S&P500_팩터_데이터_수집과_분석.ipynb

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  "metadata": {
    "colab": {
      "name": "S&P500 팩터 데이터 수집과 분석",
      "version": "0.3.2",
      "provenance": [],
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/tylee33/DLforFinance/blob/master/S%26P500_%ED%8C%A9%ED%84%B0_%EB%8D%B0%EC%9D%B4%ED%84%B0_%EC%88%98%EC%A7%91%EA%B3%BC_%EB%B6%84%EC%84%9D.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "metadata": {
        "id": "e3qXEjB746ov",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "## FinanceDataReader 설치 (for 구글 Colab)\n",
        "\n",
        "!pip install -q finance-datareader"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "BBkbaCm85L8r",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import FinanceDataReader as fdr\n",
        "import pandas as pd\n",
        "\n",
        "pd.set_option('display.float_format', lambda x: '%.2f' % x)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "8caW8R805Pyi",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.rcParams[\"figure.figsize\"] = (14,8)\n",
        "plt.rcParams['font.size'] = 16\n",
        "plt.rcParams['lines.linewidth'] = 2\n",
        "plt.rcParams[\"axes.grid\"] = True\n",
        "plt.rcParams['axes.axisbelow'] = True\n",
        "plt.rcParams['axes.unicode_minus'] = False\n",
        "plt.rcParams[\"axes.formatter.limits\"] = -10000, 10000"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "YEB6ZkmJ5TTh",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# matplotlib 컬러맵 생성\n",
        "import matplotlib as mpl\n",
        "import numpy as np\n",
        "\n",
        "def make_colors(n, colormap=plt.cm.Spectral):\n",
        "    return colormap(np.linspace(0.1, 1.0, n))\n",
        "\n",
        "def make_explode(n):\n",
        "    explodes = np.zeros(n)\n",
        "    explodes[0] = 0.15\n",
        "    return explodes"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "p8noD3r35Wxa",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# S&P 500 종목 리스트"
      ]
    },
    {
      "metadata": {
        "id": "ol3kz_4R5ckY",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "outputId": "e89ef46c-fee8-40ea-c44d-1e8741ab6cf6"
      },
      "cell_type": "code",
      "source": [
        "import FinanceDataReader as fdr\n",
        "\n",
        "sp500 = fdr.StockListing('S&P500')\n",
        "sp500.head(10)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    }\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>Symbol</th>\n",
              "      <th>Name</th>\n",
              "      <th>Sector</th>\n",
              "      <th>Industry</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>MMM</td>\n",
              "      <td>3M Company</td>\n",
              "      <td>Industrials</td>\n",
              "      <td>Industrial Conglomerates</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ABT</td>\n",
              "      <td>Abbott Laboratories</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Health Care Equipment</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ABBV</td>\n",
              "      <td>AbbVie Inc.</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Pharmaceuticals</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ABMD</td>\n",
              "      <td>ABIOMED Inc</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Health Care Equipment</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ACN</td>\n",
              "      <td>Accenture plc</td>\n",
              "      <td>Information Technology</td>\n",
              "      <td>IT Consulting &amp; Other Services</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>ATVI</td>\n",
              "      <td>Activision Blizzard</td>\n",
              "      <td>Communication Services</td>\n",
              "      <td>Interactive Home Entertainment</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>ADBE</td>\n",
              "      <td>Adobe Systems Inc</td>\n",
              "      <td>Information Technology</td>\n",
              "      <td>Application Software</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>AMD</td>\n",
              "      <td>Advanced Micro Devices Inc</td>\n",
              "      <td>Information Technology</td>\n",
              "      <td>Semiconductors</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>AAP</td>\n",
              "      <td>Advance Auto Parts</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Automotive Retail</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>AES</td>\n",
              "      <td>AES Corp</td>\n",
              "      <td>Utilities</td>\n",
              "      <td>Independent Power Producers &amp; Energy Traders</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Symbol                        Name                  Sector  \\\n",
              "0    MMM                  3M Company             Industrials   \n",
              "1    ABT         Abbott Laboratories             Health Care   \n",
              "2   ABBV                 AbbVie Inc.             Health Care   \n",
              "3   ABMD                 ABIOMED Inc             Health Care   \n",
              "4    ACN               Accenture plc  Information Technology   \n",
              "5   ATVI         Activision Blizzard  Communication Services   \n",
              "6   ADBE           Adobe Systems Inc  Information Technology   \n",
              "7    AMD  Advanced Micro Devices Inc  Information Technology   \n",
              "8    AAP          Advance Auto Parts  Consumer Discretionary   \n",
              "9    AES                    AES Corp               Utilities   \n",
              "\n",
              "                                       Industry  \n",
              "0                      Industrial Conglomerates  \n",
              "1                         Health Care Equipment  \n",
              "2                               Pharmaceuticals  \n",
              "3                         Health Care Equipment  \n",
              "4                IT Consulting & Other Services  \n",
              "5                Interactive Home Entertainment  \n",
              "6                          Application Software  \n",
              "7                                Semiconductors  \n",
              "8                             Automotive Retail  \n",
              "9  Independent Power Producers & Energy Traders  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "metadata": {
        "id": "XKgZQz2I5io2",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "93403f66-433c-4efb-fb1f-a71ce7125c20"
      },
      "cell_type": "code",
      "source": [
        "len(sp500)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "505"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
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    {
      "metadata": {
        "id": "1OyqVaxs5mtP",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "팩터 데이터 - finviz.com\n",
        "EPS, P/E 등 72개 factor\n",
        "https://finviz.com/quote.ashx?t=AAPL"
      ]
    },
    {
      "metadata": {
        "id": "OOAAku6h5s1e",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "outputId": "9eacbb8b-e993-4555-daf8-25c3349420de"
      },
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "url = 'https://finviz.com/quote.ashx?t=AAPL'\n",
        "df = pd.read_html(url)[7]\n",
        "df.columns = ['key', 'value'] * 6\n",
        "df"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
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              "        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>key</th>\n",
              "      <th>value</th>\n",
              "      <th>key</th>\n",
              "      <th>value</th>\n",
              "      <th>key</th>\n",
              "      <th>value</th>\n",
              "      <th>key</th>\n",
              "      <th>value</th>\n",
              "      <th>key</th>\n",
              "      <th>value</th>\n",
              "      <th>key</th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Index</td>\n",
              "      <td>DJIA S&amp;P500</td>\n",
              "      <td>P/E</td>\n",
              "      <td>16.35</td>\n",
              "      <td>EPS (ttm)</td>\n",
              "      <td>11.94</td>\n",
              "      <td>Insider Own</td>\n",
              "      <td>0.08%</td>\n",
              "      <td>Shs Outstand</td>\n",
              "      <td>4.74B</td>\n",
              "      <td>Perf Week</td>\n",
              "      <td>6.18%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Market Cap</td>\n",
              "      <td>923.91B</td>\n",
              "      <td>Forward P/E</td>\n",
              "      <td>15.30</td>\n",
              "      <td>EPS next Y</td>\n",
              "      <td>12.75</td>\n",
              "      <td>Insider Trans</td>\n",
              "      <td>-6.04%</td>\n",
              "      <td>Shs Float</td>\n",
              "      <td>4.68B</td>\n",
              "      <td>Perf Month</td>\n",
              "      <td>13.40%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Income</td>\n",
              "      <td>58.33B</td>\n",
              "      <td>PEG</td>\n",
              "      <td>1.26</td>\n",
              "      <td>EPS next Q</td>\n",
              "      <td>2.37</td>\n",
              "      <td>Inst Own</td>\n",
              "      <td>61.00%</td>\n",
              "      <td>Short Float</td>\n",
              "      <td>2.07%</td>\n",
              "      <td>Perf Quarter</td>\n",
              "      <td>17.47%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Sales</td>\n",
              "      <td>261.61B</td>\n",
              "      <td>P/S</td>\n",
              "      <td>3.53</td>\n",
              "      <td>EPS this Y</td>\n",
              "      <td>32.60%</td>\n",
              "      <td>Inst Trans</td>\n",
              "      <td>-0.74%</td>\n",
              "      <td>Short Ratio</td>\n",
              "      <td>2.89</td>\n",
              "      <td>Perf Half Y</td>\n",
