5) text_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=6> <b> 5 주차 강의 Notebook </b> </font>\n",
    "<div class=\"alert alert-block alert-success\">\n",
    "  클리앙 사이트에서 글을 scrap하고, 그 내용을 분석해 보자! <br>\n",
    "</div>\n",
    "<p style=\"text-align:right;\"> sumyeon@gmail.com </p>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-18T12:02:46.435982Z",
     "iopub.status.busy": "2020-08-18T12:02:46.435982Z",
     "iopub.status.idle": "2020-08-18T12:02:46.441983Z",
     "shell.execute_reply": "2020-08-18T12:02:46.440984Z",
     "shell.execute_reply.started": "2020-08-18T12:02:46.435982Z"
    }
   },
   "source": [
    "- 사전 설치 필요한 패키지들\n",
    "\n",
    "> pip install --upgrade pip <br>\n",
    "> pip install konlpy <br>\n",
    "> pip install gensim <br>\n",
    "> pip install wordcloud <br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " <hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preparation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:28.564920Z",
     "iopub.status.busy": "2020-09-28T12:24:28.564920Z",
     "iopub.status.idle": "2020-09-28T12:24:28.694920Z",
     "shell.execute_reply": "2020-09-28T12:24:28.694920Z",
     "shell.execute_reply.started": "2020-09-28T12:24:28.564920Z"
    }
   },
   "outputs": [],
   "source": [
    "import requests\n",
    "from bs4 import BeautifulSoup\n",
    "import datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import re\n",
    "import time\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Scrap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "proxies={\"https\":\"https://168.219.61.252:8080\", \"http\":\"http://168.219.61.252:8080\"}\n",
    "proxies=None\n",
    "clienURL= \"https://www.clien.net/service/board/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def retrieveURLasBSObj(siteurl):\n",
    "    \"\"\"\n",
    "    retrieve the web content of the URL in the form of BeautifulSoup object\n",
    "    \"\"\"\n",
    "    \n",
    "    page = requests.get(siteurl, proxies=proxies, verify=False) #Request(siteurl, headers={'User-Agent': 'Mozilla/5.0'})\n",
    "    bsobj = BeautifulSoup(page.text, \"html.parser\")\n",
    "    return bsobj\n",
    "\n",
    "def cleanhtml(rawhtml):\n",
    "    \"\"\"\n",
    "    transform the rawhtml into plain text : (ex, remove html tags such as <p> <div>)\n",
    "    \"\"\"\n",
    "    cleanregex = re.compile('<.*?>')\n",
    "    cleantext = re.sub(cleanregex,'', rawhtml)\n",
    "    return cleantext.replace('\\n','')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def retrieveArticle(articleid, bboard='park'):\n",
    "    \"\"\"\n",
    "    retrieve the article information of the given article id.\n",
    "    \n",
    "    Parameters:\n",
    "        articleid (int): article number id\n",
    "        bboard (str): bulleting board name such as 'park','jirum',etc.\n",
    "        \n",
    "    Returns:\n",
    "        tuple (bboard, articleid, title, create_time, author_id, author_ip, content, reply_count, symph_count, view_count):\n",
    "            bboard (str): bulletin board name\n",
    "            articleid (str): article number id\n",
    "            title (str): article title\n",
    "            create_time (str): creation time in the form of \"2020-07-27 21:04:21\"\n",
    "            author_id (str): article author id\n",
    "            author_ip (str): ip ex) 223.♡.21.155\n",
    "            content (str): article content\n",
    "            reply_count (str): the number of replies\n",
    "            symph_count (str): the number of symphathy clicks\n",
    "            view_count (str): the number of view\n",
    "    \"\"\"\n",
    "\n",
    "    targetUrl = clienURL+\"/\"+bboard+\"/\"+str(articleid)\n",
    "\n",
    "    bsobj = retrieveURLasBSObj(targetUrl)\n",
    "    if bsobj is None:\n",
    "        return None\n",
    "        \n",
    "    bsobj = bsobj.find('div', attrs={'class' : 'content_view'})\n",
    "    if bsobj is None:\n",
    "        return None    # sometimes, login page popped up\n",
    "\n",
    "    # title : <h3 class=\"post subject\"  ...> title </h3>\n",
    "    title_h3 = bsobj.find('h3', attrs={'class' : 'post_subject'}).span.get_text()\n",
    "    title = title_h3.replace('\\n',' ').replace('\\r','').replace('|','')\n",
    "\n",
    "    symph_div = bsobj.find('div', attrs={'class' : 'post_symph view_symph'})\n",
    "    if symph_div is None:\n",
    "        symph_count = 0\n",
    "    else:\n",
    "        symph_count = symph_div.get_text()\n",
    "        symph_count = (int)(symph_count.replace('\\n', ' ').replace('\\r', ''))\n",
    "\n",
    "        \n",
    "    view_count = bsobj.find('div', attrs={'class' : 'view_info'}).get_text()\n",
    "    view_count = (int)(view_count.replace('\\n', ' ').replace('\\r', '').replace(',', ''))\n",
    "    \n",
    "    content_div = bsobj.find('div', attrs={'class':'post_article'})\n",
    "    content = cleanhtml( content_div.body.get_text().strip().replace('|','') ) \n",
    "\n",
    "    \n",
    "    author_div = bsobj.find('div', attrs={'class' : 'post_author'})\n",
    "    author_span = author_div.find_all('span', attrs={'class': None})\n",
    "    create_time = author_span[0].text.split('\\n')[1].strip() \n",
    "    author_ip = author_span[-1].text.strip()\n",
    "    \n",
    "    \n",
    "    authorid_span = bsobj.find('span', attrs={'class':'contact_name'})\n",
    "    if authorid_span.find('img'):\n",
    "        author_id =authorid_span.find(\"img\")['alt']\n",
    "    else:\n",
    "        author_id = authorid_span.find_all('span')[0].text.replace('\\n', ' ').replace('\\r', '').replace(',', '').strip()\n",
    "\n",
    "    reply_count_text= bsobj.find('div', attrs={'class' : 'comment_head'}).get_text()\n",
    "    reply_count = (int)(re.findall('\\d+', reply_count_text)[0])\n",
    "\n",
    "    return (bboard, str(articleid), title, create_time, author_id, author_ip, content, str(reply_count), str(symph_count), str(view_count))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "header = \"board|articleid|title|create_time|author_id|author_ip|content|reply_cnt|symph_cnt|view_cnt\"\n",
    "\n",
    "def clien_article_download(bboard, startid, endid, filename):\n",
    "    with open(filename,\"w\", encoding='utf-8') as ofile:\n",
    "        ofile.write(header+\"\\n\")\n",
    "        for articleid in range(startid,endid, 1):\n",
    "            article_tuple = retrieveArticle(articleid, 'park')\n",
    "            if article_tuple is not None:\n",
    "                ofile.write(\"|\".join(article_tuple)+'\\n')\n",
    "            time.sleep(0.1)\n",
    "            if not articleid % 1000:\n",
    "                time.sleep(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "clien_article_download('park', 15242011,15261076, \"c:/temp/clien_park_aug_5to10.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " <hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:32.858920Z",
     "iopub.status.busy": "2020-09-28T12:24:32.857921Z",
     "iopub.status.idle": "2020-09-28T12:24:33.505923Z",
     "shell.execute_reply": "2020-09-28T12:24:33.504931Z",
     "shell.execute_reply.started": "2020-09-28T12:24:32.857921Z"
    }
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"clien_park_aug_5to10.csv\", sep='|', error_bad_lines=False, parse_dates=[3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b> Tip:</b> 앞서 배운대로 오류가 생길 경우, 무시할 수준이라고 판단된다면 error_bad_lines로 무시하고 loading </b>\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:35.721920Z",
     "iopub.status.busy": "2020-09-28T12:24:35.720920Z",
     "iopub.status.idle": "2020-09-28T12:24:35.738921Z",
     "shell.execute_reply": "2020-09-28T12:24:35.737924Z",
     "shell.execute_reply.started": "2020-09-28T12:24:35.720920Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>board</th>\n",
       "      <th>articleid</th>\n",
       "      <th>title</th>\n",
       "      <th>create_time</th>\n",
       "      <th>author_id</th>\n",
       "      <th>author_ip</th>\n",
       "      <th>content</th>\n",
       "      <th>reply_cnt</th>\n",
       "      <th>symph_cnt</th>\n",
       "      <th>view_cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>park</td>\n",
       "      <td>15242011</td>\n",
       "      <td>익스플로러가 느린 이유</td>\n",
       "      <td>2020-08-05 00:01:04</td>\n",
       "      <td>내일은$</td>\n",
       "      <td>218.♡.42.208</td>\n",
       "      <td>얼마전 초딩 아들이 어느 인터넷으로 공부하는 사이트를 사용하더니 저에게 묻습니다아들...</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>3208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>park</td>\n",
       "      <td>15242012</td>\n",
       "      <td>수요일 자정 러블리즈 입니다. [8/4 단신] (데뷔로부터 2095일)</td>\n",
       "      <td>2020-08-05 00:02:03</td>\n",
       "      <td>224-rainbow</td>\n",
       "      <td>115.♡.203.252</td>\n",
       "      <td>카메오(Musical Ver.) 작업 트랙 공개 &amp; 분석(1)[공식] tvN 새 예...</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>park</td>\n",
       "      <td>15242014</td>\n",
       "      <td>제 나이는 여름에는 쿨 이었는데...</td>\n",
       "      <td>2020-08-05 00:02:19</td>\n",
       "      <td>화이트덕</td>\n",
       "      <td>125.♡.110.208</td>\n",
       "      <td>1.코요테가 이렇게 옛날 감성으로 돌아오니 좋네요.2.신지씨 특유의 음 끝 바이브레...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>park</td>\n",
       "      <td>15242018</td>\n",
       "      <td>어느 여자사람의 셀프네일 도전기</td>\n",
       "      <td>2020-08-05 00:04:35</td>\n",
       "      <td>해리비안의 캐적</td>\n",
       "      <td>49.♡.102.42</td>\n",
       "      <td>클리앙에서 이과천재들의 전자기기 후기들을 보며 1도 이해할수 없는 용어의 홍수속에서...</td>\n",
       "      <td>51</td>\n",
       "      <td>24</td>\n",
       "      <td>11075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>park</td>\n",
       "      <td>15242019</td>\n",
       "      <td>아이맥 2020 업데이트</td>\n",
       "      <td>2020-08-05 00:04:54</td>\n",
       "      <td>Daspfel</td>\n",
       "      <td>125.♡.240.232</td>\n",
       "      <td>27인치만 나왔네요. 예상대로 디자인 변화 없이 내부만 업데이트. 10 세대 인텔 ...</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>2014</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  board  articleid                                    title  \\\n",
       "0  park   15242011                             익스플로러가 느린 이유   \n",
       "1  park   15242012  수요일 자정 러블리즈 입니다. [8/4 단신] (데뷔로부터 2095일)   \n",
       "2  park   15242014                     제 나이는 여름에는 쿨 이었는데...   \n",
       "3  park   15242018                        어느 여자사람의 셀프네일 도전기   \n",
       "4  park   15242019                            아이맥 2020 업데이트   \n",
       "\n",
       "          create_time    author_id      author_ip  \\\n",
       "0 2020-08-05 00:01:04         내일은$   218.♡.42.208   \n",
       "1 2020-08-05 00:02:03  224-rainbow  115.♡.203.252   \n",
       "2 2020-08-05 00:02:19         화이트덕  125.♡.110.208   \n",
       "3 2020-08-05 00:04:35     해리비안의 캐적    49.♡.102.42   \n",
       "4 2020-08-05 00:04:54      Daspfel  125.♡.240.232   \n",
       "\n",
       "                                             content  reply_cnt  symph_cnt  \\\n",
       "0  얼마전 초딩 아들이 어느 인터넷으로 공부하는 사이트를 사용하더니 저에게 묻습니다아들...         11          2   \n",
       "1  카메오(Musical Ver.) 작업 트랙 공개 & 분석(1)[공식] tvN 새 예...         14         10   \n",
       "2  1.코요테가 이렇게 옛날 감성으로 돌아오니 좋네요.2.신지씨 특유의 음 끝 바이브레...          1          0   \n",
       "3  클리앙에서 이과천재들의 전자기기 후기들을 보며 1도 이해할수 없는 용어의 홍수속에서...         51         24   \n",
       "4  27인치만 나왔네요. 예상대로 디자인 변화 없이 내부만 업데이트. 10 세대 인텔 ...          8          0   \n",
       "\n",
       "   view_cnt  \n",
       "0      3208  \n",
       "1       496  \n",
       "2       936  \n",
       "3     11075  \n",
       "4      2014  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:37.021922Z",
     "iopub.status.busy": "2020-09-28T12:24:37.021922Z",
     "iopub.status.idle": "2020-09-28T12:24:37.026922Z",
     "shell.execute_reply": "2020-09-28T12:24:37.025928Z",
     "shell.execute_reply.started": "2020-09-28T12:24:37.021922Z"
    }
   },
   "outputs": [],
   "source": [
    "pd.set_option('display.max_rows', 100)\n",
    "pd.set_option('display.max_colwidth',1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b> Tip:</b> pandas의 option 설정으로, Dataframe의 출력 갯수 및 컬럼 길이를 변화시켜 자연어 처리를 준비 </b>\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " <hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 한글 NLP 패키지 로딩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:39.758922Z",
     "iopub.status.busy": "2020-09-28T12:24:39.757921Z",
     "iopub.status.idle": "2020-09-28T12:24:40.063920Z",
     "shell.execute_reply": "2020-09-28T12:24:40.062920Z",
     "shell.execute_reply.started": "2020-09-28T12:24:39.758922Z"
    }
   },
   "outputs": [],
   "source": [
    "from konlpy.tag import Hannanum, Kkma, Komoran, Okt, Mecab\n",
    "from konlpy.utils import pprint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:40.783922Z",
     "iopub.status.busy": "2020-09-28T12:24:40.782920Z",
     "iopub.status.idle": "2020-09-28T12:24:43.069922Z",
     "shell.execute_reply": "2020-09-28T12:24:43.068920Z",
     "shell.execute_reply.started": "2020-09-28T12:24:40.783922Z"
    }
   },
   "outputs": [],
   "source": [
    "tagger = Okt() # Hannanum()  #Kkma()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b> Tip:</b> 한글 처리 엔진은 여러 종류가 지원된다. 장단점을 살펴보고 가장 적합한 엔진을 선택하면 된다. </b> <br>\n",
    "   엔진별 성능 비교  => https://blog.naver.com/PostView.nhn?blogId=wideeyed&logNo=221337575742 \n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b> Tip:</b> 카카오에서 만든 Khaii라는 한글 처리기가 성능이 뛰어난 것으로 알려려 있음. 실전에 사용에 추천 (https://github.com/kakao/khaiii). </b>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " <hr>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 통계 분석\n",
    " - title과 content에서 unpack과 관련된 내용을 찾아, 통계를 내어 보자"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Title/Content를 하나의 content로 처리, whitespace 제거, URL 제거"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:44.121925Z",
     "iopub.status.busy": "2020-09-28T12:24:44.121925Z",
     "iopub.status.idle": "2020-09-28T12:24:44.768919Z",
     "shell.execute_reply": "2020-09-28T12:24:44.767919Z",
     "shell.execute_reply.started": "2020-09-28T12:24:44.121925Z"
    }
   },
   "outputs": [],
   "source": [
    "df['all_content'] = df.apply(lambda row: '.'.join([str(row['title']), str(row['content'])]), axis=1 )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:44.777921Z",
     "iopub.status.busy": "2020-09-28T12:24:44.777921Z",
     "iopub.status.idle": "2020-09-28T12:24:44.828921Z",
     "shell.execute_reply": "2020-09-28T12:24:44.827923Z",
     "shell.execute_reply.started": "2020-09-28T12:24:44.777921Z"
    }
   },
   "outputs": [],
   "source": [
    "df['all_content'] = df['all_content'].apply(lambda x : re.sub(r'https?://\\S+', '', str(x)))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:44.830921Z",
     "iopub.status.busy": "2020-09-28T12:24:44.829923Z",
     "iopub.status.idle": "2020-09-28T12:24:44.847924Z",
     "shell.execute_reply": "2020-09-28T12:24:44.846920Z",
     "shell.execute_reply.started": "2020-09-28T12:24:44.830921Z"
    }
   },
   "outputs": [],
   "source": [
    "df['all_content'] = df['all_content'].apply(lambda x: str(x).replace(u'\\xa0', u' '))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Title/Content에서 명사만을 뽑아보자"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-19T12:17:01.402223Z",
     "iopub.status.busy": "2020-08-19T12:17:01.401212Z",
     "iopub.status.idle": "2020-08-19T12:22:34.416213Z",
     "shell.execute_reply": "2020-08-19T12:22:34.415222Z",
     "shell.execute_reply.started": "2020-08-19T12:17:01.402223Z"
    }
   },
   "source": [
    "df['nouns'] = df['all_content'].apply(lambda x : tagger.nouns(str(x)))\n",
    "df.to_csv(\"clien_park_aug_5to10_with_nouns.csv\", index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:45.396920Z",
     "iopub.status.busy": "2020-09-28T12:24:45.396920Z",
     "iopub.status.idle": "2020-09-28T12:24:47.342919Z",
     "shell.execute_reply": "2020-09-28T12:24:47.341936Z",
     "shell.execute_reply.started": "2020-09-28T12:24:45.396920Z"
    }
   },
   "outputs": [],
   "source": [
    "import ast\n",
    "df = pd.read_csv(\"clien_park_aug_5to10_with_nouns.csv\", converters={11:ast.literal_eval})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b> Tip:</b> pd.read_csv를 이용해 저장된 데이터를 읽어올때, str으로 저장된 list를 복원하기 위해 Abstract Syntax Tree (ast)의 literal_eval 활용 </b>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 언팩과 관련된 단어 리스트를 만들고, 해당 단어가 나타나는 article을 찾아보자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:47.352923Z",
     "iopub.status.busy": "2020-09-28T12:24:47.351920Z",
     "iopub.status.idle": "2020-09-28T12:24:47.356924Z",
     "shell.execute_reply": "2020-09-28T12:24:47.355921Z",
