\n",
    "for container in ax.containers:\n",
    "    ax.bar_label(container, padding=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc52a709",
   "metadata": {},
   "source": [
    "## Osa 4 - mielipiteiden keskiarvoja pylväinä "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "5ece9b30",
   "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>Tyytyväisyyskeskiarvo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Hintataso</th>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Valikoiman laajuus</th>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henkilökunnan palvelualttius</th>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              Tyytyväisyyskeskiarvo\n",
       "Hintataso                                       2.8\n",
       "Valikoiman laajuus                              3.9\n",
       "Henkilökunnan palvelualttius                    4.7"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df4 = pd.DataFrame([2.8, 3.9, 4.7],\n",
    "                    index = ['Hintataso', 'Valikoiman laajuus', 'Henkilökunnan palvelualttius'],\n",
    "                    columns = ['Tyytyväisyyskeskiarvo'])\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "424719e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df4.plot(kind='barh')\n",
    "\n",
    "plt.xlim(1, 5)\n",
    "plt.xlabel('1=erittäin tyytymätön, 5=erittäin tyytyväinen')\n",
    "plt.xticks([1, 2, 3, 4, 5])\n",
    "plt.grid(axis = 'x')\n",
    "\n",
    "# Lukuarvot pylväiden viereen\n",
    "for container in ax.containers:\n",
    "    ax.bar_label(container, padding=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03ac9ebd",
   "metadata": {},
   "source": [
    "## Osa 5 - useita arvosarjoja"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ddadf492",
   "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>Mies</th>\n",
       "      <th>Nainen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Tyytymätön</th>\n",
       "      <td>17</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ei tyytymätön eikä tyytyväinen</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tyytyväinen</th>\n",
       "      <td>6</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Mies  Nainen\n",
       "Tyytymätön                        17       8\n",
       "Ei tyytymätön eikä tyytyväinen    15      15\n",
       "Tyytyväinen                        6      21"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df5a = pd.DataFrame({'Mies': [17, 15, 6],\n",
    "                     'Nainen': [8, 15, 21]},\n",
    "                     index = ['Tyytymätön', 'Ei tyytymätön eikä tyytyväinen', 'Tyytyväinen'])\n",
    "df5a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cc400ac9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df5a.plot(kind='bar', rot=0)\n",
    "\n",
    "plt.yticks([0, 5, 10, 15, 20])\n",
    "# Arvoakselin otsikko vaakasuuntaisena, labelpad määrittää etäisyyden y-akselista\n",
    "plt.ylabel('lkm', rotation=0, labelpad=15)\n",
    "plt.legend(ncol=2)\n",
    "plt.grid(axis='y')\n",
    "\n",
    "for container in ax.containers:\n",
    "    ax.bar_label(container, padding=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e28b01b4",
   "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>Mies</th>\n",
       "      <th>Nainen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Tyytymätön</th>\n",
       "      <td>0.447368</td>\n",
       "      <td>0.181818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ei tyytymätön eikä tyytyväinen</th>\n",
       "      <td>0.394737</td>\n",
       "      <td>0.340909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tyytyväinen</th>\n",
       "      <td>0.157895</td>\n",
       "      <td>0.477273</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Mies    Nainen\n",
       "Tyytymätön                      0.447368  0.181818\n",
       "Ei tyytymätön eikä tyytyväinen  0.394737  0.340909\n",
       "Tyytyväinen                     0.157895  0.477273"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Prosentti-taulukko\n",
    "df5b = df5a.copy()\n",
    "df5b['Mies'] = df5a['Mies'] / df5a['Mies'].sum()\n",
    "df5b['Nainen'] = df5a['Nainen'] / df5a['Nainen'].sum()\n",
    "df5b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c7fa25cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# T vaihtaa dataframen rivit ja sarakkeet päittäin\n",
    "# stacked=True: pinottu pylväskaavio\n",
    "ax = (df5b * 100).T.plot(kind='barh', stacked=True)\n",
    "\n",
    "plt.xlabel('%')\n",
    "plt.grid(axis='x')\n",
    "plt.legend(loc=(-0.10, 1), ncol=3)\n",
    "\n",
    "for bar in ax.patches:\n",
    "    left, bottom, width, height = bar.get_bbox().bounds\n",
    "    if width>0:\n",
    "        label = '{:.0f} %'.format(width)\n",
    "        plt.text(x=left+width/2, y=bottom+height/2, s=label, ha='center', va='center')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7e2ec16b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df5a.T.plot(kind='bar', stacked=True, rot=0)\n",
    "\n",
    "plt.ylabel('Lukumäärä')\n",
    "plt.grid(axis='y')\n",
    "plt.legend(loc=(-0.1, 1), ncol=3)\n",
    "\n",
    "for bar in ax.patches:\n",
    "    left, bottom, width, height = bar.get_bbox().bounds\n",
    "    if width>0:\n",
    "        label = '{:.0f}'.format(width)\n",
    "        plt.text(x=left+width/2, y=bottom+height/2, s=label, ha='center', va='center')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8a16ee6",
   "metadata": {},
   "source": [
    "## Osa 6 - kahden arvoakselin kaavio\n",
    "\n",
    "Jos esitettävät arvosarjat ovat eri suuruusluokkaa, niin kahden arvoakselin käyttö on paikallaan."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "442f2ad2",
   "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>Indeksi</th>\n",
       "      <th>Myynti</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980</th>\n",
       "      <td>85</td>\n",
       "      <td>307954</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>83</td>\n",
       "      <td>566829</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>116</td>\n",
       "      <td>1241391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>144</td>\n",
       "      <td>2109871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>193</td>\n",
       "      <td>3009299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>184</td>\n",
       "      <td>9184649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>254</td>\n",
       "      <td>24933405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>320</td>\n",
       "      <td>29726136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>405</td>\n",
       "      <td>31719819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>442</td>\n",
       "      <td>15343617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>284</td>\n",
       "      <td>6318198</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Indeksi    Myynti\n",
       "1980       85    307954\n",
       "1981       83    566829\n",
       "1982      116   1241391\n",
       "1983      144   2109871\n",
       "1984      193   3009299\n",
       "1985      184   9184649\n",
       "1986      254  24933405\n",
       "1987      320  29726136\n",
       "1988      405  31719819\n",
       "1989      442  15343617\n",
       "1990      284   6318198"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Luon dataframen Helsingin pörssin kehityksestä vuosina 1980 - 1990\n",
    "df6 = pd.DataFrame({'Indeksi':[85,83,116,144,193,184,254,320,405,442,284],\n",
    "                    'Myynti':[307954,566829,1241391,2109871,3009299,9184649,24933405,29726136,31719819,15343617,6318198]},\n",
    "                   index=['1980','1981','1982','1983','1984','1985','1986','1987','1988','1989','1990'])\n",
    "df6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "5da9a4ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: ylabel='Myynti miljoonaa euroa'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Indeksi viivakaaviona\n",
    "df6['Indeksi'].plot(color='C0', figsize=(10, 6))\n",
    "\n",
    "# Indeksille ja sen akselille käytössä olevien värien ensimmäinen väri 'C0'\n",
    "plt.ylabel('Indeksi', color='C0')\n",
    "\n",
    "# Toinen kaavio, jolla on oma arvoakseli, mutta yhteinen x-akseli indeksin kanssa\n",
    "plt.twinx()\n",
    "\n",
    "# Myynnille ja sen akselille käytössä olevien värien toinen väri 'C1'\n",
    "plt.ylabel('Myynti miljoonaa euroa', color='C1')\n",
    "\n",
    "# Myynti pylväinä\n",
    "(df6['Myynti'] / 1000000).plot(kind='bar', color='C1')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8518e36",
   "metadata": {},
   "source": [
    "## Osa 7 - pylväskaavioita\n",
    "\n",
    "Excelissä tämä osa oli esimerkkinä pylväskaavioihin liittyvistä Excel-ongelmista. Täällä vastaavaa ongelmaa ei esiinny."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "35d45e63",
   "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>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>I</th>\n",
       "      <td>250</td>\n",
       "      <td>260</td>\n",
       "      <td>270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>II</th>\n",
       "      <td>350</td>\n",
       "      <td>300</td>\n",
       "      <td>310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>III</th>\n",
       "      <td>100</td>\n",
       "      <td>200</td>\n",
       "      <td>240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IV</th>\n",
       "      <td>140</td>\n",
       "      <td>120</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     2008  2009  2010\n",
       "I     250   260   270\n",
       "II    350   300   310\n",
       "III   100   200   240\n",
       "IV    140   120   140"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df7 = pd.DataFrame({'2008':[250,350,100,140],\n",
    "                    '2009':[260,300,200,120],\n",
    "                    '2010':[270,310,240,140]},\n",
    "                   index=['I','II','III','IV'])\n",
    "df7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8fd9e998",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b2291cb410>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df7.plot(kind='bar', rot=0)\n",
    "\n",
    "plt.xlabel('Vuosineljännes')\n",
    "plt.ylabel('Myynti miljoonaa euroa')\n",
    "plt.grid(axis='y')\n",
    "plt.legend(loc=(0.2, -0.25), ncol=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "1968e5b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2b2291c5010>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df7.T.plot(kind='bar', rot=0)    # T vaihtaa arvosarjat ja luokat päittäin\n",
    "\n",
    "plt.xlabel('Vuosi')\n",
    "plt.ylabel('Myynti miljoonaa euroa')\n",
    "plt.grid(axis='y')\n",
    "plt.legend(loc=(0.2, -0.25), ncol=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc6d609e",
   "metadata": {},
   "source": [
    "## Osa 8 - ympyräkaavio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4d948dbc",
   "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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Nordea</th>\n",
       "      <td>0.25910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OP</th>\n",
       "      <td>0.22920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sampo</th>\n",
       "      <td>0.14446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEB Gyllenberg</th>\n",
       "      <td>0.05700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Evli</th>\n",
       "      <td>0.05190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Muut</th>\n",
       "      <td>0.25820</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      %\n",
       "Nordea          0.25910\n",
       "OP              0.22920\n",
       "Sampo           0.14446\n",
       "SEB Gyllenberg  0.05700\n",
       "Evli            0.05190\n",
       "Muut            0.25820"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df8 = pd.DataFrame([0.2591,0.2292,0.14446,0.0570,0.0519,0.2582],\n",
    "                   index=['Nordea','OP','Sampo','SEB Gyllenberg','Evli','Muut'],\n",
    "                   columns=['%'])\n",
    "df8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6687d660",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# autopct muotoilee prosenttiluvut, muotoilukoodit hieman hankalia\n",
    "df8['%'].plot(kind='pie', autopct='%1.1f %%')\n",
    "\n",
    "plt.ylabel('')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00f1f158",
   "metadata": {},
   "source": [
    "## Osa 9 - aikasarjojen vertailu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a0231b72",
   "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>Etelä</th>\n",
       "      <th>Keski</th>\n",
       "      <th>Pohjoinen</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1.2009</th>\n",
       "      <td>120</td>\n",
       "      <td>98</td>\n",
       "      <td>89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.2009</th>\n",
       "      <td>130</td>\n",
       "      <td>102</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.2009</th>\n",
       "      <td>167</td>\n",
       "      <td>120</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.2009</th>\n",
       "      <td>210</td>\n",
       "      <td>180</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.2010</th>\n",
       "      <td>130</td>\n",
       "      <td>103</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.2010</th>\n",
       "      <td>135</td>\n",
       "      <td>109</td>\n",
       "      <td>99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.2010</th>\n",
       "      <td>172</td>\n",
       "      <td>140</td>\n",
       "      <td>110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.2010</th>\n",
       "      <td>213</td>\n",
       "      <td>189</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.2011</th>\n",
       "      <td>134</td>\n",
       "      <td>104</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Etelä  Keski  Pohjoinen\n",
       "1.2009    120     98         89\n",
       "2.2009    130    102         95\n",
       "3.2009    167    120        108\n",
       "4.2009    210    180        120\n",
       "1.2010    130    103         88\n",
       "2.2010    135    109         99\n",
       "3.2010    172    140        110\n",
       "4.2010    213    189        123\n",
       "1.2011    134    104         88"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df9 = pd.DataFrame({'Etelä':[120,130,167,210,130,135,172,213,134],\n",
    "                    'Keski':[98,102,120,180,103,109,140,189,104],\n",
    "                    'Pohjoinen':[89,95,108,120,88,99,110,123,88]},\n",
    "                   index=['1.2009','2.2009','3.2009','4.2009','1.2010','2.2010','3.2010','4.2010','1.2011'])\n",
    "df9"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96542084",
