konoha81/pokemon_stat.ipynb Secret

## pokemon_stat.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import json, requests\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import time\n",
    "from gensim.models import word2vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sns.set(font='Hiragino Kaku Gothic Pro')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ポケモンの名前一覧csvファイルを読み込む。（一覧は『ポケモン英語⇔日本語変換 – サンムーン対応』（ https://amalgame.jp/pokemon-eng-jpn/ ）より取得したもの。英語名はスペースを'\\_'で代替したり一部変更した。）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>No</th>\n",
       "      <th>jaNAME</th>\n",
       "      <th>enNAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>Bulbasaur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>フシギソウ</td>\n",
       "      <td>Ivysaur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>フシギバナ</td>\n",
       "      <td>Venusaur</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>ヒトカゲ</td>\n",
       "      <td>Charmander</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>リザード</td>\n",
       "      <td>Charmeleon</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   No jaNAME      enNAME\n",
       "0   1  フシギダネ   Bulbasaur\n",
       "1   2  フシギソウ     Ivysaur\n",
       "2   3  フシギバナ    Venusaur\n",
       "3   4   ヒトカゲ  Charmander\n",
       "4   5   リザード  Charmeleon"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndf = pd.read_csv(\"pokemon_name.csv\", encoding='SHIFT-JIS')\n",
    "ndf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "要素の数（ポケモンの種類数）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "802"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(ndf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "各ポケモンへのアクセス"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Ivysaur'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ndf['enNAME'][1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "各ポケモンの名前をクエリとして投げることで、JSONを取得してJSONファイルとして保存する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def fetch_data():\n",
    "    start = time.time()\n",
    "    for i in range(802):\n",
    "        jlist = []\n",
    "        page = 1\n",
    "        name = ndf['enNAME'][i]\n",
    "        print(str(i) + ':' + name + ' has started.')\n",
    "\n",
    "        while True:\n",
    "            url = \"https://e621.net/post/index.json?tags={0}&page={1}\".format(name, page)\n",
    "            jsonString = requests.get(url).text\n",
    "            data = json.loads(jsonString)\n",
    "\n",
    "            if data:\n",
    "                jlist.extend(data)\n",
    "                time.sleep(1)\n",
    "            else:\n",
    "                print(name + ' has finished.')\n",
    "                time.sleep(1)\n",
    "                break\n",
    "\n",
    "            page += 1\n",
    "\n",
    "        with open('./poke_list/' + name + '.json', 'w') as f:\n",
    "                json.dump(jlist, f, indent=2)\n",
    "                \n",
    "    elapsed_time = time.time() - start\n",
    "    print(elapsed_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "取得したJSONをデータフレームに入れる。（2分くらいかかる）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def json_to_dataframe():\n",
    "    col_list = ['artist', 'author', 'id', 'created_at', 'fav_count', 'file_ext', 'file_url', 'preview_url', 'rating', 'score', 'tags', 'name']\n",
    "    df = pd.DataFrame(columns = col_list)\n",
    "\n",
    "    for i in range(802):\n",
    "        name = ndf['enNAME'][i]\n",
    "        df2 = pd.read_json('./poke_list/' + name + '.json')\n",
    "        df2['name'] = pd.Series(ndf['jaNAME'][i], index=df2.index )\n",
    "        df = pd.concat([df,df2[col_list]], ignore_index=True)\n",
    "        \n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 2 µs, sys: 0 ns, total: 2 µs\n",
      "Wall time: 5.01 µs\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "#df = json_to_dataframe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "csvファイルに書き出しておく。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#df.to_csv('poke_data.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "csvファイルからデータフレームを作成する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"poke_data.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "データフレームの内容の上位5件を転置して確認する"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>artist</th>\n",
       "      <th>['longlevy']</th>\n",
       "      <th>['cobaltsynapse']</th>\n",
       "      <th>['nakiri_(artist)']</th>\n",
       "      <th>['pawn']</th>\n",
       "      <th>['pawn']</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>author</th>\n",
       "      <td>LongLevy</td>\n",
       "      <td>easytogooglename</td>\n",
       "      <td>nakiri</td>\n",
       "      <td>PawnKing</td>\n",
       "      <td>PawnKing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>1.09486e+06</td>\n",
       "      <td>1.09037e+06</td>\n",
       "      <td>1.08895e+06</td>\n",
       "      <td>1.08838e+06</td>\n",
       "      <td>1.08838e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>created_at</th>\n",
       "      <td>{'json_class': 'Time', 's': 1483305507, 'n': 7...</td>\n",
       "      <td>{'json_class': 'Time', 's': 1482901354, 'n': 6...</td>\n",
       "      <td>{'json_class': 'Time', 's': 1482789369, 'n': 5...</td>\n",
       "      <td>{'json_class': 'Time', 's': 1482726218, 'n': 8...</td>\n",
       "      <td>{'json_class': 'Time', 's': 1482725910, 'n': 3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fav_count</th>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file_ext</th>\n",
       "      <td>png</td>\n",
       "      <td>png</td>\n",
       "      <td>png</td>\n",
       "      <td>png</td>\n",
       "      <td>png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file_url</th>\n",
       "      <td>https://static1.e621.net/data/a8/97/a897607344...</td>\n",
       "      <td>https://static1.e621.net/data/3f/8a/3f8a5cd0d6...</td>\n",
       "      <td>https://static1.e621.net/data/a3/07/a307e6d4c1...</td>\n",
       "      <td>https://static1.e621.net/data/ee/d8/eed8b847b4...</td>\n",
       "      <td>https://static1.e621.net/data/4c/25/4c25a1a8d2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>preview_url</th>\n",
       "      <td>https://static1.e621.net/data/preview/a8/97/a8...</td>\n",
       "      <td>https://static1.e621.net/data/preview/3f/8a/3f...</td>\n",
       "      <td>https://static1.e621.net/data/preview/a3/07/a3...</td>\n",
       "      <td>https://static1.e621.net/data/preview/ee/d8/ee...</td>\n",
       "      <td>https://static1.e621.net/data/preview/4c/25/4c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rating</th>\n",
       "      <td>q</td>\n",
       "      <td>e</td>\n",
       "      <td>s</td>\n",
       "      <td>e</td>\n",
       "      <td>e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>score</th>\n",
       "      <td>-1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tags</th>\n",
       "      <td>belly big_belly bulbasaur charizard charmander...</td>\n",
       "      <td>anthro bulbasaur charmander claws cobaltsynaps...</td>\n",
       "      <td>3_toes ambiguous_gender bulbasaur charmander c...</td>\n",
       "      <td>backsack balls big_butt bulbasaur butt butt_ki...</td>\n",
       "      <td>backsack balls big_butt bulbasaur butt butt_ki...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "artist                                            ['longlevy']  \\\n",
       "author                                                LongLevy   \n",
       "id                                                 1.09486e+06   \n",
       "created_at   {'json_class': 'Time', 's': 1483305507, 'n': 7...   \n",
       "fav_count                                                    5   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/a8/97/a897607344...   \n",
       "preview_url  https://static1.e621.net/data/preview/a8/97/a8...   \n",
       "rating                                                       q   \n",
       "score                                                       -1   \n",
       "tags         belly big_belly bulbasaur charizard charmander...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "artist                                       ['cobaltsynapse']  \\\n",
       "author                                        easytogooglename   \n",
       "id                                                 1.09037e+06   \n",
       "created_at   {'json_class': 'Time', 's': 1482901354, 'n': 6...   \n",
       "fav_count                                                   13   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/3f/8a/3f8a5cd0d6...   \n",
       "preview_url  https://static1.e621.net/data/preview/3f/8a/3f...   \n",
       "rating                                                       e   \n",
       "score                                                        4   \n",
       "tags         anthro bulbasaur charmander claws cobaltsynaps...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "artist                                     ['nakiri_(artist)']  \\\n",
       "author                                                  nakiri   \n",
       "id                                                 1.08895e+06   \n",
       "created_at   {'json_class': 'Time', 's': 1482789369, 'n': 5...   \n",
       "fav_count                                                    5   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/a3/07/a307e6d4c1...   \n",
       "preview_url  https://static1.e621.net/data/preview/a3/07/a3...   \n",
       "rating                                                       s   \n",
       "score                                                        3   \n",
       "tags         3_toes ambiguous_gender bulbasaur charmander c...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "artist                                                ['pawn']  \\\n",
       "author                                                PawnKing   \n",
       "id                                                 1.08838e+06   \n",
       "created_at   {'json_class': 'Time', 's': 1482726218, 'n': 8...   \n",
       "fav_count                                                   18   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/ee/d8/eed8b847b4...   \n",
       "preview_url  https://static1.e621.net/data/preview/ee/d8/ee...   \n",
       "rating                                                       e   \n",
       "score                                                        4   \n",
       "tags         backsack balls big_butt bulbasaur butt butt_ki...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "artist                                                ['pawn']  \n",
       "author                                                PawnKing  \n",
       "id                                                 1.08838e+06  \n",
       "created_at   {'json_class': 'Time', 's': 1482725910, 'n': 3...  \n",
       "fav_count                                                   17  \n",
       "file_ext                                                   png  \n",
       "file_url     https://static1.e621.net/data/4c/25/4c25a1a8d2...  \n",
       "preview_url  https://static1.e621.net/data/preview/4c/25/4c...  \n",
       "rating                                                       e  \n",
       "score                                                        4  \n",
       "tags         backsack balls big_butt bulbasaur butt butt_ki...  \n",
       "name                                                     フシギダネ  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`id` が数値として格納されてしまっているので、文字列に直す。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df['id'] = df['id'].apply(lambda s: np.str(int(s)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "157797"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "postのユニーク数を求める。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "98424"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df[~df['id'].duplicated()])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "e621で 'pokémon'タグつきpostは 102000件近くあるため、約25000件の差が出てしまっている。この理由としては、タグにポケモン名まで記載されていないpostsが多くある可能性が挙げられる。念のため、取得したJSONファイルとe621の検索結果をいくつかのファイルで比較したが、数値が異なるものはなかった。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ポケモン TOP20を棒グラフで表示する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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209PTtWXLFt11111u2+fNm6ecnBytWLGiQYYDAAAAvJWhIP3mm29q8eLF6tWr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110d87748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.countplot(data=df, x = 'name', order = df['name'].value_counts().iloc[:20].index, color='steelblue')\n",
    "g.set_xticklabels(labels=df['name'].value_counts().iloc[:20].index, rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### postの重複を削除して集計"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ポケモン名でのデータ取得を行っているため、同じpostが重複してカウントされてしまう。<br>\n",
    "そこで、post ID を利用して重複を削除して集計を行う。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>author</th>\n",
       "      <td>LongLevy</td>\n",
       "      <td>easytogooglename</td>\n",
       "      <td>nakiri</td>\n",
       "      <td>PawnKing</td>\n",
       "      <td>PawnKing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>1094859</td>\n",
       "      <td>1090370</td>\n",
       "      <td>1088954</td>\n",
       "      <td>1088381</td>\n",
       "      <td>1088377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>created_at</th>\n",
       "      <td>{'json_class': 'Time', 's': 1483305507, 'n': 7...</td>\n",
       "      <td>{'json_class': 'Time', 's': 1482901354, 'n': 6...</td>\n",
       "      <td>{'json_class': 'Time', 's': 1482789369, 'n': 5...</td>\n",
       "      <td>{'json_class': 'Time', 's': 1482726218, 'n': 8...</td>\n",
       "      <td>{'json_class': 'Time', 's': 1482725910, 'n': 3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fav_count</th>\n",
       "      <td>5</td>\n",
       "      <td>13</td>\n",
       "      <td>5</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file_ext</th>\n",
       "      <td>png</td>\n",
       "      <td>png</td>\n",
       "      <td>png</td>\n",
       "      <td>png</td>\n",
       "      <td>png</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>file_url</th>\n",
       "      <td>https://static1.e621.net/data/a8/97/a897607344...</td>\n",
       "      <td>https://static1.e621.net/data/3f/8a/3f8a5cd0d6...</td>\n",
       "      <td>https://static1.e621.net/data/a3/07/a307e6d4c1...</td>\n",
       "      <td>https://static1.e621.net/data/ee/d8/eed8b847b4...</td>\n",
       "      <td>https://static1.e621.net/data/4c/25/4c25a1a8d2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>preview_url</th>\n",
       "      <td>https://static1.e621.net/data/preview/a8/97/a8...</td>\n",
       "      <td>https://static1.e621.net/data/preview/3f/8a/3f...</td>\n",
       "      <td>https://static1.e621.net/data/preview/a3/07/a3...</td>\n",
       "      <td>https://static1.e621.net/data/preview/ee/d8/ee...</td>\n",
       "      <td>https://static1.e621.net/data/preview/4c/25/4c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rating</th>\n",
       "      <td>q</td>\n",
       "      <td>e</td>\n",
       "      <td>s</td>\n",
       "      <td>e</td>\n",
       "      <td>e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>score</th>\n",
       "      <td>-1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tags</th>\n",
       "      <td>belly big_belly bulbasaur charizard charmander...</td>\n",
       "      <td>anthro bulbasaur charmander claws cobaltsynaps...</td>\n",
       "      <td>3_toes ambiguous_gender bulbasaur charmander c...</td>\n",
       "      <td>backsack balls big_butt bulbasaur butt butt_ki...</td>\n",
       "      <td>backsack balls big_butt bulbasaur butt butt_ki...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                             0  \\\n",
       "author                                                LongLevy   \n",
       "id                                                     1094859   \n",
       "created_at   {'json_class': 'Time', 's': 1483305507, 'n': 7...   \n",
       "fav_count                                                    5   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/a8/97/a897607344...   \n",
       "preview_url  https://static1.e621.net/data/preview/a8/97/a8...   \n",
       "rating                                                       q   \n",
       "score                                                       -1   \n",
       "tags         belly big_belly bulbasaur charizard charmander...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "                                                             1  \\\n",