     "shell.execute_reply.started": "2020-09-28T12:24:47.352923Z"
    }
   },
   "outputs": [],
   "source": [
    "filter_keywords = \"노트20 note20 갤럭시노트 언팩 버즈 와치\".split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:47.358924Z",
     "iopub.status.busy": "2020-09-28T12:24:47.357920Z",
     "iopub.status.idle": "2020-09-28T12:24:47.375919Z",
     "shell.execute_reply": "2020-09-28T12:24:47.374939Z",
     "shell.execute_reply.started": "2020-09-28T12:24:47.358924Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['노트20', 'note20', '갤럭시노트', '언팩', '버즈', '와치']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filter_keywords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:47.376920Z",
     "iopub.status.busy": "2020-09-28T12:24:47.376920Z",
     "iopub.status.idle": "2020-09-28T12:24:47.580920Z",
     "shell.execute_reply": "2020-09-28T12:24:47.579919Z",
     "shell.execute_reply.started": "2020-09-28T12:24:47.376920Z"
    }
   },
   "outputs": [],
   "source": [
    "df['interest_list'] = df['nouns'].apply(lambda nouns: [ (keyword in nouns) for keyword in filter_keywords])\n",
    "df['interest'] = df['interest_list'].apply(lambda interest_list : np.sum(interest_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:47.582922Z",
     "iopub.status.busy": "2020-09-28T12:24:47.581921Z",
     "iopub.status.idle": "2020-09-28T12:24:47.663919Z",
     "shell.execute_reply": "2020-09-28T12:24:47.663919Z",
     "shell.execute_reply.started": "2020-09-28T12:24:47.582922Z"
    }
   },
   "outputs": [],
   "source": [
    "df['interest'] = df['nouns'].apply(lambda nouns: sum([ (keyword in nouns) for keyword in filter_keywords]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b> Tip:</b> 가독성을 위해 두 개의 sentence로 나누어 작업했으나, 아래와 같이 하나의 sentence로 처리 가능 </b> <br><br>\n",
    "<pre>\n",
    "  df['interest'] = df['nouns'].apply(lambda nouns: sum([ (keyword in nouns) for keyword in filter_keywords]))\n",
    "</pre>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 날짜별로 언팩 관련 article 비율 확인"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:49.083920Z",
     "iopub.status.busy": "2020-09-28T12:24:49.082920Z",
     "iopub.status.idle": "2020-09-28T12:24:49.121920Z",
     "shell.execute_reply": "2020-09-28T12:24:49.121920Z",
     "shell.execute_reply.started": "2020-09-28T12:24:49.083920Z"
    }
   },
   "outputs": [],
   "source": [
    "df['create_time'] = pd.to_datetime(df['create_time'], infer_datetime_format=True)\n",
    "df['date'] = df['create_time'].dt.date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:49.231920Z",
     "iopub.status.busy": "2020-09-28T12:24:49.230922Z",
     "iopub.status.idle": "2020-09-28T12:24:49.259922Z",
     "shell.execute_reply": "2020-09-28T12:24:49.259922Z",
     "shell.execute_reply.started": "2020-09-28T12:24:49.231920Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>totalcnt</th>\n",
       "      <th>galaxycnt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-08-05</th>\n",
       "      <td>2291</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-06</th>\n",
       "      <td>2755</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-07</th>\n",
       "      <td>2319</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-08</th>\n",
       "      <td>1784</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-09</th>\n",
       "      <td>1648</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-10</th>\n",
       "      <td>1623</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            totalcnt  galaxycnt\n",
       "date                           \n",
       "2020-08-05      2291         79\n",
       "2020-08-06      2755        143\n",
       "2020-08-07      2319         56\n",
       "2020-08-08      1784         24\n",
       "2020-08-09      1648         20\n",
       "2020-08-10      1623         15"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "statdf = df.groupby('date').agg(totalcnt=('interest','count'), galaxycnt=('interest',np.count_nonzero))\n",
    "statdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:49.426920Z",
     "iopub.status.busy": "2020-09-28T12:24:49.425920Z",
     "iopub.status.idle": "2020-09-28T12:24:49.648920Z",
     "shell.execute_reply": "2020-09-28T12:24:49.648920Z",
     "shell.execute_reply.started": "2020-09-28T12:24:49.426920Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bXFHfytlDH6yqjyxyrlkx37CNOd+Ys0HvfIMq6u5nD62X+czX1ZizQf98Qyvq1mcPrZf5zNfVmLNB/3xDO5jY+uyhGTDfsI0535izQfN8npnYy1bMN2RbGW++rYw3GzTPN6hdH3t0PXtoVsw3bGPON+Zs0DffUIv6oKr68V7L2tzafb3MN2xjzjfmbNA336D2USd5YpJdwDeSnJ1k87LVZy9orJkx37CNOd+Ys0H/fIMqauBvgOOqagk4FTgnyVHTdW3OIloH8w3bmPONORs0zze0g4m3r6pLAKrq9CQ7gfclOZnJG9SHznzDNuZ8Y84GzfMNrah/nOTee3bwV9UlSZ4EnMHk7sFDZ75hG3O+MWeD5vmGtuvjZOBeyxdU1S7gGOCURQw0Y+YbtjHnG3M2aJ5vkO/6kKT9yaC2qJPcNckpSS5L8u3px87pskMXPd96mW/YxpxvzNmgf75BFTVwGnANcExV3aOq7gE8cbrsvQudbDbMN2xjzjfmbNA836B2fSS5vKoesq/rhsJ85utqzNmgf76hbVF/Ncmrkty00z/JvZL8EfD1Bc41K+YbtjHnG3M2aJ5vaEX9G8A9gE8kuSbJd4BzgbsDz1vkYDNivmEbc74xZ4Pm+Qa16wMgyc8zuaD3+VV1/bLlx3e4E8N6mW/YxpxvzNmgd75BbVEn+V3gg8DLgYuTPGvZ6r9azFSzY75hG3O+MWeD/vmGdmbiS4FHV9X1mVw05fQkm6vqH2hwPv4MmG/YxpxvzNmgeb6hFfWBe34kqaorkhzD5Bt6fxp8M2fAfMM25nxjzgbN8w1q1wdwZZJH7vlk+o19OrAJePiihpoh8w3bmPONORs0zzeog4lJDgNuWOmuC0mOrqr/WsBYM2M+83U15mzQP9+gilqS9kdD2/UhSfsdi1qSmrOoNTpJXp3kD29j/YlJHrqRM0nrYVFrf3QiYFFrMDyYqFFI8ifAi5hcQGc3sAP4LrANuD3wJeAk4JFMbq/03enHr0+/xOuBJeAHwEur6rINHF+6TRa1Bi/Jo4G3AY9lchLXBcAbgX+uqm9Pn/MXwLeq6h+TvA04o6pOn677KPCyqvpikscCf11Vx258EmllQzszUVrJ44H3V9UPAJJ8aLr8YdOCPhQ4GDhr79+Y5GDgl4D3JjedgHaHeQ8s7QuLWmOx0o+GbwNOrKqLkmxlcqPSvR0AXFtVj5zbZNI6eTBRY3Ae8Owkd0pyCPCM6fJDgG8mOQh44bLnf2+6jqq6DvhKkucCZOIRGze6tDr3UWsUlh1M/CqwC7gU+D7wqumyzwOHVNXWJEcDbwJ+BDwHuBF4A3Af4CDg3VX15xseQroVFrUkNeeuD0lqzqKWpOYsaklqzqKWpOYsaklqzqKWpOYsaklqzqKWpOb+H3NMuYD86A3rAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "statdf['ratio'] = statdf['galaxycnt'] / statdf['totalcnt'] * 100\n",
    "statdf['ratio'].plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 언팩 관련 오피니언 리더 확인?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:50.668922Z",
     "iopub.status.busy": "2020-09-28T12:24:50.668922Z",
     "iopub.status.idle": "2020-09-28T12:24:50.687922Z",
     "shell.execute_reply": "2020-09-28T12:24:50.686919Z",
     "shell.execute_reply.started": "2020-09-28T12:24:50.668922Z"
    }
   },
   "outputs": [],
   "source": [
    "cntdf = df[ df.interest > 0].groupby('author_id').agg(cnt=('title','count')).sort_values(by='cnt', ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:50.753921Z",
     "iopub.status.busy": "2020-09-28T12:24:50.753921Z",
     "iopub.status.idle": "2020-09-28T12:24:50.763921Z",
     "shell.execute_reply": "2020-09-28T12:24:50.762923Z",
     "shell.execute_reply.started": "2020-09-28T12:24:50.753921Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>author_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>fiat</th>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>도라에몽펀치</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>요트맨</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>이리야즈</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>그물새</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>또하나의가족</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TIME_TRAVELER</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SovereignLightCafe</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>쉭한도시남자</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Estere</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    cnt\n",
       "author_id              \n",
       "fiat                  9\n",
       "도라에몽펀치                8\n",
       "요트맨                   7\n",
       "이리야즈                  7\n",
       "그물새                   6\n",
       "또하나의가족                6\n",
       "TIME_TRAVELER         4\n",
       "SovereignLightCafe    4\n",
       "쉭한도시남자                4\n",
       "Estere                4"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cntdf.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:50.933923Z",
     "iopub.status.busy": "2020-09-28T12:24:50.932921Z",
     "iopub.status.idle": "2020-09-28T12:24:51.166924Z",
     "shell.execute_reply": "2020-09-28T12:24:51.165922Z",
     "shell.execute_reply.started": "2020-09-28T12:24:50.933923Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<AxesSubplot:title={'center':'cnt'}>]], dtype=object)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "cntdf.hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  언팩 관련 article의 긍부정 여부를 확인해 보자!\n",
    " - 한국어 감성 사전 ( https://github.com/park1200656/KnuSentiLex )을 활용해 보자"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-08-18T11:34:25.876981Z",
     "iopub.status.busy": "2020-08-18T11:34:25.875982Z",
     "iopub.status.idle": "2020-08-18T11:34:25.884981Z",
     "shell.execute_reply": "2020-08-18T11:34:25.883982Z",
     "shell.execute_reply.started": "2020-08-18T11:34:25.876981Z"
    }
   },
   "source": [
    "<b> 감성 사전의 내용 샘플 </b>\n",
    "<pre>\n",
    "[\n",
    "{\n",
    "\t\"word\": \"(-;\",\n",
    "\t\"word_root\": \"(\",\n",
    "\t\"polarity\": \"1\"\n",
    "},\n",
    "{\n",
    "\t\"word\": \"(;_;)\",\n",
    "\t\"word_root\": \"(;_;)\",\n",
    "\t\"polarity\": \"-1\"\n",
    "},\n",
    "...\n",
    "{\n",
    "\t\"word\": \"(^^)\",\n",
    "\t\"word_root\": \"(^^)\",\n",
    "\t\"polarity\": \"1\"\n",
    "},\n",
    "]\n",
    "</pre>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<b> Tip:</b> 한국어 감성 사전을 활용, 긍정의 단어가 많은 경우 긍정의 article로 반대의 경우 부저의 article로 판단\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b> 감성 사전 데이터 로딩 </b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:52.655922Z",
     "iopub.status.busy": "2020-09-28T12:24:52.654924Z",
     "iopub.status.idle": "2020-09-28T12:24:52.715919Z",
     "shell.execute_reply": "2020-09-28T12:24:52.714920Z",
     "shell.execute_reply.started": "2020-09-28T12:24:52.654924Z"
    }
   },
   "outputs": [],
   "source": [
    "import json\n",
    "with open('SentiWord_info.json', encoding='utf-8', mode='r') as f:\n",
    "    data = json.load(f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b> 단어 : 긍부정점수 형태의 dict 로 변환 </b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:53.699924Z",
     "iopub.status.busy": "2020-09-28T12:24:53.698920Z",
     "iopub.status.idle": "2020-09-28T12:24:53.707926Z",
     "shell.execute_reply": "2020-09-28T12:24:53.706921Z",
     "shell.execute_reply.started": "2020-09-28T12:24:53.699924Z"
    }
   },
   "outputs": [],
   "source": [
    "polarity_dict = { item['word'] : item['polarity'] for item in data}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b> 언팩 관련된 article만을 모아 별도의 Dataframe 구성 </b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:54.076922Z",
     "iopub.status.busy": "2020-09-28T12:24:54.075922Z",
     "iopub.status.idle": "2020-09-28T12:24:54.082922Z",
     "shell.execute_reply": "2020-09-28T12:24:54.081922Z",
     "shell.execute_reply.started": "2020-09-28T12:24:54.076922Z"
    }
   },
   "outputs": [],
   "source": [
    "focusdf = df[ df.interest > 0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b> article내 단어들의 긍부정을 sum해서 article 전체의 긍부정 판단 </b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:54.373919Z",
     "iopub.status.busy": "2020-09-28T12:24:54.373919Z",
     "iopub.status.idle": "2020-09-28T12:24:54.388921Z",
     "shell.execute_reply": "2020-09-28T12:24:54.387920Z",
     "shell.execute_reply.started": "2020-09-28T12:24:54.373919Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "focusdf['polarity'] = focusdf['nouns'].apply(lambda x : np.sum([ int(polarity_dict.get(noun, 0)) for noun in x]) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b> 긍부정 점수의 histogram을 보자</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:55.618921Z",
     "iopub.status.busy": "2020-09-28T12:24:55.618921Z",
     "iopub.status.idle": "2020-09-28T12:24:55.783923Z",
     "shell.execute_reply": "2020-09-28T12:24:55.782921Z",
     "shell.execute_reply.started": "2020-09-28T12:24:55.618921Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD4CAYAAAAXUaZHAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/d3fzzAAAACXBIWXMAAAsTAAALEwEAmpwYAAAQaUlEQVR4nO3df6zddX3H8edroGzhKmDQu640KybVCVSZXDsXsuV2bIOpEU3mUsJInS51Bg1mLBtgFk1ME7KJzqAuq5ZJQuddA7gSRTdk3hETESlDS6nMRjoosFYHAnUEU3zvj/ttci33cm/POfeeez8+H0lzz/l8f73fPT2v+z2fnvM9qSokSW35hWEXIEkaPMNdkhpkuEtSgwx3SWqQ4S5JDTp+2AUAnHrqqbV69eqet//xj3/MiSeeOLiChqSVPsBelqJW+gB7OWLnzp0/rKqXz7RsSYT76tWrufvuu3vefnJykvHx8cEVNCSt9AH2shS10gfYyxFJ/nu2ZU7LSFKDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUoDnDPcmqJF9LsifJ7iSXdeMfTvJIknu7P2+ats2VSfYmeSDJ+QvZgCTp+ebzIabDwOVVdU+SlwA7k9zWLft4VX10+spJzgA2AGcCvwJ8Ncmrquq5QRYuSZrdnOFeVY8Bj3W3n06yB1j5AptcCExU1bPAg0n2AuuAbwygXmnR7XrkSd55xZcW/bj7rn7zoh9T7cixfBNTktXAHcBZwJ8D7wSeAu5m6uz+iSSfBO6sqhu6bbYCX66qG4/a1yZgE8Do6Og5ExMTPTdx6NAhRkZGet5+qWilD2irl4OPP8mBZxb/uGtXnjTQ/bX0mNjLlPXr1++sqrGZls372jJJRoCbgA9U1VNJ/h74CFDdz2uAdwGZYfPn/Qapqi3AFoCxsbHq5zoRrVxnopU+oK1ert22g2t2Lf5lmPZdPD7Q/bX0mNjL3Ob1bpkkL2Iq2LdV1c0AVXWgqp6rqp8Cn2Fq6gVgP7Bq2uanAY8OrmRJ0lzm826ZAFuBPVX1sWnjK6at9nbgvu72LcCGJCckOR1YA9w1uJIlSXOZz2vNc4FLgF1J7u3GrgIuSnI2U1Mu+4D3AFTV7iTbgfuZeqfNpb5TRpIW13zeLfN1Zp5Hv/UFttkMbO6jLklSH/yEqiQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBc4Z7klVJvpZkT5LdSS7rxl+W5LYk3+t+njJtmyuT7E3yQJLzF7IBSdLzzefM/TBweVW9BngjcGmSM4ArgNurag1we3efbtkG4EzgAuDTSY5biOIlSTObM9yr6rGquqe7/TSwB1gJXAhc3612PfC27vaFwERVPVtVDwJ7gXUDrluS9AJSVfNfOVkN3AGcBTxUVSdPW/ZEVZ2S5JPAnVV1Qze+FfhyVd141L42AZsARkdHz5mYmOi5iUOHDjEyMtLz9ktFK31AW70cfPxJDjyz+Mddu/Kkge6vpcfEXqasX79+Z1WNzbTs+PnuJMkIcBPwgap6Ksmsq84w9rzfIFW1BdgCMDY2VuPj4/Mt5XkmJyfpZ/ulopU+oK1ert22g2t2zfupMjD7Lh4f6P5aekzsZW7zerdMkhcxFezbqurmbvhAkhXd8hXAwW58P7Bq2uanAY8OplxJ0nzM590yAbYCe6rqY9MW3QJs7G5vBHZMG9+Q5IQkpwNrgLsGV7IkaS7zea15LnAJsCvJvd3YVcDVwPYk7wYeAt4BUFW7k2wH7mfqnTaXVtVzgy5ckjS7OcO9qr7OzPPoAOfNss1mYHMfdUmS+uAnVCWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNmjPck1yX5GCS+6aNfTjJI0nu7f68adqyK5PsTfJAkvMXqnBJ0uzmc+b+OeCCGcY/XlVnd39uBUhyBrABOLPb5tNJjhtUsZKk+Zkz3KvqDuDxee7vQmCiqp6tqgeBvcC6PuqTJPWgnzn39yX5Tjdtc0o3thJ4eNo6+7sxSdIiSlXNvVKyGvhiVZ3V3R8FfggU8BFgRVW9K8mngG9U1Q3deluBW6vqphn2uQnYBDA6OnrOxMREz00cOnSIkZGRnrdfKlrpA9rq5eDjT3LgmcU/7tqVJw10fy09JvYyZf369TuramymZcf3ssOqOnDkdpLPAF/s7u4HVk1b9TTg0Vn2sQXYAjA2Nlbj4+O9lALA5OQk/Wy/VLTSB7TVy7XbdnDNrp6eKn3Zd/H4QPfX0mNiL3PraVomyYppd98OHHknzS3AhiQnJDkdWAPc1V+JkqRjNefpSJLPA+PAqUn2Ax8CxpOczdS0zD7gPQBVtTvJduB+4DBwaVU9tyCVS5JmNWe4V9VFMwxvfYH1NwOb+ylKktQfP6EqSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJatCc4Z7kuiQHk9w3bexlSW5L8r3u5ynTll2ZZG+SB5Kcv1CFS5JmN58z988BFxw1dgVwe1WtAW7v7pPkDGADcGa3zaeTHDewaiVJ8zJnuFfVHcDjRw1fCFzf3b4eeNu08YmqeraqHgT2AusGU6okab56nXMfrarHALqfr+jGVwIPT1tvfzcmSVpExw94f5lhrGZcMdkEbAIYHR1lcnKy54MeOnSor+2Xilb6gLZ6Gf0luHzt4UU/7qD//lp6TOxlbr2G+4EkK6rqsSQrgIPd+H5g1bT1TgMenWkHVbUF2AIwNjZW4+PjPZYy9SToZ/ulopU+oK1ert22g2t2Dfo8aG77Lh4f6P5aekzsZW69TsvcAmzsbm8Edkwb35DkhCSnA2uAu/orUZJ0rOY8HUnyeWAcODXJfuBDwNXA9iTvBh4C3gFQVbuTbAfuBw4Dl1bVcwtUuyRpFnOGe1VdNMui82ZZfzOwuZ+iJEn98ROqktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoMMd0lqkOEuSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUoOP72TjJPuBp4DngcFWNJXkZ8M/AamAf8EdV9UR/ZUqSjsUgztzXV9XZVTXW3b8CuL2q1gC3d/clSYtoIaZlLgSu725fD7xtAY4hSXoBqareN04eBJ4ACviHqtqS5EdVdfK0dZ6oqlNm2HYTsAlgdHT0nImJiZ7rOHToECMjIz1vv1S00ge01cvBx5/kwDOLf9y1K08a6P5aekzsZcr69et3Tps1+Rl9zbkD51bVo0leAdyW5Lvz3bCqtgBbAMbGxmp8fLznIiYnJ+ln+6WilT6grV6u3baDa3b1+1Q5dvsuHh/o/lp6TOxlbn1Ny1TVo93Pg8AXgHXAgSQrALqfB/stUpJ0bHoO9yQnJnnJkdvA7wP3AbcAG7vVNgI7+i1SknRs+nmtOQp8IcmR/fxTVX0lybeA7UneDTwEvKP/MiVJx6LncK+q7wOvm2H8f4Hz+ilKktQfP6EqSQ0y3CWpQYa7JDXIcJekBhnuktQgw12SGmS4S1KDDHdJapDhLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUoMX/ehkta6uv+NK81rt87WHeOc9152Pf1W8e2L6knweeuUtSgwx3SWqQ4S5JDXLOXcvCfOf6F8Lla4d2aKlnnrlLUoMMd0lqkOEuSQ1yzl1aogb9/wzH8tkDP1ew/HnmLkkNMtwlqUGGuyQ1yHCXpAYZ7pLUIMNdkhpkuEtSg3yfu6Qlw+8LGBzP3CWpQYa7JDVowaZlklwAfAI4DvhsVV29UMf6eTPMy99KLRrmc+pzF5y4IPtdkHBPchzwKeD3gP3At5LcUlX3L8Txdj3y5EDn34Zl0POIUq88gVj+FmpaZh2wt6q+X1U/ASaACxfoWJKko6SqBr/T5A+BC6rqT7v7lwC/UVXvm7bOJmBTd/fVwAN9HPJU4Id9bL9UtNIH2MtS1EofYC9H/GpVvXymBQs1554Zxn7mt0hVbQG2DORgyd1VNTaIfQ1TK32AvSxFrfQB9jIfCzUtsx9YNe3+acCjC3QsSdJRFircvwWsSXJ6khcDG4BbFuhYkqSjLMi0TFUdTvI+4F+ZeivkdVW1eyGO1RnI9M4S0EofYC9LUSt9gL3MaUH+Q1WSNFx+QlWSGmS4S1KDmgn3JO9P8kCS3Un+Ztj19CvJXySpJKcOu5ZeJfnbJN9N8p0kX0hy8rBrOhZJLuj+Te1NcsWw6+lVklVJvpZkT/f8uGzYNfUjyXFJ/jPJF4ddSz+SnJzkxu45sifJbw5y/02Ee5L1TH0C9rVVdSbw0SGX1Jckq5i6dMNDw66lT7cBZ1XVa4H/Aq4ccj3zNu0SGn8AnAFclOSM4VbVs8PA5VX1GuCNwKXLuBeAy4A9wy5iAD4BfKWqfg14HQPuqYlwB94LXF1VzwJU1cEh19OvjwN/yVEf/Fpuqurfqupwd/dOpj7vsFw0cwmNqnqsqu7pbj/NVIisHG5VvUlyGvBm4LPDrqUfSV4K/DawFaCqflJVPxrkMVoJ91cBv5Xkm0n+I8kbhl1Qr5K8FXikqr497FoG7F3Al4ddxDFYCTw87f5+lmkgTpdkNfDrwDeHXEqv/o6pE5+fDrmOfr0S+AHwj90U02eTDPTykMvmm5iSfBX45RkWfZCpPk5h6iXnG4DtSV5ZS/R9nnP0chXw+4tbUe9eqJeq2tGt80Gmpga2LWZtfZrzEhrLTZIR4CbgA1X11LDrOVZJ3gIcrKqdScaHXE6/jgdeD7y/qr6Z5BPAFcBfD/IAy0JV/e5sy5K8F7i5C/O7kvyUqYvx/GCx6jsWs/WSZC1wOvDtJDA1jXFPknVV9T+LWOK8vdDjApBkI/AW4Lyl+st2Fk1dQiPJi5gK9m1VdfOw6+nRucBbk7wJ+EXgpUluqKo/HnJdvdgP7K+qI6+gbmQq3AemlWmZfwF+ByDJq4AXswyvGFdVu6rqFVW1uqpWM/UP4PVLNdjn0n1hy18Bb62q/xt2PceomUtoZOpMYSuwp6o+Nux6elVVV1bVad1zYwPw78s02Ome0w8neXU3dB4w0O+7WDZn7nO4DrguyX3AT4CNy+wssVWfBE4AbuteidxZVX823JLmZwiX0FhI5wKXALuS3NuNXVVVtw6vJAHvB7Z1Jw/fB/5kkDv38gOS1KBWpmUkSdMY7pLUIMNdkhpkuEtSgwx3SWqQ4S5JDTLcJalB/w/6cQHf2UvbTgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "focusdf['polarity'].hist()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b> 긍부정 점수로 긍정(positive), 부정 (negative), 중립 (neutral) 구성</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:56.023920Z",