   "metadata": {},
   "source": [
    "Tässä vaihdan tyylimäärittelyksi **'seaborn-whitegrid'**, jossa taustaviivoitukset ovat valmiina.\n",
    "\n",
    "Huomaa, miten indeksin arvot tulevat automaattisesti kaavion vaaka-akselille.\n",
    "\n",
    "**style**-parametri määrittää viivan ja havaintopisteiden tyylin. Lisätietoa: https://matplotlib.org/api/_as_gen/matplotlib.pyplot.plot.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8f021036",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0ELGxsdx3332UlZUxbNgwwsLCWLZsGdXV1eh0Ol5++WUWLlyIXq9n8+bN3H///WRnZ+Pq6oqvry9arRYvL9nbd3JyQqVS8fDDD6PRaHj11VetMg9B53hrUzKSBJcP6cnAYO929zdWkTyYVUalrqGrzRMIHI7X1p8C4OoRvc2OaggdieUQDkkT+v5XwkNH4PZfYcFH8s+Hj1jNGQFQq9X85z//obGxkYcffhiVSsX7779PUVERM2fOJC4ujszMTD755BNcXFy47bbbmDJlCjfeeCOxsbH8+9//5vXXXyc4OLjVuC4uLixdupSVK1eybds2q81H0D5pRdWsPiSr/B+Y1rE7NWOVSL1BIkGUkRcIOsW+jJLmbLaHLjM9OmLEWI9kV4ooWGgujqshMQW1BvpdYrXDGZdmWuLv78+WLVuafw8ODub1119v8/VarZannnqKp5566rzn5s+fz/z585t/Hz58OMeOHUOlUjF58mTzjRdYhHc2J2OQYNrAoE6p/CdFBZCZUMPO5GIuG9SzCy0UCByL//wpR0euG9WHsIAO6AzbYWhvH7xdtVToGjmSU96pWiaC1ogIiUCgEFklNaw6kAN0TDvSEuOyza4UESYWCDrK7pTi5krInb3mLoRGrWq+HkXVVvMQDolAoBDvbU2h0SARFxXIyFC/Tr3WWI/kRF4lRVV1XWGeQOBQSJLEa+vlqPSNY0Lp49d2rR9TMArNd4jGl2YhHBKBQAHyynXN3UUfMOFOLcDThYFNqYq7RLaNQNAu208XkZgud9G+WK0fUzAKW/dllFJbLwoWmopwSAQCBXhvawr1egNj+/kzzsRaIsYPQZFuKBBcHEmS+E9TZs0t48II9rFskch+gR6E+LhSrzeQmC6E5qbSKYfkxIkT3HHHHYwdO5ZJkybx5JNPUlIi//EPHTrEddddx4gRI5g2bRorV65s9dpVq1YxY8YMYmNjmT9/PgcOHLDcLAQCO6KgUsc3CZkAPNjBzJq2OFuPRDgkAsHF2HSigENZZbg5aVg8xfI9oFQqVfMNgtCRmE6HHRKdTsddd93FiBEj2LFjB7/++itlZWU8/fTTlJeXc/fdd3P11VeTmJjISy+9xCuvvMLhw4cBiI+P58UXX2TZsmUkJiYyd+5cFi9eTG1tbZdNTCCwVT7cnkZdo4ERob7NToUpjO0XgFatIquklqwSUfROIGgLWTsiR0dumxhGDy+XLjlOXLSoR2IuHXZIcnNzGThwIPfddx/Ozs74+flxww03kJiYyJ9//omvry8333wzWq2WCRMmMGfOHL766isAVq5cyezZsxk1ahROTk4sXLgQPz8/fvvtty6bmEBgi5RU1/PlngxAjo6Y0/vC00XbnGIo7soEgrb541g+x3Ir8HDWcM/kruuQbcy0OZZbQUl1fZcdx5HpcB2SiIgIPvzww1aP/fHHHwwZMoTTp0/Tv3/r5kRRUVH88MMPACQnJ7NgwYLznj9x4kSnDdbrzxcM6fV6JElq/t9ZjK8x5bX2gK3Pz/i+6fX6Nt/f9jC+xpTXWpsPt6dQU69nSIg3l0T5d9jmC81xQoQ/ezNK2ZFcyHWj7Lf9uT29h6bg6PMD25yjwXA2s+b2iWH4uGpMtq+9+fm7axnQ05OT+VXsOF3A7Jhebe5nq3Tl+9fRMU0qjCZJEv/973/ZvHkzX375JZ9//jlubm6t9nF1dW3unVJdXX3R5zvDkSNH2nxcq9VSW1uLwWDo9JhGqmqqOFh4kGJdMQGuAcT2iEWj6poeNkpgq0tkdXV1NDQ0mOSgtuRC54atUF1v4NMdhQDMDldz6NChTo9x7hx7SPKd2LaTBew/cAC1nXcbtfX30FwcfX5gW3PcmVXLqfwq3J1UjPOp4uDBg2aPebH5RXsbOJkPq+NP0Vufb/axlEDJ96/TDklVVRVPPfUUx44d48svv2TAgAG4ublRWVnZaj+dToeHh1wFz83NDZ1Od97zfn6dq70AEBMTg0bT2knQ6XRkZGTg5uaGq2vn1dOSJPFb8m/899B/ya85exL1dO/JkjFLmB42vdNj2hKSJFFbW4ubm5tNtsdWq9U4OTkRFRVl0vun1+s5cuRIm+eGLfHmpmRqGgvo39OTv10xDrW64+/FheY4uNHAKzs3UlGnx71XVHMqsL1hL++hqTj6/MD25qg3SDy5ZQcAd0+OJG6seam+HZnf1W6F/Hp6HyfLIDY21qzjWZuufP+MY7dHpxySzMxM/va3vxESEsIPP/yAv78/AP3792fnzp2t9k1OTiY6Ws4giI6Obu5A2/J5U0qYazSa8/5YGo0GlUrV/L+zbMjYwFO7zy+/XlBTwGNbH+O1Ka91iVMybdo0CgsL0Wrlt0GSJDw9PZkzZw5PPPEEavXFJT4DBgzg888/Z9y4cec9t3fvXv72t7+1yma60N9n9erVvP/++6xdu9bMGZmG0a623tvOYO7ru5JKXQOf7JK1Iw9Mi8bJybSuDefO0U2jYUw/f7adKmR3aglDevtawlzFsOX30BI4+vzAdub4y6FsUgqr8XV34s5LIixm08XmNyEyUBaal9aSU1ZHaIDliq9ZCyXfvw6LWsvLy7n99tsZOXIkH330UbMzAjBjxgyKior49NNPaWhoYM+ePaxZs6ZZN3LttdeyZs0a9uzZQ0NDA59++inFxcXMmDHD8jNqQpIkahpq2v1fWVfJsoRlbY/R9G9ZwjIq6yrbHcsUjcYLL7zAgQMHOHDgAAcPHuSjjz7i559/5q233jJr/qNHj+5wavXcuXMVc0a6C1/syaC8toGIHh5caeG15UlNVVtFgTSBQKZBb+B/G+Wb4LsnR+Dl6mSV43q4aJurLotsm87T4du0n376idzcXH7//XfWrVvX6rkDBw7w8ccf89JLL/HGG2/g7+/PP/7xD8aPHw/AhAkTWLp0Kc8//zz5+flERUWxYsUKfH19LToZI5Ikcdvvt3Gw8KBFxsuvyWfitxPb3W9E0Ag+m/WZWcsiAwYMYMyYMSQlJaHT6XjjjTdYu3YtNTU1DBw4kCeeeIJhw4Y1779z505efvllMjMziYyM5OWXX6Z///7Ex8dz2223NTfwO336NG+//TaHDh3C1dWVadOm8dhjj+Hl5cVPP/3EW2+9xaZNm4iPj+epp57iuuuu4+uvv6auro5x48bxyiuv4Okpt+leu3Yt7733Hrm5uYSFhfHoo48SFxcHwK233kpsbCz79+8nKSmJ4OBgHnjgAa688kqT/yb2Tk19Ix9uTwPg/qlRaDqxVNMRjPUP4lOLadAbcNKIeoeC7s1P+7PJKK4hwMOZ2yeEW/XYk6ICSUgvYWdyEX8ZF2rVY9s7Hf7kuuOOOzh58iQHDx5svqM3/gdZ2/Htt9+yf/9+NmzY0KrTLMC8efNYt24dBw4cYOXKlQwfPtyyMzkHW9RKtEdDQwPx8fHs2bOHSZMm8fzzz7Njxw4+//xzdu7cyfTp01m4cCG5ubnNr0lISOCjjz5i9+7d+Pn5sXz58vPGLS0t5e677yYyMpJt27bx448/kpaWxpNPPtmmHTk5OeTn57N+/XpWrlzJgQMH+PrrrwHYunUrS5cu5bnnniMhIYEHHniABx54oNWS3Pfff88zzzxDfHw8M2fO5LnnnqOurvv2W/k6PpOS6npC/d2ZOzzE4uMP7uWNr7sT1fV6DmeXWXx8gcCeqG808MbGZAAWT4nEw8W6Te3jos8WLDQYbDOz0Vax7jtlJVQqFZ/N+ozaxvazSvbl7+Pejfe2u987l73DqJ6jLrqPm7bzotEXXniBl19+ufn34OBg7rjjDq677jqWL1/O22+/TVhYGAC33347a9as4ddff+Xuu+8GZEcxMFC+Q54+ffp5qdkAmzZtwsnJiccffxytVourqyvPPvsss2fPprCwsE277rvvPlxdXQkLC2PcuHGkpcl3+F9++SU33XQTY8aMAWDq1KlMmzaNb7/9lmeffRaAyy+/nMGDBwNwzTXX8N5771FcXExIiOW/jG0dXYOeD7alAnDvlEi0XRC9UKtVTIgI4PejeexMLmZUmH/7LxIIHJTv9maRU1ZLkJcLt4wPs/rxh/XxxdNFS1lNA0lnKhja28fqNtgrDumQgOyUuDu1LyiaGDKRnu49W2XXtBoHFT3dezIxZCIateWFPkuXLj0vmgRQUFBAQ0MDffr0afV4nz59yM7Obv695bKXk5NTm/neRUVFBAcHtxIqGcfNyclp064ePXq0Gteoj8nJySEhIYFvvvmm+Xm9Xt+8PHfua42CXXPSse2Z7/dmUVBZR29fN+aP7NP+C0xkUlRgk0NSxIOXmV6OXiCwZ3QNet7eJEdH7psahauT9cWZTho14yP82XC8gJ3JRcIh6QTdfrFZo9awZMwSQHY+WmL8fcnYJV3ijFyMwMBAXFxcyMrKavV4ZmYmQUFBnRqrd+/e5OXltXJWMjPlXiotnYeOEBwczH333cfevXub/69du5aXXnqpU+N0B+obDby3JQWARZdG4KztusvNqCM5kFkmuo0Kui1fx2eSV6EjxMeVG8f2VcwO4/UohK2do9s7JADTw6bzyoRXCHJv/UXf071nl6X8todarWbBggW89tprZGRkUF9fz2effUZycjKzZ8/u1FiXXnopAP/3f/+HTqejsLCQl156ifHjx9O7d+eqe15//fV8/vnnzX2Kjhw5wvz58/n11187NU534Mf92eSW6wjycuG60V374Rge4C66jQq6NbX1et5pugG4f1o0LlrlUo/jmhySxPQSdA3iBqGjOOySTWeZ2nsqsyJncaDwAIU1hfRw78HIoJFWj4y05Mknn+TNN99k4cKFlJWVMWDAAD766CP69evXqXG8vLx49913+d///tfsnFx22WUXFLVejFmzZlFTU8PTTz9Nbm4uvr6+LFy4kFtvvbXTYzkyjXoD72yRQ8f3XBrZ5aFjlUrFxKhAftiXzc7kIib371zkSyCwdz7fnU5RVR19/d24bnTXLY92hKggT4K8XCiorGN/ZmlznxvBxREOSQs0ag1jgsdY7XibNm266PNubm48+eSTF3QcjCm9RubPn9+sRzEYDK0Kq0VGRvLhhx+2Kbpt+bpx48adN+6yZcsuuP+5fPHFF61+79Onz3njdQd+OZhLVkktAR7O/GWsdVL/JkUFyA5JiggTC7oXVXWNvLdVjo48OC1a8dR3lUpFXFQgPx3IYWdykXBIOohYsnFAdDodp0+fJiDA9Nb2AtPRGyTe3ixHR+66JAI3Z+tE2Vp2Gy2rEd1GBd2HT3emUVrTQL9AD64ZYRtNJs/qSETBwo4iHBIH5JlnnuHNN99k8eLFSpvSLVl75AypRXLJ6lsnWC/tsKe3K1FBnkgS7BZVWwXdhApdQ3Nq/UOXRXdJar0pGB2SI9lllNc0KGyNfSCWbByQ//znP0qb0G0xGCTe2iQXifvrpH54Wrko06TIAJILqtiZUsQVdtb+XCAwhY+2p1GhayQ6yJM5XVB40FSCfVyJ7OFBSmE1u1OLmTU0WGmTbB7bcCUthCm9ZATK40jv259JeZzKr8LLRcvtE8OtfvyJTXdlu0SYWNANKKup5+MdctHGh6f3t3hbBnMxZtvsFOm/HcIhHBInJ7lxUk1NjcKWCEzB+L4Z30d7RZIk3mwqyrRwUjg+btafz/iIANQqSC2q5kx5+5WKBQJ75oNtqVTWNTIw2IsrbDACMUk4JJ3CIZZsNBoNvr6+FBQUAODu7t6pEu6SJFFXV4darbbLHjjtYavzkySJmpoaCgoK8PX1tYmW5eaw+WQBx3IrcHfWcMekzqVmWwofNydi+vhyKKuMncnFXDtK2fRHgaCrKK6q49Nd6QA8OqM/ahuLjgCMjzx7g5BTVktvXzelTbJpHMIhAbmCKNDslHQGSZJoaGjAycnJpr6wLYWtz8/X17f5/bNXJElqbuh16/gw/D2cFbNlUmQAh7LK2JVcJBwSgcPy3tYUaur1DOvjw4zBPZU2p028XZ0Y3teXA5ll7Ewu4vouLpBo7ziMQ6JSqejVqxdBQUE0NHRO0azX6zlx4gRRUVF2f5feFrY8PycnJ5uzyRR2JBdxMKsMVyc1d10Soagtk6ICeWdLCjtTipAkySadUIHAHAoqdHy+OwOAR2b0t+lzPC4qUDgkHcRhHBIjGo2m019wxh4vrq6uDvHleC6OPj9b4M2m6MhNY0Pp4eWiqC2jwvxw1qrJr6gjpbCKqCAvRe0RCCzNO1tSqGs0MDLUlyk2XpV4UlQgb25KZmeyuEFoD4cQtQoESrIntZiE9BKcNWrumRyptDm4OmkYHeYHwE6RbSNwMHLLavk6Xm4O+tjMATb/BT8i1Bc3Jw1FVfWczK9U2hybRjgkAoGZvNWUWXP9mD4E+7gqbI2MUPcLHJW3NidTrzcwrp8/EyNtvxq1i1bD2H7+AOw4La7HiyEcEoHADPZnlrIjuQitWsWiS5WPjhgxflDvSS1Gb3CcOi+C7k1WSQ3fJ2YB9hEdMSLqkXQM4ZAIBGbw5ka5Kuv8kb3p4+eusDVnientg5eLlgpdI0dzypU2RyCwCG9sPE2jQeKS6MDmqINVMOghfQd+ORshfYf8eycwRizj00qobzR0hYUOgXBIBAITOZJdzuaThahVcO+UKKXNaYVWo2ZchBwlEd1/BY5AWlE1Px3IAeTMGquRtBr+OxTNF3OJ2P8Smi/mwn+Hyo93kIHBXgR4OFNTr+dgVlnX2WrnCIdEIDCRN5t61syL7U14oIfC1pzPpCjZIRFl5AWOwP82nEJvkJg6oAcjQ/2sc9Ck1fD9bVCR2/rxijPy4x10StRqVXNbhx1i2eaCCIdEIDCB42cq+DMpH5UK7ptqW9ERI8Z168T0EnQNnQsxCwS2RHJBJb8ckp2CR2cMsM5BDXpYtwRoS4PV9Ni6v3d4+Sau+QZBOCQXQjgkAoEJvL1Zzqy5MqYXUUGeClvTNlFBngR5uVDXaGB/ZqnS5ggEJvP6htNIEswc3JOYPj7WOWjGrvMjI62QoCJH3q8DGHUkB7LKqNR1rnhnd0E4JAJBJ0kuqGLtkTMA3G+j0RGQqxcbs23Eso3AXjl+poK1h+Xrzarakap8i+7Xx8+d8AB39AaJhLQSMwxzXIRDIhB0knc2JyNJMGNwTwb18lbanIsi1q0F9s7r608BMHtYL+teb54d7I/T0f04GyUR12PbCIdEIOgEGcXVzWvZD06LVtia9jF+AB7OLqNChIkFdsaR7HL+TMpHrYJHplv5egubCN4hwIVqnajAu7e8XwcR9UgujnBIBIJO8M7mFPQGiSkDelhvLdsMevu6ER7gjkGC+FQRJhbYF6+tPwnImWxW78mk1sCs5bQtam1yUmYtk/frIBMiA1Cp4FR+FQUVOouY6UgIh0Qg6CDZpTX8uD8bgAfsIDpiZKK4KxPYIfsyStl8shCNWsVDlyl0vQ2aA169zn/cMwiu/xwGz+3UcL7uzgwNkW9kRH2g8xEOiUDQQd7fmkqjQWJSVACjwqxUB8ECTIqUHZJd4gNQYEcYtSMLRipY5yd1M1SeASdP9Dd+Q61nmPz4pU922hkx0qwjOS2E5uciHBKBoAPkV+j4bq/cQ+P+qfYTHQE5TAxNYeJKESYW2D7xqcXsSC7CSaNSNhoZ/778c8TNEH05pSGXyr9n7DZ5yJY6EkkSfaZaIhwSgaADvL81lfpGA2PC/RgfYcUeGhbA38OZISFydsLuFHFXJrBtJEniP03RketH96Wvv0I9okpS4dQf8vbYuwGoDBgu/56xE0x0JkaH++GsVZNXoSOlsNoSljoMwiERCNqhqKqOrxMyAFk7Yi8dRlsySehIBHbCzuRiEtJKcNaquX+agnV+Ej4EJIiaDoGyHdV+g5E0zvIyTkmqScO6OmkYEy4v+YrrsTXCIREI2mHF9lR0DQaG9/XlkuhApc0xCWOBtJ3JxSJMLLBZ5OiInFnzl7Gh9PJxU8aQuio48IW8PW5R88OSxgV6j5J/Sd9h8vCiHknbCIdEILgIpdX1fLFbjo48OC3KLqMjAGP7+eOkUZFTVktmSY3S5ggEbbLlZCEHMstwdVJz79RI5Qw5/C3UVYB/JERe1uopKbSp7kjGTpOHN+pI9qQU06g3mDyOoyEcEoHgInyyM42aej2De3kzbWCQ0uaYjLuzlhF95TCxuCsT2CKSJPFak3bk1vFhBHm5KmUIxH8gb4+9G9StvyalsEnyRrrpOpIhIT74uDlRWdfI4Zxyc6x1KIRDIhBcgApdA5/sSgfgATuOjhiZGCX62ghslz+T8jmSU467s4ZFlyoYHUndAkUnwdkTYv9y/vN9xoBaCxXZUJZh0iE06rN9pnaeFjcIRoRDIhBcgM92plOpa6R/T08uHxKstDlmY1y33pVShMEgdCQC28FgkJrrjiycGE6Ap4tyxhhTfWP/Aq5t9M5x9oCQkfJ2uunLNkJHcj7CIREI2qCqrpGPdqYBcN/UKNRq+46OAAzv44u7s4bSmgaO51UobY5A0MzvR/M4kVeJl4uWuydHKGdISRqcWidvN6X6tkl407KNBXQk+zNLqalvNHkcR0I4JAJBG3y5J4OymgYiAj24aliI0uZYBGetmrH95BoqYtlGYCvoDRKvb5CjI3+N64evu7NyxiQ2pfpGXgaBFynIFhYn/0zfbvKhwgLc6e3rRoNeIiFN9JkC4ZAIBOdRW6/nw+1yjYF7p0ahcYDoiBFjGXnRR0NgK6w5lEtyQRU+bk7ceUk/5Qypq4L956f6tknoOFBpoCwTyrJMOpxKpRLdf89BOCQCwTl8k5BJUVU9ff3dmBfrGNERI8Z164S0EuobRbqhQFka9Qb+t/E0AHdPjsDb1Uk5Yw5/B3Xl4B8hF0O7GC5eEBIrb5uxbDMp2uiQiIglCIdEIGiFrkHP+9tSAFh8aRROGse6RAYGe+Hv4UxNvZ5D2WVKmyPo5vx0IIe0omr8PZxZODFcOUMkCRIunOrbJs3pv6YXSDNm2iSdqaC4qs7kcRwFx/q0FQjMZOW+bPIr6ujl48qCUb2VNsfiqNWq5mZ7IkwsUJL6RgNvNEVHFl0agYeLVjlj0rZC4YkLp/q2RXiTjsSMCEmgpwuDesmZPLtEnynhkAgERuobDby3RY6OLLo0EhetRmGLmjDoIX0Hfjkb5bsxg96s4Yw6EiFsFSjJyn1ZZJfW0sPLhVvHhytrjDHVd/hN4OrTsdeEjgeVWu5pU5Fr8qHjosQNghGTHZKSkhJmzJhBfHx882Nr167liiuuYOTIkVx++eV88803rV6zatUqZsyYQWxsLPPnz+fAgQOmWy4QWJhVB7LJKZM/IG8Y01dpc2SSVsN/h6L5Yi4R+19C88Vc+O9Q+XETmdT0Abg/s5TqOpFuKLA+ugY9b21KBuDeKZG4OSvo/Jemw8nf5e2Lpfqei6sPBMfI2xaoR7L9dFG37zNlkkOyb98+brjhBjIzM5sfO3XqFM888wyvvPIK+/fv55VXXuGll15i7969AMTHx/Piiy+ybNkyEhMTmTt3LosXL6a2ttYyMxEIzKBRb+DtzXJ05J7JEbg62UB0JGk1fH/b+XdfFWfkx010SkL95XTDRoNEQrpINxRYn28TMjlTrqOXjys3jQ1V1piEFcipvtOgR//OvTb8Evlnhuk6EtFn6iyddkhWrVrF448/ziOPPNLq8fT0dBobGzEYDEiShEqlQqPR4Ows55SvXLmS2bNnM2rUKJycnFi4cCF+fn789ttvlpmJQGAGaw7nkllSg7+HM38Zp/AHJMjLMuuWAG3dMTU9tu7vJi3fqFSq5ijJLhEmFliZ2no9bzctjd43NUpZ57++us2uvh2mZV8bE3F31jIyVPSZAui0iiguLo45c+ag1WpbOSVxcXHExsZy0003odFo0Ov1LFmyhGHDhgGQnJzMggULWo0VFRXFiRMnOnV8vd689fOLjdkVY9sCYn7tvN4gNYeP/zopDBeNSvm/VfoONBddl5agIgd92o6z4rpOMCHCn+/3ZrMzuUj5uSLOUUego3P8fHcahZV19PZ1ZcGIEEX/JqqD36LWlSP59cMQMQ0uYkub8+szDjUqVMWn0ZfngmdPk+yYEOFPfFoJO04XcuPoPiaNYS5deY52dMxOOyQ9evRo8/H6+nr69OnDvffey5gxY9i5cyePPPII/fv3Jy4ujurqatzc3Fq9xtXVlZqazoWojhw50lmTbWJsW0DMr212ZtWSUliNp5OK4e7lHDx40LKGmYBfTjwdKaCdcSye0jLPTo/vpZM/IJLOVLItfj/eLrahbxfnqP1zsTnWNhp4e2MhAHOjnEk6ethaZp2PJDF4+xu4AdkhV1BwqGO2nDu/Qd4RuFekkLHtG0pDpphkSpBUD8D2UwXsO3AAjYKNPJU8Ry2WZ/Xmm2/i7OzMxIkTAZgyZQqzZ8/mu+++Iy4uDjc3N3Q6XavX6HQ6/Pz8OnWcmJgYNBrLhvj0ej1HjhzpkrFtATG/C2MwSDy9TQ633nlJJBPHRHWFiZ3Htwr2t79b2JBxhIXHmnSI6PgdnC6ooso9hMkxyjYPFOeo/dOROb67NYWK+gJC/d15aO54Zev8pG1DU5mO5ORByJVPEtJWI70WXGh+qvzLICGFcFUOYbGxJpkyVG/g5Z0bqarT4xwUQUzvDmb6WJCuPEeNY7eHxRyS3NxcfH19Ww+u1eLkJFfei46O5vTp062eT05OZvLkyZ06jkaj6bILuivHtgXE/M5nw4k8TuZX4emi5a9xEbbz9+kXB94hF0knVIF3CJp+caA2zea46EBOF1SxO62EObG2UXNFnKP2z4XmWKFrYMX2dAAenh6Nq7OCVVkB9n4IgCr2JjQeHb8xPm9+4ZdAwgeoM3aBie+tRqNhfEQgG47nszu1lNhQf5PGsQRKnqMWc0+nTZvGb7/9xvbt25EkiYSEBFavXs2cOXMAuPbaa1mzZg179uyhoaGBTz/9lOLiYmbMmGEpEwSCTiFJEm9ukp3k2yeG4eOu8AdkS9QamLXsAk82hXNnLTPZGYGW9Ui6t5BOYB0+2ZFOeW0DkT08mKe0A1yaDiebEio6k+rbFkZha+FxqDb9WhL1SCwYIbnuuuvQ6XT861//orCwkJCQEJ5//nmmTp0KwIQJE1i6dCnPP/88+fn5REVFsWLFivOiKgKBtdhyqpCjORW4OWm4M07BlucXwtO4jKKiVbaNVy+4YjkMnmvW8OMi/NGoVaQX15BTVktvX7f2XyQQmEB5TQMf7pAbVj48vb/yDSsTPwTJABFToccA88byCICgwVCQJFdtHTzPpGHimvraJKSXoGvQ20bpAStjlkNy8uTJVr/feuut3HrrrRfcf968ecybZ9qbJRBYEkmSeLOpbPUt40Px91Cw5fmFOPqD/DPmOvSxt6D//nac60rhin/D4KvMHt7L1YlhfXw4kFnGzuQirh9tI8XgBA7Hiu2pVOoaGRjsxeyYXsoaU18N+z+Xt01J9W2LsEmyQ5JuukMS2cOTnt4u5FfUsS+jtLlgWnfCNqT1AoGV2ZVSzP7MMly0av422QajI/pGOLZK3h52PYTHUdarSW+VtsVihxHLNoKupqS6nk92pgFydEStdHTk8PegKwe/cIi2kGQgvGnZxoy+NnJ9IPl67K71SIRDIuiWGJt63TQ2lCAvV4WtaYO0rVBdCO4BEDEFgIrAUfJzKZssdpiJxnXrlOJuX7Za0DW8vzWF6no9Q3t7c/kQ0+p0WIzzuvpaaFnEqCPJPwY1plc/jmtySLqrjkQ4JIJuR0JaCfFpJThr1NxzqQ1GRwCONC3XDL4aNLLYtjIwFkmlgZIUKM2wyGFGhvrholVTWFnH6YIqi4wpEBgpqNTx2e50AB6d0R+VgvU1AEjfLi+tOLlD7M2WG9czCAL7AxJk7jZ5GGOE5EhOOWU19RYyzn4QDomg22HMrLl2dB96+digkLOhFo6vkbdjrmt+2ODkCX1Gy7+kbrbIoVydNIwJl1MMu+tdmaDreHdLCroGA7F9fZk6IEhpc1p39XXztezYzWXkTe9r09PbleggTyQJdqd0v27cwiERdCsOZJay/XQRGrWKxZdGKm1O25z+E+orwbsP9B3X6ikpQs5a65Jlm+Tu9wEo6DrOlNfyVbzcgPWxmTYQHSnLtFyqb1sYWziY4ZAA3VpHIhwSQbfC2LPmmhG96evvrrA1F8C4XBOzANStL1GpSU9C6laTGuu1hVHYGp9aTKPeYJExBYK3NydT32hgbLh/szZCUZpTfadA0EDLj290SPKOQG2ZycMY/1a7RIREIHBcjuaUs/FEAWqV3GXUJtGVw6k/5O2h157/fMhIcPEBXRnkHrTIIYf29sHbVUtlXSNHcsotMqage5NdWsN3iVkAPGoL0ZH6Gtj3mbxtqVTfc/EKBv9IZB3JHpOHMdYHSiuqJru0c73e7B3hkAi6DcboyJzhIfQL9FDYmgtwYi3o6yBwAATHnP+8WgsRTem/Flq20ahVTIiUl226412ZwPK8uTGZBr3ExMgAxkcEKG0OHPleduJ9wyB6Ztcdpzn91/RlGy9XJ2L7+gKwq5stowqHRNAtOJlXybpjeahUcL+tRkcAjqyUf8ZcCxe6q+wCHcmkbp5uKLAc6cXV/LA/G5C1I4ojSRDfBam+bRFm1JGYXo8Euq+ORDgkgm7BW5vl6MgVQ4OJ7umlsDUXoKpA1oYADF1w4f0ip8k/sxOgrtIih57YpCPZm1GKrsEy2hRB9+TNTSnoDRKX9u/BqDDlmsQ1k74DCo7Jqb4jbunaYxkjJGcOga7C5GFa1iMxGLpPfSDhkAgcnpTCKn49LHfNvX9qtMLWXIRjP4Okl3UiARfJAPLvB379wNBotqLfSGQPD3p6u1DfaGBfRqlFxhR0H/QGiT2pxfxysppfDsrX2qMzbCA6ApBgTPW90fKpvufi00deFpL0kBVv8jCxfX1xd9ZQXF3PyXzL3HTYA8IhETg872xOQZJg+qAgBod4K23OhWnRu6ZdjFESCy3bqFSq5myb7hYmFpjHuqNniFu+iZs/SuTzw5VIgItWzZnyWqVNk1N9T6yVt7si1bctwi+Rf5pxs+CsVTOuX/erDyQcEoFDk1lcw88HcwB4YJoNR0dKM5ruqFQw5Jr294806kgsUyANYGKU6Gsj6Bzrjp5h8Zf7OVOua/V4XaOBxV/uZ93RMwpZ1kTiR3Kqb79LIWiQdY5pgb420D11JMIhETg0725NRm+QmNy/B8OblOs2ydEf5Z/9LgHvDnRDDb8EVBooPi3fBVqASU0F0o7klFNe22CRMQWOi94g8cKaJC6mcHhhTRJ6pTQQDbWw35jqe4/1jmus2Jp7QO4sbCJGhyQ+tYT6xu5RH0g4JAKHJaeslh/2yWr/B6fZcGYNnHVI2qo90hZuvmfLyFsoStLLx42IQA8MEuxJ7V7phoLOk5BWcl5kpCUScKZcR0Ka6c3mzOLISqgtBd9Q6D/Lesf1CwOfvrLGywwdyYCeXgR6OlPboOdAZvfQdQmHROCwvL81hQa9xISIAEaH24Da/0IUHIf8o6B2gsFzO/66LiwjL5ZtBO1RUHlhZ8SU/SyKJJ3tWzPmb12b6tsWzX1tTF+2UatVzdlv3UVHIhwSgUNSUKHj26ZKkQ9cZuPREWOp+OgZ4ObX8dcZha1plisj35xuKAqkCdohyMvVovtZlIxdspPv5A4jb7X+8S2kI4nrZjoS4ZAIHJIPtqVS32hgVJgfE2yhUuSFkKSz2TUXqz3SFr1HgYu3HJY+c9Ai5oyPCEClguSCKvIrFLizFdgNY/v5E+ztcsHnVUAvH1fG9lMgOhn/nvxz2A2dc/IthTFCkr1XLltvIpOiZYfkUHY5FTrH13UJh0TgcBRX1TV3GX1gWpTyfTQuRs4+KE0HJw8YcEXnXqvRQj/LlpH3dXdmaIgPALtSusddmcA0NGpVc2bWuRivuKVzBqNRW/n6K8uCE7/K29ZK9T0X/wjwCgFDA2QnmjxMb183+gV6oDdIxKcqpMWxIsIhETgcH+5Io7ZBz7A+Plzav4fS5lwcY6n4gVeCswn9dZrTf7dYzCSjjmRnN+ujIegcxVV1rD+WD4CPm1Or54J9XHn3lpHMGtqBjDFLs9eY6jsZeg62/vFBbvtgsfRf4/Xo+DcIWqUNEAgsSVlNPZ/vSgfkuiM2HR0x6OHoT/J2R4qhtYVRR5IVL5eRdzG/LP6kyEDe35rKruQiJEmy7b+hQDFe33CKyrpGhoR4s+reSSSmFZF49BRjhvZnfGQP60dGQE713fepvD3Wiqm+bRE2Sb7hMLOvTVxUIF/uyewWOhIRIRE4FB/vTKe6Xs+gXt5MHxSktDkXJ20bVBfIa9zGjJnO