category_word_add.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "## label ditection 파일 load"
      ],
      "metadata": {
        "id": "U2xUTEJpqIXz"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 160,
      "metadata": {
        "id": "6uAekzZhZVkB"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "df = pd.read_csv('/content/train_error_filtered_by_model.csv',index_col=0)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 580
        },
        "id": "I2Z5sUy9Z_SX",
        "outputId": "851e38cc-2905-436e-b02c-4461580f6dbf"
      },
      "execution_count": 161,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       ID                              text  target  \\\n",
              "0     ynat-v1_train_00000         개포2단지 분양 앞두고 개포지구 재건축 불붙어       1   \n",
              "1     ynat-v1_train_00001         삼성전자 KBIS 2018서 셰프컬렉션 선보여       0   \n",
              "2     ynat-v1_train_00002           LG G6 사면 BO 이어폰이 단돈 5천원       0   \n",
              "3     ynat-v1_train_00003            신간 블록체인혁명 2030·남자의 고독사       3   \n",
              "4     ynat-v1_train_00004    이스라엘 정보당국 팔레스타인인 50명 테러 혐의로 체포       4   \n",
              "...                   ...                               ...     ...   \n",
              "6995  ynat-v1_train_06995    힐만 SK 감독 고통스럽지만 내 상황 솔직히 알려야 해       5   \n",
              "6996  ynat-v1_train_06996    정의장 사드 국회동의 사안 아니라 쳐도 충분히 협의해야       6   \n",
              "6997  ynat-v1_train_06997          정치권 엘시티 수사 돌발변수에 촉각…왜 지금       6   \n",
              "6998  ynat-v1_train_06998   문 대통령 1987 관람…깜짝 방문에 객석 환호·박수종합       6   \n",
              "6999  ynat-v1_train_06999  120년 전 대한제국으로…가을밤 정동에서 시간 여행 떠나다       3   \n",
              "\n",
              "                                                    url                  date  \n",
              "0     https://news.naver.com/main/read.nhn?mode=LS2D...  2016.03.16. 오전 11:37  \n",
              "1     https://news.naver.com/main/read.nhn?mode=LS2D...   2018.01.10. 오전 8:33  \n",
              "2     https://news.naver.com/main/read.nhn?mode=LS2D...  2017.04.30. 오전 10:00  \n",
              "3     https://news.naver.com/main/read.nhn?mode=LS2D...  2019.06.13. 오전 11:49  \n",
              "4     https://news.naver.com/main/read.nhn?mode=LS2D...  2019.12.18. 오후 11:15  \n",
              "...                                                 ...                   ...  \n",
              "6995  https://sports.news.naver.com/news.nhn?oid=001...      2018.10.13 15:46  \n",
              "6996  https://news.naver.com/main/read.nhn?mode=LS2D...   2016.07.17. 오후 6:20  \n",
              "6997  https://news.naver.com/main/read.nhn?mode=LS2D...   2016.11.16. 오후 6:24  \n",
              "6998  https://news.naver.com/main/read.nhn?mode=LS2D...   2018.01.07. 오후 5:23  \n",
              "6999  https://news.naver.com/main/read.nhn?mode=LS2D...   2016.10.28. 오후 8:13  \n",
              "\n",
              "[7000 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-eb521789-8196-482a-8dce-ec37f4b3d99e\" class=\"colab-df-container\">\n",
              "    <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>ID</th>\n",
              "      <th>text</th>\n",
              "      <th>target</th>\n",
              "      <th>url</th>\n",
              "      <th>date</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ynat-v1_train_00000</td>\n",
              "      <td>개포2단지 분양 앞두고 개포지구 재건축 불붙어</td>\n",
              "      <td>1</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2016.03.16. 오전 11:37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ynat-v1_train_00001</td>\n",
              "      <td>삼성전자 KBIS 2018서 셰프컬렉션 선보여</td>\n",
              "      <td>0</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2018.01.10. 오전 8:33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ynat-v1_train_00002</td>\n",
              "      <td>LG G6 사면 BO 이어폰이 단돈 5천원</td>\n",
              "      <td>0</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2017.04.30. 오전 10:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ynat-v1_train_00003</td>\n",
              "      <td>신간 블록체인혁명 2030·남자의 고독사</td>\n",
              "      <td>3</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2019.06.13. 오전 11:49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ynat-v1_train_00004</td>\n",
              "      <td>이스라엘 정보당국 팔레스타인인 50명 테러 혐의로 체포</td>\n",
              "      <td>4</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2019.12.18. 오후 11:15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6995</th>\n",
              "      <td>ynat-v1_train_06995</td>\n",
              "      <td>힐만 SK 감독 고통스럽지만 내 상황 솔직히 알려야 해</td>\n",
              "      <td>5</td>\n",
              "      <td>https://sports.news.naver.com/news.nhn?oid=001...</td>\n",
              "      <td>2018.10.13 15:46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6996</th>\n",
              "      <td>ynat-v1_train_06996</td>\n",
              "      <td>정의장 사드 국회동의 사안 아니라 쳐도 충분히 협의해야</td>\n",
              "      <td>6</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2016.07.17. 오후 6:20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6997</th>\n",
              "      <td>ynat-v1_train_06997</td>\n",
              "      <td>정치권 엘시티 수사 돌발변수에 촉각…왜 지금</td>\n",
              "      <td>6</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2016.11.16. 오후 6:24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6998</th>\n",
              "      <td>ynat-v1_train_06998</td>\n",
              "      <td>문 대통령 1987 관람…깜짝 방문에 객석 환호·박수종합</td>\n",
              "      <td>6</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2018.01.07. 오후 5:23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6999</th>\n",
              "      <td>ynat-v1_train_06999</td>\n",
              "      <td>120년 전 대한제국으로…가을밤 정동에서 시간 여행 떠나다</td>\n",
              "      <td>3</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2016.10.28. 오후 8:13</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>7000 rows × 5 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-eb521789-8196-482a-8dce-ec37f4b3d99e')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-eb521789-8196-482a-8dce-ec37f4b3d99e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-eb521789-8196-482a-8dce-ec37f4b3d99e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-5d0e268e-75da-4874-a0aa-8088289ad4f4\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5d0e268e-75da-4874-a0aa-8088289ad4f4')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-5d0e268e-75da-4874-a0aa-8088289ad4f4 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 161
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## target 정보\n",
        "- 0 : IT/Science\n",
        "- 1 : Economy\n",
        "- 2 : Society\n",
        "- 3 : Culture\n",
        "- 4 : World\n",
        "- 5 : Sport\n",
        "- 6 : Politics"
      ],
      "metadata": {
        "id": "URYq4K0KagAQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "f0 = open('/content/it_science.txt', 'r')\n",
        "it_science = f0.read()\n",
        "it_science = it_science.replace('\\n',' ')\n",
        "it_science"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "iEwnL4RiZ_38",
        "outputId": "79b86d80-4c92-40b6-eae2-373189939c30"
      },
      "execution_count": 162,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'기술 스마트폰 데이터 구글 인터넷 갤럭시 스마트 카카오 아이폰 상용 애플 과학 기능 성공 산업 예약 우주 가입자 체험 인공 요금 페이스북 지능 모바일 카메라 발견 시대 나오다 협력 플랫폼 LG유플러스 SK텔레콤 로봇 텔레콤 소재 인간 적용 자율 치료 갤럭시S8 배터리 클라우드 드론 인증 이용 제공 개인 보안 주행 LG전자 알파고 활용 프리미엄'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 162
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "f1 = open('/content/economy.txt', 'r')\n",
        "economy = f1.read()\n",
        "economy = economy.replace('\\n',' ')\n",
        "economy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "54LXwzg2et4I",
        "outputId": "9a37b21a-281d-4605-952e-0aec33cd0a9c"
      },
      "execution_count": 163,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'분기 작년 실적 금융 영업익 특징 증가 금리 코스피 대출 상승 증권 주식 달러 목표 하락 상장 영업 은행 펀드 규모 이익 그래픽 주택 최대 전망 성장 결정 아파트 상품 코스닥 감소 주가 기대 거래 증시 대비 환율 인수 강세 퍼센트 분양 공급 자금 매출 배당 매수 회복 전환 운용 해외 수주 지분 경영 발행 반등 자산 현대 채권 공시 상반기 주주 수출 예상 영향 취득 매각 최저 마감 가격 동반 청약 개월 업체 수익'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 163
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "f2 = open('/content/society.txt', 'r')\n",
        "society = f2.read()\n",
        "society = society.replace('\\n',' ')\n",
        "society"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "PHkx2d-ceuUC",
        "outputId": "ca708024-603e-4f2b-ab92-29e4e335689c"
      },
      "execution_count": 164,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'코로나 교육 노조 학생 광주 사장 방송 학교 기자 안전 공공 일자리 노동자 뉴스 검찰 이사 대전 공무원 대학 의혹 언론 회장 파업 수사 수업 온라인 선임 혁신 교육청 보도 대구 경찰 사회 발표 방통위 기부 지역 고용 재단 수능 피해 감염 센터 교수 관리 토론회 협회 등교 시민 간담회'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 164
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "f3 = open('/content/culture.txt', 'r')\n",
        "culture = f3.read()\n",
        "culture = culture.replace('\\n',' ')\n",
        "culture"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "BOMBkqqjfuMK",
        "outputId": "fcd72211-04ab-4a24-8fbc-ed6e241b8570"
      },
      "execution_count": 165,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'신간 여행 축제 공연 주말 날씨 문화 주의보 제주 출간 한파 소설 기온 가을 작가 보다 미세 먼지 관광 충북 즐기다 시간 겨울 폭염 영하 영화 연극 이야기 오다 미술 페스티벌 행사 문학 해제 베스트셀러 소식 만화 내일 강풍 특보 음악 전시 뮤지컬 여름 만나다 콘서트 태풍 나쁘다 가다 호우 추위 바다 남부 예술 국제 기념'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 165
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "f4 = open('/content/world.txt', 'r')\n",
        "world = f4.read()\n",
        "world = world.replace('\\n',' ')\n",
        "world"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "4v2x-ia_f9DI",
        "outputId": "1c40d767-6726-41dd-cf48-0912080b8212"
      },
      "execution_count": 166,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'이란 터키 미국 시리아 공격 중국 사망 시위 홍콩 테러 이스라엘 대선 사우디 일본 협상 힐러리 이라크 오바마 난민 체포 인도 유럽 아프리카 중동 무역 브렉시트 수단 쿠르드 유엔 재개 대사 요구 화웨이 극우 군사 사태 베네수엘라 유조선 최소 프랑스 아베 우크라 에르도안 비판 군부 스페인 갈등 독일 경선 국가 전쟁 반대 논란 이탈리아 크다 푸틴 시진핑 금지'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 166
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "f5 = open('/content/sport.txt', 'r')\n",
        "sport = f5.read()\n",
        "sport = sport.replace('\\n',' ')\n",
        "sport"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "9pZFDQNXgDn9",
        "outputId": "6949ace3-80e8-4e1c-9894-3ae3c7666c83"
      },
      "execution_count": 167,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'감독 농구 프로 경기 배구 월드컵 여자 축구 선수 시즌 연승 류현진 리그 홈런 손흥민 우승 아시안 꺾다 출전 연속 연패 승리 야구 두산 추신수 다저스 남자 부상 이닝 안타 선두 복귀 영입 실점 결승 롯데 코치 구단 현대캐피탈 타자 맨유 이재영 넥센 득점 최다 역대 투수 강정호 GS칼텍스 제압 진출 도전 흥국생명 OK저축은행 신태용호 시작 준비 기성용 참가 예선 이적 네이마르 탈출 상대 최초 대타 선발'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 167
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "f6 = open('/content/politics.txt', 'r')\n",
        "politics = f6.read()\n",
        "politics = politics.replace('\\n',' ')\n",
        "politics"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "CnmUw3xmgKci",
        "outputId": "9c82c299-03c9-4e65-ec74-46e347b62539"
      },