     "iopub.status.busy": "2020-09-28T12:24:56.022920Z",
     "iopub.status.idle": "2020-09-28T12:24:56.032921Z",
     "shell.execute_reply": "2020-09-28T12:24:56.031921Z",
     "shell.execute_reply.started": "2020-09-28T12:24:56.023920Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n"
     ]
    }
   ],
   "source": [
    "focusdf['sentiment'] = 'neutral'\n",
    "focusdf['sentiment'] = focusdf['sentiment'].where( focusdf['polarity'] >= 0, 'negative' )\n",
    "focusdf['sentiment'] = focusdf['sentiment'].where( focusdf['polarity'] <= 0, 'positive' )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<b> 긍부정으로 구분된 article의 갯수, 글쓴이 숫자 확인</b>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:57.253921Z",
     "iopub.status.busy": "2020-09-28T12:24:57.252919Z",
     "iopub.status.idle": "2020-09-28T12:24:57.280924Z",
     "shell.execute_reply": "2020-09-28T12:24:57.280924Z",
     "shell.execute_reply.started": "2020-09-28T12:24:57.253921Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>article_cnt</th>\n",
       "      <th>author_cnt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sentiment</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>negative</th>\n",
       "      <td>56</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>neutral</th>\n",
       "      <td>224</td>\n",
       "      <td>166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>positive</th>\n",
       "      <td>57</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           article_cnt  author_cnt\n",
       "sentiment                         \n",
       "negative            56          51\n",
       "neutral            224         166\n",
       "positive            57          47"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "focusdf.groupby('sentiment').agg(article_cnt=('articleid','count'), author_cnt=('author_id','nunique'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:57.449920Z",
     "iopub.status.busy": "2020-09-28T12:24:57.449920Z",
     "iopub.status.idle": "2020-09-28T12:24:57.720919Z",
     "shell.execute_reply": "2020-09-28T12:24:57.719936Z",
     "shell.execute_reply.started": "2020-09-28T12:24:57.449920Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "focusdf.groupby(['date','sentiment']).agg(article_cnt=('articleid','count'), author_cnt=('author_id','nunique')).unstack()['article_cnt'].plot(kind='bar')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "<b> Note:</b> 언팩 후에 negative 성향의 글들이 사라지고, positive한 효과가 나왔다. </b>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Word Cloud 생성 (긍/부정의 중심 단어를 찾아보자)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 긍정 성향의 article의 word cloud 생성"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:59.100925Z",
     "iopub.status.busy": "2020-09-28T12:24:59.099923Z",
     "iopub.status.idle": "2020-09-28T12:24:59.107925Z",
     "shell.execute_reply": "2020-09-28T12:24:59.107925Z",
     "shell.execute_reply.started": "2020-09-28T12:24:59.100925Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([list(['갤럭시', '언팩', '것', '오늘', '밤', '11시', '시작이긴', '유출', '영상', '들', '싶습니다;;언팩에서', '가격', '사양', '확인', '출시', '일정', '발표', 'ㅎㅎ']),\n",
       "       list(['갤럭시', '버즈', '라이브', '11번', '재유출(', '+', '예판', '혜택', '버즈', '라이브', '글', '이번', '끝', '거', '어제', '버즈', '라이브', '11번', '글', '어제', '글', '링크', '이', '검색', '줄', '꿈', '몇', '시간', '뒤', '버즈', '플러스', '줄', '전', '검색', '곳', '버즈', '라이브', ';;(네이버', '버즈', '플러스', '최고', '순', '정렬하시', '96만원', '담당자', '것', '링크', '모바일', '네이버', '검색', '버즈', '플러스', '검색', '최고', '96만원', '클릭하시', '가격', '경유', '1', '할인가격', '19.8', '것', '같구', '예판', '혜택', '케이스', '5', '할인쿠폰', '자세한', '거', '페이지', '참조']),\n",
       "       list(['안드로이드', '플랫폼', '100', '만족', '불가능', '10년', '안드로이드', '1년', '외도', '안드로이드', '생각인데요', '안드로이드만', '죽', '때', '경직적', '자유도', '쓰레기', '정도', '인식', '장점', '눈', '시작', '미', '아주아주', '탭틱엔진', '촉감(알람앱', '다이얼', '때', '다들', '아실거에요', 'ㅎㅎ),', '듯', '지원', '기간', '등등', '좋은걸', '안드로이드', '이것들', '그리워지는거', '예전', '줄', '것들', '눈', '시작', '안드로이드', '때', '안드로이드', '뭔가', '부족', '다음폰', '노트21', '정도', '것', '데', '그때', '갤럭시노트', '기가막히', '생각', 'ㅎㅎ'])],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "focusdf[ focusdf.sentiment == 'positive'].nouns.values[:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:24:59.264921Z",
     "iopub.status.busy": "2020-09-28T12:24:59.264921Z",
     "iopub.status.idle": "2020-09-28T12:24:59.270932Z",
     "shell.execute_reply": "2020-09-28T12:24:59.269921Z",
     "shell.execute_reply.started": "2020-09-28T12:24:59.264921Z"
    }
   },
   "outputs": [],
   "source": [
    "from itertools import chain\n",
    "flat_words = list(chain( *(focusdf[ focusdf.sentiment == 'positive'].nouns.values)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 불용어 (stopword 제거)\n",
    " - 한국어 불용어 사전 ( https://www.ranks.nl/stopwords/korean )을 활용해서 불용어를 제거하자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:00.454920Z",
     "iopub.status.busy": "2020-09-28T12:25:00.453919Z",
     "iopub.status.idle": "2020-09-28T12:25:00.480919Z",
     "shell.execute_reply": "2020-09-28T12:25:00.479920Z",
     "shell.execute_reply.started": "2020-09-28T12:25:00.454920Z"
    }
   },
   "outputs": [],
   "source": [
    "stopwords = []\n",
    "with open('korean_stopwords.txt','r', encoding='utf_8') as infile:\n",
    "    for line in infile:\n",
    "        stopwords.append(line.strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:00.620937Z",
     "iopub.status.busy": "2020-09-28T12:25:00.620937Z",
     "iopub.status.idle": "2020-09-28T12:25:00.625925Z",
     "shell.execute_reply": "2020-09-28T12:25:00.625925Z",
     "shell.execute_reply.started": "2020-09-28T12:25:00.620937Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['아', '휴', '아이구', '아이쿠', '아이고', '어', '나', '우리', '저희', '따라']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stopwords[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:00.786921Z",
     "iopub.status.busy": "2020-09-28T12:25:00.786921Z",
     "iopub.status.idle": "2020-09-28T12:25:00.813922Z",
     "shell.execute_reply": "2020-09-28T12:25:00.812922Z",
     "shell.execute_reply.started": "2020-09-28T12:25:00.786921Z"
    }
   },
   "outputs": [],
   "source": [
    "meaningful_words = [word for word in flat_words if word not in stopwords]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:02.330920Z",
     "iopub.status.busy": "2020-09-28T12:25:02.329920Z",
     "iopub.status.idle": "2020-09-28T12:25:02.337919Z",
     "shell.execute_reply": "2020-09-28T12:25:02.337919Z",
     "shell.execute_reply.started": "2020-09-28T12:25:02.330920Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('버즈', 33),\n",
       " ('갤럭시', 32),\n",
       " ('노트20', 32),\n",
       " ('생각', 27),\n",
       " ('라이브', 26),\n",
       " ('사용', 22),\n",
       " ('언팩', 19),\n",
       " ('노트', 16),\n",
       " ('이', 15),\n",
       " ('삼성', 15),\n",
       " ('ㅎㅎ', 14),\n",
       " ('구매', 14),\n",
       " ('수', 12),\n",
       " ('오픈형', 12),\n",
       " ('가격', 11),\n",
       " ('데', 11),\n",
       " ('안드로이드', 10),\n",
       " ('3년', 10),\n",
       " ('T다이렉트샵', 10),\n",
       " ('노캔', 9)]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from collections import Counter\n",
    "cnt = Counter(meaningful_words)\n",
    "cnt.most_common(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 단어:발생횟수 형태의 dict 생성"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:02.971923Z",
     "iopub.status.busy": "2020-09-28T12:25:02.970921Z",
     "iopub.status.idle": "2020-09-28T12:25:02.976923Z",
     "shell.execute_reply": "2020-09-28T12:25:02.975923Z",
     "shell.execute_reply.started": "2020-09-28T12:25:02.971923Z"
    }
   },
   "outputs": [],
   "source": [
    "tags = {word:count for (word,count) in cnt.most_common(50)}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:03.688921Z",
     "iopub.status.busy": "2020-09-28T12:25:03.688921Z",
     "iopub.status.idle": "2020-09-28T12:25:04.953920Z",
     "shell.execute_reply": "2020-09-28T12:25:04.952919Z",
     "shell.execute_reply.started": "2020-09-28T12:25:03.688921Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x276acaf3d08>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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M++VdLitlpVkoQpCe7hjQVy+EQPT6Iu02Mx6Pg7fW7KOkKJPysmzMZhWr1cSk8hzeWL2Pp56N+/g6vcExefHsLisf/sq1tDd52b+lku3vHODA1irSc9yAoK2pk6AvhBAweU4JH/3G9bgzkvvujlfU89SDbxCLjHzEZrGZueXTl5JXmtVnu8micetnLiO/LJtXHn2PmsONBP1h7E4r0xZM4JLbllAyJZ8Nr+4i6Athc1kpKMshtySDu75+Hd42P3anFbsz7ouPGDF+vv8l3mnaRyAW7jMp9pgc3Df5Ys7PnYFE0hb287vDb+KLhZBIjvqb+P3hN/n70fe4smAen59+NeoAP1aPyU6ezdNvuy8a4kd7nmZ3x/F+Lowiewb/b9pVnOMpISYNWsI+fnfojZ7Y85aIj+drtvJy7Q6uKJjL12fdMGAbRkJtoL1PJE5vAnqEtsjpEz4Z/71EgVjcBaM3QXgNMvgPhOPjIMZ2vWowTMrpmaV9Vhr1tRsO8adH1vLB25Zw6UUzexKNOjoCxGIGDoe5J868oyPAD/77eRwOM9/40tXYkySzlBRn8v/uv4Siwgx6D6Kamjr541/f4/zlUymfkI3NasZmMYGA3Fw3c2fHc62OVDXR1jb6PxghBKXT8vni/97Fk796nXUv76Cj2dsTzy0UgSfbxaKLZ3Pz/ZdQNCl3wFFga2MHq5/aSDiYeoJOMhxuG5d9cFk/oy6EwGq3cPFtS1h6+Rya69oIBSJYbGbaGjt45dG1PPy9f+Jt86PrBqqq4E53MOu8ydxw70UsWDWjj5SARNIc7uwzMlYQTHTlcs+ki1iePQ2t6wd4c+kS3GY7vz/8Zo8bRBJ3S7RH/HFDMgx7aiDxx0J9DLpZ0ViYUc7dky5kZloRilAwC4WbShaTYXbyhyNvUeVr6jGyMakT1CPDbsNg6NKg0tecdH9Ij1ITaGd+RsmYzBSGjNGK9P0Y9BowOsFoAjSE85Nguw7RSypBAFPTclmVO3qZtkE9yvbW44STuKScJsvp8TmdxFlp1HOy3LS1+Xnq2S2UlWZRXJhOQ2MnTz27FZOmsGBuWc+xuiFpbvYSClsTxrt3k9WVJZqQrtPcbhtf/twVqKqC1WJi0YIJLFowAYCNmyt56dWd5Oellp4+FIQQ5Jdlc9/3b+Gqj6zklUfX8tzvVyMNyeUfXMZVd63siX4Z7CX0ZLtZfvX8Pqn8w8ViN+PyJA/3E0Lg9NhxeuwYhmTT67v4zTceo/5YPE7bYjNhd1kJh6K0Nnay5uktHNhSxb3fvZkll5+DovQPT9WEQr4tnYvzZnNt0UIKbOn9okuuLJjLVHcBTxxbz7uN+2kJe5OOXoeEEKhCwW2yMdVdwOX5c1meMxWXZuvXhkvyz2FGWhHP1WzmxZptNIbjUUZRI0bYiKEKpdc58fmhpNvWD8+QdEZDVHpbku7XpWR/Rz1XF51zejgWhAmhTkQKJxgtENPAaEHqjQgZ7TdSv7V0ITeXLhi121f5Wrhn7Z9pCvv67VOEINviTHDW+89ZadQnT8rlogtm8MLLO/j37z5FTo6b5mYfHR0BrrtmPnPO6Z94Eg5HqTra3JPWnwyH3UJujrvf+V5vkOPHW1BUgURSdazviCgzw8Edty4hM9OZNJxwJAghMFlMlM8sYsa55Tz/h7dBwNT5E5g4u3jwC3RROjWfzz3wodFqFYqa2nPWHmnk9997mvpjLZjMGkuvmMPFty4hM99DW1Mnbz2xkXee20rD8RYe/u5T5JdlUTa9ECEECgqzPSWUOrKZ7SlmTnoZeTYPahLRK0UoTHLm8sXpV3NLyRK2t1Wxt6OGUkdWv+9FQfRcRxMKSpLvzaaauLNsBSZFpdSRTZE9A5tqTvg9G1JSF2zjvab9HOis6xMds7W1km9s/xuLsiaxIns6hfZ0lmRNwq5ZAImCQrlzeIvYR/0t1ATbBzxmd1sNgVgYp2nkrg2JRD9JEA0YcPDUG6G4wfHxrr90kF6IbEH6fgGKE2n/aM9oXQiBKgSj6RDxRkME9MQzVqtiIi9F/aDBkJDwc+qmbwc/OGesUbdaTSycX0ZmhhP1JD+4xaLxsQ8vp7gogw2bDuPzhZk8MZcVy6aw4rzJWHplOqqqgsmscux4C1//9pODfnhLF0/ki5+9HK1LZEozqWiawvpNR9ixu3rQEc7ttyzuI1NwOlJ9uJHaykY0TWX6wnKcA4y2RwMpJe88t5Xjh+oRiuDSD5zHR795HXaXrcd1NmNhOek5bv75mzeorWrijcc38rFvXo9QBSZF5Z5JF6F0rXmk8gMQQmASGpNceUx05nJDsURKiXLSN7gydzqF9viiuiIEM9MSd5BW1cyVhfMGfc6wEePVuh08UvUuR3u5XrrxxkKsba5gffNB/nl8I7eXLuOKgrnMHGEGrCEl6xqP4EuQ/NKbw74mKn0tzE4vHPa9uqkPdvIf25/DfJLveSAXUD9E9yqWBiIdabkIISPI6HaEDIEYm3dTSsne9lqCSRaOMyx2CuyjY9R9sTD/s+c1nFp/169JUblnygqmuFOXFjljjXpGuoMvfOay+EjtJKMuhMDltHLjtfO5+vJziOkGZpOKpqn9fhhul5W77lhGxaGGHmnUgSgvze5zjaKCdO6+awV1DR0DnHWCyaOo+zJWvPXkRp74v9dwptn47qP3M6WXu2osiIZj7Nt8BGlIMnLTuPqjK3sMOnT54B0WrrxrJe89v426o83s33KEUCCC3WVFCIEm1LhapqFjMPxY65NjynOsaeRY4z9eAZiGIJl7MkE9wp+OvM3fj64lqA8cZWIgOepv5oH9L3LU38Q9ky7CZRq+3ERz2Meb9fsHfcM7IkHerN/PDE9+0plOqvhiYd5uqBjRNU5GCIG0XoawXgQMPKseCZ3REG/WH0jqlpvoyiFzlNwvUUNnXdORhPusqsZNpfOHdL0z1qgLIXpGy8n2A1gsJgbS8dM0lVUrp7Fq5fBiyW02M9deNfAI7UzD0A30mE4sqqeawDkiYjGdQFeGrivdjifL1a/zFULgTnfgznRSd7SZgDdENNrX7x8xdH598BUOdCaXjxgJqhDcPfFC5mVMGPK5ujR4+vgmHq16r0etEeLRNLM8JZQ7c1CFwrFAM7vajvX42MNGlCePbcChWfnYxFXD6lQMKXm9dh+HOgeXV4hniO7luuK5lDrGJrQyVaQ0QHYQN1NRiFWBmkdcNkoBYUVKPR7PPortNKTkzfr97GirTrhfQbAsZyKWEXTwY8np2apxkmIYBquf2jSg3nn14QakEXcnvP30Jqr21SQ9tmx6AZfctjRpYYrupJ9h0fU7G+wHp2kqjrT4NLqz1U9rYydpJxl2KSUdLV7am+O6KA63LR6r3gsDg4rOOra0Jh71jBRVKNxYnDjTeCCklBzy1vO3oycMugDmpU/gnskXMTOtuMdARKVOpa+RPx5ZzeqGvejSICp1njy2gYWZ5cxPnzAkAyal5LC3iUcrNybMbE3EcX8rf6vcyOdnXDIkyYBRRwaR3p8g1BKkUQ+xQ6BNhvA6UJwIyyVI/TjC/S3ANOjlUrqllOxqq+ahinf6ZfZ2k29P47zsiadl5AuMG/UzDilh85t7eevJjSkdv+3t/Wx7e3/S/UuvmMNFtywhUchtOBjhsV+8Qlrm8KaZy6+ez/xV0wc9zmTRmLloIpve2E17k5dnfvsWd3/7Rlwee49PPeAN8ezDq2mqaUMImLFoIlb72E2/RxOJ5I36XTSGTrjoZqYV841ZN1Bkz+wbGSM0prjy+fL0azGk5K2GuIhpe9TPy7XbmeMpTVmITEpJc9jHz/e9QdUQ/NgGkqePbWdGWj5XF58zYjfM8DFAb0Biii+SyhgYXlCzQIaRRhsYjYxWur4hDba3VvPDXS9yzN+a8BgBXJw/nWJH+qjccywYN+pnGIL46Hre+YMby1Qon1nEyQMOV7oDISAW1Vn30o5hX7uwPCcloy6EYPk181j9z01U7q3hzSc24G33c8ntS8kqSKetoYM3ntjAupd2YOgGxZPzuPDmRYOOlNLNDq4pXIBNHb7x39V+jLXNI/MLB/QI29uO9pges6Jxe9myfga9GyEEHrODD5YtZ2trZY+e+u7243REA2Rakmc5dyOlpDbYwc/2vsaahoqEZk8VAqdmpSOBPo4vFuaBfW9gUlQuKZhx6hNtevx+EoxaUItB73KrKdlgpLaGldqtJP5YhFdq9/DbincSim51U+rI5KbS+e9jRzc440b9DEMoghvvu4jr77lw1K7X2/XSrf3ScLwlXpFoBIOgggmph97ll2Zz97dv5Ndf/wc1hxtZ99IOtry5F7PNRCQUJRKKT4ULynO45z9uonhyfkpG/Y6y5WSMYEHrb1Xvjdio+6NhWnrJ6WaYncxMG1iyVQjBBGcOxfZMOjriRr094qczGhzQqEspCepRNjZX8tuKd9jZVpN0sW92ehE3lcznx3teoTNBVExjyMsPdr7IIW8TN5fOJ8+WhmBwd1o3WRYnH5hwLnatb6e6vukIbzccHPBciYTQCxA7ADKGcF2GjO6G2EHQhr6mkfAeUhLQI+xorebvlZt4r+lwUpcLxMNWPzrpPCY4E3fGw8WiaFyUPy2h2qdJUcmzuROclZxxo36GIYSIl3sbHRdiQvJKs/jUD29LWJ1oKAylRqtQBPNWTuerD97N0w+9yfZ3DtDZ4iPgDaFqCln5HuasmMr191xI+ayiU1b/dTTQpd6nBJ1F1VJaZDMpao94WPw6BtEkscwxQ+eov5WdbdW8XruPzS1H8Q1QXCPdbOe+KStZlFXG/o56/la5MaHxb48G+e3Bd3ijbj8X5U9jSfYEJrty8ZgHV7dMN9u5pWwhmSdJyob12KBGHSRSr48Ld6GA4gAMMFqB4Rv17gip+mAHW1qO8WrtHra1Hh/ws4J4jsJNpfO5qmj2qBf9dmhm7pmygsmukYvowVlm1A3dYPu6QzR1Sb+ejM1u4dxV07AlKYCRCpFQlE1rDuDrSJzyn5WXxtzzJicsxpGI9hYfe7ZU9ik00ZuC0kzKpxec0kUZIQRCFQn97GOJoggmzirmMz/+IPXHmqmraiboD2F3Wskvyya3ODOlrNjTDbNq6mOcO6NBWiN+Mi39o3x6442GaImcGOGbVRM2NXFv3hz289UtT3Ggs2FQ+VyLovHRSeexJLscTSh8ZNJS9nTUsr31eMLjDSk55G3kkLeRvxxZz31TVvKxScsGvMfIURD2O5HRbSB1ZHQXYALzuaQ6fZQynvwU1KO0RwLUBtrZ11HP1tZj7O+opyHYmVSxsjeqULiyaDafmLISa5LPfzQYrff6rDLqum7w3F/XsuHNvQn35xZmMHVuyYiMesAf5pFfvkZVkqpLC1dOZfai8pSN+rGDDfz0K48TDiWOW772Q8son14w7PYCRCMxjh1uHBWRrlOJJzcND/EY8UhUBzF6L/6pxKVZKbJlUOmLV+XpiAR4s2E35c6cpIueRleVpZrAiQW7PKsHjzmxGJsuDdojwUENukmo3FK2gNsnnNvjJ8+3pfHFGZfw9W1PJ10g7CYQi+CLjn15PSEEUlgAE2ilcTEvJHGpXR0w4ounXTSGvBzqbCSoR/BGw7RFAjSGOqkPdtIQ7KQp5KUtEiCkR4fkUbQoGjeUzOP+aatIN9vPiPdv2EZdCFEM/BnIAwzgISnlz4UQGcA/gDKgCrhVynjpEiHE14C7iX8rn5FSvjKi1idASpk0tlrK1CvnDHgPY6B7DPFaUqLHdPQkZe+MBJLAQ6Wt2cuPv/h3mmqTLwCd7mTmpvGdhz5Kfkn/YtbJCOpRdrUfG1HSTnUguVZKqpgVjWXZU1nXXEFMGhhInjq2gVJHFhfnzUYTfZPidGmwpeUIfzjyVo++uYJgadZkHNrw0/fNisbNpfP51NRV2HvNHIQQzMko5uuzr+D7O1+keoCFwlOOsICSBnrXYq7QAA1kFMJvgXkpIHi34RA/2PUiMUPH6NLVHym5VjcfmXQeN5XOw55E8uF0ZCQj9RjwBSnlViGEC9gihHgN+AjwhpTyR0KIrwJfBb4ihJgB3A7MBAqA14UQU6RMMXh2nGEjDQj6wwSSFJc4E7A7w4P6+E8Wu6oPtvHNHf/oF90zFGK9tMeHskjYp11CsCJnOi/WbmNnezy/oD0a4Kf7XuCQt55L8+eQa01DIGiN+HincR+PH1tPQ68QyHJnDpcVzEmqPTMYaSYbH5q4hA+VL8ah9VcXVEQ8oeY7c6/hx7tf5UBn/ftf10fYEM7PgrCB9EN0F2gT40a+p1BGPqChS4PwEEfhybCpJpblTOKjk85jtqcQNYFw3OnMsI26lLIOqOv6f68QYh9QCFwHrOo67E/AauArXdv/LqUMA5VCiEPAImDdcNswzji9UYXaJ3VbQp/szZFiUU14TMOrI5llcfGJyZfw/d1PUtclqtURDfDXynd5vmYrWRY3ihC0hn20RLx9RK+6zy20ZQz5vooQTE/L5xNTVrAidzIm0V8q48SxCouzJvDfC2/iNwfW8Fb9foIDRIOMNUJoYOqS0pUStKndO8bkfk7NwryMYm4qXcB52eXYtTNndN6bUfGpCyHKgHnABiC3y+AjpawTQnQv6RYC63udVt21bZxxRgVNKFxTuICj/maaQh2jOtI0KyorcqYz2Z03rPOFECzImMBXZlzHLw68TKWvAUk8dK8t4qctkjhTtcSexaemXMry7GlDMjCqUCiyp3N10WyuL5lLvi21VHohBOXOLP5jztWszJ3MP6o2sa+9jlAvTXGDeMm+iKETNfQ++8aMMTKuVtVEod3DoqwJXJw/jVmeQhxnqDHvZsRGXQjhBJ4E/p+UsnOADyPRjoS/OyHEvcC9ACUl/Ws2jjNOIoQQLMycyAML7qIzGkxJoC1VTIpKlsU9Ir0PRSgsyZpCni2dfxxdyzuN+2gN+/r5fxUE6RYny7KmclvZUiY68wZ1uygI0sw2TIpKuSuL5TmTWJYzkQJ7cgniZAghcJgsXF00m+U5E9nScowXa3axpuEgQT3KG3X72d1WQ2c0RNiI0RjyJryOKk7WvIxjUTVcCaR9LYo2pq4OBYFVNZFusVPsyGC2p4D5maVMdeeSZXHGVT7PYGPezYiMuhDCRNygPyKlfKprc4MQIr9rlJ4PNHZtrwZ665YWAbWJriulfAh4CGDhwoXvu2tvnDMHRQgyLM6ECUfx8mjJXifRI0nQZ2vXNomRsqzvYO2b4MjmC11a7jvbj3Gws65npJ5udjDZldejD29SkrtLepNpdfDfC27ErllIN9swK6MT+hk1DFrCfprDvp7Imkpfc0ryue3RAK/W7uWi/GlkWZw97bmicBbzM0r7Ha8IKHGkvhDeG01RcJqsKAjMiopFNeHQzKSZbWRZnBTYPZQ6MilxpJNvT+sqIG4a9jrJ6cxIol8E8DCwT0r50167ngXuAn7U9d9nem1/VAjxU+ILpZOB1ARMxsGQBtXBY4T0vindGeYsMs1Z+GJemsONFNpLMCtm/DEftcHq+PQ+6kWZ6Mfi7rtQ6tCcFNiK+tRdTYVIOMqRfXUDVkdyum2UTskbtSShtAwHFuvIYoR9sSa2tz5G1OibPSkQTPdcSZ5tOiG9k13tz5BpKaPcuQIAb6yBzc2PUOo8l4mulSNqA8SNiLmXlrsk/v1CfDQ/HENjVjTKXdkjbhucyEp9s24/fz6yngMd9SnFc59MfbCT/9z1Ek8f286d5Yu5MH8aNtVEttVFtnVwqYOhsDxnEuVLsjCrGlbFhFU1YdVMWBUNs6K976NwhfjsJ9EMxWmyjqrswEhG6suADwG7hBDbu7Z9nbgxf0wIcTdwDLgFQEq5RwjxGLCXeOTM/eORL6kTNaK8Vv8ixwJVQNwX64t1clHO5VyZfz2HfRU8U/s490/6AlmWHOpCtfz9+J+JGTGklDjvacNsRHBqLjQRN46TnEV8