4h8BfuFyaNjMDz4jY8L9cdaoyS3XkVZkeh0FgeNyKr+Sr5uWRZ+9ajDOWjXjIwK4JNSN8REByjgjIAvEa0vBJ7TzS6CWJryp0V52IjSYrseaEBHYrOvKu0iatSMgHBKBw1Cpa+DTnWmAHWhH4KyYdfDVoHU2fRwLl5F3c9YwItQXENk2grb519rjGCS4fEhPxtuKaLxlqu/Yu6yf6nsuAVHgEQT6OlkrZiI+7k4M6y3ruhx92UY4JAKH4Ys9mVToGokK8mTWkGClzbk4jXWQtEbejulgMbQLYYyupFqujPwkUUZecAE2nyxg26lCnDQqnrrCSuXYO0Lmbsg/Alo3GKFAqu+5tNSRmNkEc1JU96hHIhwSgV1j7DK6Ma2G97elAnD/1CjUSoWMO8rp9VBXLivxQyeaN1a/yaBSQ9EpOcPAAhiFdLtTi7tV+3PBxWnQG3hp7XEAFk4MJzzQBCF2V9Gc6ns9uNtIIUTjsk2GeQ5Jy3okkuS416NwSAR2S8suo+/sraCqTo9GrcJJY+POCLSoPTIf1GZehm6+0LupjLyFoiTD+vji4ayhrKaBpDMVFhlTYP98k5BJckEV/h7O3G9LzSrLs+F4U6qvNfvWtEdYk0OSlQiN9SYPMzLMDxetmoLKOlIKqyxknO0hHBKBXXKhLqN6g8T9Xx9QvsvoxairhJO/y9umZteci4W7/zpp1M3aAEcPEws6RnlNA6+vPwXAI9Ojz0v1VZTEj0DSy00new5R2pqz9BgA7oHQWAu5+00extVJ01xgbsdpx70ehUMisDtsvstoe5z4DRp1suit13DLjGkUtqZutlgZ+YmijLygBW9uOk1pTQPRQZ7cNDZUaXPO0jLV15aiIyDrSMKalmQtpCPZ4cD1gYRDIrA7bL7LaHsYi6HFXCd/YFmCVmXkD1lkSKOOJDGt+7Q/F7RNWlE1n+1OB+CZ2YPQamzoq+Poj1BbIqf69lc41bctmnUklulrsye1mEa9Y16PNnRWCQQdw6a7jLZHddHZ9NyhZmbXtETjZPEy8t2x/bmgbV7+7TgNeolL+/dgygAbqu8jSWfFrGPulNsp2BrGvjaZ8aA3vR/N4F7e+Lo7UVXXyKHscgsZZ1sIh0Rgd9h0l9H2SPpZXuvuNRwCLdyFOGKK/DN1i0WGU6lUTIgUyzbdnV0pRaxPykejVvGP2TaU5guQuQfymlJ9R96mtDVtEzRYLn7YUA25B00eRq1WMSnSsdN/hUMisDvG9vOnl8+FnQ1Fu4y2x5Ef5Z+WErO2xKgjydwDdZZR4k+KFMLW7ozeIPHir3Ka71/GhhLd0/zWBBalOdX3OttJ9T0XtfpslMTM9N9JLdJ/HRHhkAjsDo1axS3j2xbVKdpltD3KsiBzF6CCIfMtP75/BPiGyWXkzVyvNmL8ADyUVUZVXaNFxhTYDz/sy+L4mQq8XLU8MqO/0ua0pjwHjjcVF1S6b017GB0SC/S1ATiQWUq1A16PwiER2B0Gg8SfSQUAuDm1Lg+taJfR9jjW1EgvbBL49Lb8+CqVxdN/+/q709ffjUaDREKaWLbpTlTVNfLvP+Q034cui8bfw4z2Bl3B3qZU37A4CB6qtDUXx1ixNXMP6E13JEID5OuxQS+RkG6jon0zEA6JwO5YfSiXQ1lleDhr2PT4pXx15xgeHufDV3eOYceSabbpjECL7JoFXXcMC/e1AVqsWwuHpDvx7pZkiqrqCA9w57YJ4Uqb05oGne2m+rZFz6Hg4gP1lZB32Kyhmq9HB6xHIhwSgV1RW69n+boTANw7NYpePm620WW0PQpPyuI7tVZuptdVNJeRPylXr7QAE7tJHw3BWbJLa1ixXW5U+dSVg3DW2thXxdEfoaYYfPrCgCuVtqZ91BoImyBvm7mc6sg6Ehs7ywSCi7NieypnynX09nXjzrh+SpvTcY40lYqPvKxrxXdufnJNErDYss3EJmHribxKiqrqLDKmwLZZvu4k9Y0Gxkf4M3NwT6XNaY09pPq2RZhlGu21vB4LKx3rehQOicBuyK/Q8e6WFACWXDEQVyeF24t3FEk627umK7JrzsXC3X8DPV0YGCxnV+wW6b8Oz76MUtYcykWlgmevGozKUsX7LEVWvLzsoXWFkbcrbU3HMepIMnabVU05wNOFwb28ATkl25EQDonAbvj3HyepbdAzMtSXOcNsVCfSFrkHoCRVrpUwwAqVJJt1JJvBYJmKjsYwsaN9AApaYzBIvPhrEgDXjerDkBAfhS1qA2N0JMaGU33bIng4OHvJXb7zj5o1VFy0Yy6jCodEYBcczSnnx/2yJuK5OUNs767tYhiXawZeCS6eXX+8PqPlD77aEsizbBl5IWx1bNYczuVgVhnuzhoenzlAaXPOpzwHklbL2/YgZm2JRguh4+VtM9N/m3Ukp4uQJBvt2WUCwiER2DySJPHPX5OQJLg6NoTYvr5Km9RxDPqz6b6WLBV/MTRO0O8SedtCOpKx/QLQqlVkltSQVVJjkTEFtkVtvZ7lvzcJxqdEEuRtg5WO937clOo7CYJjlLam8zQv25jnkIwJ98NZoya3XEd6seNcj8IhEdg8fxzLIyGtBFcnNU/OGqi0OZ0jYydUngFXX4iabr3jWjj919NFy/AmR9DRwsQCmQ+3p5LbJBi/65IIpc05H3tL9W2LsBaN9sxYTnV31jIyzBdwrGwb4ZAIbJq6Rj0v/ybftd19SQQhvm4KW9RJjMs1g+eC1oqFpVqWka+vtsiQzWXkhbDV4civ0PFOk2D8yVkDbFMwfuwnqCkC7z4wYLbS1phGSCw4echduQuPmzWUsWqrI9UjEQ6JwKb5dGc6mSU1BHm5cM+lkUqb0zka6yHpF3nbGtk1LfGPAN9QuYy8mevVRoz1SHanONa6teCsYHxEqC9zh4cobc75SBLEvy9v21Oq77lonKDvWHnbzPTflkJzvcExrkeTHZKSkhJmzJhBfHx882MnTpzg9ttvZ8SIEUycOJFXXnmFxsazZXJXrVrFjBkziI2NZf78+Rw4cMA86wUOTVFVHW9tSgbgicsH4OFiZx9CKRtBVwaewWdrEFgLlcri6b8jQn1xdVJTVFXPyfxKi4wpUJ6WgnGbTPMFyEqAMwftL9W3LcKblm3MdEhievvg5aqlQtfIsdxyCximPCY5JPv27eOGG24gMzOz+bGSkhIWLlzIxIkTSUhI4Pvvv2fLli189tlnAMTHx/Piiy+ybNkyEhMTmTt3LosXL6a2ttYyMxE4HK+vP0VlXSNDe3uzYGQfpc3pPMZS8UPny5UarY2FdSQuWg1j+4lsG0eipWB87vAQRob6KW1S2yQ0RUdirgWPAGVtMRejQ5KxS478mIhWo2ZChPy3cBQdSadvOVetWsUbb7zBE088wSOPPNL8+M8//0x4eDj33COLjfr06cPHH3/c7G2vXLmS2bNnM2qUXEVy4cKFfPfdd/z2228sWNDx3h56vekFZdobsyvGtgXscX4n8yv5JkF2eJ+5YiCSZOBC5tvk/OqrUJ/8HRWgHzKfCxrfQUyaY1gcapUaVeEJ9KWZ4G1+Q78JEf5sO1XIztOFLJzQdsdlU7DJ99CC2Or8jIJxF62aJ2ZGm2Vfl82x8gzqpF/ka2n038y+lkzFYvMLHo5a64aqpgh9fhL0MF2oPzHSnz+T8tlxuoh7LjGvcnVXnqMdHbPTDklcXBxz5sxBq9W2ckgOHz5M//79ee6559i4cSNubm4sWLCg2UFJTk4+z/GIiorixIkTnTr+kSNHOmuyTYxtC9jL/CRJ4sXtpRgkGNfbBefyTA4ezGz3dbY0P7/sjUQ01KBzD+FYvgoKDlpk3M7OcaBPfzzKTpC19QuK+84y+/iBjQ2ArCPZt/+AxXsH2dJ72BXY0vwa9BIv/CHfWc+JdqMg/SQFFhjX0nPsdeITQgyNVPrHcCpPD3kHLTp+Z7HE/KJ9B+JddIDsnd9RFD7P5HH8G2RJRGJaMfH7DuCiMf96VPIc7bRD0qNHjzYfLy8vZ8OGDTz//PM8++yzpKSksGjRIpydnbnzzjuprq7Gza11hoSrqys1NZ3LoY6JiUGjsWz4W6/Xc+TIkS4Z2xawt/ltPlnIofx8nDUqXrlhHGEB7hfd3xbnpz6xHADnUX8hdsQIs8czdY6q0tmw4wShDSn0jY01245hBomXdm6irLYBVWA4sRYK8dvie2hJbHF+K7ankV+dT5CXC89dN8FsjVaXzLGxDvXG3wFwn/oosYNjLTOuCVhyfqqKy2HrAfrqM+ljxnU5XJJ4efdW8sp1NPr0ZVyT0NUUuvIcNY7dHhZTCTo7OxMTE8O118rFnwYOHMgtt9zC77//zp133ombmxs6na7Va3Q6HX5+nftA02g0XXZBd+XYtoA9zK9Bb+CVpuJMCyf1IyLIq8OvtZn51ZTIglZAPex6sKBNnZ5j9HTY8R/UaVtkoavavMQ6jQYmRAbw+9E89qSWMqaf6R+AbY9vI+9hF2Er8yuuquPtzXKa7+OXD8Db3cViY1t0jkd+aUr17Y1m8FyLXkumYpH59bsEti5DnbFTvibNEBLHRQXyw75sdqWWMnmA+Y0QlTxHLZb2GxkZSX19favHDAZDc3pgdHQ0p0+fbvV8cnIy0dHRljJB4AB8HZ9JSmE1/h7O3D8tSmlzTCPpFzA0ypUkeyhcfrvPGHD2lFu151smFGtM/90p+trYLa9vkAXjQ0K8udZWBeP22tW3I/QeDRoXqC6A4mSzhmquR+IAwlaLOSQLFizg1KlTrFixAr1ez8mTJ/nyyy+ZN09eH7v22mtZs2YNe/bsoaGhgU8//ZTi4mJmzJhhKRMEdk55TQOvbzgFwKMz+uPt6qSwRSZiLIZmrVLxF0PjBOHGMvKWybYxFkjbn1FGbb1tiTQF7XMqv5Kv42VN1rNXDUZtYR2QxchOlFN9NS4wcqHS1lgWJ1f5ZgHMTv+d2NRn6mhuOaXV9e3sbdtYNELy5ZdfsmXLFsaPH89dd93FjTfeyK233grAhAkTWLp0Kc8//zxjx45l7dq1rFixAl9fX0uZILBz3th0mrKaBvr39OTGMX2VNsc0KnLP9qkY2vHssS7Fwum//QI96OXjSr3eQGJ6iUXGFFiPf609jkGCy4f0ZHyEDafQGguhxVxn/6m+bWGhvjZBXq4M6OmFJMHuVPtOxzcrBnby5MlWvw8fPpyvvvrqgvvPmzevOWIiELQkraiaz3enA/CP2YPRauy0iPDRnwAJQieAr404Va3KyNeA88VFwu2hUqmYGBnIj/uz2ZlSxOT+bQvdBbbH5pMFbDtViJNGxVNXDFLanAtTcQaSfpa3x92tqCldhrFYYvpOeXnKDB3JpKhATuZXsiO5iCtjelnIQOtjp5/6Akfj5d+O06CXmDqgh31/wRmLocXYwHKNkYBI8OkL+nq5GJMFmNQUJt4lCqTZDQ16Ay+tlfunLJwYTnigh8IWXYR9n8g6rNAJ0Gu40tZ0DX3GgNoJKnOhNM2soYzXo73rSIRDIlCcXclFrE/KR6NW8cxsG75ra4+iZHnNW6WBwVcrbc1ZVCqIbCojbykdSZOQ7mhuOWU19r1u3V34Oj6T5IKqJsG4DScTNNbB3o/lbXvt6tsRnN2ht1wo1Nx+U+MiAtCoVWQU15BV0rlSGraEcEgEiqI3yKWrAW4ZF0pUJ9J8bY6jTWLWyGngYdl0WLOxsI6kp7crUUGeSBLssfN16+5AS8H4I9Oj8XGzYcH4sZ+huhC8QmDgVUpb07UYdSRmCls9XbSM6OsL2HeURDgkAkVZuTeLE3mVeLtqeXh6f6XNMR1JOptdY0vLNUb6XQqo5JbnFWcsMqQx20b0tbF9jILx6CBPbhpruZL/FkeSIP5deXvMnXKWmCMTZhlhK5yNWtpzXxvhkAgUo6qukf/7U75re/CyaPw8nBW2yAzOHILi03I30oGzlbbmfNz9IaSpYqyFuv+KeiT2QSvB+FU2LhjP3gu5B+RU31ELlbam6+k7DtRaKM+C0gyzhoqLlq/HXSnFGAymN+1TEhs+MwWOzjubkymqqqNfoAe3TQhX2hzzMC7X9J8FLja67GThZZvxEQGoVZBaWE1eua79FwgUwSgYnzKgB5faumC8VVdfG1v27ApcPM/eKJgZJYnt64uHs4aS6nqO51VYwDjrIxwSgSJkldTw4Q5ZWf7UFQNx1trxqWgwNKX7YpvLNUaaHZLNss1m4uPmRExvH8C+160dmV0pZwXj/7B1wXhlHhxbJW+PddBU37Zomf5rBk4aNeMi7Dvbxo6/BQT2zPJ1J6hvNDAhIoAZg83vv6AombuhIgdcfCDKhisP9xkDTh5yb5D8oxYZcqIDla12NPQGiRd/ldN8b7YHwfjeplTfvuMhJFZpa6xHeJz8M8M8YSu01JHYp65LOCQCq7Mvo4RfD59BpYJ/XDUIlRkFgWwCY+2RQXPkktC2itZZbuoFFiwjf1ZHYuxbJbANftiXxfEzFXjZg2C8sb5Fqm83io6ArCNRqaE0HcqzzRrK2NcmIa2Yukb7a+sgHBKBVTEYJP7ZdNd2/ai+DAnxUdgiM2msP1tR0paXa4xYWEcyOtwPZ62a/Io6UgqrLTKmwHyq6hr59x+yYPyhy6Lxt3XBeNLPcqM5r14waK7S1lgXV++zxd/MXLbp39OTQE8XdA0G9meUmW+blREOicCqrD6Uy6GsMjycNTx2uY3ftXWE1M1QWwoeQdBvstLWtM+5ZeTNxNVJw6hQP0DWKwhsg3e3yILx8AB3+xCMt+rq6+Cpvm1hoWUblUpFnLGKsh1ej8IhEViN2no9y9edAODeqVEEednw8kZHae7sOx/UGmVt6QgBUeDdB/R1kGmZMvLGdEOhI7ENsktrWLG9STB+5SDbF4xn74WcfaBxdryuvh0lrMkhMTNCAvZdj8TGz1SBI/HBtlTOlOvo7evGnXH9lDbHfOpr4MRaeXuoHSzXwDll5C1Uj6SpQNrulGL0dlr/wJFYvu4k9Y0Gxkf4M9MeBOPGrr5DrwVPG09L7ipCxwMqKEmRs43MwOiQHMoqo0LXYAHjrIdwSARWIa9cx3tbUwD4+xUDcXWyg2hCe5z6HRqqwTcM+oxW2pqOY2EdSUxvH7xctFToGjmWW26RMQWmsS+jhDWHclGp4NmrBtu+YLwy/2yqb3cTs7bEzReCY+RtM8vIh/i6EdHDA4MEe1LsK9tGOCQCq/DvP05S26BnVJgfVw2z3/bYrTjyo/wz5lqzWodbnYgpgAoKksy+GwPQtqp/YF8fgI5ES8H4daP62IdgfN8nYGiQM02MBcK6K806EvOXbeLsNB1fOCSCLudIdjk/7pfT2ezirq0j1JbC6T/l7ZjrlLWls7j7n63zYKFlm0l2LKRzFIyCcXdnDY/PHKC0Oe3TMtW3OxVCuxBhlmm0B/arIxEOiaBLkSSJF5u6+V4dG0JsU0dKu+f4GvnOLmgIBNl4Bcy2sPCyjfEDMDG9BF2D/dU/sHdaCcanRBLkbQeC8aRfoCpfTvUdPE9pa5QnbKL8s+gUVBWYNZSxrUNKYTVnymstYJx1EA6JoEtZdzSPhPQSXJ3UPDlroNLmWA5jMTR7qD3SFkaHJHWLRcrIRwd50sOrqf5BZqnZ4wk6x4rtZwXjd10SobQ5HcOY6jv6r90z1fdc3P2h51B528xlGx83J4b18QXsaxlVOCSCLqOuUc8rv8t3bXdfEkGIr5vCFlmIyjxI2y5vD12grC2m0mesXEa+ugAKjpk9nEqlas622WVHH4COQH6Fjne3yILxJfYiGM/eBzl75VTf7tDVt6NYqK8N2KeORDgkgi7j053pZJbUEOTlwj2XRiptjuU4+hMgyUI8vzClrTENrfNZEV0XlJEXWA+jYHxkqC9z7EUwbuzqO3QBeAYpa4stEd7kkFhA2NpSR2IvbR2EQyLoEoqq6nhrUzIAT1w+AA8XrcIWWZCjxmJodrpcY8TCOpKJTcLWw9nlVNpZ/QN75WiOHQrGK/PPdscWYtbWGCMkBUlQbV6kcWSYL65Oagor6zhdUGUB47oe4ZAIuoTX15+isq6Rob29WTCyj9LmWI7iFLmqpEoNQ65W2hrzMDokGbuhwXzhWx8/d8ID3NEbJOJTS8weT3BxJEnin78mIUkwLzaEEU0l/G2efZ/KgvA+Y6H3SKWtsS08AqFHk9bOzErKLloNY8L9Adhx2j6ilsIhEVick3mVfJOQCcCzswejVtvBXVtHMd7ZRUyx/1BzYDR495bLyGdYpoz8xCixbGMt/jiWR0JaCS5aOxKMt+rqe4+yttgqFkz/tTcdiXBIBBZFkiT+tTYJgwRXDA1uLpjlEEjS2ewae1+ugXPKyFtWRyKErV1LXaOel39rEoxPjqC3vQjGj6+GqjzwDO5+XX07Srjl+9rsSS2mQW9+Nl1XIxwSgUXZfLKA7aeLcNaoeeoKO6zPcTHyj0LRSdC4wKCrlLbGMrRM/7UAE5oybU7mV1JYWWeRMQXn89mus4LxRfYkGG+Z6qt1VtYWW8UYIck/KhdgNIPBvbzxc3eiul7Poawy823rYoRDIrAYDXoD/1orl66+Y1I4oQHuCltkYYydffvPBFc7KMvdEfpNAVTyh58Fysj7ezgzuJc3IKq2dhXFVXW8uVEWjD9uT4LxnH2QnQhqJxh9h9LW2C5ePSEgGpBkfZcZqNWq5mVUe6jaKhwSgcX4ak8GqYXVBHg4c9+0KKXNsSwGAxw19q6xs1LxF8MjAHoNl7ctFCVpLiMvlm26hNeaBONDQry51p4E4/EfyD+Hzrd//VVXY8H0X3vSkQiHRGARymsa+O/G0wA8MqM/3q4OVnkxOwHKs8DZC6JnKm2NZbF4+q/91T+wF1oJxq+yI8F4VQEcaxKECzFr+4QZdSSWE7YeyCyjqq7R7PG6EuGQCCzC/zaepqymgf49PblxTF+lzbE8RjHroDngZCcCwo7S7JBsloW7ZjI23B+tWkVOWS2ZJTVmjyeQaSkYv3xIT8bbk2B836egr4feo6H3KKWtsX2MEZK8w6ArN2uovv7uhPq702iQSEiz7ailcEgEZpNaWMXnu9MB+MfswWg1DnZa6Rvg2M/ydoydloq/GH3HgpO7XEY+3/wy8h4uWkaE+gL21UfD1tlyspDtp4tw0qh4+ko7EozrGyDxI3l73CJlbbEXvEPArx9IBsjcY/Zwk5qXbWz7enSwbw6BErz82wkaDRJTB/Rgcv8eSptjeVK3Qk0RuAc2iUAdDK2LxcvITxRl5C2KLBiXu2bfMakfYQEeClvUCZJ+aUr17Sm6+naGcMsv29i6jkQ4JAKz2JVcxIbj+WjUKp6ZbUd3bZ3BWCp+yDWgsZOMhs7SnP672SLDxUXLH4C7U4oxGISOxFy+js8kpbAafw9n7rc3wXhCk5hVpPp2DqNDYgFh64TIAFQqOJFXSUGlzuzxugrhkAhMRm+QS1cD3DIulKggL4Ut6gIaauH4GnnbkbJrziWiqUBaxi6LlJEf3scXd2cNJdX1nMirNHu87kx5TQOvbzgF2KFgPPcAZMXLqb6jRKpvpzDWI8k9CHXmXUP+Hs4MCZHT8Xen2O6yjXBIBCazcm8WJ/Iq8XbV8vD0/kqb0zWc+gPqq8AnVNZaOCo9BoBXCDTqINO82gcAzlo1Y/vJfTREPRLzeGPTWcH4TfYmGDem+g65Rq6vIeg4vn3BNxQkvezUmUlz918b7msjHBKBSVTqGvi/P+W7tgcvi8bPw0FDscbsmpgFcql1R0Wlsnj6r7GMvK2vW9syaUXVzYLxZ+xNMF5VeHa5U4hZTSPMcmXkW+pIbDUd347OboEt8c6WFIqq6ugX6MFtE8KVNqdrqC2D0+vlbUfoXdMezX1ttlhkuIlNBdIS0krsoo+GLfLyb8dp0EtMGdCDS+1NMN6c6jsK+ohUX5MIt1yjvTHh/jhr1eSW60grqjZ7vK5AOCSCTpNVUsNHO9IAePrKQThrHfQ0OvGr3Am3xyDoOURpa7qeiCnyz/wjUJlv9nCDgr3x93C2mz4atsaulCLWJ8mC8X/Ym2Bc3wB7Raqv2TTrSPZDvXlOhKuThtFhfoDtRi0d9JtE0JUsW3eC+kYDEyMDmD7IgUtAG3vXOPpyjRGPQIuWkVerVUxoKt5lD300bAm9QeLFX+W+UDfbo2D8+GqoPAMeQTD4aqWtsV/8wsG7DxgaISvB7OEm2XhfG+GQCDrF3vQS1h4+g0olF0FTOeoXdWU+pG2Vt4c6YDG0C2Hh9N+Joq+NSfywL4vjZyrwslfBeLxI9bUIKlWX9LXZlVKM3gbT8YVDIugwBoPEi01pvjeM7svgpjQyhyTpZ7lKYu/R4B+htDXWw5j+m7LJImXkjcLWA1ml1NTbdh8NW6GqrpF//yELxh+6LBp/exOMnzkEWXtEV19LYVy2sYCwdWhvH7xdtVTqGjmSY15J+q5AOCSCDvPLoRwOZZfj4azh0Zl2eNfWGZqXa7qBmLUloeNB6wZV+VCQZPZwYQHu9PZ1o0EvkZBWYgEDHZ93NidTVFVHeIC7XQrGVYnGVN+rwStYUVscAmOBtJy9ZtcI0qhVTIiUo5a2qCMRDomgQ9TW63l13UkA7p0aRZCXq8IWdSGl6XJ3X5Varp/QnbBwGXmVSsUk47KNDRdkshWySmr4sEkw/pQdCsa1dWWojhq7+goxq0XwjwDPYDljKXuv2cPF2XA9Evs62wWK8cG2VM6U6+jt68adcf2UNqdrOfqj/DP8ku55h9ey+68FmGQnfTRsgeVNgvEJEQHMHGxHhcQMekjfQd+jb6DS10GvEdBntNJWOQYtdSQWSP81Xo/7MkqprdebPZ4lEQ6JoF3yynW8tzUFgL9fMRBXJ43CFnUxzcs1Dlwq/mIY65Fk7IQG8/teGEPESWcqKK2uN3s8R2VfRgm/GgXjVw2yH8F40mr471A0X8zFP3eL/Fhpuvy4wDJYsK9Nv0APQnxcqdcbSEy3rWVUkx2SkpISZsyYQXz8+SVtCwoKmDhxIj/99FOrx1etWsWMGTOIjY1l/vz5HDhwwNTDC6zIv/84SW2DnlFhflw1rJfS5nQt+cdk7YTGGQbNUdoaZegxELx6WayMfJCXK/17eiJJsDtVLNu0hcEg8c+mNN/rR/VlSIiPwhZ1kKTV8P1tUJHb+nFdmfy4cEosg7Fia3YiNNaZNZS8jGqbUUuTHJJ9+/Zxww03kJmZed5zBoOBxx9/nNLS0laPx8fH8+KLL7Js2TISExOZO3cuixcvprbW/EZegq7jSHY5P+7PBuDZqxw4zdeIMToSPRPcfBU1RTFalpG3VPqvKCN/UVYfyuVQVhkezhoeu9xOBOMGPaxbArSVjdX02Lq/y/sJzCMwWq7p0qiDnH1mD2fsxm1r9Ug63Ut91apVvPHGGzzxxBM88sgj5z3/9ttvExwcTK9ere+kV65cyezZsxk1Si4hvHDhQr777jt+++03FizoeJ0Hvd7yJ7dxzK4Y2xYwdX6SJPHPX48BMG94L2JCvGzyb2Sx90+SUB/9ARVgGHwNkg3N1drnqCr8UtQHv0JK3oRh2lKzx5sQ4c+nu9LZmVzU5hy68zVYW69n2boTACy6NIIAdyf7+Duk70BzbmSkFRJU5KBP23F2ycGOUfocVYVOQH38Fwxp25H6jDNrrPH95Iqtx3IrKKyoxd/DuUvn19ExO+2QxMXFMWfOHLRa7XkOyZ49e1i7di0//vgjc+a0DncnJyef53hERUVx4sSJTh3/yJEjnTXZJsa2BTo7v93ZOhLTy3DWwJV9Gjl48GDXGGYhzH3/PEqOMbAsE73GjUO1vZBscL7WOke1dQEMB1T5Rzgav4lGF3+zxnNrMKAG0otrWL9rHz3c29YhdcdrcGVSFXnlOgLd1YzyqrD568yIX048HanQk3EsntIyzy63x1oodY720IQRClQd/YPTXtPNHi/UR0tmeSPfbNrHpL5uzY8reQ122iHp0aPtBk/FxcU8/fTTvPHGG3h4eJz3fHV1NW5ubq0ec3V1paamplPHj4mJQaOxrKhSr9dz5MiRLhnbFjBlfnUNeh7eICu675kcyfSJ0V1pollY6v1TrftW/jl4DsNHj7eUeRZBiXNUOjwMVd5hYtyLkWKmmT3esH27OZhVTrlLT2bE9mn1XHe9BvMrdPzy83YA/jEnhnH2pNHyrYL97e8WNmQcYeGxXW5OV6P4ORriDEffwKssidiYwbLOzQym5x7n450Z5DR6ERs7tEvnZxy7PTrtkLSFJEk8+eST3HrrrQwdOrTNfdzc3NDpWiv2dTodfn5+nTqWRqPpspOhK8e2BTozv893pJNVWktPbxcWT42yi7+LWe+fvhGSVgGgHnY92Oh8rXqORk6DvMOo07ZC7I1mDzcpKpCDWeXsTi3hhrFhbe7T3a7B1zYkU9ugZ2SoL/Nie9uXRqtfnNz/qPpCOgQVeIeg6RcHasd5TxU7R3sOATd/VLUlaPIOQ6h5yzaXRAfx8c4MdqeWtJqPktegRdJ+z5w5Q0JCAm+//TajR49m9OjR5Obm8sILL3DPPfcAEB0dzenTp1u9Ljk5meho273z7q4UVdXx1qZkAJ64fCDuzhbxW22b9G1QXQhu/me73nZ3IrumjPzOlGIkC4xn7xzNsXPBuL4eVE4XeLJpLrOWOZQzoihqdYu+NubXIxnbzx+tWkVmSQ2ZxZ1bqegqLOKQhISEcOTIEfbu3dv8PyQkhKVLl/L+++8DcO2117JmzRr27NlDQ0MDn376KcXFxcyYMcMSJggsyGvrT1FV10hMbx/mj+ittDnWwZhdM+Qa0FzoQ7ab0ddYRj4PCo6bPdzIMD9ctGoKK+tILqiygIH2iywYT0KSYF5sCCNCOxcptgk2vghVZ8DVV04Tb4l3CFz/OQyeq4hpDosx/dcCfW08XLSMbDrvdqbYRraN1W59J0yYwNKlS3n++efJz88nKiqKFStW4Ovray0TBB3gRF4F3ybI6dzPXjUYtdrO7tpMoUEHx9fI292td83FcHKV78iSN8jpvz0HmzWcq5OGMeH+7EguYmdyEdE9vSxkqP2x7mgeCWkluGjVPDlroNLmdJ6MXbDnHXl7/gqIugx92g4yjsUTNmScwy3T2AzGCElWvLzMrDHvK3xSVCAJ6SXsSC7i+lHK33yaNZuTJ09e8LlNm87vgzFv3jzmzZtnziEFXYgkSby09jgGCa4YGszYfuZlVtgNyeuhrgK8e8tRAcFZIqbKDknKJphwn9nDTYwKkB2SlGIWTnLwFgQXoK5Rzyu/y9mFd0+OoLevWzuvsDHqquDnxYAEI26B/jPlx8PjKC3zlAWswhnpGoKGyBEpXZncVbnPKLOGi4sO4PUNsCu5CINB+WVUUTpe0MzmkwVsP12Es0bNU1cMUtoc63Fkpfxz6AJ5nVZwFmOBtHTLlJE36kj2pBbTqDeYPZ498unOdDJLagjycmHRpZFKm9N5NiyVS8N794HLX1bamu6FWg1hE+VtC+hIhvXxxdNFS2lNA8fzKs0ez1zEp68AgAa9gX+tlXUCd0wKJzTAXWGLrISuAk79IW+L5ZrzCRokdxptrIWsPWYPN7S3D96uWip1jRzNrbCAgfZFa8H4ADxc7EwwnrIZEj+Ut+e9Ba52UuLekQizXKM9J42a8RFyJHynDXTjFg6JAICv9mSQWlhNgIcz902LUtoc63FirVyOObA/BA9T2hrbo2UZeQt0/9WoVYyPkJvtdZcy8nqDxJ7UYrZn1vL0qqNU1jUytLc3C0b2af/FtoSuHH65X94ec9fZLCyBdTHqSDL3WKQsv7GvzS4buB6FQyKgrKae/26UU7IfmdEfb9dulGVytCm7Zui18pev4Hxapv9aAFtt7NUVrDt6hrjlm7j5o0T+G1/OxhOFAMwcHGx/gvE/noaKbPALh+kvKG1N9yV4GLh4y7q3vMNmDxfXdD0mZpRSr1dWRyIcEgH/23iaspoG+vf05MYxfZU2x3pUF5296xfLNRfGWJcl7zBUFZo93KQoOUKyN6MUXYMd9GwxkXVHz7D4y/2cKT9fe/P6+lOsO3pGAatM5NQfcOBLQAVXvwsujlMK3u5QayB0grxtgfTfqCBPeng6o2sw8MPxKvakFqNXSOAqHJJuTkphFV/szgDgH7MHo9V0o1Pi2CqQ9BAyAgLsUFxoLTyDIDhG3k7bavZwkT08CfJyob7RwL6M0vZfYIfoDRIvrElqsw+ukRfWJCn2wd8pakpg9YPy9vh7z4oqBcrRXCDNfIfkj2N5VNU1AvDj8Wpu/iiRuOWbFHGYu9G3j6AtXvntOI0GiakDejC5f9t9ihwWYzG0mOuUtcMeiLDcso1KpWoOEzvaso3BIHEqv5KX1ia1GRkxIgFnynUkpJVYzzhT+X2JXBwvIBoue1ZpawRwtkBaxi4wmJ6tZozi1Ta0HiOvXMfiL/db3SmxM4m3wJLsTC5iw/ECNGoVz8w2r+iV3VGW2ZQ1ooIh85W2xvaJnAa73jhbRt5Mvc3EqEB+OpBjE8p+c2jQGziWW0FiWgnxaSXsyyihtKahw68vqDQ/lbpLSVoNR74HlRqueQ+c7KxmiqPSazg4e8r1SPKPQq/OC/IvFsWTkIv/v7AmiRmDg9FYSe8kHJJuit4g8eKvSQDcOj6MqKButiZ89Ef5Z3gceNtRh1WlCJ0AWleoPAOFJyHIvOqiRh3Jkewyymsb8HS2j2Btbb2eA5mlJKSXkJhewv6MMmrP0cG4OqmJCPQk6Uz7ac1BXq5dZar5VBfBr4/I25Mehj6jFTVH0AKNFvqOg5SN8rKNCQ5JQlpJh6N4EyIDzDC24wiHpJvy/d4sTuRV4uPmxEOXdcMGh0eaHBIhZu0YTq5y/YOUjXKUxEyHpJePGxGBHqQWVROfWsxlA21zubCspp7E9FIS00tISCvhaE45jefoPnzcnBgT7seYcH/G9PNnaIgPGrWKuOWbyCvXtXkHqgKCfVxttxqyJMnOSE2RXB10yt+VtkhwLuFx8vWYvgPGL+70yzsanbNmFE84JN2QSl0D//lTLvv/4GXR+Hk4K2yRlSk4AflHQO0Eg0Tzrw4TOfWsQzLhXrOHmxgVQGpRNbtSbMchyS2rbXY+EtNLOJV/fhPAXj6uzc7H2HB/ooM820zhXTpnMIu/3I8KWjklqhbPWysU3mmO/gjHV4NaC9e8C1oXpS0SnEv4OTqSTlaZ7mh0zppRPOGQdEPe2ZJCUVU9/QI9uHV8mNLmWB9j7ZGo6eBuo3eotkhzGfkd0Fhn9pfUpMhAvtyTqZiwVZIkUgqrSEg7GwHJKas9b7/IHh6M7ecvOyHh/vTxc0PVAQ3NrKG9ePeWkbywprXANdjHlaVzBjNrqI0uFVbmwdrH5O3JT8h6BYHtETICnNyhtgQKT3S6+eXYfv708nG1qSiecEi6GVklNXy0Iw2Ap68chLPWPtbuLYYktciuEcs1nSJoMHj2hKp8udtov8lmDTchMgCVCk4XVFFQ0fVh4Ua9gaQzFSSkyc7H3oxSSqrrW+2jUasYEuLd7HyMCfcjwNN0x2vW0F7MGBzMnpRCEo+eYszQ/oyP7GG7kRFJgjUPyWLJXsPhkseUtkhwITRO0HcspG6RdSSddEg0apXNRfGEQ9LNWLbuBPWNBiZGBjB9UJDS5lifnP1QmibfWQy4Qmlr7AuVSk7/PfytvGxjpkPi6+7MkBBvjuZUsCu1hHDLWNmMrkHPgcwyEpsFqKVU17cWoLpo1YwI9WVs0xLMiFA/PC3cX8ZYLt+1wo3YiADbdUYADn4Np9aBxhmufk/+0hPYLmFxskOSvgPG/q3TL7e1KJ5wSLoRezNKWXv4DCqVXAStI2Fnh8O4XDPgSnD2UNYWeyRy2lmHZPrzZg83KTJQdkhSigk3szZdeU0DezNK5AyYtBKO5JTTcE4pbG9XLaOboh9j+/kT09un+0UJL0R5NqxrEq9OfbrTd9wCBWhZIM3EdHxbiuIJh8TBMTb2SsioYc3mowDcMLovg0O8FbZMAQz6s+m+ohiaaRjLyJ85LKeFegSaNdzEqEDe35bK5pMF9NW6ofMu7vCHYV65rtn5SEwv4WR+JdI5i+E9vV2anY8x4f4M6Ollfz1krIEkyY3z6iqgzxiY+KDSFgk6Qu9Rcjp+dSEUnYIeA0waxlaieMIhcWDWHT1zXihOBYwI9VXMJkVJ3yHrH1x9zwo0BZ3Dqyf0jJGzlFK3mK3DKauRNRwl1Q38N6EBEhLp1Ua4WJIkUouqSUwraa4BklVyvgA1ItCjVQZMX/+OCVC7PXs/htTN8pfb1e/K/VIEto/WRXYg07fLn28mOiS2gnBIHBRjSeBz1dMS8Pcfj+Dj5mS7Kv+u4shK+eeQq0HbzVKdLUnkFNkhSdlslkOy7ugZHv724HmPG8tW//2KgWg1ahLTStibUUJRVWsBqloFg5sEqGPD/Rkd7k8PL5Ge2mlK0uDPppLwly2FwG5Yl8ieCY+THZKMnTDmTqWtMQvhkDggHW3sZc2SwIrTWCfXVQAYKrJrzCJyGux606wy8u2VrQZ45fcTrR531qqJ7XtWgDoy1BcvVyG6NAuDQV6qaaiWC9+NW6S0RYLOEtakI0k3XUdiKwiHxAGxxZLAipO8AXTl4BUiupWaS3MZ+VyT163bO0eNxPb1YeaQYMaG+xPTxwcXrVhKsCgJ70PGDnDygHlvd7q4lsAG6DNazoqqyoOSVLvuXC7OPgfkRAd6aIAdNPayJMbaI0Pni/Vxc3FyO+vUmdj9t6Pn3h2T+nHvlChGh/sLZ8TSFJ2GDc/L2zNfBP9+ipojMBEnN+jd1GcofbuytpiJcEgciFP5lTzy3UFeXJvUof1turGXJamrgpO/y9uiGJpliJgq/zTRIbHFstXdCoMefl4MjTr5vRz9V6UtEphDeItlGztGOCQOwKGsMu7+fC8zX9/GqgM5GCQuWltBhdyPw2Ybe1mak79BYy34R0KvWKWtcQzOLSPfSYxlqy+02t3tzlFrs+sNyE4EF2+Y95Zd6w4EnNWRGOuR2CnCIbFTJElid0oxt34Uz7y3d/JnUj4qFVwxNJg198fxxo2xqOC8D3y7aOxlaYzZNTHXiQ9eS9FzCHgEQUMNZCV0+uXGstUgzlGrk58Em1+Wt2e9Aj59lLVHYD59x8rNQityoDRdaWtMRjgkdoYkSWw8ns+Cd3dx04o9bD9dhEatYsHIPqx/ZDLv3jKKmD4+zSWBg31ah7yDfVx595aR3Sflt7r47LKCWK6xHCqV3P0XTF62EeeoAugb4OdFoK+H/rMg9malLRJYAmcP6D1S3s6w32UbkWVjJ+gNEmuPnOGdzcmcyKsE5GWZG8f05W+XRNDX3/2819hSSWDFSPoZDI1yozBRX8GyRE6Dw981lZFfatIQ4hy1MttfgzOH5OKAc/4nIoaORNgkuell+k4YcYvS1piEcEhsnLpGPav25/De1hTSi2sA8HTRcsv4MP4aF96u6M9WSgIrhrFUvKg9Ynmay8gfkiNRHqalkHf7c9Ra5B6Eba/K27P/A17BipojsDDhk2DHa3Iat50iHBIbpaa+kW8SslixLZW8ptbsvu5O/HVSP26fEI6PuygI1S7l2ZCxC1DB0AVKW+N4eAVDz6GQfxTStoi/sS3TWCdn1RgaYdBc8V45In3HgUoDZZnyf99QpS3qNMIhsTHKaxv4fFc6H+9Mo7SmAZAbhP3tkghuGhuKh4Vbozs0R38CJDmU6dNbaWsck4gpskOSskl8ydkyW5ZBQRK4B8JVr4ulGkfExQtCYiFnn7xsEyscEoGJFFbW8fHONL7YnUFVXSMAof7uLJ4SyfyRvUVRKFM4aiyGJr4ou4zIabD7LUjZYvdlqx2W7L2w87/y9lWvm92hWWDDhMfJDknGDoi9SWlrOo1wSBQmu7SGFdtS+TYxi7pGAwADenpx79RIZsf0QqsRiVAmUXRa1jaotTD4aqWtcVzCJoLGBSqy5b95j/5KWyRoSUMtrFoEkkFOex88V2mLBF1JWBzs/J/dFkgTDolCJBdU8d7WFH4+kEOjQS5kM7yvL/dPjeKygUGohbDPPIyl4iOnmSy2FHQAJzcImwCpW+RlG+GQ2Bab/gXFp8EzGK54VWlrBF1N6HhQqaE0DSpywTtEaYs6hXBIrMzRnHLe2ZLM70fzmgvqTYoK4L4pUUyIDEAlQt7mI0mti6EJupbIaWcdkvGiW6zNkLELdr8tb899A9xF1VuHx9UbgofBmYNylGSYfX3+CYfESiSklfD25mS2nipsfmzG4J7cOyWSEaF+ClrmgJw5CCUpoHWDAVcqbY3jEzkN1j/XVEa+HrTOSlskqKuSs2qQ5JoU/S9X2iKBtQiPkz8DM3YIh0RwFkmS2HqqkLc3J5OYXgqAWgVzh4eweEoUA4K9FLbQQTEu1wy4Alw8lbWlOxDUVEa+ugCyE+QPRIGybFgqlxD37gOXv6y0NXaP3qAnMS+RfWX7aMhrYEyvMWhstWt42CRZaJ5uf/VIhEPSBegNEn8cy+Ptzckcy60AwFmjZsGoPiy6NIKwAA+FLXRgDPqzxdBEqXjroFbL6b9HvpeXbYRDoiypWyDxQ3l73lvg6qOoOfbOhowNLEtYRn5NvvxANvR078nfx/6d6WHTlTWuLcImACooTobKPLsqgCdSOCxIg97Ayr1ZzHh9K/d+tZ9juRW4OWm4K64f256cyivzY4Qz0tVk7ILKM/KHcJQNflg4KsbuvymblbWju6OrgF/ul7dH33m235DAJDZkbODRLY+edUaaKKgp4NEtj7IhY4NCll0ENz8IHipv21lfGxEhsQC6Bj3fJWbxwbZUcspqAfB21bJwUj/umBiOn4dYU7caxtojg+aC1kVZW7oTxi++3ANQUyIElErxx9NQngV+4TDjn0pbY9foDXqWJSxDQjrvOQkJFSqWJyxnat+ptrd8ExYHeUdkYasd1WESDokZVOga+HJPBh/vSKOoqh6AQE8X/nZJP24eH4anqKpqXfT1cOxneVtk11gXr2AIGixXA03dAkPnK21R9+PUH3DgC0AF894R+ikz2V+w/7zISEskJPJq8thfsJ8xwWOsaFkHCJ8E8e+KCEl3oKS6nk92pvHprnQqdXJV1d6+biyaEsl1o/rg6mRj3nJ3IWUz6MrkmgtCx2B9IqfJDknKJuGQWJuaElj9oLw9/l75C0lgFoU1he3v1In9rEroRPln4QmoKgTPHsra00GEQ9IJzpTXsmJbGt8kZFLboAcgKsiTe6dEMmd4CE6iqqqiqI4ZO/vOB1sLoXYHIqfK6v7ULaKMvLX5fQlU5UFANFz2rNLW2D0luhJ+SfmlQ/v2cLfBL3uPgLMRy4ydMORqpS3qEMIh6QDpRdW8tzWFH/dn06CX1xNjevtw39RIZg4OFlVVbQB1Yy2qk7/JvwwV2TWKENpURr48S1b4B0YrbVH34PgaOcNJpYZr3pOr5wpMwiAZ+Dn5Z17b9xrldeXt7h/sHszIoJFWsMwEwiYJh8Te0Bsk9qQWk5hZi867mPGRPdA0ORjHz1TwzpYU1h7Opam6O+P6+XPf1CguiQ4UVVVtAYMe0ncQcvxjVA014BsOvW30A8JE7KYGgrO7XLo6bau8bCMckq6nugjWPCxvT3oI+oxW1Bx7Jrk0mRf3vMj+gv0ADPAbwBX9ruB/+/8H0Ka4dcnYJbZ5LYK8bJ24wq762pjskJSUlHDDDTfwr3/9i3HjxgHwxx9/8M4775CVlYWvry/z58/n3nvvRa2WlzJWrVrFO++8Q2FhIRERETz77LOMGDHCMjMxgXVHz/DCmiTOlOvkB+IT6eXjyi3jw9ifUcrGEwXN+04bGMS9UyIZHS6yB2yGpNWwbgmailx6Gh+rKZLvGB2kiZjd1UCInNbkkGyGcfcobY1jI0nw6yPyOR80GKY8pbRFdkltYy3vH3qfz459RqPUiJvWjfti7+PmQTejVWsJ8w5rfQ02oVFp6O9nw72bwpp0RAXH7CbzzSTRw759+7jhhhvIzMxsfuzo0aM8+eSTPPzww+zdu5cVK1bw008/8emnnwIQHx/Piy++yLJly0hMTGTu3LksXryY2tpai0yks6w7eobFX+4/64w0caZcx7//OMnGEwWoVHDVsF6sfTCOjxeOEc6ILZG0Gr6/TW4g1ZL6KvnxpNXK2GVB7LIGgrEeSfp2uYy8oOs4+iMcXy13tL76XZHmbgLbsrdxzS/X8NHRj2iUGpnWdxq/zPuF24fcjlYt369PD5vOHwv+YMX0FSzqs4gV01cwodcE9JKeVxJeQZLOj5zYBJ49IHCAvJ2xS1lbOkinHZJVq1bx+OOP88gjj7R6PCcnhxtvvJGpU6eiVquJjIxkxowZJCYmArBy5Upmz57NqFGjcHJyYuHChfj5+fHbb79ZZiadQG+QeGFNUhsBuLO4OWn48+HJvPWXkQwJEZUObQqDHtYtgYu9g+v+Lu9np7RXAwFgecJy9LY2x55DwT1QdgyzE5W2xnGpzIO1j8nbk5+AkFhFzbE38qvzeXTLo9y38T5yqnII9gjmjalv8L9p/6OXZ6/z9teoNYwJHsN43/GMCR7D0+OeRqvWsiNnB5uzbLgYoDHbyk7Sfzu9ZBMXF8ecOXPQarWtnJLLL7+cyy8/28BJp9OxZcsW5syZA0BycjILFrQu0BIVFcWJEyc6dXy93vwP4D2pxedFRs6ltkFPQUUtEYHuZh9PaYx/M0v87WyC9B1ozo2MtEKCihz0aTvsNv03MS+xQzUQEs8k2lwNBFXEFNRHf8CQvBGp7/gOvcbhztFzsOj8JAn16gdR6cqQgodjmPgw2MDfzR7eQ71Bz3envuPtQ29T3VCNRqXh5oE3s2jYItyd3C9qe8v59fXsy22DbuPjYx+zPGE543qOw1Xraq1pdBhV3wmo936MlL4DQzvvS1e+fx0ds9MOSY8e7ac4VVVV8dBDD+Hq6srChQsBqK6uxs2ttfrb1dWVmpqaTh3/yJEjndq/LRIzO7ZMlHj0FK4VjqNYt8Tfzhbwy4knogP7ZRyLp7TMPotD7SjpWGOsfSf24ZTn1MXWdA5/bST9gNqjaznhN7tTr3WUc/RCWGJ+AVnrCD/9Bwa1E8cHPIjuyDELWGY5bPU9TK9N59OcT0nXpQMQ4RbBwpCFhGpCOXXsVIfHMc5vnDSOn51+Jrc6l1c2vsI1Pa/pCrPNQqvzZThA3hGOJGxH79x+Q1cl3z+LZ9mkpqby4IMPEhAQwOeff46np/yF4Obmhk7XOiqh0+nw8/Pr1PgxMTFoNOapmnXexRDffjh5zND+xEYEmHUsW0Cv13PkyBGL/O1sAt8q2N/+bmFDxhEWHtvl5liSBn0D3578lu/yv+vQ/qMGjiI2OLZrjeoskT3h4HLcy04SOyBM7q3RDg53jp6DxeZXno36z3fl7SlPMXCS7XwJ2up7WFVfxduH3ua71O8wSAY8nTx5aMRDLIhegFrVcdVCW/N7OvBpHt/2OL8X/85dE++ir1ffrpqGyUj7IlGVpBDjWw39L7ngfl35/hnHbg+LOiRbt27l0Ucf5frrr+exxx5Dqz07fHR0NKdPn261f3JyMpMnT+7UMTQajdl/rPGRPejl40peua5NFYIKCPZxbZUC7AhY4m+nOJIEOe05kyrwDkHTL85uCqRJksTW7K38397/I6MiAwCtSkuj1Njm/ipU9HTvaZspwL59oMcgVIXH0WRshyEd/9J0iHP0Ipg1P0mCtQ9DXSX0Ho160kNgg38rW3kPJUlifcZ6licsp6BWzpi8st+VPDHmCQLdAk0et+X8ZobPZMLpCew+s5t/7/s3b1/2tkVstyjhcVCSgiZzFwxqP2Kp5PtnsdKiBw8e5L777uOpp55iyZIlrZwRgGuvvZY1a9awZ88eGhoa+PTTTykuLmbGjBmWMqHDaNQqls4ZDMjOR0uMvy+dM9ihnBGHQN8Aqx+ATS+2ePAC7+CsZXbjjJwuPc096+/hgU0PkFGRQYBrAP+c+E+WT16OqunfuUhItl0DQXT/tTz7PpHru2hd5QJomm5fRuqCZFdmc9/G+3hs62MU1BYQ6hXK+zPeZ/nk5WY5I+eiUql4atxTaNVatmVvY0vWFouNbTGMOjo7ELZazCF57733aGxs5KWXXmLEiBHN/++66y4AJkyYwNKlS3n++ecZO3Ysa9euZcWKFfj6+lrKhE4xa2gv3r1lJME+rYVIwT6uvHvLSGYNPV9pLVCQ2jL4coHcPEylhiv+Ddd/Ad7nvE/eIXD953ZRh6RUV8q/9vyLa9dcy+4zu3FSO/HXoX/l12t+5Zroa5gZPpPXprxGkHvQea/1d/VnYshEBazuIC0dEltNi7QnStLgj3/I25ctFUXnLkCDoYEPj3zINb9cw/ac7TipnVg0fBE/zfupy66Xfj79uH3w7QAsS1iGrvHiCRNWx1iP5Mwh0FUoa0s7mOVinzx5snn7vffea3f/efPmMW/ePHMOaVFmDe3FjMHB7EkpJPHoKcYM7e9wyzQOQWkGfH293CjKyQOu+wT6N2V0DZyNPm0HGcfiCRsyzi6WaYw6kXcPvUtlfSUAM8Jm8MioR85bg54eNp2pfaeSeCaRfSf2MSR6CC/Fv0ReTR5vHniTJWOXKDGF9gmbCBpnKM+E4hQIjFLaIvvFYIBf7oeGavnLZdwipS2ySfbn7+fFPS+SXJYMwJjgMfxj/D+I8OmIBN487h52N7+m/kpOVQ4fH/2Ye2Pv7fJjdhif3uAXDqXpkBUP0dZflego3b4bnEatYnxEAJeEujE+IkA4I7ZG9l748DLZGfEKgb+uO+uMgOx8hMdR2vsyOTRpw86IJElsy97G/NXzeTXxVSrrKxngN4CPL/+Y16a8dkFBXMsaCJf0voTnJz4PwFfHv+JAwQErzqATGMvIg7zMIDCdhPchY4fsjM97G9Td/mO7FWW6MpbuWsrt624nuSwZPxc/Xo57mY9mfmQVZwTA3cmdJ8c8CcBHRz4iqyLLKsftMGFNyzbp25W1ox3EmS2wXZJ+gU9nQ3UhBMfA3zZCr2FKW2USyaXJLNqwiPs23kd6RTr+rv48P+F5vrvqu07XEZnUexJXR12NhMRzO5+zvRCxEeOyTarQkZhMUTJseEHenvlP8O+nrD02hCRJrE5Zzdyf5/LT6Z8AWBC9gDXXrGFO5Byr9xqbETaD8b3GU2+oZ3nicqseu12MBdJsvK+NcEgEtockwc7/ySXgG3UQfTncsU7Wh9gZZboyXtrzEteuuZZdubtwUjtxx9A7WHvNWhb0X2CyKPXx0Y/Tw60H6RXpvHvoXQtbbSGMDknaNlmQLOgcBj38vBgaayFiCoy+U2mLbIbU8lTu/PNOntnxDKV1pUT5RvH5FZ/z/MTn8XFRprJ2S4Hr1uyttiVwNepIcg9AXZWytlwE4ZAIbAt9A/z6MKx/Tv597D1w0zfgYl8FzhoMDXyZ9CVXrrqSb09+i17Sc1noZfwy7xceHfUons7mzcfHxYd/jJdFjp8d+4xjRbZVHAuAnjGijLw57HoTshPAxRvmvgWiuzh1+jreOvAWC1YvIDEvEVeNKw+PfJjv53zPiCDlGrUaifCJ4LbBtwE2JnD1CwOfUJD0so7ERhEOicB20JXDV9fBvk/lTJpZy+HKV21aF9IW27K3Mf+X+SxPXE5lfSX9/frz0cyP+O/U/9LX23KFk6aFTuOK8CvQS3qe3fUsDbYWhVCr5Tt7EOm/nSU/CTa/JG/PegV8ba/glrXZlbuL+b/M5/3D79NoaOSS3pewat4q7oy5Eye17VQrvmfYPfR070lOVQ6fHP1EaXPOYgd9bYRDIrANyjLho8tlvYGTB9z4NYy3r2yClLKU83Qiz014ju+v+p6xvcZ2yTH/Pu7v+Ln4cbr0NB8e+bBLjmEWzem/QtjaYfQN8PMi0NdD/1kQe7PSFilKUW0RT257knvW30NmZSZBbkG8NuU13r7sbfp49VHavPNwd3Ln8TGPA/DR0Y/IqrQRgWuY7etIhEMiUJ6cfbDiMig8Dl694K+/w4ArlLaqw5TXlfNK/CssWL2AnTk70aq1LByykF+v+ZXr+l/XpcXL/F39eXrc0wB8cPgDTpV2vCeHVYicKv/M3Q81JcraYi9sf02uGeHqC3P+122XagySge9Pfs/cVXP5Pe131Co1twy6hV+u/oUZYTOsLlrtDJeHXc64XuOo09fxasKrSpsjY4yQ5OyD+s71kLMWwiERKMvxNfDJbKgukDUHd22EXsOVtqpDNBga+Or4V1z505V8feJr9JKeqX2n8su8X3hs9GN4daCRlSW4PPxypvadSqPUyHM7n6PR0Ha5eUXwDoEeA0EyyOJWwcU5cwi2NX2BXfl/4BWsrD0KcbLkJLf+disv7nmRyoZKhgQM4evZX7Nk7BKz9VfWQKVS8fTYp9GqtGzJ3sLWrK1KmwR+/eTSCYYGWZtkgwiHRKAMkiSL9r67Vc4iiJ4pR0Z8eittWYfYkbODa1dfy7KEZVTUVxDtF82KmSt4Y9obhHqHWtUWlUrFP8b/Ay9nL44VH+PzpM+tevx2Eem/HaOxDlYtBkMjDJoDMdcqbZHVqWmo4f8S/48bfr2Bw0WH8XDy4KmxT/HVlV8xJGCI0uZ1igjfCG4dcisgC1zr9HXKGqRS2Xz6r3BIBNZH3whrH4U//wFIMOYuuPEbcLFORMEcUstTWbxhMYs3LCa1PBU/Fz+eHf8s31/1PeN7jVfMriD3oObCTG8feJu08jTFbDkPo0OSvEmUkb8YW5dDwTFwD4DZr3e7pZpNmZuY98s8Pkv6DL2kZ2bYTFZfvZq/DPqL7fZsaodFwxYR5B5EdlU2Hx/9WGlzbL6vjXBIBNZFVyGXgd/7MaCCy1+RQ9M23iisvK6cZQnLmP/LfHbk7ECr1nL74Nv5df6vXD/gerRq5e2fFzmPSSGTqDfUs3TXUgySQWmTZFqWkS9JVdoa2yR7L+x4Xd6+6nXw7KGsPVbkTNUZHtz0IA9tfoi86jx6e/bmncve4T9T/tNmHyd7wt3JnSdGPwHIFVyzK7OVNchYsTV7LzTYSEpyC4RDIrAeZVnw8SxI2QhO7nDjVzDhXpu+E2w0NPL18a+ZvWo2Xx3/Cr2kZ0rfKfw872ceH/M43s7eSpvYjEqlYumEpbhr3TlQcIBvTnyjtEkyzh7Qd5y8LbJtzqehFlYtknU2MdfBYNvp99WVNBoa+ezYZ8z7ZR6bszajVWm5K+YuVs1bxSV9LlHaPItxefjljAuWBa6KV3ANiATPnqCvg5y9ytrSBsIhEViH3ANyT5qCY/IFccdvMHC20lZdlJ05O7l29bW8kvAK5XXlRPlG8f6M93lz2puEeYcpbV6b9PLsxaOjHgXgf/v/p/wdmZGW3X8Frdn0Lyg+DZ7BcIWNZGR0MYcKD3Hjrzfyf3v/j9rGWkYGjWTlnJU8NPIh3LRuSptnUVQqFU+PaxK4Zm1hW7aC4m6VyqbTf4VDIuh6TqyFT66EqnwIGiJn0oQoX1XxQqSVp3HvhntZtGERKeUp+Lr48o9x/2DlnJVd1sLcklw34DpG9xxNbWMtz+96HskWdBvG9F9RRr41Gbtg99vy9tw3wN1fWXu6mIr6Cl7c/SK3/nYrJ0tP4uPiwz8n/pNPZn1ClJ/jdoSO8I3glsG3ADYgcG0Wttpeoz3hkAi6DkmSP2y/vRkaaiDyMrlbr41WnSyvK2d5wnLm/zKf7Tnb0aq03Dr4VtbOX8sNA2+wCZ1IR1Cr1Lww8QVcNa7E58Xz4+kflTYJgoeDmz/UV8rr1wKor4af7wUkiL2ldRdrB0OSJH5L/Y25q+by/anvkZCYGzmX1Vev5proa1CrHP+raNHwRQS5BZFVmaVsBddmHUminNllQzj+WSBQBn0j/PY4/PE0IMHov8JfvgdX29FcGGk0NPLtiW+5atVVfHn8SxqlRi7tcymr5q3iyTFP2pROpKOEeody/4j7AfjP3v+QV52nrEFq9dkoiUj/lVm/FErTwLsPzHpZaWu6jMyKTO5Zfw9Lti+hWFdMP59+fHz5x7wU9xL+ro4dEWqJh5NHcwXXD498SE5VjjKG9Bgg95hq1EHOfmVsuADCIRFYnrpK+OZGSPwQUMHMl2D2azaZSbMrZxfXrr6Wl+JfoqyuTNaJTH+fty57i3CfcKXNM4tbBt3CsMBhVDVU8c/d/1R+6UaUkT9L6hZIXCFvz3sTXJXpUGsp9AY9iXmJ7CnbQ2JeInqDnnp9Pe8deo9rfrmG3Wd246x25v7Y+/lhzg+MCR6jtMmKMCt8FmODx8oC1wSFBK4t65Fk7FDGhgtge98QAvumPEdO680/Clo3WLBCLvJkY6SVp/Gfvf9ha7ZcQdHXxZf7Yu/j2v7X2s3STHto1Br+OemfXLfmOrbnbOfX1F+ZE6ngexHRFCHJ2Qe1peDmp5wtSqKrgF/k6BWj7zzrqNkpGzI2sCxhGfk1+fID2eDn4odWraWwthCAiSETeWbcM1YvGmhrqFQqnhr7FNetuY7NWZvZnr1dmYyisDhI+kUWtk5+wvrHvwAiQiKwHLkH5Uya/KPgEQR3rLU5Z6S8rpxXE19l/i/z2Zq9Fa1Kyy2DbuHXa37lxoE3OowzYiTSN5LFwxcDsDxxOUW1RcoZ49MbAgc0lZG3PUFdl2HQQ/oO/HI2QvoOWPd3KM8Cv3CY8U+lrTOLDRkbeHTLo2edkSZK60oprC3E08mTVye/ynvT3+v2zoiRKL8obh4kN0x8JeEVZQSuxghJVoJNicyFQyKwDCd/h0+ugMoz0GMQ/G0j9B6ltFXNNBoa+e7Ed1y16iq+SPqCRqmRyX0m8+O8H1kydgk+LvYdMr8YC4cuZKD/QMrrynk5XmGtQndbtklaDf8diuaLuUTsfwnNF3Ph4Ffyc/PeARfb78tyIfQGPcsSliFx4aVAdyd3ZobNtOlGeEqwOHYxPdx6kFWZxadHP7W+AT0GyRHKhmr5RtJGEA6JwHz2vAff3NSUSTMN7vwDfG3nbmh37m6uW3Md/4r/F2V1ZUT4RPDe9Pd4+7K3ifCJUNq8LsdJ7cSLk15Eq9KyPmM9f6b/qZwxRmFrykbHLyOftBq+vw0qctt+vqbYuvZYmP0F+8+LjJxLQU0B+wtsSzhpC3g4efD46LMC19yqC5wjXYVa3aIeie1EK4VDIjAdfSP89gSsWwJIMGphUyaN9aINbYnpjGRUZPDAxge4e/3dJJcl4+Piw1Njn+KHuT8wqfckq9loCwz0H8hfY/4KIAt4dWXKGBI2CdROUObgZeQN+rPXRZuo5KWbFuervbE7d3eH9iusKexiS+yTK/pdweieo9HpdbyaqEBBPKNDYkN9bRxrwVxgPeqq4Ie/wuk/5N9nvAgTH7BqGfi2xHQ93Xvy4MgHOVlykq9PfE2joRGNSsONA29k8fDFDr000x73DLuHjRkbSSlP4dXEV3n5EgWWb1w8IXS8fFeWulkuZe2IZOy6cGQEAAkqcuT9+tlXmfTDhYd548AbxJ+J79D+Pdy7T1+ezqBSqXhm3DNcu+ZaNmZuZEfODuJ6x1nPAKOOJHOPfHOJ8stqIkIi6DwVufDJLNkZ0brC9Z/DpAet7oy0JabLr8nnmR3P8HnS5zQaGonrHcdPc3/i72P/3q2dEQBnjTP/nPRP1Co1a1LXKFfCunnZxkHrkdRXw6kOLotVXXzJw5Y4XXqahzY9xM2/3Uz8mXi0Ki3uWvcL7q9CRbB7MCODRlrRSvuilcA1/hXq9fXWO3jPoXI0u74K8g5Z77gXQTgkgs5x5jCsuAzyjoBHD1i41urNwDoiptOoNLw17S3enf4uEb6OrxPpKMN6DOPWQbcC8MLuF6isr7S+EREty8g3Wv/4lkaSoPCUXJX486theTjsfqNjr/Xs2ZWWWYSsyiye2v4UC1YvYFPWJtQqNVdHXc3a+Wt5Ke4lVE3/WmL8fcnYJWjUGiXMthsWD19MoFsgmZWZfHbsM+sdWK2B0KZWGDbS10Y4JIKOc3Kd3K23Mhd6DJR70vQZbXUzOiKm00t63J0ufPfWnblvxH2EeoVSUFPAf/b+x/oG9GoqI19XIdcksUfqq+XrYe1j8L/h8PYYuSpx6mbQ14NPX3DyuMgAKvDuDWG22xupoKaAf+35F3NXzeXX1F+RkJgRNoNV81bx4qQXCfEMYXrYdF6b8hpB7kGtXtvTvSevTXmN6WHTFbLefvB09mwWuH5w+APrClzDbUtHIjQkgo4R/4Es0pMMEDEFrvsM3HwVMaWjIjkhpmsbN60bL0x8gTv+uIMfT//IrH6zGN9rvPUMUGvkc+jYT3L6b+g46x3bVCQJipPh9HpIXi/fUbasH6Fxlp2L6JkQNQMCo+H4GjnLRh6gxWBN0YRZy+S/hY1Rpivj46Mf8/WJr5trZEzqPYkHRjzAkIAh5+0/PWw6U/tOJfFMIvtO7GPUwFGM6TVGREY6wZX9ruSHUz+wN38v/078N69Pfd06B24Wtu62CYG1cEgEF8eghz+egfh35d9H3ApXvQ4aJ8VM6ugygxDTXZjRwaO5YcANfHfyO57f9Tw/zf3JuhGlyGlnHZKpT1nvuJ2hvkYW3xqdkNL01s/7hEL0DPl/+CXn1xQZPFfWV61b0lrg6h0iOyOD53b5FDpDdUM1XyR9wWfHPqOqoQqAEUEjeHDEg4wOvngkVKPWMCZ4DE55TsQGxwpnpJOoVCqeHvc01625jg2ZG9iZs9M6mYDBw8DZC+rK5YKWCiMcEsGFqauCH++CU7/Lv09/HiY9bFXxaksq6yt5Y/8bfHvy24vup0JFT/eeQkzXDo+MeoRt2dvIqcrhjQNv8Pexf7fewSNblpEvkz8UlUaSoDhFdj5Or5erqraMgqidzkZBomdAYP/2r4XBc2HgbPRpO8g4Fk/YkHFo+sXZVGSkTl/H9ye/58MjH1KiKwFggN8AHhz5IJf0vkQUNbMS0X7R/GXQX/gi6QteSXiFn+b+hLPGuWsPqtHKWW/J61Fl7ARXZZcQhUMiaJuKM3JPmrzDoHGB+e/DkGsUMUWSJP7I+INXE15t7o0xquco9uXvQ4WqlbhViOk6joeTB89PeJ57NtzD18e/5vLwyxkRNMI6B/fpI3+hF52SoxD9r7TOcc+lvkZ2PJLXw+k/LxAFmS4vw/SbbFplVbUGwuMoLfMkLDzWZpyRRkMjvyT/wruH3m3WZIV5h3F/7P3MDJ+JWiUkhtbm3uH38nva72RUZPB50ufcFXNX1x80PK7JIdkFA4RDIrA18o7A1zfIdRLcA+Gmb6GvMt05syqzeCn+JXbmyKKrMO8w/jH+H4zvNf78OiTIYrolY5cIMV0Hmdh7ItdEXcOq5FU8t/M5Vs5ZiavW1ToHj5wmOyQpm6zrkBSnyBGQ03/KYr5G3dnnmqMgM2QnpMcAxSKCXYVBMvBn+p+8dfAtMioyAPm6uTf2XuZGznW4fk72hKezJ4+OepSndzzN+4feZ3a/2fTy7NW1Bw1vqn2StRv6G7r2WO0gzjxBa06vh5UL5dz0wP5w80q5CZiVadA38OmxT3n/8PvU6etwUjtxV8xd3BlzJy4aF0CI6SzF42MeZ0fODtIr0nn30Ls8MuoR6xw4YirEv9f1fW0aauUoyOk/5fO7NK318z59IWq67IT0mwwuNrB81AVIksT2nO28sf8NTpaeBOSuvH8b9jeuH3B983UlUJarIq7ih1M/sL9gP//e+29em/Ja1x6w13Bw8kBVW4pbZRqg3FK3cEgEZ0n8UC4FLxnkD+brP1ekRfzevL28uOdFUsvl0uLjgsfxj/H/INwn/Lx9hZjOfLydvXl2/LM8uPlBPj32KTPCZjA0cGjXHzg8To5IlKZDSVq7u3cKYxQkuUkLcl4UZIIcAYmeIaewO1gU5Fz25u3ljQNvcKDgAACeTp7cPuR2bh18Kx4XTU8WWBuVSsUz45/h+jXXsz5jPbtydjGxdxcupWicoO9YSN1MUMpKCO0JCumchEMikDNp1j8Hu9+Sf4+9Rc6k0XaxoOocSnWlvLbvNX5O/hkAf1d/Hh/9OFdFXCWEdV3M1NCpXNHvCn5P+53ndj3Hd7O/w6mrM6lcPKHvOMjYgSptC2jM0K801MqpuKf/lJ2Qc/vkePeRtSDRMx06CnIux4qP8eb+N9mZKy95umhc+Mugv/DXIX/F19VXWeMEF6S/X39uGngTXx7/klcSXuHHuT92ncA1aTXk7AUgMPtP+OLPpkyw5VbPBBMOSXenvhp+/BucXCv/Pu1ZuOQxq94xSpLEz8k/89q+1yirKwPg2v7X8vDIh7t9uXdr8tTYp4g/E8/p0tN8eORDFscu7vqDRk6VHZKUzdC/kw5JcQokb2jKiNl+fhQkdHxTWu7MbhEFaUlqWSpvHXyL9RnrAdCqtCzov4C7h919XhEzgW1yb6wscE2vSO86gauxI/W5Va8rzsiPX/+5VZ0S4ZB0ZyrzZPHqmYNyJs0178LQBVY1IaUshRf3vMi+fLliZ7RfNM+Nf47YoFir2iEAP1c/nhr7FE9se4IPDn/AtNBpDPAf0LUHjZwKm16E1E34ucWAb9WFw8XGKIgxLbckpfXz3r2btCAzIeLSbhMFaUluVS7vHHyHNalrMEgGVKi4KuIqFscupq9XX6XNE3QCL2cvHhv9GE/veJoPDn9geYHrRTtSSzR3pB4422rLN8Ih6a7kH4OvroeKbHAPgBu/sWrFTF2jjg8Of8Anxz6h0dCIm9aNxcMXc8vgW3BSK1d0rbtzefjl/J72O5uyNvHcruf46sqvujbroiwLUKFqqCHi4CtwkNbh4pLU/2/vvgObqt4Gjn/TRQd0AKXsCrSU1bJkD8HFLHsU2SD82Ci+DGUpInvIFEXZRcCCiDJEFGUVKKOUJVBGGaV0U7rb5Lx/xAQqRVqa9ibp+fyjTdKb5+FywpNzz30O3DikLUJuH4XMlKe/a2EFFZs8vSOmVPVCNQvyrOiUaNaGrGXH9R1karT7A71Z4U3G1B2Dp4unwtFJrypfF7ga4Y7UsiAxdxo13DmGy4NTT7993joMOwZB+hMo4Ql9d0DxgtuA7viD48w+OZv7ifcBeKP8G3zS6BPKFi1bYDFI2VOpVExrPI2gR0FcibnCxssbGeo9NH/e7Moe7R1dz00Xh8OO/lC0NCRGZH2uWNmn3VErvQG2jvkTm4l4nPaYjZc3suXqFlL+KdYal2nMuLrj8Hb1Vjg6Ka90HVx7/9Jbu8A1/ARNyxpogWtOd5ouwB2pZUFizq7sgQOTsUwIpzLAObTbTac+ATTadte9NxfYnTRRyVEsCFrAgTsHAChlX4pPGn7CmxXflItWjYirvSuTG0xm2vFprA5ezZsV36SSUyXDvsl/Thf/IzECVJbaviC623JL1Si0syDPSs5IZuvfW1l3aZ1+KwWfkj6MqzeORmVMYG8gKce8invhV80P/6v+zD2l7eBqkAXnOd1pugB3pJYFibl60WKl1Mfa/7q3gH67CuROGrVGzY7rO1h+bjmJGYlYqCx4r9p7jKk7Rt5yaKQ6VenE/jv7Of7gODOOz2BD2w2GvaX6pdPF//D7HrzaGO59TVy6Op2A6wF8E/INMakxAHg4ezCu7jhaVWglC3szNarOKA7cPqBf4GqQWUv3ptrLowkPyf6LgUr7fAHuSC17A5ujnHz7jLtVIAuVrsZcpd++fsw5NYfEjERqlqjJ9x2+Z3LDybIYMWIqlYqZjWdib2VPcFTwS/cPyrWcTgPncCNFc6fWqNkduhvfH32Ze3ouMakxlC9anrkt5hLgG0Driq1lMWLGHG0cmfD6BAC+DvmaiKSIl/xGDlhYatdqAfodqPWU2ZFaFiTm6NZfL//2qVuslE+SMpKYf3o+fnv9uBRziaLWRfmk0Sf4t/enRoka+fa+kuGUKVqGj17/CIBl55Zx78k9wx3cCKeLjZEQgt/CfqPbnm5MPz6d8KRwXO1cmd54Onu67qFj5Y6yGWAh4VvZl7ql6pKSmcLCoIWGOahuR2rHf92941i2wG/5BXnJxvSlPtbuPRNxER6GaDfDi7ySs9/Nh8VKQgj+uPsHc0/P1e8x0/a1tkxsMFH2PzBBPar24MCdAwRFBPHZic9Y++5aw3wTN8LpYmMihCAwPJBl55dxJUY7np2KOPF+rffxq+ZXcPsNSUZDpVIxtdFUev3Si4NhBwkMD6RJ2SZ5P7AR7UgtCxJTIYS2b0jERYi48LT4+PfupLlh4G+f4YnhzDk1h7/u/wVA+aLlmdp4Ks3LNTfo+0gFx0JlwWdNPqPbnm6cijjFzhs76VG1hwEO/M908Y4BaKeHny1KlJkuNhbBkcEsO7eMM4+03TPtrewZUHMAA2oMoJhN4eutIj3lVdwLPy8/tv69lTmn5hhugauR7Ej9ygVJbGwsvXv3Zvbs2TRqpF3VfeHCBWbPnk1oaCguLi6MHDmSnj176n/nxx9/ZPXq1URFRVG5cmWmT59O3boFtN25KdFotBuAPbygLTp0xUdSVPavd6oApX2gjI/2v241YX3bAvv2maHJYMuVLXx14StSMlOwsrBicM3BDPcZLr/JmYEKjhUYW3csC88sZNGZRTQv15zSDqXzfmDddPGByVkvMTqW1RYjBTxdrLRrsddYfn45R+4fAcDGwga/an4M9R5KcdviCkcnGYvRdUdz4I52gevmq5sZUmuI0iEZzCsVJGfPnmXKlCncvXtX/9jjx48ZPnw448aNo3fv3gQFBTF69Gi8vLzw8fHh1KlTfP7556xduxYfHx/8/f0ZOXIkhw8fxs7OzmAJmZzMdIi6+rToeBgCjy5pd9v9N5WFdgfeZ4uP0t5gn82HVQF9+wyODGbWyVnciLsBQH23+kxvPJ0qzlXyfGzJePSt3pdfw34lJCqEWYGzWPXWKsNcujGi6eL8otaoCYoI4mz8WTIiMp7bkTosIYxV51ex/85+ACxVlnTx6MKI2iMMU/hJZsXRxpEJ9Scw7fg01lxYQ/tK7c3m70muC5Iff/yR5cuXM3HiRD788Ok25QcPHsTZ2Zm+ffsC0KRJE3x9ffH398fHx4cffviBDh06UL9+fQAGDRrE9u3b2bdvH927F2y7csWkJmiLjWeLj6i/QZPx/GutbLUzHbqio0xtbQ8GG/ucvVc+f/t8nPaYL899ScD1AACcizgzof4Eunh0kav9zZClhSWfN/2cHj/34OiDo/xy6xd8q/ga5uBGMl2cHw6FHWLe6Xn69VTcBzd7N6Y0nEKtkrVYc2ENu0N3oxZqANpVasfoOqNxd3RXMGrJ2PlW8SXgegDBUcEsOrOIRW8sUjokg8h1QdK8eXN8fX2xsrLKUpDcuHGDqlWrZnmth4cHAQHaf7BCQ0OfKzw8PDz4+++/c/X+arU6tyHn+JgGPXbiI4gIQRVxEVWEdtZD9e8dSP8hbJ2htA+idC1w80GU9oaSntrW2M8Hm/MYvDqAZ1s0d45z72oQFao3wOK1ZtoP/FfMVQjBvjv7WHx2MbGpsQB0rtKZD+p+gIutCxqN5pWOmxf5cv6MjDHk6F7MnRE+I1gRvIJ5p+fR0K0hJe1KGuTYxpCfof1+93f+78j/If512fRR8iM+/PNDrFRWZAptm/eW5Voyus5ovFy0eweZ4p+DOZ7DZxlbflMaTOG9/e/x651f6ValW54b4uVnfjk9Zq4LEldX12wfT0pKeu7Si62tLcnJyTl6PqcuXryYq9e/lFBTNOYiLmkx3I4OJrGEt7Y7ZI5/X0OR5IfYPb6B/eOb2CfcwP5xKNZpsdm+PN22FMlOVUh28iTZ0YMUJw/S7dyedp/UAOFpEH4p77npOUK5t4hLAEJe/c8vIi2CTeGbuJKkXfVftkhZBpYdiJedF2F/hxFGmIHifTUG/7thhJTOsbaojbutO2GpYUz5bQpjKo4x6PGVzs9QNELD7GuznytGnpUpMqlqV5WeZXriae9JSlgKwWHBBRdkPjGXc/gixpRfa5fW/B77O58d+4xZVWYZZN8pJfMz2F02dnZ2PHmStYlRamoqDg4O+udTU1Ofe97FJXdty729vbG0NNCU7tWfsfj1Y1RPnl7SEMXKomkzF6pnMx2tToeoa//MeFxE9c/ttqps1nsIVFDCA/HPJRfdfy3tS1AMKMi18mq1mosXL77yn12aOo31l9fz3c3vyNBkUMSyCMO8hzGw+kDDrPDOo7zmZwqMKcf57vPpt78fZxLOEOUSxTvu7+T5mMaUnyEERQQRdznupa+b2GwiDUo3KICI8p+5ncN/M8b8KteozLmfzhGeFs6lIpcYVHPQKx8rP/PTHftlDFaQVK1alePHj2d5LDQ0FE9P7U6Tnp6e3Lhx47nnW7Zsmav3sbS0NMwf1pU9EDCIf9+FonryEMuAQdDta3CqqF3r8ex6D3V6NkEVAbcazyw2rY3KrQbYODzX/05Jr/Jnd+rhKWafnM2dhDsANCvbjKmNplLB0fi2MjfY3w0jZgw51nStyVDvoXwd8jVzg+bSuGxjnG2dDXJsY8jPEGJfMEOa3evMId9nmcs5fBFjys/FzoUJr09g+vHpfH3xazpU6ZDnBa5K5mewguSdd95h4cKFbNiwgb59+3L27Fl+/vlnVq9eDUCPHj0YPXo07dq1o379+vj7+xMTE8M77+T921Wu/Wdr9X8e2zU8+98t4vT0Dpcy/yw4LVkVjGCmwJBiUmJYdGYRv9z6BYCSdiWZ3HAybdzbyEWrEsN9hvP73d8JjQ9lftB85raYq3RIRkOtURMaH5qj17raZ38JXJJyqlOVTgRcD+BC1AUWn1nMwjcM1MVVAQYrSFxcXFi3bh1ffPEFy5cvp3jx4kybNo3GjRsD2rtuZs6cyaeffsqjR4/w8PBg7dq1ODs7GyqEnMvpxl52JaBCg2fudPEBZ3ez3m1UIzTsvLGTpWeX8iT9CSpU9Pbqzbh642RTJknPxtKGWU1n0W9/P3659QvtKrWjZfnczXaaGyEEh+8dZsX5FS8tSFSocLN3o16pegUUnWSuLFQWTG00Fb+9fhy4c4CeVXvSsExDpcN6JXkqSK5du5blZ29vb7Zte/EmXJ07d6Zz5855eUvDyGnL9PYLwNsAXSlNxPW468wKnMWFqAsAVCtejRmNZ+Dt6q1wZJIx8nb1ZkCNAWy4vIHPAj9jd+fdhbZoPfXwFMvPLSckOgSAYjbFaFmuJXtv70WFKsviVtU/F3InN5ws96GRDKJ6ier0qtqLbde28cWpLwjoFIC1henN2hfOzfXkxl5ZJGcks+TMEnr93IsLURewt7JnUoNJfN/he1mMSP9J1zMjMjmSxWcWKx1OgQuJCuH9g+/z/sH3CYkOwc7KjmHew9jfbT/zWs5jaaulz+3h5GbvxpJWS3jb/W2FopbM0Zi6YyhuW5xbj2/hf8Vf6XBeSeHcy0Zu7KX3172/mHNqDuFJ2ktYb1d8m8kNJ5tN5z8pf9la2fJZ088YdGAQO2/spM1rbQyz4ZeRuxF3g5XnV/LHvT8AsLawppdXL973fj9Lb5a33d+mdYXWBD0M4uzfZ6lfrf5znVolyRCcijjxQb0PmHFiBl9d+Ir2ldub3IamhXOGRLexF8Bz98GY18ZeurbVJ+NPEhQRhFqjbVATkRTBh4c/ZMwfYwhPCqeMQxlWvrmSpa2XymJEypX6bvXx8/ID4LPAz0jOyF1vIVNy78k9Pj76Md33dOePe39gobKgi0cXfun6C1MaTsm2UZylhSUNSjegsXNjGpSWxYiUfzp7dMbH1YfkzGQWnTG97q2Fc4YECsXGXi9qW92kTBMOhh0kOTMZS5UlA2oOYITPCOytc9iWXpL+5YP6H3Dk/hEeJD5g+fnlTGk4RemQDCoyOZJvQr5h5/Wd+u6q77i/w5i6Y6jsVFnh6CRJS7/A9Rc/9t/eTw/PHia1wLXwFiRg1ht7HQo7xIQ/J2Tbtnr3zd0A1HatzYwmM6jqUjWbI0hSzjlYOzCz6Uz+99v/2Hp1K++6v0s9N9O/gyQ+NZ51l9ax9e+tpKnTAGhWrhlj646lZomaCkcnSc+rUaIGvbx6sf3aduacmsMPnX4wmQWuhfOSzbN0G3uVewteM49iRK1RM+/0vP9sW+1o48j6NutlMSIZTNOyTenm2Q2BYOaJmaRmpr78l4xUUkYSay6sod2udqy/vJ40dRp1S9VlfZv1rHl7jSxGJKM2tu5YXIq4cPPxTbZe3ap0ODkmCxIzdC7y3NPLNC+QkJ5AcFRwwQQkFRofvf4RpexKcSfhDqsvrFY6nFxLU6ex+cpm2u9qz6rgVSRmJOLl4sWqt1axse1GXi/9utIhStJLORVx4oP6HwCwOng1kcmRygaUQ7IgMRNqjZrgyGBWnF/B9OPTc/Q7UclR+RyVVNg42jgyrfE0ADZe3silaENuEpl/MjWZ7Ly+kw67OrAgaAGxqbG4O7qzsOVCdvjuoGX5lrJDsWRSunh0waekdoGrqdySX7jXkJi4mJQYjocf59j9Y5x4eILHaY9z9fuybbWUH1pXbE37Su3Zd3sf049PZ0fHHUaxCWN2NELDwTsHWRm8krAE7W7VbvZujKozik5VOhlk91RJUoKFyoJPGn9Cn1/6sO/2PnpU7WH0GznK0WZC1Bo1F6MvcuzBMY49OMblmMtZni9mU4ymZZvStGxTVp5fSXRKdLbrSGTbaim/TWk4hZMPTxIaH8rai2sZVWeU0iFlIYTg6IOjLD+3nGtx2o7TLkVcGOYzjF5evShiWUThCCUp72qWqEnPqj3ZcX0Hc07NYYfvDqNe4CoLEiMXkxLDifATHH1wlBPhz8+CVC9eneblmtOifAu8S3rrv9E52jgy4c8Jsm21pAgXWxc+bvQxE/+ayNqQtbxV8S28inspHRYAZyLOsPz8cs5HngegqHVRBtYcSP8a/XGwdlA4OkkyrHH1xnEw7CCh8aF8f/V7BtQcoHRILyQLEiOj1qi5FHOJYw+OcfT+Ua7EXMlSUBSzLkaTsk1oUb4Fzco2e+Fll7fd32ZJqyVZ+5CgnY6e3HCybFst5bs27m04UPEAv9/9nRknZuDf3l/RSyCXYy6z4twKjocfB6CIZRHeq/4eQ2oOwdnWWbG4JCk/6Tq4fhr4KasvrKZdpXZGe7leFiRGIDY1luMPjnPswTFOhJ8gPi0+y/O6WZDm5Zrj4+qT4w912bZaUpJKpWJqo6kERQRxJeYKGy9vZKj30AKP41b8LVYGr+S3sN8AsFJZ0b1qd4b7DDe51tqS9Cq6enZl542dXIy+yOKzi5nXYp7SIWVLFiQKUGvUXI65rJ8FuRxzOdtZEF0RkpdqVte22jrCmjql68hiRCpQrvauTG44manHprI6eDWtK7YusM6m4YnhrA5ezc+3fkYjNKhQ0bFyR0bWGUmFYhUKJAZJMga6Dq599vZh7629dPfsbpQLXGVBUkBeNgtSrXg1fQFS27W2XN0vmQ3fyr7su72P4w+OM/P4TDa03ZCvhXF0SjRrQ9ay4/oOMjXaNu9vVniTMXXH4OnimW/vK0nGrGbJmvSo2oMfrv9gtAtc5b96+UQjNFyOvszRB0c59uAYl6IvPTcL0rhsY1qUa0Gzcs3k1LFktlQqFTMbz6Trnq4ERwWz7do2+lbva/D3eZz2mI2XN7Ll6hZSMlMAaFymMePqjsPb1dvg7ydJpmZc3XH8FvYbofGhbPt7G/1r9Fc6pCxkQWJAcalx2r4gD45x4sEJ4tLisjzv5eKlvyPGx9XH6KpTScovZYqWYUL9CXx+8nOWnVtGy/ItDXbZJDkjma1/b2XdpXU8SX8CgE9JH8bVG0ejMo0M8h6SZA6cbZ0ZX288nwV+xqrgVbR9ra1RLXCVBUke6GZBdH1BLkZfzDILUtS6qPaOGDkLIkn0qNqDX+/8yumI03x24jPWvrs2T91P09XpBFwP4JuQb4hJjQHAw9mDcXXH0apCK9lZVZKy0c2zGzuv7+RSzCWWnF3C3BZzlQ5Jr9AXJGqNmqCIIM7GnyUjIuOld6HEp8Y/nQUJP0FsamyW53WzIM3LNad2qdpyFkSS/mGhsuDTJp/SbU83TkWcYueNnfSo2iPXx1Fr1Px862e+Cv6K8KRwAMoXLc/ouqNp91o7uXBbkv6DhcqCqY2n8t7e9/jl1i909+xuNHs0FeqC5FDYoax9Ou5r+3RMaThF36dDIzRcibmiXwtyMSr7WZDm5ZrTrGwz3BzclEhFkkxCBccKjKs3jgVBC1h0ZhHNyzWntEPpHP2uEIJDdw+x8vxKbj2+BYCrnSsjao+gq2dXWfxLUg7VKlmL7lW7E3A9gDmn57Cj4w5900wlFdqC5FDYISb8OeG51uqRyZF8+OeH9K/en/g07WzIv2dBqrpU1c+C1ClVR34QSlIuvFftPX698ysXoi4wK3AWq95a9Z+vF0IQGB7IsvPLuBJzBdA2e3q/1vv4VfPD1sq2IMKWJLMyvu54fgv7jRtxN9j29zb6ePVROqTCWZCoNWrmnZ6X7T4vusc2X92sf8zB2oEmZf6ZBSnXLMff6CRJep6lhSWzms2i556eHH1wlD039+Bm55btZdPgyGCWnVvGmUdnALC3smdAzQEMqDGAYjbFlExDkkyaboHrrMBZrDy/Elc7V0LjQ3O0dCG/FMqC5FzkuSzt1F+k7Wtt6eXVS86CSJKBVXaqzMg6I1l2bhnTj09/+uXgn8um/Wv053TEaY7cPwKAjYUNftX8GOo9lOK2xRWMXJLMRzePbqy/uJ57iff4vyP/p30wm6ULBaVQFiRRyVE5el3rCq2NspudJJmD8sXKAzw3U/ko+RGLziwCwFJlSRePLoyoPULOTEqSgR2+d5h7ifeeezwyOZIJf05gSaslBVqUFMqCJKf3XRvT/dmSZE7UGjWLghb952tsLW3Z7ru9wFrNS1Jholu6kB2BQIWK+afn07pC6wK7fGNRIO9iZOqVqoebvdsLVxWrUFHavjT1StUr4MgkqXDIyWXTVHUqMSkxBRSRJBUuLxuDAkFEcgTnIs8VWEyFsiCxtLBkSsMpAM8VJbqfJzecLPsZSFI+yell05y+TpKk3DHGMVgoCxKAt93fZkmrJc91T3Wzdyvw62aSVNjIy6aSpCxjHIOFcg2Jztvub9O6QmuCHgZx9u+z1K9WX7HbnSSpMNFdNo1Mjsz29nsVKtzs3eRlU0nKJ8Y4BgvtDImOpYUlDUo3oLFzYxqUlsWIJBUEedlUkpRljGOw0BckkiQpQ142lSRlGdsYLNSXbCRJUpa8bCpJyjKmMSgLEkmSFKW7bGodYU2d0nVkMSJJBcxYxqC8ZCNJkiRJkuJkQSJJkiRJkuJkQSJJkiRJkuJkQSJJkiRJkuJkQSJJkiRJkuJkQSJJkiRJkuJkQSJJkiRJkuJkQSJJkiRJkuJkQSJJkiRJkuJMplOrENrdCNVqtcGPrTtmfhzbGMj8TJ+55yjzM33mnqPML+/H1v07/iIq8bJXGIn09HQuXryodBiSJEmSJL0Cb29vbGxsXvi8yRQkGo2GzMxMLCwsUKlUL/8FSZIkSZIUJ4RAo9FgZWWFhcWLV4qYTEEiSZIkSZL5kotaJUmSJElSnCxIJEmSJElSnCxIJEmSJElSnCxIJEmSJElSnCxIJEmSJElSnCxIJEmSJElSnCxIJEmSJElSnCxIJEmSJElSnCxIJEmSJElSnCxIpGwVhga+5p6juedXGJj7OZT5Sc+SreNzKDExEQsLC6ysrLCxsUGj0fxnT35Tsn79eiIiIrCzs6N69eq0adMG0A4mc9k3yNxzNPf8dKKionByckKlUmFtbW1W43DlypWEh4dTsWJFqlatyptvvgmYzzmU+Zm+2NhYihcvnm/Ht8q3I5uRGTNmEBkZSWRkJB4eHowcOZJKlSqZxYfhmDFjiIuLo0mTJty+fZvdu3dz8+ZNRo0ahUqlMovBZO45mnt+OpMnT+bu3buo1WqqVavG4MGDzWYcjh49mkePHtG8eXNu3LhBQEAAFy9eZPz48WZxDmV+pp0fwK5du1i+fDmbN2+mQoUK+fMmQvpPH330kfDz8xN37twRW7duFWPHjhUtWrQQt2/fFkIIoVarlQ0wDw4fPiw6duyoz+Hx48dixowZwsvLS3z11VcKR2cY5p6jueenM2nSJNGrVy8RGhoq/P39xYQJE0SzZs3E33//LYQw7XEYGBgofH19s5zDH3/8UdSuXVssWbJE4ejyTuZnHg4dOiS8vLxEhw4dRFhYWL68h5wh+Q+PHj3i/v37zJ07F3d3d9zd3SlVqhQHDx5k4MCBrF+/nsqVKysd5iuLjY3F2toaCwsL0tPTcXR0pHbt2ty/f58ffviB8uXL07FjR6XDzBNzz9Hc8wNISEggPDyczz//nCpVqlClShVatWrF0qVLGTBgAFu3bqVKlSom+y00PT0dGxsbLCws0Gg0ODo60qFDBywsLFi4cCHly5enZ8+eSof5ymR+pp2fbgYyOjqafv36ERYWxqBBg9i4caPBZ0pMe54znyUkJHD16lUSEhL0j9WtW5cePXrQoEEDli1bRmpqqoIR5k3FihV58OABhw8fxsbGBoCLFy/SpEkTWrduzaVLlxSOMO/MPUdzz0+j0ZCSkkJYWBhxcXH6x8uWLcv//d//0aJFC+bMmcOTJ09MshgBqFy5Mrdu3SIgIEB/6cna2pq33nqLHj16cObMGdLT0012gaTMz7Tz0+V0+vRp3Nzc+Oqrr6hUqRIDBw7k3r17hn0vgx7NzHh6etKwYUNWr17N3bt3SU9PZ+nSpajVat58801u3bpFcnKy0mHmyoULF7h58ybh4eG8/vrrdOrUiS+++IIhQ4YwZMgQzp8/z/vvv89rr73G5cuXUavVSoeca+aeo7nn9ywLCwvc3Nxo1qwZ8+fPJyoqSv+cm5sbXbt2JSoqipiYGAWjzL379+/r/798+fKMGDGCLVu2sH//fv3jDg4OuLu7c+vWLQCTKrhkfqadH0BgYCDR0dH6nzt37szQoUOxsrJixYoV+VKUyEs2/7Jt2zYALC0t6dmzJ4MHD2bTpk20a9eOOnXqkJaWRkBAAGlpaXz77bcmNUMyevRo7ty5g42NDfHx8Xz88ccMHjyYZs2acf78ecqWLUvv3r0BiI+Px93dXeGIc8/cczT3/HQCAwPx8PDA1dUVgPfee48VK1bw+eefM336dP3jDRs2xMrKiqSkJCXDzZXNmzcTGBjI2LFjqV69OgBvv/02kZGRfPfdd6Snp9O5c2dAew6dnZ1NqqiU+Zl2fkIILl26xMSJExk+fDjt27enZMmStGzZUv+8vb09q1atYty4cXTp0oWffvqJ8uXL5/m9ZUHyjGHDhhEZGUmZMmW4f/8+W7duZe7cuSxdupSQkBCcnJyoVKkSAFu3bgWgaNGiSoacYwsWLCAmJobdu3cTHh7On3/+yfjx4xk/fjwjRoygVatWXL9+nW+//Zbk5GS2bNnCpk2bsLS0VDr0HDP3HM09P3j+w7BDhw6UKFGCWrVq0a1bN3bu3MmECROYN28erq6u7Nq1i4SEBNzc3JQOPcdUKhV//PEHxYoVo3///tSqVYvKlSvTu3dvihYtyuzZs9m1axclS5YkMDCQb7/9Fjs7O6XDzjGZn+nn5+DgQHR0NJs3bwagY8eOz93ua2try7Jly5g0aZLBCi5ZkPxjx44dxMbG8tNPPwHahUrDhw9n5MiRrFq1ikaNGnHv3j0GDhxIuXLlOHbsGOvXr8fR0VHhyHPm0aNHdO3aFWtraypUqMDAgQMpXrw4kyZNwtnZGT8/PxITEzl06BDVq1dn06ZNVKtWTemwc8XcczT3/CD7D0NdUdKmTRucnJzYunUrbdu2pW7dujx8+JBly5ZRsmRJhSN/Od2i2+TkZHx9fbly5Qpr165l+PDh1KxZE09PT4YNG8Zbb73FoUOHcHNzY8yYMfovQcZO5mfa+T3ryZMndOnShTJlyrB+/XqEEHTq1AkXF5csl57s7OxYsWKF4d44X+7dMUHbtm0To0aNEkIIkZaWpn986NCh4t133xWZmZlCCCHWr18v9u7dK+7cuaNInLmVmZkp0tLSxNixY8WCBQuEEEJkZGTob1Hbtm2b8Pb2FlevXhVCCKHRaBSL9VWZe47mnt+/BQcHi8mTJ4svv/xStGrVSmzYsEFER0dnec2ZM2dEaGioePTokUJRvrp+/fqJ3bt3i9u3b4v27duL8ePHi0uXLikdlsHI/EyT7nNDo9GINWvWiBkzZgghhPj6669F69atxYYNG0RsbGy+xlDoCxJdobF582bx7rvviqSkJCGEEKmpqfrXdOnSRcyZM0eR+Azlxx9/FF5eXuL06dNCCCHS09OFWq0WaWlponfv3mL37t0KR5h35p6jOeeXkw/DmJgYJUM0iIyMDBEYGKj/+caNG/p/1HQFpSmT+ZmmuLi4LMV9bGysSE5O1v+sG4ebNm3K13FYqC/ZxMfHk5aWhpubG/369SMgIIARI0awadMmihQpor+/vGnTpjx58kTpcHNl0aJFJCYmEhMTw7Bhw+jcuTM3b95k6NChbNiwgXr16gFgY2ODg4ODSd6SZu45mnt+OvHx8aSnp1OqVClUKhW9evXC1tYWgOHDhwOwceNGLCws6NChQ762rjY03TmMjY1l2LBheHp60rhxY0B7WdjDw4Ply5fz4YcfsmjRIiZOnIiXl5fCUeeczM+08wOYOHEiDx48ICIigkaNGtG/f39q1KgBQEZGBtbW1gwfPhyVSsXSpUuxsrKid+/e+dIdudDe9jtx4kRGjRpFnz59mDRpEqGhoSxYsIDIyEgGDx4MoO/roNFoUKvVqNVqk/jQHzFiBCdOnNC31f7ggw9Yu3Ytvr6+9O3bl379+rFjxw5OnjzJ999/z5UrV6hfv77SYeeKuedo7vnp6Mahn58fH3/8MVeuXMHFxQU7OzsyMjIAbVHSp08fli5dyq+//opGo1E46px59hyq1WrGjx/Pxo0biYiIALSfL2q1mipVqrBo0SKePHmCs7OzskHngszPtPMDmDJlCnfv3mX69OnMnz+fa9eusWTJEvbv348QAmtrazIzMwHtTR/jxo2jadOm+bdVQ77NvRixyZMni169eokrV66I06dPi65du4phw4aJffv2iZCQENGxY0fRsWNHMW/ePLFgwQJRv359ce3aNaXDzpEzZ86Inj17Znnsm2++Ed27dxerVq0ScXFxYsuWLaJjx47Cz89P9O3bV1y+fFmhaF+Nuedo7vnpZDcOhw4dKvbt26e/hJORkaF//fr1601m7VZ253Dt2rWiW7duYuXKlVmuxesuGz+7ds3YyfxMOz8hhIiJiRH9+/fPMqaio6PF2LFjxdChQ8XJkyf1jxfU1gyFriB50UkYM2aMGDZsmDh79qzIzMwUs2fPFtOnTxczZ84U169fVzDi3AkKChJvvPGGuHv3bpbHv/vuO9G2bVvxxx9/CCGEePjwoUhKShIJCQlKhJkn5p6juecnhHF+GBrSi87hunXrRNu2bcXhw4eFEFlzM6XFyDK/w0II081PCCGSk5NF165dxebNm7M8rhubo0ePLvCYCt0lGzs7OxITEzl69Kj+sRIlSvDpp5+SkpLCN998g6WlJVOnTmXWrFnMmDEDT09PBSPOHVdXV0qXLk1ISIh+yhtgyJAhNG7cmMWLFyOEwM3NDXt7e4oVK6ZgtK/G3HM09/zgv8dhenq6/pZfwCR38n3RORw8eLD+HELW3Eypk6fMz7TzAyhSpAi1atXi9OnTPHjwANDe2ly8eHHmz5/PsWPHOHPmTIHGZHojPY9edBJKlCjBggULOHnyJKdPn9a/3hT+kv3111/8/PPPhISE4O7uToMGDVi4cCHnzp3L0rCmQ4cOuLi4kJGRYRJ5PcvcczT3/P7NGD8M8yo359DZ2Zn09HQFo809mZ+WqeYHsHbtWmbOnMnSpUu5fv06Y8aMITg4mCVLlvDo0SP9Z0rJkiXx9vYu8C87heIum7Vr13L//n2cnZ1p164dY8aMoUePHixZsoRJkybpuzzqToKTk5P+d439Q3/06NHExMQQFxeHs7MzPXv25KOPPiIsLIyJEyfy6aefUqdOHYoXL865c+fIzMwkMzNTv2DXFJh7juaen05ux6EpzfyY+zmU+Zl2fgCjRo0iNjaWJk2aEBQUxK1bt1ixYgXfffcd/fr1QwhBt27daNiwIbt27dKP1YKkEsIEbhvJg3+fBBcXF1asWMGNGzfo168fzZo1y3ISvv76a7Zt22YSrahnz57NpUuX2LZtGykpKcydO5fQ0FB9W/tp06Zx9epVNBoNHh4eHDlyhA0bNuj3XzAF5p6jueenI8eh6Z5DmZ9p5wfaPdp2796t36stJCSEIUOG8N1331G7dm3u3LnD559/TlRUFDY2NiQnJ7Nw4UJq1qxZsIEW+KqVAvT999+L3r1763++cOGCqF+/vggODhZCCHH79m0xZMgQ4evrK7p37y7atWtnMh33UlJSxP/+9z9x6tQp/WMXLlwQLVu2FBEREfrHjhw5Ivz9/cX27dtFWFiYEqG+MnPP0dzz05Hj0HTPocxPy1Tz01m0aJGYPHmyEEJ7N5BarRatW7cWR48e1b8mISFB3L59W1y6dOm5zsgFxawv2Tx48IDXXnsN0DaxqVWrFo6OjvomZ6+99hpffvklMTExJCUlUbp0aUqUKKFgxDlnZWVFSkoKR44coWHDhgBkZmZSrFgxnJyc9A1tmjVrZpKLAsH8czT3/HTkODTdcyjzM+38dCpUqMDt27eJjY3VNxa0sbHB2tpa/5qkpCT9OFWKWRckpnISXoWlpSU9e/bM0rXy7t27CCH0XS5//PFHoqKiGDZsGGD862H+zdxzNPf8dOQ4NN1zKPMz7fx0GjVqRMWKFSlevDhCCMLDw0lJSaFChQoA+Pv7c+TIERYvXqzoDvZmXZCYyknIKfHPbpNqtRpLS0vatm2LldXTU5iUlESZMmUAbavtL7/8ku3bt5vUANLlqNFosLCwMLscdfmB9oPN3PLLjhyHpnUO5Rg07fyy4+7ujru7O6DNOTo6mtTUVMqWLcvWrVtZvHgxW7ZsUXz8mXVBYionIScyMzNJTU2laNGiWFpaolar9YNI98EYERFBw4YN2b17N6tWrWLLli1UrVpV4chzJzMzE2tra/30qDnlmJaWRpEiRfQf9GBe+b2IHIemdQ7lGDTd/OBpjtnRFWNpaWnUrl0bf39/vvzySzZv3qzfv0ZJZlOQmPJJeJm5c+dy79494uLi6NixI3379sXS0lL/vO7/NRoNS5YswcnJiXXr1hX8Cuk8WLRoEVFRUdja2tK/f388PDyAp+fO1HNcuXIl8fHxfPjhhzg4OGT5QATzOIcgxyGY7jmUY9C08wNYunQpRYoUYcCAAdkW+LpZHhsbG44cOcLFixfZsGGD0eRoFgWJqZ+E/zJu3Dji4uLo06cPt27dYvny5VSpUkW/4+SzihcvTrFixdi6dStVqlRRINpXo+sB0KZNG9atW0fbtm31H4bPTh2D6eZ46tQpQkNDsbe3Z9iwYRQrVkz/Qf/sFLKp5gdyHOqY4jmUY9A8xmBUVBR79uzBxsaGvn37Ymdnp3/u2RyLFi1KpUqVWLlypVHlaBYFiamfhBf566+/uH//Prt27QIgISGBY8eOERMT89xr1Wo1ffr0oU2bNpQvX76gQ31le/fuJTIykh9++AGA33//ne3bt/P9999Tr149Bg0apP8gNMUcddPA3t7eJCYmcufOHdasWcPw4cP1Dfh0fz9NMb9nyXFomudQjkHTH4PPrmt64403WLRoEenp6QwZMkS/OFeX482bN/Hw8OCHH34wusukpnsfE9qTAGQ5CevXryc1NVX/muxOgil8CALExcVhb28PaG+XdHR0xMLCgsjIyCyv8/f355NPPsHW1takBhHArVu39M2vvvrqK86fP0/VqlVxdXVl/vz5rFmzBtDmOG3aNJPLUTcNXK1aNXx8fKhTpw7BwcFs27aNgwcP6v+RM9X8QI5DHVMdh3IMmv4YVKlUZGZmcv36dUaPHs3ixYtZvnw569atyzIOjx07xoABA4iPjze6YgRMfIbk2ZPwxRdf0L59ez766COALJXhsWPHmDx5Mnv37i3wVrh5UaVKFSIjIwkPD6d06dKA9kP/2XbF4eHhNGrUiLp165rkffKvv/66fsq+Xr16/PTTT/qpYh8fHzZu3MiAAQOoVKkSderUMckcdWJjY5kxYwa2trYEBARw5coVZs2aBWh7cZhqfnIcmvY4lGPQ9McgaNdv+fn5UaNGDWrUqIFGo2HixIkADB06lCJFitC8eXO2b99uvOOvILqv5afExESxbds2/c979uwRXl5eYtWqVSI1NVX/+L1795QIL8+uXbsmhNBuc52eni46deokgoKChBBCbNiwQXh5eYknT54oGaJBZGRk6P8/PT1dCCHE0aNHRZ8+fURiYqJSYRnMw4cPxf/+9z8hhLbro4+Pj+jSpYtYsmSJiIuLUzY4A5Dj0PTHoRyDpk933nTn8ueffxY1a9YUixcv1v/91Gg0isX3MiY9QwLg4OBAt27dAO3tar6+vqhUKqZMmUJqairDhw+naNGilCtXTuFIX43udjONRkNcXBwRERH6Ke+vv/7aKK8DvgrdtGpSUhIODg4A3Lt3z6Q2WPsvVlZWZGRksGnTJlatWsUXX3xBVFQUp06dIjMzU+nw8kyOQ9Mfh3IMmj5ds0FLS0uEEHTs2JH09HTmzZvHoEGDAONu7GZWm+vpUlGpVOzatYt58+Zx4MCBLF34TFlcXBwjR47Ey8uLvXv3smHDBmrVqqV0WAYTHR3N4MGDKVu2LE5OThw9epR169aZ1CZWL6JbYHbp0iXmzp1Lu3btyMzMJCEhwWz+furIcWi65Bg0H8+Ow8TERJMomM2qIAHTPAk5FRkZScuWLXFwcMDf359q1aopHZJBZWZm8tdffxEYGIibmxtvvfUWlStXVjosgwkJCSEuLo433niDzMzMLN0hzY0ch6ZJjkHzIrK5rdmYmV1BAqZ3EnIqMzOThQsX0qtXL5O5Q0F63rP/WJszOQ4lY1VYxqCpMcuCxJwVhqpekoydHIeSZHiyIJEkSZIkSXGmecO1JEmSJElmRRYkkiRJkiQpThYkkiRJkiQpThYkkiRJkiQpThYkkiRJkiQpThYkkiRJkiQpThYkkiRJkiQpThYkkiRJkiQpThYkkiRJkiQp7v8Bp0sn6Dl2ixYAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style('whitegrid')\n",
    "\n",
    "df9.plot(style='-o', rot=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "cc7ce0f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df9.plot(kind='bar', rot=45)    # Edellinen kaavio pylväinä"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71500b1b",
   "metadata": {},
   "source": [
    "Pylväskaavio ei ole havainnollinen aikasarjojen vertailussa (vertaa viivakaavioon)!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50586f8c",
   "metadata": {},
   "source": [
    "## Osa 10 - viivakaavio ja hajontakaavio"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6baccc34",
   "metadata": {},
   "source": [
    "Pandas-kirjaston **to_datetime**-funktio osaa muuntaa eri tavoin esitettyjä aikatietoja oikeiksi aikaleimoiksi.\n",
    "\n",
    "https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.to_datetime.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c0ee8e36",
   "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>Kysyntä</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-06-03</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-07-03</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-08-03</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-09-03</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-03</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Kysyntä\n",
       "2011-06-03        5\n",
       "2011-07-03        9\n",
       "2011-08-03        8\n",
       "2011-09-03       10\n",
       "2011-10-03       11"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df10a = pd.DataFrame({'Kysyntä':[5, 9, 8, 10, 11]})\n",
    "df10a.index = pd.to_datetime(['6.3.2011', '7.3.2011', '8.3.2011', '9.3.2011', '10.3.2011'])\n",
    "df10a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e84a433a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df10a['Kysyntä'].plot(style='-o', rot=45)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6f6f1818",
   "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>Joukkoliikenne</th>\n",
       "      <th>Henkilöauto</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1980-01-01</th>\n",
       "      <td>12.5</td>\n",
       "      <td>34.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-01</th>\n",
       "      <td>13.3</td>\n",
       "      <td>51.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-01</th>\n",
       "      <td>13.1</td>\n",
       "      <td>55.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-01-01</th>\n",
       "      <td>12.9</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-01</th>\n",
       "      <td>12.8</td>\n",
       "      <td>58.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-01-01</th>\n",
       "      <td>12.8</td>\n",
       "      <td>59.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-01</th>\n",
       "      <td>12.9</td>\n",
       "      <td>60.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-01</th>\n",
       "      <td>13.0</td>\n",
       "      <td>61.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-01-01</th>\n",
       "      <td>13.1</td>\n",
       "      <td>62.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01-01</th>\n",
       "      <td>13.3</td>\n",
       "      <td>63.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-01</th>\n",
       "      <td>13.6</td>\n",
       "      <td>63.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-01</th>\n",
       "      <td>13.2</td>\n",
       "      <td>64.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Joukkoliikenne  Henkilöauto\n",
       "1980-01-01            12.5         34.8\n",
       "1990-01-01            13.3         51.2\n",
       "2000-01-01            13.1         55.7\n",
       "2001-01-01            12.9         57.0\n",
       "2002-01-01            12.8         58.3\n",
       "2003-01-01            12.8         59.6\n",
       "2004-01-01            12.9         60.9\n",
       "2005-01-01            13.0         61.9\n",
       "2006-01-01            13.1         62.5\n",
       "2007-01-01            13.3         63.8\n",
       "2008-01-01            13.6         63.4\n",
       "2009-01-01            13.2         64.3"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df10b = pd.DataFrame({'Joukkoliikenne':[12.5, 13.3, 13.1, 12.9, 12.8, 12.8, 12.9, 13.0, 13.1, 13.3, 13.6, 13.2],\n",
    "                      'Henkilöauto':[34.8, 51.2, 55.7, 57.0, 58.3, 59.6, 60.9, 61.9, 62.5, 63.8, 63.4, 64.3]})\n",
    "df10b.index = pd.to_datetime(['1980','1990','2000','2001','2002','2003','2004',\n",
    "                              '2005','2006','2007','2008','2009'], format='%Y')\n",
    "df10b"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32223960",
   "metadata": {},
   "source": [
    "Huomaa, että alkupäässä havaintojen väli on eri mittainen kuin loppupäässä."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "68da3287",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 70.0)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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Yd955p77++mvVqVPH5/4BAACAcuV0SMe3SBtnejmdWVLq79JLDaXQ6lJkjBRVR4qsLUXWKeL32nm/x0jh0ZLFUvQ+vY123/y+FNOiYBQ5f0Q5M6Xo/YVHSw3ipPqXFvyp204KjSp4vr9969p/kV8UWFx33W52ZcmvRQAL2vAsScW8TQLef/7zH4WEhGj8+PGy2WwKDw/XM888o0GDBunkydKd+nD06FGNGTNGf/jDHy4Izjt27NDs2bM1duxYd7A9fPiw1q9fry+//FJ169aVJI0fP15Lly7V999/r8suu6zU/Re1/6SkJC1fvlxff/21ateuLckVprt166YdO3YoOjpaknT33XerRo0aklwj2oVPDw8PD9e9994ri8WiTp06KTY2Vvv375ckxcfH65577lG7du0kScOHD9e8efO0ZMkS/eUvfyl17wAAAEC5MAzp5G5p//fS/h+kAz8WH0SLk53q+nPmYOm2t9gKhenaBX8iakkb3leJN+9acFfR+7TapTptC4Xkjq6f1RsWH9Ql16ng17+SF9gt59XOe9z1k30/ZTyABG14tlgs+vzeXjqX4/1ubev3n9Yd/97gdbuZd16h7i1iStwm3G7VuXPnSt1nUZKSktSoUSPZbAVvnCZNmkhyheLS+OWXX3TVVVfpP//5jx555BHVrFnTvW7NmjXq0qWLvvjiC91+++0KDQ11nz7dtGlT93Y2m00NGzbU0aNHfQrPRe0/v+9bb73VY1ubzaYjR464w3PhUWK73e5xqnnt2rVlKfQ/ZEhIiHv90aNH9corr+i1115zr8/NzVXHjh1L3TcAAADgV8kHXUE5PzCffz1vWA2pXnvp8Drv+xr1iVQnVko/JWUk5f3J++/0In7PTpUMh5Se6PpTFuG1pMZdPENynbaSPaxs++swxHX99rInPUfbazRyBecgn+c5aMOz5ArQkaHen0KfNnXVsGa4fk/JLO4EAjWoGa4+berKZi15PNuXa54XLVqkxMREjR07VpIr7IWHh6tx48Y6duyYHA6HO0AfOnRIklS3bl0dOHBA2dnZHvtKTvY8PX3gwIF69dVXNWrUKD3//PN644033OvuuOMO3XPPPRo8eLDefvttPfbYY2rcuLG7Tps2bSRJDodDx44dc49El1ZR+69f33Xtwtdff+2xv71796pp06alHlEvToMGDTRu3DgNGjTIvezQoUPuUA4AAACUWllvopV2Mi8o54Xl5AOe6+3h0iU9pRZ9pRZ/kBpe5hqt/WdH76cztxng6qF2q9I9h9ysgpDtEbiTpEPrpP2rvO9j0GtS3PDS1SutDkOkdoPk2P+TDu5Yp2aX9pCtLDcpC0BBfcOw0rJZLXp2cAdJF57qnf/7s4M7eA3OvsrIyNCcOXOUmJiotLQ0LV++XB07dlS/fv0kSa+99poyMzN18uRJTZo0ST179lTjxo3VqlUrnTp1Sj///LMMw9DixYu1b98+j32HhITIZrPp5Zdf1sqVK/XVV195rIuKitKkSZM0Y8YMbdq0SfXq1VO/fv304osv6uTJk8rMzNRrr70mh8Ohq6++2qfnVdT+69evrz/84Q+aNGmSkpOTlZOTo+nTp2v48OE6e/bsRb+Wt956q6ZPn+5+HX788UcNGjRIGzZ4P6MAAAAAcPPlJlqZKdKur6SvJ0jTekmvtZbm/1XaNNsVnC02qUl3qe/j0u1LpScPSrctlvo8JjW5XLLZC05nllRsGinL6cz2MFfobhAntbraFYJ73CNd/ZTUd3zp9lFeN++y2qTmvZXc+BqpeeUIzlKQjzz74vqODTX9z131/NIEHU/JdC9vUDNczw7uUC7TVI0YMUI7d+7UkCFDlJWVpR49eujxxx9X9erV9e9//1uTJ092B+lrrrlGTzzxhCQpLi5O9913nyZMmKD09HRde+21GjBgQJE1WrVqpYceekjPP/+8Lr/8co91vXr10ogRI/Tkk09q8eLFevXVV/Xaa6/ppptuUkZGhjp37qxZs2YpOjpaaWlpPj+/ovb/+uuva9iwYUpLS1ObNm30wQcfqG7duu75o8vqjjvukGEYuv/++5WYmKj69evrf//3f3XNNddc1H4BAABQhXi7idYtH7iuH/4tb3T52H8lw+m5bf0418hyy36um1+FVfdet6JPZ252pWvflfjmXWawGP6ae+kiORwObd68WZ07d/a4FliSMjMztX//frVo0ULh4eEXV8dpaP3+00pMzVS96uHq3iLGpxFnwzCUkZGhyMhIj+tzEVj8+Z4BAlVJx00AqEhmHI+oSU2fOR15p097ufP1+WJaFYTl5n1c4foieqiw05ndXxRIRd68qzznllbwfE7xpc8qM/Kcz2a1qFer2ma3AQAAAEAq+/XHpWEYrvmIzxyW9iwvXXCOiJHa/DHvuuW+UnRT748prfzTmc9UU7Pmncv3dOZKfvMuM1S58AwAAAAgQCQskZY9KdvZY2opSZuUF+5eKV24c+RIZ4+6wnHK4YKf7v8+IjmyfOvphlelTiPK8GQCUCW+eZcZCM8AAAAAKp63649vne26EVbKkbwgfKggEOeH49TiruktzOKaozishnRql/e+qjco4xMKUBU52l3JEZ4BAAAAVCynw3U6cZHBN29ZUcG6KLYwqWYT1+nVNZtINS/J+++832s0luyhha555iZaKBvCMwAAAICKkZ4kHf+vtGNRKa4/zgu44TUvDMTRTV3LajaRoupK1lLMwJs/ZdRnt8l106wibqJVlimjUGUEVXgOkBuDIwjwXgEAACgDf968K/2UdGyzKywf2ywd3+I63doXQ96Wut7mfbvS4iZauAhBEZ5DQkIkSRkZGYqIiDC5GwSD7OxsSQro2+IDAAAElIu5eVfaSen45ryQnPfz7JGit41p5TqV+sAP3nuq1cKHJ1BK3EQLZRQU4dlmsyk6OlqJiYmSZOocy4ZhKCsrS1arlXmeA5TT6dTJkycVGRkpuz0o3uIAAADmKs3Nu/IDtC9BuXZrqWFnqVFn18+GnVynYZt9/TE30UIZBE2yaNDAdde7/ABtFsMwlJOTo5CQEMJzALNarbrkkkv4OwIAAPCmNDfvWvyAtPkT6fctrqmhiuIOyl1cYblBJym8RtHbcv0xglDQhGeLxaKGDRuqXr16ysnJMa0Ph8OhXbt2qXXr1pwSHMBCQ0NlLc2NIwAAAKq6g2u837wr66z061d5v1hcQTl/NNlbUC4O1x8jyARNeM5ns9lMDa0Oh0OSFB4eTngGAABA8DIM6eRuaXN86bbvNFLqervUIM73oFwcrj9GEPE5PJ85c0YvvfSSvv/+ezmdTl1xxRV67rnnVK9ePW3ZskUvvvii9u7dq1q1aum+++7TiBEjyqNvAAAAAL5KPijt/17a/4PrT9qJ0j+2yxip+VX+74nrjxEkfA7PDz30kGrWrKlvvvlGVqtVf//73/XMM8/o1Vdf1dixYzVu3DiNHDlSGzZs0AMPPKDY2Fh16tSpPHoHAAAAUJK0xLygnBeYkw94rreHS017SMf+6zo1u0jlfPMuIEj4FJ63b9+uLVu2aM2aNapWrZok6YUXXtDJkye1YsUKRUdHa/To0ZKkXr16afDgwYqPjyc8AwAAAL4qy5zLmSnSgdUFgTkxwXO9xSY1vlxq2U9q0U9qcoUUEl7obtsSN+8CiuZTeN66datat26tzz77TJ988onOnTunPn366Mknn9SePXvUtm1bj+1bt26tefPm+bVhAAAAoNIr7ZzLOeekw+uk3753heVj/5UMp+e+6sflheW+rtHjsOoX1uPmXYBXPoXnlJQU7d69Wx07dtTChQuVmZmpJ554Qk8++aTq1KmjiIgIj+3Dw8OVkZHhU0P5N+QKVPn9BXqfACo/jkcAAoUZx6NKXXPnUlnn3SHJUOFJN428OZedVz8ti+GU5cCP0uH1sjiyPB5uxLSS0byPjBZ9peZ9pMjanvsvrv/YQVKb6+U8sFqHd25Q0/ZXyNr8KteIczk/50r99xkAdatKzbLwpT+LYRhFTehWpA8//FBvvPGGNm3apLCwMEmu0ehbb71VN998s9LS0vTWW2+5t//oo480f/58LVq0qFRNb968udSNAwAAAJWO4VDcyj8pJPOkR3B2r5YuWJ4dXlupdbrqbJ2uSq3TRTkR9SqgUaBy6dy5s9fZlHwaeW7durWcTqdycnLc4dnpdJ0W0r59e3388cce2+/du1dt2rTxpYTi4uICegooh8Ohbdu2BXyfACo/jkcAAoUZx6NKW3P/j7Jlnix2dX5wNpr2ktHxFhnN+8hWu7WiLRZF+6mFSvvaBkBNs+pWlZplkd9nafgUnq+88ko1bdpUTz31lF5++WVlZWVp6tSpuvbaa3XjjTfqrbfe0syZMzV69Ght3LhRS5cu1bRp03xq3ux5nEsrWPoEUPlxPAIQKMw4HlWKmmePF9wNe/fXpXqIpftdssQN918PRagUr22A1jSrblWpWV58Cs8hISH66KOPNHnyZA0YMEBZWVnq37+/nn76adWoUUMzZszQpEmT9NZbbykmJkYTJ05Uz549y6t3AAAAIPhknJYO/FQQmE/96vs+qtX3f18ASuTzPM/169fX1KlTi1wXFxenuXPnXnRTAAAAQKWRnS4dXJsXlr+Xjm/VBdNBNersmjqq2VXS0nFS6u/nbVNoW+ZcBkzhc3gGAAAAqhxf5lzOzZaO/lIwfdSRXyRnjuc2ddu5po5q0U9qfpUUUatg3Q2v5s25bBFzLgOBg/AMAAAAlMTbnMtOh/T71ryw/IN0aK2Uc950rTUvkVrmheUWfaXqDYqvx5zLQEAiPAMAAADFSViSNwp83inUZ49Jn42RGl8uJe2TMs94ro+s4wrJLfu5AnOt5pKlqMmnitFhiNRukBz7f9LBHevU7NIespU02g2g3BGeAQAAgKI4Ha7R3yKvPc5zdKPrZ1gN1/XKLfNGlut18C0sF8Vqk5r3VvKZamrWvDPBGTAZ4RkAAAA4X/opad17nqdNF2fg69Lld0g2PloDlRn/hwMAAACZZ6WDawqmjzqxvfSPjYgmOANVAP+XAwAAoOrJyZQOr3MF5f3fS0c3SYbDc5tazaXkA973xZzLQJVAeAYAAEBw8WXaqHyOXOn4Zum3Va7AfHidlJvpuU2tFgU3+GreR4qMkf7ZUTp7XMy5DIDwDAAAgODhbdqofIYhJSa4gvJv30sHV0tZZz33Va1BwQ2+WvSVoi+5sN71rzDnMgBJhGcAAAAEi2KnjTruWj5wimQLcYXlAz9K6Sc9twuv6RpRbvkH1+hynTbe74jNnMsA8hCeAQAAEPhKnDYqb9lX4z0Xh0RKl/QqGF1u0Klso8TMuQxAhGcAAAAEg4NrSjdtVL1LpfaDXYG5cTfJHuqf+sy5DFR5hGcAAAAEpux06dBa13XLOxaV7jF9HpXihpdrWwCqJsIzAAAAAkNutnT0F9c1y/t/kI5skJw5vu2DaaMAlBPCMwAAAMzhdEjHtxTMtXzoZyknw3Obmk3zpo7qLa18Tko7IaaNAmAGwjMAAADKzpc5lw1DOrnbFZT3/+C6I3Zmiuc2kXVcN/fKv8lXrRYFd8QOjWLaKACmITwDAACgbEoz53LygbyR5bw/aSc89xFWwzWq3KKva4S5Xvvip49i2igAJiI8AwAAwHclzrk8xhWEkw9IZw56rreHS5f0dK1v0U9qeJlk8+EjKdNGATAJ4RkAAAC+cTqkr73Mubz/e9dPq11qfHleWO4rNe0u2cMurj7TRgEwAeEZAAAALrlZUlqilJ4opZ3M+5kopZ/0/Hn2qJSd5n1/1z4nXXGXFFa93FsHgPJGeAYAAKjMsjNKCMOFl5+UslK8788XNZsSnAFUGoRnAACAYJOVVkwgPnHhSHFpRogLs4ZI1epJUXXzftaTqtXN+5m3POWwtPgB7/tizmUAlQjhGQAAwGyGIWWdLcXocN7y8+dC9sYW5gqy7hB8XhguHJLDo4u/23U+p0P6bpLr5mDMuQygiiA8AwAAlAfDkM4llxyCC/90ZPm2/5DIkkeHCy8Pq+E9EPvCanNNR8WcywCqEMIzAABAaTmdeYG4FKPDaYmSM8e3/YdWL93ocFQ9Kaxa+TzH0mLOZQBVDOEZAABUbU6HlJHkZXQ4b3nGKcmZ69v+w2qWEIjrF/x3VF0pNLJ8nmN5Yc5lAFUI4RkAAFQ+jlxX0C0cfNNOFD1SnJEkGU7f9h9Rq4hR4SJGh6PqSiHh5fMcAwVzLgOoIgjPAAAgOORmu8JvaaZdyjitom9kVRyLFBlTEIhLuo44so5kDy2vZwkACFCEZwAAYJ6czCLC8HlzD+cvzzzj274tVlfQ9TY6nB+IbXwsAgAUj38lAACAf2VneBkdLrQs66xv+7baC64P9naX6cgYTiEGAPgN4RkAAJTMMKTstNLdXTr9pGtbX1hDSh4VLnxjrfBoyWotl6cJAEBJCM8AAFRFhuEa9U0r6lTpIkJy7jnf9m8PPy8ElzDtUni0f+cgBgCgHBCeAQCoLAwjbw7iUowOpyVKjizf9h8SeWHwrVb/vGV54TisOoEYAFCpEJ4BAAhkTqd07nTpRofTT0rOHN/2H1q9dKPDUfWksGrl8xwBAAgChGcAACqa0+GaW/iCQHziwrtMp5+SDIdv+w+rWWi6JS831gqJKJ/nCABAJUN4BgDAHxw5rqBbqjmIkyTD6dv+I2oVMSpcRDCOqiuFhJfPcwQAoAojPAMAUJzc7JJDcOHl5077uHOLFFm7dKPDkXUke2i5PEUAAFA6hGcAQNWSk1lEAE70PF067YTrvzNTfNu3xeoKukWNDp9/Y63I2pKNf4YBAAgW/KsNAAh+2emln4M466xv+7baXaHX2+hwVD0pMkay2srnOQIAAFMRngEAgccwpOy0QsH3RNFTLeWH5Jx03/ZvDSkUfOuXcJfpeq45iK3WcnmaAAAgeBCeAQAVwzBcp0F7HR3OW557zrf928PPGxUuYdql8GjmIAYAAD4hPANAMHI6pAM/qdbRdVJ0mtSitzmnCxuGdC65UOgt7tTpvDmIHVm+7T8kqpgQfN7ocFRdKaw6gRgAAJQbwjMABJuEJdKyJ2U7e0wtJWmTpBqNpOtfkToMufj9O52uO0cXNTp8fkhOPyk5c33bf2j1kkeHC99YKzTq4p8PAACAHxCeASCYJCyRPrtNkuG5/Oxx1/JbZxcdoJ2OQnMQlzQ6nOjaznD41ld4zeJPkT5/eUhEmZ8+AACAWQjPABAsnA5p2ZO6IDhLBcsWPyAdXCNlnPIMyRlJxTyuBBG1CoJviXeZrivZwy7yyQEAAAQ2wjMABIuDa6Szx0reJuustG56MSstrrmFSzM6HFVXsoX4/SkAAAAEK8IzAAS63Gzpt1XS6n+Wbvs2A6TmvYuYg7i2ZOOwDwAAUBZ8igKAQJSTKe37VkpYLO3+WspKKf1jr3xIatGn/HoDAACoggjPABAosjOkvStdgfnXZVJ2WsG6ag2k9jdKOxaVcP2yxXXX7WZXVlDDAAAAVYfP4fmrr77S+PHjFRZWcHOYa6+9VlOmTNGWLVv04osvau/evapVq5buu+8+jRgxwq8NA0ClkpUm7VnuCsx7vpFyMgrW1WgsdRjq+tOku2S1Si365d1t2yLPAJ03v/H1k82Z7xkAAKCS8zk8b9u2TUOHDtXLL7/ssTwlJUVjx47VuHHjNHLkSG3YsEEPPPCAYmNj1alTJ781DABBLzNF+jUvMO9dKeVmFqyLviQvMA+TGnV1BebCOgxxTUe17EnPm4fVaOQKzv6Y5xkAAAAXKFN4vuGGGy5YvmLFCkVHR2v06NGSpF69emnw4MGKj48nPAPAuWTXtcsJi13XMjuyC9bFtHSF5Q5DpYaXSRZLyfvqMERqN0iO/T/p4I51anZpD9la9GbEGQAAoBz5FJ6dTqd27NihiIgIffDBB3I4HOrXr5/Gjx+vPXv2qG3bth7bt27dWvPmzfOpIYfD4dP2FS2/v0DvE0AAyEiSZfdXsuxcIu3/XhZnrnuVUbuNjA5DZbQfKtXrUBCYnc5S797RtJeSz1RTk6ZxrjO4OS4BMIkZn4+oSc1grGlW3apSsyx86c9iGEZRd50p0qlTp/S3v/1NN910kwYNGqTk5GQ9+eSTioiIUN26dZWTk6NXX33Vvf3nn3+u9957T998802pmt68eXOpGweAQGTPOq3o46tV6/gPqp70X1mMgjCcUb2lzjTqq+SGfZVZvbl5TQIAAMBD586dZbOVfBafTyPPderUUXx8vPv3iIgIPf7447r11lt18803KzMz02P7zMxMRUVF+VJCcXFxXps2k8Ph0LZt2wK+TwAVKPW4LLu+cI0wH1rrEZiNBp1ktB8io91ghdVpo/qS6vupLMcjAIHCjOMRNakZjDXNqltVapZFfp+l4VN43rVrl7744gs99thjsuSdYpidnS2r1apOnTpp1qxZHtvv3btXbdq08aWEbDZbQL+4+YKlTwDlJOWIlLDEdQ3z4XXyuPN148ul9kOkDkNkiWkpL1cwXzSORwAChRnHI2pSMxhrmlW3qtQsLz6F5+joaMXHx6tmzZq68847lZiYqClTpuimm27SgAED9Prrr2vmzJkaPXq0Nm7cqKVLl2ratGnl1TsAVKzkAwWB+egvnuua9nDd8Kv9YNcdswEAAFCp+BSeGzRooHfffVdvvPGGpk+frrCwMA0aNEiPP/64wsLCNGPGDE2aNElvvfWWYmJiNHHiRPXs2bO8egeA8pe0T0pY5ArNxzcXWmGRml1ZEJhrNDKpQQAAAFQEn6eq6t69u+bOnVvkuri4uGLXAUDQOLnbNbqcsFg6sb1gucUqNe/tCsztBkvV/XX1MgAAAAKdz+EZACodw5ASEwoC88ldBessNqllv7zAfKMUVce8PgEAAGAawjOAqskwpN+3FgTmpL0F66whUqv+UochUuxAKTLGvD4BAAAQEAjPAKoOw5CObSoIzMkHCtbZwqTW17pGmNsOkCKizeoSAAAAAYjwDKByczqlIxuknXl3yU45XLDOHiG1ua4gMIdVN69PAAAABDTCM4DKx+mQDv3sCss7l0ipxwvWhUS5gnKHoa7gHBplXp8AAAAIGoRnAJWDI1c6uDovMC+V0hML1oVWl2JvcAXm1tdIIRHm9QkAAICgRHgGELwcOdL+H1yBedcXUkZSwbrwmlLsIFdgbnW1ZA8zr08AAAAEPcIzgOCSmyX99n1BYM48U7AuIkZqf6MrMDfvK9lDTWsTAAAAlQvhGUDgy8mU9v1HSlgi7f5aykopWBdVV2o/2BWYm/WWbBzWAAAA4H98ygQQmLIzpL3fuEaYf10uZacVrKvWwDUHc4eh0iW9JKvNvD4BAABQJRCeAQSOrDRpz3JXYN7zjZSTUbCuRmNXWO4wVGrSXbJazesTAAAAVQ7hGYC5MlNcI8sJi6W9K6XczIJ10ZfkBeZhUqOuBGYAAACYhvAMoOKdS3Zdu5ywWNr3reTILlgX09IVljsMlRpeJlksprUJAAAA5CM8A6gY6Umuu2PvXCL9tkpy5hasq9O2IDDXv5TADAAAgIBDeAZQftISpZ1LXSPMB36SDEfBunqXFlzDXK+deT0CAAAApUB4BuBfZ48XBOaDqyUZBesaXuYKy+2HSnVam9YiAAAA4CvCM4CLd+ZwQWA+/LPnusaX5wXmIVJMC3P6AwAAAC4S4RlA2Zze77p+OWGJdPQXz3VNe+QF5sGuO2YDAAAAQY7wDKD0kvZJCYtcI8zHtxRaYZGaXVkQmGs0MqtDAAAAoFwQngGU7ORuV1hOWCyd2F6w3GKVmvd2BeZ2g6Xq9c3rEQAAAChnhGcAngxDSkwoCMwndxWss9qlFv2kDkOkdjdKUXXM6xMAAACoQIRnAK7A/PvWgsCctLdgnTVEatXfNcIce4MUGWNenwAAAIBJCM9AVWUY0tFNrmuYdy6Rkg8UrLOFSa2vdQXmtgOkiGiTmgQAAAACA+EZqEqcTunIBtfo8s4lUsrhgnX2CKnNdQWBOay6eX0CAAAAAYbwDFR2Tod06OeCwJx6vGBdSJQrKHcY6grOoVHm9QkAAAAEMMIzUBk5cqWDq/MC81IpPbFgXVgN17XL7YdIra+RQiLM6xMAAAAIEoRnoLJw5Ej7f3AF5l1fSBlJBevCa7rujt1hqNTyD5I9zLQ2AQAAgGBEeAaCWW6W9NuqvMD8pZR5pmBdRIzUPi8wN+8r2UPN6hIAAAAIeoRnINjknJP2fesKzLu/lrLOFqyLqiu1H+wKzM16Szb+FwcAAAD8gU/WQDDIzpD2fuMKzL8ul7LTCtZVayB1GOIKzJf0kqw28/oEAAAAKinCMxCoslKlPStcgXnPN1JORsG6Gk1cYbnDEKlJd8lqNa9PAAAAoAogPAOBJDPFNbKcsFjau1LKzSxYF90sLzAPkxp3lSwW09oEAAAAqhrCM2C2jNOua5cTFku/fSc5sgvWxbR0heUOQ6WGlxGYAQAAAJMQngEzpCe5ppNKWCzt/15y5hasqxObN8I8VKp/KYEZAAAACACEZ6CipCVKO5e6AvOBnyTDUbCu3qUFgbleO/N6BAAAAFAkwjNQns4eLwjMB1dLMgrWNbzMFZbbD5XqtDatRQAAAADeEZ4BfztzWNq5xBWYD6/zXNf48rzAPESKaWFOfwAAAAB8RngG/OH0/oLAfHSj57qmPfIC82Ap+hJz+gMAAABwUQjPQFkl7ZMSFrkC8/EthVZYpGZXFgTmGo3M6hAAAACAnxCeAV+c3O0KywmLpRPbC5ZbrFLzPq7A3O5GqXp983oEAAAA4HeEZ6AkhiElJhQE5pO7CtZZ7VKLfnmBeZAUVce8PgEAAACUK8IzcD7DcJ2GnR+YT+8rWGcNkVr1dwXm2BukyBjz+gQAAABQYQjPgOQKzEc3FVzDfOZgwTpbmNT6WldgbjtAiog2q0sAAAAAJiE8o+pyOqUjG1xheecSKeVwwTp7hNTmuoLAHFbdvD4BAAAAmI7wjKrF6ZAO/VwQmFOPF6wLiZJir3cF5tbXSqFR5vUJAAAAIKAQnlH5OXKlg6vzAvNSKT2xYF1YDde1yx2Guq5lDokwr08AAAAAAYvwjMrJkSPt/94VmHd9KWUkFawLr+maTqrDUKnlHyR7mGltAgAAAAgOhGdUHrlZ0m+rCgJz5pmCdRExUvu8wNy8r2QPNatLAAAAAEGoTOHZ4XDojjvuUOPGjTV58mRJ0pYtW/Tiiy9q7969qlWrlu677z6NGDHCr80CF8g5J+371hWYd38tZZ0tWBdVV2o/2BWYm/WWbHxXBAAAAKBsypQm3nnnHf3yyy9q3LixJCklJUVjx47VuHHjNHLkSG3YsEEPPPCAYmNj1alTJ782DCg7Xdq70hWYf10uZacVrKveUGo/xBWYL+kpWW3m9QkAAACg0vA5PK9du1YrVqzQH//4R/eyFStWKDo6WqNHj5Yk9erVS4MHD1Z8fDzhGf6RleoKygmLpT3fSLnnCtbVaOIKyx2GSk2ukKxW8/oEAAAAUCn5FJ6TkpL09NNPa9q0aZo5c6Z7+Z49e9S2bVuPbVu3bq158+b53JDD4fD5MRUpv79A77NSyDwry6/LZNm5RNr3H1kcWe5VRnQzGe2HyGg/RGrUVbJY8lYYEn83qCI4HgEIFGYcj6hJzWCsaVbdqlKzLHzpr9Th2el06vHHH9edd96pdu3aeaxLT09XRITnFD/h4eHKyMgodSP5tm3b5vNjzBAsfQYbW/ZZRZ9Yo+hjP6jGqY2yOnPc6zKjGiu5YT8lN+yrczXbuALzSUknt5jXMBAAOB4BCBRmHI+oSc1grGlW3apSs7yUOjy/++67Cg0N1ZgxYy5YFxERodTUVI9lmZmZioqK8rmhuLg42WyBe52qw+HQtm3bAr7PoJKRJMvuL10jzPt/kMWZ615l1GmbN8I8VCH1OqiexaJ6JrYKBBKORwAChRnHI2pSMxhrmlW3qtQsi/w+S6PU4Xnx4sVKTExUt27dJLnCsSStXLlSTzzxhFavXu2x/d69e9WmTZvS7t7NZrMF9IubL1j6DFhpidLOpa5rmA/8JBmFTpeo39F1/XL7IbLUayeLeV0CQYHjEYBAYcbxiJrUDMaaZtWtKjXLS6nD87Jlyzx+nzBhgiRp8uTJSk5O1pQpUzRz5kyNHj1aGzdu1NKlSzVt2jT/dovgdvZYQWA+uEaSUbCu4WV5gXmoVKe1aS0CAAAAQFH8MvFtrVq1NGPGDE2aNElvvfWWYmJiNHHiRPXs2dMfu0cwO3NY2rnEFZgPr/Nc1/hy9wizYlqY0x8AAAAAlEKZw/PkyZM9fo+Li9PcuXMvuiFUAqf3FwTmoxs91zXtkReYB0vRl5jTHwAAAAD4yC8jz4BO7ZV2LnYF5uOF735tkZpdWRCYazQyrUUAAAAAKCvCM8oucVfBCPOJ7QXLLVapeR9XYG53o1S9vnk9AgAAAIAfEJ5ReoYhndjhCssJi6VTuwvWWe1Si355gXmQFFXHvD4BAAAAwM8IzyiZYbhOw84PzKf3Fayzhkit+rsCc+wNUmSMeX0CAAAAQDkiPONChiEd3SQlLHIF5jMHC9bZwqTW1+YF5uul8JqmtQkAAAAAFYXwDBenUzqyXkrIu4b57JGCdfYIqe0fXYG5zR+lsOrm9QkAAAAAJiA8V2VOh3RorSss71wqpR4vWBcS5RpZ7jDUNdIcGmVenwAAAABgMsJzVePIlQ7+VBCY008WrAur4bp2ucNQ17XMIRHm9QkAAAAAAYTwXBU4cqT93+cF5i+kc6cL1oXXdE0n1WGo1PIPkj3MtDYBAAAAIFARniur3Czpt1WuwLzrSynzTMG6yNqu6aQ6DJWa95XsoWZ1CQAAAABBgfBcmeSck/b+R9q5RNr9tZR1tmBdVD2p/WBXYG52lWTjrx4AAAAASosEFeyy06U937hGmH9dLuWkF6yr3lBqP8QVmC/pKVlt5vUJAAAAAEGM8ByMslJdQTlhsSs4554rWFejiSssdxgqNblCslrN6xMAAAAAKgnCc7DITJF2L3MF5r0rJUdWwbroZnmBeZjUuKtksZjWJgAAAABURoTnQJZx2nXtcsJiad+3kjOnYF1Mq4IR5oaXEZgBAAAAoBwRngNN+ilp1xdSwhLX9FLO3IJ1ddsVBOZ6HQjMAAAAAFBBCM+BIPWEtGupa4T5wE+S4SxYV7+jKyy3HyLVa2dejwAAAABQhRGezXL2mLQzLzAfXCPJKFjX8LK8wDxUqtPatBYBAAAAAC6E54p05rBrDuaExdLhdZ7rGl9eMMIc08Kc/gAAAAAARSI8l7fT+wsC89GNnuua9sgLzIOl6EvM6Q8AAAAA4BXh2RdOh3TgJ9U6uk6KTpNa9Jastgu3O7VX2rnYFZiPbym0wiI1uyovMN8o1WhUYa0DAAAAAMqO8FxaCUukZU/KdvaYWkrSJrnC7/WvSB2GSIm7XGE5YbGUuKPgcRar1LyPKzC3u1GqXt+kJwAAAAAAKCvCc2kkLJE+u00eN/WSXDf9+myMVL2RlHqsYLnVLrXolxeYB0lRdSq0XQAAAACAfxGevXE6pGVP6oLgXFjqMclil1pf4wrMsTdIkTEV1iIAAAAAoHwRnr05uMY1wuzN/8RLsdeXfz8AAAAAgApnNbuBgJd2onTbZaeVbx8AAAAAANMQnr2pVsobfJV2OwAAAABA0CE8e9PsyrwppSzFbGCRajR2bQcAAAAAqJQIz95Yba7pqCRdGKDzfr9+ctHzPQMAAAAAKgXCc2l0GCLdOluq0dBzeY1GruUdhpjTFwAAAACgQnC37dLqMERqN0iO/T/p4I51anZpD9la9GbEGQAAAACqAMKzL6w2qXlvJZ+ppmbNOxOcAQAAAKCK4LRtAAAAAAC8IDwDAAAAAOAF4RkAAAAAAC8IzwAAAAAAeEF4BgAAAADAC8IzAAAAAABeEJ4BAAAAAPCC8AwAAAAAgBeEZwAAAAAAvCA8AwAAAADgBeEZAAAAAAAvCM8AAAAAAHhBeAYAAAAAwAvCMwAAAAAAXhCeAQAAAADwgvAMAAAAAIAXPofntWvXasSIEeratauuuuoqvfDCC8rMzJQkbdmyRSNGjFCXLl3Uv39/ff75535vGAAAAACAiuZTeD59+rTuuecejRo1Sr/88osWLlyo9evX67333lNKSorGjh2rYcOGacOGDZo0aZJefvllbd26tbx6BwAAAACgQth92TgmJkZr1qxRtWrVZBiGzpw5o6ysLMXExGjFihWKjo7W6NGjJUm9evXS4MGDFR8fr06dOpVL8wAAAAAAVASfT9uuVq2aJKlfv34aPHiw6tatq5tvvll79uxR27ZtPbZt3bq1du3a5Z9OAQAAAAAwiU8jz4WtWLFCKSkpGj9+vMaNG6f69esrIiLCY5vw8HBlZGT4tF+Hw1HWlipEfn+B3ieAyo/jEYBAYcbxiJrUDMaaZtWtKjXLwpf+LIZhGBdTbOvWrRoxYoTGjBmjxMREvfXWW+51H330kebPn69FixZ53Y/D4dDmzZsvphUAAAAAAHzWuXNn2Wy2ErfxaeR506ZNeuqpp7RkyRKFhoZKkrKzsxUSEqLWrVtr9erVHtvv3btXbdq08anpuLg4r02byeFwaNu2bQHfJ4DKj+MRgEBhxvGImtQMxppm1a0qNcsiv8/S8Ck8x8bGKjMzU6+//roee+wxnTx5Uq+88oqGDx+uAQMG6PXXX9fMmTM1evRobdy4UUuXLtW0adN8at5mswX0i5svWPoEUPlxPAIQKMw4HlGTmsFY06y6VaVmefEpPEdFRemDDz7QSy+9pKuuukrVq1fX4MGD9cADDyg0NFQzZszQpEmT9NZbbykmJkYTJ05Uz549y6t3AAAAAAAqhM83DGvdurVmzJhR5Lq4uDjNnTv3opsCAAAAACCQ+DxVFQAAAAAAVQ3hGQAAAAAALwjPAAAAAAB4QXgGAAAAAMALwjMAAAAAAF4QngEAAAAA8ILwDAAAAACAF4RnAAAAAAC8IDwDAAAAAOAF4RkAAAAAAC8IzwAAAAAAeEF4BgAAAADAC8IzAAAAAABeEJ4BAAAAAPCC8AwAAAAAgBeEZwAAAAAAvCA8AwAAAADgBeEZAAAAAAAvCM8AAAAAAHhBeAYAAAAAwAvCMwAAAAAAXhCeAQAAAADwgvAMAAAAAIAXhGcAAAAAALwgPAMAAAAA4AXhGQAAAAAALwjPAAAAAAB4QXgGAAAAAMALwjMAAAAAAF4QngEAAAAA8ILwDAAAAACAF4RnAAAAAAC8IDwDAAAAAOAF4RkAAAAAAC8IzwAAAAAAeEF4BgAAAADAC8IzAAAAAABeEJ4BAAAAAPCC8AwAAAAAgBeEZwAAAAAAvCA8AwAAAADgBeEZAAAAAAAvCM8AAAAAAHhBeAYAAAAAwAvCMwAAAAAAXhCeAQAAAADwgvAMAAAAAIAXhGcAAAAAALzwKTzv2rVLd955p7p3766rrrpKTzzxhE6fPi1J2rJli0aMGKEuXbqof//++vzzz8ulYQAAAAAAKlqpw3NmZqbuuusudenSRT/99JO++OILnTlzRk899ZRSUlI0duxYDRs2TBs2bNCkSZP08ssva+vWreXZOwAAAAAAFaLU4fnYsWNq166dHnjgAYWGhqpWrVoaOXKkNmzYoBUrVig6OlqjR4+W3W5Xr169NHjwYMXHx5dn7wAAAAAAVIhSh+eWLVvqgw8+kM1mcy9bvny5Lr30Uu3Zs0dt27b12L5169batWuX/zoFAAAAAMAk9rI8yDAM/fOf/9R3332nOXPmaPbs2YqIiPDYJjw8XBkZGT7v2+FwlKWlCpPfX6D3CaDy43gEIFCYcTyiJjWDsaZZdatKzbLwpT+fw3NaWpr+/ve/a8eOHZozZ45iY2MVERGh1NRUj+0yMzMVFRXl6+61bds2nx9jhmDpE0Dlx/EIQKAw43hETWoGY02z6laVmuXFp/B86NAh3X333WrUqJHmzZunmJgYSVLbtm21evVqj2337t2rNm3a+NxQXFycx6nhgcbhcGjbtm0B3yeAyo/jEYBAYcbxiJrUDMaaZtWtKjXLIr/P0ih1eE5JSdHtt9+unj17atKkSbJaCy6Xvu666zRlyhTNnDlTo0eP1saNG7V06VJNmzbN5+ZtNltAv7j5gqVPAJUfxyMAgcKM4xE1qRmMNc2qW1VqlpdSh+cFCxbo2LFj+vrrr7Vs2TKPdf/97381Y8YMTZo0SW+99ZZiYmI0ceJE9ezZ0+8NAwAAAABQ0Uodnu+8807deeedxa6Pi4vT3Llz/dIUAAAAAACBpNRTVQEAAAAAUFURngEAAAAA8ILwDAAAAACAF4RnAAAAAAC8IDwDAAAAAOAF4RkAAAAAAC8IzwAAAAAAeEF4BgAAAADAC8IzAAAAAABeEJ4BAAAAAPCC8AwAAAAAgBeEZwAAAAAAvCA8AwAAAADgBeEZAAAAAAAvCM8AAAAAAHhBeAYAAAAAwAvCMwAAAAAAXhCeAQAAAADwgvAMAAAAAIAXhGcAAAAAALwgPAMAAAAA4AXhGQAAAAAALwjPAAAAAAB4QXgGAAAAAMALwjMAAAAAAF4QngEAAAAA8ILwDAAAAACAF4RnAAAAAKikHE5DP/+WpB8PndPPvyXJ4TTMbilo2c1uAAAAAADgf8u2H9fzSxN0PCXTtWDdBjWsGa5nB3fQ9R0bmttcEGLkGQCCEN8iAwAQfCry3+9l24/rvjmbCoJznt9TMnXfnE1atv14udWurJ9TGHkGgCDDt8gAAkn+h+QNh84ps0aSeraqK5vVYnZbQInMeN9W5L/fDqeh55cmqKjIakiySHp+aYKu69DA78+7Mn9OITwDQBDJ/xb5/H8M879Fnv7nrkH/DxOA4GHWh2QCe/kx47Wt6JpmvG/98e+3YRhKz3YoNTNHZ8/lKjUzR6mZuTqbmaOzmbkey387lX7BiLPHviQdT8nUs0u2q+sltVQrKlS1o0JVKzJUtauFKiLEJovF97+Dyv45xWIYRkCMoTscDm3evFmdO3eWzWYzu51iBUufAIKbYRjKdRpyOPN+Ogxl5Tp049s/KTE1q9jH1asepk/H9pLd5voHz2KRLBaLLPn/LUveT0nn/X7+drKo2HX5/56ev0+P7crwjy6A4FHch+T8//PL60PyBcFHqrjAvu+kNmz/VVd0bFtxobICa5rx2lZ0TTPet7kOp3q/8q1+P1v8v981wu26rVczpWU5dDY/FJ8rCMepeeG4os5+DrNbFRMV6vGnVmRewI4q+Jm/LjoiRBaLRb1f+bbY0G6R1KBmuH56sn9AfdnlS74jPPsoWPoEKgtXeHR6hMiCUFmwPNdx3nZ5yy54vNNQjuO87ZyGHA6n5+9OQ7lFLcvfl8Pwss+ie8kp8vEX1qks1waVGMxVfPhW4d+L2Ic8HnPhPty1S9i/tdgvBAp/AXD+Fw6FH1PK51XS/ot5XtYiHq8ia57/mhXzuvjymp2/3Xn7t3p9XS58fLH79va6lGb/hV4bq8XzNSt6356P93xdLvy7L/p19/Il1Hn7t1qKfvwFr4sv/Z2/jzJ+SWaxlmLfRTzeaRjq8+p3Ff4huSoF9qoQKiu6psNplBjuJKlu9TB9eHs3Zec6dS7HoXPZDs+fOQ5lZjuUUfj3vPUZ2Xn/nVPoMXnL/fmvut1qUY2IEFUPt6t6uF01wvP/O8T930npWZrz8yGv+7qyVW3ZrBadTs/W6fRsJaVnKzvX6XNPFosUGWpTepbD67af3N1TvVrV9rlGeSE8lxMzvnEEpKJHIS8IZ0WGPecFIS9/eU5x4c1Ryu08gqyzUIAtOgwW7scjYDrO38bzuQXGESq4hNgsslktMgzXaVkyJEOG+3fDMPJ+mtsngMqvfYPqql8zXJGhNoWH2BSR/yfv98hQz98j8paF5y0rvL3daqkygT3QQmVxr23+l8f5n0Fy8j6f5DoMZTtcP4tbn5Xj0ISF23QmI6fYvqqH2XX7lc2U65T7M05O/n7dnylc+83xUi/b4VR6Vq6SS6hntj5t6qhTk5oeITg/JNdwh+QQhYdYvZ7dlf93+ntKZpHBvbi/U8MwlJHtcIfp0xnZSs7/70J/kjNcQTs5PVtnzuX49Jnizf/prKGdG5f+AeXMlxzKNc+lVJkvfA8WhmHIacjrKGROMaONRY1CFjlaWcQopOuxpRuFzC0ysF7YS24JgbWyjkL6k93qCoj5P0Ns1oLfbRbZrVaP9e6fNut5y6yFHuO5PD+EemznUaNgud1WzHZ56wovD7EVs53VekEfhfvdsP+0/vTBOq+vzey/9PDpG13DKDpY5wdunff7BQG8hHWGa+UF+zQkOfPe1yXu22N5oe186e/8fZSyv/ztCj8/p1HK/vIef0FvJey7qH2ocK8efRez/wvqlXLfRTxehXstYh/S+T15bud+bUqz/0LPy2nkryv+8Z6veylelwuee0nv2WJem2L2X/g9UfRzKnh8qV+z87crzf69PC+z7Pw9VTt/T62QWoZc13DeMn216lYPV0jevwV2m0UhVqtC7K7fQ2yuY2tI/jHWZlGozeo+5hZ+nN1i0cTF21XUS5i/7OmF2xUdGeq3wO5wGnp6Yck1/75gm85lO+Q0pByHUzn5X6AXCpU5+eGxiNCZvzw/XJ5KzSrV9bGdnlsuQ3Lvp7zfW6lZuXrnu33lW6QINSLsiokMdX+Jk/8lj8cXPIW+3LngC5/zfiYcP6v75mzyWvf+P7T224iszWrRs4M76L45m2SRPN5P+e/UZwd3uOB9a7FYFBVmV1SYXU1jIktVK9fhVMq5HH23K1Hj5231un296uGlexIBiJHnUjDrFKHilGYUssjTUosIdcVuV0SoK3JUs4hRSHco9OMoZP528GS1qPgw6A5txYXBIgJmoVBn93h8UUHU6rF/V6AsJhAWCpwh+b+Xohd7kcHW6j4Fsqop67fIACAVfBHi9MOXZBv2J+meUoSBcde0VtNakSWe9pp/mmtG3imuhX/PzHEox8G//8HE40uLvM8FIbaCLy3yfz+bmaODSRle99enTR21qVddIXbXZ4jC+z3/y47QvC9DivuSZNexs3pq0XavNf19WrGZ/35X5On/wfo5hZFnP/J2m3dJeuyzLVqzL0lOo/CoYkmnzZ4fdEs+bfb80Uoy5IVCSgp5hUNYEaOARQXPC0YRixiVLHYUsYTRyguDbvH9eIykFjEqabNYZA2gAw/KX1m/RQYAqeB6bKsu/hhxbYcGalgz3OuH5L9d0/aij0k5Dqcycxz6ac8p3RfvPbDf07elLqkd6fUU3sKn/OZeMHprKCfXqRNnM/XbqXSvNetVD1O1MP98rE7Lyi3xxpD52tSrpobREXnhMD+gXhgqXSHS9d+h9qJD58GkdP2rFCO8r424TFc0r3VBKM0PtXarpdRfbq/dl6RR7//sdTt/jsZe1iRab3+31+v7tnuLGL/Uy2fmv9/Xd2yo6zo0qJBLT6vC5xTCsxfr958u8TQWSUrPdmj22oMV1FHxbKUKg4UCZjEjf8UG0SKWlxhEbSUEzBJ6sZ83olnU6KV7v1YrARJVyvUdG2r6n7te8C1yAy4jAVCBKvJDcn4o/OOlpQvsT1zfzm8fzksb8N78ny5+C3ilrfmPoR39VtPhNLRg01Gvr+1NXRr77bXt3iKmVH+f/gyyZodYs/79tlkt6tmytsLPRqhzy9rlGl4r++cUwrMXiaklB+d8AzrUV/tGNYo8bfbCUc+Sro08/7HFh87zA2ZVPI0VqIoq8ltkAChORX9INiP4mBHwqkqoNCvImhnuqsq/35X5eRKevSjtBe13XNUioG65DqByq8hvkQGgOBX9IbkqBPaqFCrNCrJmhruq8u93ZX2ehGcvzPj2DwAAIFhU9Ifkyh7YzaqZX7eiQ6VZQbayhjuUL8KzF1XhwncAAIBgUtkDu1k1JXNCJUEWwcJqdgPBIP/bvwY1PU/hblAzvMKnqQIAAEDFyw94fS6JUM8KDpUVWRNA8Rh5LqXKfOE7AAAAAKBkhGcfcEoJAAAAAFRNnLYNAAAAAIAXhGcAAAAAALwgPAMAAAAA4EWZw/Pp06d13XXXad26de5lW7Zs0YgRI9SlSxf1799fn3/+uV+aBAAAAADATGUKzxs3btTIkSN16NAh97KUlBSNHTtWw4YN04YNGzRp0iS9/PLL2rp1q9+aBQAAAADADD6H54ULF2r8+PF65JFHPJavWLFC0dHRGj16tOx2u3r16qXBgwcrPj7eb80CAAAAAGAGn6eq6t27twYPHiy73e4RoPfs2aO2bdt6bNu6dWvNmzfPp/07HA5fW6pQ+f0Fep8AKj+ORwAChRnHI2pSMxhrmlW3qtQsC1/68zk8161bt8jl6enpioiI8FgWHh6ujIwMn/a/bds2X1syRbD0CaDy43gEIFCYcTyiJjWDsaZZdatKzfLic3guTkREhFJTUz2WZWZmKioqyqf9xMXFyWaz+astv3M4HNq2bVvA9wmg8uN4BCBQmHE8oiY1g7GmWXWrSs2yyO+zNPwWntu2bavVq1d7LNu7d6/atGnj035sNltAv7j5gqVPAJUfxyMAgcKM4xE1qRmMNc2qW1Vqlhe/zfN83XXX6dSpU5o5c6ZycnL0888/a+nSpbrlllv8VQIAAAAAAFP4LTzXqlVLM2bM0LJly9SjRw9NnDhREydOVM+ePf1VAgAAAAAAU1zUadu7d+/2+D0uLk5z5869qIYAAAAAAAg0fht5BgAAAACgsiI8AwAAAADgBeEZAAAAAAAvCM8AAAAAAHhBeAYAAAAAwAvCMwAAAAAAXhCeAQAAAADwgvAMAAAAAIAXhGcAAAAAALwgPAMAAAAA4AXhGQAAAAAALwjPAAAAAAB4QXgGAAAAAMALwjMAAAAAAF4QngEAAAAA8ILwDAAAAACAF4RnAAAAAAC8IDwDAAAAAOAF4RkAAAAAAC8IzwAAAAAAeEF4BgAAAADAC8IzAAAAAABeEJ4BAAAAAPCC8AwAAAAAgBeEZwAAAAAAvCA8AwAAAADgBeEZAAAAAAAvCM8AAAAAAHhBeAYAAAAAwAvCMwAAAAAAXhCeAQAAAADwgvAMAAAAAIAXhGcAAAAAALwgPAMAAAAA4AXhGQAAAAAALwjPAAAAAAB4QXgGAAAAAMALwjMAAAAAAF4QngEAAAAA8ILwDAAAAACAF4RnAAAAAAC8IDwDAAAAAOAF4RkAAAAAAC8IzwAAAAAAeEF4BgAAAADAC8IzAAAAAABeEJ4BAAAAAPCC8AwAAAAAgBd+Dc9JSUm6//771a1bN/Xo0UOTJk1Sbm6uP0sAAAAAAFDh/BqeH374YUVGRurHH3/UvHnztHbtWs2cOdOfJQAAAAAAqHB+C88HDx7U+vXr9fjjjysiIkJNmzbV/fffr/j4eH+VAAAAAADAFHZ/7WjPnj2Kjo5W/fr13ctatWqlY8eO6ezZs6pRo0aJjzcMQ5KUnZ0tm83mr7b8zuFwSAr8PgFUfhyPAAQKM45H1KRmMNY0q25VqVkW+X3m59GSWIzSbFUKixcv1tSpU7Vq1Sr3skOHDum6667T999/rwYNGpT4+OzsbG3bts0frQAAAAAAUGpxcXEKDQ0tcRu/jTxHRkbq3LlzHsvyf4+KivL6eLvdrri4OFmtVlksFn+1BQAAAABAkQzDkNPplN3uPRr7LTy3adNGZ86c0alTp1SnTh1J0r59+9SgQQNVr17d6+OtVqvXpA8AAAAAgBn8dsOw5s2b6/LLL9dLL72ktLQ0HT58WNOmTdPw4cP9VQIAAAAAAFP47ZpnSTp16pT+8Y9/aN26dbJarRo2bJjGjx8f0BeIAwAAAADgjV/DMwAAAAAAlZHfTtsGAAAAAKCyIjwDAAAAAOAF4RkAAAAAAC8IzwAAAAAAeEF4BgAAAADAC8IzAAAAAABeEJ4BAABQLLNmNTWjLjWpGax1q0pNsxGeCzlw4IDZLQAAxyIApvvwww/1xhtvSJIsFkuFfUg2oy41qRmsdatKzUBCeM6zYsUK3X///UpISDC7FQBVGMciAIFgx44d+vzzz/Xee+9JqrgPyWbUpSY