       "author                                        easytogooglename   \n",
       "id                                                     1090370   \n",
       "created_at   {'json_class': 'Time', 's': 1482901354, 'n': 6...   \n",
       "fav_count                                                   13   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/3f/8a/3f8a5cd0d6...   \n",
       "preview_url  https://static1.e621.net/data/preview/3f/8a/3f...   \n",
       "rating                                                       e   \n",
       "score                                                        4   \n",
       "tags         anthro bulbasaur charmander claws cobaltsynaps...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "                                                             2  \\\n",
       "author                                                  nakiri   \n",
       "id                                                     1088954   \n",
       "created_at   {'json_class': 'Time', 's': 1482789369, 'n': 5...   \n",
       "fav_count                                                    5   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/a3/07/a307e6d4c1...   \n",
       "preview_url  https://static1.e621.net/data/preview/a3/07/a3...   \n",
       "rating                                                       s   \n",
       "score                                                        3   \n",
       "tags         3_toes ambiguous_gender bulbasaur charmander c...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "                                                             3  \\\n",
       "author                                                PawnKing   \n",
       "id                                                     1088381   \n",
       "created_at   {'json_class': 'Time', 's': 1482726218, 'n': 8...   \n",
       "fav_count                                                   18   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/ee/d8/eed8b847b4...   \n",
       "preview_url  https://static1.e621.net/data/preview/ee/d8/ee...   \n",
       "rating                                                       e   \n",
       "score                                                        4   \n",
       "tags         backsack balls big_butt bulbasaur butt butt_ki...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "                                                             4  \n",
       "author                                                PawnKing  \n",
       "id                                                     1088377  \n",
       "created_at   {'json_class': 'Time', 's': 1482725910, 'n': 3...  \n",
       "fav_count                                                   17  \n",
       "file_ext                                                   png  \n",
       "file_url     https://static1.e621.net/data/4c/25/4c25a1a8d2...  \n",
       "preview_url  https://static1.e621.net/data/preview/4c/25/4c...  \n",
       "rating                                                       e  \n",
       "score                                                        4  \n",
       "tags         backsack balls big_butt bulbasaur butt butt_ki...  \n",
       "name                                                     フシギダネ  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ndp = df[~df['id'].duplicated()]\n",
    "df_ndp = df_ndp.reset_index(drop = True)\n",
    "df_ndp.head().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "タグの基本統計量を表示する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    98424.000000\n",
       "mean        30.944790\n",
       "std         16.768948\n",
       "min          7.000000\n",
       "25%         21.000000\n",
       "50%         28.000000\n",
       "75%         38.000000\n",
       "max        914.000000\n",
       "Name: tags, dtype: float64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ndp['tags'].apply(lambda s: len(s.split(' '))).describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "各postに付いているタグ数をヒストグラムで表示する。タグ数の最大値は100個として表示している。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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l8vJyNTU1DbZlAAAAJIlBhd033nhDP/nJTzR27NjYturqat17770qKyvTvn37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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110fb0ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tagcounts =  pd.DataFrame(df_ndp['tags'].apply(lambda s: len(s.split(' '))))\n",
    "sns.distplot(tagcounts[tagcounts['tags'] < 100]['tags'], kde=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "R-18 / 非R-18 の集計。 e = Explicit, q = Questionable, s = Safe (参照：https://e621.net/help/show/ratings )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "rating\n",
       "e    59795\n",
       "q    13592\n",
       "s    25037\n",
       "Name: id, dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ndp.groupby('rating')['id'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "割合で表示する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "rating\n",
       "e    60.8\n",
       "q    13.8\n",
       "s    25.4\n",
       "Name: id, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(df_ndp.groupby('rating')['id'].count().div(df_ndp.groupby('rating')['id'].count().sum()) * 100).round(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 'solo' 性別集計"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "各ポケモンの性別で集計を行う。複数描かれていると、対象のポケモンの性別が不明となってしまうため、まず 'solo' タグを持つカラムだけ抽出し、 `solo_df` という名前のデータフレームに格納する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <td>PawnKing</td>\n",
       "      <td>PawnKing</td>\n",
       "      <td>Ivysaurite</td>\n",
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       "      <td>png</td>\n",
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       "      <td>png</td>\n",
       "      <td>png</td>\n",
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       "      <td>https://static1.e621.net/data/4c/25/4c25a1a8d2...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>preview_url</th>\n",
       "      <td>https://static1.e621.net/data/preview/ee/d8/ee...</td>\n",
       "      <td>https://static1.e621.net/data/preview/4c/25/4c...</td>\n",
       "      <td>https://static1.e621.net/data/preview/54/d5/54...</td>\n",
       "      <td>https://static1.e621.net/data/preview/bc/0c/bc...</td>\n",
       "      <td>https://static1.e621.net/data/preview/b5/0a/b5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rating</th>\n",
       "      <td>e</td>\n",
       "      <td>e</td>\n",
       "      <td>s</td>\n",
       "      <td>s</td>\n",
       "      <td>s</td>\n",
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       "      <th>score</th>\n",
       "      <td>4</td>\n",
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       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tags</th>\n",
       "      <td>backsack balls big_butt bulbasaur butt butt_ki...</td>\n",
       "      <td>backsack balls big_butt bulbasaur butt butt_ki...</td>\n",
       "      <td>2016 anthro bulbasaur claws crying female ivys...</td>\n",
       "      <td>! 3_fingers 3_toes :d :o :| &gt;:d ? ^_^ age_diff...</td>\n",
       "      <td>&lt;3 &lt;3_eyes anthro blush bulb bulbasaur fangs f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                             0  \\\n",
       "author                                                PawnKing   \n",
       "id                                                     1088381   \n",
       "created_at   {'json_class': 'Time', 's': 1482726218, 'n': 8...   \n",
       "fav_count                                                   18   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/ee/d8/eed8b847b4...   \n",
       "preview_url  https://static1.e621.net/data/preview/ee/d8/ee...   \n",
       "rating                                                       e   \n",
       "score                                                        4   \n",
       "tags         backsack balls big_butt bulbasaur butt butt_ki...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "                                                             1  \\\n",
       "author                                                PawnKing   \n",
       "id                                                     1088377   \n",
       "created_at   {'json_class': 'Time', 's': 1482725910, 'n': 3...   \n",
       "fav_count                                                   17   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/4c/25/4c25a1a8d2...   \n",
       "preview_url  https://static1.e621.net/data/preview/4c/25/4c...   \n",
       "rating                                                       e   \n",
       "score                                                        4   \n",
       "tags         backsack balls big_butt bulbasaur butt butt_ki...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "                                                             2  \\\n",
       "author                                              Ivysaurite   \n",
       "id                                                     1087878   \n",
       "created_at   {'json_class': 'Time', 's': 1482689780, 'n': 5...   \n",
       "fav_count                                                    4   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/54/d5/54d5d8003d...   \n",
       "preview_url  https://static1.e621.net/data/preview/54/d5/54...   \n",
       "rating                                                       s   \n",
       "score                                                        2   \n",
       "tags         2016 anthro bulbasaur claws crying female ivys...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "                                                             3  \\\n",
       "author                                            Rad_Dudesman   \n",
       "id                                                     1087459   \n",
       "created_at   {'json_class': 'Time', 's': 1482638637, 'n': 6...   \n",
       "fav_count                                                   62   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/bc/0c/bc0c79d1a5...   \n",
       "preview_url  https://static1.e621.net/data/preview/bc/0c/bc...   \n",
       "rating                                                       s   \n",
       "score                                                       26   \n",
       "tags         ! 3_fingers 3_toes :d :o :| >:d ? ^_^ age_diff...   \n",
       "name                                                     フシギダネ   \n",
       "\n",
       "                                                             4  \n",
       "author                                              Ivysaurite  \n",
       "id                                                     1079273  \n",
       "created_at   {'json_class': 'Time', 's': 1481913545, 'n': 5...  \n",
       "fav_count                                                    6  \n",
       "file_ext                                                   png  \n",
       "file_url     https://static1.e621.net/data/b5/0a/b50ad569a0...  \n",
       "preview_url  https://static1.e621.net/data/preview/b5/0a/b5...  \n",
       "rating                                                       s  \n",
       "score                                                        1  \n",
       "tags         <3 <3_eyes anthro blush bulb bulbasaur fangs f...  \n",
       "name                                                     フシギダネ  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solo_df = df[df['tags'].str.split(' ').apply(lambda s: bool(s) if 'solo' in s else False)].copy()\n",
    "solo_df = solo_df.reset_index(drop = True)\n",
    "solo_df.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45634"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(solo_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "solo 比率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'46%'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "str(int((len(solo_df) / len(df_ndp)) * 100)) + '%'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "タグに含まれる性別情報（'male', 'female', 'ambiguous_gender' 以外は'NaN'として除外する）を `sex` カラムに格納する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "      <th>author</th>\n",
       "      <td>PawnKing</td>\n",
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       "      <td>Ivysaurite</td>\n",
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       "      <td>{'json_class': 'Time', 's': 1482726218, 'n': 8...</td>\n",
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       "      <td>png</td>\n",
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       "      <td>png</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>preview_url</th>\n",
       "      <td>https://static1.e621.net/data/preview/ee/d8/ee...</td>\n",
       "      <td>https://static1.e621.net/data/preview/4c/25/4c...</td>\n",
       "      <td>https://static1.e621.net/data/preview/54/d5/54...</td>\n",
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       "      <td>https://static1.e621.net/data/preview/b5/0a/b5...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rating</th>\n",
       "      <td>e</td>\n",
       "      <td>e</td>\n",
       "      <td>s</td>\n",
       "      <td>s</td>\n",
       "      <td>s</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>score</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tags</th>\n",
       "      <td>backsack balls big_butt bulbasaur butt butt_ki...</td>\n",
       "      <td>backsack balls big_butt bulbasaur butt butt_ki...</td>\n",
       "      <td>2016 anthro bulbasaur claws crying female ivys...</td>\n",
       "      <td>! 3_fingers 3_toes :d :o :| &gt;:d ? ^_^ age_diff...</td>\n",
       "      <td>&lt;3 &lt;3_eyes anthro blush bulb bulbasaur fangs f...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "      <td>フシギダネ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <td>male</td>\n",
       "      <td>male</td>\n",
       "      <td>female</td>\n",
       "      <td>ambiguous_gender</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                             0  \\\n",
       "author                                                PawnKing   \n",
       "id                                                     1088381   \n",
       "created_at   {'json_class': 'Time', 's': 1482726218, 'n': 8...   \n",
       "fav_count                                                   18   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/ee/d8/eed8b847b4...   \n",
       "preview_url  https://static1.e621.net/data/preview/ee/d8/ee...   \n",
       "rating                                                       e   \n",
       "score                                                        4   \n",
       "tags         backsack balls big_butt bulbasaur butt butt_ki...   \n",
       "name                                                     フシギダネ   \n",
       "sex                                                       male   \n",
       "\n",
       "                                                             1  \\\n",
       "author                                                PawnKing   \n",
       "id                                                     1088377   \n",
       "created_at   {'json_class': 'Time', 's': 1482725910, 'n': 3...   \n",
       "fav_count                                                   17   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/4c/25/4c25a1a8d2...   \n",
       "preview_url  https://static1.e621.net/data/preview/4c/25/4c...   \n",
       "rating                                                       e   \n",
       "score                                                        4   \n",
       "tags         backsack balls big_butt bulbasaur butt butt_ki...   \n",
       "name                                                     フシギダネ   \n",
       "sex                                                       male   \n",
       "\n",
       "                                                             2  \\\n",
       "author                                              Ivysaurite   \n",
       "id                                                     1087878   \n",
       "created_at   {'json_class': 'Time', 's': 1482689780, 'n': 5...   \n",
       "fav_count                                                    4   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/54/d5/54d5d8003d...   \n",
       "preview_url  https://static1.e621.net/data/preview/54/d5/54...   \n",
       "rating                                                       s   \n",
       "score                                                        2   \n",
       "tags         2016 anthro bulbasaur claws crying female ivys...   \n",