              "      <td>-10.61%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Book/sh</td>\n",
              "      <td>24.89</td>\n",
              "      <td>P/B</td>\n",
              "      <td>7.84</td>\n",
              "      <td>EPS next Y</td>\n",
              "      <td>11.87%</td>\n",
              "      <td>ROA</td>\n",
              "      <td>16.30%</td>\n",
              "      <td>Target Price</td>\n",
              "      <td>180.05</td>\n",
              "      <td>Perf Year</td>\n",
              "      <td>11.33%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Cash/sh</td>\n",
              "      <td>18.25</td>\n",
              "      <td>P/C</td>\n",
              "      <td>10.69</td>\n",
              "      <td>EPS next 5Y</td>\n",
              "      <td>13.00%</td>\n",
              "      <td>ROE</td>\n",
              "      <td>50.90%</td>\n",
              "      <td>52W Range</td>\n",
              "      <td>142.00 - 233.47</td>\n",
              "      <td>Perf YTD</td>\n",
              "      <td>23.68%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Dividend</td>\n",
              "      <td>2.92</td>\n",
              "      <td>P/FCF</td>\n",
              "      <td>19.24</td>\n",
              "      <td>EPS past 5Y</td>\n",
              "      <td>16.50%</td>\n",
              "      <td>ROI</td>\n",
              "      <td>26.60%</td>\n",
              "      <td>52W High</td>\n",
              "      <td>-16.44%</td>\n",
              "      <td>Beta</td>\n",
              "      <td>1.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Dividend %</td>\n",
              "      <td>1.50%</td>\n",
              "      <td>Quick Ratio</td>\n",
              "      <td>1.30</td>\n",
              "      <td>Sales past 5Y</td>\n",
              "      <td>9.20%</td>\n",
              "      <td>Gross Margin</td>\n",
              "      <td>38.20%</td>\n",
              "      <td>52W Low</td>\n",
              "      <td>37.39%</td>\n",
              "      <td>ATR</td>\n",
              "      <td>3.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Employees</td>\n",
              "      <td>132000</td>\n",
              "      <td>Current Ratio</td>\n",
              "      <td>1.30</td>\n",
              "      <td>Sales Q/Q</td>\n",
              "      <td>-4.50%</td>\n",
              "      <td>Oper. Margin</td>\n",
              "      <td>26.00%</td>\n",
              "      <td>RSI (14)</td>\n",
              "      <td>82.93</td>\n",
              "      <td>Volatility</td>\n",
              "      <td>2.20% 1.56%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Optionable</td>\n",
              "      <td>Yes</td>\n",
              "      <td>Debt/Eq</td>\n",
              "      <td>0.97</td>\n",
              "      <td>EPS Q/Q</td>\n",
              "      <td>-4.80%</td>\n",
              "      <td>Profit Margin</td>\n",
              "      <td>22.70%</td>\n",
              "      <td>Rel Volume</td>\n",
              "      <td>1.49</td>\n",
              "      <td>Prev Close</td>\n",
              "      <td>188.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Shortable</td>\n",
              "      <td>Yes</td>\n",
              "      <td>LT Debt/Eq</td>\n",
              "      <td>0.79</td>\n",
              "      <td>Earnings</td>\n",
              "      <td>Jan 29 AMC</td>\n",
              "      <td>Payout</td>\n",
              "      <td>23.00%</td>\n",
              "      <td>Avg Volume</td>\n",
              "      <td>33.54M</td>\n",
              "      <td>Price</td>\n",
              "      <td>195.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Recom</td>\n",
              "      <td>2.20</td>\n",
              "      <td>SMA20</td>\n",
              "      <td>9.57%</td>\n",
              "      <td>SMA50</td>\n",
              "      <td>15.79%</td>\n",
              "      <td>SMA200</td>\n",
              "      <td>2.33%</td>\n",
              "      <td>Volume</td>\n",
              "      <td>50027194</td>\n",
              "      <td>Change</td>\n",
              "      <td>3.68%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           key        value            key  value            key       value  \\\n",
              "0        Index  DJIA S&P500            P/E  16.35      EPS (ttm)       11.94   \n",
              "1   Market Cap      923.91B    Forward P/E  15.30     EPS next Y       12.75   \n",
              "2       Income       58.33B            PEG   1.26     EPS next Q        2.37   \n",
              "3        Sales      261.61B            P/S   3.53     EPS this Y      32.60%   \n",
              "4      Book/sh        24.89            P/B   7.84     EPS next Y      11.87%   \n",
              "5      Cash/sh        18.25            P/C  10.69    EPS next 5Y      13.00%   \n",
              "6     Dividend         2.92          P/FCF  19.24    EPS past 5Y      16.50%   \n",
              "7   Dividend %        1.50%    Quick Ratio   1.30  Sales past 5Y       9.20%   \n",
              "8    Employees       132000  Current Ratio   1.30      Sales Q/Q      -4.50%   \n",
              "9   Optionable          Yes        Debt/Eq   0.97        EPS Q/Q      -4.80%   \n",
              "10   Shortable          Yes     LT Debt/Eq   0.79       Earnings  Jan 29 AMC   \n",
              "11       Recom         2.20          SMA20  9.57%          SMA50      15.79%   \n",
              "\n",
              "              key   value           key            value           key  \\\n",
              "0     Insider Own   0.08%  Shs Outstand            4.74B     Perf Week   \n",
              "1   Insider Trans  -6.04%     Shs Float            4.68B    Perf Month   \n",
              "2        Inst Own  61.00%   Short Float            2.07%  Perf Quarter   \n",
              "3      Inst Trans  -0.74%   Short Ratio             2.89   Perf Half Y   \n",
              "4             ROA  16.30%  Target Price           180.05     Perf Year   \n",
              "5             ROE  50.90%     52W Range  142.00 - 233.47      Perf YTD   \n",
              "6             ROI  26.60%      52W High          -16.44%          Beta   \n",
              "7    Gross Margin  38.20%       52W Low           37.39%           ATR   \n",
              "8    Oper. Margin  26.00%      RSI (14)            82.93    Volatility   \n",
              "9   Profit Margin  22.70%    Rel Volume             1.49    Prev Close   \n",
              "10         Payout  23.00%    Avg Volume           33.54M         Price   \n",
              "11         SMA200   2.33%        Volume         50027194        Change   \n",
              "\n",
              "          value  \n",
              "0         6.18%  \n",
              "1        13.40%  \n",
              "2        17.47%  \n",
              "3       -10.61%  \n",
              "4        11.33%  \n",
              "5        23.68%  \n",
              "6          1.12  \n",
              "7          3.23  \n",
              "8   2.20% 1.56%  \n",
              "9        188.16  \n",
              "10       195.09  \n",
              "11        3.68%  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "metadata": {
        "id": "fu7V_wuZ7Piy",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 컬럼을 행으로 만들기"
      ]
    },
    {
      "metadata": {
        "id": "ZHLxu3U-7Nzy",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 700
        },
        "outputId": "0288c2ba-779b-4b91-c380-18d1f476ab66"
      },
      "cell_type": "code",
      "source": [
        "df_list = [df.iloc[:, i*2: i*2+2] for i in range(6)]\n",
        "df_factor = pd.concat(df_list, ignore_index=True)\n",
        "\n",
        "df_factor.set_index('key', inplace=True)\n",
        "df_factor.head(20)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>key</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Index</th>\n",
              "      <td>DJIA S&amp;P500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Market Cap</th>\n",
              "      <td>923.91B</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Income</th>\n",
              "      <td>58.33B</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sales</th>\n",
              "      <td>261.61B</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Book/sh</th>\n",
              "      <td>24.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cash/sh</th>\n",
              "      <td>18.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dividend</th>\n",
              "      <td>2.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dividend %</th>\n",
              "      <td>1.50%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Employees</th>\n",
              "      <td>132000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Optionable</th>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Shortable</th>\n",
              "      <td>Yes</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Recom</th>\n",
              "      <td>2.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>P/E</th>\n",
              "      <td>16.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Forward P/E</th>\n",
              "      <td>15.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PEG</th>\n",
              "      <td>1.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>P/S</th>\n",
              "      <td>3.53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>P/B</th>\n",
              "      <td>7.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>P/C</th>\n",
              "      <td>10.69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>P/FCF</th>\n",
              "      <td>19.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Quick Ratio</th>\n",
              "      <td>1.30</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                   value\n",
              "key                     \n",
              "Index        DJIA S&P500\n",
              "Market Cap       923.91B\n",