      "execution_count": 168,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'국회 김정은 남북 여야 평양 회의 의원 북한 한국당 선언 평화 더민주 대북 사드 원내 한미 회동 북핵 위하다 대응 참석 처리 인권 대통녕 정치 북미 국민의당 속보 국정 청문회 법안 미래 역사 체제 판문점 실험 탄핵 이해찬 의장 결의 개혁 주장 바르다 인사 출마 결과 입장 개헌 김종인 채택'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 168
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 카테고리별 단어 list 더하기"
      ],
      "metadata": {
        "id": "4ensUEAXqOwm"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for index,row in df.iterrows():\n",
        "  if row['target']==0:\n",
        "    row['text'] = row['text'] + it_science\n",
        "  elif row['target']==1:\n",
        "    row['text'] = row['text'] + economy\n",
        "  elif row['target']==2:\n",
        "    row['text'] = row['text'] + society\n",
        "  elif row['target']==3:\n",
        "    row['text'] = row['text'] + culture\n",
        "  elif row['target']==4:\n",
        "    row['text'] = row['text'] + world\n",
        "  elif row['target']==5:\n",
        "    row['text'] = row['text'] + sport\n",
        "  elif row['target']==6:\n",
        "    row['text'] = row['text'] + politics"
      ],
      "metadata": {
        "id": "kmOrLwgDj8Q-"
      },
      "execution_count": 170,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "word_dict = {0:it_science,1:economy,2:society,3:culture,4:world,5:sport,6:politics}\n",
        "word_dict"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IIf7MmQiowkT",
        "outputId": "1967a1b2-62f2-4e7e-898f-955899f133d9"
      },
      "execution_count": 171,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{0: '기술 스마트폰 데이터 구글 인터넷 갤럭시 스마트 카카오 아이폰 상용 애플 과학 기능 성공 산업 예약 우주 가입자 체험 인공 요금 페이스북 지능 모바일 카메라 발견 시대 나오다 협력 플랫폼 LG유플러스 SK텔레콤 로봇 텔레콤 소재 인간 적용 자율 치료 갤럭시S8 배터리 클라우드 드론 인증 이용 제공 개인 보안 주행 LG전자 알파고 활용 프리미엄',\n",
              " 1: '분기 작년 실적 금융 영업익 특징 증가 금리 코스피 대출 상승 증권 주식 달러 목표 하락 상장 영업 은행 펀드 규모 이익 그래픽 주택 최대 전망 성장 결정 아파트 상품 코스닥 감소 주가 기대 거래 증시 대비 환율 인수 강세 퍼센트 분양 공급 자금 매출 배당 매수 회복 전환 운용 해외 수주 지분 경영 발행 반등 자산 현대 채권 공시 상반기 주주 수출 예상 영향 취득 매각 최저 마감 가격 동반 청약 개월 업체 수익',\n",
              " 2: '코로나 교육 노조 학생 광주 사장 방송 학교 기자 안전 공공 일자리 노동자 뉴스 검찰 이사 대전 공무원 대학 의혹 언론 회장 파업 수사 수업 온라인 선임 혁신 교육청 보도 대구 경찰 사회 발표 방통위 기부 지역 고용 재단 수능 피해 감염 센터 교수 관리 토론회 협회 등교 시민 간담회',\n",
              " 3: '신간 여행 축제 공연 주말 날씨 문화 주의보 제주 출간 한파 소설 기온 가을 작가 보다 미세 먼지 관광 충북 즐기다 시간 겨울 폭염 영하 영화 연극 이야기 오다 미술 페스티벌 행사 문학 해제 베스트셀러 소식 만화 내일 강풍 특보 음악 전시 뮤지컬 여름 만나다 콘서트 태풍 나쁘다 가다 호우 추위 바다 남부 예술 국제 기념',\n",
              " 4: '이란 터키 미국 시리아 공격 중국 사망 시위 홍콩 테러 이스라엘 대선 사우디 일본 협상 힐러리 이라크 오바마 난민 체포 인도 유럽 아프리카 중동 무역 브렉시트 수단 쿠르드 유엔 재개 대사 요구 화웨이 극우 군사 사태 베네수엘라 유조선 최소 프랑스 아베 우크라 에르도안 비판 군부 스페인 갈등 독일 경선 국가 전쟁 반대 논란 이탈리아 크다 푸틴 시진핑 금지',\n",
              " 5: '감독 농구 프로 경기 배구 월드컵 여자 축구 선수 시즌 연승 류현진 리그 홈런 손흥민 우승 아시안 꺾다 출전 연속 연패 승리 야구 두산 추신수 다저스 남자 부상 이닝 안타 선두 복귀 영입 실점 결승 롯데 코치 구단 현대캐피탈 타자 맨유 이재영 넥센 득점 최다 역대 투수 강정호 GS칼텍스 제압 진출 도전 흥국생명 OK저축은행 신태용호 시작 준비 기성용 참가 예선 이적 네이마르 탈출 상대 최초 대타 선발',\n",
              " 6: '국회 김정은 남북 여야 평양 회의 의원 북한 한국당 선언 평화 더민주 대북 사드 원내 한미 회동 북핵 위하다 대응 참석 처리 인권 대통녕 정치 북미 국민의당 속보 국정 청문회 법안 미래 역사 체제 판문점 실험 탄핵 이해찬 의장 결의 개혁 주장 바르다 인사 출마 결과 입장 개헌 김종인 채택'}"
            ]
          },
          "metadata": {},
          "execution_count": 171
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "word_dict[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "UqWhwdS6pGh7",
        "outputId": "ffd35167-24ce-4aa2-8689-9a9fe147a9c0"
      },
      "execution_count": 172,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'기술 스마트폰 데이터 구글 인터넷 갤럭시 스마트 카카오 아이폰 상용 애플 과학 기능 성공 산업 예약 우주 가입자 체험 인공 요금 페이스북 지능 모바일 카메라 발견 시대 나오다 협력 플랫폼 LG유플러스 SK텔레콤 로봇 텔레콤 소재 인간 적용 자율 치료 갤럭시S8 배터리 클라우드 드론 인증 이용 제공 개인 보안 주행 LG전자 알파고 활용 프리미엄'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 172
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[:1]['text']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CfNfTy4gitSz",
        "outputId": "6a35575e-8eeb-4261-e2ed-b63e737ddd76"
      },
      "execution_count": 173,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    개포2단지 분양 앞두고 개포지구 재건축 불붙어\n",
              "Name: text, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 173
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def add_text(row):\n",
        "  dic = word_dict\n",
        "  if row['target']==0:\n",
        "    result = row['text'] + ' ' + dic[0]\n",
        "  elif row['target']==1:\n",
        "    result = row['text'] + ' ' + dic[1]\n",
        "  elif row['target']==2:\n",
        "    result = row['text'] + ' ' + dic[2]\n",
        "  elif row['target']==3:\n",
        "    result = row['text'] + ' ' + dic[3]\n",
        "  elif row['target']==4:\n",
        "    result = row['text'] + ' ' + dic[4]\n",
        "  elif row['target']==5:\n",
        "    result = row['text'] + ' ' + dic[5]\n",
        "  elif row['target']==6:\n",
        "    result = row['text'] + ' ' + dic[6]\n",
        "  return result"
      ],
      "metadata": {
        "id": "p__FUJygoeQc"
      },
      "execution_count": 174,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# df['add_text'] = df.apply(add_text, axis=1)\n",
        "df['text'] = df.apply(add_text,axis=1)"
      ],
      "metadata": {
        "id": "9lw0qgwqpkLO"
      },
      "execution_count": 175,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.iloc[:1]['text']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ki3dtx-VjLw-",
        "outputId": "815af488-9390-4299-8200-be1a01e9d8f7"
      },
      "execution_count": 176,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    개포2단지 분양 앞두고 개포지구 재건축 불붙어 분기 작년 실적 금융 영업익 특징 증...\n",
              "Name: text, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 176
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "id": "PiqgXnjaivA6",
        "outputId": "c3ee381e-69a4-40c9-b030-b8917f6e0333"
      },
      "execution_count": 177,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       ID                                               text  \\\n",
              "0     ynat-v1_train_00000  개포2단지 분양 앞두고 개포지구 재건축 불붙어 분기 작년 실적 금융 영업익 특징 증...   \n",
              "1     ynat-v1_train_00001  삼성전자 KBIS 2018서 셰프컬렉션 선보여 기술 스마트폰 데이터 구글 인터넷 갤...   \n",
              "2     ynat-v1_train_00002  LG G6 사면 BO 이어폰이 단돈 5천원 기술 스마트폰 데이터 구글 인터넷 갤럭시...   \n",
              "3     ynat-v1_train_00003  신간 블록체인혁명 2030·남자의 고독사 신간 여행 축제 공연 주말 날씨 문화 주의...   \n",
              "4     ynat-v1_train_00004  이스라엘 정보당국 팔레스타인인 50명 테러 혐의로 체포 이란 터키 미국 시리아 공격...   \n",
              "...                   ...                                                ...   \n",
              "6995  ynat-v1_train_06995  힐만 SK 감독 고통스럽지만 내 상황 솔직히 알려야 해 감독 농구 프로 경기 배구 ...   \n",
              "6996  ynat-v1_train_06996  정의장 사드 국회동의 사안 아니라 쳐도 충분히 협의해야 국회 김정은 남북 여야 평양...   \n",
              "6997  ynat-v1_train_06997  정치권 엘시티 수사 돌발변수에 촉각…왜 지금 국회 김정은 남북 여야 평양 회의 의원...   \n",
              "6998  ynat-v1_train_06998  문 대통령 1987 관람…깜짝 방문에 객석 환호·박수종합 국회 김정은 남북 여야 평...   \n",
              "6999  ynat-v1_train_06999  120년 전 대한제국으로…가을밤 정동에서 시간 여행 떠나다 신간 여행 축제 공연 주...   \n",
              "\n",
              "      target                                                url  \\\n",
              "0          1  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "1          0  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "2          0  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "3          3  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "4          4  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "...      ...                                                ...   \n",
              "6995       5  https://sports.news.naver.com/news.nhn?oid=001...   \n",
              "6996       6  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "6997       6  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "6998       6  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "6999       3  https://news.naver.com/main/read.nhn?mode=LS2D...   \n",
              "\n",
              "                      date  \n",
              "0     2016.03.16. 오전 11:37  \n",
              "1      2018.01.10. 오전 8:33  \n",
              "2     2017.04.30. 오전 10:00  \n",
              "3     2019.06.13. 오전 11:49  \n",
              "4     2019.12.18. 오후 11:15  \n",
              "...                    ...  \n",
              "6995      2018.10.13 15:46  \n",
              "6996   2016.07.17. 오후 6:20  \n",
              "6997   2016.11.16. 오후 6:24  \n",
              "6998   2018.01.07. 오후 5:23  \n",
              "6999   2016.10.28. 오후 8:13  \n",
              "\n",
              "[7000 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-cf89d78c-c55f-4afc-be2b-3ecae26aead4\" class=\"colab-df-container\">\n",
              "    <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>ID</th>\n",
              "      <th>text</th>\n",
              "      <th>target</th>\n",
              "      <th>url</th>\n",
              "      <th>date</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ynat-v1_train_00000</td>\n",
              "      <td>개포2단지 분양 앞두고 개포지구 재건축 불붙어 분기 작년 실적 금융 영업익 특징 증...</td>\n",
              "      <td>1</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2016.03.16. 오전 11:37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ynat-v1_train_00001</td>\n",
              "      <td>삼성전자 KBIS 2018서 셰프컬렉션 선보여 기술 스마트폰 데이터 구글 인터넷 갤...</td>\n",
              "      <td>0</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2018.01.10. 오전 8:33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ynat-v1_train_00002</td>\n",
              "      <td>LG G6 사면 BO 이어폰이 단돈 5천원 기술 스마트폰 데이터 구글 인터넷 갤럭시...</td>\n",
              "      <td>0</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2017.04.30. 오전 10:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ynat-v1_train_00003</td>\n",
              "      <td>신간 블록체인혁명 2030·남자의 고독사 신간 여행 축제 공연 주말 날씨 문화 주의...</td>\n",
              "      <td>3</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2019.06.13. 오전 11:49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ynat-v1_train_00004</td>\n",
              "      <td>이스라엘 정보당국 팔레스타인인 50명 테러 혐의로 체포 이란 터키 미국 시리아 공격...</td>\n",
              "      <td>4</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2019.12.18. 오후 11:15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6995</th>\n",
              "      <td>ynat-v1_train_06995</td>\n",
              "      <td>힐만 SK 감독 고통스럽지만 내 상황 솔직히 알려야 해 감독 농구 프로 경기 배구 ...</td>\n",
              "      <td>5</td>\n",
              "      <td>https://sports.news.naver.com/news.nhn?oid=001...</td>\n",
              "      <td>2018.10.13 15:46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6996</th>\n",
              "      <td>ynat-v1_train_06996</td>\n",
              "      <td>정의장 사드 국회동의 사안 아니라 쳐도 충분히 협의해야 국회 김정은 남북 여야 평양...</td>\n",
              "      <td>6</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2016.07.17. 오후 6:20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6997</th>\n",
              "      <td>ynat-v1_train_06997</td>\n",
              "      <td>정치권 엘시티 수사 돌발변수에 촉각…왜 지금 국회 김정은 남북 여야 평양 회의 의원...</td>\n",
              "      <td>6</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2016.11.16. 오후 6:24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6998</th>\n",
              "      <td>ynat-v1_train_06998</td>\n",