       "name                                                     フシギダネ   \n",
       "sex                                                     female   \n",
       "\n",
       "                                                             3  \\\n",
       "author                                            Rad_Dudesman   \n",
       "id                                                     1087459   \n",
       "created_at   {'json_class': 'Time', 's': 1482638637, 'n': 6...   \n",
       "fav_count                                                   62   \n",
       "file_ext                                                   png   \n",
       "file_url     https://static1.e621.net/data/bc/0c/bc0c79d1a5...   \n",
       "preview_url  https://static1.e621.net/data/preview/bc/0c/bc...   \n",
       "rating                                                       s   \n",
       "score                                                       26   \n",
       "tags         ! 3_fingers 3_toes :d :o :| >:d ? ^_^ age_diff...   \n",
       "name                                                     フシギダネ   \n",
       "sex                                           ambiguous_gender   \n",
       "\n",
       "                                                             4  \n",
       "author                                              Ivysaurite  \n",
       "id                                                     1079273  \n",
       "created_at   {'json_class': 'Time', 's': 1481913545, 'n': 5...  \n",
       "fav_count                                                    6  \n",
       "file_ext                                                   png  \n",
       "file_url     https://static1.e621.net/data/b5/0a/b50ad569a0...  \n",
       "preview_url  https://static1.e621.net/data/preview/b5/0a/b5...  \n",
       "rating                                                       s  \n",
       "score                                                        1  \n",
       "tags         <3 <3_eyes anthro blush bulb bulbasaur fangs f...  \n",
       "name                                                     フシギダネ  \n",
       "sex                                                     female  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solo_df['sex'] = solo_df['tags'].apply(lambda s: 'female' if 'female' in s.split(' ') else s)\n",
    "solo_df['sex'] = solo_df['sex'].apply(lambda s: 'male' if 'male' in s.split(' ') else s)\n",
    "solo_df['sex'] = solo_df['sex'].apply(lambda s: 'ambiguous_gender' if 'ambiguous_gender' in s.split(' ') else s)\n",
    "solo_df = solo_df.where(solo_df[(solo_df['sex'] != solo_df['tags'])])\n",
    "solo_sex_df = solo_df.dropna().reset_index(drop = True)\n",
    "solo_sex_df.head().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "42179"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(solo_sex_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sex\n",
       "ambiguous_gender     7992\n",
       "female              22639\n",
       "male                11548\n",
       "Name: name, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solo_sex_df.groupby('sex')['name'].count()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TOP20 のポケモンだけ抽出して、`solo_sex_top20_df` に格納する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ルカリオ', 'ピカチュウ', 'ブラッキー', 'イーブイ', 'サーナイト', 'ザングース', 'リザードン', 'ミミロップ',\n",
       "       'グレイシア', 'ゾロアーク', 'シャワーズ', 'ライチュウ', 'ウインディ', 'バシャーモ', 'ニンフィア', 'ブースター',\n",
       "       'エーフィ', 'ルギア', 'テールナー', 'リーフィア'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top20_name_list = df['name'].value_counts().iloc[:20].index\n",
    "top20_name_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14798"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "solo_sex_top20_df = solo_sex_df[solo_sex_df['name'].apply(lambda s: bool(s) if s in top20_name_list else False)].reset_index()\n",
    "len(solo_sex_top20_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "性別ごとにクロス集計を行う。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>ambiguous_gender</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>イーブイ</th>\n",
       "      <td>236</td>\n",
       "      <td>341</td>\n",
       "      <td>145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ウインディ</th>\n",
       "      <td>62</td>\n",
       "      <td>249</td>\n",
       "      <td>367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>エーフィ</th>\n",
       "      <td>56</td>\n",
       "      <td>240</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>グレイシア</th>\n",
       "      <td>96</td>\n",
       "      <td>383</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>サーナイト</th>\n",
       "      <td>89</td>\n",
       "      <td>939</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex    ambiguous_gender  female  male\n",
       "name                                 \n",
       "イーブイ                236     341   145\n",
       "ウインディ                62     249   367\n",
       "エーフィ                 56     240    70\n",
       "グレイシア                96     383   115\n",
       "サーナイト                89     939    58"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sex_counts = pd.crosstab(solo_sex_top20_df['name'], solo_sex_top20_df['sex'])\n",
    "sex_counts.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "合計値で並び替えたあと、`sum` カラムを消去する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>ambiguous_gender</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ルカリオ</th>\n",
       "      <td>353</td>\n",
       "      <td>520</td>\n",
       "      <td>846</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ピカチュウ</th>\n",
       "      <td>229</td>\n",
       "      <td>520</td>\n",
       "      <td>381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>サーナイト</th>\n",
       "      <td>89</td>\n",
       "      <td>939</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ザングース</th>\n",
       "      <td>209</td>\n",
       "      <td>391</td>\n",
       "      <td>397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ブラッキー</th>\n",
       "      <td>136</td>\n",
       "      <td>401</td>\n",
       "      <td>322</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex    ambiguous_gender  female  male\n",
       "name                                 \n",
       "ルカリオ                353     520   846\n",
       "ピカチュウ               229     520   381\n",
       "サーナイト                89     939    58\n",
       "ザングース               209     391   397\n",
       "ブラッキー               136     401   322"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sex_counts['sum'] = sex_counts.sum(1)\n",
    "sex_counts = sex_counts.sort_values(by='sum', ascending=False)\n",
    "sex_counts = sex_counts.drop('sum', axis=1)\n",
    "sex_counts.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "正規化する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>ambiguous_gender</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ルカリオ</th>\n",
       "      <td>0.205352</td>\n",
       "      <td>0.302501</td>\n",
       "      <td>0.492147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ピカチュウ</th>\n",
       "      <td>0.202655</td>\n",
       "      <td>0.460177</td>\n",
       "      <td>0.337168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>サーナイト</th>\n",
       "      <td>0.081952</td>\n",
       "      <td>0.864641</td>\n",
       "      <td>0.053407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ザングース</th>\n",
       "      <td>0.209629</td>\n",
       "      <td>0.392177</td>\n",
       "      <td>0.398195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ブラッキー</th>\n",
       "      <td>0.158324</td>\n",
       "      <td>0.466822</td>\n",
       "      <td>0.374854</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex    ambiguous_gender    female      male\n",
       "name                                       \n",
       "ルカリオ           0.205352  0.302501  0.492147\n",
       "ピカチュウ          0.202655  0.460177  0.337168\n",
       "サーナイト          0.081952  0.864641  0.053407\n",
       "ザングース          0.209629  0.392177  0.398195\n",
       "ブラッキー          0.158324  0.466822  0.374854"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sex_counts = sex_counts.div(sex_counts.sum(1), axis=0)\n",
    "sex_counts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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wlZ2drdatW1e4r3nz5srKyvLZduTIEbVr107vvvuubrzxRg0YMEDjx4/XW2+9FXjHAAAA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110f9cf60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sex_counts.plot(kind='bar', stacked=True)\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### soloで♂率が高いポケモンをpost数100以上の上位94匹から20匹表示する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29371"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_name_list = solo_df['name'].value_counts().iloc[:94].index\n",
    "solo_sex_top_df = solo_sex_df[solo_sex_df['name'].apply(lambda s: bool(s) if s in top_name_list else False)].reset_index()\n",
    "len(solo_sex_top_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>ambiguous_gender</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>アシレーヌ</th>\n",
       "      <td>18</td>\n",
       "      <td>80</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>アブソル</th>\n",
       "      <td>65</td>\n",
       "      <td>211</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>アーボック</th>\n",
       "      <td>21</td>\n",
       "      <td>96</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>イベルタル</th>\n",
       "      <td>37</td>\n",
       "      <td>60</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>イーブイ</th>\n",
       "      <td>236</td>\n",
       "      <td>341</td>\n",
       "      <td>145</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex    ambiguous_gender  female  male\n",
       "name                                 \n",
       "アシレーヌ                18      80    16\n",
       "アブソル                 65     211    67\n",
       "アーボック                21      96    22\n",
       "イベルタル                37      60    11\n",
       "イーブイ                236     341   145"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sex_counts_male = pd.crosstab(solo_sex_top_df['name'], solo_sex_top_df['sex'])\n",
    "sex_counts_male.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>ambiguous_gender</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ニドキング</th>\n",
       "      <td>0.032895</td>\n",
       "      <td>0.118421</td>\n",
       "      <td>0.848684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ゴーリキー</th>\n",
       "      <td>0.032051</td>\n",
       "      <td>0.269231</td>\n",
       "      <td>0.698718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>フタチマル</th>\n",
       "      <td>0.136364</td>\n",
       "      <td>0.190909</td>\n",
       "      <td>0.672727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ブイゼル</th>\n",
       "      <td>0.137255</td>\n",
       "      <td>0.202614</td>\n",
       "      <td>0.660131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>リオル</th>\n",
       "      <td>0.159091</td>\n",
       "      <td>0.209091</td>\n",
       "      <td>0.631818</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex    ambiguous_gender    female      male\n",
       "name                                       \n",
       "ニドキング          0.032895  0.118421  0.848684\n",
       "ゴーリキー          0.032051  0.269231  0.698718\n",
       "フタチマル          0.136364  0.190909  0.672727\n",
       "ブイゼル           0.137255  0.202614  0.660131\n",
       "リオル            0.159091  0.209091  0.631818"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sex_counts_male = sex_counts_male.div(sex_counts_male.sum(1), axis=0)\n",
    "sex_counts_male = sex_counts_male.sort_values(by='male', ascending=False)\n",
    "sex_counts_male = sex_counts_male.head(20)\n",
    "sex_counts_male.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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qypQpev755/XMM8/Ibrdr7Nixuv/++/XSSy8pJydHiYmJWrhwoRYtWlRkXAkJ\nCUpKStLatWtVvXp1bdmyRaNHj9aGDRtUvXp1n75HuDyuRwIAAABX4N1331WLFi00aNAgBQYGKiws\nTLNmzdLHH3+sc+fOyd/fX5L00EMP6Xe/+51sNpsGDRqkQ4cOKS4uTrVr15a/v7/69Omjw4cPS5IC\nAgL08ssv6+GHH5afn5/CwsJ01113KSkpqUh+Xl6e3nzzTS1cuFARERGy2Wzq2bOnunTpovfee8+n\n7wWuDFe2AAAAgCvwww8/6NNPP9Udd9zhttyyLB09elRt27aVJN1++/+7uTcsLEyBgYGuddKFSS/O\nnz8vSbLZbAoKCtLcuXO1e/du/frrr8rPzy/2FsJjx44pJydHvXr1cltut9u5wl1OUbYAAACAK2Cz\n2TRy5Eg98cQTl9wuODjY7XVgYKDrqtdvZWRkaNCgQbr//vu1dOlS1alTR1999ZWeeeaZYvNr166t\nbdu2eX8S8CnKFgDguleWMwICqDiaNGlS5Ha9vLw8LV++XKNGjSpSsq7Ejh07VLNmTU2YMMG1LCUl\npdhtb775ZqWnp+vUqVNuV742bNig5s2b69Zbb/U4H2ZRtgAAEDMCAiiqoKBAlmXJsizZbDbFxMTo\nlVde0fLlyzVixAjZbDbNnTtXJ06cUHBwsBwOh6QLn89VyOFwuJZfvKxwm5o1a+rYsWM6duyYbrrp\nJn388cd64YUXVK1aNbdjOZ1OVapUSSNGjNCECRO0aNEiRUZG6vPPP9fcuXO1efNmX7wl8BBlCwBw\n3WNGQKBsZBxPK9dZ2dnZstlsysrKUpUqVRQUFKR//OMfmjt3rnr27KmgoCB17dpVS5YskSTl5ua6\nti+c1j07O1v5+flyOByuWwlzc3OVlZUlSWrbtq0efPBBDRkyRMHBwerUqZNmzpyp+Ph4SRc+7+vi\nY44fP14rVqzQww8/rMzMTEVFRWnNmjWqX79+abxNKGWULQAAAPhc69at9dLDz/k80xN169bVoUOH\n3JbVqlVLL774YrHbh4WFFdn+lltuKbKsR48e6tGjh+v1k08+qSeffNJtm3vuuafYY9psNo0aNUqj\nRo3y6FxQNihbAAAA8LmgoCB16NChrIcBGMXnbAEAAACAAVzZAgCUC8wICAC41lC2AADlBjMCAgCu\nJZQtAIBLWV5dYkZAAMC1hrIFAHDD1SUAAEoHZQsAyhmuLgEAcG2gbAFAOcTVJQAAKj7KFgCUM1xd\nAgDg2kDViVkNAAAgAElEQVTZAgAAgM/l5+dr3759Ps1s3bq1goKCfJp5sY4dOyoxMVGdO3cuszHA\ntyhbAFAMPvMJAMzat2+fNo8ao4ZVqvgkLzkzU1r+ijp06OCTvOJUrlxZoaGhZZYP36NsASi3yrrw\n8NwUAJjVsEoV3VI9oqyH4TM2m03+/v5lPQz4EGULQLlWVoWH56YAANHR0Zo9e7bWrVun//73v6pV\nq5bmzZsnp9OpZ599VsnJyYqKitL8+fNVv359nT59WgsXLtSuXbuUl5enZs2aaebMmWrSpEmxx//n\nP/+pf/7znzpz5owaNmyoiRMn6rbbbvPxWcIkyhaAcovCAwAoSyEhIVq4cKHmzp2rzp07a/Xq1Zo0\naZJCQ0O1YMECNWnSRIsWLdLTTz+tv//975o2bZoaN26sLVu2yOl0as2aNZo5c6bWrl1b5Nhr167V\npk2btHz5ckVGRmrPnj2Ki4vT3//+dzVs2LAMzhYm+JX1AAAAAIDyyN/fXwMGDHBNaDFw4EAdO3ZM\nsbGxrqtV/fr10+HDhyVJ8fHxmjx5soKCghQcHKxevXopKSmp2GOvWLFCzz77rCIjIyVJt912m4YM\nGaK33nrLB2cGX+HKFgAAAFCCi2cODAsLkyR16tTJtaxy5co6f/68JCk0NFRLly7Vjh07lJqaqoKC\nAjkcjiLHzMrKUmpqqh588EG35QUFBWrTpo2J00AZoWwBAAAAJQgJCSmyLDg4uMiygoICjRgxQm3a\ntNH8+fPVsGFDpaamqm/fvsUe19/fX1988YVsNlupjxnlB7cRAgAAAFfp8OHD+t///qf4+Hg1atRI\nfn5+On78eLHbhoWFqVatWkU+Z+zjjz/Wf/7zH18MFz5C2QIAAACK4XA43G4DLPza6XS6ljmdTjmd\nTt14443KysrSt99+q4KCAn3xxRd6+umni2xbeIzRo0frr3/9q+uZrgMHDuipp54q0w9dRunjNkIA\nl1TWn3UFALh2Xc3PF2+yWnu4T15enrKzs12vs7OzZbPZlJWVpYiIC58PlpOTo/Pnz+uGG27QU089\npbFjx8rpdKpdu3aaO3euYmNjlZ+fr6CgIOXm5rqON3jwYNlsNk2YMEFnzpxRnTp19PzzzzP1+zWG\nsgXgsvhwXwBAaWvdurW0/BXf5RVmemDXrl1ur6tWrapDhw65LWvWrJlr2dChQzV06FC39Rdv/9vj\nDRo0SIMGDfJoTKhYKFsALonPugIAmBAUFKQOHTqU9TAAo3hmCwAAAAAMoGwBAAAAgAGULQAAAAAw\ngLIFAAAAAAZQtgAAAADAAMoWAAAAABhA2QIAAAAAAyhbAAAAAGAAZQsAAAAADAjwZqcNGzZo8+bN\nSkpKUo0aNRQbG6vBgwdfdr9Tp06pX79+iouL08CBA72JBq5LdrtdyZmZXu+fnJmpm+z2UhwRAAAA\nLsfjsrV+/XqtXLlSL774opo2baqkpCSNHTtWDodDQ4cOLXE/p9OpKVOmSJKCg4O9HzFwndoUZSms\nlnf7Zp2ydHvpDgcAAACX4XHZWrVqlebMmaOmTZtKkho3bqyEhAQNGzZMgwYNUkBA8YdMTExUrVq1\nFBISosDAwKsbNXCdCQwMVGT7BopoVNOr/dOOnObPHQAAgI959MxWcnKy0tLSFB0d7ba8WbNmioiI\n0P79+4vd7+OPP9Ynn3yiWbNmKScnRzabzfsRAwAAAEAF4FHZSk1NVcOGDYtdV69ePaWkpBRZfvTo\nUT3zzDNasmSJKleuLMuyvBspAAAAAFQgHt1GmJaWptDQ0GLXhYeHKysry21ZTk6Oxo0bpxkzZqhB\ngwZeD9LPzyY/v+Kvhvn7X/2Eiv7+fgoI8Pw4ZJNNNtlkk0022WQDKIlHZatKlSpKT08vdl12drZq\n1Kjhem1ZluLi4vT73/9ed999d5HtLcuSZVny87v8H9iIiNASbz2sWjXkCkdfsqpVQ1S9evEl8nL7\nkU022WSTTTbZZJMNoDgela369evrxIkTsiyrSPlJSkpSZGSk63Vqaqo+//xzffvtt9q0aZNr+blz\n53To0CFNnDhRL730krp163bZ3LS07BKvbGVk5HpyCiUe4+zZbK/2I5tssskmm2yyySZblDCgGB6V\nraioKIWEhGj37t1uk2QcPHhQdrtdLVq0cC2rU6eODhw4UOQYI0aMUGxsrHr27HnFz285nZaczuK3\ndTicnpxCiccoKPD8OGRfX9l5eeev/rOu8s5XuPMmm2yyySab7KvNBq5XHk/9HhcXp2nTpikxMVEt\nW7ZUSkqKZsyYodGjR8vf3/+y+xcUFMj+/3+4KrMSoqLhs64AAABwpTwuWzExMZKk6dOn6/Tp06pb\nt65iY2PVv39/SdKAAQMUExOjkSNHFrt/VlaWMq/i6gBQVvisKwAAAHjC47IlXShchaXrty5+Pqs4\n77zzjjeRAAAAAFChMHcnAAAAABhA2QIAAAAAAyhbAAAAAGAAZQsAAAAADKBsAQAAAIABlC0AAAAA\nMICyBQAAAAAGePU5W0BZsdvtSr6KD8VOzszUTXZ7KY4IAAAAKB5lCxXOpihLYbW82zfrlKXbS3c4\nAAAAQLEoW6hQAgMDFdm+gSIa1fRq/7QjpxUYGFjKowIAAACK4pktAAAAADCAsgUAAAAABlC2AAAA\nAMAAyhYAAAAAGEDZAgAAAAADKFsAAAAAYABlCwAAAAAMoGwBAAAAgAGULQAAAAAwIKCsB4CKx263\nKzkz0+v9kzMzdZPdXoojAgAAAMofyha8sinKUlgt7/bNOmXp9tIdDgAAAFDuULbgscDAQEW2b6CI\nRjW92j/tyGkFBgaW8qgAAACA8oVntgAAAADAAMoWAAAAABjAbYQVFJNUAAAAAOUbZasCY5IKAAAA\noPyibFVQTFIBAAAAlG88swUAAAAABlC2AAAAAMAAyhYAAAAAGEDZAgAAAAADKFsAAAAAYABlCwAA\nAAAMoGwBAAAAgAGULQAAAAAwgLIFAAAAAAYElPUAKjK73a7kzEyv90/OzNRNdnspjggAAABAeUHZ\nukqboiyF1fJu36xTlm4v3eEAAAAAKCcoW1chMDBQke0bKKJRTa/2TztyWoGBgaU8KgAAAADlAc9s\nAQAAAIABlC0AAAAAMICyBQAAAAAGULYAAAAAwADKFgAAAAAYQNkCAAAAAAMoWwAAAABgAGULAAAA\nAAygbAEAAACAAZQtAAAAADCAsgUAAAAABlC2AAAAAMAAyhYAAAAAGEDZAgAAAAADKFsAAAAAYABl\nCwAAAAAMoGwBAAAAgAGULQAAAAAwgLIFAAAAAAZQtgAAAADAAMoWAAAAABhA2QIAAAAAAyhbAAAA\nAGAAZQsAAAAADKBsAQAAAIABlC0AAAAAMICyBQAAAAAGULYAAAAAwADKFgAAAAAYQNkCAAAAAAMo\nWwAAAABgQEBZDwAA4M5utyvjeJrX+2ccT5O9tb0URwQAALxB2QKAcij925rKT67t1b455wKkmFIe\nEAAA8BhlCwDKmcDAQNWK6qDw2k282j/95I8KDAws5VEBAABPeVW2NmzYoM2bNyspKUk1atRQbGys\nBg8eXOy2aWlpWrBggb766ivl5+erXr16GjNmjLp163ZVAwcAAACA8szjsrV+/XqtXLlSL774opo2\nbaqkpCSNHTtWDodDQ4cOdds2Pz9fw4YNU+fOnfXOO+8oLCxMX3/9tcaNG6dXX31VLVq0KLUTAQAA\nAIDyxOPZCFetWqU5c+aoadOmkqTGjRsrISFBixcvVkFBgdu2X375pc6cOaO//e1vCgsLkyS1b99e\n9957rz755JNSGD4AAAAAlE8eXdlKTk5WWlqaoqOj3ZY3a9ZMERER2r9/v9q1a+da3r59e61Zs0YB\nAe4xBw4c0H333XcVwwYA4NrA7JMAcO3yqGylpqaqYcOGxa6rV6+eUlJS3MpW1apVVbVqVddrp9Op\nZ555RqmpqRowYICXQwYA4NrC7JMAcG3yqGylpaUpNDS02HXh4eHKysoqcd8zZ85o2rRpOnfunN5+\n+23XbYUAAFzPmH0SAK5dHpWtKlWqKD09vdh12dnZqlGjRrHrdu/erQkTJqhHjx56+eWXPf6h4Odn\nk5+frdh1/v4eP3ZW7DECAjw/Dtlkk0022WSTTTbZAEriUdmqX7++Tpw4IcuyZLO5l5+kpCRFRkYW\n2Wfv3r0aNWqURo8erccee8yrQUZEhBbJK1S1aohXx/ztMapXL/6K3eX2I5tssskmm2yyPc8OCQm4\n6mfVQn4fUOGyr9fvN3C98qhsRUVFKSQkRLt373abJOPgwYOy2+1FpnLPz8/XlClTNGbMGI0aNcrr\nQaalZZd4ZSsjI9fr4158jLNns73aj2yyySabbLLJ9i77ap9Vy+hXMbOvVnn9flPCgKI8/pytuLg4\nTZs2TYmJiWrZsqVSUlI0Y8YMjR49Wv7+/m7bbt26VXl5efrzn/98VYN0Oi05nVax6xwO51Udu/AY\nBQWeH4dssskmm2yyyfYu28/P/6qfVfPz869w2dfr9xu4XnlctmJiLkx5NH36dJ0+fVp169ZVbGys\n+vfvL0kaMGCAYmJiNHLkSO3bt0/nzp1Tt27d3I6Rn5+vm2++WRs3biyFUwAAlBamIQcAoPR4XLak\nC4WrsHT91qZNm1xfT5w4UVOmTJGfn/uDlA6HQ+fPn/cmGgBgGNOQAwBQOrwqW1cqKCio2OX+/v6q\nXLmyyWgAgBeYhhwAgNJjtGwBAHCluIURAHCtoWwBAMoNbmEEAFxLKFsAgHKBWxgBANcayhZQAXB7\nFQAAQMVD2QIqCG6vAgAAqFgoW0AFwO1VAAAAFY/f5TcBAAAAAHiKsgUAAAAABnAbIQAAgI8w4RFw\nfaFsAQAA+BATHgHXD8oWKhR+IwgAqMiY8Ai4vlC2UOHwG0EAKB38AgsAzKJsoULhN4IAULr4Bdb1\ng3IN+F6FL1t2u13JmZle75+cmamb7PzFAQC4/vALrOsP5RrwrQpftiRpU5SlsFre7Zt1ytLtpTsc\nAACAcodyDfhehS9bgYGBimzfQBGNanq1f9qR0/zFAQAAAKDU8aHGAAAAAGAAZQsAAAAADKBsAQAA\nAIABFf6ZLfgeU8cCAAAAl0fZqqDKuvAwdSwAAABwaZStCqysCg9TxwIAAACXR9mqoCg8gFllffUY\nAABUfJQtACgBt8sCAICrQdkCgGJw9RgAAFwtpn4HAAAAAAMoWwAAAABgAGULAAAAAAygbAEAAACA\nAZQtAAAAADCAsgUAAAAABjD1OwDguseHWAMATKBsAQAgPsQaAFD6KFsAgOseH2INADCBZ7YAAAAA\nwADKFgAAAAAYQNkCAAAAAAN4Zgu4QsxWBgAAAE9QtgAPMFsZAAAArhRlC7hCzFbme1xNBAAAFRll\nC0C5xtVEAABQUVG2AJRbXE0EAAAVGbMRAgAAAIABlC0AAAAAMICyBQAAAAAGULYAAAAAwAAmyABw\nSUy/DgAA4B3KFoDLYvp1AAAAz1G2AFwS068DAAB4h2e2AAAAAMAAyhYAAAAAGEDZAgAAAAADKFsA\nAAAAYABlCwAAAAAMoGwBAAAAgAGULQAAAAAwgLIFAAAAAAZQtgAAAADAAMoWAAAAABhA2QIAAAAA\nAyhbAAAAAGAAZQsAAAAADKBsAQAAAIABlC0AAAAAMCCgrAdwtex2uzKOp3m9f8bxNNlb2ytcNgAA\nAIDyrcKXLUlK/7am8pNre7VvzrkAKaZiZgMAAAAovyp82QoMDFStqA4Kr93Eq/3TT/6owMDACpcN\nAAAAoHzjmS0AAAAAMICyBQAAAAAGULYAAAAAwADKFgAAAAAYQNkCAAAAAAO8mo1ww4YN2rx5s5KS\nklSjRg3FxsZq8ODBxW576tQpvfDCC/r666+VnZ2tdu3aadq0aYqMjLyqgQMAAABAeebxla3169dr\nxYoVmjFjhnbs2KHExEStXr1aa9euLbLt+fPn9eCDD6pOnTp655139OGHH6ply5aKjY1Vbm5uqZwA\nAAAAAJRHHpetVatWac6cOWratKkkqXHjxkpISNDixYtVUFDgtu3WrVt144036vHHH1dQUJBCQ0P1\n6KOP6ne/+53eeOON0jkDAAAAACiHPCpbycnJSktLU3R0tNvyZs2aKSIiQvv373dbvnXrVt1zzz1F\njnPXXXfpP//5jxfDBQAAAICKwaOylZqaqoYNGxa7rl69ekpJSXFb9vPPPysqKqrItjfffHORbQEA\nAADgWuJR2UpLS1NoaGix68LDw5WVleW27OzZs8VuHx4erszMTE+iAQAAAKBC8Wg2wipVqig9Pb3Y\nddnZ2apRo4bbsrCwsGK3z8rK0g033HDFuX5+Nvn52Ypd5+/vp8wz3l8lyzyTIn//aAUEeD4LPtlk\nk0022WSTTTbZAEpisyzLutKNjx49qqFDh2rnzp2y2dzLz913363FixerdevWrmUTJ05UmzZtFBsb\n67bt5s2b9e6772rlypVXOXwAAAAAKJ88+tVEVFSUQkJCtHv3brflBw8elN1uV4sWLdyWd+7cWR9/\n/HGR43z44Ye6++67vRguAAAAAFQMHl8HjouL07Rp07R//35ZlqVjx45pxowZGj16tPz9/d227dev\nn9LT0/X8888rIyNDdrtdr7/+upKSktS3b99SOwkAAAAAKG88uo2w0Lvvvqvly5fr9OnTqlu3roYP\nH67+/ftLkgYMGKCYmBiNHDlSkvTrr7/q2Wef1c6dOxUUFKQ2bdpo+vTpioiIKN0zAQAAAIByxKuy\nBQAAAAC4NKaTAQAAAAADKFsAAAAAYABlCwAAAAAMoGwBAAAAgAGULQAAAAAwgLIFAAAAAAZQtgAA\nAADAgGuqbGVmZpb1EAAAuCqnTp0q6yEAAErJNVG2cnNzNX/+fM2bN6+sh+JSUFCg/fv363r8zOhf\nfvlFcXFx+uGHH8p6KABKUUZGhhISEnTmzJmyHso1rU+fPmX2s+Po0aPq27evPvroozLJLygoKJPc\nK2FibGX9fgMw75ooWykpKWrcuLHCw8P14YcflvVwJEl2u11/+tOfZLfbyyS/LP9RdMMNN6hr1656\n/PHH9cILL/g835fK6w/Kzz77TKNGjTL2D7byet7Xqvfff1+LFy+Ww+HQ3r17y2wclmUpODhYAwcO\n1Ntvv11m4/CVzZs3a/PmzT6/0hQcHCybzebTzEJRUVGaNGmSVq5cqYcffljHjh3zWbZlWXrwwQc1\nZswYHT582Ge5V2LdunUaOnRoqf+dWpbvNwDfuCbKVrNmzXT06FE1a9ZMx44d09atW+V0Ost0TMHB\nwbIsS0FBQWWSX5b/KAoMDFS/fv309ttva8+ePVqyZIlP832pPP6g/OyzzzRhwgT179/f2D/YyuN5\nX6u2bdumvXv3qmvXrjpx4oQef/zxMhtLtWrVNGbMGL322mtas2aNT/5u2bFjh/GMkixYsEBvv/22\n+vTpo4EDB+rVV1/1ye3qfn6X/9F8/vx5Y/ndunXTm2++qXbt2ulPf/qTvvnmG2NZF7PZbFq+fLk6\nduyo2NhYvfLKKz67wpeTk1PiurfffluLFi3S1KlTjfydWlbvNwAfsa4h6enpVvv27a0+ffpY3bt3\nt5YtW2ZlZmaW2XiaN29eZtmFjh07ZsXExFjr1q0rk/yzZ89aPXr0sPbv3++zzJSUFGvIkCHWZ599\n5rNMh8NhLVmyxOrYsaO1d+9eo1l5eXnW3XffbSUmJlrnzp1zW7d3714rOjra+vLLL42OoZAvz/ti\nSUlJPsu6WGpqqrV27Vqf5y5YsMAaPny49dNPP1ldu3b1eX5xfv75Z6tLly7WkSNHjGWkpaVZ99xz\nj7V161ZjGZfSvXt319d79uyxJk6caHXp0sXauXOnkbzf//73Vo8ePazf/e53VteuXa0uXbpYHTt2\ntKKjo6327dtbbdq0sVq2bGk1b97cZz9f3nnnHatDhw5WcnKyT/IK/fzzz1b//v2tSZMmGc/Kzc21\n2rVrZ02ePNk6duyY27otW7ZYt99+u3Xo0CHj47Cssnu/jxw5YvXp08f68MMPfZoLXA+uqbJlt9ut\nnj17WpZlWfv27bPGjx9vde/e3dqxY0eZjKc8lC3L8s0/ii5lw4YN1iOPPOLTzN27d1v333+/NXny\nZMvhcPgs1xc/KJ1Op9WmTRtr/PjxVnR0tLVy5UrL4XBYqampVteuXa0tW7YYyy6JL/+BcObMGevO\nO++0vv32W+NZF/vggw+sAQMGWJ988omVkZHhNp7evXtbJ06cMJZ9+PBh19fdunUzluOp1atXWxMn\nTjSacfLkSesPf/iDT39hU6hHjx5Flm3bts2Kjo629uzZU+p5R44csU6cOGHdfvvtVrdu3aznn3/e\nOnPmjJWVlWXl5ORYeXl51vnz5y273W5lZ2eXen5JXnnlFWvAgAE+yyuUlpZm9evXz3ruueeMZ7Vv\n395auHCh1b59e2v27NlWTk6O9f3331udOnWyvvnmG+P5Fyur9/vTTz+1Bg0aZD300EPWTz/95PN8\n4Fpls6xrZwYHy7LUs2dPbdmyxbXsk08+0axZszRkyBCNGTPGp+O55ZZbdOjQIZ9mluS1117T/v37\ntXjx4lI97vjx47Vjxw4FBgbKz89P/v7+stls8vf3d712OBxKSUnRZ599ppo1a5Zq/qXk5+dr6tSp\nqly5subOneuz3FdffVUfffSRNm7caCyjU6dO2rlzp3744QfNmTNHDodDeXl56t+/vx588EFjuZfi\ni/MulJSUpMcff1wrVqxQ/fr1jedJ0vHjx5WcnKzExERNmTJFnTp1kiTNnj1bR44c0Zo1a3wyjnbt\n2mns2LGKjIxU48aNFRUVZSQnPj5e33zzTbF/tgv/fJ8/f1579uzRp59+avTP9uHDhzVu3DgNHjzY\n7RY7y7KUk5OjJ554wkjuXXfdpa1btxZZ/umnnyo+Pl4bN25UtWrVSj3397//vd5++21NmzZNZ8+e\n1bJly3TjjTeWes6Vcjgc6tevn/7yl7+od+/ePs1OS0tT7969tXLlSrVo0cJYTuHfqWfOnNGzzz6r\nffv2yel0atKkSerVq5ex3OKU5fvtdDr18ssv6x//+IdeeeUVtW3b1qf5wLXomilb+fn5CgoKUo8e\nPbRt2za3db/88ouGDRumRx55RA888IDPxuSrslWW/yhKS0uTdeEKqRwOh5xOZ4n/37x581LLvVJ5\neXkaPHiwpk6dqi5duvgk0xc/KDt27Khdu3ZJuvDDceXK/4+9N4+rMf///x/nnBYtmmSP7DMiklZF\nZcleFCHKWoxQqKHsFLJMkpCKGNkae97iJksxY8teUw2KqRhbUU6nzvr6/dGn8+3ohN/MdV2nOa77\n7XZudV2vc7sez3POtbyer9fr+XzuRmxsLE6cOIGOHTvSovklmO4g3Lx5E2vXrsW8efPqdMArKyvh\n7u5OueamTZswZcoUtGrVCgCQn5+PcePG4eTJk2jfvj3lesqwtLSEu7s7Xr58iQcPHsDQ0BBBQUEY\nMmQIpTpPnjxBZWXlF69tqVQKFxcXSrWVceTIEWzfvh1eXl7yfYQQVFVVYdGiRZRq2draQktLC+/f\nv8cff/yh9D0rV66Erq4uQkNDKdUGqp2t9PR0EEKQkJCAQ4cOITExkTbH+lNSU1PRtWtXdO7cWb7v\n4sWLiIyMxLlz52jR5PP5uHXrFgYNGlSnLTExEb///jv27NlDizageE8Fqr+D1atXIy4ujnaHQxXf\n95f43//+h7CwMPz666/o0KGDSmxgYVEbVDOhRj1Dhgwh0dHRCmvsa/Ps2TPi6OhIrl69yphNTC0j\nfPz4MXn48CF58OABuXv3LsnMzCQ3b94k169fJ9euXSMZGRnk8uXLJC0tjRF7mKSsrIzw+Xz50hqZ\nTFbnPRcuXCATJkygzYazZ8/WiSFKS0sjw4YNo03T2tq6zr7U1FQyePBg8vfff9OmWxtVfO5P2bFj\nB7G3tyehoaHyV0hICFmwYAEj+kFBQSQsLIwRrRqcnJzk/8tkMpKenk5GjhxJQkNDlZ7/6oJUKiXj\nxo0jDx8+pF2roKCAFBUVfXbJ5qtXr4itrS0tccGfPsf27dtHBgwYQF6/fk251qdcvXqV9O7dm9y+\nfVthv0QiIfb29uTJkye06MbGxpJ58+bJt9PS0uTfrVAoJE5OTqSkpIQWbUKU31MzMzPJgAEDaI3X\nUtX3/TWoajkjC4u6oTbO1h9//EFCQkJIr1696nUqfv/9dzJkyBAiFosZsamhxGzRyY0bN8j+/fvJ\nyZMnSVpaGrl+/TrJzs4mQqGQEf2AgABibm5OzM3NiZmZGenWrRsxNTUl3bp1I2ZmZsTc3Jz06tWL\nmJmZ0dJRUdWD0srKSun+06dPk6FDh9LaKSGk4XQQhEIhGTlypEoSZrx69YpYWFgw4tzWvp6UOQAf\nP34kPj4+ZO3atZRp5ubmkkuXLpHbt2+TnJwcUlhYSN6/f0/Z8f8JV65cIdOmTWNMT1nMVm1WrlxJ\nCgsLKdcdMGBAHcd527ZtZNSoUbTeW9+8eUMcHBxIenq60vbVq1eT+Ph4ynXLy8uJk5MTefXqFSGE\nkKKiItKnTx+Fe/bq1avJoUOHKNeuQZmzRUh1v8HJyYmW31lV3/fXIpFIyMiRI8nZs2dVZgMLizqg\nFqnfAaB79+7YsGED9u3bh40bNyIiIqJOylgHBwe0bdsWBw4cUJGV9JCXl4fLly8jMzMTubm5KCoq\nwocPHxjRfvPmDf7880/89ttvOHnyJBISEhAcHAxbW1v4+PggNTWVVv1t27bh4cOHePjwIbKzs5GT\nk4Pc3FxkZWXh3r17uH37Nn7//XdcvXqV8piSt2/fIjQ0FFFRUbCxsVFo4/F4GDp0KK5cuUKpZg0c\nDgcikajO/lGjRmHQoEFYtWoVLbqAaj/3p2hpacHf318l9dySk5Ph5uYmX1JIJ0lJSRgzZgzS0tKU\ntvRyoBkAACAASURBVOvr6yM6OhppaWl48OABJZp37txBUlIStmzZgiVLlsDPzw/9+/fHoEGDEBIS\ngkePHlGi8/8HR0dH5Ofno7i4mHFtZaxZswYmJiaUH1cikdSp0RgQEABDQ0Ns3bqVcr0atm7dCk9P\nTzg7Oytt79mzJzIyMijXPXDgAAYNGoSWLVsCAGJjYzF79myFe7azszPOnz9PuXYNMplMaTp9BwcH\nTJs2DUuXLqVcU1Xfd32kpqYiPz9fvs3j8bBgwQK1Lt/CwsIEahOzVRs+n4/AwEB06tQJy5cvV2jL\nzc3Fo0ePMGHCBFptIISge/fujMRsHThwAJcuXUJVVRUqKytRWVmJ169fo2nTprC2toa3tzfMzc1p\nt6M2fD4fN27cwI4dO6ChoYHY2FiVBnjTwbJly9CsWTMsXLhQafuJEydw4sQJWpz7cePGISEhAYaG\nhnXaRCIRxowZg0WLFtX7EP83qPJzK0MkEsHZ2RlnzpxBs2bNaNOxt7eHjo6OvM7Omzdv0KRJE2hq\naiq8r6bTdv36dcq0xWIxMjIycPjwYdy7dw979uyBpaVlnfcdO3YMKSkptCXrkEqlyM/Px/Xr17F7\n925YWloiIiICenp6tOgp4+eff0bz5s0ZSQTj7Owsj8WTSCTYvn07jIyMaNf19/dHZGQkdHV1FfY/\nf/4cHh4eOHPmDNq2bUu5bmlpKQwMDKChoaG0vaioCFlZWZTHZJaVlUEoFKJFixb466+/4OPjg0uX\nLinUqXzx4gWGDx+OO3fu0FK/cv78+QgPD4eBgUGdNplMBm9vb0yYMIHSWFBVfd/KuHbtGubPn4+4\nuDiFQTSpVApHR0fs378fXbp0od0OFhZ1RC2dLQD4+PEjJk6ciODgYAwYMIBx/YqKClhZWeHRo0cq\nKWzcEDpFQLXTGRUVhTNnzuDo0aOUd4YvXLiAe/fuQV9fX/4yMDBAjx49YGxsTKnWpzSkB+WnpKWl\nYf/+/UhKSqL82A3xc4eFhaFDhw6YMmUKbRr379+Hrq7uFwvOymQyCAQC2oLqL168iI0bN8LT0xM/\n/vijQptYLMbLly8ZSdYhEAiwatUqPH36FImJiWjSpAntmkD1QM7X/A5UUDNDy+FwIBaL4eTkBG1t\nbdp1P8fff/+N1q1bq9QGOhGJRMjJyYGFhYXCfplMhsePH6sk0RJQXVw7MTERCQkJKtGnk7dv38Ld\n3R3r169XOkC3Zs0aGBsbY+bMmSqwjoXlv4/aOlsAUFJSAiMjI1oqvn8JsViM+/fvw8bGRiX6tVFV\np6g2ly9fxsCBAyk/bkZGBnJychRm9V6+fIns7Gzo6upi0qRJ8PHxgY6ODuXaDRlCCD5+/Kh0lFYd\nef36NfT19RkfTFAVpaWlmDZtGoYMGUJb2vOvQSaT4eDBg5g0aRJ4PJ7K7GBhYQKxWFxnJlsdaGir\nFVhY1A21drZY/h90dYrI/6WFrm+WQ5Xk5ORg+/btyMvLQ3x8PLsEgkWteP/+PZ4/f662dXAkEglu\n3ryJfv36qdqUbxKRSISLFy9i2LBhjMwifkuIRCJs2bIF/fr1axDnd0NcrcDCok6o5R3008BiVSES\nicDn81VtBgCAy+Vi8uTJlDpaL168wPTp0/Hw4UPKjkkl3bt3x86dO/Hjjz/C29sb7969U7VJlPL6\n9WtVmwCA+fP8zz//ZEyrIdOkSRO1dbRKS0vh5eWF58+fQyKRKC0szEIvhBAEBwdDKpWq2hTGEYlE\nSEhIoO2zr1y5Eu3atcPHjx8hkUiQk5ODoqIiCAQCWvS+hJGR0WcHTE1MTFhHi4XlX6B2M1sFBQXw\n9vbGrFmzMHnyZJXOuGzevBlGRkbw9fWlXYvP50NfX592ndpERUXBzs4O6enp8PLyQkhICIKCgmBv\nb6/wvqKiIrx//57xJB21ycvLo3yt//Hjx8HlcutdJkoIQdOmTeHk5ESpbg22tra4deuWypepMnWe\nf/jwAUFBQejZsycWLlxIy2/KosizZ89UUiSbEIIbN24gPj4eAQEBmDlzJu7du8e4HV8iNzcXpqam\nlF2D165dg7a2NjgcDjQ0NKCtrQ0dHR2YmJio5FlmamqKvLw8RjUlEgm2bt2K/v37w9ramlHtGkQi\nEXr16oWsrCxavvcPHz7gp59+grGxMXx9feHq6orWrVvj/fv3EIvFMDIyQtOmTWFubo4pU6YwVjCd\nhYWFHtRuZqtTp0745ZdfcP/+fYwePZrRB3RRURHGjRsn3+7duzcKCgpo15XJZBg0aBDWrl2rNB04\nXfj5+WHz5s0wNzeHnp4e3r17h/DwcKxYsUJhRDAnJwfbtm1jzC5l0NEp37hxI27cuIHff/9d6Wv1\n6tUKaXSpplGjRipxtFR1nuvr68PPzw+vXr3CrVu34OXlRbvm56B79FsZUqkU+/btw7Fjx5Ceno5H\njx6huLgYlZWVlGvdv38fXl5ejPy2ynjz5g2WLl0KKysrfPfddyqx4Uv4+fnVKTHyb9i0aRM2bNiA\niIgILF++HP7+/vD09ISlpSXmz5+PoqIiyrS+BqbuLyKRCFevXgVQ/Tw7cOAAQkJC4OXlhRs3bjBi\nQ220tLRACKHNwW3cuDECAwMRFhaG5s2bw9jYGBcuXEBmZibu3r2LY8eOISwsDNra2mxSChYWdYDZ\nsl7McuLECWJra0suXLjAiJ5MJiP29vby7YKCAjJhwgRGtK2trYmfnx/x8PCgpfhifXz48EH+/+DB\ng4lAICALFy4kCxYskO9/9uwZGTNmDK12nD17tk4RULqxs7P7bHvfvn1p1VdW3PZTqqqqKNdV5Xl+\n9OhRcvXqVULI131+OhEKhcTU1JSxIumEEFJaWkqsrKzIihUrSEBAAPHx8SEjR44ktra2xNXVtd6C\n7v+U//3vf2TIkCG0F8n+lPLycmJrayvf/lJxYbopLCwklZWVdfa7uLgwov/u3TsSExNDbG1tSVZW\nFiOahBBiamrKiI5AICA2NjbybScnJyKRSMjp06eJk5MTiY2NZcSO2jD12SsrK8mQIUOUtkmlUoXv\nhS5evnxJDh8+TLsOC8u3SsPLakAhHh4eaN26NebOnYuWLVvSvoyNw+GgdevWePHiBdq0aQMTE5M6\nI5FSqRTl5eWUZwTkcrlISEjArl274OnpiZ9//hmOjo4K75HJZJQHOtceca5JibxhwwZMmjQJx44d\ng6enJ5o2bUp7keXw8HDG15SravnegAEDwOVy8fbtWzg5OUEmk0EikciTldS8amIXqa71pqrz/OPH\nj9i5cycuX74MACrPfkf36Lcy9PT0YGhoiLCwMIX9MpkMV69eRUhICFxcXCjTGzlyJD58+IA5c+Zg\n//79jJWx0NPTU0nJjPqYNGkSKioqYGRkhI4dO6JTp07o1KkTqqqqGNFv2rQp5s2bh06dOiEwMBAn\nT55ssLN9/wQdHR2FLH8cDgc8Hg+jRo2CnZ0d/P39IRaLERAQoEIr6eFzz5GioiJaimbX5vz584iP\nj0dgYCA+fvyIxo0bA6iOm5w8eTLi4+PRpk0bWm1gYVF31NrZAoA+ffpgyZIlCA4Oxrlz52jvGHXq\n1An5+flo06YNxGIxGjVqhH379qGwsBA5OTn4888/4erqivDwcFr0Z8+eDSsrK4SEhGD9+vXo06cP\nxGIxwsPDoaOjgyVLltCiC1QH0RYWFqJr167Ytm2bPA23np4eysvLadMF0KA6ZnSzZ88eaGtrY/z4\n8eByufDw8MDUqVOhra0NLpcrjyPjcrm0LStVxXmuq6vL6DLZr4Fph7s+PS6XCwcHB1rub97e3sjK\nysKMGTOULseVyWSoqqrC+vXrKdPkcrkKzrRQKMSFCxdgYmKCbt26Uabztejo6ODq1at49eoVnj9/\njmfPnuHp06eMOVs1jBgxAleuXMGxY8cYiQVmkvrO7ZYtWyI2NhYeHh5wcHCAlZUVw5bRw/r169G4\ncWM0atQIFRUVePjwIbp06aJQvqJt27Y4fvw4rXaYmZlhwYIF2Lp1KxYvXow+ffoAAGJiYtC0aVPW\n0WJhoQC1d7YAwNPTE8eOHcPRo0cxceJEyo9PCMGLFy/w/PlzlJaWYsuWLdiwYQNevXoFLpeLmzdv\nwtHREa6urvjhhx9oSWRBasUN2NjYyLPwLVu2DImJidDS0kJUVBTlurWp7WzVLigskUhoc4aKi4vB\n5XIhlUpRWFgIiUQCmUwGqVQqn/GRyWQQi8UQCAS0Jatgkk6dOgEANDU1cfToUYSGhsLPzw9xcXFo\n3ry5wnup7Hyr+jzn8XgKn0csFuOPP/5AmzZtYGhoSKlWQ4XD4dQbI/Ty5UsMHTqUFt3Q0FCMGDEC\nBgYG6Nmzp0JbTRFnqqn9OaVSKQ4fPowXL15AIBDAzc0NCxcuZGyQhcPhyGd0W7duLU8ClJGRwYh+\nbdzd3REWFqZ2ztbnaNmyJUJDQxEREYFjx46p2px/DSEEBgYGIISgtLQUFRUV2LRpk7xo89SpU+Hi\n4sLI7L2JiQkOHz6MnTt3olWrVgCA/Px8nD59GidPnqRdn4XlW0Atna29e/eiZ8+eCpmMFixYgNDQ\nUFqcrTdv3mDcuHGwtLSUT8GvWrUKbdu2xbZt29C8eXN4e3tTrlubTztgpqamCAoKQmBgIGbOnIkF\nCxbQfuOucbY+5f79+2jZsiUtml5eXtDW1kZpaSlcXV3RpUsXEELkMzu1Z3rEYrFaOFu1ad68OXbv\n3o2EhASMGzcOiYmJcmeMahrCeV4boVCIhQsX4u3bt/jhhx/g5uYGHx8fxvSZxN3dHfr6+tDX18eH\nDx8QFxcHU1NTWFlZyZ3aDh06YOXKlbToGxoaYsmSJdizZw927NjB+Iyejo4O9u7dCwAoLCxEVFQU\nJk2ahN27d6vU0ab6eygoKJBnIwSq7+sikUghI2SfPn3Qt29fiESib2pGf+TIkdi0aRMePnyIXr16\nqdqcfwWHw5EXI5dIJEhLS8PBgwchkUiQnp6On3/+GZcuXcKaNWsY+Y0XL16ssL1z5054eHiwWRBZ\nWChC7ZytU6dOIS4urk6lczs7O3C5XGRnZ6NHjx6UarZs2VKeMenp06dYtWoV2rVrBwDo0qUL7t+/\nT6meMj51tl69eoVt27Zh3bp1GDt2LG26y5Ytw/Xr18HlclFRUQGJRIJDhw7JbRIKhRAKhdi4cSMt\n+r/99hsAwMnJCe3bt4e2tjZWrVpF+zr3hkBN/B2Hw8GsWbOgra0NPz8/HDlyBC1atKBcr6Gd53p6\nerhw4QIkEgkyMzOxbds23LhxA5GRkWjUqBHttjDJsmXLIJPJwOfzcf/+fQiFQhw+fBiLFy+Wz/LU\nXn5EB25ubjh+/DhSUlIwevRoWrUARUem9v/t2rVDVFQUQkJCsHr1amzdupV2W2QyGe0aQPUqjNqd\na0IIJBIJbty4Id/P4/Foc6obMjweD5MmTUJpaamqTaGU2rPVGhoacHFxgb29PVauXImpU6ciKSmJ\n0bjQ169f4/Llyzh37hxjmiws6o5apX5//vw5IiIisHv3bnTp0kWhjcPhYMiQIUhPT6fVhvbt2ysk\nC+jcuTOt6b9rqN0JLS0tha+vL6ZOnUqrowUAgYGB2L9/P/bv349Nmzbh+++/l28nJSXh1KlTuH79\nOgYNGkSrHVwuF/v374elpSXGjx+vknTBqqD27z516lR4eHhg5syZtMc2qeo8V9YB19DQgL29PZKS\nkiAWi2lz7FWJjY0N7OzsMHDgQOjp6SEwMBC7du1Camoq3r9/j/Hjx+Ovv/6i3Q4fHx8kJibSriMS\nib5YnD44OBhXrlxhpA5Uq1atlF5T9S3p/Kfcu3cPN2/elL9u3bqFu3fvqmQGiykHEwAqKysV4t/q\n+17nzJmDAQMGMGUWIyg71/X09BAZGYnvvvsOP//8M6P2JCcnw83NTb6kkIWF5d+jVjNbu3fvxty5\nc+uduerevTuSkpLk0/d0oKmpiUaNGqG0tBRGRkbo0KEDnj59SpteDbUfTnv37oWrqyumTJlCu27t\n5YHfffcd3r17p7KAWg6Hgzlz5sDOzg5z5szBunXrKM3M9ilisfizTmRpaSmWLVuGdevW0aIvkUgg\nFosVOmIBAQG4c+eOPNiZLlRxnovFYkgkknrbNTQ0sGzZMri6umLGjBlqObvJ4XAUOsFNmzZFZGQk\njhw5Ah8fH5w6dQpNmzalTd/Z2RkrVqxAbm4urYkqJBIJBg8erLD9KS1atMDy5cspz+yqjKSkJKX7\ny8vLIZVKVZ4Zkw4EAoF8GSPdzp6Ghga2b98OoNr5UHUinJraeTVL0ulELBajf//+StvCw8MxY8YM\n8Pl8WmK9AcDe3h46Ojryz/nmzRs0adKkzrNNJpNBKBTi+vXrtNjBwqLOqJWztWLFCnn6cWXY29sz\n0gEbNmwYysvLYWRkBB0dHXTo0IHWmyVQ/XCoeTAEBgYqpNFlCn19fZSVlaGqqorxZVy1U9pbWVlh\nx44dmDNnDgwNDRVi96gkOTkZGhoa9T6MCSG0/g5mZmZKk4+sWbMGHh4emDRpEtq2bUubPtPnuVAo\nhJmZmXxb2ch7+/bt8eOPP35xVuS/SmVlJYRCYZ39Xl5eKCoqwk8//YTExETaOoiamppwdXVFSkoK\nrc6Wrq4uVq9eLd8uKSlR+r7axbVVwYkTJ9TS0QKqf4NLly4xMqumqakpz4IHVM9gqZKKigoQQuoM\nZtGBgYFBnVIONTRv3hynT5+mvGRLbXbu3AldXd0vatCVCIeF5VuAQ6heB8HCODKZDMOGDUNKSorK\nY1UePnyI7t27M+7sDRw4EBcvXlR4YGRkZCA0NBQpKSl1svSpO3///Tdat26tajNoxdzcHI8ePVKZ\nvlQqRY8ePZCTk8NYwoiqqiqkpqZizJgxddpEIhHWrVuHxYsX0xq/9fr1a+jp6dE6ePQp31oyCBYW\nFhYW9UGtYra+VbhcLi5cuKByRwsAevXqpZJZNaFQWGc2w9nZGcOGDcPSpUsZt0fV0OVovXz5kpbj\n/hNOnTqlUv3ao99M0ahRI6WOFlBda27NmjWUOVo1xaM/pWXLlow6WsC3VUeP5dulqKgIEydOxNWr\nV1VtCgsLC4WotbP1+vVrvH79WtVmsDDAtGnTlM4uBAcH4/Xr13jx4gVlWqWlpQgMDJRnQvwWkEql\n2LlzJxYtWvTZuKkamHBA6Epx/7UYGBggLy9P7RwBPp+PuXPnIisrq8FkfquqqsLq1au/6tyjA6Zj\nVWpmKaOjo3Hw4EGkpqbi1q1byM/Ppy1xBSEE27Ztw8mTJxkv1gyAkQQvDR0TExMEBwcjOjoaixcv\nZjRJCQsLC32onbPF5/Pl/x85cgSnT59WoTWqgcmOgUAgQGpqKiNan2PmzJlKO736+vo4deoUpUk7\nYmJiMGrUKDx+/BiVlZW4ePEibty4gSdPnqCkpEQtH5CEEDRu3BgTJkyQ1zuqjyNHjsDLy4vyTG21\nqS+Gh04ePnyI3NxcxnWZRktLCxMnTsTz588bTPpnHo+H5ORkxut71SAWi7Fw4ULG9KqqqnDmzBno\n6OiguLgYV69eRWJiIoKCgtCnTx8cPHiQck2ZTIb4+HgcPXoUzs7OWLt2LSPJnWq03dzcMGfOHJSX\nlzOiWR8ikUgh0yrTWFtb4/DhwxCLxVixYoXK7GBhYaEOtXK2CgsLMX78ePl2r169GElHDQDXrl3D\n7du3kZmZifv37yMnJwfPnj1TyUgskx2DwsJCrFmzBhcvXmRE759AdXBxQEAAdu3aBbFYjJKSEixa\ntAjx8fFYtGgRxo4dCysrKzg4OGD27Nm4d+8epdq1kUgkOH78OG3Hr42Ghga+++473Lp1C25ubvW+\n79ixY9iyZQuWLFlCW8e4oKAAQ4cOxdq1axnrmMXExCA+Ph5isRgVFRUKyRtUDdWz91paWhAKhZg0\naRJu376NZcuWqbTzCVQnUCCEMJKMIj8/HxEREQr79PX1P5t8iWoaNWoEfX19zJo1CyEhIdiwYQPi\n4uJw+vRpHDhwgJbaYjweDzo6Ojh06BBSUlJgaGgILy8vhIeH0z7TxeVy0ahRIzRr1gzu7u54+PAh\nrXqf4/Lly3Bzc8PmzZtVlhBCS0sLERERyMrKwu+//86otkgkQkJCgjwjIwsLCwUQNcPBwYFIpVJC\nCCGFhYVk7NixjOi6uroSDw8P4uHhQUaMGEGcnJyIpaUl6dmzJwkMDCSFhYW06D59+pSsX7++zn5H\nR0da9OqzwdnZmWRlZTGmqWr+/vtvQgghFRUVZMiQIXXay8rKyIEDB0jfvn1ps6GsrIyMGzeOHDly\nhDaN2kilUiIQCEjv3r1JUFAQKSgoUGi/fPkysbe3J7m5ubTbUlJSQjZs2ED69u1LUlNTadd79eoV\n2bt3L/H09CTFxcXE1taWds2vIS8vj/To0YMUFxfTcnxnZ2eydetW0r9/f7J48eI6vzmTmJqaMqJT\nUlJCHB0diUwmU9jv7OzMiD4hhIhEIjJo0CClbRUVFbTdV2xsbBS2S0pKyMyZM8mECRNIeXk5LZo1\n1FxTKSkpxMbGhhw/flyhXSaTEYFAQKsNhBBSUFBA/Pz8SGJiIvHw8CBlZWW06JSVlRE+n0+EQiER\ni8V1zjdCCLlw4QKZMGECLfr1IRQKiampKRGLxYzqsrCoM2qV+h2oXvNcVFSE9u3bo02bNnUC+t++\nfYuKigp06NCBUt0zZ84o3V9SUoLDhw/D09MTe/bsqbcG2D+lSZMmOHfuHEJDQxVmEuhMFfspnTt3\nRmRkJAIDA3Hw4EFGs+BFRkbKR5w1NTWhra0NHR0ddOzYERYWFrTF09QUfKzvezYwMICXlxdiYmJo\n0a/RSExMxOTJk9GqVSs4OzvTpgVUf1YdHR1wuVy0bdsW48ePx/DhwxESEoKXL19i6dKl2LlzJ0xN\nTWm1AwCMjIwQEhICJycnLFq0CCUlJfDx8aFVT1dXF4cPH4aGhoZKksAoY9OmTRg7dixtte0aNWqE\n+fPnY+7cuTh16hSmTZuGAQMGYMmSJYzO9DCJkZERzMzMkJWVBXNzc5XYwOFw6l2GW1JSwkgNRaD6\nu9i1axdWrVqFOXPm4JdffqH92eLm5gYzMzPMnTsXWlpacHV1RXl5OYKCgtChQwcsX76cVn0TExO8\nePEC06dPR4sWLbBo0SLExcVRrrN8+XJkZGQAqI6Jlclk8vItXC4XPB4PHA4HEokEb968QYsWLSi3\nQRlaWloghEBDQ+26hywsKkPtrqaOHTsiPz8f7dq1w7Nnz6CtrY1169ahsLAQOTk5EIlEGDduHH76\n6SdG7GnatCnmzZuHTp06ITAwECdPnsR3331H2fEbQscAqK5tNXHiRIwZMwbNmjWr004IQVVVFeXL\nDQUCgXypZlVVFfh8Pvh8PpKSksDn8xEcHPzZZW//ls8tlSsqKoKlpSVt2kD18qYdO3Zg6tSpyMjI\nUOgIEUIgEAjqLIn6t2hqamLhwoWYNm0aNm/ejFGjRoHD4WDFihXo3bs3pVpfwt7eHrt378aUKVPQ\ntm3beouD/ls0NTVx6NAhHD9+HBwOBx8+fICvry/09PSgp6cHMzMzuLi4yJ1wJrh27Rry8vIQHR1N\nm0bN+a2hoQFPT08YGxvjxx9/xP3797F3714YGRnRpq1KLC0tER0dDXNzc/B4PHC5XAgEAly6dAnd\nunWDsbExLbo2NjbQ19eHvr4+SkpKsHLlSnTt2hVOTk7yGpEmJiaYNWsWLfrK4HK5WLVqFaZPn46Y\nmBjMnz+fFp3azmWnTp2wZ88eTJ48GW/fvsXhw4fRu3dvBAcH06Jdm5rBFKFQiJEjR6Jnz5606Gzb\ntk3pfqlUKq+bKZFIIBQKGb/OVBUbycKirqiFsyUUCvHgwQM8f/4cBQUFWLNmDRYvXowWLVpAJpOB\nz+dj0qRJMDU1RcuWLVVi44gRI3DlyhUcO3YMvr6+lB5bVR2DT5k+fTrOnj0Lc3NzjB49WqGNEIKK\nigrKNT8XQJyZmYmQkBBIpVK4u7tTqjtnzhwYGBhAR0cHZWVlOHv2LLp27YrOnTvLH1QdOnTAzp07\nKdVVhrGxMYKDg7Fu3ToEBQXJ99c4uFRTkwCkSZMmWL9+PS5evIilS5dCR0eHcq2vwdTUFJs2bcLy\n5cuRlpZGmx3Lly+HlpYWOBwO/Pz84O/vD6FQiMLCQmRlZSEmJgaBgYHw9vamRf9T4uPj4evrS0sa\n9srKSujo6IDH48lH2wUCAdasWYPo6Gg8ffoU06ZNw4EDB2BgYEC5vqqxsLDAqVOnYG1tDalUCrFY\nDLFYjKNHjyI7OxumpqZYtWqV3AGiitOnT8ufWTNmzECvXr2Qk5OD2NhY9OjRA2FhYYzNcNRGQ0MD\nGzZsgKurKzw8PNCuXTvKNT6dyTM2NkZgYCCWL1+OZcuWwcvLi3LN+ujUqRMKCgrQrVs3GBoa4ubN\nm8jNzUV2drY8nooueDyePDZRW1ub1pp5LCwszKAWzhafz8fmzZvRu3dv9OzZE82aNUNUVBS0tLSw\nY8cO6Ovr077E6mtwd3dHWFgY5c6WqjoGn6KhoYGwsDDMmzcPoaGh0NXVpVXvS9jY2CA2NhYzZsyA\nhYUFZUtHCSEYMmQIZDIZKioqIJVKkZGRgdjYWAiFQvj4+GDy5MmMLuUcNmwYjh07hmbNmsHR0ZEx\nXQBwcXFB8+bN4e/vj3Xr1mHAgAGM6gNA//790aNHD+zfvx8//vgjLRrW1tby/zU1NeXbffv2xcSJ\nE/H06VMEBARAV1cXHh4etNhQQ25uLh4/fkzL8iYA8mXJNTPHmpqa2LBhA/r164eBAwdi4MCBeP36\nNZYvX17vCP1/mS5dusDIyAj+/v7yfSdOnJAnxvn1118xadIkxMTEwMLCgjLdmoExQgi0tbUxduxY\njB07FqGhodi+fTvGjh2L6Oho2mfMldGmTRt4eXkhPj4ea9eupfz4nzpbf/75JzZv3oydO3cyucEz\nFAAAIABJREFUdk8rLi5GXl4eSkpKsGzZMpSVlQEAunbtiq5du2LIkCGUlZy4cOEC7t27J5/J1NfX\nh4GBAXr06MHYACkLCwtDqCJQjE6eP39Oxo8fL98+d+4cWbFiBe26+fn5pLi4mLx48YK8ePGCFBcX\n1wkml0gkZM2aNUQoFFKqXVpaSnx8fBT2OTk5EUKqA60PHDhA+vXrR+7fv0+pbn0sW7aMbN++nRGt\nr2HTpk1Kk4hQgUQiUQhkz8nJIT4+PmTatGmktLSUFs36uH37NvH09KRdp77kEDdu3CC2trbk6dOn\ntNsQHh5OLl++rLAvKyuL2NnZEYlEQrt+fQkKnj59Suzs7Cj/7Z8+fUqKiork95effvqJbNy4Ub5d\n8yoqKqLk+3///j2Ji4sjffr0ITExMaSyspIEBQUp3LtEIhEZMmQIOXv27L/W+xqYSpBBSHUyhhEj\nRijs+zRBRlpaGnF0dCQfP36kxQZlCTnS09NJnz59yF9//UWLppWV1WfbCwoKyMSJE2nRtrS0lP9f\nWFhInJ2dyfnz52nRqo/NmzeT0NBQ+Yuu5BiEVP+WO3fuJFu2bCHr1q0jy5cvJzNmzCC2trakf//+\nJD4+npGEIMpg8lpjYfkWUDtnSyKRKHSEHj9+TLy9vWnX7d27N7Gzs5O/bG1tiaWlJeWOlTIaQseg\nNvfv3yeOjo7yrJCqJjc3l9ja2tLyW0gkEjJw4MA6+yIjI8nQoUMJn8+nXLM+ZDIZcXFxIY8fP6ZV\nx9bWllRWVipt2717N+3Zs+Li4sjAgQPJq1ev6rSNGDGCZGZm0qpPSP3OFiGELF++nOzZs4dSPTMz\nM2Jra6twj1H2srW1JT169KBM9/Xr18TX15dMmTKFfPjwoU772bNnyeDBgxlxcJnuAH6aZVSZ87N4\n8WKycuVKyrX5fH69gxp79uwh7u7ulN/PpFIp6dq1K6mqqvri++igd+/e8v9jYmLIyZMnadH5Gp48\neULmzp2rMv0//viD+Pv7kwEDBpAnT54wrs86Wyws1KIWywhrw+Px0LhxY7x69QqtWrVC+/btGSnM\nSGc9pS9Rk7Hoc7i4uCAtLQ2bN2/GmjVraLXHwsICurq6uHbtGu3LN48cOQJtbW15nBQhRJ4EpWYZ\nn6mpKdasWUNLZsKqqiqIRCKFfTweD0FBQXj37h1WrlyJyMhIynWVweFw4OHhgbt37+L777+nTadf\nv34QiURo1KhRnbYpU6bg6NGjOHr0KMaNG0e59qNHj5CYmIijR48qjb90cXHBlStXFJb8UcX69evl\n51pFRQW2bNkCoLre2fDhw+WB9LNnz4ahoSGl2tnZ2ZQe72tp0aIFEhIS8PPPP8PPzw+//PKLwvLg\n4cOH4/DhwygsLETHjh1ps6Pm/kb+L36MCbp37w6ZTAYulwuZTKa0WHlgYCCePXtGubampma9tbSm\nT59OW/3G5OTkL2aho2t5tFgsln/f8+bNo0Xja2ndujUtv+vX0r17d+zcuRPJycnw9vbG2bNnlSae\nYmFh+W+gVkWNa/D29pY/GLW0tODk5AQ+n69iq+ilpmMA4LMdg8GDBzNiz5gxYxjpIKanp+PKlSu4\nfPkyLl++jCtXriA9Pb3O5x82bBgt+oQQTJw4UWnb0qVLUVZWxui5N2vWLNoDySMjI+tNiqCpqYnQ\n0FCcP3+eFu2UlBSsXLmy3vhDU1NTXL16lRZtHR0d+evT7dod1DZt2qhVUDuHw8GiRYvQuXNnJCQk\n1Gn75ZdfaHW0gOqEHa1bt4ZYLKZVpzZRUVFyx+LDhw9K76lt2rRBv379KNfW0tKCvb29fLv2PYTD\n4WDWrFmUDx5xuVz06tWLkcLRnyKTyWBtbc3o7/s59PT0cPbsWVWbgQkTJuCXX35hHS0Wlv84HELq\nKebB8p+ltLQUo0aNwm+//Ua7Vnp6Olq0aIHu3bsr7BeLxQ2mFhEL80gkElrqtHxpZuPjx48QCAS0\nZx3t168fI9dXQ0IikUAkEjGS+KaiogKEEFoyLf7XKCoqwsSJE+Hu7o7Zs2ez34maUFNbq6E9J6VS\nKXr06IGcnBw2BTwLC0Wo5czWt46RkREjHcHt27fj8uXLSkd8G9oDhIVePh2zoasg5pce/o0bN6bd\n0aqoqIBAIKBVoyGioaHBiKN18+ZNeHt748mTJ7Rr/RcwMTHB+fPnUVlZCS8vL3z48EHVJlFORUUF\nzpw5o2oz6oXP5yMhIQFSqZSS4+Xn58PHxwd3796l5HhUUjPQ0VBmGVlY1AHe6tWrV6vaCHWkqqoK\na9euRb9+/RhNAc4kHTt2xPXr15Gbm4uCggI8ePAAxsbG7MgrwyQmJsLc3Fxl51lRURE8PDygpaUF\nMzMztR8N5XA46N27N+2lFBoaTN3Trl69Cg8PDyQkJMDOzg5bt27F/fv3kZ+fj+LiYpSWlkIoFMLQ\n0FDtz7UatLS04OzsDKFQiM2bN2Ps2LG0/QYXL16EkZGR0phMOqgpmdCtWze0atVKZfX6yP/VglS2\nPLOyshK+vr6YN28eJedcUlISPD09kZaWBnNzcyQnJ+Pp06d48+YNysvL5StDVDFoqa2tjXnz5qlk\nOSkLi7qiVssI09LScP36daxatUph/+vXrxkvZiwWi2Fubo7s7Gy1vWkJhUJkZmbCwsIC9vb26Nu3\nL27cuAFra2sEBARQWn+G5f8hlUrx9u1btGrVCgBgZ2eHW7duqdSm4uJirFu3Dnw+H7t374a2trZK\n7VFXxGIxRCKR0piwBw8e4MmTJ7QkJqnRZuKeVlpaCn9/fyxevBgdO3bEyJEjMXnyZHz48EH+ev36\nNf7++2/Mnz+fliLSAoEA6enpGDFiBOXH/rf4+/tjwIABGD9+POXHfv/+PRwdHaGtrY3BgwfDy8uL\n9vs4n89HRkYGEhMTERISAltbW1r1PmeHjY0NHj16VMfJEQqF6N27N3JycijRKi0txfTp0zFz5kzY\n2dlh5MiRGDx4sMI5/u7dO7Ro0QLz58+Hi4sLJbrKePjwIbS0tNCtWzfaNFhYvnXUJhvhvn37kJeX\nhzFjxqCgoEBeePDPP/+Ep6cnzp8/jzZt2jBmj6amJgghjDlae/fuxQ8//IC+ffsyogdUj4DVBIc3\natQIu3btAp/Px/HjxzF37lz069cPYWFhatnxrp0FUUNDA9ra2tDR0UHHjh1pP88qKiowduxY/P77\n7wDQIJIxtG3bFjt37kRERATmzZtXJ5ECFTTkDjBTREREoEmTJggICKjTVlVVhdOnT9PmbDF1TzMy\nMsKRI0fA4XBQWVkJAwMDzJkzp877Hj9+DG9vb1qcrcLCQnkGUzo7up9y9+5dlJeXQ0NDAzweD1wu\nV/7i8Xjg8XhwdnbGrl274OnpSfnsloGBAYyNjXHo0CGcPHkSwcHBMDMzw+rVq2FkZESpVg36+vrQ\n1tbG9u3b4evri06dOsHb21shQQgT6OnpgcPhKJ1N4nA4lH7XRkZGOHz4MHR1dVFZWYkmTZpg3bp1\nCu+RyWS4evUqQkJCaDsHY2JikJeXhx9//BEVFRXYvHkz2MVOLCzUozbOlre3N+Li4hAVFaVQ3X7T\npk0YO3Yso45WDUwucYmPj0eTJk2go6OD2bNnw8XFhVH9Gi19fX1MnToVY8eOxdKlSzF16lTExsai\nSZMmjNnCBOnp6fLlJlVVVeDz+eDz+Xj9+jXatWuHkJAQWtKPA9VxSbWXujSUpVQcDgehoaGYPHky\nzp07h+HDh1N6fFV1gGuIjIyUDxxoamoqONgWFha0lBb4lOnTp2Py5MmYNWtWnUEMY2NjlJWV0arP\n1LlWo/M5vXbt2tE2kGNqaopDhw7B19cXrVq1Qo8ePWjR+ZTffvsN2dnZIIRAJpPJkyjU/JXJZJBI\nJDAwMMD79+/RtGlTSvV5PB5kMhmaNWuGmTNnYvLkyYiOjsaoUaMQEREBR0dHSvVqcHFxQVVVFSor\nK2FtbY21a9dCKpVi0aJFGDRoEC2an0K1Q/UlauIf6zvHuVwuHBwcaIt/BYDx48fj3LlzCA8Px9at\nW3Hu3DnW2WJhoQG1cbY0NTVhZmYGf39/+cjrtWvXkJeXh+joaBVbRz+GhoZITU1FZmYm4uPjsWXL\nFqxfvx69e/dWiT36+vqIjo5GeHg4AgMDsW/fPrVaTrlr1y6l+0UiEVJTUxEYGIhNmzbRkhaa6U5B\nbZ4/fw6RSFRn5L3mfx6PB29vb+zYsYNyZ0tVHeAaBAKBvL5RbQc7KSkJfD4fwcHBcHNzo9UGExMT\nODk54dSpU5gwYYJCm6GhISoqKmjVZ5rPOVslJSWYPHkybdqdO3dGZGQkAgMDcfDgQbRu3Zo2rRrm\nz59Pu8aXqH1vadSoEUJCQtCvXz8sXLgQsbGxsLKyokW3JkZp2rRpmDZtGjIyMrBmzRpcvHgRS5cu\nRePGjWnRVTWfO8dfvXqFoUOH0qZtZGQEXV1dHD58GBoaGmxiKxYWmlAbZwsABgwYoLAdHx8PX1/f\nbyJhQ40jY2NjAxsbG6SkpGDy5MlYsmQJLctsvgYOh4Nly5bB19cX0dHRCAoKUokdTKKlpQV3d3cY\nGxsjKCgIx48fpyVesHaopVgsRmxsLExMTODg4EDbch+gOhnHnTt3lI68S6VSEEIgkUhACMHbt2/R\nvHlzSvVV0QGuYcWKFfW2ZWZmIiQkBFKpFO7u7rTaMWnSJAQHB9dxtho3bgyhUEirNhMQQmBjYwMD\nAwPo6enhzZs3WLlyJbp27QonJyd5YpI2bdrgxx9/pNUWKysrTJw4EWPGjFFa64gQgqqqKly8eJFW\nO5hg0aJFGDt2rNLOf9++fREREYGAgAAcPHiQlrpqPB5PoVizs7Mzzpw5g/DwcEydOhVJSUkNYsk0\nFRBC4O7uDgMDA+jq6qK0tBTx8fHo2rUrrK2t5Z+zXbt2WLlyJW12aGpq4tChQzh+/Dg4HA4+fPgA\nX19f6OnpQU9PD2ZmZnBxcZHHB7OwsPwz1MrZqk1ubi4eP36MuLg4VZvCCJ8+IC9duoSxY8fi7Nmz\nePbsGZYvX64Su3g8HtatW4dRo0bBy8sLxsbGKrGDaWxtbTF48GAkJycjMDCQdr2SkhI8fPgQYWFh\n6NmzJzZu3EhLIcywsDDKj/n/l4bYAbaxsUFsbCxmzJgBCwsLdOjQgTYtU1NTVFZW4sWLFwrLozkc\njkJn9b8Kh8NBSkoKZDIZ+Hw+/Pz8YG5ujpycHMTGxsLc3BxhYWGMFXqdPn06zp49C3Nzc4wePVqh\nrSaDHVUkJCTg3Llz0NfXl78MDAzQo0cPWFlZ0ZoBs1u3bli2bBlKS0tRXFyMtm3bKrQPGjQIL1++\nxOrVq/HLL79Qqp2RkaE03lhPTw8REREIDQ3FvHnzEB8frxazLxwOB8uXL5ef448ePUJlZSUOHTqE\nkJAQjBo1CgsWLGCk1MLy5cuhpaUFDocDPz8/+Pv7QygUorCwEFlZWYiJiUFgYKDKBm1ZWNQCoiY8\nffqUFBUVkRcvXpAXL16Qn376iWzcuFG+XfMqKioiT58+ZcQmU1NT2jV2795NUlNTiYeHBxGLxYQQ\nQk6ePEk8PDyISCQiAoGAeHh4kF9//ZVWO2xsbD7bvnHjRrJq1SpabWho3L17lzg5ORGpVEr5sQcM\nGCD/f+DAgfL/hUIh2bFjB3F0dCTPnj2jXLehIBaLyejRo8mKFSvInTt3FF6ZmZkkPT1dJXZt2rSJ\nrF+/nnad8PBwcvToUYV9Hz9+JE5OTrTqMnFPq41EIiGDBg2Sb4tEIrJlyxbi6OhI7t27x5gdDx8+\nJI6OjqSiooJWnYKCAnLnzh3y+++/k7S0NJKSkkLi4uJIQEAAcXBwIL6+vuSPP/6gTV8qlZI9e/YQ\nBwcHkpaWVqddIpGQoUOHkosXL1KqO378eOLi4kIcHR2VtkskEuLv70+2bNlCqe6ndO/eXel+oVBI\nzMzMaNGUSCTExcVFvv3u3TsSFBREXF1dyV9//UWLZn307du3zr4nT56QYcOGkRMnTjBqCwuLOqE2\nM1ujR4+WZxOqzYkTJxS2CSEQCATIyspi0jzaaN++PXbt2oXc3Fzk5eXhhx9+wPbt27F79275Gvht\n27bB09MTNjY2tIy4k/9bUvY5xo0bh6ioKMq1VcW1a9fk2QiB6u9AJBKhb9++8n2WlpaYMmUKpFIp\nYzFWWlpamDNnDmQyGRYvXoxff/2V0uMfPXoUV69eVTrybm5uzljmSQ0NDYSFhWHevHkIDQ1lZAT4\na3Bzc8PUqVMRHBxMacIMsVgMDQ0N+bk1YMAAnDhxAp6engCqz7/U1FS0a9eOMs2GACFEYcmspqYm\nFi5cCCsrK8ydOxdHjhxh5DObm5vDyckJe/fuxdy5c2nT6dixY71L9EQikTxmccmSJRg1ahTl+lwu\nFzNmzIC9vT0CAwNRVVUFV1dXeTuPx0NwcDBu3rxJaeKK5ORk3Lx5E5s2bcLcuXMREREBAwMDBd1V\nq1bJV0jQsXxYIBDIl0MzGV/86fOzadOmiIyMRHJyMnx8fHDq1Clal4Z/iS5dumD79u3w9vZG//79\n1S7ZFQsLE6hVna2GRrdu3ZCbm8uIVmpqKtavX485c+bA1dVV4UEFAFFRUSgoKEBMTAzl2gKBAFZW\nVox91oaAm5sbNDU1FZwtiUSC48eP077MpbKyEoMHD8Zvv/0GoHp5z6VLlxTeIxAIMGjQIGzevJnS\nJB0PHjxAYWEhhEIhBAIBKisr8fLlS2RnZ+Ovv/6Cq6sr5syZw1hdu+XLl6N169a0doBrqJ3uH/h/\nDva4ceMUnOnz589j2LBhlGqHh4fj4MGDCtoAFLZbt26N9evX05oym8l7GgCUl5dj+PDh8jIHtdm3\nbx9Onz6N5ORkRjJBPnjwAIGBgUhPT1dpofpHjx4hICAAx48fp3UpZX5+Pnx8fBATE1MnsyohhJbM\nlGKxGFFRUUhLS0NSUlKdWKGoqCiUlJQoZBymColEgj/++APm5uZ1Phufz4e1tTXy8vIo1+Xz+Rg2\nbJj8fl6byMhIZGdnIzExkZFMoP369VNqB1Ads9qxY0fMmDGDdjtYWNQN1tmiCYlEgp49eyInJ4ex\ndMkvX75EYGAg+vbti4ULFyq0ffz4ES4uLjh48CC6dOlCqa5MJkNxcbHajao3VAQCAY4ePYqpU6cC\nABwdHXHt2rU677tx4wZ69uzJWIKYd+/eYdeuXTh79iy2bt0KOzs72jWZ7ADPnj27TqdeLBYjJiaG\n1vTMQPWsxueyUHK5XNrvM6q4pwmFQty/fx99+vSp00YIQUJCAqZNm8aIswUAw4YNw5IlS+Ds7MyI\nXn0IhUJGZpHv3buHLl261Bm8o5sDBw7g0KFDOHToEAwNDeX7+Xw+3r9/T2vsmjLKy8sRERGB8PBw\nyq91gUCACxcuKE2sIxKJsG7dOixevJi25CDr16+XDyIlJSXJM3xKJBIMHz4cPXv2BAC8ePEChoaG\napOkhIWFSVhniyY+fvyI0aNH4/z584x1BIDqyvTe3t7w8fGpE9Can5+Pzp07M2YLCzMMHz4cZ86c\nob3D/7VcuXIFISEhSE1NZSSJQUPpAKs7qrqnNSTi4+MhFosZmUlVBWVlZXjz5g2+//57VZuCjRs3\nYvDgwbC0tFS1KYzC5/MZzaAcFRUld7bi4+Mxa9YsANXOlouLC7p168aYLSws6grrbFHAu3fvcPr0\nafj6+qraFADVI1AfP36Eqampqk1RW9LT09GiRQt0795d1aYwytmzZzFy5Mgvvo+OtO/1oe4dYJaG\ng1gsVotseMpITk7GoUOHEBQUpHTgQiaTYdWqVTA1NWUz09FEUVERJk6cCHd3d8yePZvxsjWfW0bI\nwsLyz1HdwnOG4fP5SEhIgFQqpfS4+fn5mDt3Llq1aoXCwkJKj/1PadOmDeto0cj27dtx+fLlLyYF\nYQomxktEIhF8fX2RnZ39xVTXMpkMHz9+pN2mGqZPn846WjSye/duRs6xhkzN51dXRwsAevbsiYCA\nAMTGxoLP5yu05ebmYsKECXjy5AlcXFxo0T916hTKyspoOfZ/BRMTE5w/fx6VlZXw8vLChw8fGNOu\nqKiAQCBgTI+F5VtCrWa2yP/VPFE2GlRWVoY+ffpQHm8gFotx+vRpHDt2DLNnz/7slLtEIoGOjo5K\nMwux/Hvevn2LqKgoaGhooH379uBwOBg5ciRjSSFqU1VVhcGDB6Nfv36YNWsWLcVGa7h79y5SUlLQ\nsmVLzJkzR+l7CCFYvHgxnjx5gpMnT9IS20NXcD6LchwcHHD9+nVVm6EymLzGVMm7d++wbds2zJ07\nFy1btkRVVRXOnz+P5ORkFBYWYvbs2fDy8qLF4ZTJZDA3N0eLFi0QFRWFXr16Ua7xX2Pv3r04c+YM\nfv31V0aWiIvFYty5c4fWBDssLN8qDSPIgyIqKipgY2ODR48e1XkgNGrUCBwOh/JOmqamJn744Qfs\n378ftra20NLSqncUmM/nY9GiRZRn85FKpZg6dSpMTEwwfvx49O7dm9LjsyhiYGCAESNGwMLCAvb2\n9ujbty+io6NhbW2NgIAAWFhY0KpfUVGB1atXY/PmzdDW1oZEIkHr1q0xceJE9O/fH6tWrYKOjg7l\nuu/evUPv3r3RqlUrpcupCCFYunQpnjx5gt27d9PmEI0aNQqVlZVwcHDAoEGDYG9v/83GEDGBOs/m\n1IeqrjFVYmhoCDs7OyQlJSEnJwfZ2dno1q0bxo4di+HDh9OaGIHL5UJPTw/BwcGYNWsWZs+ejenT\np9Om919g+vTpuH37Nk6cOIHx48fTrqepqck6WiwsNKF2M1tmZmbIycmp0yYSiWBpaYns7Gza9G1s\nbJCZmfmP2/8NFhYWmDZtGi5cuAAej4eJEydi/PjxDSZpgrpS85vy+XwcP34c8fHx6NevH8LCwmjL\nFiYWi+Hk5IQbN24AAPr374/09HTw+XysXbsWeXl5iIuLo2WmrbKyEr1794axsTH8/f3h4eEhP8d2\n7NiBS5cu4ZdffkHjxo0p167B2dkZGzZswJ9//omMjAxkZWVh1qxZ8PX1ZbQ+jrpz69YtcLlcBAYG\nYsuWLZBIJJDJZJBKpZDJZPJtsVgMgUCAiRMnqtpkylDlNaYqCCGYN28eunbtil69eqFXr14KmQDp\nxs7ODrdu3UJBQQEWLFiAHj16YP369fL2kpISlJeXq83M4t27d1FeXg4NDQ3weDxwuVz5i8fjgcfj\nIScnB/Hx8bh48aJKyw2wsLD8O9TK2QKAHj16KHWomHC2bG1tcfv27X/c/m+o7chlZmYiKioKlZWV\niIqKoqWQMUs1n/6mfD4fS5cuxZs3bxAbG0tbAcjagcw1HcEaoqKikJmZiQMHDtDygO7Tpw+2bNmC\n7du3o6ysDD///DP++usvbNq0CcnJybQnxvi0rlh+fj6WLl2K7777DjExMYwVVlZ3JkyYAG1tbdy7\ndw9cLhd9+/aVdwpr0tDX/C8WixEdHa1qkylFldfYt0jte2lVVRWCg4PRsmVLrFy5Eo8ePUJgYCDG\njBmDwMBAFVtKDdHR0cjOzpYXNa4ZxKj5W3tAY8+ePWjatCktdkRGRsrvmZqamtDW1oaOjg46duwI\nCwsLdtUACwsFsNMeakLtJVs2NjY4dOgQ4uPj4ePjgz179qBr164qtO7bQV9fH9HR0QgPD0dgYCD2\n7dvH+GzL/PnzMWXKFOzevVuexpdKOBwOHBwc4ODggFOnTmHGjBmQSqU4ePAgYxkIa9O5c2ccOnQI\nc+fORUREBFavXs24DepIcnIyAMDJyUke77p27Vral8n+F6D7GvsWqT3u26hRI0RFRcmXFN67dw+L\nFy+Gp6enCi2klvnz56vaBADVdb4kEgmAaieXz+eDz+cjKSkJfD4fwcHBcHNzU7GVLCz/bVhnS42Z\nNWsWmjZtCn9/f5w6dYrxwpTfKhwOB8uWLYOvry+io6MRFBTEqD6Xy8Xq1asxefJkWgq+1s7C6O7u\nDmtra8ycORMpKSkIDg6mVKs2SUlJ0NLSUpoNkcfjITIyEmPGjEFGRgZbc4tCuFwuNm3ahNOnT8Pf\n3x8hISFKC7B+S9B9jamK3377Dd9//71Klkd+ushGS0sLzs7OSEpKwr59+765MhtMsWLFinrbMjMz\nERISAqlU+s1f8yws/wbW2VJzxo4di5ycHISGhmLnzp2qNuebgcfjYd26dRg1ahS8vLxgbGzMqH6X\nLl3Qvn17/O9//8OYMWNo1Wrbti0OHjyI6dOnQ1tbG/PmzaNF58GDB9DS0oJIJFLaXhNgHxsbyzpb\nFFIzaz569Gj06tULU6ZMQUVFxTdfa4nJa4wJRCIRtmzZguLiYmhqaqJ79+7o378/Bg8ejBYtWtCu\n/6mzdfbsWezfvx8HDhxAmzZtaNdnmoSEBJw7dw76+vryl4GBAXr06AErKyuYmJio2kTY2NggNjYW\nM2bMgIWFBRuSwMLyD1G7xeZqFoJGCcHBwcjKyqItXoxFOW3atMGECRMQHx9P6XFlMtlXnec//fQT\nHBwcKNWuDyMjI8TGxuLIkSMKsS1UEhkZiYiIiM8G7bu4uODFixfIy8ujxYZvkdpLlDt06IDExETs\n2LED58+fV6FV9NIQrzG60dLSwokTJ3D79m0cPnwYbm5uuHv3LgYPHoyAgADk5+fTql/7+87IyMCG\nDRuwe/dutXS0gOp71bJlyzB79myMGTMGjo6OaNGiBS5fvgwvLy/4+fkpTfbFNF27doW7uzsOHz6s\nalNYWP6zqJWzJRAIIJVKKS9c/LXUN+Jeg6rs0tXVhZ+fH+Li4lSir67UBDZ/jnHjxqG0tJRSXYFA\nIM/29zkbrK2t0apVK0q1gerz+NOipwBgbGyM8PBwrF69mtbimJ9LKc/lcpGQkMAW9aaY2udYly5d\nsGvXLqxcuRLPnz9XnVE0ouprTNW0a9cOo0aNwpYtW5CRkQFTU1OMGzcOMTExtA1o1j5LUwXEAAAG\nv0lEQVRuRUUF4uPj0blzZ1q0GgIdO3aElZUVHBwc4OLiAjc3N8yaNQvbtm3DlStX0K9fP/j6+iIl\nJUXVpsLNzQ2nTp36Yh+HhYVFOWq1jFBLSwvJyclKs0OJRCJ5ECgd1NRhEQqFSrOhiUQiVFRUQCaT\n0ZK9SiwWf7Z91KhRePXqFeW63zKVlZVK44dq07FjR2zbto1SXX19ffmsgkAgQFVVFaXH/xLBwcH1\nJv0YMGAADhw4gJiYGISEhNCiTwjBnTt3QAiBRCKBlZWVQswM62hRS2VlJYRCoUJdKXNzc/j4+GDR\nokU4cuSI2qXcV/U11pAwNDTE3LlzMWrUKPj7+0NbW5uWpCAikUhev2/EiBGUH/+/hJaWFqZNmwZL\nS0sEBATAwcEBzZo1o0XryJEj0NbWlg9iEUIgEokwbtw4eV/F1NQUa9asUZvYRBYWplG71O/1UV5e\njoiICISHh6us9pRAIICuri7lx5VIJLC0tMTNmzdpOT6LcmQyGYqLi9GuXTuV2UAIwYcPH2hLMf9P\nePr0KY4fP06bszV58mRUVFSAw+FAIpEgMTGRtrTILNWxM0OGDKlT3FgkEiEgIABr1qxRy9mdGhri\nNaYqysvLwePxKC9wLJPJEBcXBz8/v2+yiPbnqG8Alypmz55dx4kSi8WIiYlh63SysFDEN+NssbCw\nsLCwsLCwsLCwMIlaxWyxsLCwsLCwsLCwsLA0FFhni4WFhYWFhYWFhYWFhQZYZ4uFhYWFhYWFhYWF\nhYUGWGeLhYWFhYWFhYWFhYWFBlhni4WFhYWFhYWFhYWFhQZYZ4uFhYWFhYWFhYWFhYUGWGeLhYWF\nhYWFhYWFhYWFBlhni4WFhYWFhYWFhYWFhQZYZ4uFhYXlKxk+fDgOHjyIlJSU/6+duwdtao3jOP5N\njKFgUYilEV/AQUGlICeDiyLFTtJCxSXUVlRaBSl0KVgdK0XErYPWURfRDoIuBtHqIog6FJWCUF8Q\nCqZY0SYxtinEQW64sXqptud6L3w/0zn/58nz5DnDCT/Oc8LevXsJgoD29nZevHhR6TM1NUVfXx+N\njY0EQUA6nebRo0eV9oGBAXp6erh16xbNzc0EQUBnZyfZbJbXr1+TTqfZvn07LS0tjIyMVM0/PT3N\nqVOnaGxsZOfOnZw8eZIPHz78a+uXJEm/xrAlSQu0atUqRkZGOH/+PP39/dy5c4eGhgYOHTrEzMwM\n5XKZzs5OisUily5d4u7du6RSKbq7u/n8+TMAK1asYGxsjAsXLjAwMEAmkwGgr6+P7u5u2trauHfv\nHu3t7fT09PD+/XsA5ubmOHDgAJOTkwwNDXH16lUAjhw5wtzc3J+5IJIk6R8ZtiRpgZYvX87jx4+5\nfPkyO3bsYPXq1fT29lIoFHj+/Dnj4+PE43HOnTvHxo0bSSQS9Pb2UiwWGR8fr4wxMTHB0NAQQRCQ\nTCY5fvw4Dx8+pLW1lX379pFIJGhrayORSPD06VMAbty4wcePHxkcHGTr1q1s2LCBM2fOEI1GuXnz\n5p+8LJIk6ScMW5L0C5qbm1mzZk3lPB6PU1dXRz6fZ/PmzQwPD1NTU1Npj8Vi1NbWMjMzU6lt27aN\n9evXV86TySSRSISmpqaquerq6piengZgdHSUPXv2UFtbW2mPRqM0NTXx4MGDJV+nJElavNif/gKS\n9H/S0NAwrxaJRCrHb9++ZXh4mNHRUbLZLF++fOHTp09V/f8etOBbaAJYt27dT8d99+4dT5484fbt\n21V9Zmdn2bRp0+8tRpIkhcqwJUlLZGxsjI6ODlpaWjh27Bhr166lpqaG/fv3L3rsZDLJwYMH6ejo\noFwuV7XFYt7KJUn6L/IXWpKWyPXr19m9ezenT5+u1Kampsjn84seOwgCMpkM9fX1VfX79+8Ti8XY\ntWvXoueQJElLy3e2JGmBZmdnf/jPf6VSiVKpRH19PS9fvuTZs2dMTk6SyWTo6uoiGo1SKpWq+n7/\n+XK5/MP6X7XW1lay2Sz9/f28evWKiYkJrl27xokTJ4jH4yGtWJIkLYZPtiRpgXK5HIVCYV69WCyS\nz+c5fPgwb9684ejRoyxbtoxUKsXg4CDpdLry3lahUJj3pCuXyxGJRMjn86xcuXLeuPBtq+CVK1c4\ne/YsXV1d5HI5tmzZwsWLF0mlUiGuWpIk/a5I+fvN/5IkSZKkRXMboSRJkiSFwLAlSZIkSSEwbEmS\nJElSCAxbkiRJkhQCw5YkSZIkhcCwJUmSJEkhMGxJkiRJUggMW5IkSZIUAsOWJEmSJIXAsCVJkiRJ\nITBsSZIkSVIIDFuSJEmSFIKv6/uI8FE4tBgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111d4bba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sex_counts_male.plot(kind='bar', stacked=True)\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### soloで♀率が高いポケモンをpost数上位50匹から20匹表示する。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>ambiguous_gender</th>\n",
       "      <th>female</th>\n",
       "      <th>male</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ニドクイン</th>\n",
       "      <td>0.018692</td>\n",
       "      <td>0.962617</td>\n",
       "      <td>0.018692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ロズレイド</th>\n",
       "      <td>0.035971</td>\n",
       "      <td>0.949640</td>\n",
       "      <td>0.014388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>エンニュート</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.935252</td>\n",
       "      <td>0.064748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ニドリーナ</th>\n",
       "      <td>0.067961</td>\n",
       "      <td>0.932039</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ミルタンク</th>\n",