              "Income            58.33B\n",
              "Sales            261.61B\n",
              "Book/sh            24.89\n",
              "Cash/sh            18.25\n",
              "Dividend            2.92\n",
              "Dividend %         1.50%\n",
              "Employees         132000\n",
              "Optionable           Yes\n",
              "Shortable            Yes\n",
              "Recom               2.20\n",
              "P/E                16.35\n",
              "Forward P/E        15.30\n",
              "PEG                 1.26\n",
              "P/S                 3.53\n",
              "P/B                 7.84\n",
              "P/C                10.69\n",
              "P/FCF              19.24\n",
              "Quick Ratio         1.30"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "metadata": {
        "id": "2GmfN2x77xf1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 390
        },
        "outputId": "5525f074-fd61-4333-9a41-fc0e8c42668e"
      },
      "cell_type": "code",
      "source": [
        "df_factor.tail(10)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>value</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>key</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Perf Quarter</th>\n",
              "      <td>17.47%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Perf Half Y</th>\n",
              "      <td>-10.61%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Perf Year</th>\n",
              "      <td>11.33%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Perf YTD</th>\n",
              "      <td>23.68%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Beta</th>\n",
              "      <td>1.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ATR</th>\n",
              "      <td>3.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Volatility</th>\n",
              "      <td>2.20% 1.56%</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Prev Close</th>\n",
              "      <td>188.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Price</th>\n",
              "      <td>195.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Change</th>\n",
              "      <td>3.68%</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                    value\n",
              "key                      \n",
              "Perf Quarter       17.47%\n",
              "Perf Half Y       -10.61%\n",
              "Perf Year          11.33%\n",
              "Perf YTD           23.68%\n",
              "Beta                 1.12\n",
              "ATR                  3.23\n",
              "Volatility    2.20% 1.56%\n",
              "Prev Close         188.16\n",
              "Price              195.09\n",
              "Change              3.68%"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "metadata": {
        "id": "DCFUwx7c71Kk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "afe99f5b-6190-46d2-e925-a5cc1c0bd173"
      },
      "cell_type": "code",
      "source": [
        "len(df_factor)"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "72"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "metadata": {
        "id": "u8QlMDsx74b0",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 주요 팩터\n",
        "\n",
        "*   Market Cap\n",
        "*   Dividend Yield\n",
        "*   PER\n",
        "*   PBR\n",
        "*   ROE\n",
        "*   Beta\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "metadata": {
        "id": "N9hrWpKm8d5f",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "2ce9cb12-c972-40a7-bba4-2d5460b01219"
      },
      "cell_type": "code",
      "source": [
        "v = df_factor.value\n",
        "\n",
        "marcap = v['Market Cap']\n",
        "dividend = v['Dividend %']\n",
        "per = v['P/E']\n",
        "pbr = v['P/B']\n",
        "beta = v['Beta']\n",
        "roe = v['ROE']\n",
        "\n",
        "marcap, dividend, per, pbr, beta, roe "
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('923.91B', '1.50%', '16.35', '7.84', '1.12', '50.90%')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    },
    {
      "metadata": {
        "id": "lxShDRAx8iVY",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 데이터 전처리\n",
        "\n",
        "1.   단위(B, M, K) 수치값으로 변환\n",
        "2.   '%' 삭제\n",
        "3.   float 타입 변환\n",
        "\n"
      ]
    },
    {
      "metadata": {
        "id": "Hb7J5T9S80X0",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import re\n",
        "\n",
        "def _conv_to_float(s):\n",
        "    if s[-1] == '%':\n",
        "        s = s.replace('%', '')\n",
        "    if s[-1] in list('BMK'):\n",
        "        powers = {'B': 10 ** 9, 'M': 10 ** 6, 'K': 10 ** 3, '': 1}\n",
        "        m = re.search(\"([0-9\\.]+)(M|B|K|)\", s)\n",
        "        if m:\n",
        "            val, mag = m.group(1), m.group(2)\n",
        "            return float(val) * powers[mag]\n",
        "    try:\n",
        "        result = float(s)\n",
        "    except:\n",
        "        result = None\n",
        "    return result"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Zb0B1srW8hNW",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "fcf0974c-63e8-4786-fdf3-9f248b4d8d76"
      },
      "cell_type": "code",
      "source": [
        "marcap = _conv_to_float(marcap)\n",
        "dividend = _conv_to_float(dividend)\n",
        "per = _conv_to_float(per)\n",
        "pbr = _conv_to_float(pbr)\n",
        "beta = _conv_to_float(beta)\n",
        "roe = _conv_to_float(roe)\n",
        "\n",
        "marcap, dividend, per, pbr, beta, roe  "
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(923910000000.0, 1.5, 16.35, 7.84, 1.12, 50.9)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "metadata": {
        "id": "U0xbedXq87db",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 팩터 크롤링, 함수로 정리하기"
      ]
    },
    {
      "metadata": {
        "id": "DSxaTAmj8-yT",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import re\n",
        "\n",
        "## 데이터 전처리 변환\n",
        "def _conv_to_float(s):\n",
        "    if s[-1] == '%':\n",
        "        s = s.replace('%', '')\n",
        "    if s[-1] in list('BMK'):\n",
        "        powers = {'B': 10 ** 9, 'M': 10 ** 6, 'K': 10 ** 3, '': 1}\n",
        "        m = re.search(\"([0-9\\.]+)(M|B|K|)\", s)\n",
        "        if m:\n",
        "            val, mag = m.group(1), m.group(2)\n",
        "            return float(val) * powers[mag]\n",
        "    try:\n",
        "        result = float(s)\n",
        "    except:\n",
        "        result = None\n",
        "    return result\n",
        "\n",
        "def stock_factors(sym):\n",
        "    url = 'https://finviz.com/quote.ashx?t=' + sym\n",
        "    df = pd.read_html(url)[7]\n",
        "    df.columns = ['key', 'value'] * 6\n",
        "\n",
        "    ## 컬럼을 행으로 만들기\n",
        "    df_list = [df.iloc[:, i*2: i*2+2] for i in range(6)]\n",
        "    df_factor = pd.concat(df_list, ignore_index=True)\n",
        "    df_factor.set_index('key', inplace=True)\n",
        "\n",
        "    v = df_factor.value\n",
        "    marcap = _conv_to_float(v['Market Cap'])\n",
        "    dividend = _conv_to_float(v['Dividend %'])\n",
        "    per = _conv_to_float(v['P/E'])\n",
        "    pbr = _conv_to_float(v['P/B'])\n",
        "    beta = _conv_to_float(v['Beta'])\n",
        "    roe = _conv_to_float(v['ROE'])\n",
        "\n",
        "    return {'MarCap':marcap, 'Dividend':dividend, 'PER':per, 'PBR':pbr, 'Beta':beta, 'ROE':roe}"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "MppQbuS59DAJ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "outputId": "cf2b18c9-6bdc-4703-fe58-a20e943b51a1"
      },
      "cell_type": "code",
      "source": [
        "stock_factors('AAPL')"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Beta': 1.12,\n",
              " 'Dividend': 1.5,\n",
              " 'MarCap': 923910000000.0,\n",
              " 'PBR': 7.84,\n",
              " 'PER': 16.35,\n",
              " 'ROE': 50.9}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "metadata": {
        "id": "3mVCx3Zz9WxG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "outputId": "4a343f2d-0313-486f-d61b-d39d58d6183d"
      },
      "cell_type": "code",
      "source": [
        "stock_factors('NFLX')"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Beta': 1.38,\n",
              " 'Dividend': None,\n",
              " 'MarCap': 163770000000.0,\n",
              " 'PBR': 31.49,\n",
              " 'PER': 144.23,\n",
              " 'ROE': 25.8}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "metadata": {
        "id": "a2wenaSq9atP",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 전종목 팩터 데이터 수집과 저장(JSON)"
      ]
    },
    {
      "metadata": {
        "id": "9pSd1O2l9eOA",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# 디렉토리가 없으면 생성\n",
        "import os\n",
        "\n",
        "folder = \"sp500_factors/\"\n",
        "\n",
        "if not os.path.isdir(folder):\n",
        "    os.mkdir(folder)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "hoR4qFQa9hXM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 8602
        },
        "outputId": "b6ff2b15-a97d-4a89-daf4-6556d6dfed06"
      },
      "cell_type": "code",
      "source": [
        "import json\n",
        "import pandas as pd\n",
        "\n",
        "re_map_sym = {'BRKB': 'BRK-B', 'BR': 'BRK-A', 'BFB':'BF-B'}\n",
        "\n",
        "for ix, row in sp500.iterrows():\n",
        "    sym, name = row['Symbol'], row['Name']\n",
        "    json_fn = folder + '%s.json' % (sym)\n",
        "    if os.path.exists(json_fn):\n",
        "        print('skip', json_fn)\n",
        "        continue\n",
        "\n",
        "    if sym in re_map_sym:\n",
        "        sym = re_map_sym[sym]\n",
        "    factors = stock_factors(sym)\n",
        "    with open(json_fn, 'w') as f:\n",
        "        json.dump(factors, f)\n",