              "      <td>문 대통령 1987 관람…깜짝 방문에 객석 환호·박수종합 국회 김정은 남북 여야 평...</td>\n",
              "      <td>6</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2018.01.07. 오후 5:23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6999</th>\n",
              "      <td>ynat-v1_train_06999</td>\n",
              "      <td>120년 전 대한제국으로…가을밤 정동에서 시간 여행 떠나다 신간 여행 축제 공연 주...</td>\n",
              "      <td>3</td>\n",
              "      <td>https://news.naver.com/main/read.nhn?mode=LS2D...</td>\n",
              "      <td>2016.10.28. 오후 8:13</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>7000 rows × 5 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cf89d78c-c55f-4afc-be2b-3ecae26aead4')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-cf89d78c-c55f-4afc-be2b-3ecae26aead4 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-cf89d78c-c55f-4afc-be2b-3ecae26aead4');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-84a0be60-3d5d-45ca-8889-14c539249b49\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-84a0be60-3d5d-45ca-8889-14c539249b49')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-84a0be60-3d5d-45ca-8889-14c539249b49 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 177
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_csv('category_word_add.csv',encoding='utf-8-sig')"
      ],
      "metadata": {
        "id": "1xRlvSM4tFo0"
      },
      "execution_count": 194,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 단어 길이 시각화"
      ],
      "metadata": {
        "id": "P6x9XD4PryYO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def text_len(t):\n",
        "  return len(t)"
      ],
      "metadata": {
        "id": "dKK5PS5cqUu0"
      },
      "execution_count": 178,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "text_len_list = df['text'].apply(lambda x : text_len(x))"
      ],
      "metadata": {
        "id": "XQ6qO4CdqYYZ"
      },
      "execution_count": 179,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "text_len_list"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XUE1IwbZqojq",
        "outputId": "8edcf2bd-5035-4219-9352-1c246e40bb8a"
      },
      "execution_count": 180,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       257\n",
              "1       218\n",
              "2       216\n",
              "3       202\n",
              "4       229\n",
              "       ... \n",
              "6995    256\n",
              "6996    192\n",
              "6997    186\n",
              "6998    193\n",
              "6999    212\n",
              "Name: text, Length: 7000, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 180
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "text_len_list.min()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ba2t5LUuq6Mx",
        "outputId": "4ebd3db7-3277-4712-8ef2-85d396e62588"
      },
      "execution_count": 181,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "167"
            ]
          },
          "metadata": {},
          "execution_count": 181
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "text_len_list.max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7xUvufD0qq9N",
        "outputId": "f0d263c1-28a0-4d81-ac07-d1ca4c6b1b10"
      },
      "execution_count": 182,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "272"
            ]
          },
          "metadata": {},
          "execution_count": 182
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "temp = text_len_list.to_frame()\n",
        "temp[temp['text']>256]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "Fy4-lz7u1Vg4",
        "outputId": "651bc215-9762-41c4-d3a0-6ec1b63f097f"
      },
      "execution_count": 198,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      text\n",
              "0      257\n",
              "5      258\n",
              "6      259\n",
              "7      258\n",
              "15     259\n",
              "...    ...\n",
              "6952   258\n",
              "6978   260\n",
              "6986   258\n",
              "6987   259\n",
              "6992   257\n",
              "\n",
              "[1122 rows x 1 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-4e433c10-15b2-4800-b8e9-fc1e1a2073d4\" class=\"colab-df-container\">\n",
              "    <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>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>257</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6952</th>\n",
              "      <td>258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6978</th>\n",
              "      <td>260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6986</th>\n",
              "      <td>258</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6987</th>\n",
              "      <td>259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6992</th>\n",
              "      <td>257</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1122 rows × 1 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4e433c10-15b2-4800-b8e9-fc1e1a2073d4')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-4e433c10-15b2-4800-b8e9-fc1e1a2073d4 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-4e433c10-15b2-4800-b8e9-fc1e1a2073d4');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-f695e9e0-d096-43bd-a0b7-4992f5a063ec\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f695e9e0-d096-43bd-a0b7-4992f5a063ec')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-f695e9e0-d096-43bd-a0b7-4992f5a063ec button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 198
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "text_len_list.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bphL1wElqzMd",
        "outputId": "7433f3c3-5683-43d0-ec00-c73239f5cabb"
      },
      "execution_count": 183,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "220.39842857142858"
            ]
          },
          "metadata": {},
          "execution_count": 183
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "text_len_list.median()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gmOPiVYjq4O-",
        "outputId": "63f8f0e9-b9d0-4a66-8ec9-b8b4c3b54030"
      },
      "execution_count": 184,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "221.0"
            ]
          },
          "metadata": {},
          "execution_count": 184
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "metadata": {
        "id": "ptINpX30rxwH"
      },
      "execution_count": 185,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y = text_len_list.values"
      ],
      "metadata": {
        "id": "cnxRgIs-rNnn"
      },
      "execution_count": 186,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x = text_len_list.index"
      ],
      "metadata": {
        "id": "rxskkQDgrA35"
      },
      "execution_count": 187,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(x,y)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "nYelD6jrsxbm",
        "outputId": "4547d8eb-292b-41eb-d11b-6f9cc626699c"
      },
      "execution_count": 191,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.bar(x, y)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "lXN68HIxrvhN",
        "outputId": "05e27abd-69b6-4aa2-8add-275b4ce19663"
      },
      "execution_count": 190,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.scatter(x,y)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "1CtllsjCsk5t",
        "outputId": "a1dac534-8672-4703-89b4-bf8bd80a38d4"
      },
      "execution_count": 192,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAigAAAGdCAYAAAA44ojeAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAACxaklEQVR4nOyde3wTVd7/P0maSxvatKG2KddWQKEWKUWBWkHFoigriLr7qODjbXXlKfso7rqKrgsuj6Kr+3Mvsuh6w0cW2dUVRMX6FEEQLKBAkVIQqOUiNC0lvdF7m/n9kU5I0pnMmcnc0pz369WXkszlnDPnnPnmezUwDMOAQqFQKBQKRUcYtW4AhUKhUCgUSihUQKFQKBQKhaI7qIBCoVAoFApFd1ABhUKhUCgUiu6gAgqFQqFQKBTdQQUUCoVCoVAouoMKKBQKhUKhUHQHFVAoFAqFQqHojjitGyAFr9eL06dPIzExEQaDQevmUCgUCoVCIYBhGDQ3N2PQoEEwGsPrSKJSQDl9+jSGDh2qdTMoFAqFQqFI4OTJkxgyZEjYY6JSQElMTATg62BSUpLGraFQKBQKhUJCU1MThg4d6n+PhyMqBRTWrJOUlEQFFAqFQqFQogwS9wzqJEuhUCgUCkV3UAGFQqFQKBSK7qACCoVCoVAoFN1BBRQKhUKhUCi6gwooFAqFQqFQdAcVUCgUCoVCoegOKqBQKBQKhULRHVRAoVAoFAqFojuiMlEbBejxMthV5UFtczvSEm2YmOWEyUjrElEoeiRW1quc/YyVMaPwQwWUKKS4vBrPfFyB6sZ2/2cZDhsW35SNGTkZGraMQqGEEivrVc5+xsqYUcJjYBiG0boRYmlqaoLD4UBjY2PMpbovLq/G/FV7EPrQ2N8VK+bl0QVMoeiEWFmvcvYzVsYsVhHz/qY+KFFEj5fBMx9X9Fm4APyfPfNxBXq8USdzUij9jlhZr3L2M1bGjEIGFVCiiF1VniCVZygMgOrGduyq8qjXKEpU0eNlUFp5Fh+VnUJp5Vm60StIrKxXOfsZK2NGIYP6oEQRtc38C1fKcZTYgtr11SVW1quc/YyVMaOQQTUoUcSxuhai49ISbQq3hBJtsHb90F+n7sZ2zF+1B8Xl1Rq1rP9Cug6jfb3K2c9YGTMKGVSDolNCQ+wmDE/Be7tOCJ6X4fCF41H0iRahk0J2fQN8dv3p2S5dh3FGW9jpxCwnMhw2uBvbOcfeAMDl8K3t0sqzUdOvUEj7SbIvyXmtaCXa5rmSUAFFh3Cp4p12MzwtXYLn3n75sJidzHpHKxOLGLt+/oiBirUjEqLRPGUyGrD4pmzMX7UHBiDohcuu0FnjMnDVi5ujql+hkPRz8U3ZRPuSnNeKRqJxnisJNfHoDD5VPIlwAgCZqQlKNIsSIVqaWKLdrh/N5qkZORlYMS8PLkewScLlsOHBqVn4+9aqqOxXKOH6KTYsWM5rRRPRPM+VgmpQdEQ4VTwp1DYrH3KoWnu8DHZUnsUT/94vysQip5qXdE4cqTmH0sqzvPei5ilpzMjJwPRsVx+T7VUvbo7qfoXC1U+pc0TOaymNXPtEtM9zJaACio4QUsULYTQA9S2dMrYodpFD1cp1DS5CTSxyq3mF7Posr2w+ilc2H+W8FzVPRYbJaAhqX2nl2X7Rr1BC+6mXaymFXOuiv8xzuaEmHh0RqYrdywBFq2NTFSgncqha+a4RjtrmdkXUvKxdHzhvxw9H6L2oeUp++mu/Ygk51wWdD9xQASVCpCS+4jqnx8ugrrmD6J4GgbdMrGRaVCLpmByZLKWa6lLtVsWyaPLZ9bkIvFdnt1fWLKHhnhfX9/017LS/9osLudepHNfj24NJryt3xlut54NeEzhSE08ESFHvcZ2TnGAGADS0hneENQBIEYjmiRVVoFImBzlUrWJNdWzoJAxQVM0baNfffvQMXtlcKXivd0uPydImoefF9/3TM8f0y7DTWAmnlXudKmV65dqDw11XbpOMlvNBz5FDVIMiESnqPb5zGlq7BIUTljm5g4mO68+qQCVNDnKoWsWMfWDoZN05Mg1aJM+WteuPSk8kOv64pzXiNgk9r2UbKni/L1q9F7PG+TbJUMVhNIedhjO7RXO/ApF7nSppeuXag8NdV26TjFbzQe+RQ1RAkYAU9V6kETpGA7D8zjwUZruIjk+1WyXe6TxKqVIjbZOSxcTkULWKUcMGhk4qreYNfBak5sThTrKw9dA2sfdau+dHPLm2nPd5MQBe/6oq7Pfr91Vj+Z19zVPpSVY8UjgKHd1eXamlQ+FbAzNyMrD8zjyk2C1Bx4eG0+pV/c5Hj5fB9iN1YSPXAO49kq+fJOt+yfoD2H60LqwJUcwezM6/J9fux9q9wddUYq2qHV4dDYUZqYlHAlLUe5FG6HgZIMVuIY7I+NX7+7BklnQVnVKq1EhVh0p7u8uhaiV5RsnxZiyfm4fJFw70/ypSUs3L9SyMBt+84iPDYcNd+Zl4Y1uVqDaRRi+xCO1/1Y3tSLFbsO3xaf5wzmN1rXhv1wm8vPFIUHv1oJYOJNwaAICln1bAExB557Sb8fTMMf4+6Fn9zoVSkWsk697d1IG5b+zkPB+Qvgd7Wrqw8J9lQdecnu1SZK2qGV4dDZFDVIMiASnqPTlMLrXN7cQRGTVN0lV0SqpSI1UdKu3tLoeqVegaBgDP3zoWBSNTg66jlJqX71kICQazxmXAEmcU1SYp0UsklFS4/eYpa5wRf9p4GO4mfaqlWcKtgYdW7cFDHN/Vt3ShaPVeFJdX6179HoqSkWtS1nPoOMmxB7PXLKlwK2aSYef57NzByB8xUDEzXzREDlEBRQJS1HtyeF+z12BVgelJ/GYcqSo6paNYIlUdquHtLoeqVeo15FbzRmJaXL+vGj1ehrhNciQa5OOjstP+SAu9q6UBsjXARaC5Ysl6/feTRenItdQB4k3WoeMkxx4ceM3p2a6oznirdeQQCdTEIwGxqvgeLwOvl0FyvBkNbWTOsOGuB/heZIk2c5BKMxQpKjqpar/AbIp1zR2KqQ7V8nafnu1CotWM0h/qAPh+0QSaY0iQqq7lOw+A6KJykZgWA58R26YdlWeDxuTyTKe/TULPnY/QmitcnG3pxK4qj79dfLBza+X2KqQmWmVTkXNlCwXA+2wjGXfWXCF0jNbqd+D8uGw/ekZS5JqXYYieJxgQmbb5zt9V5fHvHZFq9wLn2D0FWbrJeCs2o+2E4Slw2i1BJsZA9BBJRgUUCYgpaCXWHs8Hl7pQiagPKWo/qX2UojpUo5gYV3/+vedHSXZ/qdkwQ8+T6osQqXo28PySCndQG17ZfFTQj4UEo9FApAkQ05elnx70/3+kPhtSwlLVUotrqX6Xuu4DCyX+8r29ROfUtXTwrnsSAs3jD63aI/JsbpZ+ehBvbKvShT+Q2P2BPT6ccAJoH0lGTTwSIVF7k9pkkxPM/g0vlIww6kIlVHRirxmJz4FU1aGS3u56tPtH0qZI1bNCz1kOC4OYZFZS+hPJs5MalqqWWlwr9Xsk6z6wUCKpRjkt0SYq2SDX+YBv71hYOEr0+XzowR9I7P5A8uz0YqaiGpQICKfCJ7HJBkZy9HgZvFt6DFVnW2AAMH5oCtKTbIDBpynhKuImxtxBqv4jiUBx2s1wN7Vj+5E6Xju5EK4kK6fqkLSdkXi7B94j1W6Fl2Gws+osvAyw5puTYQt2LVl/AIk2M+rOdRCp+knaEDpvQtsmFK755Nr9aOvyIm2A1T9f2GuSRn2FEjp3lPItEdsWQLyqn312gcXWSOaZlLBU9j5bHrtG0rij9xo+/zIDapr4z08wG/HPb05g29EzuGJEKrEJMlzfQ7+bMDwFu4/X9zFtSZkP7H53eaaTt1BiKKHPPnDduxvbUHeuA69srkRjGEEn0WZC7tBk/78XTBuF93ad7ONkLQWuuSUWKcUG2XNO17diySfCPjyB817o2SXaTNj0q6sRbzGJ7ovcGBiG0YeXlQiamprgcDjQ2NiIpKQkrZvDSWnlWdzx+g7B4957YDIa2zolZzZkpWGA29yxYl4eAIhW/3FdU06SE8x4/paxqhekk8vkxiI2AyVfGzIcNswal4H1+6pla1tgOOv8VXtECyjsLyjSuawkrwb8motkfvKtN65nFkm/2fvwrU2G4//ZfwPn162YfnKtqVCEwp6FQtEzHDbcfvnQoPBuIQL7JHY+Bc5DoX6Ew2gAHpiShUU3ZvvPl8vUw/LeA5NFm3PlykZO2jbSsXfaLXhuTo4iGhQx729q4lEIUttwSYU7osyGQuYOAKLNA5GoUklpbO1SvSCdEiGwYjNQ8rWhurEdr22tkrVtbDsA3yafHM9tRgwlOcEc9FKQw8/BHsGvsfsKMoM2ykjmJ99643pmkfS7trk97Np8dV4eXhUwU4rtZ0NrFx4Ks1akhD2HWt/cje2ihBOgr7mAdFxD56FQP8LhZYDXtlZh2YYK8oaLROx8kTMbuRAlFW5RbfS0dGpuugKoiacPQurP0CgGPrUqqW14Xdlp0SrkUDPD9GwXb9THlS9sCmuy4FJ7uxvb4GnpxK+vuxgNrZ1ITrDg2Q0HeR2qpBB4/2mj0wVDDZ9cux/TRqfDEidOpg7s09JPD6pipmDv8fgH3+Gkpw2piVa4knzqcjVNJYFjvO3xaYJRXyzL78hDwahU/7+lhHhyt0Ya145O7xO9NCMnA9NGp+Pd0mM47mmF1+vFqp0nBa/Ft97YzxZ96DOXuZJsEfU70OchnCkynIl4V5UHHd1evHTbOHT3ePFfq3ejpdMreG92TQMIMhcKhS2TIObYAVYTXrvrsj57JOm4hs5DIPJQ9r9vrcIjhRdjyXr5BRWSPZ9kP+IzG3V2e3mzMgvxUdlpPDUzW7TPUiSmKzmgAkoAQurPJz7cH/Rr+ZXNR3nVqiT+Ib7Cf+Je+iQZE1lKK88Sh/tyqb1ZnAIFCqXC3l+oIB3gy+Y4edkXotSOcptzxNLY3o1nN5yPJlFqHMMR+IwnXziQyGdpckj00JL1ByJuB8mLlas9jgQzfvX+viB/gUjMYULrrb71fNZQV5IVyQlmNLZ2Eb8UuEIzw0VycX3HNW/FRK5UN7bjlU1HseabE5rNfQA419EDo8EQ9HIjmU9c85Al0ozcDIBb/7ZdFv+TUDYdqhFdMJMPrky7v3p/H1o6eiS1jQ3TF+OTpodQdmri6YVE/clV0I9PrUqSFZS08J8QfCrBSM1MLEq/VEkL0olROyqV0TQS1BZOAhHKQhwuK6xQTg4lYF/IDa1dfV4mSpjDuKhp6kCDSOEEiCw0k2/eiv3V/PLGw7qY+6HpCITmk9AYymFurHA3R3wNLl7/it+EJHU/YjPtPrRqj2ThhIXNxszuAWLaoBVUgwLpWR8DCVWrsmaS/8wfjg/3nkJze7f/WFevxsMRb8Gb249F3H4+laASZiYlIC1IB/j6yqXCDlSPR6IK7a+kJdrQ42XgiLfg3oJMrCs7HaRNSEu0YMqoC7DtaB22H63DuCHJeO6zQ6qMYXJ8HLq9wLmO82sk0WpCl5dBW5d4zYtc+B1ZDQBJKIHLYcPTM8cg0WrGS58fAmDApCwnjEZDUGRV4Is3NGpLalScXnn/m5M4XNOMyVkDifo2wGbCbXlD4Ii3oMfL9Bkr0iKXSpBkM6GpPbyQ8PpXPhPSnuP1fleAy4enSN6PdlWdxcf75PEDWbf3FJ6a6asj9EjhRfj7lqNoIVhfWmaSpVE8iMxbP5CFhRcJqlWddjP+Z3YObrx0EHq8DK58YZOkUEQ+Aj3Jha5/3syk3S97owH4y3+Mx7OfHRQ1Dlxjzar+39/9o+x9kiMhmVYkJ5jx3M1jsfTTYPWy027GnNzBqGnuwIb91ar3b8E1I2E2GfHerhOKqNzV5La8IZg2Og1PrtvPqWllCTTHam2C1DvROlY2sxHtGgrW4fjJpRnYfbyeaBxZU9u2x6fJ6oMi5v1NBRQAH5WdwsNryiJvGCGBoXOs6k+uh/Dn23MxO8B0JBSGfF9BpixanEgwAP7ETVE3GaMYKRk55eS+gky8vf1YTD1zdt3R+U4G3Ru0ITQ0XE5omLFItFBhsQWsZuRkYPmd48NWJhZDbVNHUGbO84UFg/uYYjfjr7fnYlByvEx3joz1+6qx/M48OO1kobCUyNF6w3//2x81b4PaML1/en3hGrTLas4JA5/ZRI9j1Z/RSyZZKqDgfMSNWgR6RwNAit0q2wJ8dsNBTPifkj6OpO1d3UH/9rR04Zf/LAuqWaIV7Hik2C3YsagQ8WY6LWOB5o5u4YP6KXp94epRnx6tptVo5qXbxmkunABUQAEASZ7NcsB6R8vtJR0YWcR6gDe09X0Z6G0zqm1uhyXOiEkaVs+kUCiUWKeuRTtn5EBoFE8v07NdsFtNEYdyiYE1LSllYlqy/oDuhJBwsOMwZdQF+PJwncatofRHBljj8NJPLwUAPP7v79DIIbhTKGLR2p9LbrSM3AmEalB62VXlUVU4yQhI5qSUicnd1IEaDcPyWGxxBjgTLGH9bNgChKWVZ3HnpOHQsMI3pZ9iNQHXjk7Dh3tO4aSnDX+5fbzWTYpJ0hMtSCEsuxAtPH79xbD3A9O0AcHvJq2hGpRe1E5GM2tchj90izUxyRnNoyfauxl40R22b56W8xk8Mxw2XDsmDSUVtaq0jxIbdPQAH+07DQD4v4oajVsTu9w8fjDe3XFC62bIyvOff691E2SBQWSJBuUm+kU+mVBbpfX3rVWcRf/UdNZVk85u8rwA7sZ2bKyoxYThyco1iEKRmdvyhmjdBM1ZWHiRv8J3KCkJZvxiahZe21qF1k71tNWU6IVqUHphzSxqJgIKzYjKFgbzMgxKf6jD6YZ2DE6Jx+SsgTAaDXA3tGHxxwdwjtAUlZ5oQWcPg/owiaP0CKtp+d7dBEd8HPUToOgep92MpTfnYNvRuqhPOhcJP5w5h5dvG4fDZ87hmypfLTCb2YShzgTMyR2M3/z7O62bSBHgybXnC2aGZj5WG1GJ2pYtW4YPP/wQhw4dQnx8PK644gq88MILuPjii4OOKy0txVNPPYWdO3fCZDIhNzcXn3/+OeLjfTk3PB4PfvnLX+Ljjz+G0WjErbfeij//+c8YMGAAUTvkTtTm79+GCry2tUq265HAlRE1NGup1Aypes5oSKH0NzIcNuQMTqKmSUq/ga8QbSQolkl2xowZuP3223H55Zeju7sbTz75JMrLy1FRUQG73Q7AJ5zMmDEDixYtwk033YS4uDjs27cPs2fPhtXqK7N9ww03oLq6Gq+99hq6urpw77334vLLL8fq1atl7yApcmd0pVAoFAolmlEio6xqqe7PnDmDtLQ0bNmyBVOnTgUATJ48GdOnT8fSpUs5zzl48CCys7PxzTff4LLLLgMAFBcX48Ybb8SPP/6IQYMGCd5XbgGFrVkTDXUeKBSWOy4fgve++VHrZlAouieaa2npgQwZa/Koluq+sbERAOB0+kKSamtrsXPnTqSlpeGKK65Aeno6rrrqKmzbts1/TmlpKZKTk/3CCQAUFhbCaDRi586dnPfp6OhAU1NT0J+c7KryUOGEElVY4oxYQ4UTCoUIKpxERmDmczWRLKB4vV488sgjKCgoQE5ODgDghx9+AAAsWbIEDzzwAIqLi5GXl4drr70WR44cAQC43W6kpaUFXSsuLg5OpxNut5vzXsuWLYPD4fD/DR06VGqzOdlYwX1fCkWvdHZ7qTmSQqGoRokG70nJAkpRURHKy8uxZs0a/2der88h8xe/+AXuvfdejB8/Hi+//DIuvvhivPXWW5IbuWjRIjQ2Nvr/Tp48KflaofR4GXy495Rs16NQKBQKpb/xUdnpoEK0aiApzHjBggX45JNPsHXrVgwZcj72PyPD50STnR1c12bMmDE4ccKXmMflcqG2NtjLvbu7Gx6PBy6Xi/N+VqvV72ArN7uqPFEXhkuhUCgUipqcbenErioP8kcMVO2eojQoDMNgwYIFWLt2LTZt2oSsrKyg7zMzMzFo0CB8/31wVr3Dhw9j+PDhAID8/Hw0NDRg9+7d/u83bdoEr9eLSZMmSe2HZNTOIEuhUCgUSjSi9vtSlAalqKgIq1evxkcffYTExES/z4jD4UB8fDwMBgMee+wxLF68GOPGjUNubi7eeecdHDp0CB988AEAnzZlxowZeOCBB/Dqq6+iq6sLCxYswO23304UwSM3zgSL6vekUCgUCiXaSB2gjCWDD1ECyooVKwAAV199ddDnb7/9Nu655x4AwCOPPIL29nYsXLgQHo8H48aNQ0lJCUaMGOE//h//+AcWLFiAa6+91p+o7S9/+UtkPZHIIXezJvelUCgUCiWqUNkzX5SAQpoy5YknnsATTzzB+73T6SROyqY0J+tbtW4ChUKhUCi6p66lQ9X7xXyxwKEpCVo3gUKhUCgU3ZNqV9fEE/MCyuj0RK2bQKFQKBSK/lG5bmDMCyietk6tm0ChUCgUiu6pO0dNPKqSlmjTugkUCoVCoegetd+XMS+gTBieAhnqH1EoFAqF0q/JHZqs6v1iXkDZfbyeFpKiUCgUCkWA1TuPq3q/mBdQaCbZ2IRqzSgUCkUcxz3qpuWIeQGF+qDEJo54s9ZNoFAolKhiuFPdtBwxL6BMzHLCaacvq1jCaTfTApEUCoUiAqMBuCs/U917qno3HWIyGjAnd7DWzaCoCH3eFAqFIo6rL74Aljh1RYaYF1AAYNrodK2bQFGR/BGpWjeBQqFQoooHpowQPkhmqIACqJ4dj6ItP//fb7VuAoVCoUQNGQ4bJmY5Vb+vqGKB/ZVNB2u0bgKFQqFQKLqC/e2++KZsmDQIfYx5AaXHy2Bt2Smtm0GhUCgUiq5wOWxYfFM2ZuRkaHL/mDfx7KrywNNCIzooFAqFQmFJtMXh6ZljNBNOACqg0ERtFAqFQqGE0NzejaLVe1FcXq1ZG2JeQKGJ2igUCoUMA4DkBJo3KpZ45uMK9GhUDybmBZSJWU5kOCITUuLjDCgcnQabOeaHk0Kh9GMYAA00yWHMwACobmzHriqPJveP+TeqyWjA4puyI7qGwWjExkO1aO/yytQqCoVCoVD0gVauEDEvoADAjJwMLCwcJfn81s4eGVtDoVBCGWCN+YBDCkUztHKFoAJKLwumjYIrqX/5ozhscXjqxjF4+T9y8e69E+FMsGjdJApFNBkOG/Y8PR3/uH8S/uvqCzHrUpcsuRWjPT9jeqIF7943UdXCl9E+ZkqSHG/GP34+CeVLrte6KbKiVZI2gAoofkxGA5bMyoYB6izCX0zNUvw+L9x2KR6YeiHmjB+MKRdfgOduyVGtfxSKXCy+KRuWOCOaO7qwdu9prP/ODTlc9rRx+5OPZ2bnYM+JejS2qecTEu1jpiTP3zoWBSNTMcAWhwnDk7VujmzMGpehSZI2gAooQczIycCKeXlwhTjNJlhMst0jJcGMV+flYdGN2VgxLw/JKv764eufVIwGYHp2mqzjowRKj/F9BZmqPsdY4r6CTMzIyUBxeTXmr9qD6sboSQtgjTP2iXiRa57cV5AJAHh54xFZrjc9Oy1ssIBd52tca9h5CgDF5dXYfbxB2wbJyN+3VmkWakwNuyHMyMnAtNHpeLf0GI57WjE0JR5vbjsWsZ/JnNxBuO2yoZh84UCYjAb0eBk44i2YO2kYln9ZKVPrz2OALzxserYrSPqdkZOB6dku7Kg8i6LVe9Ag4deX1WTEDWNduDVvCCZdOBBT/7BZt344T88cg9EZSZj7xk7F7jE924Vrx6Qrco+nbhyD1AEW1J3rQENbFxgGSEmwwGm34NkNB+Fp6ZT9nmIpHHMBNh48o8i1p2e70ONl8MzHFVH3691uMWHHk4XYfbwetc3tSEu0wcswssyTa0en49cf7JOhlT7KTzVhy2PXYPfxergb2/zzzQADJmU58ev396FFp2tcD0zPdgGAf672Jxhwv0vUgAooIRSXV+OZjytk/aWW4bDhpZ/l+h+uEvcIJTA8LH/EwKDvTEYDjEaDJOEEADp6vFhXdhrryk7DaTfrNhNvhsOGewqy/P8v93gb4EsFzdpn5RwL9tr3XZmFkgo33tp+LKj9co+7AUBSfBya27shJuWB0QDJwonRADAMt9kgcGx3VXmiSnPC4mntwu7j9UHrr8fLIMNhg7uxXbLA5bRbAANkHZPqxvY+bWUprTyLmuYO2e7VnwjdA/Q+V9k8NvUiQ8X53iVKQ008ASilRg604amtquYLD5MrbEyvwglwftzlCCXngy2iZTIaMCd3sCzXDCzQVVLh5pwvco87A6CxTZxwAkD08QD8flAPTMny/zv0e+D82EZztufQtgfORam/RW/OHYS6c/ILDErvFdGO0DwF9D1WbHtvGS9tnyqpcMvXGEKogNKLkmrk9fuq0eNlNFFV84WH9YeIHoPADv9R2Wl/BsRpo9NlvbfRACy/Mw/Ts10orTyLj8pOYVByvCzXdjlsWDHPd2015oszwSw6O2gkml62f6wfVqhPVIrdjPsKMpFoNWP70TocqWmWfjON4Vp/fL5gdiuZn8f0bJciYZ9814zlbNsGA/C3O/PwKsfzYudxYK0aPY9Vit2M5XeOR2GvOUosgfupWlATTy9KquYCM/HJdY/pY9Kwo8qD5vZu3mP4wsOKy6ux6MP9srRDCwzwLTYhLYK7qQOvbDqKhwtH4d3SY7K2wcsAR2rPYekLm4KeqdEgXqvgSrLijz/LRd25DqQl+p6ZyWhAaeXZiOZLvNmIeEsc6ls6eYUcp92MP//HeNz11i7B6901eRjyhjvhOdeBpZ8eFNUWp92Mp39yCVxJ5/sHnPeJ2lXlQUmFG+vKTsPT0ok3tx/Dm9uPEV8/wWyEyWQMux7UJFT1H0pgv1n/lAnDUzD1D5vhbuJ/5oFrWshUlJ5oAWAgMs+ECyWdmOWEK8kKd1N0mXlsZiPuLcjEP7/5MewaCAfDACl2C/JHDOzzvALnMQubmTwSE55c2C1GGAwGnOvw+Q55Wrqw9NODeHrmGEltPNvSqbqZh2pQelFaNVfb3C7rPX4ybhDunDg07DFc4WGsiUmsDVIKBp7/lwNSc8rLGw+juLwaxz2tMrfAd+1QAULKD4zZuYNQMDIVs3MHI3/EQNnUxW1dXvx0gm+cuNTTBgDPzRmLL7+vJbreZZlOzBk/GKmJVuI2BN5nzvjg/rGYjAY0tnXi7e3HRDv9sldq7fLqSjgBglX/XJiMBuSPGOh/7pY4I2+qA/azQJMin6mIPfaZ2Tl4ZvYlRG0O11aT0YDZuYOIrqMn7pw4DI/PGIPn5uREdB12HYY+L67xUtKcLJaWTq9fOGFxN7ajaPVezBrn0/qI3ZfVNmFRAaUXpVVzaYk2pA4g39iFcMZbsH5f+NAv1rTEorSJyWkPNhu5HDa8Oo9bPZrhsOEXU7NE10FKssVhxbw8UWrKJesPwKuyalKMCST0ObHIMSff3/0j7inIRArHs2HNSGvLThFdi22PmHZxqcFDiWRepidZNS9eF5rllqTPfEzPduGRwov6JF/juiafqSjw2Bk5GXh1Xh7vGKUkmPG3O8fDEW/BR2WnUFp5ts9c7PEygnuNkiRLMEEC5yNrZuRkYPmd4yWbJVPt4vZt9rk47fpLPcA+2fX7qrH8TvEpJ9Q2YVETTy9CqjkDfJvhH3+Wi9qmdiz99CCR2pBV9da3dOL3nxyQrb3//c+9glqQUM9rJc1YA+0WlC66NiikMlAFyqce/c2MMdhV5cHp+lb8+t/fgREY0J1PFiLeYvJHQ5D0x93UgVU7T8jRTWK8jC/Eub61E69sDh9GzuchL4e62NPShbd7TSVOuxlzcgejMNsVZEYicbgdaLf4TQATs5zEUUQv3TYOBaNSwx4jZV4uuGYkCkamEoft3pw7COvKTou6BwmuJCu2/mYa77wXA1d0X3K8GfcWZGLBtFGc1+QyFYXePzC1wPbKMzjd0I7BKfG4YkQqGlu7sPTT4HtmOGxYfFO2XxiSa9+QGkGy/I48TB4x0N/HVLsVv3p/H7EpDABS7FZJ2k0A+NX7+7BkVrYogZNNVzF52RdhtYIDrEbMm5Tp74sSczQUNsIzxW7BtsenYVeVB58fqMY7pcd5918hk6VSUA1KL0IqUwBYMusSFIxMxZy8IX61YbhtiP1u1rgMFK3eI6sNl3SRB6rklFTPzc4dBEuckVcFyqceZT+/9bKheLA3qiMcWw7X+s/TiyqVj9REK0alJxIdy/VsSOakGOpbuvDW9mNobOsUbUaanTso6JmRmtjqWoTnvJR5OSp9APJHDCSOZkmSOZEea0ZZMuuSsPOeFL7ovsa2Lvxp45GwERSkpoeCUan4zYwx+NPt4/HY9aPR3N6FotV97+lubMf8VXv8ybnk3DekRJDUtXQE9bFgVCqxKYwlkj7UNAWPBymWOCOem8OdvZv97KWf5uKJG33P5JrRaZLbKIXa5na/efWdr/mFExYhk6USUAElABKVqdCxoectv3M81u+rFvwFLNXkIUSgSk6Meo40ooBlukTP8EB+M2NM2IyVbPI5VgUdaZFHKWQ4bMT3TEu0EY8533Hh5qTYvrNzMHAMSdsX+nxJTWwk15eiNhZrbhruTBB9j0C4zJdSzTihhDNxcT0zORBzTznU+mzUm5QIEjGRUHzPJZI+RPIMxLRTTBuFIhhJSEu0EZlX2Wcnx1wXCzXxhBCoDi39oQ6AT3KffGFfz+VQ9Wqq3QoYEBSNQaoeZVXhrMmjtrkdtU0deHaDuGgJFi6VHGsyIGlPS0cPnHYLkdOiK8kqi+pvV5UnbLZKruRzC6aNwnu7ToZV94Zj+pg0lBwUdhItunoErhx1gb+fa745GdYcGDj2riQbb/tIVKd8anyhdnAROoYkZiSuCA8SkyipStgXJcI/RuGuS9qOu/Iz8ca2KtHmMvZ8NstqpGYcLoT2iHBJF5W+547Ks5g8YmDEpkZvbzSMGLOllEgovucSqbk0kmdA2k7SaKkMhw2bfnU1Vu88jqqzLfio7DTOtXcT90tsEkT22WkB1aBwUFLhxq8/2IdXNlfilc1HMfeNnbjyhU2cKr5Q1WNoNAapapFVhQdeLy0pMqfaUJWcWLPIzbmDiEwJ7d1eWZL4kI5V4HGRFnnMIMxdcpEr0f9MSUwv7NiXVLjR3s0tdJFGewDcavxIkn6xz4skGoSrfWLGgKQtfGMkdF3SdljijKLHKvT8SM04fEiZ92rds2j1HpRUuGUxp7ImBZLnIDUSKlwkkhzmUqnPgNQMt2SWcNTV4puyEW8x4f4pF+J/bh6LF2+7FABZP6QmQdQqAR0VUELgswWH2mVJiUTFH4la8sGpWZwqOTFmkenZLqyYlydodmps7ZI0NqFIHatIiiCSqv5J7xmoumXnUgOPv1BygjliM4HUvr+1/Zj/eYlVlwvdW4z5Q2iMSK5L2g6+4/jMq3KaccIRqRlQyXs2tPnWNuDbU+S4J6l5XO6xl8NcqnQUS7ioK7bQLOn854p+Ch1XLeaeGAwMI+Qaoz+amprgcDjQ2NiIpKQk2a7b42VwZUjirUBY1di2x6cR/4Jirymkgua6ptC54cgI084eL4OC5zcJmh3Y83u8DHZUnsV/rd7DW9qd6xwS1auY/grdY8LwFL8anvX0r2kKf60tj12Dq17cLOn5sG3m6qfQGAM+09j2J66VPF5c7XA3tmHpp8JFBLn6JbUNkZwXbr0Bvk35dzf1TfAWSTvCPbNI+u9ubIOnpRPOAVai9oaOg9AclNPMJGZvYSMYAYMkUyrfGgocby7zOF/f5ForoeZSqfu0ErB7bqibgdj5DyDsWEXyfpKKmPc39UEJQAlbMKtanL9qDwwILowmpMYMd64Q4drJmkXYX0ZCbWKLC/IJJ+w12Hs2tnX2CZcMDV3kQsxYcYVksveY3RthwvYx3LVY1b+U58O2mWuMX9l0RHAzdzd1RDRefO2It5jwUO+z5YNrLvP1Rcy9xUBi/65v7YIryUZ0fdJ28B0npR/hCn+SPkOSeT9rXAauenFzRHOE755CMIDkCMRwa0iu8Y5krQQSyT4gN2zUlVCIfug5XP0KN8aRvJ/UgJp4AlDKHheJKjwS80W4doptE2mf+YrbkZrIxJhOhO4Rqepfqpq5uLwaL288QnRspOPFxYycDNxfkEl0rJbFzfRu/xZCqPBntYhnGG4OPjg1C3/fWiXrHAm8Z7KMIdih15LTVCO3+T0UufeBaEHP/aYmngBKK8/ijtd3CB733gOTJf1ijEQ1GXhuXTNZLRSSdoYzk4TWhSEZm3CRP2LUheHU8GLNcJGq/sVAYrYIRK7xCkXpuSwH0dBGPkifs9hnyLUeQzUnkVyfi+1H64iS3ZHw7r0TERdnlD3aiXTdy2EGk2Mf4LtmoBkwbQC5WStSSPqkRL+5oCYeicgZOsmFVFV46Lk9XiZsyKSYdgZet7i8mleNPD3bJRimZwDC+j6IMZHxjZUUM1ykqn8xiMm66cvGKs94haL0XJaDaGgjH6TPWewzDJ2DQgUj5QhBnnxh+DDiQB8UPp8ulsf+/R2WzDpvZpUL0nUfmrlVihlMjn0gkHBmwEAiMdmJvT/XveTutxxQE08AcoZOKokS7RRSn5KEGpKq4iJR2evdLCDmvqTZWKX0JRrmcjS0kQ+xz0TqfFRjvpM8hyWzLsGSWcLhwVKzrgpB2r9QgV8u849UhMyAgSjRVqXNYkpDBZQQ9GyPC0TOdpJmlZye7Yqo6BZLJCFreg+LI73vwsKLZM3GykU0zGUxbezxMiitPMtb1E5NxD4Tqc9QrflOWnhwxby8Xm0KN0plvpXaP6XaQ4LYIphyt1WLDMVyQ008HIjJUKglcrVTjNkkkqJbcqjs9W4WIMlY6UqyYsG0kQCgeF+iYS6TtFGO6A05Ic3KHOkzVHO+kxYeTLSZw/qsKJH5NpJMsEq0hwQpRRblbKsWGYrlhmpQeCDNUKg1crRTjBp5o8SMsXKp7PVuFiDJzLpk1iWiM9JG2ia9z+VwbdSjmpp9diQjGckzVHu+k8wV0gKNcppZSTPQqtUepe8nR1v1bg4ngQooFGL1aardirVlp4iOVbK4mp5MF1xmB772pdjNuK8gE454S1DBQ730RY/oWU3NPju+TMsZMj1Dvc0RrcysfOPgtJOFSatt9lXDlC3HNbQyh5NATTwUYjUyDICnRTgl+UC7BaWLrlWsuBqgD9OFkNmBbV9JhRvryk7D09KJN7cfw5vbjwUdp4e+6BW9q6kDn53UTLJi76P1HNHSzMo1Dmwott7MvmKKs7LI2