       "      <td>0.016260</td>\n",
       "      <td>0.918699</td>\n",
       "      <td>0.065041</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex     ambiguous_gender    female      male\n",
       "name                                        \n",
       "ニドクイン           0.018692  0.962617  0.018692\n",
       "ロズレイド           0.035971  0.949640  0.014388\n",
       "エンニュート          0.000000  0.935252  0.064748\n",
       "ニドリーナ           0.067961  0.932039  0.000000\n",
       "ミルタンク           0.016260  0.918699  0.065041"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sex_counts_female = pd.crosstab(solo_sex_top_df['name'], solo_sex_top_df['sex'])\n",
    "sex_counts_female = sex_counts_female.div(sex_counts_female.sum(1), axis=0)\n",
    "sex_counts_female = sex_counts_female.sort_values(by='female', ascending=False)\n",
    "sex_counts_female = sex_counts_female.head(20)\n",
    "sex_counts_female.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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nGjFihGJiYjRq1CgdP35cn3zyiW677TbdcMMNmjRpkqxWqyvryJEjmjJlinr0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\nIYQQQgghHPg/KFk+FnSeIjsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f0fee10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sex_counts_female.plot(kind='bar', stacked=True)\n",
    "plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "csvに書き出す"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#solo_sex_df.to_csv('poke_solo.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### feral / anthro"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "soloイラストで、タグに feral または anthro が入っているポケモンのTOP20をみてみる。feral, anthroの定義は下記を参照。<br>\n",
    "feral: https://e621.net/wiki/show?title=feral\n",
    "<br>anthro: https://e621.net/wiki/show?title=anthro"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "solo_df = df[df['tags'].str.split(' ').apply(lambda s: bool(s) if 'solo' in s else False)].copy()\n",
    "solo_df = solo_df.reset_index(drop = True)\n",
    "\n",
    "solo_anthro_df = solo_df[solo_df['tags'].str.split(' ').apply(lambda s: bool(s) if 'anthro' in s else False)]\n",
    "solo_anthro_df = solo_anthro_df.reset_index(drop = True)\n",
    "\n",
    "solo_feral_df = solo_df[solo_df['tags'].str.split(' ').apply(lambda s: bool(s) if 'feral' in s else False)]\n",
    "solo_feral_df = solo_feral_df.reset_index(drop = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "45634"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(solo_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "23048"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(solo_anthro_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12049"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(solo_feral_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYAAADABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYA\nAADABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYAAADABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYAAADA\nBKEZAAAAMFHq0OxyuXT06FG5XK4S1zscDh04cOCyKwYAAAAEilKH5ry8PPXo0UNnzpwpcf3XX3+t\nSZMmXXbFAAAAgEBR6tAcFhYmwzAUHh5e4vpmzZrp4MGDl10xAAAAIFAEX+qGb731lt5//31Vr15d\nFotFI0eOlMVi8drGMAzt379f1113nc8rCgAAAFSUSw7NLVu21B133KHq1atr586d6tGjh0JCQopt\nFx4erttuu82nlQQAAAAq0iWH5k6dOqlTp046d+6cnn76ad1zzz0X7aIBAAAAXElK3afZYrHomWee\nKbGVGQAAALgSXXJLs1toaKgGDBigc+fO6dtvv5XNZvNa73A4ZLPZ1L9/f59VEgAAAKhIpQ7NkrRv\n3z498MADys3NVe3atb0GBDocDuXn5xOaAQAAcMUoU2ieOXOm+vXrp4kTJyo0NNTXdQIAAAACSpl+\nRnvv3r166KGHCMwAAAC4KpQpNNevX1/79+/3dV0AAACAgFSm0Dx69Gg98cQTOn78uM8qkp+fL+l8\nn2iHw+Gz1wUAAAAuV5n6NOfk5KhRo0bq1auX7rrrLq9fACwsLFRubq4eeeSRUr3mkCFDdOTIEWVn\nZ+sf//iHbrnlFq/1a9as0dq1a5WWlqbo6GgNGzZMgwYN8tpm06ZNWrVqlVJSUhQWFqYBAwZo1KhR\nCg7+dTd37dqlFStW6Mcff1RISIh69uypxx57TNWqVSvDOwEAAICrQZlC85tvvqmaNWuqXbt2ysjI\nUEZGhmed3W5XTk5OqUPz+++/L0nq0aOHqlev7rVu9erVWr58uRYtWqTY2FilpaVp3LhxcjqdGjx4\nsCQpKSlJTz75pBYuXKi4uDhlZGRo6tSpysnJ0eTJkyVJqampGj16tJ599lm9+OKLOnXqlGbPnq3H\nH39cCxYsKMtbAQAAgKtAmULzp59+6ut6eBiGoSpVqngtW7FihWbOnKnY2FhJ53/SOzExUUOGDNG9\n996r4OBgvfrqq5o4caLi4uIkSY0aNdLixYvVrVs3DR8+XHXq1NGbb76p+++/X927d5ck1alTR889\n95y6deum5ORk3XDDDX7bLwAAAFReZerT7G9F530+ePCgsrKy1LFjR69tWrduraioKCUnJys/P1/b\nt29Xjx49vLaJjIxU+/bttX37dknSxo0b1atXL69tQkJC1K1bNyUlJflpbwAAAFDZlamluW/fvqpR\no4ZXX2E39y8Crlu37rIrJ0lHjx5Vs2bNSlzXuHFjpaenKyoqSpGRkYqIiCi2TZMmTZSeni673a5T\np06pefPmxba55ppr9PPPP/ukvgAAALjylCk033HHHQoLC1NISIhn2e7du/XJJ5+oY8eO6tOnj88q\nmJWVpbCwsBLX1apVSzab7Te3iYyMlM1m05kzZxQSEuJV5wtfpzSCgiwKCrLIai2fxnqrNUjBwQH5\nxQAAAMAVr0yhecyYMSUuf+yxx/TAAw+oZs2al1WposLDw3X27NkS1+Xm5io6Ovo3t7HZbIqJiVF4\neLgcDofy8vKKDTS02WyKjo4uVb2iosJksVgUEVE+s25ERFRTZGTJDwYAAADwrzKF5oupX7++ZsyY\noYSEBJ+1Njdp0kQZGRkyDMOrr7MkpaWlqUGDBmrQoIFsNptycnIUHh5ebJu4uDhVr15dtWvXVnp6\nutq0aVNsm6ZNm5aqXllZuQoKsig7O79M+1Va2dn5OnMmt1zKAgAAuBL4ssHRp6FZOj9A78SJEz57\nvebNm6tatWrasWOH12DAPXv2yOFw6LrrrpPValW7du20YcMGDRw40LPNiRMnlJKSoq5du0qSunTp\nog0bNniF5ry8PH311VcaOXJkqerlchlyuQw5na7L3MNL43S6VFhYPmUBAADAm887ya5atUqtWrUq\n8987nU45nU6vZZMmTdLUqVOVnJwswzB06NAhPfHEE4qPj5fVapUkjR8/XnPnzlVSUpKcTqcyMzM1\nbdo0DRo0yNNdZOzYsXrjjTe0fv162e12ZWdnKyEhQTfddJNatGhR9p0GAADAFa1MLc09e/ZUWFiY\n1+wZLpdLmZmZys3N1cqVK8tcoby8POXmendDcHf1mD59ujIzM9WoUSMNGzZM/fv392xz4403KjEx\nUYmJicrIyFCdOnXUr18/rxbkJk2a6NVXX9W8efM0a9YsRUZGqnv37powYUKZ6wsAAIArn8UwDKO0\nf/Taa68VC83S+UF7HTp0UFRUlM8qGKhOnsyRJH333beau+ZrRTX0X0t11pH9mnLP79W+fZzfygAA\nALjS1KkTbr7RJSpTS/Pw4cN9VgEAAAAg0F3WQMCPP/5YO3fu1LFjxxQTE6OOHTuqd+/evqobAAAA\nEBDKNBCwoKBAf/7zn/Xcc88pJCREN910k0JDQzVv3jwNHjxYBQUFvq4nAAAAUGHK1NK8YMEC1ahR\nQxs2bFBoaKhn+cSJE/XII49o4cKFmjJlis8qCQAAAFSkMrU0b9myRRMnTvQKzJJUpUoVTZgwQf/5\nz398UjkAAAAgEJQpNJ84cUL16tUrcV39+vV18uTJy6oUAAAAEEjKFJpbtWqlb775psR1O3bs4IdC\nAAAAcEUpU2geMWKEZs2apS1btngt/+qrrzRr1iw9+OCDPqkcAAAAEAjKNBDwjjvu0KlTpzRp0iRJ\nUr169ZSZmSnDMDRu3Dj98Y9/9GklAQAAgIpU5nmahwwZon79+ik1NdUzT3OrVq1Uo0YNX9YPAAAA\nqHBlDs2LFi3SgQMHtGDBArVv316S9OCDD6pu3bqaM2eOgoLK1PMDAAAACDhlSrZvvPGG1q1bp/vu\nu89r+Zw5c5SamqqXXnrJJ5UDAAAAAkGZQvPatWs1f/58dezY0Wt5/fr19dRTT+mzzz7zSeUAAACA\nQFCm0Pzzzz+rYcOGJa5r0KCBjh8/flmVAgAAAAJJmUJzbGxssenm3DZv3qxWrVpdVqUAAACAQFKm\ngYDx8fGaMGGC7Ha7evfurRo1ashms+mTTz7RvHnzNH/+fF/XEwAAAKgwZQrNt956q5555hk9//zz\neuqpp1S1alUVFBQoJiZGs2bN0q233urregIAAAAVpsxTzvXq1Uu9evVSZmamjh8/rrp166pevXqy\nWCy+rB8AAABQ4cocmt3q1q2runXr+qIuAAAAQEDiF0gAAAAAE4RmAAAAwMRld89AxbHb7dqz50e/\nl3PttdcrNDTU7+UAAAAEKkJzJbZnz4/6+9J3FFG3kd/KyM7M0OzRUvv2cX4rAwAAINARmiu5iLqN\nFNWwRUVXAwAA4IpGaEaZ0DUEAABcTQjNKBO6hgAAgKsJoRllRtcQAABwtWDKOQAAAMAEoRkAAAAw\nQWgGAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgG\nAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAA\nTBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCa\nAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAA\nABOEZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAAABOE\nZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCaAQAAABOEZgAA\nAMBEcEVXACgtu92uPXt+9Hs51157vUJDQ/1eDgAACHyEZlQ6e/b8qL8vfUcRdRv5rYzszAzNHi21\nbx/ntzIAAEDlQWhGpRRRt5GiGrao6GoAAICrBH2aAQAAABOEZgAAAMAEoRkAAAAwQWgGAAAATBCa\nAQAAABPMngGUAnNEAwBwdSI0A6XAHNEAAFydCM1AKVXUHNG0cgMAUHEIzUAlQSs3AAAVh9AMVCL8\nEiIAABWD2TMAAAAAE5UqNNvtdtntdq9lBQUFys3NraAaAQAA4GpQqbpnrF+/XtOnT1d4eLgkyeVy\n6dy5cxo2bJgmTJggSVqzZo3Wrl2rtLQ0RUdHa9iwYRo0aJDX62zatEmrVq1SSkqKwsLCNGDAAI0a\nNUrBwZXq7QAAAEA5qVQp0eFwqHfv3po3b16J61evXq3ly5dr0aJFio2NVVpamsaNGyen06nBgwdL\nkpKSkvTkk09q4cKFiouLU0ZGhqZOnaqcnBxNnjy5PHcHqDQqcuYOZg0BAASCShWaT58+rejo6Iuu\nX7FihWbOnKnY2FhJUsuWLZWYmKghQ4bo3nvvVXBwsF599VVNnDhRcXHnZwdo1KiRFi9erG7dumn4\n8OGqU6dOuewLUJlU5MwdzBoCAAgElSo0nzp1SnXr1i1x3cGDB5WVlaWOHTt6LW/durWioqKUnJys\ntm3bavv27Zo/f77XNpGRkWrfvr22b9+uu+++22/1Byqzipy5g1lDAAAVrVKF5szMTFWtWlXx8fFK\nSUlRVFSU+vfvr/vvv19Hjx5Vs2bNSvy7xo0bKz09XVFRUYqMjFRERESxbZo0aaL09HR/7wIAAAAq\noUoVmjMyMnTkyBHNmTNHsbGxOnDggCZPnqzs7Gxdc801CgsLK/HvatWqJZvNpqysrItuExkZKZvN\ndsl1CQqyKCjIIqu1fCYgsVqDFBwcVGwZZVM2ZfuvbAAA3CpVaJ40aZJatWrl6XfcokULJSQkaNSo\nUZo7d67Onj1b4t/l5uYqOjpa4eHhF93GZrMpJibmkusSFRUmi8WiiIhqpd+RMoiIqKbIyLBiyyib\nsinbf2UDAOBWqUJzly5dii1r0aKFsrOz1aRJE2VkZMgwDFksFq9t0tLS1KBBAzVo0EA2m005OTme\naeuKbuMeHHgpsrJyFRRkUXZ2ftl2ppSys/N15kxusWWUTdmU7b+yAQCVmy8bQypNaHY6nVq7dq26\nd++uqKgoz/K9e/cqJiZGzZs3V7Vq1bRjxw6vwYB79uyRw+HQddddJ6vVqnbt2mnDhg0aOHCgZ5sT\nJ04oJSVFXbt2veT6uFyGXC5DTqfLNztowul0qbDQVWwZZVM2ZfuvbAAA3CpNBz6r1aqtW7dq8uTJ\nOnr0qCQpJSVFCQkJio+Pl3S++8bUqVOVnJwswzB06NAhPfHEE4qPj5fVapUkjR8/XnPnzlVSUpKc\nTqcyMzM1bdo0DRo0SDVr1qyw/QMAAEDgqjQtzZI0e/ZsLVmyRMOGDZPNZlP9+vU1cuRI9e/fX5LU\np08fSdL06dOVmZmpRo0aadiwYZ71knTjjTcqMTFRiYmJysjIUJ06ddSvXz+NHDmyQvYJAAAAga9S\nheZq1app4sSJmjhx4kW36dOnjyc8X0yXLl1K7B8NAAAAlKTSdM8AAAAAKgqhGQAAADBBaAYAAABM\nEJoBAAAAE4RmAAAAwAShGQAAADBBaAYAAABMEJoBAAAAE4RmAAAAwESl+kVAAChPdrtde/b86Pdy\nrr32eoWGhvq9HABA2RGaAeAi9uz5UX9f+o4i6jbyWxnZmRmaPVpq3z7Ob2UAAC4foRkAfkNE3UaK\natiioqsBAKhg9GkGAAAATBCaAQAAABN0zwCAAMQgRAAILIRmAAhADEIEgMBCaAaAAFVRgxBp5QaA\n4gjNAAAvtHIDQHGEZgBAMUy1BwDemD0DAAAAMEFoBgAAAEzQPQMAEDAYhAggUBGaAQABg0GIAAIV\noRkAEFAYhAggENGnGQAAADBBaAYAAABMEJoBAAAAE4RmAAAAwAQDAQEAENPdAfhthGYAAFSx090R\n2IHAR2gGAOD/q6jp7pifGgh8hGYAAAIA81MDgY2BgAAAAIAJQjMAAABggu4ZAABcxRiECFwaQjMA\nAFcxBiECl4bQDADAVY5BiIA5+jQDAAAAJmhpBgAAFYL+1KhMCM0AAKBC0J8alQmhGQAAVBj6U6Oy\noE8zAAAVWhTzAAAgAElEQVQAYILQDAAAAJigewYAALjqMAgRpUVoBgAAVx0GIaK0CM0AAOCqxCBE\nlAZ9mgEAAAAThGYAAADABKEZAAAAMEGfZgAAgHLEzB2VE6EZAACgHDFzR+VEaAYAAChnzNxR+dCn\nGQAAADBBaAYAAABM0D0DAADgKsEgxLIjNAMAAFwlGIRYdoRmAACAq0hFDUKs7K3chGYAAAD4XWVv\n5SY0AwAAoFxU5qn2mD0DAAAAMEFoBgAAAEwQmgEAAAAThGYAAADABKEZAAAAMEFoBgAAAEwQmgEA\nAAAThGYAAADABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYAAADABKEZAAAAMEFoBgAAAEwQmgEAAAAT\nhGYAAADABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYAAADABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYA\nAADABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYAAADABKEZAAAAMEFoBgAAAEwQmgEAAAAThGYAAADA\nBKEZAAAAMEFoBgAAAEwQmgEAAAATV21oXrNmjYYOHarOnTurT58+eu+99yq6SgAAAAhQwRVdgYqw\nevVqLV++XIsWLVJsbKzS0tI0btw4OZ1ODR48uKKrBwAAgABzVbY0r1ixQjNnzlRsbKwkqWXLlkpM\nTNQLL7ygwsLCCq4dAAAAAs1VF5oPHjyorKwsdezY0Wt569atFRUVpeTk5AqqGQAAAALVVReajx49\nqmbNmpW4rnHjxkpPTy/nGgEAACDQXXWhOSsrS2FhYSWuq1Wrlmw2WznXCAAAAIHuqhsIGB4errNn\nz5a4Ljc3V9HR0Zf0OkFBFgUFWWS1Bik7M8OXVSwmOzNDVmuQgoO9n3Eom7Ipm7Ipm7Ipm7Ip27xs\nX7AYhmH4/FUD2IEDBzR48GBt375dFovFa93tt9+uF154Qe3ataug2gEAACAQXXXdM5o3b65q1app\nx44dXsv37Nkjh8Oh6667roJqBgAAgEB11YVmSZo0aZKmTp2q5ORkGYahQ4cO6YknnlB8fLysVmtF\nVw8AAAAB5qrrnuH28ccf6x//+IcyMzPVqFEj3X///erfv39FVwsAAAAB6KoNzQAAAMCluiq7ZwAA\nAAClQWgGAAAATBCaAQAAABOEZgAAAMAEoRkAAAAwQWgGAKACFRYWVnQVAFyC4IquAAAAVyuHw6Hp\n06erefPmuv7669WlS5eKrhKAi6CluZII5Om0y7tuhw8fLtfycHUL5HOvtK6kfblSGIahOnXqqGbN\nmqpbty6fERDACM2VgMPhkMVi0cmTJyu6Kh65ubn6/PPP5XK5ZLFYyq3cp556SgkJCRX2dSY3tCtb\n0c93z549klSux7c/OZ1OWSwWHThwQPv27ZPE8VzRDMPQrl27lJOTo7S0NDVr1kwWi0VOp7Oiq3ZF\nK3rcnzt3TpLkcrkqqjpXNX9dgzIzM7V3716fvy6hOYDl5+fr22+/VUhIiFJSUtSjRw99++23FV0t\nHT58WBaLRb/88ou++OKLcit30aJF+uGHHzR37lwFB5/vWWS328utfHfo+OWXXwLqAaY8XA03FMMw\nPAF58eLFGjx4sHbt2lXBtfINp9Mpq9WqtLQ09e3bV88++6ykK+eBwFfcYbW8risWi0U33nijEhIS\nFB8fr1deeUWZmZmyWq0B08/5SnuwKnqez507V8OHD5fT6VRQEHGoPDmdTs9n4Y9j7KuvvtKUKVN8\nfh5xlASwjRs3atSoUXrvvfc0YcIE/e1vf1NcXFyF1ccdnNLS0vTEE09o165dCg8PL5dWkYULF+qL\nL77Qq6++qujoaEnnWwjuuecefffdd34vv2joGD58uN58801lZ2f7vdySFA2w5XFDMwzDc0P53//9\nX73++ut+L7O8Fb2RPvfcc1q9erVuuukmZWVledZXpMt5aHEfu/v27dPDDz+soUOHKioqyoe1uzLY\n7XZZrVYdOHBATz/9tLZu3eq3sgoKCvTxxx8rMzPT0wDw7LPPasGCBRo6dKgKCwsVHBxc4S3OhYWF\nslgsys/PL7cHCX8+oBc9zxMTE7Vu3TqFhIQoJyfHb2VeiquhUeJCW7du1bhx47w+E1+qWbOmmjZt\nquDgYJ9evwnNAcrlcqlPnz569NFHNXPmTN122226//775XK5KuRC6nK5FBQUpOPHj+vTTz/VgQMH\n9MEHH6h58+ayWq1+DRVLlizR2rVrtXz5cs/N3ul06q9//atiY2PVvn17v5Wdn5+v9evXy2q1KjU1\nVWPHjlWrVq20detWpaamSirfC577c5Ck1157Td9//71fyztx4oTngjZt2jT9+OOP+uabb3TixAm/\nllueLgzMn3/+ub744gv17t1bS5cuVUFBQYW2yBYWFiooKEg2m00//vhjqf7WHZh/+uknxcfHa9So\nUZoyZYr+7//+TxkZGX6q8eUrek7l5ub6tSz31/OhoaFKSUnRX//6V+3YsUOffPKJ38rcsmWLPvjg\nA33//fey2+2aOnWq7Ha7UlJS1KFDB0/rp9VqrbBA5Q7uDodDf/jDH/Tmm2/6tbyTJ0/q9OnTfmvx\nvTAwb9q0Se+++66qVKnil6/xL9XlnN+VWa1ateRwOHyeHdznS15enurVqyfJt9+oEZoDkPuron37\n9mn16tUqLCzUxx9/rG3btikoKKjcv0YqGpjnzZsnp9OpSZMmqW/fvlq5cqXsdrvfQsXChQv1yiuv\n6JprrtGZM2c8y4cNG6ZrrrlGL7zwgiT/tQR+++23+tvf/qZFixZp/PjxevDBBzVv3jz17NlTs2bN\n0pkzZ8rt8ygamBcvXqxnn31WkZGRfitv3bp1Wr58uSRp6tSpysrK0ooVK2S32z2DMcujBdbhcGjx\n4sX65Zdf/PL67mN33rx5+uyzz/T2228rJCRErVq1UlhYWIV+besOLoWFherRo4c+/PDDS/7boi3M\nDz30kEaNGqXBgwfL5XIpOjq6wlvPL6bocf7MM8/oxRdf9GtXhYSEBN133306cOCAJkyYoPHjx+vT\nTz/Vtm3b9Nprr/mlzF69eumPf/yj/v3vf+vBBx9UTk6OFi5c6KlPw4YNNXXqVM97Ud6fVdGW7r59\n++rmm2/Wgw8+6Ncyv/jiC/3973/3fG3vS0UD8/z587VhwwatWLFCDRs2VHh4eIWd45dzfvtC0e5I\n5d0dqGXLlsrIyNC2bdt8+rruzzItLc3z7Ygv943QHGDcN7rU1FQ98sgjnptdx44dNWHCBP3nP//x\nWx+gklwYmC0Wi/r166euXbuqW7du+umnn/x2wZk9e7Y2b96spKQkde7cWYsXL9aOHTt03333qUWL\nFpo1a5akXwdK/vzzzzp48KDPyne5XPr973+vxx9/XEuWLNEDDzygQYMGSZJGjBihtm3bek54f38e\nRYPEokWLtHLlSn322Wdq2rSp31qiYmNj9eWXX2rIkCE6ffq0Xn75ZTVt2lTXXnutli5dWq4X2c2b\nN6tKlSp+e/3nn39en332md59913Vrl1bktSmTRsZhqF//etf2r9/v3bu3Kl169Zp/fr1+vLLLz0D\nBf2laHDp06ePOnXqpOnTp1/S3xZtYX744Yc1YcIEDRkyRNL5rgHVq1dXnTp1/Fn9Mil6nL/44ota\ntWqV+vXr5+nC4A9z5syR0+nUXXfdpeHDh6tPnz6e5UlJSUpPT/dpee4b+b333quff/5Zqampmj17\ntiwWiwoKChQaGqpx48apatWqWrJkiaTy7Xte9Ljr3bu3WrZsqcWLF0uS377lNAxDDRo0kCRZrVaf\n7u+FgfnLL7/UO++8o7p160qSsrKyKuQB8nLOb1+Vb7VaVVBQoPvuu0+7d+/2eRkXuzc5HA5Vr15d\nrVq18nljiPuzPHv2rMLDwyVJwcHBPrtPEpoDSNF+s2PHjtWIESPUv39/HTx4UO3bt9dzzz2nKVOm\nlFtwLikw9+/fX3/4wx8kSbfffrsyMjL08ccf+7zsbdu2KTk5WS+//LKqVaumhx9+WC1atNDYsWMV\nERGhmTNnSjr/1WpISIhsNpumTZumDRs2+KR8d2t/amqq3njjDc2aNUv33nuvpPPvS2hoqMLCwvT5\n559L8u9NraTA/P7776tp06Z+G8DidDrVokULNWzYUFFRUXrllVcknb/Qdu/eXefOnVNQUFC53Myz\nsrKUk5Mju93ul2O+sLBQOTk5WrFihWrXri2n0+l5z/Py8rR8+XLNmDFDL7/8slauXKm3335bq1at\n0n/+8x+f16VonYoGl1atWmnRokWSzIOLYRiyWq1KSUlRfHy8HnroIfXt21ezZs3Sc889p2PHjslq\ntXq6JQSKC4/zFStW6OOPP1abNm38Etbcr3nw4EGdPn1aTz/9tOeh2OVyqWnTpjp37pzPB/2GhoZK\nkh5//HHVq1dP3bp106OPPipJqlq1qiSpbt266t69uw4ePOi3b1hKcuFxFxsb6xWYrVarX8q1WCzq\n3LmzMjMz9cMPP/j0PHdfoxYsWKCNGzfqn//8p06cOKG3335bDodDVatW9esDeUku5/z2dfkDBw5U\nRESE/ud//sfn5bjPZ6fTqcOHD3vGAbkfgkNDQ7V//36flmmxWJSVlaWvv/5a3333nd5++21PXXwR\nnPlxkwDiDswPP/yw56tUSbrpppu0b98+DR48WE899ZQmTJig559/Xj169PC60fhaUFCQjh49qhde\neMETmG+55RZJ51tLQkND1alTJ50+fdrnZbdp00avv/665yYiSbt27VKDBg0UGhqq5ORktW7d2nOx\nGz16tKKjo/XQQw/5pHyr1ar9+/dr7NixGj16tPr37y/Ju0X57rvv9txQ/KWkwPzBBx94ArO/bmLu\n123Xrp1nkIz7M7/++uuVnZ2t5ORkv1xoLxQcHKymTZsqIiLC569tGIaCg4M1Y8YMz4Oou49+cHCw\nfve73+nOO+9UXFycqlSp4vk8HA6HQkJCfF4f6fKDi8Vi8VwvJk2apPvuu0+S9Oc//9nzsLly5UpP\n60sgzBpwseP8mmuu8ctx7v6cU1NTNW7cOI0cOVL33HOPV11iYmLUuHFjbdu2zacDsO12uyZPniyb\nzaYVK1ZIkuLj4/Xee+9p0KBBMgxDISEh6tixo5588kkdPHiwXM6z8gjMFzve3EHRarXq1KlTPn8Y\nf/bZZ/Xll19q1apVqlWrlnbu3KnvvvtOp0+fVvfu3dWhQweflvdbKurB5GLlt27d2hPYfXk9sNls\nWrx4sfbu3SuHw6FDhw5p3rx5uvnmmz3Xzvz8fL88vJ87d07h4eFq166ddu7cKafTqfvvv98TnC9n\nHyv+agmPwsJCvfLKK3rggQc8gdnN/TR21113afbs2Ro/frw2btzo1/5u2dnZWrRokfLy8rwCs2EY\nntaSxo0b64cffvAs95XIyEhPYLbb7Ro6dKiaN2+uDz74QLGxsVqyZIm++eYb7du3T8OGDVNERITn\nwuOLp8mCggItXLhQ0dHRnsDs7gbiPuHOnj2rY8eOyeFwXHZ5JamowCz9ehOrW7eup3UgNDTU85Ve\njRo1/D5Ay308/fTTTzp16pQOHTrk8zLcN+eL/ffo0aPKy8vzPJy5Pw/3Rd/X556vbqjHjx/X3Llz\nPV0yDMNQbGysHnvsMR0/ftwzlV4gB2Z/Hufu1qixY8fqj3/8o6ev94V9iIOCgjwzqPjKwYMHFRER\n4QnMTqdTHTp08BqMdvz4cT344IO64YYbyiUwO53Ocglyv/zyi44dO6affvpJH330kWdAscViUWho\nqBo0aODzbl/btm3Tnj17tGrVKs9A8i5duiguLk5Op1Pt2rWTVD4/ZR5ogTk2Ntarhbus1wOXy6Xj\nx4979U+uUaOGbrvtNvXt21fPPPOM5s+fr3bt2ikkJMRzfwkJCdHvfve7UpVlt9v10UcfKTk5+aL3\n3jVr1uj666/XlClT1KFDB/3www+egayX2+Jc8VdMeAQHB2v69OkaNmyYpF9P4ho1angGfLlcLvXu\n3VvPP/+8xowZo3//+99++4rcMAy1b99ef/nLX7wCc9HyQkND/Rqe8vPzNWDAAMXExCghIUGSNHbs\nWLVt21avv/66ZsyYoQYNGuill16S5Lsn5aCgIN1zzz2Kjo7Wc889J0nFWhbtdrtq167tt9lDig76\nK8/AXLTsmJiYElsCCgsLfdqXuqT3z32cffvtt0pPT9cHH3zgl353Zop+23EhX5577uDiPscv9Yaa\nn5+vf/7zn8rIyPD0l7311lvVq1cvSfL6AaKWLVsqKiqqQmcLKKoiHwzz8vLUtWtXpaWlaf/+/V7d\njdzHY+3atdW4ceMyl+EOB0Vv7q1bt/aMx3A/hHbt2lW7d+9Wdna2XC6XqlSpop49e3r6NPt7Bg13\n39Y+ffqodevWfglyx44d08yZMzV48GAlJCRo2bJlOn36tOf4dLlc+vnnn2Wz2XxSnlvnzp09My+5\n76nVq1dXz549dfjwYX366aeS5Nd+81LZz29f8Wdgz8nJ0Z49e7Rs2TJt27bNc7x26tRJ9957r5o1\na6bOnTt7vi20Wq06duyYtm/f7plC9lIdPnxYBw4c0JYtW5Sfn1/ivSM9PV1t27aVJPXp00ft2rXT\nDz/8oLfeekvS5TUWEJorSEFBgXbu3Fls7kt3x3Xp1xuyzWZTjRo1JMnTCtKrVy8lJiaqZcuWfqtj\nzZo11b9/f916662SvAOz++JjGIYaNWrkVd/LVfQkCA4O1oQJEzRv3jxJvw6ieeyxxzRt2jTNmDHD\n80MNvvxqKTQ0VJ07d9bgwYOLTT/l3vfdu3erY8eOfu3b+/TTT+u1117T2rVryy0wS79+lkeOHNHZ\ns2c9N3/3jcXpdPqs711eXl6J75/L5VJ+fr6OHj2qOXPm6Ny5c/r888/13//+1yflShdvKXY6nZ5j\nrWHDhj4r77dYrVbZbDbPV6aXckNzOp06dOiQdu3apQ0bNpS4XdFzIjIyUl27dtU777wjm81WrgOK\nS/p30UF/5f1g2KhRI40YMUJNmjTR5MmTlZmZ6XUcFhQUaMeOHZ5pq0rLHYgPHTqkBQsWlDg9pHvm\nhPDwcM8sRFarVZGRkfrrX/8qybfXNan4Me9yuVRQUKChQ4eqYcOGXi2PvvwMYmJi9Le//U0rVqzQ\nW2+9pTfeeENt2rTxXD+DgoJUtWrVy3pIuZD7OKtSpYqny5V0/j2IiopSfHy8Nm/e7JkN6HL91vlU\nlvPbV/zdwv3NN9/owIEDioqKUuvWrX/zeHXfP48cOaJ27dp5WvovhcPh0GeffeY5JyIiIordO95/\n/30lJSXp9ttvl/Rrjmnfvr02bdp02VMnEporyL/+9S9NmzZNu3btuuhXDO4DOS0tzRNQ3E/lhmHo\nzjvvVIsWLfxaz6IDJIoenO6LT3Jysqerhi+4J9PPy8tTSkqKQkJC1KNHD0nnT+7Q0FDPhbBFixZq\