        "    print(sym, name)"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "MMM 3M Company\n",
            "ABT Abbott Laboratories\n",
            "ABBV AbbVie Inc.\n",
            "ABMD ABIOMED Inc\n",
            "ACN Accenture plc\n",
            "ATVI Activision Blizzard\n",
            "ADBE Adobe Systems Inc\n",
            "AMD Advanced Micro Devices Inc\n",
            "AAP Advance Auto Parts\n",
            "AES AES Corp\n",
            "AMG Affiliated Managers Group Inc\n",
            "AFL AFLAC Inc\n",
            "A Agilent Technologies Inc\n",
            "APD Air Products & Chemicals Inc\n",
            "AKAM Akamai Technologies Inc\n",
            "ALK Alaska Air Group Inc\n",
            "ALB Albemarle Corp\n",
            "ARE Alexandria Real Estate Equities\n",
            "ALXN Alexion Pharmaceuticals\n",
            "ALGN Align Technology\n",
            "ALLE Allegion\n",
            "AGN Allergan, Plc\n",
            "ADS Alliance Data Systems\n",
            "LNT Alliant Energy Corp\n",
            "ALL Allstate Corp\n",
            "GOOGL Alphabet Inc Class A\n",
            "GOOG Alphabet Inc Class C\n",
            "MO Altria Group Inc\n",
            "AMZN Amazon.com Inc.\n",
            "AEE Ameren Corp\n",
            "AAL American Airlines Group\n",
            "AEP American Electric Power\n",
            "AXP American Express Co\n",
            "AIG American International Group\n",
            "AMT American Tower Corp.\n",
            "AWK American Water Works Company Inc\n",
            "AMP Ameriprise Financial\n",
            "ABC AmerisourceBergen Corp\n",
            "AME AMETEK Inc.\n",
            "AMGN Amgen Inc.\n",
            "APH Amphenol Corp\n",
            "APC Anadarko Petroleum Corp\n",
            "ADI Analog Devices, Inc.\n",
            "ANSS ANSYS\n",
            "ANTM Anthem Inc.\n",
            "AON Aon plc\n",
            "AOS A.O. Smith Corp\n",
            "APA Apache Corporation\n",
            "AIV Apartment Investment & Management\n",
            "AAPL Apple Inc.\n",
            "AMAT Applied Materials Inc.\n",
            "APTV Aptiv Plc\n",
            "ADM Archer-Daniels-Midland Co\n",
            "ARNC Arconic Inc.\n",
            "ANET Arista Networks\n",
            "AJG Arthur J. Gallagher & Co.\n",
            "AIZ Assurant\n",
            "ATO Atmos Energy Corp\n",
            "T AT&T Inc.\n",
            "ADSK Autodesk Inc.\n",
            "ADP Automatic Data Processing\n",
            "AZO AutoZone Inc\n",
            "AVB AvalonBay Communities, Inc.\n",
            "AVY Avery Dennison Corp\n",
            "BHGE Baker Hughes, a GE Company\n",
            "BLL Ball Corp\n",
            "BAC Bank of America Corp\n",
            "BK The Bank of New York Mellon Corp.\n",
            "BAX Baxter International Inc.\n",
            "BBT BB&T Corporation\n",
            "BDX Becton Dickinson\n",
            "BRK-B Berkshire Hathaway\n",
            "BBY Best Buy Co. Inc.\n",
            "BIIB Biogen Inc.\n",
            "BLK BlackRock\n",
            "HRB Block H&R\n",
            "BA Boeing Company\n",
            "BKNG Booking Holdings Inc\n",
            "BWA BorgWarner\n",
            "BXP Boston Properties\n",
            "BSX Boston Scientific\n",
            "BHF Brighthouse Financial Inc\n",
            "BMY Bristol-Myers Squibb\n",
            "AVGO Broadcom\n",
            "BRK-A Broadridge Financial Solutions\n",
            "BF-B Brown-Forman Corp.\n",
            "CHRW C. H. Robinson Worldwide\n",
            "COG Cabot Oil & Gas\n",
            "CDNS Cadence Design Systems\n",
            "CPB Campbell Soup\n",
            "COF Capital One Financial\n",
            "CPRI Capri Holdings\n",
            "CAH Cardinal Health Inc.\n",
            "KMX Carmax Inc\n",
            "CCL Carnival Corp.\n",
            "CAT Caterpillar Inc.\n",
            "CBOE Cboe Global Markets\n",
            "CBRE CBRE Group\n",
            "CBS CBS Corp.\n",
            "CE Celanese Corp.\n",
            "CELG Celgene Corp.\n",
            "CNC Centene Corporation\n",
            "CNP CenterPoint Energy\n",
            "CTL CenturyLink Inc\n",
            "CERN Cerner\n",
            "CF CF Industries Holdings Inc\n",
            "SCHW Charles Schwab Corporation\n",
            "CHTR Charter Communications\n",
            "CVX Chevron Corp.\n",
            "CMG Chipotle Mexican Grill\n",
            "CB Chubb Limited\n",
            "CHD Church & Dwight\n",
            "CI CIGNA Corp.\n",
            "XEC Cimarex Energy\n",
            "CINF Cincinnati Financial\n",
            "CTAS Cintas Corporation\n",
            "CSCO Cisco Systems\n",
            "C Citigroup Inc.\n",
            "CFG Citizens Financial Group\n",
            "CTXS Citrix Systems\n",
            "CLX The Clorox Company\n",
            "CME CME Group Inc.\n",
            "CMS CMS Energy\n",
            "KO Coca-Cola Company\n",
            "CTSH Cognizant Technology Solutions\n",
            "CL Colgate-Palmolive\n",
            "CMCSA Comcast Corp.\n",
            "CMA Comerica Inc.\n",
            "CAG Conagra Brands\n",
            "CXO Concho Resources\n",
            "COP ConocoPhillips\n",
            "ED Consolidated Edison\n",
            "STZ Constellation Brands\n",
            "COO The Cooper Companies\n",
            "CPRT Copart Inc\n",
            "GLW Corning Inc.\n",
            "COST Costco Wholesale Corp.\n",
            "COTY Coty, Inc\n",
            "CCI Crown Castle International Corp.\n",
            "CSX CSX Corp.\n",
            "CMI Cummins Inc.\n",
            "CVS CVS Health\n",
            "DHI D. R. Horton\n",
            "DHR Danaher Corp.\n",
            "DRI Darden Restaurants\n",
            "DVA DaVita Inc.\n",
            "DE Deere & Co.\n",
            "DAL Delta Air Lines Inc.\n",
            "XRAY Dentsply Sirona\n",
            "DVN Devon Energy\n",
            "FANG Diamondback Energy\n",
            "DLR Digital Realty Trust Inc\n",
            "DFS Discover Financial Services\n",
            "DISCA Discovery Inc. Class A\n",
            "DISCK Discovery Inc. Class C\n",
            "DISH Dish Network\n",
            "DG Dollar General\n",
            "DLTR Dollar Tree\n",
            "D Dominion Energy\n",
            "DOV Dover Corp.\n",
            "DWDP DowDuPont\n",
            "DTE DTE Energy Co.\n",
            "DRE Duke Realty Corp\n",
            "DUK Duke Energy\n",
            "DXC DXC Technology\n",
            "ETFC E*Trade\n",
            "EMN Eastman Chemical\n",
            "ETN Eaton Corporation\n",
            "EBAY eBay Inc.\n",
            "ECL Ecolab Inc.\n",
            "EIX Edison Int'l\n",
            "EW Edwards Lifesciences\n",
            "EA Electronic Arts\n",
            "EMR Emerson Electric Company\n",
            "ETR Entergy Corp.\n",
            "EOG EOG Resources\n",
            "EFX Equifax Inc.\n",
            "EQIX Equinix\n",
            "EQR Equity Residential\n",
            "ESS Essex Property Trust, Inc.\n",
            "EL Estee Lauder Cos.\n",
            "EVRG Evergy\n",
            "ES Eversource Energy\n",
            "RE Everest Re Group Ltd.\n",
            "EXC Exelon Corp.\n",
            "EXPE Expedia Group\n",
            "EXPD Expeditors\n",
            "EXR Extra Space Storage\n",
            "XOM Exxon Mobil Corp.\n",
            "FFIV F5 Networks\n",
            "FB Facebook, Inc.\n",
            "FAST Fastenal Co\n",
            "FRT Federal Realty Investment Trust\n",
            "FDX FedEx Corporation\n",
            "FIS Fidelity National Information Services\n",
            "FITB Fifth Third Bancorp\n",
            "FE FirstEnergy Corp\n",
            "FRC First Republic Bank\n",
            "FISV Fiserv Inc\n",
            "FLT FleetCor Technologies Inc\n",
            "FLIR FLIR Systems\n",
            "FLS Flowserve Corporation\n",
            "FLR Fluor Corp.\n",
            "FMC FMC Corporation\n",
            "FL Foot Locker Inc\n",
            "F Ford Motor\n",
            "FTNT Fortinet\n",
            "FTV Fortive Corp\n",
            "FBHS Fortune Brands Home & Security\n",
            "BEN Franklin Resources\n",
            "FCX Freeport-McMoRan Inc.\n",
            "GPS Gap Inc.\n",
            "GRMN Garmin Ltd.\n",
            "IT Gartner Inc\n",
            "GD General Dynamics\n",
            "GE General Electric\n",
            "GIS General Mills\n",
            "GM General Motors\n",
            "GPC Genuine Parts\n",
            "GILD Gilead Sciences\n",
            "GPN Global Payments Inc.\n",
            "GS Goldman Sachs Group\n",
            "GWW Grainger (W.W.) Inc.\n",
            "HAL Halliburton Co.\n",
            "HBI Hanesbrands Inc\n",
            "HOG Harley-Davidson\n",
            "HRS Harris Corporation\n",
            "HIG Hartford Financial Svc.Gp.\n",
            "HAS Hasbro Inc.\n",
            "HCA HCA Holdings\n",
            "HCP HCP Inc.\n",
            "HP Helmerich & Payne\n",
            "HSIC Henry Schein\n",
            "HSY The Hershey Company\n",
            "HES Hess Corporation\n",
            "HPE Hewlett Packard Enterprise\n",
            "HLT Hilton Worldwide Holdings Inc\n",
            "HFC HollyFrontier Corp\n",
            "HOLX Hologic\n",
            "HD Home Depot\n",
            "HON Honeywell Int'l Inc.\n",
            "HRL Hormel Foods Corp.\n",
            "HST Host Hotels & Resorts\n",
            "HPQ HP Inc.\n",
            "HUM Humana Inc.\n",
            "HBAN Huntington Bancshares\n",
            "HII Huntington Ingalls Industries\n",
            "IDXX IDEXX Laboratories\n",
            "INFO IHS Markit Ltd.\n",
            "ITW Illinois Tool Works\n",
            "ILMN Illumina Inc\n",
            "IR Ingersoll-Rand PLC\n",
            "INTC Intel Corp.\n",
            "ICE Intercontinental Exchange\n",
            "IBM International Business Machines\n",
            "INCY Incyte\n",
            "IP International Paper\n",
            "IPG Interpublic Group\n",
            "IFF Intl Flavors & Fragrances\n",
            "INTU Intuit Inc.\n",
            "ISRG Intuitive Surgical Inc.\n",
            "IVZ Invesco Ltd.\n",
            "IPGP IPG Photonics Corp.\n",
            "IQV IQVIA Holdings Inc.\n",
            "IRM Iron Mountain Incorporated\n",
            "JKHY Jack Henry & Associates Inc\n",
            "JEC Jacobs Engineering Group\n",
            "JBHT J. B. Hunt Transport Services\n",
            "JEF Jefferies Financial Group\n",
            "SJM JM Smucker\n",
            "JNJ Johnson & Johnson\n",
            "JCI Johnson Controls International\n",
            "JPM JPMorgan Chase & Co.\n",
            "JNPR Juniper Networks\n",
            "KSU Kansas City Southern\n",
            "K Kellogg Co.\n",
            "KEY KeyCorp\n",
            "KEYS Keysight Technologies\n",
            "KMB Kimberly-Clark\n",
            "KIM Kimco Realty\n",
            "KMI Kinder Morgan\n",
            "KLAC KLA-Tencor Corp.\n",
            "KSS Kohl's Corp.\n",
            "KHC Kraft Heinz Co\n",
            "KR Kroger Co.\n",
            "LB L Brands Inc.\n",
            "LLL L-3 Communications Holdings\n",
            "LH Laboratory Corp. of America Holding\n",
            "LRCX Lam Research\n",
            "LW Lamb Weston Holdings Inc\n",
            "LEG Leggett & Platt\n",
            "LEN Lennar Corp.\n",
            "LLY Lilly (Eli) & Co.\n",
            "LNC Lincoln National\n",
            "LIN Linde plc\n",
            "LKQ LKQ Corporation\n",
            "LMT Lockheed Martin Corp.\n",
            "L Loews Corp.\n",
            "LOW Lowe's Cos.\n",
            "LYB LyondellBasell\n",
            "MTB M&T Bank Corp.\n",
            "MAC Macerich\n",
            "M Macy's Inc.\n",
            "MRO Marathon Oil Corp.\n",
            "MPC Marathon Petroleum\n",
            "MAR Marriott Int'l.\n",
            "MMC Marsh & McLennan\n",
            "MLM Martin Marietta Materials\n",
            "MAS Masco Corp.\n",
            "MA Mastercard Inc.\n",
            "MAT Mattel Inc.\n",
            "MKC McCormick & Co.\n",
            "MXIM Maxim Integrated Products Inc\n",
            "MCD McDonald's Corp.\n",
            "MCK McKesson Corp.\n",
            "MDT Medtronic plc\n",
            "MRK Merck & Co.\n",
            "MET MetLife Inc.\n",
            "MTD Mettler Toledo\n",
            "MGM MGM Resorts International\n",
            "MCHP Microchip Technology\n",
            "MU Micron Technology\n",
            "MSFT Microsoft Corp.\n",
            "MAA Mid-America Apartments\n",
            "MHK Mohawk Industries\n",
            "TAP Molson Coors Brewing Company\n",
            "MDLZ Mondelez International\n",
            "MNST Monster Beverage\n",
            "MCO Moody's Corp\n",
            "MS Morgan Stanley\n",
            "MOS The Mosaic Company\n",
            "MSI Motorola Solutions Inc.\n",
            "MSCI MSCI Inc\n",
            "MYL Mylan N.V.\n",
            "NDAQ Nasdaq, Inc.\n",
            "NOV National Oilwell Varco Inc.\n",
            "NKTR Nektar Therapeutics\n",
            "NTAP NetApp\n",
            "NFLX Netflix Inc.\n",
            "NWL Newell Brands\n",
            "NEM Newmont Mining Corporation\n",
            "NWSA News Corp. Class A\n",
            "NWS News Corp. Class B\n",
            "NEE NextEra Energy\n",
            "NLSN Nielsen Holdings\n",
            "NKE Nike\n",
            "NI NiSource Inc.\n",
            "NBL Noble Energy Inc\n",
            "JWN Nordstrom\n",
            "NSC Norfolk Southern Corp.\n",
            "NTRS Northern Trust Corp.\n",
            "NOC Northrop Grumman Corp.\n",
            "NCLH Norwegian Cruise Line\n",
            "NRG NRG Energy\n",
            "NUE Nucor Corp.\n",
            "NVDA Nvidia Corporation\n",
            "ORLY O'Reilly Automotive\n",
            "OXY Occidental Petroleum\n",
            "OMC Omnicom Group\n",
            "OKE ONEOK\n",
            "ORCL Oracle Corp.\n",
            "PCAR PACCAR Inc.\n",
            "PKG Packaging Corporation of America\n",
            "PH Parker-Hannifin\n",
            "PAYX Paychex Inc.\n",
            "PYPL PayPal\n",
            "PNR Pentair plc\n",
            "PBCT People's United Financial\n",
            "PEP PepsiCo Inc.\n",
            "PKI PerkinElmer\n",
            "PRGO Perrigo\n",
            "PFE Pfizer Inc.\n",
            "PM Philip Morris International\n",
            "PSX Phillips 66\n",
            "PNW Pinnacle West Capital\n",
            "PXD Pioneer Natural Resources\n",
            "PNC PNC Financial Services\n",
            "RL Polo Ralph Lauren Corp.\n",
            "PPG PPG Industries\n",
            "PPL PPL Corp.\n",
            "PFG Principal Financial Group\n",
            "PG Procter & Gamble\n",
            "PGR Progressive Corp.\n",
            "PLD Prologis\n",
            "PRU Prudential Financial\n",
            "PEG Public Serv. Enterprise Inc.\n",
            "PSA Public Storage\n",
            "PHM Pulte Homes Inc.\n",
            "PVH PVH Corp.\n",
            "QRVO Qorvo\n",
            "PWR Quanta Services Inc.\n",
            "QCOM QUALCOMM Inc.\n",
            "DGX Quest Diagnostics\n",
            "RJF Raymond James Financial Inc.\n",
            "RTN Raytheon Co.\n",
            "O Realty Income Corporation\n",
            "RHT Red Hat Inc.\n",
            "REG Regency Centers Corporation\n",
            "REGN Regeneron\n",
            "RF Regions Financial Corp.\n",
            "RSG Republic Services Inc\n",
            "RMD ResMed\n",
            "RHI Robert Half International\n",
            "ROK Rockwell Automation Inc.\n",
            "ROL Rollins Inc.\n",
            "ROP Roper Technologies\n",
            "ROST Ross Stores\n",
            "RCL Royal Caribbean Cruises Ltd\n",
            "CRM Salesforce.com\n",
            "SBAC SBA Communications\n",
            "SLB Schlumberger Ltd.\n",
            "STX Seagate Technology\n",
            "SEE Sealed Air\n",
            "SRE Sempra Energy\n",
            "SHW Sherwin-Williams\n",
            "SPG Simon Property Group Inc\n",
            "SWKS Skyworks Solutions\n",
            "SLG SL Green Realty\n",
            "SNA Snap-on\n",
            "SO Southern Co.\n",
            "LUV Southwest Airlines\n",
            "SPGI S&P Global, Inc.\n",
            "SWK Stanley Black & Decker\n",
            "SBUX Starbucks Corp.\n",
            "STT State Street Corp.\n",
            "SYK Stryker Corp.\n",
            "STI SunTrust Banks\n",
            "SIVB SVB Financial\n",
            "SYMC Symantec Corp.\n",
            "SYF Synchrony Financial\n",
            "SNPS Synopsys Inc.\n",
            "SYY Sysco Corp.\n",
            "TROW T. Rowe Price Group\n",
            "TTWO Take-Two Interactive\n",
            "TPR Tapestry, Inc.\n",
            "TGT Target Corp.\n",
            "TEL TE Connectivity Ltd.\n",
            "FTI TechnipFMC\n",
            "TFX Teleflex Inc\n",
            "TXN Texas Instruments\n",
            "TXT Textron Inc.\n",
            "TMO Thermo Fisher Scientific\n",
            "TIF Tiffany & Co.\n",
            "TWTR Twitter, Inc.\n",
            "TJX TJX Companies Inc.\n",
            "TMK Torchmark Corp.\n",
            "TSS Total System Services\n",
            "TSCO Tractor Supply Company\n",
            "TDG TransDigm Group\n",
            "TRV The Travelers Companies Inc.\n",
            "TRIP TripAdvisor\n",
            "FOXA Twenty-First Century Fox Class A\n",
            "FOX Twenty-First Century Fox Class B\n",
            "TSN Tyson Foods\n",
            "UDR UDR Inc\n",
            "ULTA Ulta Beauty\n",
            "USB U.S. Bancorp\n",
            "UAA Under Armour Class A\n",
            "UA Under Armour Class C\n",
            "UNP Union Pacific\n",
            "UAL United Continental Holdings\n",
            "UNH United Health Group Inc.\n",
            "UPS United Parcel Service\n",
            "URI United Rentals, Inc.\n",
            "UTX United Technologies\n",
            "UHS Universal Health Services, Inc.\n",
            "UNM Unum Group\n",
            "VFC V.F. Corp.\n",
            "VLO Valero Energy\n",
            "VAR Varian Medical Systems\n",
            "VTR Ventas Inc\n",
            "VRSN Verisign Inc.\n",
            "VRSK Verisk Analytics\n",
            "VZ Verizon Communications\n",
            "VRTX Vertex Pharmaceuticals Inc\n",
            "VIAB Viacom Inc.\n",
            "V Visa Inc.\n",
            "VNO Vornado Realty Trust\n",
            "VMC Vulcan Materials\n",
            "WAB Wabtec Corporation\n",
            "WMT Walmart\n",
            "WBA Walgreens Boots Alliance\n",
            "DIS The Walt Disney Company\n",
            "WM Waste Management Inc.\n",
            "WAT Waters Corporation\n",
            "WEC Wec Energy Group Inc\n",
            "WCG WellCare\n",
            "WFC Wells Fargo\n",
            "WELL Welltower Inc.\n",
            "WDC Western Digital\n",
            "WU Western Union Co\n",
            "WRK WestRock\n",
            "WY Weyerhaeuser\n",
            "WHR Whirlpool Corp.\n",
            "WMB Williams Cos.\n",
            "WLTW Willis Towers Watson\n",
            "WYNN Wynn Resorts Ltd\n",
            "XEL Xcel Energy Inc\n",
            "XRX Xerox\n",
            "XLNX Xilinx\n",
            "XYL Xylem Inc.\n",
            "YUM Yum! Brands Inc\n",
            "ZBH Zimmer Biomet Holdings\n",
            "ZION Zions Bancorp\n",
            "ZTS Zoetis\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "tiXGxOEMEyYz",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "# JSON 팩터 데이터 읽기\n",
        "for ix, row in sp500.iterrows():\n",
        "    sym, name = row['Symbol'], row['Name']\n",
        "    json_fn = folder + '%s.json' % (sym)\n",
        "\n",
        "    with open(json_fn, 'r') as f:\n",
        "        factors = json.load(f)\n",
        "        \n",
        "        for f in ['MarCap', 'Dividend', 'PER', 'PBR', 'Beta', 'ROE']:\n",
        "            sp500.loc[ix,f] = factors[f]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "jYZkmxkQE1Yr",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 669
        },