oOQuNDG01+D4kUa+fc/vaWvuX+arm8IJ2Xz95x/E7hyd4sBCgMkyMqNuyBj+WAsR40TiWCDWSmu4ikLHXPJs0wkbPva0P0+5c1mPUQ/rXg571+A0ZY2KUe+N6CoCoaQo0jXWSCmpD3byYMUaXqjeRWAQ3ffBiEmDXe01fGfH82xoruS+qedTkMS/H9MN3j1cRZO3//qC3WJm1eQJ2Mwmth+voz0YZGl5CTZT/J0Yi45iNEm32PnhvOuJJMgI1oRCod0zavcaSfTLuyQvlnhRknN+APxguPf8V8asmLip6ANEZTwaIagH+GPlgz0LSAYGESPS4z4ospXwsQmfJKKHqQvV8mLd07RGWpiTOZeFGUtwai7sqgNHCuneJ+PrDBL0D/xj72zzE43q74uSotElO9xNdyEVtymPS/K/1scBc7DzTVY3PIAqBmpn/POpD+5le+uTA97bZcplgnMpgvjIa6z16MUoJmR1y/T+566X2NhcNTp1W7sI6BH+eWw7R/2tfHXW5UxPy+vX7phh8OLuA2yvru+zvdUfwGOzMrcoH6tJ49FNO9hT28Af77q5x6if7pgVjalpw1tkHypnVUbp2YwQCh7zCbnP1kgLMRnDrSUuqdUQquOZ2sfxxbwE9ABZlhxmpp3D/s49HPYfxK46mOKcxjUFNw1ppC6l5Mi+uqQZsN20N3upP95CToHnlE9731mzn3ffjYtwCSG46KIZLF4yCSGUPsY77mZoRxEqVjW5aJJNTSPPNp3OaAN72p8f8N75tpmUORYhhMJ771awft2h0XmoBJgtGjffsoiCgpHLwEopOeJr5ts7nksqFzDieyDZ0nKUb29/lu/MvbafYbdoKl+97Hwi+onRrJTwP6+/w7bjJzK4ja70/9FcCD+bGDfqZyBSSuqCNUSMMPm2wn5GU0qJVbUy030OVtVGujmDXEseFtXKeZnn0xRuwBvrxKkNfboaDkXZueHwoCPQYDDCro2VnLNoYvL53Bhx+HAjb75xQipi8uRcFi+Z1O84Q0ZpDB3Apqbh0vqKKbVGqtjX8TKljnOxaxlcnP9VdDl4zLYiTChdnWRFRT0vvbRzhE+THLvdzMWXzBqxUe/WXf/x7lfYkYJBtygaBXYPxY500s0OFAEdkRA1gTaqA+34BxHH2ttRx3/tfpn/nH9Dn1BLIQQZjr5KhYaUQxqNn7zQfSYxrv0yDELBCJvfqcCTMbwEEgC/L0TAN3Dx3rEkLhca4N3m1eRZCyiwJg7139G+lW3tm3qdByB7FfIFm2qnzFFOtiW1uqlSSo5W1HNggKpLJw6Gjav3cdUdS0jPOv18nXFDdoS64G4KbHNwaH2jLppChwjpnWRYSjke2MJh7zspXVcTFhZl3YXHnLhA9elITBr85cgG1jYdGXDsa1NNLM0u5/qSuczyFOIx2zEpCiCISR1fNMzBzkZeqtnN63X7aIskFr0D2NpyjN8dfJcvz7psVEWymkJeHqncSCBJwejTEbtm5oPli8kZpTWBfymj3tHq51ffeXpEA0fJ6OixDPm+UhLUAzSHG1nd9DrHA1V8oOQj2NTE1dTLnZOwKBZURUMAxwNH2dy2gYtzLsdlirsaTMKMXU29g4tFdV57cjMdramVdKs6UM+GN/dx2S3nnlZhY1JKfLFGNrX8BV3GmO65HEX0NSzlzmUsyb4bq5pGZ7Qek2InagSpCWwnZoRJMxdiURx0RGsI6h2km0vJtk5CExZEkkiG4uIMMoZZRSoRVosJu3344nTQXb6thn8e3TagGFih3cN9U87nsoIZCTMtzUIjw6KxKKuMeZnFXFIwnV/ue4vd7TUJOwoDyYvVuzg/bworcyYjhCCmG12ulxNnSBn3tUspCUWjBCJRdCN5O9siQZ48unXADuV0I8Ns56qi2eNGfbi8HwZ5NPDFvPz16MNUB4+RZvJwa/GdTHPPTFo5x6xYqAwc5pr8G8m0ZLOzfRv7vXtZkLE45ZF5b6SUbHvvIGuG4E6IRmI886d3mXXuBArLst53wx41gnRE6mgKV7C3/UVawpUsyPwAhfY5/dpmUmw4tHibJ7tWMcl1Pnvan6cmsI1zMm5kbvqNmBQ7TaGDrGn4JUIIFmXdhduU37NI2hsh4MabzuXSy2aP6jOZzSOLmokaOk8e3UprkoxWgDJnJt8652rOzSodVEu8O1zzvOx44tMPdr7I+iQzAG8szONVWzg3swy7ZmZ95TEeendTH4kEJFS1ttEZDPO1p1/FpKpUNrfitJ4ZpQzfD/7ljPqZikkxMTd9ISuyL6TEXoZLcw9oJH1RL/s793JB9qW4TWkU2Uu4rfhD2FUHUSM+NRUoqANogXQjpaRyfx1//OnLeNuHNgI6erCeP//sFT717etJy3C8r4a9LrCbN+r/m4gRIM1UwPKcTzHFfSHKID8DIRR0I0ylby12LZM56TfiNMV98IX2uczwXMnaxodoDB7AYy4CEvl2BSaTinWEsfajzTF/K+uakhfqzjA7+PLMyzg3q2xIYmJCCMocmXx11uV8acuTVHQ2JDxua8sxKjobmJNeRJrNyoz8nPj71tLGe4ePsWryBK6aNbXneENCiz/QE9c/Tn/Gjfoo09LQyerntqNqqY2gjh9uQE9h9mBVbSzNXJFyOxShEDZC/OP4n7EoiWPFSx0TuDr/xgGjXwxDcmh3Nb/+3jNU7k+sIT8QUsLaV3djtmh85AtXkJk7cGc0ljhMWZyTfgPp5lJyrFNxaBlJXSUnIzEwZAyBgnLSSDy+MCrRGUgDRcajNkZxptgdzjjcz1NKyfa24zSHE6f5KwhuLJ3HeTkTh6UOKYRgoiubj09ezre2P5uwVFxnNMiG5krmpBcxuzCP2YXxsL+Xdh9gU1U1tyyYxaop5T3H64ZBiz/A7tr6ftcaJ864UR9lKg/U8cA3nkj9BDk6K/a5lnxWZF2ITYv72IvsJVxfcAtBo39R4W6yzDlJDYKUkqA/zNrX9vD3X79BTWXq1ehPRtcN3np2Gy0NndzxbxczfW4pqqaccuOeYS4jI6NsWPfVhIV822y2tf6D3e3Pc0769ZgUGy3hI+zreBmblk62ZWLS86WEF5/fzrYtVSN4gr5MKM/h1tsWYzINzwVjINnZVoOe5P3Lsbm4puicERWdFkKwPGcSMz35bGnpv8AugV1tNUQNHbM6bo5Gg3+5TzH+ex7ZUulgNliOsLbncCiwFVFgK+r526m5OD/n4iFdo7vAiK8jwN5tR3nlsY1sX3uIUHDgSAKHy8o5iyeyec2BpNIBhiHZvu4QVQfrWXnlHC68dh6lk/Ow2EynzLinpFKIglV1Y1JOLqwhmOm5iubwYba3Pc5R/3osiou2yDF0GeXcrA+TYSkb8Nr799exfxiznWR0dAa5+ZZzgeEZ3bAe4/gAlY5mpBVQ7Bi63O/JuE1WlmZPTGjUAWq7wiBHw6i7TBbOz5uC/xRUZxoKIT3K5pajp0TK+F/KqLvT7dxyzyrc6cMPaQz4wzz5u7dpru8Y/OBTyEim4NGITmebn+ojTezceJht7x2k6kD9oMYcwGRWufbDy7j2zvP4/Y9f4o2ntwxYzKK92cezf36Pt5/fzpRzilmwYgrT5paSV5SOw2V7X0bwvXGasri84NuYT4oqEkLg0LK4MO8LHPK+TXVgGxE9QKlzCZNc51Ngn90Tn36mENajtEeSz+Qmu3Mwj0KhWiEEU9w5mIRKNIEyiDcaIqBHST/pHFVREuoSKUJ0KUD235dvS+M7c64l1Tqmp4r6YCd3r/3zKakqdWa9hSPEZrew4opzyC0a/uijvcXHK49tPO2MejK6XTuGIYlFdcKhKP7OIO0tPhpr2jh6qIHKA3VUH2miub6DUCD1+F7NpHLZLYu48WMrcbis3PX5y/D7Qqx/fc+gVYo6Wv1sWr2fzWsO4HRZyS5Ip7g8m7IpeRSVZ5OV7yEt3YHdZcViNaGZ1J66r0M1+nIILi4FrWexM35u3/OsahqzPNcyw3MlUhooQkOQWkc0oTyb7OzkmatDZdKkXJQRSNXGpEE0gRZJN+nmxOGyw8FlsqEpClG9//2iUid6kib7nKJ8fnjdpUzP7ytSpgjBnYvm0hEKkWbrH84phEA7jcJnu4l3UKeGfymj/q9IZ5ufZ/+ylvrjrbS3+Oho9eNt9+P3hggFI0lrow6GxWbiytuX8IH7L8LhssazAXPcfPLfr8NqM7HmxZ3EooPrtUlD4u0I4u0IcmRfLW+/sANVU7DazNhdVlxuGy6PHXe6g0mzCrn+ruWYhyjs9e67FdTXtw/rORNhs5m54caFZA0hqUoIuP76BaMa0qgoIuUC5wnbNIg+50AGf6h01w5N3o6+LclPc5Gf1v/zFUIwtzh/1Np1NjJu1M9yOtsCvPT39QMqKg6VrLw0br5nFZfdfG4fwS4hBJm5bu779+soKM3iub+uTTlRqTd6zMDvDeH3hmiqbe/Z3lzfwVUfWDqoUde0voZuz+5q9uyuHnI7kuFOs3HhRTOHZNQhboDN5tPnJ2dSVGxa8njv6kAbEjlkaeaT6VZ+TNZJWFUTllHMKv1X5/R5w84SiiZkc9H181MOaaw71sJrT24mFjv9VYjNFo25503mtk9cwNS5JQlHiUIIXGl2br3vAqbNLeGxB1ezd2tVSqP20aKoKANNU8+Iz/T9xKqayEpQTKSbve11dEZDeEbohtGlwdbWY0lVH9PNdhwDdC6JiBl6n0VHu2o+4wpEjxXjRn2UySvO4Ma7V6bsItix7hBvPrP1tDZAZovGpJmFXHH7EpZcNKPH3TIQJpPG/OVTmDSzkHdf3sXLj2+k6kD9KTHu555bzm23L2bXruPEBnAvRSIxqiqbeo5xOCyUlGQiBins4XRYhpxEJKVk86ZKfKOoG6SZVFaunEbmMKUHzIrKJHcObzdUJNx/yNvI5pajXJQ3tPqovZFSUulrYcMACU4TnFnY1aEZ9a2tR/nF/tfQpYFVNfGlmVcyI61gWG082xg36uMkRAhwpzuYNreEVVfPZd6yybjTh5YRKoQgLcPJlR9YwtKLZ7JpzQHefn47B3dV4/MGxyxAwemyctdHVhCJxAZcIK2tbefrX32Mlpa4a2rKlDy++a3rB029F0JgsQz+0zm56tPq1ftYvXpfCk+QGna7malT84dt1AHmZxTzV0UjnKB4dFCP8pfD6zknvYjsXuXohkJIj/Fo5QbqgokDC1ShsDCrdEjJTVJKKjrr2d1ejSReZOKor5np7vz3XYridGDcqI/Tg6appGU4KJmcy9ylk5h73iRKJuaOOJa8exH10psWsuLy2VQeqGfbexXsXH+Y40ea8LYHRjnTUqCqAptt4NGf1dr3uVRVwWYzp2SwUyEvz4OqKqP6bKOJEIKZngImOLPY35k4Q3Nb63F+c+BtPjfjYpyaZUjvQcSI8eSxLTx/fFfS/rvAlsaCjNIhXTegR1jffLjnmjFpsK7pEBflzRhSrHu8wzeQDDR7FF3RTWpXrdoYvUcjoitHwJBRFGFCoiPQUs5UHgvGjfq/IEIINJOK1W4mLcNBbmE6ZVPymHJOMWVT8sgu8GC19VfiG4372p1WZswvZca8Um782Eoaqts4sr+Oip3HOXqwnsbadrztAULBSNwldXqFG6eMEIJFi8u59LLZ7N1TPaAbaLjYbOYRL7xmWpxcXjiTCm9DwugUXRo8dWwbAJ+auopMy+Czte4ap49VbebBijVJS+IJ4OL86RQMoZSbLg1eq9vDlpaqPtvfbjjAhXmHWJk7dUij/lrv32kNrkm6XwAF7g+SYVuJLgNUtf2MYOyE5nyO40osWgH13ifIc91IvfcpSj2fxmZ6/6SXx436WY7FamLWueXoMR2Xx056lousvDSy8tLIzE0jPcuJM82OuWt0eiqmr0IIEGB3WpkwLZ+yqXlccO08wqEI3vYgbc1emus7aK5rp7mhk/ZmL96OIDmFnhGF8J1q0tMdfOazl+LzhQaN2x8OQgjc7pMzX4eGIgRXFc3mldq97OtInO0aNXSeOLqV4/427p68jLkZxVgULWFxFl0aHPY28efD63m5dk9CvZduSp2Z3Fg6DzWFd05KiT8W5uXaXfy64q2ejsKmmgjqUdqjAX6890VCRpSVOVOxqanNLq1aAS7zzIT7dBmgwfdPMmIXdLUhSnt4EybFQ5plAQBmNYeo3kpnZAcZ+krawxspkqMXaTYcRmzUhRAqsBmokVJeLYTIAP4BlAFVwK1SyrauY78G3A3owGeklK+M9P7jDExWfhpf+O/bemKauxcBu1/4eO2M3vrVckiGPV6FqYO2cOrqjfEiwXEfrS4NjvpaCXYXNbABxSqe4gw8ZDCReCy7rsc1tQ+HmylQPaRbRi8xZqwQQmA2a2RkjJ6G+liQb0vjnsnL+Y8dz9EZTbyQq0uDtU2H2dtRy+KsCZyfO4VJ7hzcJisCgT8W5qi/lbWNh3m38RD1wY4BJ1l21czdk5ZR5uwvydy9DhKTBiE9QlPIy672Gl6t3cXm1qqejmJGWgG3lS3m4UNrOOZvoTrQxnd3PsOSrIlcnD+TGWkFZFqcWFVTVwZq30GLEIJM+wVk2i9I2MZwrInW4Nt9tgkg3XoeJZ5P9LhjmgOvDfwBn2JGY6T+WWAf0J0q91XgDSnlj4QQX+36+ytCiBnA7cBMoAB4XQgxRcoEecPjpEQgGqXR50uoRSMEZDscOMxmoiJKRzBMht2GrVc8sCElla1trKmsorqjg1ynk/PLy5iUmdkTHuYLR/CGw6TbbVi1/q+LBP54aD3PHNuRcrs/Omkpn5gaV5wMxCJ8d8eL7GtPTRNFIPjmnCu4unh0dcn/lRFCcEHeVI74mvltxTsJF027aY8EeaV2L6/X7cehmeNRK0IQ1qP4YuGUEpZMisrtE87liqLZCV0lIT3KXyrXcqCjjoZQJ/XBDtoifmJdcrsmobI4eyKfmXYJk105FNo8/Gzfq+zrqMUfC/NG/V7ebjhAhsVBrtVNttXFLE8RH5pwXh+fu5QGMcOb1KceM9qRUseQYWQCqV9deqls+ymd4Z1wGpmxERl1IUQRcBXwA+DzXZuvA1Z1/f+fgNXAV7q2/11KGQYqhRCHgEXAupG04V+ZHbV1fO2VV/sU6u1GEwrfu/Rizi+fwMsVB3lwwya+c8mFnFdaCsRHQ+uPHee7b7yJPxIh3+3m5YqD/GPnLr5x4SouKJ+AEIKXDlTwu82b+c7FF7GkpL+fUABLsifgNiWW9+3NEW8zr9TsJdTLaJgVjSsLZzIvo4iXqvfQHPZxfclcPOYTboUtLcfY2FzFZQUzmOjKYqIraxif1jgDYVY1PjxxCcFYhL8e2TCgYYf4yL0zGko6sk96H0Xl5tIF3DN5OVYlsfkJGzFeq91Dhbfv4q1VNTHJlcO1RfO4tGAWHpMdIQQLMyfwkwW38c/jW3mldhc1gTZiUqcx1EljqBOA1rCf28sWY+5l8mJGOwda/p1QLHFimpQxwnoDrYHV5Dlu6LdfoGE3TSKqt+GLjF5U00gZ6Uj9AeDLQO/UulwpZR2AlLJOCNFd0bcQWN/ruOqubf0QQtwL3AtQUlIywiaevRSlpfHh+fPQDcnOujperjjIJZMnMa+gAEVAaboHAF8kQk1nJ8HoiR+qLxLhNxs2EtUNfnb1VUzLzmJvYxNfffkVHtywkfkF+XhsNrzhMMfbOwhGk/tG52cWMzVt8GpKaxsP81pt35ffpKhckD8FfyzC1pbj+GMRLi2YTqHD03NMSI+yufkoS7InsCx34qhqkoxzArtm5hNTV+IyWfnDobV0RJOLfQ0Ht8nKh8qX8KGJSwaNpLGoGm6TFZdmI8+WxvS0AhZnlTPLU0i62dHPjVJgT+e+KRdwffF8trUeZWNLJYc6G2gKewnEwpi7yjr2RhF2Cpy3EZM+BlJu1RQXimJFN/q6GFXFTqH7TsxqNr7ogeF8JGPCsI26EOJqoFFKuUUIsSqVUxJsS+h2k1I+BDwEsHDhwjM0/mHsKfak8bGFC5BS8tdtO3i54iDnFhXxkQXzBvWLd4bixnp2Xi5z8/PQVJV5BfnMyMlhW20d7aEQHtvgi3AS+P3BtbxwfPegx4b0aM8UuptALMK3tz3P/o4GWsN+olLnS5ufQusVEuaNhYlJg5/vfZPfVrzLF2ZdzOWF/Re3Ghs7eWfNgZQTuTo6ggR7KVHW13fw5BMbU16MdafZuGDVdKwnhU42N3lZs2Y/0VOURetyWVl1wQzs9pGVeBMI7KqZj0w6j3JXFr85sIb9HfVJM0FTRRGCae487p2ygvNzp2BSBq625dAsfGXmVahC4DE7SDPbsKnmfj7xk1GFQqE9nQKbhysKzsEXC9MeDdARCaAKBYvSN2FMERZiRidRo4N8122DqmzqBABBR3gTxzvioYwmJYP4suLAWFUTK/Om0BLqv4jqNFlwaYPPdFNlJCP1ZcC1QogrASvgFkL8FWgQQuR3jdLzgcau46uB3vP3IqB2BPcfpxctgQASaA2ktmDpspgpcLuoaG6mormFiZkZHGxuoaK5mTyXE7cltYLGAihzZrEou2zQY+sCHWxsPtpnmyoUZnoKSOvlbpHEy5zVBTo4L2ciGb0WRQWC7CSp7bU1bTz8u7cJh4enWV1d3crDv3t78AO7KCnNZPHiif2Men19B79/eE2fDmMsKSxK59xFE0ds1CFuNE1C5cK8aUxLy+efx7bxQvUuqgNtSQW5kqEKhSJ7OlcVzeaGkrnk29JSWoQ3KSqz04sGPS4ZQghUIUgz2+LvlSMz6bHt4Y2EY7Xku25mMHOoCBvptuV4w7toDb4DgFUrwm2ZN2ibPCYbX5l1WeL1LxhWZalkDNuoSym/BnwNoGuk/kUp5Z1CiB8DdwE/6vrvM12nPAs8KoT4KfGF0snAxmG3fDht7v53FCoNnU7EDIOqtrhOc1V7OzHDwKQmHz0YUnK0vYNpOdn8bftO/u3Z55mQkc6R1lbqOr3cPHsW+xqbmF+YWtr19SVzuL7knEGPe6PuQMJCCdeVnNNnLGhIyf/seZ3WsJ+bSucx3ZPX53irqmFIOao/hHH6IoSgwJbGJ6eezzVF5/Bu4yHWNBzksLeJtrCfsKEjTxrBCwQWVSPDbGeyO5eVuZNZlhMvQK0w/LJ7Y4sgorfQEng7yUhd4DBPwaoVoggzZZ7P0ju2QwhBS+Ctwe8iBCpiZPV5UmQs4tR/BDwmhLgbOAbcAiCl3COEeAzYC8SA+0915Iu3PcCff/YKNkdqo9BEREJRWhpOLy31Jn+AvY1NABxoaqLJ76fAnVy325CSv27bzisVB1GEoMHno7qjA11KLJrKc/v2s6Wmlt/edP2g926PBHmpZjfB2OCj40PeJgwke9vraAx5ybW52dFazbe3P98vaqI9EiCkR/nejhf7lVObl1HEDxZch/UkZT+L1URRUTrh8MCLfCMlHIkSCEWx2Mx0+kKIk9w1UkBhYTqhUJRgOEokEsNuM2NKIPKmGwbBUBRdN7BaTJjNah9VRENK/IF4FR+H3dLTkcV0HV8gjJRgtZvx+kNoZhUEOO0WDEPi9YWwWU2YzRr+QASzWcVmORG/HY3FrzGYd8WNjSsyZ3NJ5gyCaoSaQDu1gXaaw36C3fHiigmrYSLfmsbUrDzyHO4+sey6buALhFAUBac9eWKbISVvN+ynyj/88onJmOrOY2nWpD73dpgm0hHaSFX7zxOeIxCUeu7HqhXG68FiAtH3vdMUN3ZtAppwYtNKUcTw7ctoMCpGXUq5mniUC1LKFuCiJMf9gHikzNggBva5Bf1h3np225jdHkajXN7Q0A2DVyoOUtvZydz8fA40N/FyxUE+PH8eWhLVOlUI7l64gOtmTAfiP6SHNm5ib0MjX7/gfLIc8cpQVk0jnCCypjdtkQB/PLielkhfid2IHiMmDSyK1kc9z6qa2N9eT12wk1ybG4/FxrlZpehDqA5f7soiUcmBSZNy+M//um3YMzHDkFRUNsYN3UlYzBrTynMxmVReeWcff31mI9WRAF//2XMnabwIPnjtQn74o1vjax3PbOKNdQe44/blLJlbduIwCUeON/PMG7vYd7ieWCSGLcPJBUumcMGSKdi6BMPaO4P8529eBSRfu+8yPF3JRhWVjfz4t68TCkepiYb45s+fR1EEFrOJL91zMb5AmAf+8CZXnj+TGZPz+cWfVnPBkinced25PU3Yf7ien/7hLaLR1DrBqeW5fOnjF1Oa09+d0doR4D9/8wobA8f5yr35WN19DV9dUyc/evBVsjOc/NuHzsdhN2M29U9gMqTBCzU7eK1uT0ptGgo3lSxkSdakPm9OnvNWsuyXk7xnE2jKwBLLadaFOM0zUBUbTsssNCVttJo8LM6qjFJFiH7+zVON1W5BUU+NUW8NBHjhQAUPbdzErNxcvnHhKr735ls8tGETAsHV06aS5egfKSKEYFJWJt7aMO3BEIuKi8h2ODBrKvMKCjjW3s6v12/EkJIG38DZcfm2NP5n0U39RtqPHNnEa7X7+NzMC5md3jfISRUKE13xijaTXTncWb6IiBFjsjsXywBuo15PkLDbNJm0EYlb+YNh/vbSFvYe6q+DUpCbxgPfuImsDBeaRaMjEKakIJ3CXM/JTSPNZSMz0xlPTlGg3RfEYjP16K9LGe88fvnoGo7VtVFelInLaaWquoU/PrMBXzjK3bcswWI2gSLwhyNIIM1jJ6srkckbDDNzWgHhrpqwEjhY1Uh1fTubdh4lGIpytKaVts4g/mCEw8eamTWlrzstEIpSebwFt9PKlAnZg+qmZ3qSSwR0eoPsP9xAIBihuc1HaWHf6mKRaIzK4y3sP9JAdX07c6YV8okPLE84e1GFgmmQxUeJ7LPoriUpb3fydXsT971bUZWRLVIqwozSpTJpVt/fUTqcbUZdVcgvTb4ociooLMs6ZansL1cc5L9Wr2FKViZfu2Als3Jz+NKK5Xz79Tf48Zp3iOg69y5amPBcQ0r+snU7O+vq+eOtN+Ewm/BYrShCYDOZyHXFjVIwGqXJn7zQhU0z9TPaUkper92PgmCiK4f5mcnDUsNGjJ/seZ2GYCcPnnfHkHRARhuTpnLBkinMmJRHVXUra7cdYfrEPOZOL8LjtmGz9B0wXLpsOh+6YVG/66iDSPeGIzH++swmqmpaufnyuXzo+kXYrWb2H2ngvx58jadf28H8mUUsnlOW9BpZGU5uunwuepf8gDQkjzy7iY07j/Lbx94DSc++wZg7vZCvf/KyQd9bIUioWS6lZP+RBjp9QWK6we6KOubNKO6nUtlznQHuoQqFj0xczlWFcwZsS22wnV/ufw1fLEy2xcVnp19CmmngUNd8W9qYzKFbfQE6QoPH62uKQp7b1dOR6YZBQ4ePsN5/piQQZLkcOC1morpOk9ePzWTCYx9c9vqsMuoA5yyeyLN/fg+/d/R0q1PF6bYxb9nkU7YgVOh289llS7l8yhSK0twIIVhQVMj/XnsNL1VUUOIZeBpoSIneteB43+JF+OdFyXM5Kfak9SySvnHoMM/s3UemfWxiwyXxUEd/LBL/N4Uq8BZVQxuFgsgnYzZp3Hx5PJLh1Xf3s257JQtmlnDfHcsTfqeKItDUoRfKbmj2svNADfnZbm65fD7p7ngSzZxphVx78Wz+7y9rWLv1CIvOKUt6jarqVv79gecJhk6sZUSiOiZN5Y5rFhIKR3n85dRcjUeOt/Dnf25kMGHBaeV5LF9Q3meblJLK6haeeHkbhgRNVXnx7d3Mm1HErCn5/Wqo5me7uef2ZWRnOBN2EEIIpqcVMH0QD8bBzgZMigaEsaomFmdOJMc2evVfh8KjG3bw+OZdgx6X6bTzwO1XU5LpAcAfjvCtZ17jYENLv2NVIfj61Rdw8YxJVLd18KXHXmJJeTGfv2zFoB3TWWXUhRBMm1vC+VfP5ZXHNw67/uZw0EwqF9+wgKlzTl2y1IoJZaycUNbHqChCUJ6ZwaeWLE4pujii6xxoaia7y49+oKnvAlWu08nd5y6gMG1sfjDd4VwtYR9f3fL0oNXrVaFw/7TzWZpTPuBxpxMSaO8MUNfUQUaanbbOAL5AmLKiTDI89p7vTwjB5NIcTCaVuqbOASV7ja4F1vzsNC5fOb3HeGqqwqrFkzlQ2cCTr25PqX3H6lp58pXBO4Arzp/JsvnldL9u9c2dvLJmL6++t5/jdW1csXIGGR47j72wle/88kUuXDqVK86fQXnxiQzgqppWvvWz51k0p4xvfupylDHonE81i8qLcFqSu30NJC/sOECzz49unPhODSlp8wexm03cuGAWpq7vcH99Ey/tOkC4a60jphvUd3hpC4TiL9MgVv2sMuoQj4D48OcuIys3jXde3klzfQeRcIyEAaIjRcT9uFn5aay6Zh5X3r64R+3wVDBQSF98pT45AnBbLbQFg3zxxZcHvJYi4N8vupBrp09LuW3pFjsljvQ+WjOJsKgaF+VPQ0r6hcglbsvpGhqXHMOQ/P6JdTzx8ja++onLMGkKiiKIRGJ9DLeUknAkimFIzJrKgI/Z9f0GwxGq69v7fCaaqpCZ7ki5fQtnlXDPbcsGDRFNc9v6tGl3RS2/f2I9bpeVD1y9kA9cvRCzWcXttPHES9v42/ObSXNZ+xj1jDQ7Fy6ZwsTS7KTumdFGSpkwxr77N9Id5nzyuyWlJKzrNAf8GFKSabdj1/qrPy6aUMyiCcmldnXDYF9tI82+xG7M/DQXdy6di80U/628vKuCl3cnrkaVCmedURdCkJbu4Lb7LuDy2xbR0tBBwBdGjoH0KUJgs5vJyk/Dk+FEOU1lYefk5/OpJYuZkJHes00Rgo+fu5BFRUXog3R4ApiTlzfgMSdz+4SFXFt8zqD1LRUEd5Yv4pay+SnNLAQMOpo/3RACyouzKCnIIM1pxeW0kJPh4mhNKxVVjcydXoQQgkhU590tR9B1g6nluQP6uDM9dsqLs2ho8bJ2W2WffbGYzrIF5V1GavD2mU0a6W77oGsBJlPfz70kP4NP3bmSudMLKS/O6nFF3XblfJbMLWPrnuNMKIqvcTlsFpYvLCfT4+CuG5dgOYUFuA+3tfK7bVuInOS7npGdw0fmzOeNysPsamzg/oWLewyrlJKDrS38avNGdjc1IKVkQno6n5h/LgvyC0/rHImzzqh3o6gK6Vku0odU8f3sZG5+HnPz+xplIQRl6emUpacnOWv4CCFwmay4UhD56s7+syvvb9TSWKIIwXUXn8PF501DiPi0+7IV03n48XX871/e5o5rzyUzzcG67ZW89u5+SgszOH/x5AGvWZDj4YdfvLaPT70bq8VETNf58j2XMKErsua+O5YzqTS7z3GaGp8xbNp1lH/77uODdgDTJubx9fsuxdpVf3dyWTZ52W7qGjto6wiQ3RWZo6oK5cVZPQYdwOO2csOlczGbVDTt1A5+VEWh1tvJnqZGLi6fyNGOdg62tDArJxcBHGxt4Z1jVdw7fyE24s/WFgrxvXdW449G+PySZVhVjUd27+Bbq9/k11deQ5kn8e8mGInS6PXhsdtIs6UWVeMLR9hb04i5awH1WGv7iIrDnLFGXcoYSB9gAmEf0pRcSgnSDzLBYqriBGmA7ADFE99mtINwI5TUp7TvJ1JK2lt8+DpHV5DpdMLmsJCZ435fXTHBcJS2jkByH6eEUFcilBCix92gCsENl8yhrSPAS2v28r3/famn7N2Eokw++cGVFOenD/hsQsD2fTVs2d0/Q7c3uypOKHFkpfcN9ywvzuLGy+bQ2OxN4WmhtKBvm4QQbNt7nB89+BrXXTybu25YkrRjOF7Xzrd//gKFuWl8//PXYLeeuk68yOVmWXEpjQE/98xbyBtVR2gPhVhZUkZbKEgggVhdVXsb+5qb+P4FF3NZ+SQAsux2Pv78P9nV2JDUqO+uaeCbT73Kx1Ys5LZFA2dZa4qCw2Jmx/F67v/rMz3vUUw3UBUFu3loxc17rjuss04HYgfQO7+DMC9FcX6WoSX8SGTgDxihF07arqA4PgVCxfD+HMX9TcDA6Pw+ivPTCNu1o9f+MURKePqP7/LaU5vf76aMGYsvmM7937kBLUGc81ijqfHUp+ff3MW7mw8PeGxLe2I/qtNh4b47lnPBkikcqGwgFI6Rl+3mnKkF5GS6UuqsqqqbeW/rkUGPC4djeP0hTJrKxedN7dnucdv41B0rU0/WEv3XcaIxHa8/xCvv7GN3RXJN/FA4Sl1TB+lu26iUKEw32/lA2WICegSP2Y5dS95JHGhp5pmKfTQF/HzhtZfwRiJ0hEN84bWXUIVCvd9H1knRXWZVRRWC1mAAo6twTFsoiCFJWFegm4iu0+j1E4wMnmFtt5j54mUrqGpp77fmZzObWFCWUMR2UM5coy4DENsPagnDekuUDIRaeuJyei3EDnSN4BXQj8XvgQT9OMjURjOnC35viLamM6vNQ8HXGXzf6pfOnV7IpSum4w8MLtgVjsR60vx7I0Q8+/OcaYWcM214P96bL5/HZStmDHrcum2V/OLPq/ts6zbkYpAs7EQkqo6lqeqgo+/BkoOGQqbFyb2TV6V0bGmah28sPz9pdvTepka84XCfMNny9AwumjCR32zZRFV7O1ZN4+XDB5mTm8e8vNQ0kQZDEYJp+dkUZ3iwm01YTMnNsSJEyn78M9eojwiB0GaC6NU7h99Fxo6AkgNGV1if9MZdMWdq9eNxxoTy4iy++anLU1It/MWfVvP0a6lXhUoVIQQetx2Pe/D8gQOVDf22tXUE+NvzWxJKIgzE1PJcrrlwVr+6oovOKeXDNy5Oarar69v55s+eG9K9BmIoHZHNZGLt8WNsqE1cDCOqG5R5PH2+T5um8YWly5iYnsF7x48SkwZXTprCLdNnkZmCJHWqbKys5oHX3uPelYu4dFbidZRct5OvX3UBuWnOlBa+/0WNusQIvYgMPtH1ZwQIgzoBYZqMDDcDMQzvA8QN+ulTqmqcU4PdZqI4L500V//FLiEEqioYzPEjpTxlYXtDJRiOsnnXUVo7Uq8tC/GRvZSzev7ujnh5c90Btu1LbDQBolEdry8Ur5N7ij8SRQhWlJYxKSNxtvlrlYepbG/D6CU74ItG+OOObZxXVMyds+cgkVS1t/Onndu4e+4Ccp3x9YmYbhCKnYiqCUWigCQc0/GF4zM5wzCIGUZXhnYMwzjxXnhDYSrqm2kPJk+WdNusXD57SsrPexYYdQOIIOVAK+oC0BA9KXMCxX4H0rICovswgo+A3oJi/wAo+SfOUbMBCUZj4suOc9aycFYJP//3m7GPUEuoMNfDnOlFcV/yMFBUhbxsNxKGLT+Rkebg3NmllBScWNzLyXTxwy9c2ycZJhVsVnOf0MepE3K5atXM+ILxIEwqzWLFwkmnNJwR4tFGLxw8wPqaauxa/8XHjnCIQpcbgUBKScww8IbDvHL4INl2O/PzChAIar1eXjh0gOunTifdZsOkKGw9WsMv3ljb8zl6QxEius7jm3ey+kB8vUXKeESLLxThxy+t4Xs3XkJRet+U2Zq2DnZW99cc6o3baqEk0zOoG+YMNurxB5OR9Rhtn2LAhVJhRnF+Bkzd/scIMvQCRvhdiB0EoaI4P4mw3YoQapezRUVx3AvSwOj4wtg+yjinHVaLqSd0byRcf8kcrrlwFqYB/KUDkeay8q1PX9Hz/8NhzrRCZn7puj7G2KSp5OeMXE0wL9vNlz5+ccqLreowZBVGipSSRr8fh8nEtVOmJfTtZ9ntWDSVqGHw841r2VZfR623k7/u2sGblfHF6NZQkJZAkG+//SZTMjP5ynkrsJpNFHrcfXR2puVl97t+txF3Wc191FMdFjNmTeWv67fzj007B3yOZZPK+NHNl6EMInp35hp1tQBhXoLUa5FGXEscoxOM2rhfXOmlEifMXS6Wbgxk7CAQRtiuRrFeDaY5iH4fh8IpnyuOAgLIyktjwrT8QY8da3QZxZDJFxRVYRm0jFgicgrST/uvRgiB2aSCSe3KTvQSM4YeZmrpiqQN6f7hewIFxCTxSgbDvYRQsaoelF4Kit2uqNMZRQhK0zzsbWrkkV2J1zemZGZxQVk5Vk1jSkYWNs3EeUX9JT8u7QpvzLDZ0BSV2YW5/PCmy4bcnm7mlxTw37dcgT88+KJ7rtvZT2kyEWeuUVfyUdJ+Bpz4MGToVYzOb6HY70TYP9DrYAGid4y5BcX1TUCC4gaSi/afkQi47q5lXHn74ve7JVR0vsCB9mcT7lOEyvyse8i3zRvydTWTNqIM3vjIUiJlAImBIuxA/9qZutFJIPQOQpiwW1agKAO7USKxKqKxo5jUEsymCX327Wl7jMPeV4bd5vcbh5bL+Xnfwl+v0NbYt1CMxWYmvzyHuiONhHuV8XNnOMktzeon7HUqUYTg0+cu4YOzkys/mlUVu8kUTxSbOn1I1z950XgoOK0WLpw+cdjnJ+KMNepCdBvqE8ZaCgdxA25DKMkzJYVQkNKH4fsZQpuJcNwNvZe9lHQwzQIlLR79YprZd+R/miOEwGa3YLO/v9rOUko0I0A4XJVwv0DF4tJxu05tUpeUEsNoo93/CP7QW0gZxmqeS7rzbkzahD6GPabX09D2TVTFRXHO4ygMbNS9/mdo8f6cDNenyEr7Yp99Ib0db/TMLstroPPcb9/ihd+92Wd72cwiPv+rj/PAp//AsQM1XVsFxVPy+dbfPkNmniel60spickQwVgLvlgDgVgTYb0TXUbi74vqwqHl4DTl49CyUYVl0AGZEAK3xZJy3d2htbMVf6wBf087wwgUTIoDm5aBU8vFoeVgVl0ITo3r6Yw16iNGepHhd0gUPSssK1HN5/aEPKrpD4MYvWrfvbHYzBSVZ8dFxxLgSVHmIByJUd3UPqCyX889