n3bq1JO8f4PCV0NBQxcXFaebMmerZs6dnuXvft27d6hmBfTlcLpfnYnv8+HHP/x85ckSpqalatWqV\n3/p2momOjtbw4cM9renuG2xYWJhPjr1vvvlGY8eO1c6dO4u1aLv71KelpenGG2/U8OHDlZ2drc8/\n/9wn81NfeKwVZbVadfjwYaWnp5fbe+5wODRt2jTFxMRccnBJT0/Xp59+qrZt26pt27aXVNe2bduq\nevXqfvtRgZIEBQXpxIkTWr16teffbvPnz9eLL75Y7g+G0vnuZQMHDtQDDzygWrVqedXXfV42b968\nVK/pftgKDg7Wvn37NHz4cG3dulWbN28ucTBrcHCwqlevrnPnzpXYyurr65r7M1+1apVnQG9eXp4e\neeQRzxSTvvwM3PtrGIZiYmI8142oqCivrjCbN2+WzWbT9ddf75NyJe/3ruixbrFYVFhYqIYNG6pm\nzZo+6Vdb9HzasGGDpzuZ+35VlvPbF9wPCw6HQ3369PFLC3evXr3UsWNH1atXz9OaXNK3I0UfXBIT\nE1WzZs3f/CbvQiEhIRozZozuvvtuzwNnUWfPntXu3bt1//33q169ep7pC2vUqKE+ffrolltu8eSJ\nsiI0V5ChQ4fq7rvv1ksvvaTvvvuuxCdU97IzZ854Zqy4sM+lP11KK1RBQYE6dep0ydv/lqKT6d9x\nxx3asmWL13r3yV3STcRf70eVKlXUpk2bYg8G69evV4MGDTwzapSFe1S+xWKRxWLRunXrNGDAAGVm\nZko63zKzbNkytW7dulwurkUvcu6bd+/evT2fr7s1aNu2bTp06JCqV69e6jKKHiP//e9/lZeXpxo1\naqh+/frFRrDn5+crMTFRnTp1UmRkpOrVq6fRo0crPT1dGzZsUEFBQVl2U5L5sSad70sdFxenJk2a\nlLmcC7kffrds2eIJKG5BQUEaP368Vq5c6dnW7DNv1qyZhg4dquHDh2vmzJl65513POsuvGm53/vc\n3FwFBweX64wBhmFo165d2rRpk9cDyrlz5xQTE6N169ZV2INhixYt1Ldv32Ln+OLFi1WtWjW1adPm\nkl/L5XJp6NChWrx4sbKysjRu3DhNmDBBc+bM0caNG5WamlrizEe//PKL6tatW66/1Pj999975oaO\niopS9+7dPftwuZ+BYRjav3+/V6gxu0YfOnRIv/vd7xQSEuKz7iivvfaakpOTPXUqKjg4WFarVWfP\nnr3sXwQsGpiXLl2qRx99VLNnz5b06/3KarWW+vz2BYvFIpvNpj/84Q9q0aKFTwOz+3r2008/acyY\nMUpKStKrr74qqeS+w+73aN26dYqIiNDjjz8u6dKyg/tY2rt3rwYPHqz58+cXazWuWbOmBg0apJtv\nvlnSr9MXGoahiIgIPfDAA4qJibmMPSY0Vwj3h//oo4+qffv2mjdvnueXgIoePO7BKjt37vR0zyiP\nsLx3714lJyeblrVx40bt2rVL11133WXX7cLJ9K+//nqfzYThD7169dKMGTMkle1hYdOmTXr++ee1\nd+9eWSwWbdiwQXPnztWsWbM8Xwe7v66UVC6BuWgf6jVr1ni+AXEfe9KvUwfdfvvtpe6LVvTG8vTT\nT2v+/PlyOBwaPHiwUlJSdPToUa/t8/PzdeONN3pu5oWFhapXr56mTJmiYcOGlaqFoqhLPdaqVatW\n5q/mL8b9M81PPPGE1/ualZUlq9WqZs2aSfp1doff4n6/ateurSVLlig6Olp/+ctfJJ0fOLxnzx6v\nFjT3e79r1y7PrxyWV/cMi8WiDh06KCIiwivEVKlSRX/+85/VqlUrn4S1y6nfhe68804988wzki79\nHA8KCtLChQu1dOlS3X777RoxYoTuvvtuzywss2bNUnZ2drHyDh8+rJo1a/r0QeZidXYHmS5duujI\nkSMl7sPlOnv2rD777DNNnDjR0xXoYiwWi9LS0rRkyRLddtttCg4O9lnrumEYmjt37kV/1dN93QsP\nDy/zuZCbm+uZs33p0qVKSkrSJ5984vmFSXc9goKCSnV+X6qi9f7oo4+KdTUxDENZWVkaMWKEXnzx\nRUm+C8zuqS1HjBih4cOHa8aMGdqxY4eWLVsmqeTgfOLECW3dulWxsbGqVq2aJPPs4O4PnpKSolGj\nRikhIUFvvfWW3n33XR04cMCzncViUZs2bYoNnvVpY6OBcnHu3DnD5XJ5/l1YWOj5/4SEBOOOO+4w\njh07VmydYRhGenp6+VTy//vkk0+MMWPGGCdPnrzoNufOnTM++OADY/78+ZddnsPhMAzj/H736tXL\nGDt2rGfdhe+FP7g/l4yMDE9din5WF9v+cnz99dfG9OnTjVdeecVYuXKl0blzZ+Prr782DMMwnE7n\nZb9+aRQtb/HixUbr1q2NtLS0i26fmppqHDhwoFRlFH3PFixYYPTu3ds4e/asYRiGsWXLFqN169bG\n7t27i/2d+/Mo6XXKoqzH2uWUm56ebsyePds4e/asceTIEWPs2LHGihUrPOs//fRTY86cOUZmZuYl\nv+Ynn3xiTJkyxVi3bp3x4YcfGtOnTzcOHTpkGIZh5OTkGMuWLTMWL15snD592uvvsrKyjKefftpY\nuXJlmfentIq+d9u3bzduv/12Y+/evf+Pve8MiOr43n6WrqJ0QQV7i4q9gCWKBVERJdaIgiKKDUWw\nx957wxo79m5AoygKFqxAFIMUURRFKdKkLCy7e94P/O5kFxaELZj8X58vsLfMmZl75syZmVMqjb5k\nHfLy8krUSVng+CczM5N69uxJly5dIqKi8SUSiSgpKYmmTp1Knz59KlddlYWwsDAKCQmh169fS13/\n+PEj2drasnlHmbh79y6dO3eOVq9eXYIHiyMnJ4f27NlDmzZtUhp9rg9jYmJo1KhRlJ2dLfO5ffv2\nkbOzs0K0fH19afHixXTkyBEaM2YMffnyhYiIZs6cSVeuXFGo7G9Bklc2bNhA3bt3p69fvxIRUVRU\nlMxvq4w5lSsjKiqKrK2tydfXl4iIcnNz6datW+Tm5kb79u1jz0vOMR8+fKDt27czeVVRWseOHSMi\noi9fvpCHhwfdu3evBA1V4ofSXAkQi8U0duxYWrlypdR1Seb19PQkR0dHlQjziuLDhw+0bt06phiV\nxYz5+fkK0fq3KMx37tyhdu3a0bZt20rcUxXi4+PJ1dWV2rRpQ3/88QcRfV+FeceOHdS2bVt69+6d\nUutSXGG2t7dnC7Lr169T37596eHDhyWeVTa+F6/x+Xz69ddfacmSJTRr1izatGkTFRQUkEgkotzc\nXNq5cydt376dKXTlQVJSEh09epS8vb1p0KBBUpPz8+fPydXVlYKDg0u8JxaL6cOHD5STk6OUtpWF\ne/fuUUhISAklcfPmzXTq1Ckiqhx+53gqODiYJk6cSBkZGUSk3G/OtSM2NpZsbW3p5MmTJegTETk6\nOrK2qxr+/v40c+ZMsrOzoylTptBff/3F7gkEAkpOTqZ+/frRhw8flE770aNH9ODBA9qxYwdTIktD\nTBlrV3UAACAASURBVEwMOTs707lz5ypMh+v3Gzdu0NmzZ+natWsleMre3p5CQkJkvv/gwQN6/Pgx\nEckve7Kzs8nS0pJGjhxJycnJ7Pr169fJxcWFsrOzVcLnkvXdunUrDRo0iMnVgIAA6t69O12+fJmI\nlMvrpSnMHPLy8igwMLCE4ixZh4KCAqXQWr16Nbm6usrVDnnxQ2muJERERFCvXr3Ix8dH6jo3kfP5\nfHJzc6MXL158j+rR58+f2WRCRLRr1y7y8PBQKc1/i8IcFBREAwcOpPPnz5ONjQ0T3qqqA1fu3bt3\nqUOHDuTk5ETXr19nilRlQZbCHB8fL1VHZWLHjh1SCvOtW7fIxsaGTVrKbHvxsr4Xr3FlFxYW0saN\nG8ne3p7Gjh3Ldt98fHxowoQJrE/KM3FL7r5v3bqVunbtSo6OjpSRkUFv376lPn36sN2Y74nTp0/T\nqFGjaMKECbRs2TI2UR4+fJhGjRpVKXWQXBTb2dnRsGHDpGgLBAKl0UpOTqbu3bvTxYsXiajoO3H0\nOX6cOXNmiYlfVUhISKDz58/T169fZSopeXl51Lt3b4qKilKYVl5ensxFWvGTIg6SfP7x40cKCAiQ\ni+7t27fJw8ODBg4cSGvXrqVHjx6xe1ybhw8fTnfu3Cm1jPIqcLJQWFhIIpGIXF1d6dq1a+y6SCSi\nBw8e0MSJE4nP58tdfmkorjDb2dkxGXLjxg2ysbGhiRMnkouLi9JpExH9/fff1L17dylelpS5eXl5\nFBAQQO7u7qXuOH8LXBtfvXpF3bp1k6LF8dWLFy/IxcWlUvQFDj+U5kqA5GqpR48etGvXLpnP/PLL\nL3T69OnKrh4lJSWRs7MzzZs3j5YtW0ZERUzp5eVFiYmJKqHJ9cn3Upg53Llzh2xtbdlOxN27d2nc\nuHF09+5d9syNGzcUEqwcxGIxEwQBAQFkZWVF4eHh9PjxYxo+fDi9fPmSPadqVLbCvHHjRhowYADb\ndQoODqbOnTuzHdLSJteKQCwW05s3bygpKUmqDd+T1yTLnzdvHq1fv57Wr19P/fr1ox07dpCNjQ0z\nyyhvH0jykKOjI7179462bdtGbm5uZG9vT0uXLpVJ/3vgy5cv9Pr1a1qwYAE9f/6cXXNycir1yFxZ\nkFwU29rasp1WDw8PWrZsmVTfJCUlKUwvISGBRo8eTYsXL2bXuHHG1WXx4sVMuaqMcc7RyMrKorS0\nNLp+/Trrd7FYTEOGDFGK+d+1a9eoWbNmdPXqVSIqqRyFhITQ5cuXacWKFeWqb3khEAjo4cOHMk9p\nuDr88ssv9Oeff1ao3Ipi69atdPLkSXr48CF5eXnRqFGjaM6cOWRpacnkqiqwadMmqR3mGzdu0M8/\n/0yhoaFERDR+/HilLIokkZaWRh07dpRShkv7bkFBQWRjY8MWkhVFTEwMNWvWTGoTQJJWUlIS2dvb\nU1JSUqWd0v9wBKwEqKurQyQSoXnz5vj9999x+vRpFtwe+MegvlmzZhV2rlIUnHPVtm3bMGHCBKSm\npiI5ORkaGhpISUlRWRIEdXV15OXlwcHBodKDvHMIDQ3FypUrsWLFCnTt2hVisRjt27dHnz59EB4e\njk+fPmHixInw9/dXSlg9LkrGjRs3sHLlSmzcuBHt2rVDly5dYGVlhXXr1rFYrapEZSeUePHiBSIi\nIuDr6wsjIyPcvHkTK1asgKmpKR4/fgygyJOdFHRKy87OxsOHD7FmzRqEhYUxB5TvyWtc+bNmzcLX\nr18xf/58zJ8/Hx06dMDx48fRp08fVs/y9gGPx8OjR4+wevVqeHt7o169evD09GSOZF++fEFoaKgU\n/coCn8/H06dPcfXqVWRnZ8PIyAiNGzfG2rVrWTxWTU1NfP78mUWJURV4PB6Cg4OxZs0arFy5kjkH\nTZs2DQUFBbh16xYAYPTo0bh48WK5yy3tG1lYWGDLli1ISEjAhAkTAPzjVMfj8ZCRkYHw8HBUq1aN\nXVM1eDwefH194eHhgVmzZuH27dss5Nf169eRn5+vlLCZtra22LRpE7Zu3YqgoCAWYvC3337DtGnT\n4OXlhcuXL0NXV7fMzHsV7RNNTU1YW1ujSpUqSExMRFxcHHbt2oV3796xvldTU5Mr0k9FIBaL8erV\nK4jFYnTv3h1OTk7w8vKCmZmZyvj8/PnzuHDhAo4ePQpjY2MEBARg3bp1WL9+PTp06IC8vDykp6cj\nNjZWqXR1dXXh6+sLd3d3ACUTnkl+33379sHCwgLVq1eXK6xfWloatm/fzhK+SdISCoUQCARQU1OD\ntrZ2pYXPVG0KnB9gkFSc9+7diz///FPqXlpaGl6+fMmyeFUGcnNzcffuXSQkJKBRo0bo168fy6wH\ngMVAVgUEAgFGjhwJU1NTlSkxxQdzcZiammLTpk3o2LEjUyR1dXXRs2dPHD16FC4uLujUqRPWrl2r\ntDq9evUKnp6e2L9/P3r06IHCwkJoampi8ODB+Pvvv5UazYBrf/F+qOyEEm3atMGBAwego6ODW7du\nYf369dixYwcsLS1hZ2eHHTt2YNasWQoLveDgYGRmZrLUrFw7K4PXysLRo0eRk5ODAwcOAAA+fvwI\nc3Nz2NnZMe/+vn37YuDAgeXqg9zcXISHh2P69Ono1q0bhEIhXr16BRMTE3Tp0gUFBQWYPn06Fi5c\niL59+0pF6VA1NDQ0EB8fj7t372LHjh0YOnQo7OzsWGzewsJCFklAmZNcaWM9OjoaS5YsQZcuXdgY\nr1u3Ljp37owXL17g6NGjsLCwwLRp0ypMJzIyEk2aNJFaUNeuXRvLli3DjRs32NjmIBKJULt27QqF\nsFMUAoEAOTk5cHFxQYsWLWBmZsbupaSkwMrKCtra2gonUNHQ0MDgwYNBRFi6dCnq1KkDfX19iEQi\nDBo0CIsXL4apqanKxtzx48dx8uRJNG/eHNra2jA2NoZYLMaLFy+UHvtZFszMzMDn89GtWzep6w0a\nNACfz1cJzU6dOuHmzZuoUaMGU5jXrVsHa2trFBYWomrVqmjRogWj/635sLzQ0tJi2faKl8lFuQCA\nsWPHwsjISEqnqCisra3Z/8VpaWhooKCgAHl5eaXmulAJKmU/+/9DFD8q4I6Kih+Xcr8fPXpEHh4e\n3/Q0lgfFj8ok6/bq1Su6fPkyDR48mC5evEhZWVnsnru7u5RDi7IRERHB/lfFMfLLly+ZyUNxyLKt\nkjweHzp0KM2bN6/M5+VFTExMiTLT0tLIxsaG3VMUXH++ePGCDh48WOL+ypUrqXXr1szpT1XH+JK8\n5ufnR/369ZOyOwwNDaWpU6dSSkqKUo7XwsLCWGQKyfJUzWtlITw8XOqI9vr167R06VJ69+4dJSUl\nkb+/P3Xp0oX2799f7jKTkpKYlzwR0fLly2n79u2szbdv36ZffvmFTp06pRTTorLA0Sxuv3vx4kU6\ncOAAPX/+XOpb5OXl0eDBg5Vi+hUfH18uvuGe4WyYv379SlZWVjR//nz2zLfGePFIBc2aNaNDhw7J\nfE9WnZYsWUITJ078Zl3lQWnzDZFsu+03b95Q79696fbt20qvi7+/P/Xo0YM2bNggdZ0bd6o4Rg8O\nDqZnz56VGNtXrlyhiRMnUk5OjkqP7w8fPsz8lSTN8Nzc3MqMRKQM+Pn5kY2NDXOm5qK1EBEtWLCA\nTpw4weqlSkj2/dixY2nKlCnst7J9dbjywsLCyN3dXallfws/lGYlQygUStmxPXz4sIRdmywsWLCA\nlixZovT6cLQ/ffpEt27dkqqnJJKTk5ltG1fPOXPmKM0e6+PHj6WGmVKF81tGRgbZ29uzsE/fgmR/\nTJ06lebOnav0+kmWU5wXsrOzydbWlt6+fauwcOPaEhcXR126dKFmzZrRmzdv2P3CwkJas2YNs3Wr\nDCUyLS2NbG1tmUMO1xefP3+mQYMGVTiEnSS4sv7++28aNGgQubm5UXp6epnPqgqS5cuyq46Li6Nh\nw4aVsLGMjY2lLVu2SEW1SEpKKldEjQULFtDYsWPZoo/7GxMTo5JwYpKQxTuSSlpOTk4J+ff48WNy\ndHRUmO8SExNp/PjxFB4eLvN+8XEkSW/mzJkVGuOSZW3cuJEGDRpEN2/epP79+9ORI0fK9f69e/dY\nmEVlKjDc9w4LC5OaQ0qjIRKJ6MyZM1KRgpQJsVhM165dIxsbGyk+V7TN2dnZtGTJEnr27FmpzxQP\nbebo6CjloCcPZIWKLd6W6OjoEiEz37x5Q1ZWVhQbG6sQ/bIQGRlJtra2dP/+fSL6p/0ikYiys7Np\n0KBBcjtZVgTKVpi58r717vz581UesKA4fphnKAn5+fnQ0dGROn7y9PREQkICxowZg+HDh5d5NDJk\nyBCWxYaUdIzCHbnFxMRg4sSJ+Omnn5Cbm4shQ4ZAXV2d3SciKbs2Ho+H0NBQPH36FLNnz1aoDlxb\nbt26hV27duHEiRMljieVnSZWJBLh8OHD6NatGxwdHdk1dXV15OfnQ01NTepIlSQCzXt4eEBXVxcb\nN24EALmOLSMiItC6desS7xdP6Sr5ncPCwlClShUW/F5ecO2MjY3F5MmTMX36dLx7967EsdbChQvB\n4/FUaqaQnp4OHo8HAwMDGBoa4ty5c9DT05PiO0NDQ2hqaiI3N7fC5efl5SEwMBAODg6Ijo7G3Llz\n0bVrV6SkpCA9PR0GBgYlvp+yea04uPK5RB1c/3J21d7e3ujfvz8GDBgAoIj3iAhNmjSBp6cne//9\n+/fw9fVF165d0bVrV5YEgENERATMzMyY/eC+fftYwhbueLRp06YqbatkMhIfHx/weDxMnz4dmpqa\njLc5+13gH3vVFy9eQF9fX6bpUHkhFAqxZcsWNG3aFO3atWP1UVNTY8lrih8bc3WdNm1ahca4ZB03\nbdqEgIAAnD59GiYmJtDV1cXixYsBAM7OzjLL4d7v0aNHib5QBEKhEEKhEDo6Onj9+jUWL16MxMRE\nNG/eHGPGjCmVRmpqKi5fvswS4SgbPB4PAwcOhFAoxKZNmyAWizFo0CCFvjdQZEsbExPD0jTLgmT/\nR0ZGolOnTgqlTZas7+bNm0FEmDt3bok2SJoycvyUnJwMKysrNGnSRGUp6w0MDHDgwAHUrVtXSq5y\n/VCjRg1mGlVRlDaPFYekHPjll19Qu3ZtlkRFnvmTG798Ph+7du2Cs7OzzCRTWVlZyMvLw9ixYwEo\nT2/6Fn44AioJa9euxeDBg9nvOXPmICcnB2PGjEFcXBwePXok8z36nw2rKhXmSZMmwcXFBQMGDEBY\nWBiuXLkCAGyAyaJXrVo1LFy4ELVr164QXa49QNFExePxEBgYiHv37sHKyqpSMpBFR0cjMTGRTVL5\n+flQV1dHbm4uZs+eLZVBCPhnAhsxYgS0tLQUUpiJCIcOHcKsWbMAlMyIFB0dzVLXSvZ7jRo1YGVl\nhby8PLn7SFJhdnd3x6RJkzBu3Dikpqbir7/+knqWo61Ku95Lly5h/Pjx7Leenh4Aaeeo7OxsFBQU\nyJUJLTIyEjt37sTt27fh6ekJV1dXLF68GFWqVMGmTZukaFUmrl+/jgkTJpTI+lW1alUsX74cU6dO\nBfDPWJe1qKpXrx7MzMxw7tw5PHv2rIQTze3bt7F8+XLUrl0bCxcuRLVq1SrVTvvLly+svnPnzoW/\nvz9iYmIQFBRU5nu5ubl48+YN7OzsFLJrDgkJgY6ODmbMmAEAbDH89etXnDp1qkRaZK5fxo4dCz09\nPYUU5nPnzsHExAQCgQDW1tZYv349jh8/Dl9fX5npn1UxkQsEAmzZsgW5ubl49+4dZsyYAWdnZ2zY\nsIFlhCtNjgQHB6Nq1aoYOnSowvUoTkPyt4ODAzw9PbFlyxbmw6NIX+Tl5SEzM7NcKbYzMjLg4+OD\nWrVqyZ1lUfLbb9++HSdPnsTt27fx/v37Mt/j+OnChQsszbSqlLlatWqhbt26UnQ5Whs3boSGhoZc\nSnNF5jFOjzhw4AAMDQ2VojBzC62kpKRSs7Ly+XxkZWXB3NwcQOU41gL4YdOsLGRmZtKsWbPIy8uL\nvL29pexstmzZQmvWrJE6IlcluCON6Oho6t69Ox0/fpyIio63Dh48SEuWLGFBz4lKPzaTN3FJRkYG\nO6J99uwZ2dnZUVRUFO3bt49lEFS2fVXx49MBAwbQ1q1b2fF0YWEhOTk5kaenp8z3CwoKmO0XkXxH\nStzRukAgIFtbWyla3HHT27dvafr06SWOpnNycqRsVCsKrrzo6Gj6+eef6ezZs+yeq6ur3CF/FEFS\nUhJ5eHiUGafUx8eHRo8eLTeNGTNmUNeuXaWSe7x69YqmTJmi1Bi8FcWSJUuYOZRYLC43P0VFRZGf\nnx/7vX//fnJ3d6eQkBAp2+S///6bvLy8lFvpcuLWrVssfOD8+fPJ3d2d+Hw+bd26ldasWfPN90Ui\nkVx21twYLygooGXLltGwYcMoKCiI3RcKhTR06FApO2VJhIeH06xZs6TqUV5wYQI5n5Pix8dPnjyh\n3r1705EjRyrF3EkoFNL48eNp6tSp5ODgwMZ7REQEdejQocx4/5J9r4i5EmcWkpuby+xpZcHf359a\ntWqlcNg3gUBATk5OlJaW9s35IyIiQmoOruh8U3w+sbW1ZXKFiytfFgoKCujx48dMpld20rKcnBw6\ncOAAM2WpCH155zHJJEby8FXxWPqSZhel1V8VMbC/hR9KsxLAfeysrCzq1asX2dnZSd3Pysqi+fPn\n0/r160s4zSgbxRVmThHkrmdnZ9OhQ4fKrTjLgxMnTpC3tzddu3aNZs6cyYLeHzp0SEoxVQX27t1L\n06ZNo2vXrtHatWvp8OHD9OnTJxo7dqzM+KmyIM+AT0hIoFOnTrHJihM4M2fOZM8IhUJKS0tjiwhl\ngatvTEwM9erViy5cuEB5eXnMqdDDw4OePn2qNHqyIIt/vn79Sv369SszsUBUVFQJW/qKYN26dUy4\ncu9nZGRQjx49yrR9VAU4ZaSwsJDOnj1Le/bsqdD7YrGYXr16RU5OTrRz5052fffu3eTm5kaPHj1i\nsub9+/fUt29fSk1N/S6xmBcuXEgtW7YkNzc3du3jx4/Uo0cPKbmiLEjyxv79+8nV1ZU2b95Ma9as\nYfGfnZycymXTS1SxMb5582bq1q1bCYWZg6Qi0blzZzpy5IhKnS+5doWEhFC7du0oMDBQ6vqCBQuY\nHa+qbPg5PhQIBNSrVy/avn17qc8KhUI6d+6cwptGr1+/ppEjR7LfpbWtLKfI8qC4wtynTx/27Zcv\nX04LFiyQSac0+opAke+Xk5NT4Y0vZcxj8rT/eyc6qwh+mGcoCLFYzGwIV65cCT09PXTo0AGBgYEQ\niUQQiUSoUaMG5s2bh0ePHrGjC1UcJUiaZLi5uWHKlClwcnJi9IgIurq6GDlyJOrWrYvnz58zUw1l\n1sfJyQkWFhY4ceIEcnJyYGBgAAAwNzeXCnmkbOzZswc3b97Ehg0bMHDgQPTs2RPx8fEYM2YMzM3N\nWWxskUhU5rGRPEf6hYWFSEhIgJ+fH2JiYqCpqQl/f39ERkbC09MTQNERsYGBAUxMTJRqpqKmpoaX\nL19iypQpmDRpEoYNG4aQkBB4eHggMDAQDRo0QJ06dZRGTxaK849YLEb16tXx008/4evXr6W+17x5\nc1hYWMgsoyxwR4UtWrRgMViJCEKhEPr6+mjevLnKQj3JwokTJ7Bv3z6Eh4dDQ0MDffv2xfXr1/Hs\n2bNyl8Hj8dC0aVO4u7vj5cuXOH78OIAiG1wubB9nZlO1alXo6+ujWrVqlWaCwh01c3W1trZmYfQK\nCgpQp04dTJkyBXFxcQBKNw+QBxxv7Nq1C7dv38a+ffswYcIE6Ovrw8/PD/b29mjYsCFWrlzJ6loW\nP1Wkz5o3b47z58/D0NAQQqGwVBMYgUCAr1+/IioqCl++fKlA6yoGrl01a9aEgYEBOnbsCOCf/q5W\nrRpu374t9awywR2hi0QiODg44KeffmLH+LKgrq6OESNGoGHDhgrRTUhIQGxsLM6ePQugpMkAh+Jt\nruj44N5fv349rl+/jnPnzsHQ0BBEhNatWyMvLw9AkblIXl4eUlJSkJKSguTkZJn0KwrOlperu0gk\nktlOzp+htHFWrVq1CpumKGMeq2j7Jflp4MCB3y1vQ3nxQ2lWENyAnDFjBnJycnDu3DlYWlri8ePH\nzAFIIBDA0NAQCxYsQGRkJHJyclRWl/j4eDg7O2PhwoVMYab/2WZJKs5ubm6oX78+/Pz8cOPGDaXV\ngRvI9vb2MDU1RZ06dbBu3TqEhobC1taWOWWUxy6tIkhMTMSbN29w8OBBFpe2a9euCA8PZ0IbKJrY\nVDEIGzZsiD59+kAkEiEoKAgJCQnQ0tLCn3/+ib///hteXl4A/rHj5QSvMpCYmIg5c+bA2dkZY8aM\nAQD06dMHTk5OOHv2LAYMGIDatWtLKT3KQnp6OqKjo/HgwQP4+voiOjoawD/jQltbGxkZGQCUq0Rx\n5RsbGyM6OhqFhYVSC1gAKlHeSoOZmRl0dHTg5eWFBw8ewNDQEF27di1hW/stqKuro2PHjvjll18Q\nFhaGy5cvAyiSL23atMGePXvw/PlzhISEwNjYGFWqVKk0Wz5u3MyZMwfJyclMYRYKhWxyNjAwQGBg\nIPh8vtLrFRQUhEePHmHv3r3Q1NSEoaEh7OzsEBQUBB0dHSxYsIDVR5ljfNCgQahVq1YJ/gL+cYJ6\n+PAhxo0bhz179mDDhg0V9gWpKIgIdevWhYWFRQnlqVOnTiqzpS2u4DRu3Bh79uwBAJXIF+CfuSIm\nJgbNmjVDcHAwTpw4AaB0xVlRhIWFITIyEseOHYOhoSEKCwvB4/HQtWtXBAQEYP78+XBwcMC4cePg\n5uaGYcOGwdnZGWFhYQrTTklJwa5du7B8+XIAReOOk3fZ2dn4448/4OPjg9GjRzNna2Whsuex/5rC\nDPxIbqIwiAgXLlxAeno6Tp06BQDo2bMn9uzZg06dOqF///7Q0tJCTk4ONm7ciCZNmqg02UB0dDSy\nsrKYR7lAIJCKFCHp6RoYGIjs7GxkZ2eDz+eX8NCXBxoaGsjPz8fcuXPh4OCA8ePHw8/PD97e3pg1\naxY6deoECwuLMp0Q5QGnnHNtLSwsxIQJE9C+fXvUq1cPW7ZswZEjR5SS2a80dOzYEXw+H3/++Sfu\n37+PAQMGwNDQEH5+fnB0dGR9YGJiglatWimNrqamJjZv3swC+HP9am9vj4yMDAQHB6NRo0ZK35FM\nTEzEnj178PjxYzZ5161bl9Hi8Xj48OEDWrZsCUA1u15aWlqoUaMGSyLBnbaoqamxEw5VKpXx8fH4\n8OEDrK2t0bdvX9jb2zOFSUdHB/fv30fv3r0rxOtVqlSBtbU1MjIy8PTpUzRu3BiWlpaYOXMmtm/f\nDh8fH+jq6qJJkyYAKs9rHABWr16NuLg4dkLFTXocmjZtCm1tbZUoUN26dUPHjh1RvXp1AEWT6rJl\ny9CsWTOIxWLcvHkTQ4cOVdlEW3z8cLz26NEjeHp6Yvny5bCxsSk1qZAywePxoKGhga9fvyIxMRFG\nRkas3fn5+fj8+TMA5fLG91JwuH5/9OgRunbtivr16+Pq1avg8XhwcnJiirMy5Vvr1q2xY8cOGBoa\nQiwWM/kiEolgbGyMoUOHYvjw4bCwsICuri6Sk5MhEomUErGmXr16CAoKwrBhw6CtrQ0vLy+8e/eO\nOa/GxMSgT58+6NOnD5NxyoSq5rHivMgtQv9LCjPwQ2lWGDweD3369GE7mfn5+TAzM8PgwYNZ+kw+\nn49Lly6hdevWbPWoKoE6YMAAJCcno1+/fjh+/DjatWvHGFCSESdMmABTU1OcOHGixMQnDyQjIOjo\n6GDy5Mmws7MDUORFbWJiggsXLuD169ewtLQsd/azioATbEKhEBMmTED9+vXZce39+/fh5+eH4cOH\nK5UmB+579ujRAzk5OTh16hRatGgBQ0NDVK1aFRcvXsSvv/6KUaNGoXPnzgq1vfgEUbNmTRYyUJKv\nDA0N0aRJE5w/fx5TpkxRrIEyUKdOHXh7eyM/Px+1a9eWyUdqamoqNQ15/fq1VLhEsVgMHo+HzMxM\n6Ovrq4wuUNTXGRkZuHfvHnbv3o1JkyaxxSpQtOvKRb2o6PfW09ND9+7dERYWhr/++ostiDw9PbF1\n61b4+fmxLHaV5jWOolTRZ8+exdu3b9GwYcMSigq3AyyZCU8ZEIlE0NLSYoteIoKzszMaNGiA1atX\n4/79+1i2bBmsrKwUNgErj2yWVJhnzZqF5cuXY+DAgVLvqvq7CIVCFBQUlIisIhQKWT9JbpIoSut7\nKDhcf7569Qo1atTA5MmTmRkWd0KqbMWZiBgfA9KLJW1tbZiZmcHS0lJq86tatWrseys6t4vFYtSq\nVQsXLlzAyJEj4efnh549e6JmzZoYNmwYGjVqpBJlGVDdPJaXl4erV6/CyspKKtpHVlYWRo4ciWbN\nmmHnzp0A/t0KM4Af0TPKC7FY/E3nDkmD9d27d0sF+JbMtKcq5wxJA/wjR45Qy5YtmUG/pEPAhAkT\nyuWZWl4EBAQw72nJrHpE0okO3r17R6dPnyYfHx+pJA7KREZGBtnY2Eg5/REVOYxV1DGropDsx+3b\nt5ONjQ1lZ2eza6mpqeTs7ExPnjyRmwbHY0lJSVJJHcr6hr/++qtCNGWhPDz87NkzGjx4sFQfKILM\nzExasmQJRUZGsmt8Pp8lzZGsk6OjI3MQUyZK6+eAgAC6desW5efns2fWr18vFcVEHty/f5+6detW\nIlPkhw8fFCpXERw8eJCaNWsmFaGBa/OBAwfI1dVVKXSEQqFM3klNTaUhQ4ZIOf0VFBTQtGnTmFOp\nMlEar9+/f5+srKyY051kJrjKwKdPn2jXrl1sbuFk75EjR0pk4ysPCgoKyMfHhx48eEBfvnxh1zmZ\n8z2dtDZt2kQuLi6Um5tLREWy4NKlSzRlypQKZdJUFNnZ2eTi4lJpSZKSkpLI1ta2RNY7ZWRXXB6b\nAQAAIABJREFU/Pz5s8wIQ6qYxyIjI8nGxkaKr4iKoidNnTqV/f63Of3Jwg+b5nJALBbjwoULCAkJ\nkelcJBKJkJOTA3V1dWZfVqtWLandFi4gO0kEHlcE9D/7NUl7Lu5IEADGjx+POXPmYMyYMQgPD2e7\nwK6urtDV1WWrOm5nThEkJCRgzZo1EAgEJXYaJfugXr16cHBwgJubm1TSA3lAEnaqkjst+vr6mDhx\nInP6EwgEAABTU1Ol2hHLqgePx0NhYSEAYNasWWjdujVu3boFoMhcxNjYGIcOHULnzp3loiUZh3ns\n2LHYuXMn7t69y2iTDNtdsVjM4lkqitzcXLx+/fqbjpRcPeLi4lC7dm2WSEdR6OnpIScnB3/88QcA\nsMQOP/30E4B/doT8/PygqamJNm3aKERPsj8fPHiA3NzcEgkzuGdsbW3Ru3dvaGtrs2f+/vtvtlsl\nD8RiMbp3746ePXvizZs3AP7xGeBik34PTJw4EQsXLizB+0BR4gwuProsfiwvCgoKsHjxYmbTLYmo\nqCg0b96cnSJxO6tfvnwpEYNdXhw/fpzJyOK8TkSIj4+Hm5sbFi1axHaYAdXtLssaP7Vq1YKTkxOb\nWzjZGxgYKJd8FQqFyMvLQ3R0NEs2xO1U5+bmwsHB4bscoT9//hyBgYGYPXs2qlatCrFYDD09PfTu\n3RtWVlZ49uwZMjMzVUK7OA9HR0cjOTmZjUNVgds5NzU1xbFjx/D8+XN2Si0Jefntw4cPOHbsGBIS\nEgCU1CO438qax0xMTKCnp1fiBGrGjBlSNvH/6h3m/+GH0lwOqKmpIT8/H2fOnMHTp09LHIc9ePAA\no0ePRkFBARNcqampMo8JlZW4hMfjIS0tDXfu3GHOV1z5xRVnFxcXREZGYsaMGSUUZkUUeEk6BgYG\nLKh+WahatSp0dHTkpgkUKcJcP65evRq7du2ScrjiHCC5I10ACA0NVbqdpeSCIywsjNm+cQKnZs2a\nePr0KYB/Fg/ymsFwAoWLjDJ48GAMHDgQfn5+pSrO3ALN2NiYRahQBEePHsXq1au/yTM8Hg9v377F\n/v37YW9vjypVqii8UOT6tE+fPsyxsLS+NDExQceOHUv1Oi8PSOKIdd26ddi/fz/7nZSUBKDIQUdy\nPEu2MTY2FrVr15Yy16goJLMLPn78GID8/KNsuLi4lFiURERE4OrVq2jfvj0AxWSdtrY2xGKxTBna\no0cPrF+/HgCkMiDy+XylmYX07t0bwcHBMpNS8Xg8NGjQAFeuXMHgwYNVqjBnZ2cjNzcXampqCA0N\nZREaOBQ3QXr//j3U1dUrbIbG5/OZA2dmZiYsLCwgEAhYhsVhw4ahZs2aKleYiyupnMzmfGEkN530\n9PQwePBgbNq0SWmmWBy9goICmWYWaWlpMDU1ZQk4VAlOcTYzM8Ply5dx8+ZNLFu2DAAU3oiwsLDA\nq1evcPjwYUZLFm1AOfMYj8eDqampVDZHyfpTsURQ/2b8UJrLgEgkwosXLwAA48aNQ4cOHXD69GmE\nhoayHUygyPGvQYMGUqvdpKQkpdv1cVBTU2MhYAIDA5GYmCh1v7ji7O3tjWHDhiEzM1NuhVkgEODy\n5cv4/fff8fvvvzM6QNEAysrKklLelQ2BQIApU6bg8+fPTBGeM2cOHjx4gLy8PNy4cQP5+flS73CD\nMD09HVWqVGGTuTIg2X9bt27F2rVr2W4u1y+9evXCp0+fFKZVXGF2d3fHzJkzYW1tjRYtWpSqOPN4\nPDx69AhRUVEK7XhyaNasGRo2bFjqrjYHPp+PoKAg2NnZoX///hWmI1k2J1i5Pm3VqhVevHhRQnmQ\nhKWlJaZOnSrldV5R+pKZwO7du4etW7eiatWquH37NpycnBASElJmGQ0aNMDMmTMV6neuHywsLFQ+\nQSsDRkZGOHToEEu9Ky+4tnLObGWBG+MvX75ElSpVFKIt2cd16