        "outputId": "41568da0-9577-4477-f586-3a618eeb1ee8"
      },
      "cell_type": "code",
      "source": [
        "sp500.head(20)"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Symbol</th>\n",
              "      <th>Name</th>\n",
              "      <th>Sector</th>\n",
              "      <th>Industry</th>\n",
              "      <th>MarCap</th>\n",
              "      <th>Dividend</th>\n",
              "      <th>PER</th>\n",
              "      <th>PBR</th>\n",
              "      <th>Beta</th>\n",
              "      <th>ROE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>MMM</td>\n",
              "      <td>3M Company</td>\n",
              "      <td>Industrials</td>\n",
              "      <td>Industrial Conglomerates</td>\n",
              "      <td>121720000000.00</td>\n",
              "      <td>2.75</td>\n",
              "      <td>22.80</td>\n",
              "      <td>12.43</td>\n",
              "      <td>1.04</td>\n",
              "      <td>51.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>ABT</td>\n",
              "      <td>Abbott Laboratories</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Health Care Equipment</td>\n",
              "      <td>140980000000.00</td>\n",
              "      <td>1.60</td>\n",
              "      <td>57.51</td>\n",
              "      <td>4.62</td>\n",
              "      <td>1.13</td>\n",
              "      <td>7.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>ABBV</td>\n",
              "      <td>AbbVie Inc.</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Pharmaceuticals</td>\n",
              "      <td>120320000000.00</td>\n",
              "      <td>5.27</td>\n",
              "      <td>22.42</td>\n",
              "      <td>nan</td>\n",
              "      <td>1.15</td>\n",
              "      <td>-202.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ABMD</td>\n",
              "      <td>ABIOMED Inc</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Health Care Equipment</td>\n",
              "      <td>14860000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>70.39</td>\n",
              "      <td>17.85</td>\n",
              "      <td>0.36</td>\n",
              "      <td>29.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>ACN</td>\n",
              "      <td>Accenture plc</td>\n",
              "      <td>Information Technology</td>\n",
              "      <td>IT Consulting &amp; Other Services</td>\n",
              "      <td>106230000000.00</td>\n",
              "      <td>1.74</td>\n",
              "      <td>24.80</td>\n",
              "      <td>8.48</td>\n",
              "      <td>1.11</td>\n",
              "      <td>39.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>ATVI</td>\n",
              "      <td>Activision Blizzard</td>\n",
              "      <td>Communication Services</td>\n",
              "      <td>Interactive Home Entertainment</td>\n",
              "      <td>37180000000.00</td>\n",
              "      <td>0.76</td>\n",
              "      <td>24.51</td>\n",
              "      <td>3.27</td>\n",
              "      <td>0.82</td>\n",
              "      <td>17.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>ADBE</td>\n",
              "      <td>Adobe Systems Inc</td>\n",
              "      <td>Information Technology</td>\n",
              "      <td>Application Software</td>\n",
              "      <td>134540000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>47.34</td>\n",
              "      <td>13.78</td>\n",
              "      <td>1.10</td>\n",
              "      <td>27.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>AMD</td>\n",
              "      <td>Advanced Micro Devices Inc</td>\n",
              "      <td>Information Technology</td>\n",
              "      <td>Semiconductors</td>\n",
              "      <td>27890000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>86.88</td>\n",
              "      <td>21.96</td>\n",
              "      <td>3.39</td>\n",
              "      <td>33.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>AAP</td>\n",
              "      <td>Advance Auto Parts</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Automotive Retail</td>\n",
              "      <td>12340000000.00</td>\n",
              "      <td>0.14</td>\n",
              "      <td>29.90</td>\n",
              "      <td>3.48</td>\n",
              "      <td>0.99</td>\n",
              "      <td>11.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>AES</td>\n",
              "      <td>AES Corp</td>\n",
              "      <td>Utilities</td>\n",
              "      <td>Independent Power Producers &amp; Energy Traders</td>\n",
              "      <td>12160000000.00</td>\n",
              "      <td>3.01</td>\n",
              "      <td>11.86</td>\n",
              "      <td>3.79</td>\n",
              "      <td>1.08</td>\n",
              "      <td>37.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>AMG</td>\n",
              "      <td>Affiliated Managers Group Inc</td>\n",
              "      <td>Financials</td>\n",
              "      <td>Asset Management &amp; Custody Banks</td>\n",
              "      <td>5350000000.00</td>\n",
              "      <td>1.22</td>\n",
              "      <td>24.55</td>\n",
              "      <td>1.60</td>\n",
              "      <td>1.49</td>\n",
              "      <td>6.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>AFL</td>\n",
              "      <td>AFLAC Inc</td>\n",
              "      <td>Financials</td>\n",
              "      <td>Life &amp; Health Insurance</td>\n",
              "      <td>37310000000.00</td>\n",
              "      <td>2.16</td>\n",
              "      <td>13.19</td>\n",
              "      <td>1.62</td>\n",
              "      <td>0.78</td>\n",
              "      <td>12.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>A</td>\n",
              "      <td>Agilent Technologies Inc</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Health Care Equipment</td>\n",
              "      <td>26080000000.00</td>\n",
              "      <td>0.80</td>\n",
              "      <td>22.86</td>\n",
              "      <td>5.18</td>\n",
              "      <td>1.40</td>\n",
              "      <td>24.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>APD</td>\n",
              "      <td>Air Products &amp; Chemicals Inc</td>\n",
              "      <td>Materials</td>\n",
              "      <td>Industrial Gases</td>\n",
              "      <td>41190000000.00</td>\n",
              "      <td>2.48</td>\n",
              "      <td>24.88</td>\n",
              "      <td>3.78</td>\n",
              "      <td>0.83</td>\n",
              "      <td>15.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>AKAM</td>\n",
              "      <td>Akamai Technologies Inc</td>\n",
              "      <td>Information Technology</td>\n",
              "      <td>Internet Services &amp; Infrastructure</td>\n",
              "      <td>12030000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>40.96</td>\n",
              "      <td>3.75</td>\n",
              "      <td>0.56</td>\n",
              "      <td>9.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>ALK</td>\n",
              "      <td>Alaska Air Group Inc</td>\n",
              "      <td>Industrials</td>\n",
              "      <td>Airlines</td>\n",
              "      <td>6810000000.00</td>\n",
              "      <td>2.54</td>\n",
              "      <td>15.67</td>\n",
              "      <td>1.81</td>\n",
              "      <td>0.81</td>\n",
              "      <td>12.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>ALB</td>\n",
              "      <td>Albemarle Corp</td>\n",
              "      <td>Materials</td>\n",
              "      <td>Specialty Chemicals</td>\n",
              "      <td>9070000000.00</td>\n",
              "      <td>1.72</td>\n",
              "      <td>14.04</td>\n",
              "      <td>2.53</td>\n",
              "      <td>1.67</td>\n",
              "      <td>19.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>ARE</td>\n",
              "      <td>Alexandria Real Estate Equities</td>\n",
              "      <td>Real Estate</td>\n",
              "      <td>Office REITs</td>\n",
              "      <td>16210000000.00</td>\n",
              "      <td>2.72</td>\n",
              "      <td>40.92</td>\n",
              "      <td>2.08</td>\n",
              "      <td>0.95</td>\n",
              "      <td>5.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>ALXN</td>\n",
              "      <td>Alexion Pharmaceuticals</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Biotechnology</td>\n",
              "      <td>29970000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>1742.99</td>\n",
              "      <td>3.27</td>\n",
              "      <td>1.57</td>\n",
              "      <td>0.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>ALGN</td>\n",
              "      <td>Align Technology</td>\n",
              "      <td>Health Care</td>\n",
              "      <td>Health Care Supplies</td>\n",
              "      <td>22030000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>57.04</td>\n",
              "      <td>17.90</td>\n",
              "      <td>2.12</td>\n",
              "      <td>33.40</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Symbol                             Name                  Sector  \\\n",
              "0     MMM                       3M Company             Industrials   \n",
              "1     ABT              Abbott Laboratories             Health Care   \n",
              "2    ABBV                      AbbVie Inc.             Health Care   \n",
              "3    ABMD                      ABIOMED Inc             Health Care   \n",
              "4     ACN                    Accenture plc  Information Technology   \n",
              "5    ATVI              Activision Blizzard  Communication Services   \n",