Va9m8NJoAIKhTibIKlqd3buIH9xNSXRMiyONTuELnzW7MD+sm1s68Tb248JHqfHED89EA1qarWenV7miNbZR7nGQY/ZUAPHiUS/J3dbtX5OckBNPBQAZGpkUlXgdMLolGiF1OzQ2e3VrXkiWugPaur+iN7MTnprT2i7hAquAuoXSIwGEzLNJEsJIlw2QZICY+GKFPYXSDOgPj1zjGwZf2MVLYqZCbVHD2YWvaC38ZCzPUpcS8+ZZNWCZpKlSCacGrk/qAzlgNSccNzTKuv1YhE9zTm9hTrrAb2YnVjkao/cz1rrcdL6/lKhJh6KKKJdZSgHpOaE4c4EWa8Xq+hhzukx1JmiDPRZ6weqQaGIRk8RBVpA6h1/V36mbDWTYpFQtbQcheCktiOcL5EB5zMtx8oa6K+Q+Jc9uXY/2rq8skdqUfoiSoOybNkyXH755UhMTERaWhpuvvlmfP/995zHMgyDG264AQaDAevWrQv67sSJE5g5cyYSEhKQlpaGxx57DN3d3ZI7QVGfaEj+pRSkybMscUZdJ5XTM8Xl1bjyhU244/UdeHhNGe54fQeuenEzGts6VZ9zYkKdKdENSfZXT0sXFv7TNyevfGET1agoiCgBZcuWLSgqKsKOHTtQUlKCrq4uXHfddWhpaelz7J/+9CcYDBwl7Xt6MHPmTHR2duLrr7/GO++8g5UrV+J3v/ud9F5QKCpDanbQg3ki2tCbij0aQp0p8iD2GVKzj7KIMvEUFxcH/XvlypVIS0vD7t27MXXqVP/nZWVl+OMf/4hvv/0WGRnBG/D//d//oaKiAhs3bkR6ejpyc3OxdOlSPP7441iyZAksluAMpHpATx7QFP1AauqKdZOYGPRoTqGhzrGD2GfY30x8envXReSD0tjYCABwOs/b0FtbW3HnnXdi+fLlcLn65sMoLS3F2LFjkZ6e7v/s+uuvx/z583HgwAGMHz++zzkdHR3o6DifJKypqSmSZouCeu5TwkHqHR+tXvRqo8fMsf0hIyeFDClFCbXOZiwXenzXSY7i8Xq9eOSRR1BQUICcnBz/5wsXLsQVV1yB2bNnc57ndruDhBMA/n+73dyF6JYtWwaHw+H/Gzp0qNRmi0JvqmYKpb+jR3OK3gtUUuQjkqKE0Wzi0+u7TrKAUlRUhPLycqxZs8b/2fr167Fp0yb86U9/kqNtfhYtWoTGxkb/38mTJ2W9Phd6LlJGoSgBV+FDtdGrOYX6EuljfqgB37MWIlpNfHp+10ky8SxYsACffPIJtm7diiFDhvg/37RpEyorK5GcnBx0/K233oopU6bgyy+/hMvlwq5du4K+r6mpAQBOkxAAWK1WWK1WKU2VjB5VzRSKUuhFvatnc0os+xLpZX6oRWgRyKWfHkR9S6fu5qQc6PldJ0qDwjAMFixYgLVr12LTpk3IysoK+v6JJ57Ad999h7KyMv8fALz88st4++23AQD5+fnYv38/amtr/eeVlJQgKSkJ2dnZEXZHPvSoaqZQlEBP6l29m1NiMbxeT/NDTdhnPSdvCJ6b43Nj0OOcjBQ9v+tECShFRUVYtWoVVq9ejcTERLjdbrjdbrS1tQHwaUBycnKC/gBg2LBhfmHmuuuuQ3Z2Nu666y7s27cPn3/+OX7729+iqKhIdS1JOPSqao5VYkW9rDZ6VO9Sc4p+0OP80IJonZMk+6ae33WiTDwrVqwAAFx99dVBn7/99tu45557iK5hMpnwySefYP78+cjPz4fdbsfdd9+N3//+92Kaojh6VjXHGrGmXlYTvap3Y9mcoif0Oj+0INrmJOm+qed3nSgBRUrhY65zhg8fjg0bNoi+lproqUhZLMOql0NnEate1vOvl2hAz+pdGpqtPXqeH1oQLXNSzL6p53cdLRYYhmhV6/UXqHpZefSs3qVoD50f0YeUfVOv7zpaLFCAaFPrAfrLBigVql5WHj2rd+Wgv6wFUuTub3+aH/11LoT2y8swkvZNPb7rqIBCQLSo9YD+5a9B1cvKo2f1bqT0p7VAghL97S/zo7/OBa5+Jcebic7l2jf19q6jJp5+RH8LB6TqZXXQq3o3EvrbWhBCyf5G+/zor3OBr18NbV1E50fDvkk1KDoiEhWkHousRUp/Ui/rgXDzi0+9CwCllWd1o/IlQc21wDWmAFRVk6vR3xk5GZg2Oh3vlh7DcU8rhjsTcFd+Jixxyv7GjdQs0x/3xR4vgx2VZ/HEv/cT1wsKJTneDC/DoMfL6LrfVEDRCZGqIPujv0Z/US/rAZL5FarejVa1uFprgVO9nuBTrze0nv8Vq/SYqdFfrr6+sa1K0X7JMf/6277INSZSaGjrwtw3dup+PVMTjw6QQwXZX/01ol29rAekzK9oVoursRZ41eutXUHCCaD8mCndXy3mglz37E/7It+YhEPIH0Xv65lqUDSGJCTsybX7MW10elh1qt78NeTwmGev0dHtxUu3jQMMQN25jqgxNegBKSpupdXiYucG3/F8n4tdC4HXSbVbBedZuPHhQmlTAml/65o7iFT67Hi4G9tQd64Dr2yuVNVEIuf8Ix2bzYdqcaTmHPJHDMTkC6WXMFAqUkjsnGP56x3jAQaYv3o3znX09Ple72YuKqBojJAKEgA8LV2YvOwLPDcnh1djoCd/DTlUs+GuEQ2qWL0gRcWtpFpc7NzgO37WuAys31fNeZ3p2S7itSCkMudqG8maDUVJU4LQ2mdZ+ulBQbOMWBOCEv2Sc/6Rjs26stMAgFc2H0VyghnP3zJWtHZWSZOolDkHALuP1+N/dxzjFE5Y9GzmoiYejSFVLXpaOsOq4vRSZE0O1Ww0mxf0hhQVt1JqcbHPle/46sZ2vLa1ivc6JRVuorVQUuEWVJlztS0Sc4ASpoRwaz8UKWY9EuTsl5zzT8zYsDS0duEhkfuM0nuW1PH90xdH4Gkhi+rRo5mLalA0RqzJJZwqbnq2Cw9fOwpvbPshSGJOsZsxJ3cwHPEWThWvWBU3H2JVs3wREEImryXrD4hSR7Je76U/1AEwEKtxQ8+blOWE0WhAbVM7PC2dSE6woKG1E84BVriS9Gl2Sh1AVoAzcB5KMRcKqbalzA2xKu3A62x7fBpWzMvr84s2xW7G/8zOwfRsF658YZPg9bnaFomZlOtcKWaB0DWbaDPj3oJMrCs7DU9Lp6j+sNeTYkII1y8SAs1JnhbfWqpr7iA697C7GaWVZzFheAp2H68PG0m1/M48LP1UnHPpk2v3o63LC1eSjfMepCZRwLdnJdrMqDvXIWmPVcM0r8ewYyqgaAypChIIr4orLq/GEx/u7+OgZ4DPRPTm9mN4c/uxPipHKSpuPsSoZhvbOjnVobdfPlRwE3E3deCVTUfxcOEowTZxjQuJGpf7vPD30ptHfHF5NZasPxD2GC7TX31LB4wGgK+CQOg5JKptsWp7qSrtwOvMyMmA1wv89qNy/0vb09KFpZ8exJHac5LNGGLWLAufiVWKWUBozSbaTGhuF6fSlzrekZiOI41IWf5lJZZ/WdlnrvJFUj09cwxS7FZsP3oGr2yuFLy+p6ULC/9ZBgB97hH4jEjGzt3Ugblv7OT8jmTfkDLnSNFzugZq4tGYQBUkKaGquOLyajy0ak8f4QRAn8kcqHIkUekqEUnEp1p3N7bj5Y1HiK7x8sbDgm0KNy7h1LjhzgtHtY5MUOyzdTfx/xrlMv0Vl1ejaPVeXuEEIeeQqrbFqu0jVTfXNrf39mVPH42CmHnG1TaxZgM+E6uc0VWBhBNOApFi1gskEtNxJOakUELnKl8kVdHqvWhs68So9MSI7xH4jCKdqyR7rBRTlRj0mq6BalBkpsfL4Osjdfj33h/R0tGN9CQb8oalICM5njciINFqxvTsNGw6VItur/A9AqMPdlSexeMffEfcPlbF6/tlbRCl4p42Oj1IzRmo9ky1W1FDuNmsKzsdVh1KCqumBvomxgKAxR+F1x4AwapXtk8k5/HBIFg1HKhuZqMiGtq6YAhjagpnkiIxB5Cq6x3xPrMAO4Yk5xkNwCt3+MK7e7wMlqwPr9pe9OF32HuyHtuPnBVojQ820iRSdXOq3Ypfvb9PlnnGEtgmNvw9VAOQYDHBaDDgXEe3/zMXxy9kobHjM8PwnRNpf5wJFtHnu3q1Eo54Cz4qO8Vr2gudy3nDUvDk2nLZNQHhYO/1xL/3o+iakbq6Hqn5e0ZOBpbfmRekEYyUgXYLng0TfKE1BoZhoq4UbFNTExwOBxobG5GUlKR1c/wUl1fj0X/tQ2sn9y8YLvMKl1kmHMkJZuz+7XSUVLhlSdgjBqfdErQwwpkBuDAASLCa0BLGo1wsCwsvwppvTvRRkV82PBkff+cWfT1rnBEdJFIiIVzq5tDvA01NfHMiOcGM/7hsCG/kSuAGU1p5Fne8voO4jew1HPEWovPee2Ay8kcMxJ83HpakiSBpz9Mzx2DppwclqbQH2i24a/Jw/OkL+drGrjsuYfCVTUfx9vaqoBTjzl6/r8JsF6cQSTp27FiLOUcIVqW/7fFpMBkNWLahAq9trSI+PznejOVz89DY2tXHryNwPkrZ39QiNPGjXq733gOTec3fXJFrkeC0m7FjUaHi2YBDEfP+pgKKTLBmASEMAFbMywMAouO5+MXULPx9a5Wqv0AiRe4Nob/xqsQ5wb72ApPWfVR2Cg+vKRN9jWmjL8AXh84IHn9fQSYmZjklz1/S9jw4NUvUi5Nl2ugLsImgH2J5lSMxIGuqCJ3bXM8l8BzSsfvz7bmYnTtY1DnhCG2XWOEkcP8K12+pzy7Wua8gE29vP6boXhlubqoBFVBUpsfL4IplG1HTLKx2MwBIT7KCYYAaQm/1UMRqLvSAK8mK9m6vLn9N6QFXBHMi9Bfx9iN1mPsmt0Oe0HVIppUzwQxLnAnuJuW0d+w6kTJnQjV9crUncIwB37q/8oVNvL9opZwTynsPTMbELKeocwIJHYtADUdntxcX//Yz4pdhYJ4ZofZEyw8SvbVTibkbitbO/GLe39QHJYTQsLfkBAs8LeH9BnZVeYiEE8C3GMI5LpIQqXDCbv6QoS2k5Ax2YOPBWlXuFY1E8hzYqIyV26twT0EWvBJ/c5Ce5WntAqCsoCl1nVhNBkU2eHaMvz5Sh7g4I2qb21HX3EEUmfTWth+QPciBunMdqG0Kf04gGb2RFVIjbAbaLShddG2Qn5iXYbCz6izKTzWhvqWD+JnfNXkYnv7JJbDEGVFaeVawPXp66YeDAXDnxKFYveuk1k2B3WJUXDh5euYY3JWfiW+qPHjp80MQk3ZBC6gGJQDSsLdQvwGxKnWtMQAozE7DxoraqNlIKGQkJ5jR2tGNzh76ZJVAzV/crElJ6v4ybfQFeOueiQCk+buFwv7y7uj2RtV+J0SC2YTWLvn84vTMfQWZ+HDvKU4fNynZc6Ug5v1Nw4x7ERP2FhqiurFCvDOmlowdkoQSKpz0Sxpau6hwoiBqjezCwov8LwupEU2bDp3xpxOQEjYfChtGf6yuJaLr6I1YEU4A4K3tx0SnXdASauKB9CyKj//7O8THmfCJhGgRLfnuxyatm0AJISUhDt09DJpljHCiRC9nmtvx5lc/4K78TH+SLilmniXrD0BuJfl7u07AlWRDTRN/hJXefDv0isNmQiNh3ho1WPRhcIoErc0+1MQD8WGZFAqFogZGA/DAlCyMH5aiWNSUFBYWXoSXNx7m/f4XNIon6lHKmZaaeESixyJJFAqF4mWA17ZWYe+Jelw7+gKtm+OnsU1ZZ06K9uihOCsVUKDPIkmU6MNKmPCoYMRAzL/6Qjjt4rN3UmKT17ZWYeuROq2b4Wdd2emw3/+dak+iHqb375mPK9CjUV4LKqDAV4iJzfhJoUiFNAPt9sqz+Oc3JxUPKaT0L7p05PwsNHf101JKpLCFJbWACijwFa+jCcQoauJpofONQqFEByUaRarGvIDCRvBEK7Y4IxzxVPtDoVAoFGX4qOy0JmaemBdQpGZp1Avt3V40ttFf4xQKhUJRhrMtnZqYeWJeQKERPBQKhUKhhEeLd2XMCyg0godCoVAolPCkDrCqfs+YF1DYLI36K5PkI9FGk/1SKBQKRWM0CM2KeQHFZDRg8U3ZWjeDl59OGKJ1EygUCoUS49S1SK+4LpWYF1AAYEZOBlbMy4PTrr9omGtHp8NuNWndDIqGWEx61e9RKJRYQQt3CCqg9DIjJwM7FhXqyqSSZIvD1z/UoYUWkItZ/uPywRiVNkDrZlAolBjFAF9dnolZTtXvTQWUACxxRvxMRyaVpvZuLN9cqXUzKBryz29O4UB1s9bNoFAoMczim7I1qWxMBZQQCrNdWjeBQqFQKBTNSUkwY8W8PNkrGpNCBZQQJgxPgQaCIoVCoVAousJiMmC6hj/aqYASwu7j9dCocCOFQqFQKLqhprkTr2w6qtn9qYASwkaNiiJRKBQKhaI3Xt54GMXl1ZrcmwooAfR4GawtO6V1M3QPjXqlUCiU2OGZjytosUCt2VXlgaeFFt4TooeawCgUCiVmqG5sp8UCtYYWDqRQKBQKpS+0WKDG0MKBFAqFQqH0hRYL1JiJWU4kJ+gv3T2FohXU34hCoQCgxQK1pqTCjYZW6oNCobBQfyMKhQLQYoGa0uNl8MzHFVo3g0KhUCgU3UGLBWrIrioPqhupkyyFQqFQKIHQYoEaQyN4KBQKhULpCy0WqDE0godCoYSD+gtTYpGFhRdpViwwTpO76pCJWU447WaaqI1CoQAACi504oIkGwanxCM53oJnNxzUukkUiqqkxMdh/tUjNLs/1aD0YjIaMCd3sNbNoFAoOmH7Dx7srPJg7GAH0pLUzwFBoWhNfVs3Jj63kdbi0QOFGpaVplAo+sPd2I75q/bgWF2L1k2hUDShobULD63ao4mQQgWUACZmOeFKor4oFIqeiI8zwKCRAwjT+/ferhNIT6RaFErsokXBQFECyrJly3D55ZcjMTERaWlpuPnmm/H999/7v/d4PPjlL3+Jiy++GPHx8Rg2bBj++7//G42NjUHXOXHiBGbOnImEhASkpaXhscceQ3d3tzw9ioCSCjfau3u0bka/hzobUsTQ1s2A0ThhnLupA1NGXaBtIygUDdGiYKAoAWXLli0oKirCjh07UFJSgq6uLlx33XVoafGpP0+fPo3Tp0/jpZdeQnl5OVauXIni4mLcf//9/mv09PRg5syZ6OzsxNdff4133nkHK1euxO9+9zt5eyaS4vJqzF+1J+oyyUbjy97lsOH+gkzi46eNvgAJFpNyDaJQCDhzjqYioMQ2aqfjMDCM9N8mZ86cQVpaGrZs2YKpU6dyHvP+++9j3rx5aGlpQVxcHD777DP85Cc/wenTp5Geng4AePXVV/H444/jzJkzsFgsgvdtamqCw+FAY2MjkpKSpDbfT4+XwZUvbIqKRG0mAGMGJSHDYcNlmU68ta0KNc3qpyAm4ebcQRiSkoBJWU4YjQbUNrXD09IJ5wArPOc6sPRTsqiIp24cjT9tPIKWTv1ot/7r6hFItJnw5y+Oor3Lq3VzKCqQYDailT5rSgzz3gOTkT9iYETXEPP+jijMmDXdOJ38GebYRsTF+W5VWlqKsWPH+oUTALj++usxf/58HDhwAOPHj+9zjY6ODnR0nH8JNzU1RdLsPkRTFtkeAOWnm1B+uglf/3AWLR36eWkHkpxgxh9/lutP7lNcXo0/fP590DgbQFZ/6tkNh5RppESMBuBwTTO+OFirRf0sikZQ4YQSyzjtFtWzyUp2kvV6vXjkkUdQUFCAnJwczmPq6uqwdOlSPPjgg/7P3G53kHACwP9vt9vNeZ1ly5bB4XD4/4YOHSq12ZxEaxZZvQongM/zu6TC9zxZ81moEBitL3cvA2ykwgmFQokhbs4dpHo2WckalKKiIpSXl2Pbtm2c3zc1NWHmzJnIzs7GkiVLpN4GALBo0SI8+uijQdeWU0ihWWSV4dF/7sPxs614e/sx+jKnqIrBAFUda21mIzX1Ufo10zVIwyFJg7JgwQJ88skn2Lx5M4YMGdLn++bmZsyYMQOJiYlYu3YtzGaz/zuXy4Wampqg49l/u1zcA2C1WpGUlBT0JycTs5xITjALH0gRRWtXD5Z9dgjupujUUFHUZe6koXAl2WRx/GYY4K7Jw2S4EhlUOBHGlWTFP34+CUUaZibtjyTZ4jDAqmxS+KgoFsgwDBYsWIC1a9di06ZNyMrK6nNMU1MTrrvuOlgsFqxfvx42W7B2Ij8/H/v370dtba3/s5KSEiQlJSE7O1tiNyKjpMIdddE7FEp/w2Q0Ysks+fYAg1bJUyiczM4dhIKRqTjklteHMNZpbu/GuQ5l03RERbHAoqIirFq1CqtXr0ZiYiLcbjfcbjfa2toAnBdOWlpa8Oabb6Kpqcl/TE+Pz1/iuuuuQ3Z2Nu666y7s27cPn3/+OX7729+iqKgIVqv6iZB6vAyWrD+g+n0pFEowzW1dcMRbsPzOPDjtkWs0hyTHy9Aqily8v/tHvP/tSXxx6IzWTelXKG3JTE4wa2LeAUSGGfP9Inn77bdxzz334Msvv8Q111zDeUxVVRUyMzMBAMePH8f8+fPx5Zdfwm634+6778bzzz/vj/QRQs4w49LKs7jj9R0RXYNCochHhsOGp24YjSfWlkf0y/CW8YPw4d7TMrZMHAuuGYlJmU48/K8yeFo6NWtHf2XupKH44uAZ1DS169LHzQDAkWDuF9p5OcKLWRQLMxaSZa6++mrBYwBg+PDh2LBhg5hbK0a0RvBQKP0Vd2M7Fqwpi/g6WgonADAqfQCmXHwBnpuTg4dW7dG0LUpBmipACViT4PxVezRtBx8M0C+EE0C792TM1+LpDxE8Kf3YwZd6EcQeenvRSIXdW6Znu+CIV9aJ8eFrR0EDFwG4HDYsLByl/o0BDHcmYEZOBlbMy4PLoc993ADAbo3+LNhavSdjXkDxFQiM3iJgyfFmzL8qerzi37nncvzX1RfCZiabeivvvhxOu3B2YYr+yRkkb/SdnglMarWryoPGNuWcGJ12My4bngKpddxI1yIXL902DgumjVK9kKLRANyVnwkAmJGTgS2PXYOnZ47Bf+YPx1M3jka6TvZ0Br58VQOiWEgZqEGCNhZlxfoowGQ0YMmsS6JWBdvQ1oXnPtNXplU+rHFGPPyvMlFqz4aOLjw3Jwfze59Pf/l1HYuUn9YuekNtE0BgUiul1eOeli788r29ks+flOXElsN1ks6ta+lASYUbHT3qhlk/MCULljifYFVcXo1nPq7QdTbwczpOqinEbA0StLHEvAZFTWK94F1Ht1e0TTYt0eZX4zoITFl2i4nmtKEEsbDwoj4mgAyHDb+YmqXYmnTEn9f6SVWPi5nHDW3SfR2mRlCluaSiRtUiq0YD8IupWVh0oy8cnS9LNeU807PTkBGBCSxwLqtNzGtQerwMnvm4QrHrGwD88afjkJ5kw6/e34dWkQXvnHYznv7JJUgbYIWXYfDL9/ZGtBmxJFlNmJU7GAyA9ftO41x7t2y/MI0GSFY3sxjgs2+zqsXp2S4sWV8BgL/vKQlm7HyyECajAbuqPHA3tsHT0onkBAv+59MK1Cu0iSaYjTAYDaqXHjD0qgX4hlqO5xDtGAA8OPVCLJg2EruqPKhtbkdaom9e9XgZvP5VlSL3XfPNCSyYNhImowG5Q5NFn28AYIsz4t37Jsq25rnIcNhwV34m3thWBXej+GiYT7+rDnuO0By1W4zwMkAbQaK7RJsJu56cjvheobKz24sn15arrlVVUhtnizPAEmdCU7t8JsHyU03Y8tg1+KbKg6LVe0TPpcC5rDYxr0FRulAgAyAjOR5Go0FSRlVPSxdcSTYUjEpFnMko20bV1NGDVTtP4B87T6BZJuGEnb5yvBQZBCcH2lXlERy/+tYu7D5eD5PRgPwRAzEnbwjun3IhBiXHKyacAL4iclrURXpwii9RYui2IedziHYYAAUvbEJJhRv5IwZidu5g5I8YCJPRgHdLjyk2RtWN7dhV5QEAPL1uv+jzGQDupg4crmlWRDgx9P4tvikbljgjFt+U7f9cDELDx/QKJ7zXNRiIhBMAaG7vQdnJBgA+zcnkZRs1Cd9WclnNv3qkrMIJ4JuLu4/Xw2g0SJpLgXNZbWJeQFEjfKq2uT2i+7Dn6j0k2uWw4f6CTEWuTdp3ruPe+KqS6Nxpo8OrutUyHRkNPrUs3/1SEsx4dV4eFt2YzRnBoORziEY8LZ2Yv2oPisurgz4/7mlV9L4lFW4Ul1fjgz2nJF9DShuT44PnTXKCuc9ccjlsWDEvDzNyMgBA0WiY+woyec2zYgX72uZ2v1nH0yK/4BY6dmrTpJCmTK53kNrEvIlHjfCpSO+RarfKch0SBliNyL/wArR1dmNb5VmicxZcMxIFI1MxMcuJXVUevLn9WMTtMAB45uMKfwbDuuYOovNqm9rx0ueH4GWAlAQLkhPMxJkrw/1KMACwmgxYdMNo/PmLI6JNdaQUjBiIh64agStGpgIAdlSexfbKMzjd0I7BKfG4YkQqJl840K9ZmpGTgenZriCTlnOAFZ5zZOMVKzAAlqw/gOnZLv/YDXcmKHrPdXtPYcN+7grtpEhp4/I782A0GvqYs94tPYbjnlYMdybgrvxMv5MpS+Bcqm1uR11zB5Z+ejCi9gNAepJNtsKNzngLfvPhd4poMZ66cQxGuxJx11u7FLg6GWu+OanIdSN9d2gVZiwqk6xekDOTbI+XwZUvbJJkfwXC2yNZP4ptj08DAMn3cSXZsGRWNqZnuyJqqxJk9PaP3fR7vAwuf7ZEtl83CwsvwppvTsScE1yGw4bFN2X7f+EKwRXJoHZF32hgYeFFeLg3b0dntxejn/5Mt6awDIcNWx67Ble9uJlozQfuN4H+Alxzg2R+Rbo3KkFKglkxc60ryYbbLx+CP31xVJHra0Gk7yC+ORUJYt7fMW/iMRkNfvurGNhHFe5BB/pRSL0PANQ0tWP+qj0oqXBLthUrRWgRKZPRgDm5g2W7/ssbD8eccAL4sqlymSW44Itk0FI4MfD8v9a8vPGwf0wtcUY8MKVvwVO9IMY/hP0udD3yzQ2S+RXJnqUUSvqS1TS1R7VwwueLxvUOIlmTfHNKTWJeQAHO21/FFChLS7RAqFiqAcC00elB91l+53jRGR/Z9wxr8uCyFSfa1A1hZv0gAn+B9XgZlFae9XvZU6TD9P49uXY/1u49hdLKs+jh+KnPRqHp5Rcui8thw6vz8vCqDrN8PvNxBXq8DHq8DK6+OB3TRl/QZy0bAFw7+gLcljdEkzY+fO0oOOIt+KjslL+AYrhxTE+y4pHCUejo9vrnSri5EbindPae81FZ33kmdc/SG6xfV7iknEqvISWGcKDdwrvOQv2MAH5fIxI/JS2IeRNPIJ3dXkxe9kVYz/