1g7VuVakZSAjPeRITE/Xbb7/p5Zdf1saNG81uB0AVxbEIgJlyc3MlSampqerYsaO+//57TZs2TVL5fkg2oy41qRmsdatKzUBU5cOzw+GQJGVkZOiaa67RJZdcoqlTp+q///2vyZ0BqEo4FgEIBHa7Xbm5uUpOTtZNN92kPn366Lvvviv3D8lm1KUmNYO1blWpGYjsZjdgNovFIklauXKlhg4dqri4OM2aNUuvv/66HnvsMXXp0sXkDgFUBRyLAASKlJQUxcXFaeDAgTpz5owMw9B3330nSbr//vvdH5Lzj1vBXJea1AzWulWlZqCxGFXhK4Ii5Obmym4v+O5g5cqV6t+/v6xWqzZs2KC5c+fqxIkTGj9+vDp37mxeowAqNY5FAMz21VdfKTk5WZ07d1ZMTIwaNmzocWxKSkrSZ599ph9++EFXXHGFHn300aCtS01q+kNVea5mvb6BrEqG59dff13Hjh1T7dq1ddlll2nQoEGSPD/E/vLLL/r888+1c+dOvfjii+rUqZOZLQOohDgWATDbvffeq8TERNntdtntdoWHh+vhhx9Wp06d5HQ6JUlWq1VJSUmaPXu2tm7dqtdff10xMTFBV5ea1OS9G9g1g4JRxTz44IPGLbfcYnz88cfGQw89ZIwePdqYMGGCe312drb7v9esWWNMnDjROHLkiBmtAqjEOBYBMNucOXOMYcOGuX9fv3698eSTTxoDBgwwNm/ebBiGYTgcDsPpdBqGYRhJSUnG6dOng7IuNanJezewawaLKnXDsG3btunYsWOKj4/XqFGj9Morr2jkyJHavXu3nnjiCUlSSEiI+8Y9vXr10tNPP63GjRub2TaASoZjEYBAkJaW5r6fgtPp1BVXXKG//OUv6tKliyZPnqwDBw7IarW6r1+MiYlRrVq1grIuNanJezewawaLKhWe09LSlJycLKvV9bQjIiL0xz/+UXfffbcOHTqkDz/8UJJks9ncd4sLDw83rV8AlRPHIgCBIDo6WitWrNDvv//uPh61bdtWo0aNUs2aNbV58+ZKU5ea1AzWulWlZrCoUuG5S5cuioyM1LvvvuteFhYWpquvvlo9evTQ5s2b3efwV+a7xAEwF8ciAIGgT58+6tSpk9588039/vvv7uWdOnVSWFiY1qxZU2nqUpOawVq3qtQMFlUmPBuGIbvdrptuusl9B9t84eHh6tmzpw4ePKjU1FQTuwRQ2XEsAhAoGjVqpAEDBujEiRP617/+pePHj7vXNW3aVPXq1SuXeVvNqEtNagZr3apSM1hUmXmeLRaL7Ha7hgwZomPHjumbb75Ramqq7r77bknS7t27VbNmTYWEhJjcKYDKjGMRgECQnZ2t0NBQDR06VCkpKVq/fr0eeOAB3XDDDUpNTdVnn32mOXPm+P3sFzPqUpOawVq3qtQMJpV2qirjvAm6HQ6HbDabJGnt2rVat26dVq1apXPnzikuLk5r1qzRBx98oA4dOpjVMoBKiGMRgEBT+Dj02muv6bLLLlP9+vX17bffavv27WrQoIHGjBmj2NjYoK9LTWoGa92qUjPYVMrwnJWVpbCwMDmdTlmtVvdPSfrb3/6m5s2b6+6779aZM2f01VdfqXHjxurYsaOaNWtmcucAKhOORQDM9vHHH6tly5bq2bOnJM8v9B5//HFt3LhR3377rXv7/I+FFzuqZEZdalLzYmuaVbeq1KwMKt1p2x9//LH27dun8ePHKyIiwuPD6sMPP6x9+/ZpypQpCg0NVbVq1TR27FiTOwZQGXEsAmAmwzCUkpKiuXPnqlGjRgoNDVXXrl3dH3zj4+O1detWLV++XJKUk5OjkJCQi/5gbEZdalKT925g16xMKt0NwzZu3Kjly5fr3XffVVpamqxWqwzD0MaNG5WRkaGFCxcqNDRUubm5ZrcKoBLjWATATBaLRRaLRWfPnlVycrJmzZqljRs3utd369ZNX331lUJCQpSbm+u3+yyYUZea1PSHqvJczXp9K4tKE57zP4Dm5OSoVatWSkhI0Hvvvaf09HRZLBbFxsbq3Xffdb8R7PZKN+gOIABwLAIQKDIzM9W8eXONGDFCWVlZmjVrln755RdJUmxsrGw2m5xOp9+PQ2bUpSY1g7VuValZWVSa8Gy322UYhvbt26fbbrtN3bp10+bNm92jPtWqVXOfbsAbAUB54VgEIFAkJCSoZs2aGj58uG6//Xbl5uZq9uzZ7g/JktyXkwR7XWpSM1jrVpWalUWlu2HYW2+9pXHjxkmSpk+frrVr16pz58665557FBUV5XHdIQCUF45FACrarl27lJGRoa5du7rvmpuZmanw8HBJ0urVqxUfH6+wsDCNHDnSfaOgYKxLTWr6Q1V5rma9vpVRUIfnefPm6fTp07r00kvVpEkT9x1q8+8Wl5ubqw8++EDr169Xy5Yt9cgjjygqKsrkrgFUNhyLAJjtgQce0IkTJ7R//3517dpVnTt31l133aWwsDD3DX8k1xR506ZNU6NGjfT888+7PzwHU11qUpP3bmDXrMyC9pzB++67T8ePH9cll1yiRYsWqXnz5rrxxhs1cOBAWSwW95vhrrvu0rlz5/Trr78qKyuLD6wA/IpjEQCzvfLKK0pMTFR8fLySk5M1b948rV+/Xr///rsmTpyosLAw9z0WevXqJavVqmbNml30h2Mz6lKTmrx3A7tmZReUI89LlizRrFmzNH/+fEmu8/Y/++wz7dq1S3/+85914403SiqY6NvhcOjs2bOqVauWmW0DqGQ4FgEwm2EYmjBhgq677jpde+21klw3A1qyZIm+/PJLXXbZZRo3bpz7fgz+mm7GjLrUpKY/VJXnatbrW9kF5QV3SUlJatCggSTXh9IOHTpozJgx6tixoxYtWqQtW7ZIkvtOcTabjQ+rAPyOYxEAs1ksFqWkpGjx4sXuZeHh4RoyZIj69u2r7du36/jx4+5tg7kuNakZrHWrSs2qICjDc5s2bbR3715t2rRJNptNktSqVSsNHz5cubm52r59u3tbbsgDoLxwLAIQCIYNG6bU1FQtWLDAvSw8PFyjRo3Sr7/+qh9//LHS1KUmNYO1blWpWdkF5ae55s2bq23btlqwYIF2794tyXVqQrt27dSuXTt99913cjqdJncJoLLjWAQgEPTq1UsNGzbUV1995THKFBkZqR49epTbGS9m1KUmNYO1blWpWdkFZXhu0qSJbrrpJu3bt0+ffPKJtm7d6j7dICwsTE2bNuX0AwDljmMRALNlZ2erZs2aevLJJ1WzZk0tXbpUU6ZM0a5duzRz5kz99NNPuvTSSytFXWr6t2bh2x5V5ucZCHWrSs2qIOBvGHb+BeyFb6m+ePFiffnll8rMzFTz5s0VHR2tTz/9VLNmzVK7du3MahlAJcSxCECgyb9LriQtWrRILVu21MaNG7V8+XJlZ2crLCxMzzzzjDp06HDRtQofA/NvglgRdfNV5HOVJKfTKcMwKuR5Fn49K+K1XblypfsGUhVV83wVVXPOnDkaNGiQe4S1op9rRb6PCqvo/1+qkoAPz/lvcsMwZBiG+7rBv//97/rjH/+oevXqKSEhQd99952aN2+uYcOGqW3btiZ3DaCy4VgEwEzz58+X1WqV3W7X4MGDPdY98cQTWrdunb7//ntJrqB79uxZhYSEKDIy8qLq/vDDD4qLi1OtWrXcI5X5Ibq86s6aNUtnz55Vbm6u7r77blWrVs29rrxqfvbZZ8rJyVF4eLhuueUWj3XlVXPq1Km68cYb1aZNGzmdTlkslnJ/be+9916dOnVK8+bNc++3vGu+++67On78uGrWrKlHHnmkQmpK0oQJE7Ro0SLNmDFDV155ZYXU/fzzz+V0OhUWFqZhw4Z5rCuvmsuWLZPD4VBmZmaFvXersoCd5/nVV19VcnKy0tPTNXLkSPXs2dP9rc1jjz2mLVu26IUXXpDdbtell16qESNGmNwxgMqIYxEAs40dO9Y9n/ymTZu0aNEiPfLII+rYsaPeeOMNbd68WStXrpRUMOJUs2bNi677yy+/aNKkSRo1apRuvvlm1ahRw73ulVde0ZYtW/xe97777lNiYqKuuOIKLVy4UHv37tW//vWvcq15zz336OTJk2rcuLF27dql7t27q2nTppKkKVOmlMvre/jwYc2ePVs//PCDXnvtNbVq1codoMvreT7wwAMewVkq+CLk1VdfLZfnee+99+r48ePq37+/e3aK8q4puf5Ojx8/rq5duyonJ8ejbnm+d0+cOKH69etr165d6ty5s5o3b16uNe+9916dPn1a9evX1/r167Vo0SJNmDBBl156qd54441yqVnVBeQ1z/fff7/Wr1+v2NhY1alTR2PHjtX06dN16tQpLVy4UPv379dXX30lu92u3Nxcs9sFUElxLAJgtk8//VRnzpzR0qVL9a9//UsrVqzQmTNn9Morr2jt2rVq2bKlvvzyS4WEhHicqukPEREROnjwoJYtW6Z58+bp7NmzkqSMjAzFxsb6ve7777+vM2fOaP78+ZowYYI+/vhjbdq0SXv27FFmZma51HzjjTeUnJysBQsW6NFHH1WtWrW0Y8cOffTRRzp8+LBat26tZcuW+f31bdy4sWJjY2W32/Xggw9q9+7dslqt7uf59ddf+7VmfojND86rVq3S0qVLNWvWLB07dkxt27bV8uXL/VpzyZIlSkpK0uLFi/W3v/1NzZo10+LFizVr1iz9/vvv5VJTkh566CGdOXNGS5YsUadOnfTzzz9Lknt0tjzeR2+//bZOnz6tBQsW6JlnnlHLli114sQJrVq1SllZWWrfvr3fa86cOVNJSUn67LPP9Pbbb2vVqlXav3+/pkyZop9//lktW7bU0qVLy+XYUJUF3Ku4adMmnThxQvPnz3cvu+yyy/Taa6/JarWqd+/e+vzzz2Wz2XgjACg3HIsABIKMjAzVq1dPkusGQNWrV9esWbP017/+VbNmzdJbb72lkJAQj/sw+EtaWpoGDRqk2rVra9myZbJYLLrpppsUHR2toUOHymKxyOFw+O34d+bMGXXu3FmSK+iEhoYqOztb586dU3h4uPs0WKfT6beaJ06ccJ8G/+WXX2rr1q364osvtGbNGq1cuVIvvviirFarX19fp9Mpp9OpkJAQXX311frtt9/08MMPa+7cubJYLLr88stltVr9+tpKUkxMjCTpww8/1Jw5c9SxY0etW7dOq1at0rPPPiuLxaLs7GyFhob6pV5KSoqio6MlSe+8847mzZunLl266KefftKqVav097//3e81n3rqKe3bt09fffWVJNdrvXXrVkmSzWaTzWZzv4/8+frm5uaqT58+kqSFCxdq3bp1SktL0549e9SzZ0+9/vrrstvtfn0fJSUlqWXLlpKk9PR0RUVF6aqrrtKqVav06aefaurUqZJULseGqizgRp4jIyN17tw57du3z31tzdChQ/X444/r/fff15EjR/iwCqDccSwCYKb8ae7Cw8OVnJys06dPKzQ0VLm5uapWrZo+/PBDbdu2Te+9954klcuH41WrVqlWrVp66qmn1KNHDy1fvlwLFixQSkqKLBaLx42QLobT6ZTD4VBqaqoSExPd+61du7bq16/vcc1zWlqa+54TF1szOztbZ86cUWxsrLKzs5WYmKhvvvlG77zzjvsL1Dlz5kjy7+trsVhkt9t1+eWXq2nTprr33nvVqVMnDR06VN27d1d2drYk+e21lVxnUtlsNj3++OP66quv9PHHH+vtt9/W+vXrdezYMffz9EeIza9pt9uVmZmpo0ePas2aNZo7d66mTp2qDRs2KDExUTNnzvRbzXx33HGHOzhL0siRI5Wdna1t27ZdsK2/37sLFizQmDFj9MEHH2j58uX66KOPtHLlSm3dulX/93//J8k/76P8L19SU1N1+PBhSVJUVJQk1xckL730ktasWaPZs2f7rSYKBFx4llwXs2/btk0Wi8X9P+CQIUN077336s0331RaWhofVgGUK6vVyrEIgCnS0tJ05swZSdLAgQN1/PhxvfTSS5LkHr2qVq2ahg0bpsTERL/WTU5Odv/+4IMP6vHHH5fkusdDt27dtGLFCi1cuFBnzpzxy1R8+c/VZrPp4Ycf1jXXXOPe74EDB5Samqo6depIkv79739r8uTJ7nB5sTVDQ0M1bdo0de/eXaGhoZo4caKaNm2q9PR0Sa4vTAu/HhdbM39f+c/P6XRq9erVatGihTp16qTk5GQ1atTIPULsj5r576P27dsrLi5OCQkJ+sMf/qCGDRu6n+fNN9+sU6dO+b3m9ddfr19//VXPP/+8WrVqpQYNGujcuXOSpFGjRrm/KPFX3dOnT19wo84aNWooKytLq1ev9kud82vmv3cfeughDR48WDVq1NDNN9+sxo0bKycnRzExMbrpppv89v9pfk2r1aq7775bu3bt0r333qt33nlHDz/8sH766Sddc801uvbaa5WSkuKXmvAUEJ/6fvnlF6WkpKhfv35q166dhg4dqmeeeUa1a9dWnz593HfHyz/VIywszOyWAVRCu3btUnJystq3b6+2bdvqz3/+syZOnKiYmBj17duXYxGAcvfEE08oMTFRu3fv1vDhw3XzzTfrww8/1P/8z/9owoQJ+t///V/3XXIzMjLco7DnT6d3MXVHjhyp3r17q1u3bpLkPq12/Pjxmjp1qj777DOFhIRo1KhRFzUKXLjmiBEjNGDAAA0cONC9Pj8k1KhRQ7Nnz9Y777yjf//73xc1Ulm45q233qrevXvriiuukFQwApo/inf27Fl3kL2Y17dwzf/5n/9Rr1691L17d11++eVat26d9uzZozfffFMPPfSQtm7dqnvuuUcfffSRQkND/VLz1ltv1Q033KC7775bJ06cUNeuXT2e56lTp1SjRg2/voeGDx+uIUOG6O2339b48eO1f/9+nTt3ThEREZKkY8eOqUaNGnI6nRc9Anz+63vVVVe537t169bV/fffr1dffVVXXnmlOnXqdFG1iqo5fPhwDRo0SI888ogSEhK0aNEiSQWv77lz59w32/PX+2jEiBEaNmyYvvjiC02ePFkHDhxQnTp1NGXKFEnyOBX+Yv9e4cn08Dxu3Dj9/vvvOnHihKKiovTll1+67xyX/2bv2bOnatWqpYSEBGVnZysrK4tTEAD41bhx43Tq1CklJSVJkgYPHqw77rhDycnJuv/++zVlyhSORQDK1fjx43Xo0CH94x//0N69e/Xpp59qz549GjVqlObMmaM777xTjzzyiFq0aKGoqCgtXbpUn3zyiSRd1Ifjouru3r1biYmJGjhwoPt0cbvdrkceeUQhISHq16/fRQXnomru3btXN954oztAnzp1Su3bt9e8efP09ttv66OPPrqoeWmLe31PnjypgQMHau/evfrkk0/UvHlzZWRkaMGCBfr4448llf31Larmrl27lJqaqtjYWI0fP16zZ8/Wq6++qoEDB2r37t2Kjo6+qC9ni6s5ZswYvfDCC8rOztYXX3whq9WqY8eOacGCBfrkk0/8/h7at2+fBgwYoBdeeEGPPfaYxo0bpzZt2igqKkrz5s3T7NmzLzo4e3vvSlK3bt105ZVXavbs2Xr44YfVpEkTv9fcs2ePbrnlFnXr1k3x8fHKzMzUlVdeqaNHj+qLL75QfHy8JP++j3bv3q3bbrtNb731liTXHdy3bNmizZs3a9WqVbrvvvsuqiaKZmp4fuGFF5SYmKg5c+Zo8+bNmjNnjo4cOaKYmBg99dRTql+/vl588UU1adJEdevW1aZNm/TBBx94XPsCABfr9ddf14kTJ/TRRx/JZrNpxowZmjVrlk6ePKlx48YpMjKSYxGAcnX69GklJSXp7bffVv369dWuXTu1adNGH374oeLj4/W3v/1NS5Ys0f/93//p9OnTysjI0Mcff6w2bdqUW90lS5aoRo0a6t27t+x2u3u++wcffLBca1arVk19+/aV1WrVqlWrtGPHDs2cOfOigrO3mrVq1VLLli3166+/6siRIwoNDdWsWbPUqlWrcqn52Wef6YYbblDv3r01fPhwXXXVVZKk2NjYMtfzVvOjjz6SYRjq0KGD5s6dq5ycHEVGRio+Pv6C050vtmbr1q01Y8YMLV++XLfddpvmzZun1157Tfv371f9+vUVHx9f7u/d6tWrq0+fPqpfv766d++ur776yj3yXR41P//8c8XExGj69Ol67rnntH37dtWoUUMzZ84st/fR7Nmz5XA41LdvX8XHx7tvjjZ79mz3zcTgZ4ZJzp07Zzz44IPG6tWrDcMwjMmTJxuXXnqpMWDAAOPqq682PvjgA8MwDGP9+vXGwoULjc8//9w4dOiQWe0CqKRycnKM+++/3/j00089lt90003G4MGDjXfeeccwDMNYu3YtxyIA5SYlJcXo16+f8cknn3gs3717tzF27FjjqaeeMgzDMLKzsw3DcB27KqLu//7v//qlTllq7tq1yxgwYICxe/fucq85ceJEwzAMIysry+NnedZ85ZVXjJSUFMMwDMPpdBpOp7Pcaz7zzDOGYRhGWlqakZWVZWRkZJRbzV27dhljx441nn76acMwCl7T3Nzci65ZUt3i3rv5r3V51nz22WcNwzCM1NRUIz093UhPTy/3mvl/p6mpqUZOTo5faqJ4pt0wLCQkRCEhIZoyZYoeffRRzZs3T3PmzNGcOXN08803a/78+dq5c6euuOIKDRs2TMOHD3dPWA8A/mK1WuV0OrV9+3bl5OS4l3fu3Fndu3fXkiVLlJiYqJ49e3IsAlBuqlWrpmuuuUZbtmzRvn373Mvbtm2ru+++W4sXL9bOnTvdl4r4407Bpak7f/587dq1yy+1fKmZkJCg2NhYzZs376JGRUtbc+HChUpISHBfJ+qPS3JKqnnXXXdp9uzZOnr0qCTXqbX+OL3W2/NcsGCBduzYoaioKIWGhl70SGxJNWNjY3X33Xdr0aJF2rlzp/u19cfd0kuqW9x7N/+64/KsOW/ePO3YsUPVqlVTZGSk+/4E5VlzwYIFSkhIULVq1WS32/1SE8UzLTzbbDYNHDhQrVq10qZNm/Too4+qc+fOqlOnjh588EGFh4dr2bJlZrUHoIqwWq268sortWXLFv373//WDz/8oCeeeEKHDh3SxIkTZbfb9c0335jdJoBKaP78+Xr33Xe1du1anT59WqNGjdKWLVv06aef6sCBA+7tunTpoq5du3rcKOtigpavdf0RJH2tmX/N78VcHlPWmlLZX9/S1uzatesFf6dl5evzDA8Pr/CaVem9a8bryw1MK06FXvM8depUnTx5Uqmpqerbt6+GDRuma6+9VosWLVJaWpr7WhrJ9W1VixYtKrI9AFVE4WNRv379NGbMGGVlZenbb7/Vt99+q/r162vatGmSpKZNm170zUUA4Hz33XefTpw4odq1a+u7776TzWbTU089pVdeeUWPPvqosrKydO2116pPnz765JNPdOTIEb+MnJlRl5rU5L0b2DVRehbD8NMEa1489NBDOnXqlP7617/q22+/1f79+1WvXj1NmTJFa9eu1UsvvaTHH39crVu31oYNG/Tmm29qzpw5at68eUW0B6CKOP9YtG/fPrVo0UKTJk2SzWZTcnKysrOzFR0drcWLF+udd95RfHw8p2oD8JuFCxdq9uzZWrhwoSQpISFB8+fP13fffac333xTISEh+te//qUtW7aoSZMmSkxM1JtvvqlLL7006OpSk5q8dwO7JnxTISPPW7du1bFjx/TRRx8pMjJS1157rd58801Nnz5doaGhmjJlir744gs9++yzqlGjhsLDw/Xee+8RnAH4VUnHoszMTE2ePFnVqlXTyy+/rNWrV8tut2vatGkEZwB+lZqa6v6M43A41KFDB1WrVk1Wq1XPPvus3nzzTb3yyis6fvy4srKyVK9ePdWpUyco61KTmrx3A7smfFMh1zwnJSXpyJEjys7Odi/r3bu3+vfvr9OnT2vu3LmaMmWKpk+frmnTpunDDz+8qOkIAKAoJR2L8qd9CQkJ0Z/+9Cd98MEHmj17tjp27GhixwAqk9zcXDkcDrVv315r167Vjh073JerXXLJJRoxYoQaN26sVatWKTIyUq1atVKHDh0u+sOxGXWpSU3eu4FdE2VTrqdtZ2ZmKjw8XMePH9cDDzyggQMH6rbbblNoaKief/55Va9eXbm5udq9e7c+/PDD8moDQBVX2mPRnj179P7775vdLoBK6OWXX9bhw4d1+vRp9ezZU1lZWfr99991//33q02bNjIMQxaLRc8995xOnDih6dOnB21dalLTH6rKczXr9UXZlNvI89SpUzVjxgylp6erdu3a6tu3r1auXKkBAwbor3/9q3755Rc9+uijGjBggM6cOaNz586VVysAqjBfjkWnT5/mWATA78aNG6eEhAQNGjRIffr00fz585WTk6Nz587pvffe06+//uq+A3GtWrXUsGFDOZ3OoKxLTWry3g3smrg45XbN88mTJ7VkyRLZ7XaNHTtW99xzjwYMGKBNmzapQYMG6tevnyRp9erVqlOnjt/mKwSAwjgWATDT999/ryNHjmjBggWSpDNnzmjt2rXq1auXLBaLFi1apEcffVR9+vSR5JqiZvbs2Rc9F64ZdalJTd67gV0TF8/v4Tn/1AKHw6F+/frpjTfeUHZ2tsaOHav27durffv2Onz4sJ5++mnVrl1bn332mebMmeOXee4AIB/HIgCBIDk5WZGRkZLkvpN/bm6ujh07pjFjxqhJkyZau3atNmzYoAYNGmjOnDlq27ZtUNalJjV57wZ2TVw8v4dni8Wi3Nxc/frrr5o0aZIGDhyoxx57TBaLRX/5y18UEREhi8Uiq9WqyMhIffLJJ2rTpo2/2wBQxXEsAhAIWrVqpcTERB07dkwNGjSQ5PpyL/+WM23btlXNmjV1++23B31dalIzWOtWlZrwA6McpKWlGXPnznX/vmTJEiM2NtZ45513jKysrPIoCQAX4FgEIBDs3r3bMAzDcDgcRnZ2tjFkyBBjw4YNhmEYxr///W8jNjbWSEpKMpxOZ9DXpSY1g7VuVamJi1Mu4dkwDCM7O9swDMPIyckxDMMwli5dalx66aXGa6+9ZmRkZJRXWQDwwLEIQKDIyckxTpw4YXTv3t1ITk42PvvsM6NXr17Gtm3bKl1dalIzWOtWlZoom3K7YVhISIgkyWazyTAM3XjjjcrOztbkyZN15513KiIiorxKA4AbxyIAgcJutyskJEQtWrTQ1KlT9eWXX2rmzJnlPp+8GXWpSc1grVtVaqJsynWe53z5JSwWi9LS0lStWrXyLgkAF+BYBMBsiYmJ6tu3r6KiohQfH6927dpV2rrUpGaw1q0qNeG7cht5Lsxisbg/tEZFRVVESQC4AMciAGaLiYnR7bffrltvvVWtWrWq1HWpSc1grVtVasJ3FTLyDAAAAJfc3FzZ7RUyfmF6XWpSM1jrVpWa8A3hGQAAAAAAL6xmNwAAAAAAQKAjPAMAAAAA4AXhGQAAAAAALwjPAAAAAAB4QXgGAAAAAMALwjMAAAAAAF4QngEAAAAA8ILwDAAAAACAF4RnAAAAAAC8IDwDAAAAAODF/wNwjHvoVVRHZgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df10b.plot(style='-o', legend='reverse', rot=45, figsize=(12, 6))\n",
    "\n",
    "plt.xticks(df10b.index)\n",
    "plt.ylim(0, 70)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "cca5747a",
   "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>Markkinointi (10000 euroa)</th>\n",
       "      <th>Liikevaihto (miljoonaa euroa)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>72.9</td>\n",
       "      <td>23.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>77.3</td>\n",
       "      <td>29.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>78.0</td>\n",
       "      <td>35.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>82.9</td>\n",
       "      <td>34.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>89.5</td>\n",
       "      <td>39.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>96.3</td>\n",
       "      <td>45.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>99.1</td>\n",
       "      <td>50.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>102.3</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>105.0</td>\n",
       "      <td>53.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>103.9</td>\n",
       "      <td>56.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>111.7</td>\n",
       "      <td>58.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>126.3</td>\n",
       "      <td>64.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Markkinointi (10000 euroa)  Liikevaihto (miljoonaa euroa)\n",
       "0                         72.9                           23.2\n",
       "1                         77.3                           29.2\n",
       "2                         78.0                           35.4\n",
       "3                         82.9                           34.7\n",
       "4                         89.5                           39.8\n",
       "5                         96.3                           45.6\n",
       "6                         99.1                           50.2\n",
       "7                        102.3                           55.0\n",
       "8                        105.0                           53.8\n",
       "9                        103.9                           56.7\n",
       "10                       111.7                           58.9\n",
       "11                       126.3                           64.4"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df10c = pd.DataFrame({'Markkinointi (10000 euroa)':[72.9, 77.3, 78.0, 82.9, 89.5, 96.3, \n",
    "                                                    99.1, 102.3, 105.0, 103.9, 111.7, 126.3],\n",
    "                      'Liikevaihto (miljoonaa euroa)':[23.2, 29.2, 35.4, 34.7, 39.8, 45.6,\n",
    "                                                       50.2, 55.0, 53.8, 56.7, 58.9, 64.4]})\n",
    "df10c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "9c93c6cf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Markkinointi (10000 euroa)', ylabel='Liikevaihto (miljoonaa euroa)'>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df10c.plot(x='Markkinointi (10000 euroa)', y='Liikevaihto (miljoonaa euroa)', kind='scatter')    # Hajontakaavio"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}