zSaKctJQFQUpJc0dftq8g7sF3HYLuRmpJcac3kRp6fwFbb4/oAgrCI1QZAeR6GHyM3+Jpp7sEzWQJA9tDUcP4g08g0QnGFqPlCGkHF7x69MdAcw9fwY2h4V3n9lMJBTlgluXkpHnwZ3h4OI7lvHEz18kPSeNnOIs9qyvIJxC2KQhdXzROqr966n2r6ctUklY70CXka7Pvvv+CoowYVU9pFvKKXEso8ixBIeW0ysQYmyQUmIQoyNyjBr/BmoDm+mIHCOkd6DLcJ92gkARGibFjlPLJcc2mxLHMrKtMzApyYuNjAYjMupCCA/wO2AW8Tf+Y8AB4B9AGVAF3CqlbOs6/mvA3cQ9g5+RUg5rLiplBGKHT/KTA/pRQMb97JGTfGdCA20iop9xloCBlL0/ZA1EL2MqXNC1Mj7aX8bEGQV87+G7k4pIWm2pLdbVtnTwzQdfpM0bIBYzULt0PbrRdQNDSkyqyuTibH5w31W4ukbyT63eyeNvbsekDqwMeMGCyXz+A6tGNN08HYjEjuENPodJKyTX8wMUJY2mjh8QDK8nGN6Ay371kK4XjVXR5n0IKSPIf4Hw1wUXzWLeqhlUH6zH3xnkts9fhdYV0XLxB5ax5qkNlE4vYsbiSezdcHDAa0kpCeotVHS8wKHOl/BGa08yjicdj4Euw12j4wZq/BtJM5cwNe1aJrovxaKMjXSElAZtkUr2tz/NMf+7BGLNDJy/IjFklLDeQVjvoCVcwaHOl8ixzmKa5wYK7eemNMsYDiMdqf8ceFlKebMQwgzYga8Db0gpfySE+CrwVeArQogZwO3ATKAAeF0IMWVYxaeNVvSOL4F+UlysjAE6MvAoevDxvvuUDNT034LW7b/qip6J7sLo/FbP38kQlgsQlouH3NTBMJm1UREdy3Q7+NjVizl4vIlHXt3CpYumsnBa90KP5MV1+6g41sQHL19AWV5Gn7CyUJcE7CdvXEZ+ZnLd9GyP87RWp0sVgYrLfi1mbRJ26wpAxW5ZTjC8npg+9PBVq3keBVkPgZR0Bp6kM/DU6Df6LERKg8bQbrY0P0RDcNewOkSJTnukkk1N/0dtYBPzM+8hwzJp1Ixlt5vlcOcr7Gp7dETus6gRoCawkcbQHspdF3FOxp04tfxRN+zDNupCCDewEvgIgJQyAkSEENcBq7oO+xPxgtRfAa4D/i6lDAOVQohDwCJg3dBv7kSx3x6Pdkn5HFvcV96NkgHaNNCPdblhBjldmzDoMe8n7d4gj725ncZWL9GYwfo9R9lb1ZVJKKG5w08gFOGfq3cxpSSbuVMKe1ThIB7iNndSIROLspLc4fRDSonR5W5ShhAqZ9LKyE77d0CiGy1EY9UEwu+gCCdmUzJ1RImUsQRuFYGUQWKx+vgo0hi4puvZgKEbVO2roeFYM+FAhMo91Uw8p2RIC9dSGlT717O+6ed4ozWDnzBYm4hx3L8WX7SexTmfId82f8TuGCklYaOT7S1/oKLjeWKJBACHQdTwc6DjOdrClSzO/jeyrNNH1bCPZKReDjQBfxBCzAG2AJ8FcqWUdQBSyjohRE7X8YXA+l7nV3dt64cQ4l7gXoCSkv5hRUJxIux3jqDpgJKH6vlFl75LKse/P6WyUsVi1jhvVhmhyAnf/N6qejbvO86li6aS12sEnpk2NFXL0xWfN8Rffvk64VCUuz5zCRnZqc144s8uMIwAjW3/TiD8LrrRjtN2OTZz4kicmN5AQ9tXEKLvYpumFmI1n0ND+9fjbsFhSkoowkSu9RxMytiUDRwNbFoGqrCwbfUe/vdzf6alvh2B4Ht3/pJP/vcHWXJlalFMUkrqg9tZ1/gzfLHkImDDoS1yhPcafsyy3C93GfbhvedSSiKGl81Nv+ZQ58sYI4kFTXwHGkO7eLfhRyzL/TLZ1pmj9psciVHXgPnAv0kpNwghfk7c1ZKMRC1O+AuQUj4EPASwcOHCMRFeEUIB9cwZlQ7Ghj1HeW1T32op7d4gumGw81AtB6tPlKkzaSrTSnM5Z9IJYaJIVOfdnUeoON6U9B6F2WnMnjj608VU8HtDvPncdny9as8GA2HefmkX0WgMh8uKK+2EQTRbNC64as4ghl4ghAkh7ICPYHgrvtDruGzX9ozyVCUdi2k64eg+QpHd/a5gNrWT5riZXM8PkRj4gq/iD7065OczK04W5/wbHnPZkM89lQQ6Izz20xdRVIUvPXQvqqbyp+89yd9/8jwzFk/CYhs4wkRKiTday6amX426Qe/GG61hQ+MvWJX/bTzmCcN6X3UZYWfrI2Nk0E/QFjnC+sYHWJn/76SZSkbltzUSo14NVEspN3T9/QRxo94ghMjvGqXnA429ju9d86kIOLPju04jSvPSWTZ7QkqZfSaTSkYvIajS3HTcTitPvLVjQCW9VfMnMbM8731ZKA34w7z5wg6a6tqJxQw62vxIQ/aUD3zqT+/Fq15lONA0BYfLxvylkwY06kJYyPF8D91oxxt8kdbOn9PS8QA28wJMWvxVVZUs8jN/gW50JLmGGZNaiNUcj4GO6XXDMuoQ9/UPJxHrVNLW0MTxilqu/NgFLL92IQhoONrEo//9LE3VrRRNHjjhzZBR9rT9g+bwgQGPU9BwmHJwmQqxqekowkTUCOCPNdAZqSFsdDLQrKgtcphtLX9gee5XMKvOpMclQkqDKt9b7O94elCDrggTdjULpykfe9dMxpAxQno7/lgDvmgDMTlwZFlz+ADbmh/mvNwvYVFHvr427DdISlkvhDguhJgqpTwAXATs7fr3LuBHXf99puuUZ4FHhRA/Jb5QOhnYOJLGj3OCnAwXB6ubaE8hNHFSURaZafHYcCEEVyydzqKZJRiDlPyzW83v20JpepaTr/3kNvSYzlsv7ORvD77F3CUTueYDS1AUwXN/28DWtQe5+rZFXHjNXFRVSWjQpTSQRLs6LxOqmo6qppOufpRgeB2B0LuEo/t7jLoQAiEs8VA6xY2qZJ0VrqvhoqgKiqoQ9IUwDAMhBAFvCEVRiEV11r2wlZa6dhCCaDjaZ5AhpaQxtIcj3jdIZpAFClnWaUxLu548+7wegy4QSAyiRpDO6HGOdL7BYe+rhPS2pG097l/LUd8aJrmvGNJ31hmtZkfrX4gaibXwIZ4JnW+fzyTXZWTbZmBV01GFuaudEkPGiBhe2sJHqPS+yVHfmq6OKBGSY/53yPPOY1radSNeCxjpsODfgEe6Il+OAB8FFOAxIcTdwDHgFgAp5R4hxGPEjX4MuH9YkS/jJMRi0phemosvmDwmOKYbrNl+GEURfQy4xaxRkDVyHZCxRNNUcvI9RCMxDu6tweGy8ZHPXEJ5lxRCRraLit3V7N9ZzS13r8RiTRwKGtNraGr/PpqaS1baV7tcL/FRu6pkIjEwThpZ+YKv0NzxI1z2G8hO+wYDRUpZTDNw22/Bap49Og9+mpGZ52HK/HLe+Pta7G4bqqby4u/fYtKcUtyZTn71pb/SXNNGc00bBzYfoWhSHuYunXWDGIc6XyKcbNaDykT3JczPvKcr7lyctF/BorrIUqeTaZlCoWMRm5r+j7ZI4kIhugyzv+MZihxLsWmplW00pE5Fxwt0RJJXlLKpmczN/AgTXZckjDkXxLOlNcWCTc0kzzaXUudKNjc/SFskcVEVXUbZ3/40JY5lOEw5CY9JlREZdSnldmBhgl0XJTn+B8APRnLPcRITiekcrmmm3Zd8hd6QBoEENS3PKIToSZrS9RMdk67HpU3FoHI9KqHoHozwRlz2G7Ca5wIQ1Y8Tju5GEQ5Mat/1e8MIENPrMVKItnLaLsNpu5ShVeI6c7DYzdzx5Wv41Zf+yj/+53mQMGFmEXd+/XqyizK5/38+RMjfNbAQ4Mlyk5EbHzD4onXUBrYkvXa+fT4Lsz6JTc0YuJQfAiE0Cu2LMOXaeaf+B3RGE8v+toYP0hDcQanz/JRG6/5YI0d9a0g2k7AobhZlf5oJrgv7aOAkbasQqMLc1bFk8E79D5N2Qh2Ro9QENjHZfeWIZoOntwPvX5BuTZKYjKB3hc+pQuua2iUP2wtHouw6XIfDZmZGWV5Sm1KQlUZxjgetK/ysurGd93ZWplTwAWDhtGImF/dXoTtVaJrCkguns2XtQf7wwCtce8dSFFXwzF/XEQpEWHrhdEwDSLtqajYO6wrafX+hsf2bpDluB1S8gacIRytw2a7EYpqa9PzBGOusxvcbIQQT55Tyzb98mqq91UhDUjajiIx8D0IIpi4oT3ielJLG4J6upJ3+mBUXs9PvGNSgn9yWHOtM5mR8mLWN/4Mu+89SdRnhuH8dJc4VDKaAL6WkKbgHXzTxAq5AYUraNZS5VqVk0E9ua6ZlKguy7mVN/Q+IGP2rkhnEqPavY6LrElQxfMnncaN+mhDPrGunNrib4/7ttEWOETZ8SCmxqA7STIUU2c+h0D4Hp5bZz3ioioKmqXT4QhyqTh7BAvRUtAc41tDGn1/alJK8AELgtFneV6MuhGD5JTNpbfLywj828OOvxZPMHE4rt9y9kguunDOIUdBId91HNHYcf+gdQpGvdW1XsVvOIzPtSwiRWIsmHNlNa+cvUmqnxTwdh/WSlI28IWM0h/YN6CN+PxEopFsmYlHjMhEZeR4yUtRzgXgmaGMoeYJRjnUmObZZQx6hCqFQ4lzOwc4XqQ9uT3hMS7iCiO7Fqg3WXkljaHfSxVG7lsVk9xWoYniSzEIICuznUmBfQJVvdcJjWsOHCOptOJXcYd0D/gWMerJokOHUZUzGSKZK8Yy1MIe977Gj7Z80hY+gJ5CqrWYH+zpeJcNSwmzP1Ux1X4RZORFvnp3u5NM3L6eueXAXQXa6s2ekPndyIf/3xZtTbm9GCuXTxoKAL9QnnHHFZbOYNL2A6qomDENSVJpFYVkW3s4g3s64T9xmN+N02/p8P0IITGoJeRkPEAi9TSgSNzRW80wc1gtRlewE9TdzUISTUHQPoeielNrrtt+Ew5p6BnLE8LK28ScITs+RvqZYubDgB+Raz8HfGSQ4gJvPle7Aarfg7wzQ3uQlpzgTqYVpjxxNek6+fQHaMPWVzIqLIscS6oM7SOQ2CcSaCeptgxp1XUYG9KWnmUtwmvKG1cZuVGEm3z6fKt/bCdsa1NvwxxpxmsaNelKaw0eo6FzdoychEEx0LSfPNm1I1wnpnexsf5awfmJFvMQxj1LHomG3LZ6x5mNj8yPsbn+B6CChTwYxmsNHWNP4G+qD+1mWczf2rumqxaRx2eKhPRPEI1rK8k9/BcrVL+7ksYfXDCm354Kr5/Dhf+tvWIUQaGoWLvuNuOw39tmeCIf1fAqyfo8hk0dDnIxJLYAhGuhEnflpgxGPHAJ47qHXeeXPibOwFVVwz/dvZ+nV89m+eh9/+/GzfPOvn8ZVIAnGWhKeowoz6ZbyYQ+OhBBkWCahClPCzzBmhAjriRdn+xwnQwT11qT7HVrOiNwi3W11mQoGbKs/NrJKa2e9UW+NHGVL6z96iQQJ0swFQzbqYcPP7vYX8cVOuDY0xTwio67LKJtb/s6Otr7xsAIFh5aJU8tCCAVfrBlftLln6qrLCPs7Xwfg/Nz7sainVrr2/SAz182MeaV9jHosprN9/WFiUZ15503CclKlovzigTurVI2IojhwWJcPuc1nK7kl2cxYMinhPkVRSOvSMoqEI3Q0ezH0eChi1Eicva0JKzY1teiUZFgUN6owJzSUBrGUUvxjRjhpGwEsqpuTF6ukNECG6DvaECAsxIP8JGAGwsQ7eTNmxYWSxKhLdEKxthGJB571Rl3Kk33FktMhklJKSXVgB7vbX+hj0G1qGuekX8cU1yocWiYCCOjtHPa+y7a2f+LvWmiSGFR4V1Ngn8XMtKHF4Z6JLFoxlXOX9y2+6/eF+OYn/oSvM8h9X72KzJPj0s/yz+T9YtUtS1h1c/ICLCJBse2YDPcs/J+M0hUIMBJk1z/JGfxd0GVkwNmSKvpnyxr6UcId30HKE5o/QjixuL9BLPQCht6IxfVZwp3/jaKVYXbejypMKAMs2oYTLKIOhbPeqOsy1u/L1uXYpf2miiFj7O98jXAvASiL4mJlzieZ7F6F0qsKj1l1MC/jZjIspbxR/zP8XdNYXUbY1/Eak1wrsQ4xa+5MQyiiX7arUJT4b1UIFEWMqBLSOKkRT8aKF1MOByPoUR2L3YKqDSyoJlCwa1mYjP5FRqxdCUbDJR5k0JrUIKuYMA1SsQriv0ljgAFfovUOIawophnQ5TrVo7uJRbZgkX702GFk7DjIEHp0N/Ro8gsG6mRixsiEw856ox6TYU52xMYShD6daoJ6Ow2hvlotk1zLmexaiZogVVwRKqWOc5nluYoNzX+h+5laI0fxRuuxqomnw2czgvh0X0kwMhxn7IiEIrz95Ebeemwd/s4gk+eVcf2nLqVwYm5Sw+4xl3JJ4X8lDDhQhIpNyxxBiyRNob0YSWYCJtWBNQX3zkCFUJKhqPlY3V/u+Tvs/T+M2CEYoJMa7G0dqSb/WW3UpZREExT6jRrBMSl4MRRCupewfmKaJVApdswbcMSiCJVi+zy2Kk/0+P6iRhB/rI3hBBnuaKzn5cMVSV/jNIuVO2acg8Ns5tmD+zja0c7kjEwuK5/M8wcPcKC1mbI0DzdNnYlpkArnY4HFauLOT15INKbjdA8+Ejud0YSNqWnXppz5eKpRhIbLVIBhSN78xzoe+vrfcKU7cWc6ef3R96g+WM+Xf3cvGbmehOerihmXUpBw30gJ6m3U+Dck3e/U8kbss0+FeJnEBhAORFeRHSkD6LGDXX73FK8zTKXPbs5qow4Q1vvrW4cH0HQ4VUiMPl+eIB4FMFhHE/fHnZgGxlOVhtez729p4jfbNiZ9hYpcbq6eNBWLpvF0xT7WHK/iivIpXFw2kVcqD/LykYMsKyrhuinTMQ2S2JGMoN5CZyRxNmAqTF4UN+ZhGkihIPuQUYSGXcsecrLJUNEUK1PSribdcnrr9nc0e3nh4bconlLA5/7vY2Tme3j5T2t45EfPsOX13Vx8x7JTOliKi2+tpi2cOEsTINd2iiSNpR8jegBFLUIoHgCM2GFC7V9GGu2ozB/7NnDWG3VJSO8ftx3SvUiMQTPMxhKz4sAkbISIt89ApzF0kHLneShJElaklDSFDxHpNfvQhBmrOjKtd0UIpmdm9yvMm213YNXG7hWR6Gxt/h07lD+P2T1GistUyAX538U+IvfA2UNHs5emmlZu+NSllE4vRAjByhsW8fzv3qRyz/A75+EgpaQtcoS9bY8nTRiyKG5KnMsYa9kGKSV6dDdG7ABmx0d76hsrWilm5/2EvT8b0/v35qw26gY6Ab293/aQ3oEhY2M++hoIu+Yh3VKMN9bQs62i800mOJeQZ53Wb7QjpaQ1cpRdbc/1GZm7TDm4R5CoAGBVNb66dCUL8/pqngghMKsqEX3sooXCRicDlKR839GEbcCamf9qmCwaJotGc20bekxH1VTamzsJB8LYXVai4SgVW6sIB8NU7q5OWnt3pHQvjm5ufjCp7gvEk5oyLJPHdPYgpUQadUR8vwbhQrNeSXcnIoQbzbyQSJIs5bHgrDbqMSNCMIFRD+odxGQYjYEF/ccSTViZ4lpFTWBHT6hXR7SON+sf4Lzsj1Jkn9OTYafLCHXBvaxt+gNN4RMqbwKFSc7lo+IvtKgaNtPwIxCSkSgMbJwzl4w8DzOXTGb1E+tJz02jcGIuL/5hNYYhmXv+dDqavfzi//2R+somDMMgpygTzTS6g6fuqkRbm387oC/dqnqY7rlh2JmqqWDoTcRCrxENPokRO4zF/TUULbH+zanirDbqEcNPINbeb3sw1klY94/YbTEShBBMdC2jyreBQ7536V51bw4f5pXaH5Fnm06mZQIKCi2Ro9QF9/RzJeXbZjLTc0VSd81IkFJiyLjXX5dGSsU3TkYIgdOUi4I2ptVjxjl1mK0mbv/iNTTXtPG3Hz+LNMDhtnHL565k6sKJxKIx7vza9QS7JB2yizKGpBGTClEjwPaWP3Ko8+WksyiBwiT35eTYZo/pKF2PbCPc+V8IrQRr2nfRrJcjhPq+5sKc1UbdH2tN6FMPGz78sVbSzANXaRmMmIwQ6bPoKjAp1pTdOhbFybKcjxORQY77t/a8oGHDx1H/Jo76NyU5U5Brncr5uZ/EqY2NuFZIj/GrLRuo7GjDkJL9rQOLhCUj0zIFhyl3VIoLj/P+I4SgdHohX/vjJ9m38TD+zgCl0wqZeE4pJrOGyayx8obhZ1kPRFwnKciO1j8NWpUoxzaLmZ5bx7ySlGqehS3j/1C0qQilv9De+8FZa9SllLRHavosKnYTNYK0R6vJlzNG1Isf6HiTmsDOnr8tipML8j5DurlowPMieoDm8BEMdJCS6e6LMQkrtcFdBAfRqLAoDvJsM5nkWk5YD1AT3IlAkGmZgHUUSmF1EzMM3qs+xtaGkVUcdJrymZ1+B9taHh5QV+NfHSkN/LGG07qcnSI0HFo2itDIzE9n+XXxUgrVB+t44x9rWX7dQpxpYxNlEjfoIba3/Im97U8MmPnpMhWwMOs+7Fr2gOUZRwNFLUBRxyZUc7icvm/QiJE0hPYnDPeTGDQGK5juvoSRrIoH9FYCvQyVVXUTMwZPbGqP1vBi7ff6iIOdm3k78zNu5qD3bWqDu/FFm3uSpFRhxqGlk2udzhT3+XRG61nT+Osel4imWLiq8FsU2ecM+1lOxqQorCqZQFmaB11K1tUcozEw9FBQRahMSbuKDMskagOb8UXrkyaJpIJOlFr/pqSlwdymYrKtM0btx2zTMsbUJ9tN2OhkTf0PBkwff79xmHK5MP97mGUGseiJUfLeDYf46w//ydT5E1C1viNVgcBsNY042zcmQ+xqfWRQg25V01mY9UlyrEOX8R1tVG0yhvCAsKKa56CopZyK4ilnrVEPG37qg/uT7m8IHSBs+Ed1dJsqUhrEjPBJIkOCfNtM8mzTCes+Anp7j2vHpNiwqx6sqguByr7OV4kZoRNx7oZMoHEzMiyqxqcXLokrSeo6n3j56WEZdYiP8HJsM8m2zmCoGXsnEzY6eaX684TDiY16vn0+S3M+P8ojtNG51sBtkqetlno3qmJGYvDWY+t49S8nVBrbmzppb+rkp/c/jMXaV8PF6rBw739+gJKpwxvNSimJygA7W/7CnvbHExbC6MaiuFmY9QlKnStOAzeIgtl5H/HQLjPWtO8SF/Q6zY26EOJzwMeJ/1J3Ea9Ragf+AZQBVcCtUsq2ruO/BtwN6MBnpJSvjOT+yZBS0hKupHUAbeS2yHFawlUUDEOYvxtNWDApJ0ZxFtXVZ9GyKXSY44Gt/cK6fLFGYieNNmqDu9na+kRK920MHeiTuGRInYPet2kMHep3bKF9Fnm26SldtzdCdJkgIVAMY1SMZPxzHtl1BtMbjyvEDKxD8n6hKWM/4j8VSAlGr6Iq7gwn7oy49lAkFKVqbzXpOW4y89MxDGPY/Xg8I9zP9tY/sq/9qQFH6BY1jYWZn2Ci+7LTwoUVf/96d3Cn7rsf9tMLIQqBzwAzpJTBrqLStwMzgDeklD8SQnwV+CrwFSHEjK79M4EC4HUhxJSxKD4t0TnofeekRcy+hA0/h73vkW+bMewkpKnui5ibcUPP3woK7l4i+vXBfbzT+BCpvNUDL4wOjEGMXe3PJ9x3XtbHhmXUz3SklCB9SNklpSqsgA4yCpgQwoo0WhBqFtLwATpCyUEIBSl1pNEWP35QVISSjhhkcTyuo11IvFMbo+DtU8SFty1l5Q3nJnyKjqZO/v2mn3LJncu55t6LEYDFNnQFxp6wxZaHOdDx7IAuO5uawcKsTzLRfclpYdDfb0b6CWiATQgRJT5CrwW+Bqzq2v8nYDXwFeA64O9SyjBQKYQ4BCwC1o2wDX2QUtIcruSw990+2zPMZRgySnuvKIzDvneZ6bmcDHPpsEZ2ds1DprnstBwVDoWIofOX3dt5var/SH+iJ4OrJ6euPT+U0EchRNLjDSlRhMBAdlVnH/p0Ohx4hIj/UUBgsl2GoTegR7ahms/BbL+VUMcPsXm+TyTwFNJox57+U8CKNNoJtH8OI3aUgWcWEkUrxu75OULNGrQ9ObZZOLTsERdBeL/RTCqq1rcTEyL+fYYDYYQiMJlN2J3DG53Gi8d0sqX5IQ52vDBglItdy2JR1qe76oaOG3QYgVGXUtYIIX4CHAOCwKtSyleFELlSyrquY+qEEDldpxQC63tdorprWz+EEPcC9wKUlJQMpU2EDT+bW/7Rp5iFIjTmpl9PSO9kXfMfe0IHO6MNbG19gvNz78cszmxBqOFg10yoQiFmGDx3KPH6w6qSCVwxMfVCzI2hDv5+dC1B/cTIyqyo3FyyhGJ7Ji/UbiMQC3FTyRJUBG817GFjy4mEqiJ7Bsuzp/HEsfXcVLKYl2u3M9tTwvKcoVd1kkYrUgaxOD+Gqk0n7PsVQnFjsl4FUmIY9UgZjh9ntMX9CgJAx9CPI5QMzPYbSGzYJZHgMxix45BiDL7HXMrs9A+yvfWPp73/fCDe+ecmtr65u8+2pVfPZ/Hlc0d8bSklIb2dzc2/4XDnKwMadKeWx+Kcz1DsWPa+ZoefbozE/ZJOfPQ9AWgHHhdC3DnQKQm2JRymSSkfAh4CWLhwYUpDv25Fxi0t/+CI770++/Ks05noWkbECLKv83XaenztkorOt/CYC5mXfmNKglpDIcc6hSVZH0o62e6I1HLQu6afr1AgsKhubKoLEIT0zh69mt4oqExwLiXLMiFpQYgC++yk7VuQV8BN02ZS7U0eRjkjK4ehKNsaSMJGlHCXUW+P+tnZdpRVuTMpsmewo62K1rCPG4oXowrY2X6M1Q17WJQ5EVWoRI0Y3liQdc0VXJQ3i82tR/CYh59iLRQPZtutCGEjzK9RtHJM1kuJRdYPeq6iZqOZzyVxWTpJLLwWXU9coi3h9YTGVM+1ZFqnUBfYgi/WgHEaaPunilX1oCk29m06zOt/ew9Pthspob2xg+zizBEb9e7U/01N/8cR7xsDCtW5TIUsyfl/FNkXnwaLoqPNyGzQSOYrFwOVUsomACHEU8B5QIMQIr9rlJ4PdM81q4HiXucXEXfXjAgp4xVPOqK1bG19nH0dr/WpsGJVXCzIvBWb6olXFfJcw7tND/UcE5NhNrU8SkjvYE769bi0HECMinHPtU0h1zal33YpJf5YC6/X/6RfNRi3KZ+ZaZdT5jwXu5oBQhCMtXHUv4U97S/2cR8Z6PhizSzLvhuPuWjIbc53uvj+youJDRA5owqBMQQXcJ7VwxenX9Pz99bWKio66zAryV+1UkcWX5l5PTbVBAgOeuuAU+B5ljp6ZCuG0Yigl0SCMCGEh2j4XWKR7clPl35UbTIMoWqPKkzk2maTY53Fmelbj79jE2YW84XffJxYVOe/7v7NiK8qpSSgN7Ox6X+p8r41oN5OmqmEpbmfJ982f1QNujhF0SmDfevKCIuPj8SoHwOWCCHsxN0vFwGbAT9wF/Cjrv8+03X8s8CjQoifEl8onQxsHMH9kdKgNriHI773OOJd32XwTnxkqjAxJ+MGSh0LeyIvpqVdTG1wFwe97/QcGzWCbGt9iirfJiY4lzDRtYw86/Qx85Ub6Gxre5Jj/q192ptvm8n5OZ8ixzqZ3h2LU8sky1JOqWMBbzf8iprgiYSnhtABNrY8yoV5n8U0xHhqIQQmVR1UNjcUS300GY+aibdbSkl9qA2zog0y2hYoiD5+86Ae4dGqd6kJjF3CkiRC2P87pBFAM5+QRRXCjS3t+0ijjoF/ggKh5iNE2pDvPRqRQO8nJquJ3JIsYtEYJvPIfNnxQU4jG5p+zjHfuwMa9HTzRJbmfp5c6+xRH6ErQj0leQISfcBZyEj1kkbiU98ghHgC2ErcqbiNuMvECTwmhLibuOG/pev4PV0RMnu7jr9/pJEvuoyxueXvVCUQ9VGExsy0K7rcKidGYRbFydLsj+GPtVIbPOEXlBi0Ro7S2noUf6yV3PypYybN2xY+RkVn39GI25TfZdCnJOxMhFDIskzk/Nz7ean2e7T1aJBLKn3raAhdPqrJR6NB2IixtqmCMmc2mZahl9uLGv1LEY4mQliwur5GNPQc9HKD6NFtRPyPpnRvgcDs+ECXm2acoSKlxBerZ33jAxz3r2WgTjTTMpXzcr5A1hgNuBRhGrBIzWipdUaNwIBuN/MIC8mPqIuVUn4b+PZJm8PER+2Jjv8B8IOR3POkK8ZT7U/CpNg5x3MNCzNvx6z0/YCEEHhMhVyY91nebvgV1YEd/b6ssZRalVJSE9zVU2e0q1VMT7uEbOvAEqFCCLIsE5iRdgVrmx4+SStmM4W2c8bkZRci7qop96ST63AiEBS53EzLzKLE7UHpV2FdEpU6r9btYEfbUT437UqsimlIBtqmmvlw+fn8quLV0X6cXigoWjFCuOhKpQBAygiG0U5vTWApO9Ej21C0CSjqicV7iYIcIH76X4Utr+8i0BkkFAjT3pg4MexkpJR4ozWsa/wZNYGNDGTQs60zOS/nC2Mqo6sJ64C5BLEhVC9KRvesJFnMvUDBqqaP6BnPqhgggUKmpYwFGbcyybUi6cKnEIIMcxmX5H+Zra2Pc6DzjUE1V0YPSXP4SB8DZ1ZsFNvnpZTgI4RCkX0OZsXep2h1a7gKQ8b6zEpGC7Oi8rWlK4noOhZNw6yqfPbc8/jU/MVoioq5Vym79oifba2VrG8+yNrmCq4snMfynGkDhi+2R3y82bC7x+9eF2wjauj9OothIYPo0W0oajzQShot6JFNGNEDkGQtQTMvQLjdCKwoWtyA69Gd+Fvuwmy/FYvjYyefMfJ2nkHYnVZcHkdXEWqBO8NJ5d5qag7HawNY7GayizIGvIaUko7oMdY1/JS6YF83ZF8EebY5LM35PB7zhDENH9YUC1Y1uSstGGtBoiNG9H1LmkMHkg4c45IgIxPpO+PfRgUFi+Ik3VzMRNdyprjPx6UlL4DbjRACp5bF8uyPM8m1nP2db1Ad2IEv2jymIkASSUTvmxQVr17kSvmFtapOTIq1j1GPGAEMdFRG36gLIfBY+4Z8usyJ/X4HvfX85uDr5FrT+NSUS1mVMxOrmnwhcYIjm80th/lb1YmIpbARJWwMXx+mp91KdlfM+Zcx265HqPnEQm/gb7sfZARJ4ntIo5Ng+9dRtcnYPP+FEBpCOFC00q5Eo6En05xNXP3xCwmHIphtJkxWE5/95UeJhE98lpqmkl2UvFJUXGyvirWNP6EhuJOBDHqBfSFLcz6H21Q85vkgqrDgNOVDcHvC/a3hwwRjbThMwze6Ib2j65kTY1HTcGg5Sfenwhlt1BWhMT/jVjTFjMdchFVxDmnxRAiBKswU2GaTZ5tBINZKe6QaRZgGTUcfPgJV6WsUYjKaUE0yGREj2E9mQBXmMVekS4UZaUX8bMGH8Zgd2NTBQ0SvLJzH+bkz+vysD3vr+eHuf46oHUIIzPZb0cwLiWeLZiOEFcPxIUCiR3YR8iUrMSaRshMpfV3G30BRi7Gn/wahuE5ytwhAO+MT0IZCem7f0Wz+hNSNULyC1yHWNfwPjaHdSY8TKBQ5lrAk5//h1PJPyecrUMiyTOUQL5Ooo+mMHKfK9xbTPTcNKy5eSklNYAPtkcqkx6SZS7CNsHTiGW7UVYodc0d8HSEEKhqu/9/eWcfHcV17/HtnZllaacUMFpgZY07sOAxN0jRpkyZt05ThlZnplV/KaVNukzZp0jA5hsTMzLZky2LWrpZ37vtj1wJrV1rJklHfflKv7swO3J05c+fcc37HkEGi4dyekgPuC0GSobeOe0B3U+PeF7WM3dlIKan1HOhTUNtuyOx3kud8YdNM2LRYs/cCk2LoNXI3KBrJZ0VPOIwJpJoSMSgqjsjDYSgoShKKcXrvNjVc+i+c2BzrwS0AlaB/G52tH6C/KBVFzcFs/wJCJA/pGK8kwppMh9lQ/2OafLHF9gQKhQmLmZP+MWxaxnl7YAohyLBMxqwm4Y1SMU0nyN7Wx7Eb8smzDS4+XkpJu/8U+1qf6EfDJvxmcq6qoJe0Ub9UybKMxyDMBCITLxLJgfZXKU6Yg8NYEPMillLSFqhmf9vLvXxyChrZlokXxUi9PwRwb9ECgjKE1s8NkW9N5RtT3k6qKZHPjL8Fa8yHxNBRlEyMlttRlEw00wKk7ITI6EsoSZis9xEK7GOgqGKhJI/gW93lg5SSRu8BNjb8hGbfkZjrCVTGJC5jdvqHsaip5/0NKNlYSKZlCiddb0Zd7g42srHhJ0xPfR9FiUvRhDmOgZhOm7+SzY2/oKVHOcqzsWnp5NuuOudzHjXq5xkhBBnmctLNZdR49na1t/hP8mbDb1ic8WEcxr7+w/DEUg1vNfy2V51SAIcxjzzr1F7f0XWJ0+vD7fNj0jTsVjOq0h377gsEaXd7sZmN2EzhkXAgFKKpw43ZoJFsM3dNbra7vXj8AdISbRg0FX8wiNPjw2oyYjHG/3YghCDX2v8EGoBR1brWy7Ikx739waBoJZjtXwMExq6akmeKBRsw2h4k/uSgi/thejHgCtYOaNAhPFkJgr2tjw/bvjVhYlzS7Sj+JDpaXDF/VaPJQHJaIuVJt1Dr3oFfd0VdzxWsY2PDT6nqXE+Z/UbSzOMxRWSxu5GEpJ/OYCOnOzdyqP1Z2v0n+zlKQXHiNSQZ45dFicUlb9TPRFRI2S0qFG2dM8uhn3UA+tnOcGFWEpnmeBtNvhM9lCQlJzu383LNd5jmeBt51mlYIjPxXt1JtXs3u1qficjr9kywMjLFcSsJWlrXeTi9Pp7etI/Xdh+l1eXGajIyr6yAdy2eTrYjPCG791Qd3/vPKt61eDp3zgtLCdS2OvncX19kZkken75lUVcf/G3tDtYdrOR/77+RogwHuytr+eF/13Lf4uncNmdir3PTZZA69y68+shEEwV1D76QM+byjsBpKpxvxJRNOFeSDAWkmErjuj5CMkCdeyc+PfbxXsokG4twGMfE1ReeYCsdgYETyAO6m+PO4VXkNioJFCYs5sTmRv7581fRo6RI+7wBCsuy+NRP30m2ZQYl9us41PZMzCiVoPRQ6VrD6c5N2I35OIzFJBiy0BQLugziDbbSEaimzV+JO9jUb7IRQJppLOOT7xiW3JhL2qiHdJ0DR2p5a8sxnJ1eJpbnsHReOQm28Ou6lJKWtk7Wbj7K0YoGrBYT82cWM2V8HoaIypyUEo83wNbdlezcfxqfP0h5cQaL5pSS6rCNUNy3oDhhHtMct7O95ckePrZwuOOq+v8jQUvHpqUgEHQGW3AFG/tICiioTEhawTj78i7/XiCk88c3tvHPt3YyPi+D66aNpbKxhac27aWquY1vvmMFjgQLXn+AU01tdLi7iw6EQjoN7S72nqzjv1sPoCCQSHZX1lLf7iQYCl+Ybl+AioYW2t1943aDuo+dzX/sdxLsXOkvj6DGvZ1a944R2/dExztIMZXGtW5Q97Kj+Q80eWP7jy9lpqTcjyN1zMArXiRMmDWG//nxO4n2Brb2uZ3s3XwcqcvIQOk+OvynB4yfD0ovLb6jtPiODvm4rFo6M9M+MGwTwpesUZdSsmv/ab7/q1dwdvowGVVef+sgNfVtvPfu+WiaSktbJz/87ets33uKBJsJry/Aq2v389A9C7hl+RRUVcHjDfD7x9fx4qp9mIwaqqrw+lsHWLv5KJ/9wLXkZCZ1pb6rQusl73kuvlRNMTIz5R0A7Gp9Br/u7lqmyyAdgVo6ArWxvy9MTEi6jnlpD2BQusMNT9Q389zW/YzLy+AH991AVnIibl+An7/wFs9s2c+6Q5XcPLN/xcP9p+upaGjpUv72+AMoQvCn1dtItlk43dxOUI9tWMNp0COXwNU/ckSzUBnkeUmpX8C+GFlGtp+HF12XHN55kuqK6AXUq0800NbkpKWhg9zidKxaGnMzPs6G+h9R59nNSOn0WNQUZqd9mGzrjGEbQF6yRj0U0nlp9T58/iBf+uj15GYm8eu/vckb6w9zy/IpZKXbWb3xCDv2neL+O+ZyzfxyGltc/PIva/jns1uZObmQvOxktu6u5MU39rJkXjl33zITs1Hjra3H+cuTG/nPSzv4yANLUVWBVXOwLOtTvUIJkw3nVnDWoFiYnfouUkxF7Gj+d3cx6n4QCJIiqpLjkq7FcNZEzbHaZlo7vTywtJSs5LCrxWoycMOMcbyw/RC7K2u4aQCjPr+8gA9edxVKZLuPvbGFlXuOseNENQZNxe0LIAej8jXKKBccyamj9ezZeCyWNCzF43LwecL3txCCJEMBCzI/z9bGX1HVuXFAF8pgSTTkMivtgxQmLB5W6eBL1qgHgjqNzU4y0hKZPjGPRJuZh+5ZwOET9ZiMGiFdsv9ILZlpidxw9UQyUhPJy3awYvEEfv/PdVTXtZKXncz+o7UIRXDbiqmUFqYjhODmZVZWbzjM3sM1uD1+EhPMGBQz+bbpAx/YIBBCoAkj5YlLybFMosK1kROujbT4TuINOSPuFokiNIyKlSRjDsW2uZTaF5NsyIkaUuUNBAFJotXUaz9WkwFNVfD4AwMWsjAaNFISLF1G3WzQsFtNfOueFRRlpLDpyEm+8a+Vw9kVo4wyoiiKQkFZFlveOBD1+td1SUaug9zi7sQiIQR2Qx4LMj/PgbanONz+3LDo4CvCQLZlBtNT30u6efywC5NdskbdYFDJz0lh5bpD/PuFHSyaU0pxfirjS7MQQqDrkrddNw2fP4jDbgXC1XTaOjxomoIlUmLL7fajqSpmk6FrxGvQwn+3trsJBIe92l4fwqXO0pmcfAvjk1bQGWymM9iML+RCIjEoFmxaCglaGkalfz9/tiMRg6qy92QdN88cj1FTkVJy8HQDbl+AgrTkLmN9NqqqoKkK6w9VcvB0Q1dMR2unB6vJSLrdRrrdht1iHql5yFFGGTHSspOZffX4qEb9wPZKKg7V9plEFUJgVpOZlvogudY5HGx/mprOrfj0+PRteqKgkWwqZmzSLRQnLsOk2Edkzu6SNeqqIrj7phnUNrTz+LNb+e+ru5hUnsP9d85lQlk2iiKYMr67sJKuS7btOclraw8wZXweYwoi0SJnVrgIjJQQAoMwk2zMJdkYtSjUgEzIy2RyYRav7zlKcaaDuaUFnGxs5U+rtpGeZGPJxNgTWxlJCXzouqs41dTW24UoID81mazkxCEd0yijmNUkihOWDoso1mDRhBmTYufQsXpe+Pt6bAlmxFmVXzydPvJLoic6hZMTDWRappBmHkuz7ygnXW9S696BK1CLX++M4ZoJZ6xbVAcppjIKExaRY5uNVU0bWQ2bEdvyCCOEoCA3ha9+/Ea27z3Fuq3H2LKrkp/+/g2+89lbyc7oTmXWdcm2vSf5+R9WYU8Mu2kSrMOf0HIxkGwz84mbFvLjZ9fy61c28pi2FX8wRJrdyidvWkhZduwLyqSp3DhjHP5gCIsx7K6JSj/Xo6oYGJt0K3m2q4bhbLrx6QG2thyk0JpFvrVv1m+jr40D7ZXMTBlLgmahxd/BnrbjTE0uxW7oK2V6xFmFM+hmpmMs6iBef9PNEwdeKYIqjIxLvh13sCnu71xKZFqmxL1uoiGX+ZmfHcGj6R+Bgs9Tjc/jZ9aScVE14LMK01C12NdC2F1qjhQ5mYgv1IEzWEOH/zTOQA3eUBtB3YcQCkbFhlVLx27MI8mQj1VLH/bKarG4ZI26ruv4/CESbSaWLRjL4jmlPPXyTv7w+Dr2H6npMuq6rrNpZwU/f2wV9gQLn354GeXFGf2qBl7KCCGYXJDFTx64mT2n6mhod2G3mJhUkEV+ahKK0r8Be27bAV7cfojP3raEifmZUdcpzUrls7ctYWpRdp9lqjBSlnTTsJxLT1r9Tv5Q8WtOeRIo9vVV0qvz6hxxJvO2gjsosGWyu+0Ya4//kRqfik3reyNVdBpINxXy7jH39Ss4di5oionypJtHZNuXGuEIsgtbR7SgPItJs8fQVBc9h8JoNsRtE4RQMGvJmLVk0s3j6f7amQ9nEtnOvwvgkjXqdY1OfvGn1SyaW8oNSydiMKgU5qYghMDrDQvQh0I667Ye4xd/XkNGWiKfemgZJZHJ0DOYjRq6lASDIaSUCCEIBkN4fQEMBhU11mj1IkYIQXpSAssmxxdP3ZOGdhcHTtfT6YutEZ6bksQ7Fpz/ghw6ks6Ql1Z/32QeV8Dd64aUEhQEedZ0Uox9HwIt/g4uzXJyowyV0kl5fPaR+2P+7EKAMqT7XfSYY7rwftxL1qibTRp1TR0888ouCnNTsZgNvP7WQYwGlfwcB7qUvLnlKP/3x9UYDSp33jAdCRw/2YgQgqx0O1aLkTGF6fj9QVatP0xKkg2jUWPzzhNU1bQyf+YYrOYrS2ZVAFKXnG5qI8nav7CQw2YhI2nwFY2GikBg12xkmPtKDYSkTo23281hVDQUobCj9WjU+qhtfhfj7IUxJ41HufwQQqBpF/Zt4XxwyRr1ZLuVt103ld/+/S0+//2nUVWFTrePG66eRPmYTEJBnVfWHKCpxYXBoPKTR7tD8IwGlS9/7AZmTy1i/swxbNhezNOv7GTd1mMYjRp1DR2kpSRwx43T0frxsV2O2MwmgrrOj597E03t/wa4Z8FUPnz98PrOY2FVTSxKn8oJVzVVnfVR11mUNpVkYyJSStJMSTxQfAOekC/qugLIs4ysIucoo1wIBjTqQog/AjcDDVLKSZG2FOBfQBFQCdwtI/XAhBBfBN4HhICPSylfjbTPBP4MWICXgE/Ic3BqK4rg+qUTSUtJYOOOCgKBEJPH5bB4Thlmk4auS5bOK+uKcumJqggy0+wAJNstfPr9y1m57hA79p3C5w8ya0oh1y+ZyJiCkZ2lvpDkpibxwNKZTC7M6tV+/fSxpCRY8McRylmW3bdvRwpdSpZmTGNReuzJOUV061SuatjBa7Xddc1D6AT1IAbF0FVRyaaZybKkUmTLirK1UUa5NBED2VUhxGLABfy1h1H/IdAipfyBEOILgENK+XkhxATgcWAOkAOsBMqllCEhxBbgE8Amwkb9ESnlywMd4KxZs+S2bdtiLj8j1hU+rqFPTEgpCQRDSF1iMKhdpbouV3r+7pfCee5qPcqvjj5NIFKrXJc6Pj2ASTGgRKJXBHBf0XVckzGDKncDJ9112DQLqlA43HGKp6rW8FDJLWSaHQCoQmGMLQerdm761bEIBoLUVDYR9Hc/IJNSE0jJsNPW7KKt2UlSSgLJaYkoysX/G4xy8TBr1iy2bdsW9aIZcKQupXxTCFF0VvNtwNLI578Aa4DPR9qfkOEKBBVCiGPAHCFEJWCXUm4EEEL8FbgdGNCoD0TY+J7rViKVcgyXrDdq0FwKhrwnJQm5fHrcvV16IzWeRn537DnuzF9CeWK3XGmWOTxZ7gn5eL56PR8pu4NCWxZSSjLMDibYi8iznlsNyHhpb+7kZ595nJqKRhRVQdd1bn1wMeVTC/j7T1+mub6d5LRE3vmJ65i3YtKAkUmjjBIPQ7VimVLKWgApZa0Q4oxzMpfwSPwMpyNtgcjns9ujIoR4GHgYoKAgPn1hKSVOvw9faGQzQI2qit1o6mUUg7pOu8+LHuWtRxGCZJMZ9awbNqTrtMX4jhBgN5p7FXQeDIFQiHa/lwsVsWk1GLAZ4p9g9oWCeIKxa5LaNCOJBivjDN3XgkkxoCkqBdZMxtsL+3zHE/Jzyl1Pk6+dRIOVDLODD5bejlHRIpEvYBAaCZqlzwMuqOu4Av6Y4W0GRcFmGDjmONFh5YZ3XsVff/wS42cWU3mohpKJufzlRy+SW5zO3R9ezsbX9vLXH79E0bhscorS8YeCdAai94UArAZjn+siLBstGb5onrCAXX/FWqKJefX3nXjpktKObF+c2fI5vIH37Zv+zy/693t++9yOKdZ+zpZIG+p+hntoGm3vsp/2qEgpHwUehbD7JZ4d61Lysx0beLM6dv2/4WBBTiFfnXs1hh43Vm2nk0+vfYlmr7vP+hmWBH6y5AZyEuy92uvdLj699mUaPH2F+I2KxrfmL2N2Vt6QjvFwaxNfXPca7mDssMSR5P7x03lw4oy4119bVcEvdm2K+oAzKApfnLOEudn5fZaFk4aiX/BGRSMkdX5x9D9Ro18AxiUW8NGyOzGqvQt9HG5t4usbVsZ80MzKzOXLc68e8KFrNBkom1LA5HmlTJ5XSkqGHb8viNft475P3UBeSQalk/P42gOPcmzvaXKK0llfc4qfbl+PLvsqO6pC4bOzF7Eot6hXe533JOubnkeXwX6PJ17Mqo2lGXdhN0QvaNIWaOTNxmcI9JiETjPnsjDtVrQhlFSUUuLXvTT5aqj1VtLkq6Yz2IEuQxgUE0mGVDLNBWSZi0gypqGgxG3onMFW1jQ8hbdHsfcUYxaLM96GMY6ycU2+ajY2v0SwRyH0HMsY5qSuGNa4e0+ok7ca/0tnsDuGPtHgYGH6bVjUvslz/TFUo14vhMiOjNKzgYZI+2mg592XB9RE2vOitA8bEqhzOznW1jKcm+3DmKSUPk8jfyhERXsrDZ7OPuu7AwECUWRqA7pOZUcrNZ19Y65Nqoq7n5HrQHiDAY63t9AZuDBGvSXKw63f9X0e9jbVRx39GRSFDn/fCJYMs4OPlN0Rc5JzTEI2Xxh/H95Q7D5IMtpQlb43ZmfAz4GWhpgj5lSLLeoDKBq7NxzFkZ6IEDB3+URcHZ6wHEQko1EzaChqODcCoM3nZV9zfdTtq0Khw9c3zd4ZaGFv2zqCcujXTE8StGSuSr0RYhh1T8jF3rb1eHrUyS2yTWR+6k1A/EZdSklA+jjq3MW2lpWcdh/DE3JFlSpWhUaSIY3yxOnMSllOprmway6lP7whN/vbN+EKtnW15VlKWZB+a1zH6Ay2sqNlNQHZfQ16Qi5mp1w7rCHpAd3L3vb1tPq7I7vSTLnMTb3+vBn154AHgB9E/n22R/s/hRA/JTxRWgZsiUyUOoUQ84DNwLuBXwxx36OMQoJmYV5q35R9Xdfx+4IYDBozU8YOads9J99jLY/H1SF1SX1VM68+sYm07GT83gAr7pkHwDN/WMPiW6az6bW9+DwBisedm4zzpYaUko5AM6sa/s2etnX49f41YUIySIu/jk3NL3O4YzuLM97GdMdSDMrlKfdxLsQT0vg44UnRNCHEaeDrhI35v4UQ7wNOAW8HkFLuF0L8GzgABIGPSCnPOLk/RHdI48sMwyTpheBiL+58uaLrkpbGDgwGDbvDGs78DYRobuggMdmKNVLtqq6qld//8CVuuHsOc5YMzaiHYviMu5frcXmvt7yxnx1vHWbm0vE89JXbePkfGziy+xS3v28pTz+6irde2InJYuSuD15DQVl0SYbLkXC93Waeq36UI87tgy620Rpo4OXav9AZ7GBh+m0YlCsrQXAg4ol+uTfGomUx1v8u8N0o7duASYM6uosQTVEYjT47/wT8QR79wYvkjUnn/o8uB6C5sYMffOYJ3v6+xcxfHh61e9w+Duw8ybxrxg95X0Fdp78aIEFdj0sjxNnuprPDgz3ZSlJKAo70RE4cqOaaO2YxdUEZTbVtpGYmkVOUhnoOmY4JhmTG2+cQGoJPPSSDnOw8hFfv6zocKXy6h5V1/4xq0I2KmUxzAemmPIyKCVewnXrvSZp9db0KyPh1L282/heblsSslOVxuWKGC3nmf1HmPc5lm8PFlRPDN0wkGIyjqeUXACkl7S2dONK65X/1kE5LoxOfd3h8yWcI6KF+jXZA1+PyqS+5dQZHdp9i9TPbaahppfpEA7c+uBizxUjemAzyxgxPRmu2uZi3F3ySoUS/eEOd/Lni29R4TgzLsQyElDp72t5ib/uGPoYs11LC0oy7KLZNxKRaEQh0QjgDrexpW8f6pud7+cb9uoe1Df8hz1pKtrn4vIXp1noqeLb6t+dUzvJs/LqXzuDgNdqjcdkYdQFMTM2IObkVL/5QkF2NtXiC0Uc9aRbrRe+CsZvMLMotjHkO54rT72NPYx3BGCOVvU31/PPQ7ri3t7WumotJXMsXCtKfgyWghwjFYdQNRo3EZBuT5pbgSE9k9tUTWHbX7D5a3udKWO97aCN9BfW8Xs/tgRY2N7/SqywkQJ6ljDvyP0KGKb+XcVbRSDamszD9VlKMmTxX8/teESJtgUY2N7/CLTnvH1LkzVBoCzSyo3X1ednXULhsjLoiBB+YMof3Tz4341DjcnLfy//mtKvvU1MRgvzEvop//SEJPyi8ZxlYXyg4YmasNDmVR64eOcnX3Y11vPe1p3FGiUoBWFV1gtVV8Y/8zrUfQkGdgD/cv8Fg6Jy35w0G+x2J+0Ohfgtv9+TmBxYiAHtK/xWrrgSklBxz7aLBe7pXu1VN5Nqsd/Yx6D1RhMr4pLk0+2tZWfdEL1fM4Y4dXJVaQ5alb77ClchlY9TDVYPOPW60w+/F6Y8eBmdRNYqSHIO6OVu8br647jXMWu9RhDcYGHToX7woQmBSR+6nNSjqgGO78zXullLywhObeevVvQC4XT68ndEfNvHS2U/iEYAvFCKgx5fk1tNddKUTkkGOdOzoU1x9rH0WRbYJA95XqlCZ7riavW0bqPV256O4gq1Udu4n01xwxT844TIy6sOBlJIdDTU4A9GNQoY1gcLE5EFt0xcKsbW+ehiObpRYeDp9XUbY5/HHHUMeDSklzoC/34eSPxSMK3PZ6/axeeV+3M5wuJ7JaqRscj4Hd1QSCoTILkrDYjPhavcwfVH5ZS8T4A45qfdV9WrThJGJSfNQRXymKFFLZpx9Vi+jLpGcch9hdup1Q3ZDDYZkQzolCVOGtWC0X/dyuGMbPt1zztsaNeo9aPa6ef74oZhGYXJaJmmWwSUCXAhcfj/H2pv7FNEdLo60NRGK0/0w0ggheNsDC1i4IhxYVXm0nm999G/ntM32KAk+PfGFQnjjSA7zdPp44a/rOLL7FGlZSaRkJqHfM4/HvvMsCJixaCwZeSlUHatn6vwyLnObTmewHfdZk4EJWhKZ/bhdzkYIhQLrWDRh7OWXb/XXE9B9qKp1WI85GjmWMdya+3DcD6J4aA80UeU+gs8/atSHDX8oxD8P7WFPU13U5QZFZVlBCYZL4M470tbEB1c+i2uEMkp1qY/YJOxQMJkNJNgtAFis51YHUgKtvv5vLF8/+iw9SUpJ4N6Pr+CP33uej/3gbiw2E8117WQVpDJpbgnN9e0gOWeNnmZfLfvaN0SVFhiIgPTTEWg9twOIE0+ok4De+5q0aXYs6uAKrSQaUjAqJoI9soW9ITdB3Q/nwajD8OjcnL294WLUqBMWwPrvsQM8tm9b1JR+gLLkVK7KvjR8dnpEkOpCyQQoQgwq7FOXMm6XydH91Tz5hzeBcBy45xz952cT1HVavf0b9YAeosPf/2gewqXRbHYLmkGlsaaNlU9u5po7ZqNqChbb8GVCNvtqWVX/72GTCRgKIRmgPdCEIdR9XppixKbau+6ZkAz2kQDQhBFlkHNhmjD0GSWHZLCPr/5K5Yo26meUHR8/vIdf795MW4zXboOi8PbySaRbL37Xy8XATcVjua0k/uSft6or+euBnQNOrpqsRo5tr+TksW59DJPZQGLS8I3O/HqIVm//Bjug67QMYPjPkJqZxLV3z0EIwtrqgcvT8NR6Kvhzxbd7jTiLbBO4Pe+DaCKc8akKtU9sd0gGBm2MQzKALnt/RxHqBS9sfbFwRRp1KSUBXWdPYx2/37eV1VUn+p34mpWZx60l44aUdKQJhbzEpD5um4Ae4rSzI2as96XMmCQH1xbGX/Q6rG4p6C9mxmjSeN+nr8ft8vVpzytO7/G3gfwx6V3umMHiCQRoG8D9oktJg9vVVai8P9Kyk7np/oXsePPQkI7nUiEoA7QFGnu1pQZzev2iZtWGphh6qTt2hpx4Q+5BuWCcwbY+WjFm1Xbe5AJ8uocGX9Wg3zD6wxVsG1JGcDSuGKMe1kWGDr+P/U31PHv8IG9UHafJ039YYZY1gU/OuIpU89BGg6kWK/939U3knSW9e9rZwcMr/0u9u6/07ih9URSFwtKB9VFyClL46i/uw2Id2g3e4fdFVYU8m5pOZ0xN6YuBRM1BtqWIoRyhRU3AqAx/NagELQmbZu+l7ugKtNHgrSLZkB63vvkp92ECZyUvpRgzzptRr+w8wJ9OfJPh/PUlOp7Q8Eg1XHZGvVtkH4J6CHcwQLPHQ0VHC9vra9hcW8Xh1qa4JhHtRhOfmrmA2Zl5Q/alq0LgMFn6RM10BgKoF9A/P7J7vnDnpWoqSY6hu8mavW5cMUJae1Lb6SSo6/1qqkspCQZCXf+eTUdLJ6o6MhPvhbbx3Jn/UZQhuiSGFtkhzvqr999W1U6GqYAmX7fqdkD62Ne+kZKEKXFlhDqDrRzq2NpnP/nWsUM+1/5QhBa+93u8coRkkM7Q8KT094cq1CG9DVwWRl1Kye7GOvY01eENBunw+2jxumlwu6hzu2hwd9Lm8wyqKlKyycynZizgbaUT+1QtutS5vqiMZfklI7b9CanDo2nSk1BIp+JwHW5X79fupBQbBSXh/Z0J4VSUoUUmSCmpcXX0yf6NRl2nC3cw0K9Rd7V7+NP3n6Oxto2Olk5CwRCqpmC2mjAYNY7trUJRBPOvnzrsE/ACBU0YhtVF0B9pphzmp93cyzDbDamoPfavCo2x9pkc6tjay49+qGMrU5IXUprQfz+EZJAdLauo85zs1Z6oOShOmDgiQQx2zYFNS8Ifx8T4cJNqzMakDN6NeFkYdYBXTh7lt7s3D0smY2FiMp+etZAbisqHXFLuYmZSaiZ3j518oQ9jUPi8AR77ycsc2lWFRHaV+lpw7UQe/sJNbF59kF2bjgMwbV4J86+diNVmGvSNfry9JS5dl0ZPJ21eD8mm2G4KRRE4MpJACDJyHOSMSWfKvFIKx2ZjSzQz5apShBCk5zhQ1IvVkRMfCZqD6clLMaqx+0MIQVnCVDLNBb2Sh9whJ6/X/YPEvGQyzYVRf7OQDLG/fRMbml6ImpGaZhwZPfokYzrz025iY9NLuEPOc48/jQNFqKSasvs8JOPlsjHqyHMXrzSrGkvyivjY9KuYmJo5qsZ4EWE0atx8zzxmLijj2b9toGRCDrMWlpOSnsg/fvUGrz29HVuiGYlkw8r9HD9Uy4OfXIHZEr+fNajrHG1tjmvddp+X2k4nRUmOmOtYE83c96nr+7Q7MsLzK+k5sb97uWI3pHJV2o08X/2HXtWEqj3HebLqEZZkvI0xCZOxqAkIFEIySEegmd1tb7Gp6aU+bo8UYxbzUm8Y1kSgnigozE29gfH2ObiDzmGVyI2FKjTsBgfWHuGgg+HyMerngFFVmZSaybvGT2VFYSmJhsGP8EYZWTSDyoJrJ+Jsc7P2pT2Mn1rATffMZdtbR1j1/E6W3DiZOx5chJSSpx57k5X/3cHMBWXMWlQe92/Z4fdR0RFfIo4nGOBoWzPzsvvPhtT1gbOLhBCIIbqMLjWEEExKmk+V+yjbWlb2iluv81bydNWvSDPlkGLKxiCMuENOGn2nafM39YlxN6s2rsm8mwxz/BmpQzleFRWHMQOHcfjdiiPBFWvUFSFIMVuYlp7NLWPGsTC3kFSz9Yq4sdaeroipsDhSmDWNe8dNJds2NIGrUFBn95YTmM0GHvyf60hy2Hjz5b288dxOLDYzd713MblFaQDc/f4l7N58gn3bKpm1qDzufVS7OqiLUjM2GpKwxLAuZcwJ784OD//42Ss01/c/qVY4Nou7P7Qcg+nKuB2Nipllme/AG3Kxv30Teg9jHZB+ar2V1Hor+92GWbVxTcbdTE5acF4LZFwKXBlXEeEoFJvBSIbVRrkjjblZ+czJyqM4yYFZ1a4IY36GrfXV511kzG40sbygdMhGPRAI8u/fr6GoPIsPfOEmTh1v4A8/eonWJhfZ+SlYrN1vVxabCaPZgMcTf0atlJL9zfVxhTOe4WBLAx1+Hw5z7MksVVNQNQWfx8/uDUcpnZRHSmZv+WZFUS7e2MgRQAhBgpbMzTkPYTeksqN1da8wx36/iyDNlMPSjLuYlDQfTTk/GuqXEvHUKP0jcDPQIKWcFGn7EXAL4AeOA++RUrZFln0ReB8QAj4upXw10j6T7hqlLwGfkPHUBIuTRKOJvAQ7mqJgVDWsmoEkk5l0i5W8hCSKkhwU2pPJtdlxmC0YFOWyNeSKUIaxJsvFg9QloWCIlkYnL/xzE16Pn3nXjGfHhmNsXnOI5bdPR0rY+MYBWho6KIojrv0MQV1nU+3pQSk8VjnbOelsi2nUbXYL7/3irUigua6dr97/W+54+BpmXd0721bAsBfOaPCeYlX9kyNyjTsDrX00XAaLEAKblsS1We+iLHE621ve4GTnQVyh9j7ZogAGxUSKIZNx9tlMT1lKmjF7WFUSLyfiGan/Gfgl8Nceba8DX5RSBoUQ/wt8Efi8EGICcA8wEcgBVgohyiPFp38DPAxsImzUr2cYi0+/c9xUbi0ZhyoUjKqKUVExqhoGRema8BwpI55sMnP/hGlRddiTTCbsxr46H3ajiXeNn0q7r+/IUFMU8hMGV4yjJwlGI2bNgPMCab+MJFvfPMKBnaeormxixR0zueWd82hucPLnn7/K9vVHkBL2bq2gqDyLWYvj96c3eDrZ3VQ7qGNp9/nYVlfN1LSs6BEbQZ3qigZCQR2Py0copKMoYsghlzGJsq163ynqG04N3z5GgHANBCOlCVMpsk2g1V9PvfcUzb7aLuNuVEzYDWlkmPLIMOeRoDmGXUzrciOewtNvCiGKzmp7rcefm4C7Ip9vA56QUvqACiHEMWCOEKISsEspNwIIIf4K3M4wGXUhBA6zpd/X4JEkxWzhY9OuGtR3kk1mPjJ13ogcT4Y1gQJ7Mo2e81dM+HzR2uyirSWcol9UlklOYRof+eqtPP7bVRzdF3YpTZlTzL0fuob0rPgejFJKttdXU+0cXEKJRLL2dAX3jpuCzdA3yqa9xcWPP/kPWurbUVSF9hYXW1cfoKA8i4zcwRVb6Q+TYkYV2gUV9OqJlBKvP8iRmiaanZ2k222U5aRhMmhICbsrazBqGhPywxOPB083YFBVSrPzwOvA5yxkalYKh6sbKc5M4VhtMwlZqdgNiei6ZHdlLQ3tsd01qYlWpo3JuezyS+JlOHzq7wX+FfmcS9jIn+F0pC0Q+Xx2+2XBUG7OeL8T0nWqnO34gr1fSY2qQr49CW8wSFVHO0VJDiyGsH/RbjRxV9lEDjQ34IlD9/tSYsHyCSy9aSr/+v1a/vOndUyaVUzJ+Gw++4O7aWkKT3KmpCVishji7mNfKMjLlUfwx1nNqCd7m+o53NLE9IzsPvuTusTn8XPTuxdiMhv4169eZ/1Luzm+7zQf+vZdlEzMHRbDnmLMIt2Uy2nPsXPe1nDg8vr5xQvreXPfCawmIx5/gGumlPChG6/CqGn85Y3tpCRaGf+OZUgp+ceanZgMGh+8YR5vHqjgmY37+J9bF/L9J1fz4Ruv4nevbuYD180lyzGWoK7zl1Xb2Hm8hvTkhKhTEZMLs5hUmDVq1IeCEOLLQBD4x5mmKKvFksiI6bwUQjxM2FVDQUHBoI5Jl5JTzjY6org1LhUUISi0J5NoNOEOBPjehrUcaW3CEwgikVgNBvITk/jZshs50dbKV958nUeuvZlxqeld37+9ZAK+UIj/HN1Hrcs5JIM1nCQaTajD4DdOTLIye/FYLFYT3/nkP9i+7gj5Y9IxW43kFKQOenvhCdIGNtVWDbxyFNp8Hl6oOMSU9Cy0KAZaKIKyyfmkZSez5tntvPOT1/PM79fw5/99gc//4n4Sk89d+TNBS+aGnPewqeklWv31vaJJRoKA7qfJV9MnxBDC/bl23wne2H2UT9y6iLnl+Ww8dIpfvLCeSYVZLJtaFpZa7lHAJaTrrNl7nMOnG2h3e/EFQ6zaexyX1xdZV6dnvRddl0wpzub9K+ZEfSgmWc0YtcsvaTBehmzUhRAPEJ5AXdZjwvM0kN9jtTygJtKeF6U9KlLKR4FHAWbNmjWoydSgrvOTbetYc7pi4JUvUkyqyv9dfTMLcgqxGAx8dt4iOnw+vrdxDUFd5yvzr8ZmMHCguZFtddW0+ryEzlJ7tBoMPDBhOreVjKPJ4w4Xuj5fhUOjoCoKxfahJ9uoqsLUeSVdLpUx47JYuGISQgikjOpWjgt/KMQTh/f2K6U7KTWDE+2tuKO89UjglcqjvKN8MuWOtH5H3kJRKJmYy7s/cyM//Pjf2L+1gnnXThragffcrhAUWseRl19KUPpHPEGmznOSv5/8Ad4oAlRSwo7j1RRlpLBsSik2s5Frp5Xx3Ob97DhezTVToqt3zirL48FrZrHx8Ekee30rmw+fwtePTPHuihq+9+TqqL/7oonFfOC6eUO+Ji51hmTUhRDXA58Hlkgpe8ocPgf8UwjxU8ITpWXAFillSAjhFELMAzYD7wZ+cW6HHguJOxgYVGjaxYZJVbuq1WuKQmlyCtWuDtq8XoK6TprFSpYtgT/t3cGWmtMxK9uHY/GtpAxRYfJ8YVI1UsxmolXfMygKBkVFM6jc8/DSrnc+a4KZD37x5nDizhBvXiklG2tP8erJozHXSTaZ+eSMBTy6dytb6k5HXafG1cE/Du3my3OX9ir4LRSBxWpC1RQURWC2GBFCYcyEXDLzUzi65xRzlw+PZokQAk0Y0Bj5ED+TaumnUk+44EnPQilChCUTYkUWCQTVze2s3XeCY3XN5KbY+fgtC/nek6tiHsOMklw+dMNVUfvObjWds0Fv9FZT5T7C+SuhHhtVaJQkTiVBi2+OKJ6QxseBpUCaEOI08HXC0S4m4PVIp26SUn5QSrlfCPFv4ABht8xHIpEvAB+iO6TxZYYx8uVyJhAKsa2umr/t34UnGEAg+N7GNdw/aTqfn7uI7XU1fH3dGxf6MM+JpXnFjL3h7qjLBJCXmBQ23mfpoxiMQ/ceSimp7XTyy12b+q1JuiCnkAU5BdR1OtnRUBP1ASqBZ48fZFFuEcsLSroMjd1h4+P/+w4ych1oRo0PfftOktMSUFWFBz93Mybr5RdjLYRgWnEO6/ZX8Ob+CmaV5bHlyCkq61u5bW7fB5giBPPGFdC528+BqnDxk6unlJKSaIlqmEV4JzR3uNlxvDqqUc9MTiA10YZ2Dno6FZ37eL769+dFFmAgTIqVB4q/MnxGXUp5b5Tmx/pZ/7vAd6O0bwPO/V3zCqPd5+OX2zdhUFV+dPX1qIrC73Zu5RfbN/LLa28h0TR8ZdEuFOc7cklKiTPg55GdG9neENMLSLLJzDvHTcWiGVheWMo/D+/hQHND1HXbfF5+sn0d+YlJjI24YQxGjTETuuMBisd1i05NnDNm+E7oIkIIwdVTSthVUcPPnn2TRKsJp8fH0iklLJnU95yFEKyYVs70MTmkJtowaiqKIqiob8GgqqiKgtlo6DLQqiKYWZLLqj3HeWXH4ajHMCE/k/njCuEcZI0lEh3JxTBSD89dxH8cV0xG6aVKksnENxctI9lkJsViRQCT0jJpdHd2GcLwq/AV6kAcJFJKXAE/v9y1if8c29+PSyAsUTwrMxyhkmlN4J6xk/n2ptUx69geamnkmxtX8Z0F1zImafhCFi817BYTn33bEg5U1dPY3klGcgIT8jOwGA0EQn377lB1Az955k2+9a4VjMkKT3ZnORL5wl1XU5qdylffsYxsR1gETQjBO5dM464Fk2POEamKwDA6UTrKxYpBVTnS0sSaUxV8Zf7V2E0mEoxGEozhuOiiJAefnD2fLFvfcmC6lOxrqqfBc+lWV1IQTE7LGpb6sFJKql0d/GLXJp4+th9/P/r6RXYH7500C1NEelkRgpuLx/FyxRE2xoiUkcDG2lN89s2X+eKcJczIyEERV16ijBACm9nI7LL8gVcGfIEQ9W0u2jq9dLi7XWETC8IZwflpyZgjrrbqlg42Hjw5YObvrNI8SrIHHw11BpNiwWFMZyhJ71KCz+tHURSMw6DnY1ItqIOQ4L3sjLoiFK4vKqMkKeVCH0q/bKqrYndjXVzr1rqc7Gmowx8KEtJ7/7iZVht3jZuIEmWkHpI6j+7dyiuVR4blmC8EBkXll9fcwrKCoRf1kFLS7vfx5ukK/rB3G3ub6/s1CjbNwIenzqUsObWXQU4xW/jQ1Lkcbm2KGS0jge0NNXxs9Qu8c9xUbi8dT67NfkUa9/7o2RVGTcUXDPKdf73RZbx7rQs8sGwWK6aXU9/m5NWdhwlGGfF3b1uQkZxwTkZ9vH0ORbYJg3O+SEmny4uz3cPfHnuD3MJUbrx7DhaLkeaGDtpbO7EmmGmqb2fa3BJUTaX6ZBPHD3VnMhsMKqUTcjiw8yTjpxZw6kQjtgQzmaXxh3ZfdkZdUxTeXn5xF4CQUvL9LWvjNuqKUKjtdPH1dau6Ro49Maoq7586ixJH34s4JPWY7oJLhcHosfTEFfBzrLWZbfXVvHbyKHua6vAMUNVIFQrvGDuZW6IUGhdCMD+7gPvHT+fXuzf126+1nU5+vmM9/z12gCV5xSzIKWB8agY5tsRL3rhrwkCKMatXSGOSITWuuFJVEdxx1STMRq1rGFKem8bX71mO2xc7Ua4sJ6zAObUoh0cevm3A/ZxxvwjCUgQG0Z3xq8VRy9SkWjCpg5vnCQRC/OsPr7Bjw1Eaats4uqWVfWsbuOPdC2hrdrFrywmmzC5m89rDzJ89C6vRxNrNR/nzI2+RledAVRWsCWYyHsrhpT/uI/tTeWx4toLs/BTmz7mCR+qXI1fl5nPaOTGmu8CoqmGlv1F6serUcb66YSUdPl9k0qt/FAQrCkv5yLR5mNXot4amKLxn4gyOtzXzYsWRfqMjQlJyvL2F4+0t/OPQLm4vmcD3Fq6ImqQ0kshIsk97Sye1p5ppqG3D7fKhagqOtASy81PJzEnGaI4vCzfVlM19RV/ode6aMPQynLFQFYWlk3u/dSWYTSybWhbXuWiqgqbGX/gkyZjKXQUfJ6h3PzDMqnVECmurqkJxeRZvvbaPez9wNfXVrezecgJbopkj+04TCupIXSL17olPKSWaQaFgTAYGo0pSio0kh5VAIMQrT2+j8mg92XmD8zpcdkZdSolfDw15dHc+kBKCMv7R89iUNL4yf+nIHdBlSmcgQLvPG9crtCIES/OK+crcpf3q6gshSDaZ+cKcJbT5vKyvORnX9n2hEM44CloPN7quc7qiiZXP7mDrm4epr27D5/Gj6xIhQNNUEh1Wyiflce3tM5g+vwzzABILqtCwSDu1VS1dBbWFEiAr14TFFjsaq9PppbUpPr36s0lKsZGYZCUYCHHqeAO+yKjeaNQoKMnAYNTQdUl1ZRMuZ9g1JoQgtzCVoqQJQLjOrd8fxGTS0EMST8CP0ahx6mQTJpOB7JzkSDKbxO8PoWnKoAqDCwF1p1son5TL2+6bT2uTi4O7q/jPn9dRVdHImLHZUb+nqgp2hxWTyYA92dp1DM42N37fwPVyz+ayM+pBqYdD1epjh6pdeCQnO9riXvtSf12/2NGEwnVFZXx57tK43CNCCPIS7Hx7wXK+tmEl66tPxfUmcL7x+wKseWkP/350DTWnmvtEi0gZdhm0NDjZtOoguzcdZ+F1k3nnh68hM2LgYtHS6OR/P/svmurbATCZDHzuh3czaVZxzO9sefMwf/jRSwxiPAOEjeW9H7yam++dh7Pdzc+/+jTVJ5sAyMpL4Zu/eYC0TDuhYIi/PvI6OzaEk8k0g8pnvv92Zi8eC8DxY/X846/reegDV1Nb08arr+zhoQ9czR9+t4a8ghQ++OFlALS2dPK737zBiuunMLOf84lGe6ubZIcNzaBiTTBjMhtYcO1EGmraqDxa3/fcFEEopNPe0onRqNHW7OLwvtO4XT7u/NwiXn162+A6i8vQqEspOdTSyMbai1t29Hwx+jjonwSDkXeOm8oHp8whxWyJ+wEqhKDY7uAHC6/jx9vX8WLF4X6jac43fl+Q//5tA/96dA1uV3xvCB63n5X/3UFjbRsf/dpt5BSmxuwPXZc42z10tIYTyk1mA8Fg/9ba5/HT2ugcklyFN1LwRErwuH1d5+Tp9PWKUPF5/V3LNINKsIcQnsvp5cCBaurq2qmqaubwoVoC/iA+f4CAv3tE7PMH2bf3NLNmDz6XIDM3mW3rjuJs99BQ04arw4On00fd6Zao60+ZVcy1t80gGOjuO82gkpXrwGozkZphJ8kxuMivy86oj9KNKhTuHTeVBTlFF/pQ+mVb/WmeOXbgvI51FSEY60jjw1PnsqKwDJOqDvqNSAhBboKdb81fzsTUDP64bzs1cZbDG0mklKx/fV8fgy6EICMnmbKJuaRnJ+H1BDhxqJaKw7Vdr/lSSnZvPs6ffvYqn/jW20hMurglJgaLx+3n5z9+mUAgeE4ZydEQQjBn0VhWv7ibH33pSTraPOQWpaHrkoojdWTn9w1kyMhxkFuYRqerO5RTD+lYE8zs3VaBxWYirzhtUMcxatQvYxQhWJRbdNGLHKuK4JljBzkf2XsCyLYlclvJeO4dN5X8xKQ+US6D2p4Q2I0m3jtxJnOz8vnLgR28ceoErb7YAmEjTXN9B//501u9DLrJbGDZbdO57b75ZOenoBnUsN+23cPGNw7w+G9X01DTBoRHw1vWHmbDygOsuGPmsLn/covSuPb2mRzaU8Wp4+HMXEURTJ1bQlpWOLmordnFjvXHCEVCFjNzk5k8ewxFZVnDcgyqqlA8Jh2Xy0tT4/A/gAtLM/joV25l/cr9WG1mlt0yjbSssMzFvu2Vfdb3+wIc2HmS1pa+uSR6SHL8UC16SGfBsolxH8OoUR/lisCqGRiTlMLyghJuLC6nJDkVdRhjx1VFYXJaJt9dsIJ3jqvnhROHWVdzkipn24BhlMOJlJJdm49zsof/VtUUbn3XVdz7wasxW41d5yyEIMlhY8UdM0lJT+TnX32a1qawcQn4g6x5cTeLrp+MtZ/Jz8EwaWYRE6YX8ugPXuwy6qqmcNt9VzF7yTgA9m+vZO+2SkLusLulbGIeH//m7WgxMkR1XdLp9GC2GAgEQr3cGNEwmQ3c/+AiKk408OfH3qSysgmPe/gqhCmKwsTphUycXtjVJoTAYIh+/I7UBD75zTuiJjn5vAG+/T//HPQxjBr1US5bMqw2biguZ0JKBjMychiXko7DbAmLKozA5LMQArOmMSMjh2np2TR53RxuaWJPUy2HWpoYk5Qy4nMcui7Zt62yl3+7qCyL2+6f38ug90RRFGYsKGPZrdN56k9vdb0wVR6t58COk2Tm9pVMbqprJxQc3ByCEAJF6RvOLiIl/s587r2QfhO3mhs6+MGnn4i8eUBdVXTfdY/NIUT4WFpbO/nxD17A5wsydlz0yJShEPVYRWS/ioiEH3c/WGNlnUopUdXBDzyuOKNuUFSmpGViNVy8CnkGRcVh6k58kFISiqZLOwwoovuG6omUYQnVeCe1FCUstSp7fkf0nqg9037mGh3pqJ7FeUUsyi0670XGhRCoEb2YTGsCi3ILCUq9S5J2JAkGQjTUtPZqGz+tAEda/1E9mqYyfX4Zzz++CZ8nHC7Y3uLiR5//N6rWN6xPD0mc7e4+7eebYCDEyWPRRdYGwmozseK6yWxYP/IZ1zPnl1FYkkF2XgplE3Ixmgc2vZpB5W33LcDuGNy8xhVn1JNMJr694NqLXkbA0CM+1unx8euXN9LQNvwaLrfOncDSSX1T8AMhncde38LRmqYBtyGE4