tTB2LFjkZaWVuIe979k6mRVKMyc\nL4y/vz9u3boFT09PfPz4scx3zMzM0K1btwrNPUSEvXv34uLFi1i2bBk8PDywaNEiXLhwAUCRfN+3\nbx+OHDkCQLU7glw/cjug6urqaNu2LWbNmgVDQ8MS/WxoaKg0hZmLulJQUIBp06bh3r17Je4/fvwY\nXbt2Zc7GykJaWhq2b9+O9PR0qeuc8lqrVi1cvHgRN2/eZCcs8tLn+NfT0xM5OTlsgVAcXF/b2Ngo\nPI+FhYUx/YhbmEjWvzL9MhTFD6W5DCQlJcHX1xfbtm0DAEyePBlt2rTBsWPHEBYWxo7iiQiJiYmI\niIhg7zo6OmLu3LlKr1NcXBxOnz6NadOmwdraGm5ubjLDuBVXnNevX8+OdL91vF4coaGhWLZsGXx9\nfaGuro4WLVqwe9zioUGDBio9stLS0kKVKlUwe/Zs5ObmYtGiRcjNzcWNGzfQoUMHREREIDw8XOZu\nsq6uLuzt7RU+rucgqTD7+PjA19cXGzZsKBGtoaCgAO/fv1coxGBxhVky9ra5uTns7OzQsmVLmYqz\nQCBAVlYWJk6cKOUsV1FwfJSWlsZiIpcl5FJSUnD16lWYm5vLtXDk8XgQCAQgIjZ58ng8xrff4jNd\nXV25I9RIKszbtm1DQEAAjh8/DhMTE9y4cQPLli1DrVq1mEJXmjKrqamJOnXqKDQZcO/+/PPPGDRo\nkNzlyAPJPi5vvOs6deqgefPmCtPmxpaGhka5FSIDAwPY2NgoJIP8/Pywe/duCAQCiMVimJubY//+\n/UhJSZGSl8XTFatqwtfW1ka7du3w4sULrF69Gps2bUKHDh3KPDHT1tbGpEmTKrxY69+/P4yNjbFy\n5UrMmzcP79+/Z+EriQj169cHoDzHwrKQn5/PYp5zMDY2VilNyfTNgwcPhqamJnr27Cn1jFgsRn5+\nPnNkUyaMjIwQHByMa9eulbgnqThfvnwZp0+fZuaH8oDjXwMDA4SHhyM8PFwmD3PX8vPzFZ7HUlNT\n2Qm9pBnrfxIqtJf+z0MoFNLDhw/JxcWFjhw5wq77+PiQq6srPX36lKVxnD17tszUpcp0DPH396ff\nfvuNFi1axFL0cnjw4IHMDGiS9OV1vhMIBBQaGirTEZJzWHB1dVVptj9J5yorKyspZ6PCwkLy8fGh\nRYsWUXx8vFS9itdTUUiWs2PHDmrbti2jWdyJIT8/n96/fy83LcnU2JLZHYvT+vjxIx04cIC8vb1Z\n9kUOfD5f7nToxbFq1Spau3YtEX27P0NCQuSi8fDhQ9q+fTs5ODiQvb09ubi4SGUSS0tLIxsbG4X6\ntTzYvn072dnZUWpqKhER3bhxg3r27EnPnz+nhw8fko2NDWVmZqq0Dt8Lkimily5dSpcvX1Zphrvi\nEIvFlJOTQ87OzpSUlEREJR2MZb1TET4vzr+5ubnk5+dH06ZNozFjxtBff/1FREXp0MPCwirYAsXB\n1e/+/ftkY2ND7dq1o3PnzlFGRgYRKXde4b53amoq9erVi3r27MnuKfu7FxQUlJniWyQSUVZWFg0Z\nMqTS+r2s9M3F+eT169dKp8/1/9GjR8nHx6fU57i6xMXF0du3b5VCe+fOnbRv3z7KyMhgwQ6KO+sp\nMo9xfevh4UFt27alX3/9lfHut8b0vxU/dprLgLq6Otq3b4+xY8ciLCwM58+fB1BkvN62bVvs3bsX\nMTExSE1NRWxsLNt5loSydiGSk5Px5s0bWFpawsXFBX379gVQZHqwa9curFy5EsHBwfj69atMBx0A\nFXYO4crR1NREhw4doKWlhTdv3uDFixdYtGgRIiMj2aqVz+ez+KnKhlAoZO34/PkzdHR0WHxILtbj\njBkzoKamhq1btwKQbaOlKCR3mHfu3IkjR47g8uXLqF+/vswjS21tbYV2JdTV1fHmzRtMmjQJ06dP\nl0pWI0mrTp06GDFiBFq1aoWTJ0/iyZMn7J6Ojk6Fs0IVB8cHAoGAxSDm4myXhq5duwL4dhKb/Px8\nbN++HXfu3EF6ejpq1aqFJk2aYPr06Vi2bBk2bNgAU1NT9nxeXh6MjIyUYm5SGpYuXYoLFy7gxIkT\nMDY2RkBAANatW4e1a9eiTZs2aNWqFczMzJiz1P8lcHwsFosxceJEhIeH4/bt28wcRtIsDVBN4hge\nj4c3b97gyZMn2LRpEwCwcGdlvfMtPheJRPj06RMKCwul5EFCQgJiYmIwePBg7N69G7/99hvatm0L\noMimWHLHszJA/7Pb5cyCPDw88NNPP+HTp0/w9fVFdnb2N02kvgWBQIA7d+4A+MfEZc2aNTAyMoKV\nlRW2b98OsVgMLS0tpX7jt2/fYuHChTIdPIGi71ijRg3o6OioNKsiB1mh9CRDnxWfNxo3bgxAfr4n\nIiYTub9c/5ubm+PWrVul7uhydWnUqBEaNGggF30AePHiBUJDQ7FhwwY8fvwYJ0+ehKOjI3799VeM\nHDkSgwcPljLHUGQe09DQQGFhIT58+IBNmzahevXqGD58OIgIGhoa/8kd5x9K8zegra2NLl26oHfv\n3nj8+DEePHgAAPDw8ECbNm2wc+dOBAcHo3Hjxko5miwNpqamGDduHAYNGoSmTZuCiHD27Fns2rUL\n9+/fx7Zt2zBp0iTUqFGDKZiKOL5FRERg6dKlSEhIQG5uLqM3efJknD59GlWrVkWtWrUgEonw5s0b\n5Ofnyx0V4lvgnA7mz5+P7OxsrF27Fnw+HxEREVBTU2MT+apVqxAXFyfziEtRVFRhVgY9APjjjz8g\nFAoxevRodl1yIcQt1PT09PDnn38iIyMD0dHRJZxVFUV6ejru3LmDAwcO4OrVqwBKj9ghiW8tVjQ0\nNJCeno60tDR8+vQJ9evXh52dHWxtbdGxY0eYmppKLfb8/f0hFAqVmiCouCLYq1cvXLp0CUZGRkxh\nXrduHVsIVK9eHXw+H69fv1ZaHf4N4I7exWIxJk2ahEaNGsHf3x+1atViKXQ5f4K3b98iPz9f6aYJ\nHN+npKSgW7duyMzMxOzZswGAxZqXF+/evUNAQACWLl3KFgF5eXlIS0vD5s2bsWTJEgQFBTHFCCiy\nW9bT01OgRRUHj8fD3bt3sXXrVixcuBCOjo5ITU1FkyZNIBKJcOTIEXz9+lUqykFFcfnyZZw7dw6B\ngYEAAG9vb2RkZODChQvMd+To0aOsPspC8+bNMWnSJKxfvx7+/v4l7kvSUpbTa/HxzUGR2NPy9gmP\nx2My8evXrwCKFGkigoGBgcysk8oCn8/HlStXMHPmTBw7dgxfv35F69atYWBggJUrV2LTpk3Yt28f\ndu/erZSMltzc8PDhQ5iamqJv377Yu3cvDA0N/9OK8w+luRyoXr06unbtCmNjY7x48UIqHIulpSVW\nrlyJqlWrKhxG7VswNDSErq4uRCIRPD098ddff6Fp06bYt28fWrRowYR7REQEtm7dit9++00uOoWF\nhSzM0Pv379lOb6NGjbBlyxasX78eixcvhqGhIdTV1fH69WtoampCU1NTabsSr169Qnx8PICiidTD\nwwPv37/HoUOHYG1tjczMTJw8eRIApLL8aWhoKH33i9v5AVSrMOfk5CA2NhYfPnxg9Ly8vNCxY0e4\nuLggNTVVSgkViUTMZtjV1RXm5uY4efIkxowZo/DuMgf6n40vn89nzlH79+9nGeEU2fHi8/l4+fIl\nMjMzkZ+fzxadshRtbsx9+fJFagGhDPz+++84ePAgQkNDIRaL0bt3b5iYmOD69evYsGED1q1bB2tr\na4jFYjYB6+npSXmC/18Ad3rg7OyMOnXqYPHixQCARYsWoWbNmkx5vXTpElatWqWSnXbu2//xxx9o\n0qQJli1bBj6fz9L3KqI4X7hwAYWFhWjQoAE7vahatSratWuH/fv3o3Xr1hAKhRCLxYy3Xr9+rXK5\nDkjvXL558wZ79+7FokWL0KlTJwgEApiYmKB9+/bo06cPCgsLceTIEWRmZsp9gtazZ090794dDx8+\nxOjRo5GWlsaU5Jo1a8LKygrx8fEsQZciePHiBc6cOYMnT55AIBBg6NChWLx4MVavXl1CcRYKhSy7\nnrI2objxHRYWxvpZ0oa5spK1PHnyBIcOHYKrqytGjhyJFStWsDTYPB4P+vr6EIvFyMvLU8kJTpUq\nVdC5c2f4+vrCx8cHa9aswfjx41GlShW0adMGFhYWMDMzUyjijyS4hcWdO3dgYGDATnh2794NIyMj\njB49minO/yX8UJrLCVNTU9ja2uLs2bMs/ApQ5IG6bds2FgpGFcxeHJcuXYKenh6mT5+OX375BQYG\nBhAKheDz+Zg7dy5Onz6NxMREODo6ylX+8+fP4efnh9zcXGhpaTFlvGPHjmjbtq1UG5OSknDq1CmM\nGTMGRkZGCu9KiMVi5Obm4syZMzh27BgTIgMHDsSZM2fYc97e3oiLi8Pnz58hFovx+fNnzJkzBzVr\n1oS9vb3ctIEi5VWWiYsqFWYiwpkzZ3Dp0iWsWbOGOfJxdPX09DBnzhzmXc15egP/xN7eunUrtLS0\nlCqEuLb/8ccfMDc3x5QpU+Dm5oZDhw4prDgvXboUO3fuxM6dOzFy5EjMmzePeegXh5qaGsLDw3Hx\n4kU0atSIXVMUfD4fubm5KCgogLm5OWtHSEgIvL29sWbNGqYwq6mpQUtLC2lpaUhISFBpSvbvhceP\nH8Pa2pp56HM8uHLlShgZGWHy5Mk4cOAA5s6dCyMjI4XpSfIN9z+3OBwxYgQsLCzg5eWFvLw8hRVn\na2trNGvWDFZWVli8eDHjX7FYDF1dXQwfPhx9+vSBjo4O46309HSl7LpJQrLNXOQjSblpYWGBNWvW\nsJM7LS0tdsLUunVr9OvXD+np6Thw4IBcC0eRSAQzMzOMHDkS4eHhSExMxMiRI9n9qlWrolevXoiI\niGDxeRXB58+f8fDhQ2RkZLC2Dx48GL/99htWr17NTgY5Ber169fIy8tTihyTHN916tSBWCyW2uEc\nMGAAmjVrVimxp4VCIYgI/fr1w5gxYzB16lQpGZKeng5DQ0MYGBgoNI9yfVz8LwDUrl0b9erVY1kV\ns7OzWQhPVeDu3bu4d+8eJk+ezDbVtLS0sGvXLhQWFjJn0/8S/lsq/ndGhw4d8OuvvyIwMBBWVlYo\nLCyEpqYmsy/mduUUBVdOaeWNGDGCpe0GioTSs2fPcOnSJWhqamLx4sUwNjaWa4fk2rVriIuLQ+fO\nnbFw4UIA/5gEyPIWj4qKQtOmTfHzzz9XmJYsZGVlMXOPjRs3AiiKhjBgwAAA/9iZaWhoICcnBxkZ\nGahVqxZq1KgBBwcHVo+KhtTjng8PD8fx48exaNEimJiYsPuHDh3C77//Dn9/f5WYZGRlZeH169fo\n0aMH2rZtCx6PBy0tLUZn586dmDlzJmbPno2NGzeynTJZyWrkUSaLt4frZ+5bv337FlZWVgCAvn37\ngohw6NAhqKmpwcHBQS6+9/LygpeXF5YuXYq8vDykpqZiwoQJMp9NT0/HxYsXMXnyZHTs2LHCtErD\nhw8f8NNPPyEqKgq6urrMPMHMzAxnz56FpaUl61Pub05ODurVq/ddE4zIi2/JFmtra1hbWwMAizsO\nFMW+JiLExMTg0KFDUiYMFaUNAOHh4Wjfvr1UHbj/L168iLdv37KICU2bNsWcOXOwbds2TJw4EYcO\nHarQ2CMiiEQiJhvmzp2LlJQUrF69GoB0NAzJ+oSGhkJdXR0NGzascFvLqgtHY/fu3bh//z4WLlzI\nIvtwdsTcwlAoFCIrKwt8Pp8pWK1bt4ZIJIK5uXmFx7pk9Itp06ahevXqGDJkCMLDw8Hn8zFs2DAA\nRZEV+vfvj9TU1BL1rgji4+OhpqaG3NxcNGnSREqmOTg4AChakPF4PAwcOBBpaWm4fPkyRowYoVDE\nHw6yxjcAZGZmwtHREZaWlpWWvrlbt27o1q1bqfcDAwOlZK484GTUs2fPcP78eWzcuLHUyBgaGhqo\nXr06tLS0wOfzlX5yVlhYiMTERDg4OMDc3FxqbtLS0sLhw4cVisjxvfBjp7mc4FZrJiYmeP78udSE\nwkGZiUvS09Nx//79EvFoi68eIyIisHnzZjx//hx9+/bFgQMHUK9ePbmPFOvVqweBQAB/f3+sW7eO\n0eJCfnF1BIp2ZPfs2QMDAwMWbk1RGBgYoGbNmnj58iXS09NL2DtxQs3IyAiNGjViO2HVqlVjk6Kk\nOUV5wA3muLg4LFy4EJaWljAxMYFYLMaqVavw6dMn2NjY4OrVq2jQoIFKhKu+vj6cnZ3RtGlTljyD\nc/jj+p3bcV60aBELJacMhZnbtX737h0OHjwIAFLtu3DhAp48eQIbGxsARX09YMAATJo0CWvXroWf\nn1+FaRYUFKBWrVo4ceIEAgIC8OzZMxw/fhxASRtEsViMv/76C8nJyUxxVxaaNm2Ktm3b4q+//oKf\nnx/y8/OhpqaGRo0awdLSUoqXuL9btmxB9erVK93WVVF8S7YUh6QS6efnh5CQEBw4cEBhhXnDhg3Y\ntWsXi6sumanz9evXuHv3Lry9vaGnp8d4v3HjxnB3d4e6ujobHxWhy+1azpkzB7m5uTh27BiAsv0+\nLC0tsXr1aqWZZ0j2waZNm+Dr6wt9fX0pM7Ti41dDQwOfP39mGzSc7G3Xrp3Uor4sCAQCZrvMLf6e\nPHkCDQ0NHD9+HE5OTtDX10dERARiY2MZDaFQWCK8XkXb26BBA7Rs2RL6+vpo1KgReDwe1NXV2fzl\n4OCARYsWYfny5bh16xZSUlKgoaGBDh06VJieLBQf35yvR1ZWFvr06VNpCnNZ4Po7IyMD48aNAyDf\niTW30RETE4MlS5bg+vXrOHv27DdpGxgYoFq1ako/JdfU1ISdnR3s7e2hqalZgrf19fX/kxsPP5Tm\ncoITGl26dGEB0FUBNTU1REdHY968ebh58yYiIyNl1oPH4yE0NBSTJ09GixYtMGbMGIwdOxaAfLae\nnB1Zq1at4O7ujokTJyIsLAxubm7Yu3cvEhISmFDhmP/Nmzdo3Lgxpk+fDkBx0xSu3tnZ2WjYsGGp\npgY8Hg85OTl48+aNwhFLJBXm6dOnw8XFBa6urhCJRBg1ahTy8vJQu3ZtNGzYEPXr11dZnFIiQsuW\nLaGrq4sdO3bgzz//ZO0orjhXq1YNvXr1gpaWlkIKs0gkAp/Ph4aGBmJjY+Hu7o69e/eyHX4u62RY\nWBjc3d1hbGzMFjHa2tro06cPZs+eXe6EEgUFBQgICGDvA0XOnQ0aNED9+vWxYcMGACjhsc+dLNSr\nV09pCWq4/oyOjsbo0aOhrq6OoKAg1ucc/eK8FB8fj9q1a8PFxUXquf8CviVbJCGp4F26dAn79u3D\njh070LRp0wrTlSyLi5SyceNG6OjoICAgACNGjGDe+jVq1EDnzp3Z7q7kWGvVqhV8fHxkZgmUhYiI\nCKm02vPmzcPVq1cxfvx4AP/4bpQGbW1tmJmZKWW8F1eYAwICcP/+fYwYMQLbt2/Hly9fZI5fImKn\nPLq6unItis+fP4/z588zB141NTW0bt0a+/btA1A03saMGYMhQ4bA1NSU0QgNDZUreytnKsjj8RAV\nFYXJkycjKCiI2UwD0iZdQ4YMwW+//Yb58+fDzc0NxsbGsLS0rDBdSZQ2vjnUq1eP2ex/7/TNampq\nePz4MQIDAxlvV3SRwrUhNjYW06ZNg7OzM5YvX87Mf0qTU9zutq6urkrijRsaGqJJkyZKL/e7omIR\n6n4gLi6OPD09lRonk8Pbt2/p3Llz1KNHD9q+fTu9fPmS3ZNF7+3bt/TgwQOpa/LUKyAggMaPH0+5\nubkl7h0/fpwWLFhAVlZWNH/+fFqzZg0dPny4RPxOReMgS9Z7wYIFNHv27DKfz8nJoaFDh1JkZKTc\nNLk6x8bGkq2tLYuDLBQKycnJiZYtWyazfqqGr68vjRs3jpKTk6WuS8ZmXr58Oe3du5eI5Ov7goIC\n2rBhA925c4ciIyPJzs6OTp8+TS9fviRvb2+KiopizwYFBVFERITMcirSL9euXaNRo0aRv78/ERF5\neXnRuHHjiIgoKyuLXF1dadeuXd8sR9FvwfVjVFQUWVtb09mzZ4mIyNHRkVatWvVN2p8/f67UuMXK\nQEVlC4czZ87QgAEDKDo6Wi66kmVv3bq1ROzrHj160KhRo+jatWvsuby8PLloFae7du1a8vLyIiKi\nOXPm0Pjx4+nEiRPk6upKf//9t8I0KlIXDhs3bqQ+ffqwPiAiWrx4MV2/fp2IZI/l7OxsCgoKkpt+\nRkYG7du3jxYuXEhXr14ttW6S/0dFRZGHhwd9/PixQrQEAgFt2LCBUlNT6e3bt2Rra0tnzpyhGzdu\n0Jo1a8qkefXqVVq4cKHMexWBIuP7eyA1NZVmzpxJv//+u1zvc+2NjY2l3r1706lTp4iIKCwsjLp3\n704JCQmlvrtjxw5asGABEVXuHPdfxg+lWQ5wzKVMJvPz86NVq1bRnDlzmADlEBYWRlFRUVL0lJWs\ng6hI0Dk6OkoJLIFAIPXMw4cP6cqVKzRt2jTavHlzmQHqywvJQPdisZhEIhElJSWRl5cXxcbGsuuy\nEB8fTwcPHlS4DrGxsdS/f3+mMItEInJ2dqbVq1ezZ4onLVE13r17R25ubvT8+XMiku4Dybqkp6fL\nTaOgoIB8fHzI3d2drKys6MyZM0RUJMC9vb3p2LFjcpddGpKSkujatWvk5eVFw4YNk0pQIxAIKDg4\nmObMmaOSBAIcik+ovr6+7F5wcDDNnj1bqWPr34CKyhaiIp7Lysqi0aNHSynY8kKWwtyzZ08KCQmh\nY8eOkZubm8I0iiMjI4Pc3d1p9OjR5OLiQkRFyX7Wr19PPj4+JBAIVK4oyFKY09LSiOgfGbt06VKa\nNWvWN9+XBxy/Z2VlMQXp9u3b33yvsLCQIiMj6evXrxWiJxKJyNXVldzd3dlCnIgoMjKSOnTowJLG\nSEJWG+Udg//m8R0UFMRkOgehUEjXrl2jWbNm0atXrypcJteWmJgY6tu3L5vHxGIxCQQB22amAAAS\nvklEQVQCmjJlCr17967Ee4WFhSQUCunkyZNy0f3/GT+U5n8BEhMTaeXKlXT06FGpHb6cnBzas2cP\n2dvb05EjR5SyA1McnJBJTk4mBwcHqaxzqp5QXr58SQMHDqTLly+zaydPnqRhw4bR58+fSzyfm5tL\nKSkpJa7LW89Xr15Rp06dpHaYXV1d6eeff2Y7UaoQsKWVKdmOuXPnsl2y8r5fXnCTdVRUFLVr144u\nXLggdf/hw4dkZWVV5g5FRcHVWSAQ0PDhw8na2pouXrwo9Uxqaio5OTnRuXPnlEZXEmVNqERFi5Uu\nXbooZUH4b4GiskUZ2SRXrFhB/fv3l6kwExUtpkaMGEFfvnxRmswRiUSUk5NDY8eOZQozh6tXr9KQ\nIUOY8loZ2LBhA/Xr14/RFAqFrK2hoaHk7OzM6q0oCgsLpbK6cWVmZGTQihUraP78+Srhca49jx49\noo4dO1JgYKAU/YULF9KVK1ekrikT33N8i0Sib46VU6dOkbu7O3ueqKjPjh49KnWqWVHExcVRp06d\n6Pz581LXExMTadSoUbRq1Sq6desW+fv70x9//CH1TGVvCP1fwI/oGf8CmJiYYMqUKdDR0UH16tVB\nRLhy5QpevnyJ58+fY9WqVahVqxaqVKnC3lGWHRbnlFGzZk04OzvjxYsXyMzMhL6+fgkbJ1JSdBAO\nrVq1wsyZM7Fx40ZUqVIFnTp1wtGjR7Fo0aISdotEhPDwcOTn56Nr166oWrUquyevk0pGRgaWL1+O\ngQMHQiQSwdnZGcbGxhg1ahSuXr2KmjVrltvZpiJQU1PDp0+f8O7dOxgaGrJ4pDwejzn8ODo6wtfX\nt9T35QXnwBoTE4PZs2djwYIFzGOei0/bvn171KtXT8pBS1Fwdeb4fN68eQgJCQGfz2eZDo2NjWFt\nbY2YmBhWH2WEleOgrq6O58+fw8PDA1OnTmVON1y769Wrh1atWrGkA/8XoKhsUUa8b0NDQxw/flwq\nuyIX+5r+F/4rKysLmZmZSgljBxTxW7Vq1dCvXz98+PABQFH2SR0dHQwaNAiXL1/G7du3paIQqQon\nT57E4cOHERISAkNDwxKyW1NTE+/evUNGRobCzqVEhNWrV8PU1BQjRoyAsbExc/7T19fHtGnTsHz5\ncly5cqXcvgjlBSeHTUxMoKenV8KZr3r16ggODsaQIUNUYj/7vcY3EeH06dMwNjZGjx49pOam4vXj\nQoZK+iZx/hFcWRXpG5FIhODgYMybNw/Dhw/H06dPsXfvXmhqaiIlJQX5+fnw8/NDSkoKUlJS0LJl\nSzRv3pz5JnxPW+7/Kn4ozf8CaGpqMuVMLBbD29sbOjo6aN68OWbMmCGVMjg+Ph7Xr19HlSpVMH78\neKUIH66Mtm3b4siRI3j27Bn69etX6nPKRP/+/aGuro61a9eiWbNmGD16NHr27CmVrUldXR0ZGRm4\nevUqrKysShVKFQGPx0PHjh1ZCKTx48ejcePGWLFiBV6+fInNmzfj/fv3LNSWstuekZGBY8eOITo6\nGv3790e7du0wYMAAFpHF3Nwc0dHRSE5OlkojrSjU1NTw4cMHeHp6YuzYsSw+K6egck53IpEIUVFR\naNasmdJoh4eHQygU4vjx4xAKhcjNzUV4eDg6dOiApk2bsuQaXLQCZSrMQFGfc06ukl7qXLuBIr6I\ni4tD9+7dlUr7e+F7yhZu3MyYMQMAcPPmTSmFWSwWQyQSQVdXFzVr1lRaQh5J2tWrV2dKs46ODpMn\nJiYmSkncURZtDkOHDkXfvn1hZGQkc7OjevXqqFWrFvT09BTmeR6Ph+HDh2Pfvn3Q09NDv379YGJi\nAjU1NYhEIhgbG2P+/PkYM2YMBg4cqNTwjUBR2y0sLGBubs6ctOl/TmgdOnTAn3/+yeqpbHyv8c3j\n8dCmTRssXboUQFHiGEkHSu6bGxkZsUWhpMOxrP/LC3V1dYwbN46FI9TX18fAgQPRtWtXGBgY4NSp\nU8jJyYGnpyebU39AMfzowX8ZDh48CF1dXYwfPx516tSBjo4OC0S+Zs0aiEQivH//HjNmzFC64GnU\nqBGGDx+OEydOoFu3bqhSpYpKhFtx9O3bFzweD4sWLYK5uTkLESUQCJgw8PLyQqNGjTB06FCl0eWS\nBvz6669o1qwZVqxYAaAo1FTHjh2xYcMGnDlzRunKGwC0bNkSu3btQmxsLI4cOYKwsDDUrVsXLVu2\nZLFaAcVSoZeGgoICFBQUoGXLlqyPuTZyO93VqlUrd5SC8qJ9+/Ys1JeGhgYGDhyItm3bwszMTMpj\nX9lh5TgYGBjg/PnzqFu3LgDpSYqbUKpVq/Z/LtMfh8qWLZJlXLt2DfPnz8fBgwdhZWUltUhLSEhA\nYmKi0jI8StKuWrWqlJLKKXB6enpyRYb4FiR56tGjR2jYsCFLBU//CyFZHPHx8RAIBEqTM61atcKM\nGTOwc+dO8Hg89O3bFyYmJiwGuYWFBZo2bYrMzEyl0JMEj8eDpqbm/2vv7mOqqh84jn/u5SGWF01g\nopJFaj4g2S4Za9OUuGzlhEH9wxB6lNoaG7UwH9pc6RSI5tIt063+sAebMlekm0IF+k9p5dOwKBZE\nIpQoEHAvARfo/v5w9wQIv/v75X0AfL/+wXvu9XzPOfee7/mc7/me71FXV5f++OMPo1zp+tB3Q4fT\n9PaxJZD7d3x8vLZs2aKioiKZTCatWrXKOAl0r/8vv/xiDKfpXrbRxin/f7mPFS6XSwsWLBg2wk1v\nb68x0tfg4CCh2QvYguPM2rVrZbFYjNctLS06f/68PvroI4WFhemVV17RXXfdpfDwcJ+Uv2zZMh09\netQY09VfbDabduzYoeLiYi1dulRpaWlGZZCdna3p06dry5Ytkrxb4TY2Nmrp0qXG8EPuEGmz2XT2\n7FmfXr4KCQnRkiVL9MYbb6izs9NoETSbzcbYmb4IzfPnz9fOnTtVVFSknJwcPfbYY0YLd0hIiFpb\nW3X58mWfPT7Y/f1Nnz59WDeg2tpahYeHe/XEaKTRDqhug4ODampq8tqY4+NNIOuWmTNn3hCY3X/b\n29u1YMECxcTEeD1MxcXF6ccffzTGIneHhp9//tnr3/PQZd+1a5f27dun/fv3G1eKxlqv1tZW4zPe\nag1ctGiRXnrpJb399tvq6OhQdna2pk6dagTzKVOm+KQxQLp+4t3b23tD967+/n6jTvfV0J2B3L+t\nVqs2bdqkoqIimc1mrVy50hg+02QyqbOz02jh9sVJw9D5uRs/7Ha70brtzSs5tzJC8zgz9KBWXV2t\n0tJSmc1mpaSkjPm0NG+Kj4/X4OCgTp06NWoXDV9yP1mxpKREXV1dSklJ0fr16xUeHq533nlHkvf7\nucbGxg4br9MdHu12u7q6uozKx5csFovxvbvXr6mpybik5wtWq1UFBQX65ptvjO3prsjb29u1ePFi\nxcbG+qTssVpXFi5cqNzc3GH7gK+MPGC5u6T09fUN67IwmQSybnH3bx26/7r/7tmzR1FRUT4JUXPm\nzFF+fv6wINrW1qbbb79dNpvNa+UMDUFvvfWWKisrZbPZ1NDQoIceemjMkORwOHTs2DElJydLkldb\nAhcuXKi8vDydP39+WOvq77//rurqamVlZXmtrKGcTqdSU1MVFxcn6Z8TAbvdrvj4eEm+70sbqP07\nISFBmzdvVmFhoUwmkx5++GGFhoaqvr5eR48eNcai99UJi5v7mFVbW6ukpCSflnWrITSPU2fOnNHL\nL7+sp556SsuXL9eSJUskeT80DuVyuYyWVrvd7pMyPElJSVFQUJBeffVVVVZWKiYmRsXFxZJ8u+7S\n8Ir83LlzxiNNfdEqMJah3RTcrWO+kpiYqGXLlt3w1K+SkhJNmzbNZ1cz/hv344QDoaysTBaLJaDL\n4A+BqFvcRs7/p59+0h133GE8mMkX+9rIIDowMCCLxeK18DQyMFdUVKi0tFQHDx7UuXPnlJWVNeY6\ndXd3y2QyGQHT2+677z7jQSHu7/fy5ct68MEHb/oBImOxWCx67rnnjJZN9/b/8ssvfdb16n/hr/07\nISFBr732mgoLC2U2m5WYmKhTp04pLS3tvz5G29v+/vtvhYeH+73xa7IjNI9TERER2rFjh1atWmVM\nc9/U4Csmk0m33XabXn/9da+OnPD/euSRR1RRUSGn06lZs2ZJ8s8B3c1ut6u+vl7p6ekB6QPm7vuX\nkZHh80tqI7dpX1+fHn/8cePOen+eMARaY2OjcWPUZF7vQNQtY5k3b57Wr19vtIT6Y5tHR0dr27Zt\nXunTPPR3UlJSooqKCh06dEgRERGaPXu28UTCsX5PnZ2deuCBB7x+Q95o3N+v+wqDL6/ojNy2ly5d\nUkhIiF9GKxmLP/dvd3AuLi7Wn3/+qRMnTigtLc1n5Y2mqqpKFy9e9MqN8/iHyeW+MwIYpwIRYJxO\np1wuV0D7gTkcDr90VcB1Bw4c0IoVK3T33XcHelHgY96oU4bO480331RFRYUOHz5stGCfPn1au3bt\n0ocffqigoCCPV438Uc8NDAyopqbG7yfFTqdTH3/8sTIyMgLW/SkQ+/fZs2eVm5ur5ORk7dy502/l\nSlJ9fb3q6ur06KOP+rXcyY7QDOCWNplbleF7JSUlOn78uA4fPqzIyEiji9u3336r9957T++//36g\nF3FUt8rvPtDr2dzcrJiYmHGxLLh5dM8AcEvjIIZ/q7i4WJ999pmOHTtm3LQ7dLjI8TzE163yuw/0\nehKYJ5fxu0cDADBOORwODQwMqKysTJGRkbpy5Ypqa2t17do1OZ1ONTU1qaOjQ2VlZZo1a5bmzZun\nqKioQC82AoTAPDnQPQMAgH/BPZyay+VSdXW1Tp48qfr6evX29mru3Lm6du2aGhoaJEn33HOPNmzY\n4NUnfALwL0IzAAA+4nQ6FRQUpEuXLmnu3LmBXhwAN4HQDACAF7mHyBytHyt9W4GJi9AMAAAAeOD/\n0ewBAACACYbQDAAAAHhAaAYAAAA8IDQDAAAAHhCaAQAAAA8IzQAAAIAHhGYAAADAA0IzAAAA4AGh\nGQAAAPCA0AwAAAB4QGgGAAAAPCA0AwAAAB4QmgEAAAAPCM0AAACAB4RmAAAAwANCMwBMYKtXr9aB\nAwd05MgRrV69WlarVdnZ2aqtrTU+09bWpo0bNyopKUlWq1WZmZn67rvvjPe3b9+u/Px8HT9+XGvW\nrJHVatW6devU0tKihoYGZWZm6v7771dqaqqqqqqGld/V1aXNmzcrKSlJy5cv16ZNm9Te3u639QcA\nfyE0A8AENm3aNFVVVWnPnj3aunWrvvrqK8XHx+vpp59WX1+fXC6X1q1bp56eHu3fv1+VlZVKSEhQ\nXl6e/vrrL0nSlClTVFNTo3fffVfbt29XeXm5JGnjxo3Ky8tTVlaWTpw4oezsbOXn56u1tVWSNDAw\noLVr1+rq1avau3evDh48KEl69tlnNTAwEJgNAgA+QmgGgAksJCRE33//vT744AMlJiYqMjJSBQUF\n6u7u1g8//KC6ujqFhoaqpKREsbGxioiIUEFBgXp6elRXV2fMo7m5WXv37pXValV0dLRefPFFnT59\nWunp6crIyFBERISysrIUERGh6upqSdLnn3+ujo4O7d69W4sXL9acOXNUWFgos9msI0eOBHKzAIDX\nEZoBYIJbs2aNZs6cabwODQ1VVFSUHA6H7r33XpWWliosLMx4Pzg4WBaLRX19fca0uLg43Xnnncbr\n6OhomUwm2Wy2YWVFRUWpq6tLknThwgUlJyfLYrEY75vNZtlsNn399ddeX08ACKTgQC8AAODmxMfH\n3zDNZDIZ/25sbFRpaakuXLiglpYW9fb2qrOzc9jnhwZm6Xr4laSYmJgx53vlyhWdOXNGX3zxxbDP\nOJ1OzZ8//9+tDACMU4RmAJjEampqlJOTo9TUVL3wwguaPXu2wsLC9MQTT9z0vKOjo/Xkk08qJydH\nLpdr2HvBwRxeAEwu1GoAMIl9+umnWrlypbZt22ZMa2trk8PhuOl5W61WlZeXa8aMGcOmnzx5UsHB\nwVqxYsVNlwEA4wV9mgFgAnM6naOOVNHf36/+/n7NmDFD9fX1unjxoq5evary8nLl5ubKbDarv79/\n2GdH/n+XyzXqdPe09PR0tbS0aOvWrfr111/V3NysQ4cOacOGDQoNDfXRGgNAYNDSDAATmN1uV3d3\n9w3Te3p65HA49Mwzz+i3337T888/r6CgICUkJGj37t3KzMw0+jV3d3ff0PJst9tlMpnkcDg0derU\nG+YrXe+C8cknn6i4uFi5ubmy2+1atGiR9u3bp4SEBB+uNQD4n8k1siMaAAAAgGHongEAAAB4QGgG\nAAAAPCA0AwAAAB4QmgEAAAAPCM0AAACAB4RmAAAAwANCMwAAAOABoRkAAADwgNAMAAAAeEBoBgAA\nADwgNAMAAAAe/AfyMco/Zv3ZHQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x111268748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.countplot(data=solo_anthro_df, x = 'name', order = solo_anthro_df['name'].value_counts().iloc[:20].index, color='steelblue')\n",
    "g.set_xticklabels(labels=solo_anthro_df['name'].value_counts().iloc[:20].index, rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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rcJll3qoNAABwtfN6SH7nnXeUnZ2t4cOHu5fZ7XbZbDb16NFDzZo1k81mU05OjkJDQ0s9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\nlzRs3KWEQp8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10cf7df98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.countplot(data=solo_feral_df, x = 'name', order = solo_feral_df['name'].value_counts().iloc[:20].index, color='steelblue')\n",
    "g.set_xticklabels(labels=solo_feral_df['name'].value_counts().iloc[:20].index, rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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