DkeDOWz81DxekmPLtB2D779MwxuH/Khf5/R1qckC3a1ONlsKvKg5IKN9aVnSbyZk9JiIM1Lk5yca2bcwdhSEoC8kcMDPKDAKIjWVK0w6WW12OxSwOAn0/JxFMzLwHgE6J2VJ6VFOLI4rDFwWQyor6lk9+kKsKkxWU6TLSZMCwlASfq29AcEEmhdrh2cnwcbOa4oKi1DIcNT88cgxS7FbXN7T6/NANQd64Dx+pa8d6uE32Ov/3yoXh54xHB+zntlqD9I3Se6XGOhcNpN2PrY9Pwz29O9PG52X60DnPf2Klh2yxh57C4a5mxY1Gh35eIfScE+h7xaT64jgVAfH4kKFYssL9jiTPyZi1lH9Pzt45FwchUfH6AzPkt1As/Um9o9nyT0YDGtk68vf0Y0WQ3AFh2y6UAILm4ltNuwa+vv7jP56waOeok3SiDVcsH/qpRyrs+klwPDIDXvzoGo8GARTf61MMFo1Lx/K1jRWdsZtfdC7fxz132mAenZOG1rWR5TV7eeLjPZ83tPThQ3dznc7V9VBrauoGQ1PjuxnYUrd6LFfPyMDvAhFpcXo0/bTzc51m5G9uJhBMAfX7chM6zjRWROfqGQ86cIuw8eG7OWAywxQX9MGSp09h5/ObcQXh7+7GI+h3Yz0BHZza9Agl8x8pVsVguqIknhOnZLjxSeBEc8eHVXaTe9YOTz6vSerwMcTQKH6l2K3q8DLYfqcMT/95PNMmNBp9n/4ycjIjCCT8qOx2kDt5+pA5fHT5D3I5AkhPMcCVxtyHDYcN/T4ue+kJqEaiWZ9XwqQPkrznyyLWjkBJS/4hLBSzE37dW4avDZ/ymg2mj0wWvEfp7LT3J6l93PnNDXp9rsMf8ZsYYRU0ySps57BYj7DzmUS6TzL+/PYnHPuCOaInkpc+aF3/9/j588O1J/Gv3jxFcLTyRFBsMfR4pdjOW3zme0+zMzkHS9bKw8CLB7KsJFhMGWMX9xucz0YcjtBYZn+kltK9cJmH2uO1H6vDS54fw0uffY/vRuj7Hkl5LaaiJJwAuM0VyvBn3FmRiwbRRQeou0ggAo8FXN2L8sBRZTCCPXDsK//z2pOjrsKYhFlbF525sw2/XlaOFMGw2VB0cCf+4f5IvgV1AeKwryada/M0HZfj3ntOy3CeQRJsJN+cOwTBnPN7cdiysuctuMRGPi9q898BkNLZ1Ysn6A3A3yfOr0ADAkWCGLc4UZC5w2s34n9k5uD4nA69sOoq3t1dJMtU47WbR0V1sBNuMnAwUl1fj0X/1zcZsAFCYnYbyU01Ra2IUY56Scw1qyVM3jsF9V/qclKVGCyXa4oLMcYHmKa793JVkRXu3F42tXZz3Co16eWXTUby1vQqNAfM9VPvhtJsxe9wgfLSvmtd8ExoNQ2L2ZM/Z8tg12H28PqzphTRSq7i8Gk98uL9PaYLkBDOev2Us77iJjSoMh5j3NxVQeuEzU7DTgEtiXbahglilrDX3FWTidzdd0ufz4vJqzQol/vn23CB1NYtSbTIg+DmyzxzgNhncV5ApS04XJbivIJPYvBcpfhPK1Cz8fWuVqqa8wHtHy1rTI2oXSyQhcP3LZSYWmquB48BnKmT3CNI2hd4TAtcNRGgPInFSJX13keyrvwgzbqTtEYKGGYuE1Ns9VM216MZs/GKqfsMUA/mo7DSnGk/JOkRCcCX/UapNGSI82lkVamFvkjg9sq7stKwvHAP4M+WyKv/Xv1JXOAm8txzCiQE+M0qswVUsUQ9BOYHrX65oIaG5yqbdT04wIz2JP+pFTHQce8z6fdWc0VbhomGE9iAhYUBMpNaS9QcE+xJu3NhrqWnuoU6yEK7Hw+B8PQLWTMKaSLIHOTD38qH4h0IZAOXibEsnfvWvMvz0sqH+CByl6xDxEVoIMBC52pRgMeKRay/CBUk2v9mox8vgza9+CPLsD82emWr3FWUs/aEOp+rbYLeaVK2zYzUZ0NEjvAHIreJnAMGKtHpNaEYKA6Clk6zuS3+AXWcLpo0MKpYoV4bYSHDazZgwPMX/7x4vg+rGdtnmWLjrsHP9H/fn9TExO+It6PEy+Pponah9iH1HVFQ34aXbxvkjrLhMMqERNNOzXUF7EJ8ZhzULlf5QB+C8kyvJu+vd0mNEpmChcQt9DyoNFVAgvs5LtIbUris7jXVlp/32xo5u9TdroeQ/YqNS+NS0/+9nuUG/PpZtqMDrX1UFLcBnNxzEA1N8pdvzRwxEcXk1it5Tp3Q8n8qdRDihUEgJXGfsS+WjMum1geTC09KFq17c7E8cpsV++sWhGkzMcuIPn38fdO8Ei0lyKYtXNh/FK5uP+n02Ql/kUv07uHxHXtl8FAmEOae2HiEr90GCmnV5Yk/fyQFpnYFjda28mRmjiYbWLjy0ag+O1bUoeh8pyX/EtOkXU7OIVKOsr1DorwMv4zMdLNtQ4bfPkgonA6zSk9Fxqdwp/QutTSgD7RbedaZVXZVQ3I3teGjVHjyk0X761vZjnPeWo84WV6ZeqVl9w+1NpG3dcrhOROvDo+b8oRoUABOznHAlWQVVYK9/dRQmo0l3zmZSWfl1FRzx5iAPdT4MvT/5SfqeHG/Gn/8jF4drz6Hq7DmcaepAepINWal2ziJlLJ3dXqz8+hhR2w3w2XxZD3cuNa3JaEBntxevfxXef+G1rVVIiRcXSplgNqK1s0e0SjolwYxhAxPwh1suxaGaZlSdPYd1e0+L2hR92TANkhPuSUXthGVaYQDwv/dNhKe1E6l2K371/r6gqCY+nHYznv7JJXAl2ZA7NBkFL2zSJNom0WbCUzeOgSPegrbOHqzeeTzIrDkxy4kMh03zGjtK3lvrOlSsr0tgwdNwviKBx4aag0h8R0iI1FE6nGleKaiAAl/SmjsmDhNMbHSuwwug/9iw61u7hQ/qhWSxs8vq8qwU3PvON5wvsze2VXGqM4vLq/Hk2v3EtTZYe+ju4/VobOvso6Zl1aan6tuIXqr1IsNma89JMwPVt3Zh4T/LJJ3LMjt3EMYPS5GccE8s7HN9QEQiNL7rRIN8wwCIMxn9ESazczOI+u1p6YIryeZX6/MlfVSa5vYePPr+Ps7vWLPm4puyVZs/WqCH2NRAnw2AzFck1L9jV5VHtjQCkQongPp1eaiJp5fMVLvWTYh6XA4bCrPTUFJRyysUVIdRfUqpgFxS4Q6rNv1KRturXmBDGaUm3BMLazZbdGM27i/IjOg60RL1FuhvJkYoC7TP80VokPoNKAFr1tx7ol61+RPr1Da3i/Zz5Pt3pFx1USrRcckCiUrVgmpQetGLXVYMFiMw5aIL8MUhdV/CA6wmzBnvS3Y22pUET2sn0hJ9au1LFhcTXYNE9UkCX7gt+9nO3l8v/Y1nPq7Atsen+b3/tx89g1c2V8p6j+uy03F5Zor/GZdWnsW0MemicsM8PXMMUhOtSEu0YcLwFFz14mZZ26gUaYk2Ser1uuYOv3kRgD9KjI2+8DLAmm9OhjXpxZuNaOtSVlP7+ldVOLR0tH/+nK5vxbcnPPj37lPopI7asnKk5hxSCLMwh76H5H4vTR11AZE/yp9/lguLxaR4XR4hqIDSi17ssmLo9EJ14QQAznX04N0dxwEgyFv9za9+IDKniFF9hsNuNQna+JXe6LUgVB2cP2IgJmY5sWrnCVkjkP6vogb/V1ET9JkryYrkBDPRfYwGIMMRjxsvPV90Tu/O5YF2dinq9aWfHuxjxiypcIuKUlFjznoZ4N3SY7h/yoX48vuaPhFuFPl4ZfNRAMI+XMkJ5j7+HaT+kUKw8/qu/Ey8sa1K8D137/9+449w1BJq4unFZDT4Q94o5AR6oIcWRhSitrk9okJkauYn0SOB6t+SCrcq4dE1TR3E9/EyQNHq8+Y8NcMTpcLgvJ1dansD14Seo/6Oe1p5I9wo8iM0xg2tXSgJ2Q9NRgOWzOqbAVwKi2/KhiXO6H/PhdOHBEY4agkVUAJgbcZOu7iiaLEMm7lxyfoD8Irc5dyNbXh3xzFJ99U6jFMPHHY3o7TybG+WSHU2EinvsSXrD2D70TocdvetFKw3khPMftOj1EKM7JpYuKaMt5ifHhicbBOMcKOcx2ZW9nVpgG+tfHX4DF76/BD+UHwIr2/9AW1dXiwsvKiPXwgpiVZTUBFF9j2XlmgRONPn79amYT0yWouHg85uL/KWluBcB3mUC0Uc/S16YOqoVFw6xCG7HwgJame77e8oUYhRSRLMRrR3e0VpQQwAFt0wGs99dkixdvUHrHFGTRJacuFKsqJg5EBJRVQDiwGy3P7a19hRVS94bqItDi/edqlsDrK0Fk+EbDpUQ4UThelPwgkAbD1Sp9kvDSqcyAsbGRYNwgkAtHaJE04A3/r7ulK+5F39Fb0IJwDgbuqQXOGdTc7JmluXbaggEk4AoLm9O2wiOSWhGpQQerwMrnxhky5txv2B/qY5CcRuMaFFQ3UoRR4SbXFobo+OHyjJ8WY0iMzhA/jW4QCbCc3t6s1Xp92McUOS8c0xD85RoVoT7BYT5uUP81UsFqlxczls2Pb4tIijeagGJQK0KqAXK/RX4QRARMKJPYLU+RR5iRbhBIAk4QTwrcPm9h5fhmgVSLTFwdPShc3fn6HCiYa0dPbgtS3ihBOgb+SlWlABJYRoiDSg9D+omYaiBddcfIEq94kmoY/Cj9rvRyqghKBUwjYadUKhUPTG/VdeiF9MzYIGObgoUYjaCU1porYQJgxPgdNukbXIV6LVhNJFhXhv13G89H+HRTleJVpNMBqNRAX95MRqAuT+UZ9gNsBoNFIVL4WiE7q7vLj64nRclJaIsh8b4GWA9ftO60rjMcBixN0FWWB6s/BqUYAx1tGiUCBAnWSDKC6vFpXxkZRpoy/AwermqPJtsZgMNOU1hdLPCXVaz3DYMGscWXFEtejPjvXRAKtck6sWD3WSlYCSGR83HToTVcIJACqcUCgxQOgqdze24+9bq3DTpS5N2sOFFjvRAOq07kerQoEANfEA8IUWR1KwLhxC9Re0QI9t0hOuJCtevG0cFqzeg0YdqbrVgP21RKdHbMLANwd2/nBW66aojt1iwj0FmbhiRCouz3Tiqhc3R/zD0mL01UwTIi3RgtpmfZmukuPNWD43D5MvHKhJoUCAalAAKBtarEdBQI9t0hNLZl2CKRddgPuuzNK6KarDpmmnPpOxCwOg9py6Pm96oKWzB1eOvAAFI1P9NWsiXQckwgkAzJ2UGeGd5KehrQtGg0Ez4QSgAgoAGlpM8WG3mPBqgCozM9WucYu0w0FYHp5C6U8EvgvYmjUZDuUjVzJTE/DqvDwk62zdaf1upCYeqB86RdEn07PTkWgzo8fLwGQ0INUurVhcf8AWZ8Q/fj4JtU3tqDvXgYa2LtWjKBbdMBp/+7JS9Qi2UIScNBNtJsydOByvbv1BrSZRFCIt0YYeL4NdVR7UNrcjLdGGTb+6Gqt2HMPLG4+gVaFM0WmJNuSPGIhpo9Px+4/LsWrnSUXuIxat90AqoACYmOVEhsMWdY6sFHlZV3Ya68pO+wtrJdr09WtGTdxNHfj2WD3WfHNCs3VhNBg0F04AYX+c5vYe/PNbfbxQKNIZaLegvqWzT6kTJX32AsN3lYoijQiNbb3UxAPAZDRg8U3ZWjeDEoCW64ItrLXpYI2GrdCelzce1nSz3Hb0jGb3Fkt9q/aCFCUyxg11oGh130hOJYUTAFh8U7a/QKWuhBMAdee0LZhJBZReZuRkYGHhKK2bQeklOSEOt4yXN6wtOT5OlI13bdkpWe9PEceeEw1aN4ESQ3xdeVbV6DU2fHd6tkuxKNJI0dr9gQooASyYNgquJOqPogfqW7vx4V55y3vbzHF47uYcPD1zDNHxnpYuOO0WrbWcMYuesplS+j/tXeQZvrkQs0847WY8PXMMZuRk6LZAbXKCWfXMsaFQASUAk9GAJbPEh5bRF1h0UNPUjqLVe3G6oY34nJtzBwGI7BnrZX7kDJYv6zKFQvFh6P17cGqW//+FqG/pQtHqvSgur9Y8UoaPhtYulFS4NW0DFVAC6PEySLSacf0laaJeKi6HDY9cO1KxdslNgsWIAdbY849mc3z8aze5Q+O1o9PxSOFFcMRLd5h1OWz4253jNQshNAC4dvQFmJM7WJP7q0VyvLpz2m6h2UYpQJItDrfmDcboDAceKbwI6QRaeHYveuyDfUiOYG8hRUoqEwOAZz6uQI+GibNoLZ5eisur8cSH+9EgwtltwTUjUTAyFROznNhReRZz39wpS1vkxGIywBIXXKCPZpIlIznBDFucCe6m879wpNQF+cf9k/DtcQ9e3nhE1vZJoT8+ezYS4t4rMvHcZ4eIznHY4mAyGVHf0qlL2z9F//DtBa4kKy7LdGLzoVq0EIYl2y0m4mNJmT4mDTfkZKC+tRNLPz0o+TrvPTAZ+SMGytYuWotHJMXl1Xho1R5RwgkAjEofgPwRvjTAdS3aejvz0dnD9Kke3N9eUErR0NoVJJwA0lLAf3GoRhfCCdD/nn1gJMSPIkx3t08ciufm5ARdg0IRA99Scjd14JPvqkUJHHILJwDwk3GDcMuEIaJM2lxoaYKKeQGlx8tgyfoDks5NHXA+iY3W3s4UdRHzUltXdlqxdugNg8pv+8BCZsOdCcTnrd9XjenZLqyYl4f0JOWTUdktJiTwmITsFpPuMohS+NEw87so2KRzkUYjavluiz1HhBB2VXngbpKo/QgQoSdmOeFKskq/FiWqYADEm41oE/D8T0kwq5Z5VQ8wDPD0zDFw2i3wtHTC09qJ5ZsrI7pmSoIZf7l9PHZWnUW3l8G59m4YDAZkDkzAnZOGo+xkAz4qO4WL0hKJTVjVje1Yub0K9xRkIdFmxtw35DfPXjY8BUOSbcge5MAFSTakDbDCyzAo/aEOpxvaMTglHleMSMXkC33q811VHrgb2/D7TypUz6sy9/Kh+Mc3+kk2N2/SMMAAMAwDh80CGNTNYsxHos2E5nZlssn6rh8nS/RaRm/ytx0/nIWnRfpcctrNmDA8JeL2SCXmBZRI1FeBZh1fBNAleGjVHjmaRYkChIQTAGjpiL1Q2dREK2b3OuQu/ViadjKQ8cOS8Zt/f8cZivnshoNBAkmCxUScjnzppwfxxrYq3JjjiriNXHx7vB7fHgfW7TsfLp/hsGHxTdn4zYy+OX5YO3+8xaT6PmKK05cyfdXOE/7/Z8esx+vFa1urNGkPqzSZmOnEF4eUSyA4NCUBFdVNEV+HTf72xL/3R3QdT0sXrnpxMxbflO2vUaYm+pqVGhCJ+ir0XLmSvQ2wxuEXU7Oo2jeKYSM8Onv6mdMHAey6KC6vxpvbj0V8vU2HzvDmiQjVlrSJtOW7G9tlaaOY+81ftQfF5fw5fmbkZKheOE6MeUxt3I3teGjVHtWEE2ucsc/Yuxw2PDg1S1HhBEDEwklKghmvzssDAMxftQcNhKUinHYL73ckc1YpYl5AYU0zYjDgvAotlEiTvaUkmLHn6en4zYwxsMWFD2N02s3440/HqZJMLN5sxOMzLkYKFZo4SUmIQ9E1I7DgmpF4976JsoRxJ5gNsFvFhbIm2UxYdMNoJNm0UY6y66LHy+CZjytUvz8rr5CuB//xBnWcZdn7hQvf7PEycMRbsPgn2Vh0w8Wi54BYMhw23JWfKXofVAu1RfyUBDN2PVmI9x6YjD/fnov3HpiMLY9dg/X71H9BiyElwYydTxaKzkyb4bBh++PTeIUUkjmrFKIElGXLluHyyy9HYmIi0tLScPPNN+P7778POqa9vR1FRUUYOHAgBgwYgFtvvRU1NcE1TU6cOIGZM2ciISEBaWlpeOyxx9DdrY0qnDXNkBIYNWDi8JYKTPYW+q2B5//ZfxsALLtlLCxxxl7fmPDmJ09LFwYlx6sSjdDW5cULxd+LfgGohdbtqW/txpUjL8Cvr78YcSYjapoj90Vq7WLQ0iFOI9DU3oNlnx1Ck0ZZWGeNy4DJaNA8O6bYbZRh1HsRMvD5wOyq8vT5rri8Gle+sAl3vL4DC/+1D8s++x5mk2+bVmqOL74pG5Y4o6h9sD/jburA7uP1yB8xELNzByN/xEDsPl6vy2yvgdS3dmH38XpRa88A3/MvO9kQ1r8n3JxVElECypYtW1BUVIQdO3agpKQEXV1duO6669DS0uI/ZuHChfj444/x/vvvY8uWLTh9+jRuueUW//c9PT2YOXMmOjs78fXXX+Odd97BypUr8bvf/U6+XokknEo1NCohMGog3PVWzMuDyxGsSXE5bHh1Xh5e5fku8LqkvjG1ze2891OCxl7nPYfONCkuhw33F2SKOue+gkzfc5cpURKbdVGvmSGlELomMhw2TM9O4z3+71urdJ0dUyzJCeY+YyBXFEfoGBWXV3MWjItkzSUnmHnNxaw5gN1z2H2QL9oolgh9NmLmc4bDhl9MzUJGyH7Mrp3Q+WM0+BIpykFtcztxW5MTzP53jpj3jZqI0gMXFxcH/XvlypVIS0vD7t27MXXqVDQ2NuLNN9/E6tWrMW3aNADA22+/jTFjxmDHjh2YPHky/u///g8VFRXYuHEj0tPTkZubi6VLl+Lxxx/HkiVLYLHw28KUZEZOBqZnu7Cj8ixKf6iDlwFSEixw2i1oaO2Ec4AVriSf+ppLc8J3vV1VHtQ2tyMtMfjccN8B5L4x7HHs/VZur4ooKY8Q5zUoDIquGQEDDLh8eApKDtYEObapydMzx+CegizsqvKI8ieYnu1C/oiBskVxfFR2Gk/NzI6qkPNwiecMAGxxRvzj55NQd64DaYk2TBiegqte3Bz2ms98XIGXfjpO7qZKRmzkhdNuxtM/ucS/3gEErdUJw1Ow+3g9apvbkWq3Agbg66N1WP6luGilwHnCmsS4ngUD37Owmgz+6ChSlt+Rh4JRqfjNjDH+vQ0wIH/EQEy+cKB/z+nxMthReRblpxoxfUw6PtonPTSeJLpNCxZcMxKOeDOe3SC8P4au4cCUEuFg9yKT0YDfzBjDucd3dnvxbukxHPe0YmhKPEa7krCz6qws/i1i9h52bog5T+29LSJDdWNjIwDA6fQt4t27d6OrqwuFhYX+Y0aPHo1hw4ahtLQUkydPRmlpKcaOHYv09HT/Mddffz3mz5+PAwcOYPz48X3u09HRgY6O8yrzpqbIvZy5MBkNKBiViuaOLjzzcUXQLxnWk5xEOAm8Hl8GvnDfAT7fmAyHDe7Gds5Ni82eGegHYzIacE9BFt7YVsV7nlzUt3b7w0e1zE460G7xbwhiQr0DfYgmXzgw7FiTcralE7uqPFEVch6uvwx86m6jweCPyimtPBtWfcyqgsFAcP768o8YUNOk7Fxtbu+B024hzhrraemCK8kWtD5D12qftcuAWEDhWrtCankGQE0zuWDC3mNybzvZvY19IQUiJYt2ONq6vLKFy8oBOxbZGUn4/Sfho8q4nk1xebVgriz2PHYvAvj3eEucEfdPuRDF5dV93jNSCW03ybtjckDbpLxv1ECyk6zX68UjjzyCgoIC5OT4fCDcbjcsFguSk5ODjk1PT4fb7fYfEyicsN+z33GxbNkyOBwO/9/QoUOlNlsQPjWr2p7MJqMBi2/KBsDvy8IlMJGcJzdaZiednTsoaEMgtaMHjl3gmEVKbXO7aL8mvROo1iVV8da1dAjOwyWzLsGSWdzHyA1b9JEUsapssZmkQ9euEqpzkh9UUrNoC5E3LFnW60mF7f2scRkoWr0n7I8Grn2VfR+IPU8IvveMFELvL+XdIfV9ozSSBZSioiKUl5djzZo1craHk0WLFqGxsdH/d/KkMgmFOru9eHJtOa+aFTjvydzjZVBaeRYflZ1CaeVZYu/m0PM6u7281wnny7JiXh6mZ7s4zw13nhxh0HpienZwDguhEM1Qu3vgeSvm5cFpj8wfJdDkpnaoqFKk2sVnTE5LtAnO3xk5GbzHkD4H0u2SzRpLet3Qfgqtd9JxGWi3cPqwyak657tHKJFk0RbiypHy+FSIJfT96XLYsPzO8Vi/r1pQexbqBxjO7MZ3Hsl7gfS6pHD5RfKtq/QkKx4pHIWObi+2H6nD9qN1/rZOz3Zh+Z15SAmJ5iHxu1QKSSaeBQsW4JNPPsHWrVsxZMgQ/+culwudnZ1oaGgI0qLU1NTA5XL5j9m1a1fQ9dgoH/aYUKxWK6xWZUPgisur8eTa/WGz7rHq61c2HcWab05wmoDCPUQulV6oeST0Ony+LCUVblz5wibeNvCdBwBvba9CY1t49avRoG5kQygDrKY+NYRC4Qv1DvQn2l55pk/WTr5fATNyMtDdzWDBmr2i28ulAmXb8fWROsxfvVuwP3rlV+/vw5JZvnklVhUs5IvFd8yE4SmY+NzGsL/snXYztj42DVNf3MzrlxHYHpPRgGmj0zF52RdEx7NwrdvQdSo0LgBgt5pQuuhaWDiSopGMK4lJzGk3894jlIiyaIchOcGMN776QfbrAr5CfC/eNg47q84CMGBSlhNGoyHIR4r1D2LnGmlUy0u3jQsygYk9j2SeiLkuKaHtZgldV8fqWvHerhO8dcHYH1OBa85pN+PpmWM0EU4AkRoUhmGwYMECrF27Fps2bUJWVlbQ9xMmTIDZbMYXX3zh/+z777/HiRMnkJ+fDwDIz8/H/v37UVtb6z+mpKQESUlJyM6WR80uFlbdRpoS+OWNh0WbgPhUeqECNtd1WFsmG/JWUuEmMkOFnmcyGlBS4RYUTgDggSm+Z6tV+O7PLhM244VTObI299/MGIM/3T4ej10/GgUjU8OqKIvLq/FLicIJX3tMRgOmXHwBXvrpOM7Q82igpun8vJKqPg6dh6GEHrPpUI2g2eG5OWMxwBaH5+bkhA3rD2yPJc4o6nhSky87LuEE+paOHmw6VMP5Hcm4hjOJsf15bs5YIuEEUC4io6G1S5Ywey6WzLoEUy66AL++fjR+ff3FmHLRBSgYmeqfN5Y4Y5+5JsYsGYiY88S4Bsg97uHMi+y6ssYZ8aeNh8Omrmho7eqz5upbulC0eq8mSdoAkQJKUVERVq1ahdWrVyMxMRFutxtutxttbb5qiQ6HA/fffz8effRRbN68Gbt378a9996L/Px8TJ48GQBw3XXXITs7G3fddRf27duHzz//HL/97W9RVFSkuJaEC7nUbUzv3xP/3o/tR+uCVHti7iGUFEfI258B8OTa/Vi7t6+KkTVhhcMA4G935mHRjdmqhS5zMT3b1RsC3FfJx2emiYS2zh489sF3kuZBit2M+woy4Yi38Jr6IjVlDLRb8MtpIyS0LnJC5+SMnAzJqmBSFfiS9eGTvCUnmP3mPRJTUuC1HfEW3FuQKdh+krX22Af78OHuH1FaeRbTRqeHNekZED7Z1fRsFx6+dlSfxGx2qxHXX5KO8lNNsFvi8PC1o+CI75vplNSsw45/nUJChBBShfRb8wZjerZLtHldjFmys9uLN7/6Ab/7qBzfHiPL+ZFqt4adJ0DwcydtTyJhskWh60XyjmPnuRZJ2gCRJp4VK1YAAK6++uqgz99++23cc889AICXX34ZRqMRt956Kzo6OnD99dfjb3/7m/9Yk8mETz75BPPnz0d+fj7sdjvuvvtu/P73v4+sJxKRW93W0NaFuW/sDFLtib1HYFKcUC9wkmt5Wrqw8J9lAM6rGAEImrDYex+pPQcgWEXobmzD0k8PEkdCSCVQxV5S4YbNHAcEaHxSEsx49uYcWYWTZRsq8PetVaL65bSbMTt3MD4qOw1PSyfe3H4Mb24/FtbUx2XKONvcgf/+596wjsas2v6dr48RtU2JMM/AOdnY1omln1YEmUlIVMGkKvBXNh0RTFLY0NoVtD5ITElc93fazZiTOxiF2a4+x5Osteb2Hjz6/j7/tcJpfcKt63CRNOc6vCg+UAMcqMErIRHeyfFm3FuQiQXTRhE5xIb2P1yYuVJIvd+/95zCF4d8mvfAcRIyr5OaJTcdqsHcN3YQO/2z58EAosg29rkTt+dXV6PghU2izJFcyPGO45u3SiPaxMP1xwonAGCz2bB8+XJ4PB60tLTgww8/7ONbMnz4cGzYsAGtra04c+YMXnrpJcTFaZOaWyk1Z6BqT+o9uM4Tey22jsVDIk1YoWaiOXlD8NycHFU2M7bQlc97Pri/Da3yqhyXbajAayKFEwOAn04YgpXbj/XZPIRMfYGmjMa2TvxyTXjhJFBtf7K+lah9E7OU20T4zItCqmBSFXhxeTWvjTyU0LUQzpTEd//6li68tf0YGts6+7zgxa410vXFlaBNaiRNY1sX/rTxiD9JIB98/Y+2SlFcZgiSNSdkPssZnITXv6oSJZwAvr2q7hyZJop97qRm0niLSZQ5ko83voqsmjiL0BxTgpivxSPG+/6Ra0cSXzdQtedMkJZ8jqttYr39pW5AXCq96dkuoqgUqZEwbPRBuFoSctaF6Oz24vWvxBUgG2i3hI0KIG0fidrVaACW33lebU9a0G3qqFTFIojWlZ0W3W8hUwl7Xme3V1T9HtLkWaT3lxqZI5bQBG2RRNKQ1vaRM2pEb5CMQTgz4F9vz8UXB2s5z+Mj0KQmJckZqVlSjPmSi85uLzbJVODwo7LTqpt5tFFb6AgS73tWxf5NlQfAUeJrs6q9Q25xieVCVXdslkc2w60zwQJPK3nSJilwqfR2VXmIfuX9+Wfj8fC/9hL/ogR8phs2+oA0GRibFC2cWh/wjR/XMe+WHhOVw4WdB0J1OUJVulz3J1G7ehkgxW7xn58cb4ahN7oqHCkJFjjiLdj1ZCG+qfLgq6O1eG2LOC0RF067mahex8slh1EwMtU/ziRJyKob2/HO18fEqaIJO0R6/6+P1CEuzhgUSeRKsgmam0gJXNfsM91+9EzEkTRC883LMLqvIxMp7BgsWV+OvOFOpA3wZfitO9eBVLsVXoZB+alGzBk/GCkJFqQmns8MvnI7mebkrsnDcFmm0589uO5cB0orz2LC8BRJSc5IzJJijuPi3dJjsgmmbCJKNc08MS+gsOq2+av29LHHso+fVbGLTcbEcrK+jfjYUNWd3FkexSC1HoWnrRNzcgeLSjvPANh0qEZUXYiSCjce/VdZWJ+GcH4Pxz1kJhMWdh6IqVvBd/8bc7hD6kPh6qMQrE8E288nbsgGwyDicvWkz/SVzUfxyuaj/vt3dJP5w7xcclhUe0jXI+nz+s+3dwWt/+QEMzoJ2y5E4LouqXDLlkE0EL75plRtHS38V4R4d8cJvLtDuORGcoIZz98yFiajgXgfMBgMsMYZ8esP9vVZz7PGZfCuLwbhi8uSvPBJjwtF7B4nhNq1eGLexAOQq9GO1bVwnS4IqWo+9J5KZXkkJVR1KUaVWZhN9gJmaWzt8tuRScf5re19f3EH2qOF/B5aO6Sl4iYdh2N1rbz3JxXeuPpISuBYjB+WIukaLAsLLxL9TNn7kz7P1i5xeWLInwPZ/UNftg2tXWjtlCd3DbuuAciWQTQUvvkmVx8CWVh4keSIND3Q0NqFh3rXBun+3NrRzbueIxX+lULMu4eEqKrF058Ip0ZjTSxvbRM3CVnV3l35mYL1cZLjzVg+N8+fSEzJLI8k2C0mbDt6Bl6G8beJNJmUl2HgbmgjMkewML3nL1l/gOgcvvo/gdfxlTTkP+arI2dE1RFasv4AEm1m1Da1CxZtS0mIw3u7ToT1exBKhhdpjaPQsZCKK8mKBdN8/ldiahaxx6z8ugqOeDMa2+QTtJ12MyYMFxa6erwMVmtUxJLFGmfAvVdk4qqL0jDtj1/KrnVg1x3ffFPiXpdlpmCYMx6elvOFVHOHJoeNOtEjz3xcgU2/uhrPbjgouNZKDtaGXc/hePzf3yHRZsbkC31akNCitIEmp9CCgsOdCbgrP5M4v00gd04aLkvxWK1q8RgYhvQVoh+amprgcDjQ2NiIpKQkRe8ltaAT+zoI1IbMX7UHALcZKdThqbTyLO54fYf0hssIqw6dkZPhj3oJd6xWGh8pTBiejN3HG7Ruhi7hmpt881gLSLI3/3njYeKoIKVR0iSysHCU4v1k2x+6xlkTx/p91VHp6/LeA5Px5fc1qmhBWLMhn1Yrw2FDzuAkfHGwNkhgMhp8yTMX3UiezFRO9wAD+r6jpCLm/U1NPGGIpKBTcoI5Im9stW194WDVoWy+EKFjowkqnPATrsaHQwc1hkiyN+tFOAGUFeiaZNROsYS6TDg4UqEDPufU17ZWRaVwAvj22khNoKQImQ2rG9tRUlHbR5vj7fUhW7aBLMpNinuAlUdDkxFttXhigUhD8zq7e7D/VKNfrWcyGoi8sVkP/CM1zfJ0hICUhDj0eIEmgfLof/8q8kgQin55fMZFOFXfjuOeVmQOTMCTN/pyMYRGhUwbnQ5bXAUAZYXRlAQznrxxDH7/SQWaOeYmOxefXLsf00anB6nASbLR9idIk/gJ8fTMMUhNtCIt0WeyWb3zOI57WjE0JR5vbjsGpZ+5FqTarfj1B/u0bgYRr39VhUcKL0bZyQbUNrf7I5RKf6jz1xybnDUQiz8S7x5gt5jw1j2Xo7apPch0RxoxpATUxMODnCaWQBNJOKSak/oTjvg4xJvjwhZEEyKwsJpcIaLRDol5IdRnyGgArh2ThvJTTUFz0m41oUWlwoe35Q3BB3t+FDzOabfguTnnMwzrybQTLSQnmLH7t9P90YOxsBdlOGx46afjMPeNnVo3hZhEWxynwC4H7z0wWfEwYmrikQE5TSyBHuN8RGJO6k80tnVjdq7vJSNFZg8srMZeh0JmXgj9qeJlgJKK2j5zUi3hBACRcAIAnpbOoOgtKpyIp6G1CyUV7pjai8RkgtULSgkngL5cCwBq4uFFiXAqNgqETR7U3ePF2rJTaOnoxo4qDzWf9PJR2Wk8fO0orPz6GBpE2tZT7Gb8z+wcTBudLlgYkdL/iDRiKdZZ/FE5DAZjv9+L7BYTHpx6Ia4ceQEW/nOv1s3RDex7jy+5pdpQEw8PPV4GV76wiTikkqIcdosJLSJyOSQnmNHV41X1lz6FQtE/ekwupxdYEx9XIkGSiDlSqIlHBgILOlG0RYxwAvhU1VQ4oVAooVDhhJ+G1i78ofggUVFPtaACShhm5GTgr7eP17oZFAqFQqEozus8kZpyFmkVAxVQwlBcXo3ffUz9GCgUCoXS/wknewQWpVQL6iTLA+vJTlWCFAqFQqH4UDPSh2pQOIg0SRuFQqFQlEGjnGGUXtQsGEg1KBzsqvLERA4ACoVCiTbe/s/LYTQa8MGekyg+UIOObq/WTYoZkmxxqhYMpAIKB3pLVkOhUCgUHw/8Yze6erzEldIp8jF+WIqq+VCogMLBsboWrZtAoVAoFA46qcZEM6aOSlX1ftQHJYQeL4PVO49r3QwKhUKhUHTFnZOGq3o/KqCE8LPXvkZNc6fWzaBQKBQKRVeUnWxQ9X5UQAnggf/9BruPN2jdDAqFQqFQdIfa/plUQOmlrbMHJRW1WjeDQqFQKBRdkmq3qno/KqD08tyGCq2bQKFQKBSKflE5Bw0VUHo5drZV6yZQKBQKhaJb6s51qHo/KqD0kjkwQesmUCgUCoWiW9TMIgtQAcXPkzdma90ECoVCoVB0SYbDpmoWWYAKKH7+tPF7rZtAoVAoFIoumTUuQ9UssgAVUAD4MhO+/lWV1s2gUCgUCkWXrN9XjR6vuvUFqIAC4N3SY1B53CkUCoVCiRqqG9uxq8qj6j2pgALguIdG8FAoFAqFEg6aqE0DhjtpBA+FQqFQKOGgido04K78TLXzz1AoFAqFEl3QRG3qY4kzYtroC7RuBoVCoVAouoUmatOIn08ZoXUTKBQKRTIqR4BSYpBjder6a8apejcdMzHLiQyHDdWN6joByYURwMg0O8ZkOHDL+MGIizPC3dCGX//7OzA0QilqMQCgj48ihAFASrwJZ1t7tG6KLhlgNcJoMKCpnY5PJKz55gQWTBupWj4UqkHpxWQ0YPFN0ZtN1gvgcG0Lthw5g7buHhSMTMWtlw3Fg1OytG4aJQKocEIhIW94MhVOwnCuw0uFExlQO9SYCigB7D1Rr3UTIqahtQsPrdqD4vJqAMCiG7Pxi6lZVP1LofRDDAZgenYadh9v0LoplBhBzVBjauLppb9lk33i39/BbolD3bkOpCXa8MKtl6LsZD1qGjuwrbIO7V1erZtIoVAiYIDVhB2LCjH95S1aN0VzTEZgcpYTwwYmYLjTjh8b2vBR2Wk0t3dHfG2zyYCuHqrLZFGzYCAVUHrpb9lkG9q6cddbu7RuBoVCUYhzHT345zcnotZvTk56vMD2Sg+2V8pvfqDCiQ8DAJfKBQOpiacXmk2WQqGoiYHn/8Xw9tfHZGgJhRIedn4uvilb1YKBVIPSy9CUeK2boGvizUa0UbMQhSIbKXYz5uQORlK8Be/tOgF3k3hNyI/1bQq0jEIJxuWwYfFN2ZiRk6HqfamA0ktzW5fWTdA1gcJJos2EZuoRT6FEhKelC29uPwYAcCVZsbBwFDJT7Ui1W/Hov8pQ0xw+KRb90UBRmgXXjETByFRMzHKqqjlhoSYeAMXl1fjL5kqtmxE1UOGEohbTs9NggOoZtlWnpqkDf9p4BNY4IwpGpeKZ2ZcInjPQblGhZZRYZlT6AOSPGKiJcAJQAQU9XgbPfFyhdTMoEZDhsGF6dlqfUGoDALvFpEmblCQlwax1E1Rh5th0LL9zAh4pvAhJtv6t7GXdMJ/5uAI9XgbTs11IFnjOZ1s6lW8YJaZRM2KHi/696gnYVeWhXvBRyACrCT+dMATXXZLhVz92dnvxbukxHPe0YrgzAXflZ8JkNGDl9ios/fSg1k2WDYvJiOQEMxpbu3gTuSVYTDAaDDjXEXmYpRpcOXIgvj1eHxT+/un+Gmwo/yxmMiEzCE6E1dAa3uxMzTsUJTEagHqNheCYF1DUTDpDkY+Wjh6s/Po4Jl14Xv1oiTPi/ikX9jk2NVHdEuFKU9vc4RdMQlPhs/9u7YwuM9y2o2c5P48V4SSQ2uZ2fHeygejYnMFJKD/VpGyDKDGJlwGKVu/BCmOe6s6xLDFv4tFahUWRRqhKPBz97Rkz8AkiyQlmpCcF9y09yQpHfMz/7sBAuwVTR6Vqcu/kBDPsFulba6rdirVlp4iOferGbOQNc0i+FyVyDP3cQYpkj1WKmN/J2CKB7sZ2XnW5ngq2uZKsePG2cXho1W60RNmvZLlhVeIvlxwO62kudyFIo8H3y55kTqQNMKOtmxGd0dJqMqKjh1+Fz8BnAvjH/XkwGg2obW5HWqINXobB3Dd2irpXfyPJFofSRdeix8tgzO+KVbnnAIsRv589FhnJ8ZiY5cTXR+tEJ0pkE2HB4IvwESLRasKE4Sn41fTRmPumvp/54GQrerzAhakJ+O5UE851CO9dd00ehtyhKfC0dOCVzZVo1Gmk5RMzLobRYMTJep9pOSt1AO575xvV7p9oi5MlYy4XgWbH/BEDFblHOGJegxJYJDD01cZGDzw4VT8F95bMugQtnd26EZj0wCubj+KO13fgyhc2+WsQBcI+40h/6LDz4doxacTj3+mFqM2Dvce8ycOIjq9r6UD+iIGYnTsY+SMGou5c+NBUpdHDj8nbJgyBJc6IeIsJ07PTwh4b1yvQRtruuDgTEqwmf8SDp1Wc7T4wERbpM2zu6MHE5zZi06Eaka1Vn1MNHXA3deDrH+qJhBMAuCzTiVsnDMEDU0fghVvHckZzsZ/9YmqWZnNv2Wff463tVbhixEDcP+VCNHeoJ0jZLSbFhJNAtHKFiHkBBQBm5GRgxbw836+XAFwOG1bMy8OiG7OxsHCURq07z8LCiwAA81ftiTofAzVwN7ZjfkChxEDYZ5zhkG7ucTlseHBqFjZW1BKfI+ToyHWPFfPyUJjtIjo+1HyltTnL5bBpvlamB4zd6/95eVghhVVdO0IiZpITzH2iaJITzEjgiQprbO0KmnvH6lpEtTk5wYwV83y2fjHPsKH1fC6V/kbgOJDs0Svm5cFpFxfhJvZ4PgL3HjXWICuMqaVF12pfiXkTD8uMnAxMz3ZhV5XHry4PNBnMv3ok/vzFEdnr9STaTJg1bjDW7zuNc+38mhFXkhXzrx6Bq17cLFp7oicTlRDJ8SZ09jBo7RQfocD6ZjzzcQWmZ7v8z67Hy2BXlQcd3V68dNs4wADUNrXD09KJpHgzfv9JRdhfIcnxZiyfm4fLM52Sxp8E9h6Te51+O7u9MBoQdr4ZDcCE4SlBn03McsKVZIW7SV1NSuAYfVPlQXK8GQ0aqOQzOGqFvDrvMhQ8/wXnmLDDazYwmDdpGI57WpE5MAFP3pgNS5zRvx+k2q3wMgwWvLcXQN+XAjv3lqw/ALslDm9+9YOodlvjjH7BSsozFJorYklPtODnU0bguKcFDMPgk+/cqplY+Gq+CO3RM3IyMG10OiYv+wKeMNEndosR9xRk4YoRqf41Han5lx36JesPYOtvpgm6DTjtZjx1Yzae3XAwbFtZ0gaY8cDUkThZ34qhKfF4c9uxsJmHUxLiYI2Lk5SdOBAt6u8EIlqDsnXrVtx0000YNGgQDAYD1q1bF/T9uXPnsGDBAgwZMgTx8fHIzs7Gq6++GnRMe3s7ioqKMHDgQAwYMAC33noramq0V1OajIYgdXmgP8Pu4/WKFBP8+ZUj8Oycsbhz4tCwPjBLZl2C3cfrJS2kaBFODADuLbhQknDCEhqqWVxejStf2IQ7Xt+Bh9eUYe6bO/Hr9/ch3mLC/VMuxJCUBEEVaUNbF4wGg+TxJ+E/Lh+CgpGp/jlHMt+8jO+4QExGA5bMEk7yJYRYdXlDWxe+PVaPq17cjLlv7lRdOGFV/Vy1QnZVeQRf9mdaurFq5wl8daQO7+44gUsWF+MPxQeRP2IgrHFG/PqDfbjrrV1hX9IMAHdTB+56axeaCM0YLO6mDv+cNRkNuGMimYmPRe696c5JmXhg6oX4n5vH4tk5l/pNLEojVPMl3B4N+CL5npuTEza5X0unF8s3V+LX7+/DpkM1fhO/HLibOrDiy0rBa/50whAMSo4nEk4A4Pc3j8UDUy/E72fnIGdwsqDgUd/aLXoOccFA/fo7gYgWUFpaWjBu3DgsX76c8/tHH30UxcXFWLVqFQ4ePIhHHnkECxYswPr16/3HLFy4EB9//DHef/99bNmyBadPn8Ytt9wivRcqoJQNLjM1AcXl1fj71ireYx6cmoUZORmq2QGT44PVnmpMTVbFnZlql+V6tc3tKC6vxvxVe/oIFYHqWNIxrW1uV3T8/761Ksg0JaZdoczIycCr8/IEE32FI9TkQcLLGw8rnlMow2HDL6Zm9THVsap+rnBIKc/NywCvba3CA//7DeccUoKSCrf//+VaB1LJTE0I+jdrYgndG+Qm3HMkhW2r0Byu7t0H9p6oD3ucWF7eeBhAeN/Fv2+twsaA5x2O+woyg8aDdD5npibg/oJMomP1imgTzw033IAbbriB9/uvv/4ad999N66++moAwIMPPojXXnsNu3btwqxZs9DY2Ig333wTq1evxrRp0wAAb7/9NsaMGYMdO3Zg8uTJ0nqiMErZ4Gqb2rF8c2VYLcf6fdX4zYwxqtkB/3rHeMSZjH41au7QZBS8sIlY2pfC8jvyUDAqFaWV3PkwxOJubMNfNx3lHNdAU9BLPx1HdD01xp41TQFAnUAdFha+drHq8Le2VeHZDeKS1PnUwyYA+oqasJmNmJM7GAWjUvGr60Zj9/F6/xydMDwFu4/X46OyU31U/5E8uxIR/kaR8lHZaTw10/drVWtfolR7cO6gHi8DR7wFd0wcihVbxJmvSEgwm7Bw+kW4+wpfcsXSyrNBZhwAvKad0HbuqvKgrbMHRoL4XwYI++NQKkvWH4DQTzvSUPJrR6cH/Tt1AFlep9qmdrgckRXB5TKZq4nsPihXXHEF1q9fj/vuuw+DBg3Cl19+icOHD+Pll18GAOzevRtdXV0oLCz0nzN69GgMGzYMpaWlnAJKR0cHOjrOb9hNTeonJpI7VBXw2Y2f3XBI8DjWZFHf0gGDQfnkVUaDISikrLTyrKLCyUC7BZN77yeHD4UBPs/6cLCmIDAIay8OtcEK2ZalwrbnlU1HseabE4LzjMQ2bDIacN+VWXhre5WoNte3dgPQXwba9i4v/ralEn/bUonkBDOev2UsZucORnF5dR8/goyA6qtKrF0lONvS6Q/n1LrNv3p/H5bM8o1fcXk1nvm4QtG2tHb14NkNB7H8y6MAgp3LWU1g4GcZHNV1pbZTie1UaP9i4Asld9otqG/pDNuG0GfhE36EIXm3CNHvwoz/+te/Ijs7G0OGDIHFYsGMGTOwfPlyTJ06FQDgdrthsViQnJwcdF56ejrcbm6V17Jly+BwOPx/Q4cOlbvZgsgVqhqIGLtxSYUb/7V6ryqZNetaghcXqSpSKrNzB/mlczE+FHzPQswQ1bV0hA0zB87bYAND0pWCxEwiZKcPJFwYfTTT0NqFh1btwbINFYJmPDWem1yw6nuT0YBZ47TJ3gkANU2+8eMbX6VoaO3qE/nG9VloxB6fOVfv3Jw7SHC/coc8C7Ud4IF+FGb817/+FTt27MD69euxe/du/PGPf0RRURE2btwo+ZqLFi1CY2Oj/+/kyZMytpgcf6hbUmSp06VoytbuFVYHyvUCOlJzDqWVZ9HjZdDjZYhVkVIJVWGG86FISTDj1Xl5eJUj5FBK/7895kFblxePFF7UJysrlz2cnQMpCWTKRyWEArF2er4QTTnQyHfOz+tfVfGa8YDzWTBn5GRoHv5MArv2Oru9+KjstGbtYHr/+MZXawKfb2e3F898XKHLdgpx7eh0Il8xBsDfNXwW/SLMuK2tDU8++STWrl2LmTNnAgAuvfRSlJWV4aWXXkJhYSFcLhc6OzvR0NAQpEWpqamBy8Wd+8FqtcJq1VM9Fem7coLZiFYRRb4MAFLsZqLMkgyA2/KGoGDkQCz9lCx8jYtXNh/FK5uPIsNhw+2XDyW6dyQEqjBZWB+KHZVnUfpDHQCf2WlyQO2dwJDDuuYOSQUB391xAu/uOAHAF8q9sHAUMlPtYe3cM3IyYLfEEWUKDaqTI4N5LtEWh6dnjhHtRMiO51++OIK/fHEk7EbniI9DvDkONU38ZqHkeDOKrhkp2r9FbsJpIUPV0wumjcJ7u05GHHqpJOzacxKueVKkphrQKMM5Eezzfbf0WNRpTgCfmQoG8lxJcmrPSedD1IUZh6OrqwtdXV0wGoMvazKZ4PX6XsoTJkyA2WzGF1984f/++++/x4kTJ5Cfny9nc2SHVSNGssFdLuJBs6/GObmDic/5YM+PiLeY8NycHJEt64u7sR0vbzwS8XWEYNXJoQnWTEYDCkal4tfXj8avr784KAyX/Z4NOTzd0BZxO9xNHfjTxiOwxhk5QxgDEZspFODfYMSIu83t3ShavZczGZ0QJRVuQeEEABrbujE7N4OzbWz45vO3jkVahJpEtQg0myyZJa+ZVinkFE6mZ5NnPo5GjntaJZ9rAHDJoET5GiOCxTdlY9NBbdJrkAonQJSFGZ87dw5lZWUoKysDAFRVVaGsrAwnTpxAUlISrrrqKjz22GP48ssvUVVVhZUrV+J///d/MWfOHACAw+HA/fffj0cffRSbN2/G7t27ce+99yI/P1+3ETyAzzt8yfrI1Ygp8RbyY+1mLL9zPHFWURbW6zpSlbZam5qYwn8snd1evL61Eg/+77d45L09WLPrhGxteXLtfqzde8pv5uIiEpVn6FJP79XciGmj2AJePV6GWA1ugC9y7C93jEeKPXi+BpqXtI40IaWuucM/Vqy5S64MomLIcNjwwJQsOO3ke0CkPDAlC6/OuyyikHO9M9yZIHwQB64kKx4pHIVRaeoLKAsLL8K00en41+4fVb83KXKEfEeKaBPPt99+i2uuucb/70cffRQAcPfdd2PlypVYs2YNFi1ahLlz58Lj8WD48OF49tln8dBDD/nPefnll2E0GnHrrbeio6MD119/Pf72t7/J0B3leGXTEVlUw+v2kduVPS1dWPrpQTw9c4yoyBZWrb1g2ii8/fWxsCpEu8Wki6KDYrzFl22owN+3KmeP9bR0YeE/ywBwRwsAkUUb9W23AaPSBoiKEBLrWb+rykOsBmefxeL1B4LMhE67Oci8JDXSxACfUPbHn+WitLIOr2yuFHV+0LUIzGZLPz2IN7ZV+Z8jacZRORhgNWHpzWPhSrKhvqUTSz+tUPyegUwbnY5dVR7RJRdYxBTGVBvW/HBXfibe2CYuUg3waSPV0BCH4kqyYlTaAExetlGVOjpiWXDNyLDFV9VEtAbl6quvBsMwff5WrlwJAHC5XHj77bdx6tQptLW14dChQ3j00UdhCIhJt9lsWL58OTweD1paWvDhhx/y+p/ogeLyak0mMuAzsxSt3ovZuYNEnVfb3I6SCrfgxjT5Qm1si3wIeYsv21CB1xQUTkLhq+8jV8ZWwGfiKlq9V3TURomI6CopXvihL9L6lq4g85KUyDb22CWzLkHByFSMSo/s1yupXb465DmSZByVg59dNhRzxg9GY1snilarH2VSUuGOKALj6osvAKC/CLBA84MlzigpUk3tH2bsXJudOwhFq/co7tsnlVHpAwRN3GpBiwUKwKrGtYLdf9fvq8bf7syD3cpdrCyUVLtVsN2O+DjsOdEQWQMDCJ3PUuZ3OLNBZ7dXkaRK4QhnfmKjjWzmyJZR4DNefie5+eGjstPEZh45zDFcYyE2si1UbSy1XcnxcZLMFlxtT1fQl+baMemizGty81HZaeLEXlw8MGUEZwSYFiayQELnkVKRakYDcNOl8vx4djlsWH7neKzfVy3rXEiyyZvOTE+mW1osUAAxqnGp3Jw7COvChBSyKvcUuwV7n74urGqaVXvCAMF2N7bJp158euYY3JWf6c/uKTaqhs9bnM0MWdvcjm+PeTTZ5Nnx31F5FkajISib5YycDOy9KA3Zi4sj8rIPfMY7FhViwv+UCKp/AxN7haPHy8DrZWQp4MdlipuRk4FEmxlz39gpeP49V2Si/FQjyk81IX/EQFye6RQ0bV1gj8PPp47E7uP1sFtMuCVvCAAQRVFxtX3l9iqkJlqRlmjD9GwXcdslwaizh/BxtqVTMBkhH2zhRZPR0KdI34ThKbjqxc2yJC102s24Y+IwLCcw9dnMRtx/pa/Q3+QLg+f99GwXEq1mf9RfQ2snVu2U5puWlZqAghGpeGqmT0Pz7fFNkvsaWAhU7Fww9Ibb8N03wWLEf109Aiu2/CBLMceBdotmETtcUAFFADUS1CQR1reobW73q6bnr9oDICSMtfe/i2/KRt05dZP5pCZaYemNfgGAj0TkTuHzFlcjg6UYilbvCXrBB/qnPDglC6/JoN0pqXAjf8RA/GzCELy5/Zjg8ULzU6kxDL0v6Xxb9tn57JavbD6K5AQz/uOyIfj71qo+oY/sv7sYQ9B5mw+fQWe39IKSgYJzhsOGG3OUMy+HJj3UgrqWDswal0E8P7nWIxsxF8jim7Ixf9UeySHM7H2emzMWHYTPs73LV+hv+ebKoPXHNc8TzGTaZi6q6lpRVXcCn+yvxvO3jOXtq1Df2Yi3gpGpAMS9TwwAHpySxbk2WFo7vXi+OHzWbDEEJs3UA9TEI8CxuhbF70Hqhc6q3vjUmVpGWITeT8z9ubzF9ZgZMlT7EOifsujGbPxialbEicve2n4MxeXVxJFb4cZZyTGM5HkH0tDahde2VuHBqVl95rODI8U5++9WmfwH3I3tRIKgVNISbarsIeE4Vtca1jRqtwS/yEmjNyI1q7AFQqXuV+z648t229oV+RxhMxYD4OyrUEFCttArC+lcGGi3YMW8PCy6MVuxJItcTBcZMao0VIMShh4vg/dkCl/lwwDgzknDw3qhc5k/QtWZoUnM2AiLcNf02d4NYRNykeC0m+Fuasf2I3WAwfdrOtVuhSvJJpjsi1V9Bkrtnd1ePLm2XHKbkuNNuPridLR0dGNHlUcxT/nAooPTs11YdGM2fnXdaLzzdRW+OVaPBLMR2YMcuCDJhtQECx7+V5lgBAd7vS2PXSOqRlAokfg9hIvc4LvvhOEpMBqkJ/Zav68aWx67xm8iTLVb8av390HpgoVsc6VqAfhgx2nC8BQs/OdeydeJJIqGXePv7ToR9vxEWxz+/p+Xoe5cR9gEhUCwyZU1kUmNiLLGGTE924XObi/KTzUgwWISJXiyfVIj2+0zH1dg2+PTgkxdJHOULfRqMhqI3ydOuxmli66FJc6nPwhMWhmqxZUTu9WEzq4ebD9aRzQX1IAKKGHYVeVRvO6Br5rmD2FViECwupVLnfnvPT8GhcOyERbhrslGoUSipgWCw3IDSU4w+1/iXPcPVH2yFJdX48m1+yPycH/+1nGYkZOB0sqzKDmobDXaUJ+MTYdq8Nb285kt1+2r5ix2JnS93cfrRc2JUCLxe2CFDDH33X28PqKso2yfWTNCaeVZVTO+KvGCW3xTNnYfr5e0h7Cje+2YNEkVldnz75g4TDAC0d3UAaPBgNkCCSG59p3z2abFh067mzrw8Jq92LC/OqK5o0a228A1LmaOBp5H+j65Oz/LL5ywmIwGGI0GxYQTAGjp6MHdK78J+owvzYJaUBNPGEjthcmEPiR8vLzxMABuFWKoupVPbc8VDktiCiJV0xrQVxUsRGPvCzlUDcqnQmb7JlU4sVtNeDXgumLsvRkOG34xNcuXfjoA0mdb29zO+2y4ip2RXI/k+YU7PxLuK8gUdV85fLUCr6FVcTISUhLMnHOFJSNgnKT2w+Ww4cGpWdhIKJyEyqnss8pMtROdT+LLxLfvRJKC4ZPvIhNO1CR0jEif7etfVYo6PjOV2+Qf6Zrg2+PCwZdmQS2oBiWEQBVmXTPZL5/ld+bBaDTgdH0rlnxSIcmkwKVCDFWxhVPbh5ob2HNY9SDfNfmOyR2ajNU7j+O4pxXDnQm4Kz8TJqPB9yugsY2o1g/bJlucEf/4+aSwasNITBI2swGvzbsMV466IOi6pHbtp24cg/uuzILJaMBvZowJGgcvwxBFeDjjfSYcufbaQH8joecX7nypTM924amZ2cT3lcPnKfAaclzvzolD8el+tyzRDYFY44z4zYwx/rnibmyDp6UTzgE+s2bgOEnpBxsRd9WLm8POJ6fdjKd/cglcSdzr1RJnRGnlWaJ71jV34KOyU5zPWWjfUZLC0Rdg46EzCt+FjNomX0Zisc9286Ez+OrwGTgTyDIIp9q5w8IjWROXDU/G9Zdk4O4rMvGr60Zj0nMbUU+o0eV6r6gFFVAC4FJhhrOrs3bmySMGoqTCjWc/OyjZ34FLhRiKkNqeLxsrlwd+KFzH3D/lwj7H5Y8YiNLKs8QqXQZkKuRITBLtXQwscaY+i0fID4flzW1VGOqMx4ycjD7j0ONlBH1BHAlm/Pc/9xIteCG4fDxInl8opH0Pd38x95V6P5aMkD5Hej0AyEodQCycuHr9sUjMSu6mDsG1yiKmH+zY31OQRbQePC1dcCXZ0NjWiWl//DLoeDZz7vRsl+D9jYa+kU2Ban0tw6RJhJNIfJ/E8OyGg3hr+/mMxBOznEi0mdDcHt5vhoEvJJ701c5VPBWQnrkZAL493oBvjzdg2WcHMXOsS9ReJSbLt9xQE08vfCrMcMIJ4LMzl1S4IzJNsAip8EhVfEqrx6VcX66+iTmf9cMBwmeY5CtWKHQN1kejobVLNuEEkKc4F2nf5bq/lPsFEnrPSK8HACfryYvILZl1CZbMyiY+nnS+kvYjdOxJr8/uPXwm35IKt+D9Q/e4ULW+2NBYtWAzsz4wJUu1ewaOjclowIRhKcTnkspQ4Yqnis3cHIqXAT7+jjwDdSBamF2pgAIy8wKfjXd6tku2LJFCKjw+1Z/U48LR42VQWnkWH5X1LZonRdUodE6kKv0jNec4i/uRZAtlz1iy/gC2H63r02c+X5D0JKusRdgiKc7F9bz42s1ni460OJiUsFODAfjbndz35LseaTblJkLtycLCi/z+WKRFG8XMV5JxkZph9/3dP4Y1vbCqed8aCL4mnwwamjGYtC0LCy/q08fkBHOfNSKXlYAds0U3ZkdcGJWU0LGZMuoCxe/B0uNl4Ii34N6CTFULTrJokWGWmnhApsL0Mj7bMJuBklWBl1aejVj9KRQyGnQg6QUjgM9bP1C1KVZtLdS3SFX6r2w+ilc2H+X0OifJdMqaogKPCbwWly8IqX9KOAzwZVe97hKX5JA+oefF58MS6m8jR0hh4P22Hz0jWAiQYdCnYjLf9QKzmE79w2ZBc0y47MwsriQrFkwb6f/3qLQBRGZdsdk2Q/uRarf6Q/K5xp50PYQzKQeq5s9/cp5wZpHAc0lSFrgcNiyYNhILpo3sM6cABPn1ickwHcpdk4fhskxnnzFbMG0U3tt1UpXIr8CxuSs/E89uOCi7iSnUrMK1xp12M2aPG4QhKQlwDrAibYBvTv1542HsOlYvW1ukznk5oBoUkKuuUhOtmJ07OKiQUqRqLzFqddJsnV8crJHcHpIoIalq63DIodIPbWcgUjLrhl6L9clg54Ac2XoZACu/PobGtk7JwgnJ8wpsd2h20NDPI4W9LmkhQKE1FNpOS5wRS2ZlR1Tojz13yaxLgsL3i1bvFXzZSDXBBfajYFQqCkam8o69XOsBOG8GkhLuXNvcLmjmBM6PCdecCvwsNTEy7a6h15ctdMx8xTsjmxNiYTN7K2liChcdWN/ShZVfH8fglHjMGe+bU83tXbIKJyxymJ2lQAUUkKuuuI6LVO3FpVbnM6+Q3ktMEblASLz1WbWjFLW1EGJNElwEtrOz2+sfR9KILL5rhapaSyvP4khNs+hr8sFVjFAI0ucVOA5cZjCliGRdCRFpFtPQuUlq5l3OY45SArkK4K0rOy3ZBC0mezUJkRQuBMJn3VaqYCAf7NjIlUWaC7boK8merERhW2dvRlut8qBQEw/Isq7yqbikmib4sqiGU9dPz3bBaTcLOuOSFpELRWyUkFi1NQkkJgkh0wHbztDsllK8/UlUrZEi1Uue9HmFjoNayZciWVckiDUnAcCCa0aiYGRqn7lJauYNZ45Sghk5GfB6gcc//E50hKABQIrdLCmJGtezkRryzlJcXo0l6w+IbguL0QDclZ8Z9hi+Pam2qZ0oNQIpoVFngVmkX954JOJSDOz4CxV9DTXjyR1t9eef5WLKxfL72ZBCBRSQZV3lU3GFO5cLoSyq81ft6XMNVl2/Yl4e5uQOlqWIXCTnBB4nJQRWCL5rsp+TtjN0M4pEcRCoalVK/yD2mUkdh8D5pKSQEsm6EnMPMXNiVPoAzrmllwi5UHxmJ/Fzjh1R0v2C61yuZyN1vcuxdh6Y0jfDKhd8bYy3mGRbv1xjY4kz4oGpIzDUmeCv3yOFwPEnNSMrNS89bfIIdFKhJp5eIlFh8p3L5cHOdz1Sdf20MelE/VEi0iaSa8uJFvcPp2qVC7H9kjoOfKYrJZDLNCBEpHNXj3M/kuSF7PiSFp3kOleuZ0PajwyHDdOz0/qYSowG4BdTs7DoRvIwcC7YuchnKnbaySLy2KivcPeJJKpIStHXtESbInNT672ealACiESFyXcugD7ZJh3xlqCMhOwxJKo8MFBMbS5WJR9aOEytwlJyJPEihVTVKsc9xD6zSMZBzeRLkZoGSIjUnKS0OUoKYhOkBWaWZceXJNFgepIVf/xZrmIF4kj78dJt41AwKhWd3V68W3qsT1ZcOQici6EZgCcMT8FVL24Ou55Co774kBJVxGV+FDsvSRK5sc88XKFYLSN3AqECSgiRmCz4zm1s68QfPv+eNwwUIFfR1bV0KKY2F6OSFwptVRKxZjWpSFG1sueFjh0T5jv2HlKTo0UyDmqZLJQwBYZeP5J1oYY5SixiE6Q9N2dsn7VHWjQ01NwsJ6T9+OJQDQpGpcISZ+TMYi0X4eYiyViRzAE2qkiMSYnL/Ch2XrLHCt0zXKFYreY7F9TEozCkxf1IVWnH6loVVZuTXFtMwUKl4GsnqZqWBCmqVq5kVS6HDa/Oy8OrCjyzSCMXtFbhykmk60ItcxQppM9moECkhdb9Iu3HW9uPaVaUjkXOsWKvRbon8Y2TmDYJmbECC1lqPS9IMDAMo07MoYw0NTXB4XCgsbERSUlJWjeHlx4vg4LnN/Gq+Vg12rbHpwEACp7/QjBXQUbv8az6VqhYWbi2hVO5833f42Vw5QubeNWIgX1SQ/oObSeJmjYcXGpy9j5XvrBJUNXKPstwBR8jNXVwXYO9J2khR7Wfk5pEOsZyPyOp0W1Ccw7wzdcdiwqJTCBamWSF9gyW0DmpVXvZNst1785ub59IukBI16KYNol5N6g9zmLe39TEoyCvbDoS1gYZ6gdwx8RhgqXLA483GQ1E5qNQSMwzfGpQqQULlYKrneFUokKmFi41OXsfMapWvr5HauoQenakhRwZ6EOFqwSRjrESzygQUlMoyZx7bs5YYv8Mpc1s4e67+KZswciWwL2jsa1TMxMyIO9YWeKMeG5ODub39l+qOUVMm5Q6Vm2oiUchisurBYUNFtZGm5lqF3W8FFNLpOYZvYZjBhJOdRmJqUVrlSjJsyMd9/sKMnWhwu1v8D2jQMSYQrWec3IxIycD9xdkEh0rVABRazOQFPrLc1QbqkFRALEZ/Vjbo5iQMqGwZAPOFwoLNC+IPYevrSRtZBGrQpRD5SgUORJptNaOyrMo/aEOgO/Xx+QLlf0FQvrsXvrpOKLrTZcQfhqNqKm+Jg2nJV1rLGpEQalBYbaLKCcLX+ZbseOmN/rLc1QTKqAogJjwwMCMhGJCyqSYWuQwz4gNexMb7SNndFA41WUkas2SCndQG/mKFMqJHsLQow21I83ErHuxplA9q+FJIdk7hDLfqm1Clpv+8BzVhJp4FECMeSPQ9iimKJcUU4sc5hkxbRRrTtJDdJAQWrVxY4Wb6Dg2DB0Qfj79GS2ek5LZm/sDJHvHnNzBRNeKpXGLZaiAogBiQlJDf8mR2ipJ71HX3OEvEkdaqEvo2iRtFFN4EBBXqFArtGpjj5fB2rJTRMemJdpi3t6t1XNSMnuz3uAraCqE0NwkzXwbreMGSB+7WISaeBSAJMNnuIyEJLZKknsYDcDSTw8G3TM5wYzG1q6I1f9CbRRrTtJbdBAXWrVxV5VHsEAk4MuHwT67WLZ3a/WcxGT2jWZTW6Sms3BzkyTzbbSOG6C+2THaoRoUBRBSZRognJGQtVXOzh3sDykmvQdLqGBe09SBhl7hRA71f7g2ijUnRUN0kFZtJL3e7NxBQc9AaA71V7R6TiRrMvC7aDS1yWU645ubYkzI0UY0mLD1BhVQFEINNTvfPfjWLiuYJCeYkZ6kr+JtchdrU0KNqlVBOdLrxUpkjhBaFv4jyewbraY2tUxn/dFEGQ0mbD1CTTwKooaaPfQedc0dQWadUBgADa1d+Mf9eTD2OtvqoXibnMXalFKjalVQjsR0kBHFam+50brwX+ialJpJVm+oaTrrbybKaDBh6xEqoCiMGmFlgff4iNCZsq6lA7MJPealtklM5lW5irWxatTQFxOrRo3kF5hWBeX0WMhOz+hhvPpjOKnaprP+NIbRYMLWI9TE08/QUr0dilhVbaSqXTXUqFqpn/uj2ltJ6HjJj572lmiDjp00qAaln6G1ejsUsaraSFS7aqlRtVI/9ze1t9LQ8ZIXve0t0QQdO2lQAaWfoQf1NlebxAgEUlW7aqpRtSy81l/U3mpAx0s+9Li3RAt07KRBTTz9kFhVb1M1KoWiLLG6t8gBHTvxGBiGibq4pqamJjgcDjQ2NiIpKUnr5ugWNQul6YEeL4MrX9gkqEbd9vi0fj0OFIrSxNreIiexPnZi3t/UxNOPiTX1NlWjUijqEGt7i5zQsSOHmngo/QqqRqVQKJT+AdWgUPodNHqDQqFQoh8qoFD6JVSNSqFQKNENNfFQKBQKhULRHVRAoVAoFAqFojuogEKhUCgUCkV3UAGFQqFQKBSK7qACCoVCoVAoFN1BBRQKhUKhUCi6gwooFAqFQqFQdAcVUCgUCoVCoegOKqBQKBQKhULRHVGZSZYtwNzU1KRxSygUCoVCoZDCvrfZ93g4olJAaW5uBgAMHTpU45ZQKBQKhUIRS3NzMxwOR9hjDAyJGKMzvF4vTp8+jcTERBgM8haAa2pqwtChQ3Hy5EkkJSXJeu1oINb7D9AxoP2P7f4DdAxivf+AcmPAMAyam5sxaNAgGI3hvUyiUoNiNBoxZMgQRe+RlJQUsxMToP0H6BjQ/sd2/wE6BrHef0CZMRDSnLBQJ1kKhUKhUCi6gwooFAqFQqFQdAcVUEKwWq1YvHgxrFar1k3RhFjvP0DHgPY/tvsP0DGI9f4D+hiDqHSSpVAoFAqF0r+hGhQKhUKhUCi6gwooFAqFQqFQdAcVUCgUCoVCoegOKqBQKBQKhULRHVRACWD58uXIzMyEzWbDpEmTsGvXLq2bJImtW7fipptuwqBBg2AwGLBu3bqg7xmGwe9+9ztkZGQgPj4ehYWFOHLkSNAxHo8Hc+fORVJSEpKTk3H//ffj3LlzQcd89913mDJlCmw2G4YOHYo//OEPSneNiGXLluHyyy9HYmIi0tLScPPNN+P7778POqa9vR1FRUUYOHAgBgwYgFtvvRU1NTVBx5w4cQIzZ85EQkIC0tLS8Nhjj6G7uzvomC+//BJ5eXmwWq0YOXIkVq5cqXT3iFixYgUuvfRSf5Kl/Px8fPbZZ/7v+3v/Q3n++edhMBjwyCOP+D/rz2OwZMkSGAyGoL/Ro0f7v+/PfQ/k1KlTmDdvHgYOHIj4+HiMHTsW3377rf/7/rwXZmZm9pkDBoMBRUVFAKJkDjAUhmEYZs2aNYzFYmHeeust5sCBA8wDDzzAJCcnMzU1NVo3TTQbNmxgnnrqKebDDz9kADBr164N+v75559nHA4Hs27dOmbfvn3MrFmzmKysLKatrc1/zIwZM5hx48YxO3bsYL766itm5MiRzB133OH/vrGxkUlPT2fmzp3LlJeXM++99x4THx/PvPbaa2p1k5frr7+eefvtt5ny8nKmrKyMufHGG5lhw4Yx586d8x/z0EMPMUOHDmW++OIL5ttvv2UmT57MXHHFFf7vu7u7mZycHKawsJDZu3cvs2HDBiY1NZVZtGiR/5gffviBSUhIYB599FGmoqKC+etf/8qYTCamuLhY1f5ysX79eubTTz9lDh8+zHz//ffMk08+yZjNZqa8vJxhmP7f/0B27drFZGZmMpdeeinz8MMP+z/vz2OwePFi5pJLLmGqq6v9f2fOnPF/35/7zuLxeJjhw4cz99xzD7Nz507mhx9+YD7//HPm6NGj/mP6815YW1sb9PxLSkoYAMzmzZsZhomOOUAFlF4mTpzIFBUV+f/d09PDDBo0iFm2bJmGrYqcUAHF6/UyLpeLefHFF/2fNTQ0MFarlXnvvfcYhmGYiooKBgDzzTff+I/57LPPGIPBwJw6dYphGIb529/+xqSkpDAdHR3+Yx5//HHm4osvVrhH4qmtrWUAMFu2bGEYxtdfs9nMvP/++/5jDh48yABgSktLGYbxCXlGo5Fxu93+Y1asWMEkJSX5+/yb3/yGueSSS4Lu9R//8R/M9ddfr3SXJJGSksK88cYbMdX/5uZmZtSoUUxJSQlz1VVX+QWU/j4GixcvZsaNG8f5XX/vO8vjjz/OXHnllbzfx9pe+PDDDzMjRoxgvF5v1MwBauIB0NnZid27d6OwsND/mdFoRGFhIUpLSzVsmfxUVVXB7XYH9dXhcGDSpEn+vpaWliI5ORmXXXaZ/5jCwkIYjUbs3LnTf8zUqVNhsVj8x1x//fX4/vvvUV9fr1JvyGhsbAQAOJ1OAMDu3bvR1dUVNAajR4/GsGHDgsZg7NixSE9P9x9z/fXXo6mpCQcOHPAfE3gN9hi9zZmenh6sWbMGLS0tyM/Pj6n+FxUVYebMmX3aGQtjcOTIEQwaNAgXXngh5s6dixMnTgCIjb4DwPr163HZZZfhpz/9KdLS0jB+/Hi8/vrr/u9jaS/s7OzEqlWrcN9998FgMETNHKACCoC6ujr09PQEPQgASE9Ph9vt1qhVysD2J1xf3W430tLSgr6Pi4uD0+kMOobrGoH30ANerxePPPIICgoKkJOTA8DXPovFguTk5KBjQ8dAqH98xzQ1NaGtrU2J7ohi//79GDBgAKxWKx566CGsXbsW2dnZMdP/NWvWYM+ePVi2bFmf7/r7GEyaNAkrV65EcXExVqxYgaqqKkyZMgXNzc39vu8sP/zwA1asWIFRo0bh888/x/z58/Hf//3feOeddwDE1l64bt06NDQ04J577gEQPfM/KqsZUyikFBUVoby8HNu2bdO6Kapz8cUXo6ysDI2Njfjggw9w9913Y8uWLVo3SxVOnjyJhx9+GCUlJbDZbFo3R3VuuOEG//9feumlmDRpEoYPH45//etfiI+P17Bl6uH1enHZZZfhueeeAwCMHz8e5eXlePXVV3H33Xdr3Dp1efPNN3HDDTdg0KBBWjdFFFSDAiA1NRUmk6mPB3NNTQ1cLpdGrVIGtj/h+upyuVBbWxv0fXd3NzweT9AxXNcIvIfWLFiwAJ988gk2b96MIUOG+D93uVzo7OxEQ0ND0PGhYyDUP75jkpKSdPESsFgsGDlyJCZMmIBly5Zh3Lhx+POf/xwT/d+9ezdqa2uRl5eHuLg4xMXFYcuWLfjLX/6CuLg4pKen9/sxCCQ5ORkXXXQRjh49GhPPHwAyMjKQnZ0d9NmYMWP8pq5Y2QuPHz+OjRs34uc//7n/s2iZA1RAgW8jnzBhAr744gv/Z16vF1988QXy8/M1bJn8ZGVlweVyBfW1qakJO3fu9Pc1Pz8fDQ0N2L17t/+YTZs2wev1YtKkSf5jtm7diq6uLv8xJSUluPjii5GSkqJSb7hhGAYLFizA2rVrsWnTJmRlZQV9P2HCBJjN5qAx+P7773HixImgMdi/f3/Q5lRSUoKkpCT/ppefnx90DfYYvc4Zr9eLjo6OmOj/tddei/3796OsrMz/d9lll2Hu3Ln+/+/vYxDIuXPnUFlZiYyMjJh4/gBQUFDQJ73A4cOHMXz4cACxsRcCwNtvv420tDTMnDnT/1nUzAFZXG37AWvWrGGsViuzcuVKpqKignnwwQeZ5OTkIA/maKG5uZnZu3cvs3fvXgYA8//+3/9j9u7d+//buX+QZOI4juMnxB0d0R9QJIQLgsChwZZAcDOCpnCShoiaqlVCF0ehPVpaWgpco6Ua0qDAoqEkiGiwpiAIgqCGkHdDJN2TPMNDPP06Pi9w+v2483scx4fDj9ze3gLv1bre3l62trao1+tMTk62rdaNjIxwfHzM4eEhQ0NDvmrd4+Mj0WiU6elpLi4uKJfLuK7749U6gIWFBXp6eqhWq76a3fPzc2vP/Pw8nuexv7/P6ekpyWSSZDLZWv+o2I2Pj3N2dsbOzg6RSKRtxW5paYnLy0tWV1eNqVkWCgUODg5oNBrU63UKhQKhUIi9vT0g+PO387nFA8G+Brlcjmq1SqPR4OjoiLGxMcLhMPf390CwZ/9wcnJCR0cHpVKJ6+trNjc3cV2XjY2N1p6gPwubzSae55HP57+s/YZ7QAHlk5WVFTzPw7ZtRkdHqdVqP/2V/kmlUsGyrC+fmZkZ4L1eVywWiUajOI5DOp3m6urKd4yHhwempqbo6uqiu7ub2dlZnp6efHvOz89JpVI4jkMsFmN5efl/jfhX7Wa3LIv19fXWnpeXFxYXF+nr68N1XTKZDHd3d77j3NzcMDExQWdnJ+FwmFwux+vrq29PpVIhkUhg2zaDg4O+c/ykubk5BgYGsG2bSCRCOp1uhRMI/vzt/BlQgnwNstks/f392LZNLBYjm836/v8jyLN/tr29zfDwMI7jEI/HWVtb860H/Vm4u7uLZVlfZoLfcQ+EAL7nXYyIiIjI99BvUERERMQ4CigiIiJiHAUUERERMY4CioiIiBhHAUVERESMo4AiIiIixlFAEREREeMooIiIiIhxFFBERETEOAooIiIiYhwFFBERETGOAoqIiIgY5w3qEQZBEhmmGgAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "NnN-BcAmtCm9"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}