N5FU5lVls+x2maeeGsXIV0nPy2Z+5bOwKipvLbzCBsPnwRgZmkeN88aP+zncjYG5eIQdQoXWD4/x6LrOgF/7xF0YlJ0GduzsSWY0DQVH2GjLiV0tF14wz2cBIIhtm45QWNDBzabkZtumcbx431DDYeb0vE5lI4Pq3QWlmbG9R1NU5m7dNyg93XFGXWBwKiomLVL59T9wRCbDp+ior7/V8uhMH1MTtR2XdfZcbyaLUcHLvOmCMHSiKxqfZuL57YcwB8MMbU4m3sWTcOoqew5Wcczm/YDYf/z+TDqVyKqqmJN6O0Dr61qIRTU0WL4dSH8ZlZf04bPe2nVtDWaNIrHZmEwakhdcvJ4A6722JPUPm+Af/x1PVJKUlL7iuD1hy69+IN1MMLlAsMIDGo6qjK4Y4Qr0KhfiggBFqMBmyn+9OhYSMKV3gebcWsyaGhnSRF4A0FCF6GujD8Y4vmtB6hp7QCgIC2Zm2aORzsHfe2B0KXkjT1HOVTdCEBqgpXb507Cajq/bj6DQSW/JIMta7u1xvdureDYgRrGTsmL6YLpdHpZ88KurgxRAHuylZkLyzEY+z4MPJ0+tr55pCt+PB50XaKH9F71SQFCIdkVTx46S6hL6pJgsDu1KxTSewVJpaQn8pnvv53UzCSCgSA/+My/2LE+diUrs9nI/Q8upK62jXVv9dZjb25y8dore2hudtHZ2Te23xs4zvGmjxGSfcv4DTcClcKUb5NsWTbo715xRt0V8PHr3ZtINg2/9sNwoSkq7xg7mdLkcFyr3WrmG/deiy9w7lEULq+P7z+1mlONbfEfj6rw0RvnM63HqF7XJb99dRMbD50852MaLFJKgiE95oPJ4w/w3NYD7KwIZxXPKy/g6sklmGK8nSmKQBvA7x6e19Bjzm2EjfpxXtpxCICSrFSumVIas9i2IgSaOgK+fgEz5pfy8r+24I4YpuaGDh77yct86Mu3UFSW1WsORUqJq8PLk39Yy7Z1vX3Lc5aO42Nfvz3qCL/udAuH9lQNyqjv3nycFx7fRMXhbiG7YEDnyT+sZeUz24Gwu6dnavyh3VX872ee6Oonvz9Ic0NH9+kKgclixGI1EvArqP1UO1I1BXuShclT8rHbLezcUdmj/wXt7W5eeXkPLpcXq8WII6V30o8uAwRCDYTkyEtZCzR0PXZFrv644oy6Jxjk6WMHLvRh9ItJVVmYW9hl1A2qytjc9GHZdlunB4txcKNHgaAo08GUou4IgZCuk2y7MA9GXzDEr17awLG66P7+kC45Xtfc9feh6gY+++cXo04IA0wuyOLhFXPRoihgnkFK+PvanWw+Gj1TWUo4Wtt9PLWtHXzlH69iiDLJCJCXmswnb16IzXzub189EUIwfmoBMxaUse61fV3t+7ZV8v1PPcGNd89h2rwx2JNtBAJBTh5r4JUnt7Jt3ZFeo3RHWgLX3TkLgzF6Ula4bXAPpPrqVja+caDX5LuUkoO7Ymd/Nzd0sHFVR8zlg6G0LIsvf+12cvMcpKUlUlScTlp6IsuWTyI52UpeXgrf+u5d6LqOwaCRlRVf+biLjXhqlP4RuBlokFJOOmvZZ4AfAelSyqZI2xeB9wEh4ONSylcj7TPprlH6EvAJORQF+gERIx5hMMqFRdd19p6qY8eJ6rjWb+v0svFIbMOhKkrUotc9kUiO1DaxPs43E7cvwJZjsecjxua6CYyQrIDZauTeD17N6YrGXnojpysa+cOPX8aebMWWaCYYCNHW4uqKdjmDyWzgjgcWMm5K/mWlO2SzmSgtC09Sms1GkpLDUSU33DS1a52i4tiDJ01JIsmylJAc+cQygYpByxjSd+MZqf8Z+CXw1147FSIfuBY41aNtAnAPMBHIAVYKIcojxad/AzwMbCJs1K9nBIpPq0KQbDp/9S5HuTAYVAVjj4SUaO6YMz70swsqqIrSyy0Sr69dU3rvM5o7RlUUFBHeZ88lZ1w83cevRsoQDj9CCIrHZvHRr9/O777/AscOVHeNjvWQTluzi7bm6C6EBLuZOx5cxM33zut3YnUoWG0msvJShlRN6Ax6SNLc2EFoAJ2ZaAx1v2cebCatkOLUnw5pG0Pa7xAdKfEUnn5TCFEUZdHPgM8Bz/Zouw14QkrpAyqEEMeAOUKISsAupdwIIIT4K3A7I2DUFSGYmp7Ff47uI3QRy+9eCQRDOs1ONx6/Aa9/+KIqTAaNj9+0gHZ3xGfs7OR3r23mdHM7AijKcHDt1HLG5aUjgIOnG3ht11FONrYigSmFWbxr8XSskYnnlARLn0ngs1GE4L4l01kxrRyATp+fP6/axv6q8Eg4MzmBa6eUMbUoB6NB5URdM6/vDk+c6lJSmO7gvdfMJjUxPDpMMBuxmkduElUIwYTpBXz+R+/gqT++xYaV+/sNT9QiFXfufM8i5i4dN+y6KACzl4xj/PSCc1KD6Ghz839ff4b66nAsfmKSpZdbzZpg7orrNhhUDIbu86g61cyz/90+YNbpGaZOL+DqayZ0/S2EgmB43WUjwZB+OSHErUC1lHL3Wa9nuYRH4mc4HWkLRD6f3T7siIgu9uS0LHY11g78hVFGjGO1zXzs0f8ihKDFOXzxzqqiMLkw7N/3+gP89Pm3qI1EuswtL+Bzty9hTGZq181+9aRSrps+lh88vZqtx06zv6qeE/UtvG/Z7LgLFAshKM9JpzwnnWBI529rt3f50MfmpPPFO69mamE2iqIgBCydOIYbZozj5y+s47VdRzjV2MrOimo+e9uSYfej93fMOYWpfOjLN7P89hlsWXOIQ3uqaG7owO8NoKgKCXYz+WMymLWonOlXleJISxgxl4vFGp7QPBcc6Yl87n/v7lJV1Axal4qhpqk8+MkVvOP9S8IrRwTMztDe7mHb5hP4/fEFHCQnX5piZoM26kIIK/BlYEW0xVHaZD/tsfbxMGFXDQUF8dfmO0Nugp3vLbyWR/dsZWdDLc6A76IumnE2JlXDcBlUMvIFglQ2tA68IuGwzeg/Uf8RKTsranhx2yFCuiTbkcj/3LKIkqzekrGKIijNSuUTNy/kf/74PI0dnTyxbhfzyguYWpQ9aCNW2dDCE+t24w+GSLSY+NhN85lenNNrO0IIsh2JfPymBRyrbeJYXTMvbT/EvPICrptWft581eE0dAMTphcwflpBlzRtwB9EKAKL1YTVZkLVzm/W7VDRNJW8GH5voQiy+qkSVD42ix/85N643TC2QWjehLcpAR2JRKAAF6ZPhzJSLwGKgTOj9DxghxBiDuEReM8S4nlATaQ9L0p7VKSUjwKPAsyaNWvQ1lgIwYSUDH64+HqaPG6c/kvLqAshyE+4NGfee6KpCnaLCSEEnV4/3hghmdPSs/nC7MVRlylCUBal9uoZNh4+idMbdsNMK86hNDu6BrgQgrE56UwsyGTNvhO0uDxsPHKSqUWD0/yQUrKroob6SHZvSVYq04tzY+4zx2Fn3tgCjtU14w0EeXP/CZZPKUOLEXpn0TSybYlRr1dVCMza0Fw2QohwvoPVhMU6PAJdQ0EP6VQercfVcR4mGxVBYUkG9shI3mQykJ2djK5L3J0+XJ0+DJqCPcmKNoSHmpQSiR9v4Dgu3048gcME9GaQIVTFjtkwhgTjdCzG8aji/NWmHbRRl1LuBbqmZSP+8llSyiYhxHPAP4UQPyU8UVoGbJFShoQQTiHEPGAz8G7gF8NxArEQQmBSNXIT7CO5mxEnEEmkOd3UPizb8wWCNLZ3J0+8daCC9KQEVkwrjxnyN1RKs1L52j3XYjFq/OmNbTy3JXoo6biUdMalDD5kU5eSxo7uc3HY+veNG1SVZGv3JHpTR2fM18j+aHR2dhldu8WEqZ8JRSHCiUhnaHZ5COp6zMnZhTlF/PPGu6O+xwoBaZbBFUy42PD7g/zpZ6+yd1vFiO/LYFD57P/ezZwl3an2bref11/dy6qV+2ludmI0akyYmMedb59DUXFa3IZXSh134AANzj/T7lkbNuZ9Mk0FqkjAZppOZuJ7sJsXoMRRx/VciSek8XFgKZAmhDgNfF1K+Vi0daWU+4UQ/wYOAEHgI5HIF4AP0R3S+DIjMEkaD35fgJa6dvQBMiFVVSU1OwktMtGi6zpN1a34vAHMNhNp2b3Lfem6pLW+HZ934GSM5LRErIndxqW1oZ3munZUTSF3TAbGHj7XYEjnxW2H2HbsdLRNnTObj1ThsFlYPrUMZZijMUxGjaIMB1aTAbt1+GPahRAkWrpHnaeb2/EGgjHj8D3+QFeWKUCixTykM+65z/p2F06Pj9TE6LdSSNc52SPRK8FsRO3HcCQYjSQYh+fGDwZDHNlzGpcznMQiBBSVZZKenTws2x8SMlyV6ewwypEgFNR7ZagGgyGefnIL/35iE9k5DiZMyMXl8rFx/REqKxr50tduIyenryLl2UgZpNX9Cqfbf4gv2F+FNUlIOunwvkmnfw9Zie8nM/E9qIqFkaxJFk/0y70DLC866+/vAt+Nst42YNLZ7eeb6mP1/OD9v6dzgNe/lMwkvvTHD5BVGK464vME+PUXHufIjkqmLRnP/zzyQK8IgYAvwG+/9AQHt57od7tCCN73jTtZeuecrrbV/9nC4z9+kaTURL7+9w+TXz58MqCXMwKYkJeJqiiEdJ1dlTVsPlLF4onFfXIVdCnZePgkByLRKgZVZXze4OOAhRCUZ6djMxno9AWorG9h5e5j3DV/MupZbwlSSvZX1XcJmQkBE/IyRlSuoCc+j5/HfvoKR/eGBwRCEXzkq7ey4o5Z57ztBLuZ2+67CldH+IGhGZSoEr0XEw31Hbz6yh4WLh7Lex9aiiPFRjAQYsvm4zzy81d5a+1h7r5n7oCZxW2e1Zxq/SYBvbHXMoGGEGYECjo+wkGAYUJ6G7Udv0QIlczE96GIkYt8uuIySkPBEG2NHbhiyIbqIRmRj5W99KKllHQ0u2ipb8fZ2tlnVk9Kic/jx+2M/rAIBkL4vQGEEHjdPtY+s5UT+8LJKQe2HMfZ2omqKX10MTRN4Y6rJnHVuMJom+21/7X7TrD3ZDgFe0xmCjfMHBvRbu6fMZkpl2TClhCCOWX5jMlM4WhtEx1uHz99/k2ECEsDnIkp9wdDbDh8kp+/sA5X5E2qPCetz+RmvIzLTWdKUTYbD5/CFwzxu9c3YzSorJha3qX1EtR19p6s4yfPvkl9e9j/npWcyOIJY86bb1XK8HUXiGSKCkGf62uoJCZZufM9iwb9Pc2gcv1ds5g+v3RYjqMnHpePV57aGjN0s6nRidcb4LobppAaifJRVYU580ooLc2ksqIRXZf9Sg34Q9XUtP+sl0E3KOkkWZZhNy/ApOUAKkG9FZdvB62eV/AGjgM6uvRQ1/F7bMZpJJr6f3icC1ecUc8qSufTv3pPr5Tonrzy93VseXUPiiL6Cvb3g9Fk4KFvvR23M5peg2T9Czt58pFXUDUFm93Khhd3svqpzQNu16Cq3BSHoqEuJfVtri6jXpjh4D2DCNnrH0mn109bZ/cDK6RLAoMskjASZDkSed+y2Xzv6dV0uL1UNrTy5X++yqySPCbkZYCAg1UNbD1eRUckrt2RYOGh5XNItw/NP51oMfHQ8jlUNrRS2+qkqaOTHzy9hld2HmFqYTYmo8ax2iY2H62iKeLztxgNvHvpTMZkXdySzyONZlC5+uZpI7Lt5oYO1r++L6ZR1wwqSGhr7V4upcTrCeBy+ciMlJ2LhZSSFvdLuANnhMAECaZZ5CV/HptxamSk3v39JPMS0mx3UdvxS5o7/4skQFBvptH1OAmm6QhGZsL6ijPqCUlW5qyYEnWZrutsXRnWy9AM2qAy6hRVoSCG28TvDfD8H9aAhESHjZwxGUyYW9LlVjt5sKZr1H4xceb6DIZ0HnlhPX9cubVrmQTqWp091r0wI31FCK6dWobHH+C3r26ivt1Fh9vLqr3HWLX3WJ/1cxx2PnLDVSyZWDzkYxZCMGNMLl+842p+9sI6Kutb8PgDbDx8ssvV0hOHzcKD18ziznmT+rhoRjl/5OQkk52TzN/+so5gUKekNAN3p49XX9lD1alm7nj77H5153XZSbtnNWEFFLAYyih0fAeLIXqIqhAKJq2A/OQvEdKdtHpeAcDl24Y/WIvZUDQCZ3kJGnUpZR/5zZ70LI2lR1K11TjV8EJBnY5I+rQlwYzJcm4TVmdcMiuf2Miml3cBMOmqMnJLMikcl81171oIwJOPvHLRGXVVUbBbwpObEqhpiS2qpKkK9nMIkzsTNxzSJWKA8mXRMGgqt8+dSGl2Kk+s283WY6dpdbkJRCbJDKqCI8HKnLJ87l04jQn5GedsXFVFYfHEMeSlJvHvDXtYd7CShnYXgWAofM0pCklWE1OKsrln4TRml+QN01vTKEMlKdnK/Q8s5Ne/eJ2f/uhFrFYTgUAQXZdcd8NU5s4t6fe6C+otPSZGFdJsd2ExlPX7HSEEqpJMRuL9tHvfQpedBPRmfMFTo0b9DKcrm/jHr1fhjTF7PmFaAXe+ZyEBf5C//+oN3J1+Hvz48q5Y1f7wdvporA4XokjNSsI86OSDiCysP4SztZMT+6pY9eQmNr2yG4/LR3ZxOnd+ZAVGk8Yzv13J3g1hqdPq40MrxzWSaKrCrXMnUNfm7OV2ORtVUZhWnNOV4TlY/MEgO07XsuboCarbndiMBmYX5LG0rJgUq6XrhpFS0u714gkESTKbsfaIcPEHQzS4XCTbrbx3xWyumzWWyoZWmp1h10dKgpXijBRyU+0YNY3TbR3YjAZSbdZeN6TL56O5n3ONRlaKnc/evoR3L5lBRUMrDe0uQrpOks1CZnIC9gQzBlXF5fdjV0x9Hlhtbg9tXi/JZnOvcMugrtPgdHU9mOLBbNBIT7BdkvMj5wMhBDNnj+Gb372LzZuOU326BavVyJSpBUydXoh5ANmGoN7RJburCAs24zSEGHhwEK5dW4JBzcAXrEBKfyQEMkyb38NrNQfwBPtGzk1MzmFmagEhqbOuIfzmuTCj//mIS86oB3xBaqta8Lj9eN0+GurasViNpGWG/WFZeQ6QklBQZ9/2SjraPPg+sDSubddXNVNfFe7sogm5GGOExtWcaOCJn72Mwagy/6YZFIzNpqPZxSt/X0dDVTON1a3UVjbScLoZn9uPUARjJuXxvm/cRfmMIqQuObb7FJte3j1c3TLsCCFYOKGYqUU5eAOxw88UIbBbzb2EruLFEwjw2Mbt/GXrTjq8XoyqRlDXeX7fIeYV5fPl65ZSnOJACIEuJb9dv5U3jhzn01cv4Prx5V3bOd3WzieefpE2T/z60yvGlvKlFUt6hReuOVbJD994M/66rELwheWLuWFCOXlpyeSlJQMQCIVYd+Ikv928leNNLQRCIRxWC0tKi7l35hQyEmxdhv2p3fv5y5YdPDBnBg9d1R2V0ub28Jn/vkJVW/z5CdNys/nhbddhiVF/V0o4tPvUiOi6AJSMz6GwNOOizkxVFEFBYRr5BakEgyEa6jtISrZiieetXOpdARICFSHiH/QJoSFEj36X3fNRzT4Xvzy4Gl3qOEzhwWdAD1HjbuO+krnMTC3Ar4f449ENSCQzU/sPmrjkjHpBSQbf/PX9SAmbVh/kl99+jtLxOXz6e3dhMhvQQzrPP76Z+upWGmrbMcfpQtF1yY7VB+hocWE0G5h0VVnMUNLq4/X844fPh+PKS7IoGJtNW7OTZ36zkrbGbjeFyWKkcFwO826YxnXvWkB2UTpCEehIltwxm6IJYfmbPesOs33V/nPum8HQ1u6modnZq82gqeRlO2ho6sDZ6aMgN4XmJheJCSbSUxOHdf8SeOPICf6waRuaovDQvFlcVVxAbbuTv23dyboTJ3lk7Ua+e/O12CJx282dbk61tOHy9R7RBHWdRlcnnkCAqbnZGPvRRT9DdlJiH5XEJLOJsRnpA6aRS+BwfSP1kX32RJeSlw8e5XuvrcHl81OankqiyUhFcyu/27CFww2NfOvG5aRF3hJcPj/1zs4+5xSSkqbOTlrcbqbkZHX1QX8UOJJ6jdKFoI+P+LWnt/PaMzsG3NZQePATKygsHZpc7PlGCEFrq5vvfftZ7r5nHkuuHjgYQVEsCGEECbr04A+eRhqnxPUQC4SaCYXawvtGjVqm7o7CGTxQMg+AGk87H9v8RK/lOpIKZxNf3fkczkDsAcwlZ9Q1g0qSw4bfF+TIvmpCQZ2aqhbaWzopn5SLs93D+pUHqDxah9vlw5w78M0gpaShqonVT25C6pKCsdmUTy+K+WPZkizklWahaSqJkeooJrOR8bPHEAyEcGTYySvNZMykfIrG5+LITApH00S2pyiCeddPZd71YR1ni83EqcO12FMTUM+T33XD9hP85i9ru/y/wWCI3OxkvvP523j65V3s2FfFpx9ezo9++xqL5pbx0L0LhnX/gVCIVw8eweMP8MEFc/jIonldxbaLUx187D8vsKmyisqWNiZmxWcoMhMT+N7N15KeMLCrTY2kzfdkfnEBcwrzon+hB7ou+dILr/Pywb5V6Gvbnfxu/RZcPj8PXTWL+2dPw2IwcLihkW+8vIo1xyp4evd+3j9/dlzpJ4kmE19ZsZTS9NhSCWdQRG95X82gkWDvLUMdligZGcmMESmPMIw0N7vY0KMYSIfTQ01NGxvWH6ElihTxhEm5jB3XXe1LUxwY1DSCehOSAM3u57BbFqHSvwSAlEHaPK92uVwUxYZR7Vsb2K8H6Yy4YNxBf9T+lEgCev9RZ5ecUfd6/Jw81sCbr+xhzUt7SE6x4Wxz85vvvcAdDyygfFIen/jGbXS0uXnkm8/2Ko0VDSklHpeXJx95lcpDNWgGleX3zCc5Lba8wNgZxXz+0YcwGLWu7M+M/BQ+/+hDKKqCpqkIJf7JvmvePo/ZyyejqIKUrOS4++JcmDo+j6yMJCxmA4vnlvHYE+tZMq8cgaDD5cXr9RPSdVydPny+4c/+8wdDNLrcGFSVGfk5vdw3ZempZNsTONbYQpu7r4/7RHMrmyqrKEpxkGXvHvEIBEZVjVm2biCONDSx+ljFwCN1CceamqMu21ldS0VzKxOzMnj37Gmk2MISAdNys3nvvJl86YXXeOPICe6dOQW7Ob4sW8MQz8lo0lh641SOH6zF2eYecaM7mBDgC0FDfTt//8s63O7upCAJbFh3hA3rzn5AC+5/cOFZRj2ZBON0PIFwycJ2zxrqOn5DVuIHUJW+4ZBntGFa3C9R7/wLZ2QELFoJJq1bqNCoaFg1I/89tYvXaw4CEJI67QEviVrva6Q4IY3vz7idzYafxDzPS86oH95zmh987l+4XT7GTsnjnR+4mp2bjvPyk1v58ZeeYuG1k/ifb78NR1oiZouhX6MupaS5ro0nH3mV1x/fgNQl068Zz9V3zun3AlU1FWuCGUOPosKKouDz+Dm66yRyiAkemlHDnpIwYj7PnqSlJpCUaCYxwcz48iwMmkpOVhJ/fWoT67YcI9k+soVGDKpKis1CQNfZXV3H/OKCrlHmieYW6p2dWAwaSZbeF7UE/rJlB//YtosvXruEe2ZED08dCvvqGvi/NRsA4oqOObuuqZSSU61tBHWdcZnpJFu6+1AIwYSsDOxmM42uTjq8vriN+lARQrDkpikUlGZQf7qV5mYnW7ecoKa6lewcB7PnjOmqwyl1SVOjE1VTSUmxgQjHczc19Q5bzc5OxucLx3WnpNhobnaRmZmEyawxZmx4stzj8dPU6CQY0klNSSDRbkYIgZSS+vp2BIKMTHs4Ec8boKa6td8C5kaDRm6eA22At1iLzcTt716AM5JYqCgK+WO63/IKCtP42rfuGFAiJHK2ZPYpZ6eSYruVFs/LhPQ2JD7qOh7D7T9EesI7sBonoyl2QEGXHryBCprd/6Wl83lCsiOyVQMptltRle5tZ1nsfH3azTR4ertDNaEwJSWPoAwXgJniyI0MXPq3D5ecUU9IsrD0xqmMn5bPlNljSHJYmTC9kDmLx7Jz0zEs1rAqoKopTJtXgrvTj6nHrLbfG8DZ2klLQzv7Nx1j1ZObOLb7FLquM3ZmMe/9xp3YU/v6u+Lh+J4qvve+R/F7hzayTU5P5LtPfZLCsX1fzQZCALNK87oq+pTnpA9aoEsRgrElmew9VD3k0Xleqp13Xz2ToK6T47B3uVTmlOV3pcdPKczCpKlcN66M9SdO8rdtu9ClZF5RPnUdTv6yZSdNrk5WjCujOKVv6vmcwnzK01MpO8sl4Q0G2Vdbj6N94JqWDquFQkdy1LepOYV5vHvO9AGjSAQwPjOjTxucGaX1lgvrOVKOt+pRUNc5VN9Ip39gTaEEk4kxqY5eDySDQaN8Uh6p2Un87Ccvc/hUM6mpCRw93QxWA5/6zI2kpSXi9fr5/nefJyPTzu3vmoeiKDzz9DZeWrUfm82EUARGg8bHl17HwQM17DxUzV1vn8vTL+3ic1+4hbHjspFSUlXVwp//uJajkTJ6KSk23vmu+cyeU0IopPPY79egaSqf/uyNaJpKVVUz3/ja00hdj5kXkp3t4ItfuoXkASLYLFYjN90zN+Zym83ExEl5XWHRfl8QRVUwGbW43jKEECSYZpBuewf1zseQBJH4afeupsO3AaOaiaakIoRKSO/AH6zrMuaRLWA3LyLFekuv604TCvWejq5Rek9eqj5TZ1YSlDoliQML311yRn3M2Czues9CXB0e2ltctLeEfWEJdjMLr52ElJLTJ8PFCxZfPwWDQcXaIzRx48u7+Nv3n6OjxYmrzY2uSwwmjbnLpvDgV95GwdjB62ufQTOoJCZbCQzg8jkbT6cXj8tH0B88p6ow100v57rp5QOvCBytaKC6rh2j0cWLK/fh8QbYvvcU73/XQg4fr2Pb7vhqcZ5NUWYKH7u5r/99yaQxLJk0plfbtWNLqWhu5e/bdvHb9Vv40+btXSF8VxUX8IklV/UKXYSwibxpQjl3TeuWEdJUBU1RqOtw8qlnXu43geQMN04Yy7duXBZVXCszMYElpX31Y6LRe2JSUJzqwKCq7K9roLnTTXok0kWXkt3VdbR7vBTnZmM39x85oSkKBlWlw+vjqy+tjOtYZubn8os7b8Zi7PuWsXXLCfbvq+Zjn1jBzFnF7N51ip//7BX++Y8NjB+fg98f5GRlI1Zb9xyU3x/EYNT4+CevJzU1ASEgMyuJ3TtP0dnpIxAI0tHhIRSpterxBPjjH9ZwsrKJhz9wNUlJVp56cgu/+dVKsrKTyclJprPTh8Gg9iqv53H7eNf9C5k+PXpUh8GokpA48FtNXBOWgRA7tlWw6o391NW2YzYbmDq9kBXXT46cY//bUISRLPsHCOptNHc+gyT8sJXShy94Ch+xBL4UEk3zyHd8GU3pO1AxKhoJhtjXREjX2dRYQWfAT0j2/6ZxyRl1gOf+uYlX/rMtrnWz8hx87f/eRWpG2Efe0ezi9LE6hCKwJVoonpjHsnfMY8HNM0hItg7ZoAOUTy/iu0/9z6B9ly/9eS3P/GblkPcLg8/obGjswGoxApLDx+soyHXQ0OjEN8gH0rlgNRr40MI5zCrIZfXRE9S0d2AzGplVkMuy8pKuCJGByLEn8sEFczjS2BT3vqfkZPXZtoj83/aqGj7731cGfDgIIbh3xpRek6vT83IYm5HGofpGfrdhKw/OmYHNZGBvTT2PbdqGEHD9+DJspv4n8JPMZh6eP5sdVTWREf/AFKU4YrqNOto9GE0aJaWZ2O0WSkoysJgNbNp4jIMHasIqpE19JwsNmkpBQSqZWUmEgjoerz9m5aCamlb27T3NPe+8ioWLxgJhDfMvf+nf7NpxkpweVYh6IiXs2X2S5rOisc6QnZ1M1jDMNem6zuuv7uWxR1ejaSoZmUk0N7t4/O/rOXigmk995gYcKQO9pQs0xUG+48uYDSU0uv6OL3iavrK73WiKgxTrrWTZH8aoRtcbyrEmMc2RH+XbYfx6kL1t8RVavySNevmk3K5yVrEI+EOse30fzjZPLxGjwvE5vP0T15NTlE7RhDzyy7Ow2S3nZMzPYLaZyCvNHPT3koY5XDAeFs4tZda0ol5tihBYRrBu5tlIKTGqKguKC5hfFE6wEEJEIlPi/z3MBgPvmjV14BUHoMCRTH5yEk6vn02V4QxfXeo4I+GGiSYjSo9kE0UIlpWX9NpGRoKNjy+exzdfWc3j2/ew5mgFVqOB2g4n3kCQWyaO49bJ4wcceWuqwq2TxnHrpHH9rhcv4yfkIp/awp8eW8u8q0rZuuUEgUCIz3zuJsZPyMHrCfDtbz7T7zaOHqvjN79aSW1tG44orhCXy0swGCInp9utlZqagNVqpKU1eqFriGiqtHTG/M2NBm1YJnmbmlw8/eQWysdm876Hl5Kd48DnC7Bm1QH+/pf1rHvrCDffOn3Aa08IgSbsZCW+j2TLNbR53sDp3YAveJqQ7AR0FGHGoGaQYJxBsnUFNuNkBMaY236j9hB/PraRTHMiBiW6G0ogyLLYB5TIvuSMuhCCBcsnsmD5xH7X63R6Obr/NB1tvaMnJs8vZ/L881dO7GJFIHhr01EkcN2SCRgi/kwpJaVFGQgEiQlmpozPJS975CRV1xyrYEdVDYtKivoNJxQIcpPsTMjKwGHpO4k7HL/njLwc/vjOO/D0qNDU6OrkS8+/hgS+f/O1pCf2HsllnfW3EIJFJUX87G038p/d+zlY34A/GGJqThbXlJdw88SxA7pehvOczjB+Qg4Pf+Aannl6G3/98zocDivvf/hqZswsQtNUjEaNseNySEm1EStBI8luYfbsMezYUUlnp6/P8uQkK0aTxvHjDcydV4qiCKqrW+l0+cjMjF3JS1EUbrhhKrNmF0ddrmrqsMgV19e1097u4YMfWU5JaSZCCGw2EzfcOI0N649y6GANN90yLe5+F0LFYijFrJWQmfBugrIDXXcjI0ZdU+wowhZX1imARTXwjuJZZJpjR96lmGwxjf4ZLjmjfq5c6cb8DMFQiJdX70eXkmsWjO0y6gA3L5+MlBJFUfjCR68f9opIPdlYcYo/b9mJ3Wzq36gLeP/8WTw4Z3rMIhjniqYqFDiSe7UlmowYVBWJZExaCjlJA1fSUhWFqblZTMrOpNPvJyQlFoOGWdMu2PWnaSolJRm8/e45FBWn40i2kWi3dP22mqYyd14JZosxptspO8fBfe9eiJSwbt3hKMuTueqqMl56YRdms4HkZCvPP7eTrKwkZsyMbrANRg2jSeMff1/P0//ZGnWdrOwkPvO5m8+5EPSZ0zq7VGBYartvolbc2xUCISwYscAQ00wyzXY0ReGvxzf1OxKfkpLHjNT+6zZf3kY9kmAybLfRSN2Pos+H80YoqNPu9OCPUT8Uwq+/WpyiaCOFECKcVXmWKzoQClHvdBGMK0ytN4kmU5e+TKffT5PL3cd/3eDsJKjr4Qn4tg78od6JHwJBms3ax0cuhEBTRZ+QzHgI6Tr1TleffcWDxWDoJUPQkzWrD7J61QHeed8CrNbex+v3B/nXE5sYOzabCRPCfl8BeLx+Nm8+3mVQ0zPsMV0hRqPGux9chNVmYtXK/QRDOoWFadz9jrlkZtoJRpFqzstL4UtfvhWXq+/Iv+ucLIY+xzsUMrOTSHZY+ffjm7BajeTlpeD1Blj1xgFOHKvnmmUTLsg1LoTg9oJpzEgtQB9gEtSqGTFdbiGN8WI0a7z9vYsI+IPYhiHm2mDUuPGBxcxePpmcMRkocaSix8uUBWN5z1fvwGQ1kpx+fvzrQgiMBpXDx+v43Hee7tfHu2BOCQ/du3DII5l4ONnaxsaK/kqDdZPnSCI/Ofw6X+908fH/vEiDM7bPNha3TR7Pp69ZiAC2nDzNN19ZRfAsAS1dSlrdHiTwyadf7NNPmqLw1euv7uNbPxdcPj9ffuF1jjZGT3Dqj3lF+Xz35mujJivpuqSx0cmT/97cFfratUxKamvbKC3rnhPKy08hNTWR55/b0TXcmDO3JGbooRCClBQbD71/KS6XFz0ksSWYMBjU2P5yo8aUqf2PPIeL1NRE7rp7Lr//3Sq+9uWnSE1NwOsN0NLSyZw5Y1iw8MK5ZRMMJiYkD0/Fs8vWqBsM2oB+90Ftz6ix/J75w7a9nkyYU8KEOcNnFOLBaNC4/665HDpWP+AkVHFB2ogZdGtE0+Tp3Qd4bu+huL7z4YVz+eDCcDlAo6pSlp5Kqm3wr+ZZ9u4HaKLJxLiMdEKDnJBThYjbRx73NhVBcWoK2hAGDvln6b+cTUamnY98dDm2sxRIff4gv/5l7wisOXNLmDgpr1eggdGo8Z+ntsTcfriakCApaeDfIxjUee3VPVRVtQy47vjxOSxaPPacjK6iCJZdO5H0DDtrVx+gtqYNs9nA2+6czdXXTCDpHN07FwuXrVEfpX8URTB9UgHTJ52fUVI0hBDcOnkcQtBrcnIgJuV0jybTE2x856blQ5IzUZTuFKAZeTk8cufNg98I9NJbGSzFqQ6WlhZTnNo9GW0zGvnitYuHdk4idjas3W6hrdXN//381T6GX0pJW5ubadMKOeMG1DQ1qnFWlbAUhqIoGAyDmydQeslnhKNe6mrbBvxebhwFoeNB01Smzyhk6rQCgoEQiirCsh6X0VybuNhFeGbNmiW3bYsvJn2UUS41grpOSNfDhnKEqyK1tbmprGiMmZKvCEF+QeqASThVp5ppbnaRX5DKyZNNlJVlkRhHcpCu6+zedQohBFOmFgyqZmpYcXJwoa6XM7NmzWLbtm1RO2N0pD7KKBcQ7TwY8zMkJ1uZFiNrczDkF6SSXxCWaEgdhKSGoihMn1HUq62/Is+jDI2LfqQuhHACfeOnrlzSgPhTJy9/RvujN6P90ZvLtT8KpZRRhWAuhZH6YSnlrIFXuzIQQmwb7Y9uRvujN6P90ZsrsT9GS5uPMsooo1xGjBr1UUYZZZTLiEvBqD96oQ/gImO0P3oz2h+9Ge2P3lxx/XHRT5SOMsooo4wSP5fCSH2UUUYZZZQ4GTXqo4wyyiiXERetURdCXC+EOCyEOCaE+MKFPp7zhRCiUgixVwixSwixLdKWIoR4XQhxNPKvo8f6X4z00WEhxHUX7siHByHEH4UQDUKIfT3aBn3+QoiZkX48JoR4RFyiqYgx+uMbQojqyDWySwhxY49ll3t/5AshVgshDgoh9gshPhFpv2KvkT6EtYQvrv8IqxIfB8YQFlvdDUy40Md1ns69Ekg7q+2HwBcin78A/G/k84RI35iA4kifqRf6HM7x/BcDM4B953L+wBbgKsJCJi8DN1zocxvG/vgG8Jko614J/ZENzIh8TgSORM77ir1Gzv7vYh2pzwGOSSlPSCn9wBPAbRf4mC4ktwF/iXz+C3B7j/YnpJQ+KWUFcIxw312ySCnfBM6W7RvU+QshsgG7lHKjDN+9f+3xnUuKGP0RiyuhP2qllDsin53AQSCXK/gaOZuL1ajnAlU9/j4dabsSkMBrQojtQoiHI22ZUspaCF/UQEak/Urpp8Gef27k89ntlxMfFULsibhnzrgarqj+EEIUAdOBzYxeI11crEY9mm/rSom9XCClnAHcAHxECLG4n3Wv5H6C2Od/uffLb4ASYBpQC/wk0n7F9IcQIgH4D/BJKWVHf6tGabss++QMF6tRPw3k9/g7D6i5QMdyXpFS1kT+bQCeIexOqY+8LhL5tyGy+pXST4M9/9ORz2e3XxZIKeullCEppQ78nm6X2xXRH0IIA2GD/g8p5dOR5tFrJMLFatS3AmVCiGIhhBG4B3juAh/TiCOEsAkhEs98BlYA+wif+wOR1R4Ano18fg64RwhhEkIUA2WEJ38uNwZ1/pHXb6cQYl4kouHdPb5zyXPGeEV4G+FrBK6A/ogc/2PAQSnlT3ssGr1GznChZ2pj/QfcSHhm+zjw5Qt9POfpnMcQnqnfDew/c95AKvAGcDTyb0qP73w50keHuQxm74HHCbsUAoRHU+8byvkDswgbu+PAL4lkT19q/8Xoj78Be4E9hI1W9hXUHwsJu0n2ALsi/914JV8jZ/83KhMwyiijjHIZcbG6X0YZZZRRRhkCo0Z9lFFGGeUyYtSojzLKKKNcRowa9VFGGWWUy4hRoz7KKKOMchkxatRHGWWUUS4jRo36KKOMMsplxP8DCAguFScUcwEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from wordcloud import WordCloud\n",
    "\n",
    "wc = WordCloud(background_color='white',font_path='C:\\\\WINDOWS\\\\Fonts\\\\HYWULM.TTF',  width=1200, height=800, scale=2.0, max_font_size=250)\n",
    "gen =wc.generate_from_frequencies(tags)\n",
    "plt.imshow(gen, interpolation='bilinear')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 클러스터링"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sentence를 vector화 하자"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:06.211920Z",
     "iopub.status.busy": "2020-09-28T12:25:06.210931Z",
     "iopub.status.idle": "2020-09-28T12:25:06.550922Z",
     "shell.execute_reply": "2020-09-28T12:25:06.550922Z",
     "shell.execute_reply.started": "2020-09-28T12:25:06.211920Z"
    }
   },
   "outputs": [],
   "source": [
    "from gensim.test.utils import common_texts\n",
    "\n",
    "from gensim.models.doc2vec import Doc2Vec, TaggedDocument"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:07.194920Z",
     "iopub.status.busy": "2020-09-28T12:25:07.194920Z",
     "iopub.status.idle": "2020-09-28T12:25:07.202930Z",
     "shell.execute_reply": "2020-09-28T12:25:07.202930Z",
     "shell.execute_reply.started": "2020-09-28T12:25:07.194920Z"
    }
   },
   "outputs": [],
   "source": [
    "documents = [ TaggedDocument(row[12],[row[0]]) for row in focusdf.itertuples()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:07.895920Z",
     "iopub.status.busy": "2020-09-28T12:25:07.895920Z",
     "iopub.status.idle": "2020-09-28T12:25:10.718943Z",
     "shell.execute_reply": "2020-09-28T12:25:10.718943Z",
     "shell.execute_reply.started": "2020-09-28T12:25:07.895920Z"
    }
   },
   "outputs": [],
   "source": [
    "model = Doc2Vec(documents, vector_size=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:10.720920Z",
     "iopub.status.busy": "2020-09-28T12:25:10.720920Z",
     "iopub.status.idle": "2020-09-28T12:25:11.071930Z",
     "shell.execute_reply": "2020-09-28T12:25:11.071930Z",
     "shell.execute_reply.started": "2020-09-28T12:25:10.720920Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "focusdf['vec'] = focusdf['nouns'].apply(lambda x: model.infer_vector(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:12.831931Z",
     "iopub.status.busy": "2020-09-28T12:25:12.831931Z",
     "iopub.status.idle": "2020-09-28T12:25:13.223923Z",
     "shell.execute_reply": "2020-09-28T12:25:13.222919Z",
     "shell.execute_reply.started": "2020-09-28T12:25:12.831931Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"\n"
     ]
    }
   ],
   "source": [
    "# Number of cluster chosen is 3 based on Elbow Method, please check the full code for it\n",
    "from sklearn.cluster import KMeans\n",
    "\n",
    "kmeans = KMeans(n_clusters=5)\n",
    "focusdf['cluster'] = kmeans.fit_predict(focusdf['vec'].values.tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:13.874920Z",
     "iopub.status.busy": "2020-09-28T12:25:13.874920Z",
     "iopub.status.idle": "2020-09-28T12:25:13.891924Z",
     "shell.execute_reply": "2020-09-28T12:25:13.891924Z",
     "shell.execute_reply.started": "2020-09-28T12:25:13.874920Z"
    }
   },
   "outputs": [
    {
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       "      <th>cnt</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cluster</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>135</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>52</td>\n",
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       "      <th>4</th>\n",
       "      <td>126</td>\n",
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      "text/plain": [
       "         cnt\n",
       "cluster     \n",
       "0        135\n",
       "1          4\n",
       "2         20\n",
       "3         52\n",
       "4        126"
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   "source": [
    "focusdf.groupby('cluster').agg(cnt=('nouns','count'))"
   ]
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  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:14.535920Z",
     "iopub.status.busy": "2020-09-28T12:25:14.535920Z",
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     "shell.execute_reply.started": "2020-09-28T12:25:14.535920Z"
    }
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   "outputs": [
    {
     "data": {
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       "      <th>title</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>노트20 제정신인가요?.jpg</td>\n",
       "      <td>120만원 가격 책정해놓고 노트9에 썼던 디스플레이 주사율 60너프 뒷면 플라스틱 기본앱에 광고까지 집어넣고 os업뎃은 2번이면 끝나고 플래그쉽 급나누기는 중국보다 심하네요 화웨이도 저러지는 않을테데;;; s10 놋10이 잘만든거였어요 ㅋㅋㅋㅋ 정점을 찍고 급추락</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>갤 노트20 ‘리뷰’ 영상, 언팩 25시간 전 유튜브에…관리의 삼성 ‘구멍’.gisa</td>\n",
       "      <td>http://www.m-i.kr/news/articleView.html?idxno=735276이로써 알려진 사실모서리가 둥글게 처리, 펀치홀 더 큼, 뒷면 플라스틱 재질, 구형 AMOLED 사용, 120hz 미지원 등등노트20은 노트20 울트라와 완전히 급이 다른걸로 확인.... 노트20 라이트라고 불러야 할것 같네요.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>노트20이 플라스틱이라니...</td>\n",
       "      <td>노트 울트라는 그렇게 비싸게 내놓고... 노트20은 여러모로 빼는 게 많네요. 재질까지...s20 판매량 몰아주기인가요 이거...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>617</th>\n",
       "      <td>유튜버가 노트20 영상을 사전에 올렸었군용..</td>\n",
       "      <td>제가 그 때 바로 알았다면 영상을 다운로드 했었을텐데!!못봐서 아쉽습니다...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>646</th>\n",
       "      <td>갤럭시폴드2 방수방진 되는지 안되는지 아직도 미확정인거 맞죠 ?</td>\n",
       "      <td>가능성 제기라는 기사는 있던데 결국 언팩에서 공개되려나요 저는 디자인이고 뭐고보다 폴더폰은 방수방진이 되면 그때서나 사려고 했어서 그게 제일 중요한데 지금 투폰 중 안드로이드폰은 노트8이라 슬슬 업그레이드 고려해야 하거든요 빨리 방수방진 폴더폰 나왔으면 좋겠습니다</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10978</th>\n",
       "      <td>LG 벨벳 정가에 사기 vs 삼성 갤럭시노트20(울트라x) 정가에 사기</td>\n",
       "      <td>누가 더 ㅎㄱ같을까요?전 개인적으론 노트20 나오기전까진 전자인줄 알았는데, 노트20이 나오니 후자같네요.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11088</th>\n",
       "      <td>QCY T1 고장이 안 나네요..</td>\n",
       "      <td>15000원에 구매해서 2년째 사용중인데 가성비는 말할것도 없고 뽑기를 잘 한건지 아직까지 큰 문제 없이 사용중입니다.유닛도 두어번 정도 떨궜는데도 괜찬네요.개인적으로 먹먹한 느낌이 별로라 오픈형을 선호해서 버즈 라이브로 넘어갈까 싶은데 아직까지 너무 멀쩡해서 고민이네요 ㅎㅎ 고장날때까지 일단 버텨볼까 하는데 T1 쓰시는 분들은 고장없이 잘 쓰고들 계신가요?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11112</th>\n",
       "      <td>버즈 라이브와 에어팟프로 지하철에서 비교 사용해보는데</td>\n",
       "      <td>더 자세히 리뷰하기위해출근길에 번갈아 써봤는데 출근때 처음에 버즈라이브를 끼우다가에어핏 프로로 바꿔 끼우니 차이가 더 명확해지긴 하네요  오픈형이라해도 특이한 구조라서 그냥 들어도에어팟보다는 노래가 더 잘들립니다  노캔 켜면 그래도 노래 들을만 하네요.    소음이 얕게 캔슬링 되긴한데진짜오묘하게 되네요/GreenteaCat</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11323</th>\n",
       "      <td>버즈 라이브 실리콘 캡 수령 방법 입니다.</td>\n",
       "      <td>직접 방문해 수령해서 글 내용 추가 합니다제가 방문한 곳은 as센터+디프 복합인데 as접수를 통해접수 하니 디프 컨설턴트 분들을 통해 실리콘 팁 수령 했습니다.디프에서 준다고 해서 문의 하니 아예 뭔 소린지를 모르더라구요. 그래서 삼성 고객센터를 통해 버즈 담당 고객센터로 문의 하니 섭센에서 제공이라고 답변 받았습니다.그리고 매뉴얼상으론 그냥 가서 받으러 왔다고 하면 주는게 아니라 as 접수 후 귀에서 헐렁이는지 체크 후 제공 한다고하네요.(개인적인 생각으론 형식적인 절차가 아닐까 싶습니다)흰색인데 흰색은 아직 없어서 전 존버 해야겠습니다ㅜㅜ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11944</th>\n",
       "      <td>마스크 때문에라도 에어팟이나 버즈 사야겠네요..</td>\n",
       "      <td>한참 블투 이어폰 쓰다가 충전도 그렇고 귀찮아서 유선 이어폰으로 다시 돌아왔는데마스크 때문에 불편하네요..아주 높은 확률로이어폰을 먼저 끼면 이어폰 벗을일이 생기고마스크 먼저 끼면 마스크 벗을 일이 생겨서 엉키네요... ㅎ버즈나 에어팟을 살 아주 좋은 구실이 생겼습니다 .</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>135 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                 title  \\\n",
       "31                                    노트20 제정신인가요?.jpg   \n",
       "399    갤 노트20 ‘리뷰’ 영상, 언팩 25시간 전 유튜브에…관리의 삼성 ‘구멍’.gisa   \n",
       "531                                   노트20이 플라스틱이라니...   \n",
       "617                          유튜버가 노트20 영상을 사전에 올렸었군용..   \n",
       "646                갤럭시폴드2 방수방진 되는지 안되는지 아직도 미확정인거 맞죠 ?   \n",
       "...                                                ...   \n",
       "10978          LG 벨벳 정가에 사기 vs 삼성 갤럭시노트20(울트라x) 정가에 사기   \n",
       "11088                               QCY T1 고장이 안 나네요..   \n",
       "11112                    버즈 라이브와 에어팟프로 지하철에서 비교 사용해보는데   \n",
       "11323                          버즈 라이브 실리콘 캡 수령 방법 입니다.   \n",
       "11944                       마스크 때문에라도 에어팟이나 버즈 사야겠네요..   \n",
       "\n",
       "                                                                                                                                                                                                                                                                                                                  content  \n",
       "31                                                                                                                                                                    120만원 가격 책정해놓고 노트9에 썼던 디스플레이 주사율 60너프 뒷면 플라스틱 기본앱에 광고까지 집어넣고 os업뎃은 2번이면 끝나고 플래그쉽 급나누기는 중국보다 심하네요 화웨이도 저러지는 않을테데;;; s10 놋10이 잘만든거였어요 ㅋㅋㅋㅋ 정점을 찍고 급추락  \n",
       "399                                                                                                                                   http://www.m-i.kr/news/articleView.html?idxno=735276이로써 알려진 사실모서리가 둥글게 처리, 펀치홀 더 큼, 뒷면 플라스틱 재질, 구형 AMOLED 사용, 120hz 미지원 등등노트20은 노트20 울트라와 완전히 급이 다른걸로 확인.... 노트20 라이트라고 불러야 할것 같네요.  \n",
       "531                                                                                                                                                                                                                                              노트 울트라는 그렇게 비싸게 내놓고... 노트20은 여러모로 빼는 게 많네요. 재질까지...s20 판매량 몰아주기인가요 이거...  \n",
       "617                                                                                                                                                                                                                                                                           제가 그 때 바로 알았다면 영상을 다운로드 했었을텐데!!못봐서 아쉽습니다...  \n",
       "646                                                                                                                                                                   가능성 제기라는 기사는 있던데 결국 언팩에서 공개되려나요 저는 디자인이고 뭐고보다 폴더폰은 방수방진이 되면 그때서나 사려고 했어서 그게 제일 중요한데 지금 투폰 중 안드로이드폰은 노트8이라 슬슬 업그레이드 고려해야 하거든요 빨리 방수방진 폴더폰 나왔으면 좋겠습니다  \n",
       "...                                                                                                                                                                                                                                                                                                                   ...  \n",
       "10978                                                                                                                                                                                                                                                         누가 더 ㅎㄱ같을까요?전 개인적으론 노트20 나오기전까진 전자인줄 알았는데, 노트20이 나오니 후자같네요.  \n",
       "11088                                                                                                           15000원에 구매해서 2년째 사용중인데 가성비는 말할것도 없고 뽑기를 잘 한건지 아직까지 큰 문제 없이 사용중입니다.유닛도 두어번 정도 떨궜는데도 괜찬네요.개인적으로 먹먹한 느낌이 별로라 오픈형을 선호해서 버즈 라이브로 넘어갈까 싶은데 아직까지 너무 멀쩡해서 고민이네요 ㅎㅎ 고장날때까지 일단 버텨볼까 하는데 T1 쓰시는 분들은 고장없이 잘 쓰고들 계신가요?  \n",
       "11112                                                                                                                              더 자세히 리뷰하기위해출근길에 번갈아 써봤는데 출근때 처음에 버즈라이브를 끼우다가에어핏 프로로 바꿔 끼우니 차이가 더 명확해지긴 하네요  오픈형이라해도 특이한 구조라서 그냥 들어도에어팟보다는 노래가 더 잘들립니다  노캔 켜면 그래도 노래 들을만 하네요.    소음이 얕게 캔슬링 되긴한데진짜오묘하게 되네요/GreenteaCat  \n",
       "11323  직접 방문해 수령해서 글 내용 추가 합니다제가 방문한 곳은 as센터+디프 복합인데 as접수를 통해접수 하니 디프 컨설턴트 분들을 통해 실리콘 팁 수령 했습니다.디프에서 준다고 해서 문의 하니 아예 뭔 소린지를 모르더라구요. 그래서 삼성 고객센터를 통해 버즈 담당 고객센터로 문의 하니 섭센에서 제공이라고 답변 받았습니다.그리고 매뉴얼상으론 그냥 가서 받으러 왔다고 하면 주는게 아니라 as 접수 후 귀에서 헐렁이는지 체크 후 제공 한다고하네요.(개인적인 생각으론 형식적인 절차가 아닐까 싶습니다)흰색인데 흰색은 아직 없어서 전 존버 해야겠습니다ㅜㅜ  \n",
       "11944                                                                                                                                                            한참 블투 이어폰 쓰다가 충전도 그렇고 귀찮아서 유선 이어폰으로 다시 돌아왔는데마스크 때문에 불편하네요..아주 높은 확률로이어폰을 먼저 끼면 이어폰 벗을일이 생기고마스크 먼저 끼면 마스크 벗을 일이 생겨서 엉키네요... ㅎ버즈나 에어팟을 살 아주 좋은 구실이 생겼습니다 .  \n",
       "\n",
       "[135 rows x 2 columns]"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "focusdf[focusdf.cluster == 0][['title','content']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  Visualization - PCA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:16.055936Z",
     "iopub.status.busy": "2020-09-28T12:25:16.054929Z",
     "iopub.status.idle": "2020-09-28T12:25:16.105921Z",
     "shell.execute_reply": "2020-09-28T12:25:16.105921Z",
     "shell.execute_reply.started": "2020-09-28T12:25:16.055936Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  after removing the cwd from sys.path.\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \"\"\"\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "from sklearn.decomposition import PCA\n",
    "\n",
    "pca = PCA(n_components=3)\n",
    "focusdf['x'] = pca.fit_transform(focusdf['vec'].values.tolist())[:,0]\n",
    "focusdf['y'] = pca.fit_transform(focusdf['vec'].values.tolist())[:,1]\n",
    "focusdf['z'] = pca.fit_transform(focusdf['vec'].values.tolist())[:,2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization - 2d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:17.639924Z",
     "iopub.status.busy": "2020-09-28T12:25:17.638935Z",
     "iopub.status.idle": "2020-09-28T12:25:17.773923Z",
     "shell.execute_reply": "2020-09-28T12:25:17.773923Z",
     "shell.execute_reply.started": "2020-09-28T12:25:17.639924Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x276b00fa708>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.scatter(focusdf['x'], focusdf['y'], c=focusdf['cluster'], cmap='rainbow')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization - 3d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:19.190921Z",
     "iopub.status.busy": "2020-09-28T12:25:19.189935Z",
     "iopub.status.idle": "2020-09-28T12:25:19.717934Z",
     "shell.execute_reply": "2020-09-28T12:25:19.717934Z",
     "shell.execute_reply.started": "2020-09-28T12:25:19.190921Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.92, 'Clien Article Clustering (using K Means)')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "fig = plt.figure(1, figsize=(10,10))\n",
    "ax = Axes3D(fig, rect=[0, 0, 0.95, 1], elev=48, azim=134)\n",
    "ax.scatter(focusdf['x'],focusdf['y'],focusdf['z'], c=focusdf['cluster'], cmap='rainbow')\n",
    "ax.set_xlabel(\"x\")\n",
    "ax.set_ylabel(\"y\")\n",
    "ax.set_zlabel(\"z\")\n",
    "ax.set_facecolor('white')\n",
    "plt.title(\"Clien Article Clustering (using K Means)\", fontsize=14)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cluster Common words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:21.893920Z",
     "iopub.status.busy": "2020-09-28T12:25:21.893920Z",
     "iopub.status.idle": "2020-09-28T12:25:21.906925Z",
     "shell.execute_reply": "2020-09-28T12:25:21.905935Z",
     "shell.execute_reply.started": "2020-09-28T12:25:21.893920Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_flatwords = {}\n",
    "for cluster_num in focusdf['cluster'].unique():\n",
    "    cluster_flatwords[cluster_num] = list(chain( *(focusdf[ focusdf.cluster == cluster_num].nouns.values)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:22.737920Z",
     "iopub.status.busy": "2020-09-28T12:25:22.736920Z",
     "iopub.status.idle": "2020-09-28T12:25:22.814919Z",
     "shell.execute_reply": "2020-09-28T12:25:22.813935Z",
     "shell.execute_reply.started": "2020-09-28T12:25:22.737920Z"
    }
   },
   "outputs": [],
   "source": [
    "for cluster_num in cluster_flatwords.keys():\n",
    "    cluster_flatwords[cluster_num] = [word for word in cluster_flatwords[cluster_num] if word not in stopwords]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:23.487930Z",
     "iopub.status.busy": "2020-09-28T12:25:23.486919Z",
     "iopub.status.idle": "2020-09-28T12:25:23.493920Z",
     "shell.execute_reply": "2020-09-28T12:25:23.492931Z",
     "shell.execute_reply.started": "2020-09-28T12:25:23.487930Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_counters = {}\n",
    "for cluster_num in cluster_flatwords.keys():\n",
    "    cluster_counters[cluster_num] = Counter(cluster_flatwords[cluster_num])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-09-28T12:25:23.494920Z",
     "iopub.status.busy": "2020-09-28T12:25:23.494920Z",
     "iopub.status.idle": "2020-09-28T12:25:23.512920Z",
     "shell.execute_reply": "2020-09-28T12:25:23.512920Z",
     "shell.execute_reply.started": "2020-09-28T12:25:23.494920Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "[('노트20', 77), ('버즈', 50), ('언팩', 40), ('라이브', 36), ('울트라', 24), ('삼성', 23), ('갤럭시', 19), ('노트', 16), ('폴드2', 16), ('구매', 16)]\n",
      "4\n",
      "[('노트20', 59), ('언팩', 49), ('버즈', 43), ('라이브', 35), ('갤럭시', 22), ('삼성', 20), ('폴드2', 13), ('카툭튀', 11), ('이번', 11), ('케이스', 10)]\n",
      "3\n",
      "[('노트20', 37), ('버즈', 32), ('라이브', 26), ('삼성', 24), ('갤럭시', 20), ('생각', 18), ('울트라', 17), ('소리', 16), ('노트', 16), ('수', 15)]\n",
      "2\n",
      "[('버즈', 20), ('라이브', 20), ('카메라', 20), ('갤럭시', 17), ('삼성', 16), ('노트20', 16), ('거', 14), ('수', 14), ('프로', 13), ('생각', 13)]\n",
      "1\n",
      "[('사용', 14), ('생각', 12), ('T다이렉트샵', 8), ('쿠폰', 8), ('노트20', 7), ('갤럭시', 6), ('3년', 6), ('삼성', 6), ('지원', 5), ('이', 5)]\n"
     ]
    }
   ],
   "source": [
    "for cluster_num in cluster_counters.keys():\n",
    "    print(cluster_num)\n",
    "    print(cluster_counters[cluster_num].most_common(10))"
   ]
  }
 ],
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