              "6    ADBE                Adobe Systems Inc  Information Technology   \n",
              "7     AMD       Advanced Micro Devices Inc  Information Technology   \n",
              "8     AAP               Advance Auto Parts  Consumer Discretionary   \n",
              "9     AES                         AES Corp               Utilities   \n",
              "10    AMG    Affiliated Managers Group Inc              Financials   \n",
              "11    AFL                        AFLAC Inc              Financials   \n",
              "12      A         Agilent Technologies Inc             Health Care   \n",
              "13    APD     Air Products & Chemicals Inc               Materials   \n",
              "14   AKAM          Akamai Technologies Inc  Information Technology   \n",
              "15    ALK             Alaska Air Group Inc             Industrials   \n",
              "16    ALB                   Albemarle Corp               Materials   \n",
              "17    ARE  Alexandria Real Estate Equities             Real Estate   \n",
              "18   ALXN          Alexion Pharmaceuticals             Health Care   \n",
              "19   ALGN                 Align Technology             Health Care   \n",
              "\n",
              "                                        Industry          MarCap  Dividend  \\\n",
              "0                       Industrial Conglomerates 121720000000.00      2.75   \n",
              "1                          Health Care Equipment 140980000000.00      1.60   \n",
              "2                                Pharmaceuticals 120320000000.00      5.27   \n",
              "3                          Health Care Equipment  14860000000.00       nan   \n",
              "4                 IT Consulting & Other Services 106230000000.00      1.74   \n",
              "5                 Interactive Home Entertainment  37180000000.00      0.76   \n",
              "6                           Application Software 134540000000.00       nan   \n",
              "7                                 Semiconductors  27890000000.00       nan   \n",
              "8                              Automotive Retail  12340000000.00      0.14   \n",
              "9   Independent Power Producers & Energy Traders  12160000000.00      3.01   \n",
              "10              Asset Management & Custody Banks   5350000000.00      1.22   \n",
              "11                       Life & Health Insurance  37310000000.00      2.16   \n",
              "12                         Health Care Equipment  26080000000.00      0.80   \n",
              "13                              Industrial Gases  41190000000.00      2.48   \n",
              "14            Internet Services & Infrastructure  12030000000.00       nan   \n",
              "15                                      Airlines   6810000000.00      2.54   \n",
              "16                           Specialty Chemicals   9070000000.00      1.72   \n",
              "17                                  Office REITs  16210000000.00      2.72   \n",
              "18                                 Biotechnology  29970000000.00       nan   \n",
              "19                          Health Care Supplies  22030000000.00       nan   \n",
              "\n",
              "       PER   PBR  Beta     ROE  \n",
              "0    22.80 12.43  1.04   51.70  \n",
              "1    57.51  4.62  1.13    7.70  \n",
              "2    22.42   nan  1.15 -202.20  \n",
              "3    70.39 17.85  0.36   29.00  \n",
              "4    24.80  8.48  1.11   39.60  \n",
              "5    24.51  3.27  0.82   17.20  \n",
              "6    47.34 13.78  1.10   27.20  \n",
              "7    86.88 21.96  3.39   33.80  \n",
              "8    29.90  3.48  0.99   11.80  \n",
              "9    11.86  3.79  1.08   37.00  \n",
              "10   24.55  1.60  1.49    6.80  \n",
              "11   13.19  1.62  0.78   12.30  \n",
              "12   22.86  5.18  1.40   24.30  \n",
              "13   24.88  3.78  0.83   15.80  \n",
              "14   40.96  3.75  0.56    9.10  \n",
              "15   15.67  1.81  0.81   12.00  \n",
              "16   14.04  2.53  1.67   19.00  \n",
              "17   40.92  2.08  0.95    5.50  \n",
              "18 1742.99  3.27  1.57    0.90  \n",
              "19   57.04 17.90  2.12   33.40  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "metadata": {
        "id": "dTA6dNrvE57J",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 섹터별 종목수"
      ]
    },
    {
      "metadata": {
        "id": "heGfNPATE3wr",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "9b2cb872-4532-4bda-9662-a5665eec71bf"
      },
      "cell_type": "code",
      "source": [
        "sector_count = sp500.groupby('Sector')['Symbol'].count().sort_values(ascending=False)\n",
        "sector_count"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sector\n",
              "Industrials               70\n",
              "Financials                70\n",
              "Information Technology    66\n",
              "Consumer Discretionary    64\n",
              "Health Care               62\n",
              "Consumer Staples          33\n",
              "Real Estate               31\n",
              "Energy                    29\n",
              "Utilities                 28\n",
              "Materials                 26\n",
              "Communication Services    26\n",
              "Name: Symbol, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "metadata": {
        "id": "loo68lvXE_Ba",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "outputId": "6d9c1e6e-19bb-444d-c0a4-ae96ff94abd4"
      },
      "cell_type": "code",
      "source": [
        "# sector_count 섹터별 종목수\n",
        "values = sector_count.values\n",
        "labels = sector_count.index\n",
        "\n",
        "n = len(labels)\n",
        "plt.pie(values, labels=labels, colors=make_colors(n), explode=make_explode(n), autopct='%1.1f%%', shadow=True, startangle=135)\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ldLrH7QJeeclU3XB60sOhSMjuMEZCfpY7aRKnwTBNk8mpbUG3y+G0O5ZBWgVs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\niIiIiGhasNggIiIiIqJp8f8DbfduEITxwNwAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "RfuLMrUWFCx5",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 섹터별 시가총액"
      ]
    },
    {
      "metadata": {
        "id": "AqL17_oVFCIQ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "ec54391d-2d98-43a7-b199-683ca373b934"
      },
      "cell_type": "code",
      "source": [
        "sector_marcap = sp500.groupby('Sector')['MarCap'].sum().sort_values(ascending=False)\n",
        "sector_marcap"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Sector\n",
              "Information Technology   5215300000000.00\n",
              "Financials               3855020000000.00\n",
              "Health Care              3577560000000.00\n",
              "Communication Services   3528390000000.00\n",
              "Consumer Discretionary   2642080000000.00\n",
              "Industrials              2364120000000.00\n",
              "Consumer Staples         1996650000000.00\n",
              "Energy                   1340490000000.00\n",
              "Utilities                 785580000000.00\n",
              "Real Estate               718550000000.00\n",
              "Materials                 666890000000.00\n",
              "Name: MarCap, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "metadata": {
        "id": "JDxd2BjpFIDB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "outputId": "52c68aa5-0c53-4eb7-a3ca-34d3f8d0362f"
      },
      "cell_type": "code",
      "source": [
        "# sector_marcap 시가총액\n",
        "values = sector_marcap.values\n",
        "labels = sector_marcap.index\n",
        "\n",
        "n = len(labels)\n",
        "\n",
        "plt.pie(values, labels=labels, colors=make_colors(n), explode=make_explode(n), autopct='%1.1f%%', shadow=True, startangle=135)\n",
        "plt.axis('equal')\n",
        "plt.show()"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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vcE+6jkj9CEw0AAqAp4KR6sVOByKEGHqSbAghhtSFZ9yWF450vu7zZpw8VGP4\nTP+Ygnc31g7V9Q+WYbo8teti9U6N39LtHrHLkKxYPHrgo8QOoWBXsyofVqVu+yoNqA5Gqi93OhAh\nxNCSZEMIMWQu+PQtEy0r/o7Xkz59qMcKxDIq0jbWbBnqcQ4kHMsvDXc6M7sRT8ssiEbjMSfGHigr\nLslGX2Ti6nS5nG9sOUAm8IdgpPo3wUi14XQwQoihMdKfqIQQe1i7cPGRaxcudvwP93mf+uNhpul+\nw+P2j03WmGX18QIz2NGWrPF6Y5huz9b3nZndMF1ub+32zpFZAtcamUmSE4LNHbXjx+aXOh3HIPou\n8I9gpHokLgkTQhyAJBtCpJC1CxefA7wI/MXJhOOsE/53gdeT8ZzL5clO5rgu0+0rXVcXsuIxRytf\nhKP5Y8OdUUd6gNS1Wns2FhsZ4pYkGwfBsixrbGZmSnSM38NngFXBSPVIKOMrhOgDSTaESBFrFy4+\nA7uzrRu4FIcSjlMXXvXprIzClS6XJyPZYwNkGOlFee9v2uTE2DsYpttbsy5a58TYISNtZL5Ys+Lx\nAx8kgo0dmwsD2Y5XXhsiC4DHgpHqpL5JIYQYWpJsCJEC1i5c/ClgBYmOtwlJTzhOnv/9zwVyx9/r\ncnnSkzVmbwpD/grvtu3bnIyhO5JfEg5Fu5I9rpmWntceDAeTPe5AGZYlycYBxKKxyKSiQKomGjsc\njT3DMSJLOAsh9ibJhhAjWFWgxPjT9KP+y7KsfwO9rXdOWsJx0vz/+lJx/tQ7XKbbP9RjHYhhGEb5\n5lCm0dXlyFImAMN0+2red2Z2Y0t917DorN4XJpJsHEh3S9fWrAy/IzOGSTYXeCIYqR7jdCBCiIGT\nZEOIEez0wrLvL8grvM4wjP29wB/yhGPW1HNOLs4/5EbTdA+bteQe05tZsnaroy+6u8OBYidmN5q7\n3CPuud1AOszuT3coHJxaXphKm8IP5AjgyWCkOs/pQIQQAzPi/iAJIWxXTZr1tRMDJde4DfNgui4P\nWcJRXjLn6KbWDQu2bHvzUcsaXi8Ys8kozfpw00anxjdcHl/NukjSl3PF/JkF8djw+l0ciGmMrHiT\nzdMdb/J63KOtw/ph2AmHzHAIMYJJsiHECHRphTr/9KLyX3hMsy+lIgc94SgvmXMscCoQ/2jz829t\nqn3t/uGWcJS0ukvdzS2NTo3f3Z1fEumOJbVClOl2+7Y1hBxrLtgfLgPHyzUPVx1toYZJZQUVTsfh\nkNnIpnEhRjRJNoQYYZYUjzv1wrETbshwufuzgXLQEo7ykjnHA6cAO9faD8eEwzRMd9n6FoNo1JGm\ncYbL46t5L5z07ubbmp0pvdurQ6uwAAAgAElEQVRfMrOxb3keb9Q0R/Wf6yOBR4OR6kynAxFC9N2o\nfvYSYqQ5MVBy/JfLp9wQ8PoG0ihvwAlHecmcMmARPRKNHYZjwuE3/XkF726scWr8ru784mh3LJzM\nMTsYWRuJXabMbPSmvTG4tbwor9jpOIaB+cCDwUh1mtOBCCH6RpINIUaIqkDJnK+UT/lZRVrG1EG4\n3IASjs21b2wBnmQfzyHDMeEIxDIq0jbVbHFibMPl8W99P5zUZMdIyyjoDEU6kznmQLgNQ5KNPcTj\n8XhFXq6jZaSHmeOB+6TTuBAjiyQbQowAVYGS8ecWj7t6ZvaY+YN42YEmHE8AzzKCEo6yuni+Gexo\nd2Lsrq5AUbQ7mrTZDcMw2FLX5dhelb5yu+Tv0Z46mzo3B3IyZHP07k4B7g5GqiU5FWKEkCd3IYa5\nqkBJ4Pi84h8vzCs6fQguP6oSDpfp9peuq+u04rGkx2O4vGk16yJJnd1o7Bw5T/FuU/4e9RQJR7um\njC0odDqOYWoJ8EungxBCHBx5chdiGKsKlPhmZo35/llF5ReahjFU/19HVcKRYaQX5b2/aZMTY4dC\ngcJodyySrPGivoxAPD4sfuwH5HaP7h3Qe4q3h+vS/V7Zn7Bv3wtGqi91OgghxIHJk7sQw1RVoMQs\n96df/vnSCV/pY4nb/hhVCUdhyF/hrWtIendvw+VNr9XJ27therzp25u6GpI13kB4XIbL6RiGi1BH\nd6sqLyxzOo4R4E/BSPUip4MQQuyfJBtCDENVgRIj2+254MvlU76d4XLnJmnYUZNwGIZhlG/qTKer\nO+ndvTs78wqikVjSyvDWNkaCyRprICTZ2CU9brS73S75eRyYG1gRjFQf6nQgQoh9k2RDiGHIhBO/\nWqF+GPD6SpM89KhJODymN6tk7Zakv+tvuHzpte93b03WeO1x34hYiuNxm26nYxgOgi2ddRNLC2RW\n4+BlAQ8HI9UDKQcuhBhCkmwIMcxUBUrmLCuffFVFWsYhDoUwahKOHDLKsj5M/v6Nzo5AfrJmN4y0\njIKu7mhSO5j3h8dtjPpkw7IsitPT5e9y35UBDwUj1SOqt4wQo4U8qQkxjFQFSsYfl1f0rVlZYxY4\nHMqoSThKWl1jXc2tTckc03D7MratCydldsMwTXNrXWh7MsYaCI/H9Dgdg9OCjR2bi/NzCpyOY4Q6\nDLgnGKmW5WdCDDOSbAgxTFQFSvKKfWlfPqOw/Jxh0t9sVCQcpuFyl69vhmg0afsoADqCeYFYJB5L\nxljbO4y9Or0PNx7X6F5GFYvGoxML85K1PytVnQ78zukghBC7M4bBG4tCjHpVgRKfAd/44cRDv17i\nT5vodDx7uBn42vRn7+vXk0V5yZyTgIVAry94J5YfO6ui5IizDIczrEZXx8btsyeOS+aY6Wk1G8tm\npA/5mPHu7vYFk42snrfddsnvadveutexs049khMuObXX62xbX8Ozf32cbetr8Pg8TJk/jYVfPAWP\nz56UaNrSwMrf30fTlgYqZo3n1O+cs/M+gGgkyp3f/AvzPrOQ6SfM2hVfLBadPzY6qpONzobghkMn\nlFY6HUeK+E6mZ4kkHUIME5JsCOGwqkCJAXzp82MnnHfUmIKTnY5nH0ZFwrGxwNoSqihJ2uZcK9oV\nnHxkZ5rpNod86cfUrLamwBh/3o7vb7vk90yefwiHn7V7U3qP34M3be9Ky8Gmdu68/M9MmKs4YvHR\ndLZ28MRfHqZkSimnfuccAKqvuYucojHMOXMej//hfibOm8qR5xyz8xov//NZNr75Eef9/GJ6/qpj\n4UjomPL4iNjIPhTCXZHOibk5bp/X43U6lhQRB87M9Cx52OlAhBCyjEqI4eCEOdl5R8/NzT/R6UD2\nY1QsqSqri+WbwY72ZI1nuP2ZtbprSzLG2toQ3utxefxeMsZk7vbRW6IBsOaRVzHdLk7++hnkjyui\n4tAJHHfxKax79l1atjUTi8bY8u4Gjjh7Pnml+Uw/6TA2vvnRzvPb6lt47d8vcsIlp7JnThmPx5O6\nhG24MUPRBkk0BpUJ3BmMVJc7HYgQQpINIRxVFSipzHF7Tjq/pPLsIewQPlhSPuFwmW5/6bq6Tise\nS1oMwba8vHh06PdutEW9A3oxu/ntTyibUYnLs2sSpmLWeDBg09sfE2rrJB6Lk12QA0B2QQ7Bpl35\nzdO3P8b0E2ZRML5474uP4mSjs72rcXJZobwoHnx52BvGR/XyPCGGA/lPKIRDqgIlPuAzXymfcnqG\n2zPG6XgO0qUAaxcu7teSqs21bzxRXjIH9rGk6qPNz78F4OSSqgwjvSjv/U0bmqePr0zGeIbbn7Xt\ng6ZNY6elVwzpQGmZheFwd8TrdfWr6lNLbTOl03ffXuLxe0nPyaClpgn2yBEN02BH3rjhjfXUrtvC\nKTd+o9drW/F47GDf+6qvbeXyJTft8/4/Vn+VwpKc3W5bcevz3Hv7C3sd60vzcOeT3wVg64ZG/vTT\nh6jZ1MTMI8Zx+TVn4PPv+lFFwlGuuPA2lnxxPsedNvOgYj0YuS532OUyh0VFiBQ0H/gZ8H2nAxFi\nNJNkQwjnnHd2UcWxlemZM5wOpI9SPuEoDPnHBesa6iJF+UXJGK+9dUxuPBqKm25zyGa3DNN0ba0P\n1Y0vy9zZ/KxufS3V19xFw8Y6PD4vhxw/kyOXHIvbs/efhnBXNx7/3pMjHr+XcKgbf3Y6hmkQbGon\nuyCH9oZ2MvOyiEVi/OfWlRz7hROJhLp5+PoVNG7aTqCigEWXn0VmIBusg5/ZyS/M4uYH905aHvnn\n67z6zAfkFWT2el6gMIuf3/aF3X8mPf553fHbJ5gwtZjLrz6dP1/3CCtXvM5ZS4/aef8Dd79CbiCD\nhacO3n/X9qaOmsMqx0ozuqH1vWCk+plMz5JHnA5EiNFquC/bECIlVQVKjlYZ2UcfFyjqvezP8JfS\nS6oMwzDKN3Wm09XdlZTx3GnZ2z4Y+r0b29utyI6v03IyiHZHOPysozjn6s9z2BnzeO2+l3jyL/3b\nU+v2uBk7tZz3nlpDLBLj/affovzQ8bx+/4uk5aQzrWoWT9/+OPnjivjy/32bQHkhz9yxyj45fvDJ\nhukyyQ1k7vaBYfD4v97gwq8fj9vd+1570zT2Oi8nz+4BF43GWPvGJs68cB5jxwWoOuNQ3nrlk10/\nt9pWHrj7VZZdccpe+036Kx63rPKcLP+gXEzsj4G9f0O6sgvhEEk2hEiyqkBJUZrpOnVp6cRz3MaI\nbmSW0gmH1/Rmlazd0pCs8dqasnK2PPKk9dZ1v+W17/2Ed37xB+qee2W/5zS+/hbv/O8fWf3dq1lz\nzfXUPvX8bve3f7yRt3/+e17/wXV8cs+/6TL8O/s4XHD9lzntyiU8csO/6A6GOOzTc5m75Fje+89b\ntDe07TWWL91PuHPvRuThzm686fam8oUXn8yaR1bzx8/+nHAozKR5itX/eoETLjkNwzDY8u4GDjlu\nJqbLZFrVoWx+235Bb1jWgPqA3HPzs4yfUsSRCyf36/y25k5isTj5RdkAFBRn09QQ3Hn///v9kxx3\n2gwqJxcOJMzddDZ1bMofk5V34CPFIAgg+zeEcIwkG0IkUVWgxA189kvlkz+V6/EmZYnOEEvphCOH\njLLM9Zs3JmOsrrceyan9z4tW+adPZsb3L6Pg6CPYWP0Q219+vdfjm95ay0d3riDnkMnM+P5llJ1+\nClsefoK6517eeczHf/sXgTkzOeSbX6Htg49pWfdxTnNr987mGs8vf5LxcyZRNqMSgILx9j/Jjua9\nC3LlluTRuq1595iDIUJtnQTK7KbXxZNLufSvV3DJbd/lguu/zEv/eJZDjp9FYWJTeHdH185qV940\nH13BEADGnhs++mB7bSvPPvIuZ188/8AHH8COSQvDNHbuQVnz8sd88M5Wzv/KggFff4doJNY9uSRf\nOoUn1zHAtU4HIcRoJMmGEMl11kn5JUdNzcw50ulABlFKJxxjW8xSV3Nr01COYYVDhD98Ad+0k8K5\nh063/PkBio+fT7aaSMNra3o9Z9vTL5IxroyKsz5FWlEB+UfMouSEY6hZ9QyWZdHd2ES4qYWSExeQ\nPraIwOGH0rruQ7Zu725p2trAv396Nx+88B4LLtrV2qX+420YpkFO0d71CioPm8iWtRuJdu9cicUn\nr6/HMA3GHbarD6VhGqTnZrBxzUdsXbuR+RdW7bzPm+6js7UDgI6WIP5Mu7WGSf9nNh6+ZzXlE/I5\n9MjK/R7X3RXl1usf41vn3cKXT/sDv/7Bv6jdbP9as3LSMF0GTdvt2Yym+nbG5GcSjcS447dPcMHX\njyfUGea6b93DV8+8keu+dQ9N2/tfITna1rUtI82X3u8LiP76fjBS/SmngxBitJFkQ4gkqQqUzMp2\ne+Yuyh/7aadjGQIpm3CYhstdvr7ZIhoduvKsHj/ZS36Gb+qJ/rr1oZ17NzxZmUSDnb2eEtpWT9bE\nyt1uy50+lUhrO6Ft9YTbgrgzMzA99ko975hcwq1ttEY8nsy8bDa9swFfhp+W2iZatjWz9sk1vPbv\nF5lx0hzSstN5fvmT/Osnd+289qxTj8R0mTx+44M01zSy+d0NPL/8CWaecjiZebs1JycWtTeFL/jC\nSfgzdm1LKJ9eyZsPv0pzTSNvPPgK5TPt+E2jf7/WcHeEpx56m0Xnztnvcf50D740D+UTCrjiF2dz\n2VWn01DXxlWX3k1bcycer5spM0p5+pF3iEZiPPvoWmYcMY4H//YqWbnpHHfaDO78/ZNUTCzkxn99\njbLx+dz5h6f6FXNXZ3fb1PIi2T/gDANYHoxUlzodiBCjiSQbQiRBVaAkBzh9aemE49Jc7qwDnjAy\npWzC4Tf9gYK1G7cO1fUNw8D0Z2G4vbQ15WbF45YVC4dp++BjMiv38brUsjD2KF7lzrQ3PHc32KVo\ne+5lNgx7aZDlzyxY+9Rb8ezCHEqmlvHwb6r5f5ffyCsrnuOIxUdzwiV2zYKO5iAtPZZNpWWns+Qn\nS+loamf5d27mkV9XM+WY6Ry/bNFeob3xwMv4M/xMO2HWbrcf96VFdDYHufuKW+gOhjjui6cAYEK/\nfqdvv7qBcFeEOfMn7ve4My6Yx5+qv8qiJXOomFjA7KMm8L1fnkN7ayer7rNnjpZefgKP3fsGn6/6\nDZ0d3Ry5cAr3L3+ZL11xMoZh8N6bm1mwaDout8lxp85k7eub+hMy/gitbrdryDvGi33KB/4ejFTL\n70CIJJHNUkIMsapAiQlccFh2XoXKyJnrdDxDLGXL4gaiGePaN9du7SovGdJ3RQ13em79+pbNnasf\nLY+Fuig5aWGvx/kL8+nYvHv+07l1GwCx7m7SSgqJBDuJR6OYbjfhlja8OdlEu7o9L/ztKeus/z4f\nf2YaT978MIZhUDChmMPOOArTZScwi7551l5jFlQW8ZnrLjrgYzjynGM48pxj9ro9uyCn1/NdhtWv\n3+Vrz6+nckqRXZGqjwKF2WTmpNHSaC+dmjSthJsfuoz2lk5y8jK44Yf/ZuGpM6icYu9jCbZ3kZZh\nl/5Ny/ASbA/1ecyO1s76WeUl0sDPeQuA/wGucTgOIUYFmdkQYuidbMLYs4srTjcd6huRZCk7w1G2\nLRYwgp39X6x/ECzLovbRVYWNr73FhM+fiz8/0OtxhcfMpe2Dj6l/6TXisRidNduoWfU0GAaGy4Uv\nkIcnO5PGN94m1tVN45vvkD1lAlsefJzsyrLO8hmVPP6nB1DHTOdLN38T4hav3vvcUD60fXL18y/R\n+29uZsqMA+d+d9/4NE89+NZutzVsa6O9JURJ+a6CUKZpkJOXwduvfsL7a7Zw/iW7NoWnZ/hobbb3\nm7Q0dZDRj6q1Bf60Pp8jhswPg5HqwevOKITYJ0k2hBhCVYGSQuDo80oqD8/z+EZT866UTDjcpttf\ntm5bhxWPD8m4VjxO54vLiWxc48s7+ayGvFnT9nls/tzDGHvK8Wxc8SCvXXENH956N2WfPgksC09m\nBoZhMG7J6Wy89yFe/8F1+PLG4MsP0PTmO5SedWo4HOqm/qNaDjn+UFxuF4ccfyib39kwFA/rgFwm\nff53Eo/Fqa9toWCPbuEAf/vLM/zs2//Y+b2FxV9veIL/PPQ2dVtbWPfWFn77P/cxJj9zryZ90WiM\nv97wBBd8/bjdEoppcyp49J+vU7u5iUfuWc2Mw3fvpn4g7Y3BLWMLcgevdq4YKA9wazBSLa+DhBhi\nsoxKiCFSFSgxgMWlvvSsebkFJzgdjwNScklVhpFePGbdpg0t0yorB/vaodX/JLLlbTJP+AbR3BIz\nHg9jmr0/NMMwKDvtREpOXECsqwtPdhahmm1gGKSV2Et/xsyYyuG/+BHRrm7caX7e++3NjF1Uhb+4\neExD3dYgkLmjFK0nzbuzFG2yuc2+//46O8LEYxbpGXt3NW9pDFK3tWXn9xd81U4c7r/rFW779eN4\nfR5mHF7B5VefQWb27jMUD/99NRlZfo7/9O5vel/8rRO58dqH+P7FdzB52li+cdXB13mIxeKxysCY\n7D4+RDH05gLfAn7rdCBCpDLDoWqSQqS8qkDJXOCM/5ow/ZyKtMx9v0Wd+m4G+pVwAJSXzDmJfSQc\nABPLj52V7ITDsizrkwpvfbgwMGi9Uro/fJ7Q6nvJOOHreIqnAJCTW7OlaHJ6rzvE2z/ZRDTYwZiZ\nh+y8bfMDj9H+8UamffuSvY6vf3E1dc+8xPT/+gamy0VWe83mJ3/85/Kv3PYdMvOyeP+Zd3jzoVe4\n4PovD9ZDOmiBSNPWyWUZKVshqKMhuGHWhNJKp+MQveoEZmR6lnxywCOFEP0iMxtCDIGqQIkfOKkq\nUDx+lCcakIIzHIZhGGUbO9I+yvB3dX/0jD/8yWrina2YmXn4pizEp3rf1N3676uwOvbRssPlxTvp\naKxIN233/4R4VzvB4skFOcs+hT8vh4/uuhfDNCk/cxFv/+x3BA6fxfYXVzP+c2eTNXEcrevWU/fs\ny0y5dOlel452dLLloVVMuvh8zEQhpKCRbhROKOb1+15k5qLDeXvlaztL0Sabx5W6S3rD3ZGQKi0s\ncToOsU/p2G+InOJ0IEKkKpnZEGIIVAVKzk83XTOvnjz7Gxlud67T8QwTKTfD8X7Nv4NtoU8y0+Z9\nFldeOdGt7xJ67V+kHXUBvklH73V8vKudPZtlxxo20PHsbWDF9jnO3N9fx/t/vBXDNPGOycWKRpmw\n9DNsffRJGl55g0h7B2nFhZR9+iRyp6u9zt/wzweIdoaYdPH5u2KJRrunWFs9T/z5QbO5polxh03k\nlMvOxJfuG8BPpH/KjJb6ssK0lNzPEGkKbTyksrhvGzyEE76Y6Vlyh9NBCJGKJNkQYpBVBUomABd/\npXxy1azsvGOdjmeYSZmEIxrr4vUPbiCrfEGzedxndrbcDj75J4jHyTz5mwe8hmVZBB/7De788aQd\nsYRYsIH2B64j5/zrMVweQmseJN5e3z3r2+f4TNMguGEz+i93MPOH38abM/B2LZW+5vrSogzHX+SP\nd7c2FQX8eQc+cmQJBbuapxXl57hc/a23JZKoGTgk07OkzulAhEg18gQoxCBK9NQ4Y1pmTmBm1pj5\nTsczDKVMlSqX6WPO5G8xOe3ITFdz687ud4Y/m3h38KCuEflkNfG2enwz7UZ6VqgNw5+J4bK7fpsZ\neVjhkK/xk9BWKx5nw70PMnZR1aAkGgB1zXFndoTvweM2UrLBWhaukCQaI8YY4I9OByFEKpInQSEG\n14kG5H+mpPJ00zDk/1fvUiLhMAwDjzsDj8vvKV/fHCcajVnRMNG6D3DnVx7wfMuK0/XuY3inLMD0\npe+4cc9BAGiqy/Jtf/E1rEiU4uP2Xp7VXx34MgbtYgPgcZspt38w2NxRWzk2fzSVu04FnwlGqvfu\nZimEGBB5MSTEIKkKlOQB888sKp9R4PVXOB3PMJcSCccOftMfyF+7cUvo1X9ghTvxTT/5gOdENr9D\nPNiITx238zYjLRurK4gViwJgdbZgpOVgxY38TQ88Hh937umEtm3nvd/dwptX/ZIPb/87sa6ufsdt\npGXkd4Yinf2+wCDxuI2USjYsy7LGZmbuXZNXjAR/Dkaq927eIoToN0k2hBg8Z3kN033MmMIqpwMZ\nIVIm4bAsi7bNz4wLf7Ka9PkX4coqOOA54Q+ewTPuMMy0Xe0XzMx8jLRsIhtew4p0Ed74Bp5iRdeb\nD2AWTIpkT57Ax3//F3mHzWTW1VeCZVHz+DP9jtswDDbXhRr7fYFB4nG7UuqFebCxY3NhILv31u9i\nuBsL/MrpIIRIJZJsCDEIqgIls4EJi4sr5qS73PKu2MEb8QmHZcX5qPYBtre+zcSSs8K+wOQDbtiI\nd3cSrVuPp3T37tWGYZB+5GfoXL2C1n9+DzMjDzMrn/DGN0if+1lfvW6u7dxcQ/6RszFdLgJHzKbt\nw48HFH9Tp7PbJeLxeMzlSl4FsaEWi8Yik4oCkmiMbF8JRqqPcDoIIVKFJBtCDFBVoMQLLEo3Xcbc\nnPzeGyyI/RnRCccn21bS3K45pOJzFORM95a+vy1oxeP7HSu69V0A3GMP2es+T9lMcs77Fdnn/oKM\nqq8Seq0a/8xPYabn0rjJ9AC4fPZEgMvvJdo5sD3eUV9G4ADhDikrFos4NvgQCLd01WRl+IfFXhjR\nbwZwg9NBCJEqJNkQYuAWAennFI+b63e5Mp0OZoQakQlHXfMbbG99iyll55GdbrdSyDTSi8es27hx\nf+dF69djZhdhetN7vd8wXZi+TMLrX8KKduObaq/MM9ML8wEiwQ4AIu1B3GlpA3oMpsebvr2pq2FA\nFxkAKxaPOjX2YOsOhYOqvFA2haeGBcFI9RKngxAiFUiyIcQAVAVKMoE52W6P57CcvGOcjmeEG1EJ\nRyweZlP9UxTmzCbNl084Gtz5MaYtUuGpb6zveOFOOl+6a+9z2+oxM/e/0ibe3UHXmgdJO/IzGKa9\n1MnwpmHmFEdrn3qeUN126p9/lewpEwb8WGobIx0Dvkg/WfHUSTY83fEmr8ftcToOMWh+FYxUJ7/L\npRApJqUqgAjhgEWAsaR43FE+09X729SiLy4FWLtwcb8a/22ufeOJ8pI5sI/Gfx9tfv4tgJ6N/+JW\njJqGF2hoe5dwpB2fJ4eiMUdQnNf7ku31NQ/Q0Pr2zu/rWl6nruX1PQ8zfZvy8iORFgx/FpYVp2cl\n5HhXEKvhE6J1H+IumtzrOF1rHsRdPAVP8e4dwTOO/aK7+ZXbIttfes2TM3UyY085rtfz+6I97hvY\n9MgAWFY8lgrve3W0hRpmlhVKFbrUMgH4JnC904EIMZJJsiFEP1UFSnKBmXker/9QaeA3mJKacGzc\n9jgNbWuZUHIaGf5imoPr2VC3EtN0U5g7u9cxMtPKmFJ27m63GZh43Ha+ueajP5OfPcN0Z5dv21T/\nWHFk45t4Kw/feaynYDxWXtk+Ew2A9Hmf7fV215hS0k78VpOabxXt9wfRB0Z6ZkFXV6jL73f7B+ua\nBy1FZjYCHm/UNEd+0iT28qNQ1723p/nPdbxqmxAjlTwzCtF/iwDOLR53jMc0Zap9cCVlSVUkGrLq\nW96krGABgexp+L15lOTNJSdjAg2t7+zz+oZh4nVn7vaxI9HoCjfTHWllbGA+xb7xxelZ41ujte/v\nPDe6/RPCm94kbc7Z/Xlo9vienKKmzaFt/b7AntczDGNLfciZfRtxa6+EcKRpbwpuLSvKK3Y6DjHI\nLOs9fzj+SVrEusrpUIQYySTZEKIfqgIlBcD0Yl9axrTM3HlOx5Oihjzh2Fr3zv2HTfqmVZg7Z7f7\nPO4MorH+VXmKRIN4XOmYiabY+fFAZrylPgp2mdzQ6n/in3kqZvrAKiRv35w2qOViG4KGIy/6DeIj\nOtmIx+PxcWNypfpUKrGszd5I/MWMbusQd5zZwFdpX1HpdFhCjFSSbAjRP4uA+DlFFQvcpikbQofO\nkCYcH2954a3a7e/fbxruncu1YvEIbR0byEwbnKJCpuly+UMRi2g0Fv7wBaxYFN/U4wd8XcOTW9S8\nZfBmNyLejLzBulZfGNbIntnobOzcnJeTket0HGLgwuFIV8u2lg/Su+JF3hjzDbsELoAX+KmTsQkx\nkkmyIUQfVQVKxgJTKvwZ2SozRxo/Db2kVqnasO1RorEuxgb2vQ0nGu1k/db7eGP9H3n9g9+xvuYB\nwlG7l5/HnUEk1kncigEQjrTj94zx5L69rmZHdal46zbaH7uB1uof0fHsrVjh/s2ibN80ePu6Ta8v\ns6Ep+d3EDYa+w/tQiYSjXVNKCwqdjkMMTCwWj9VvbdqY3hWnLDd7imkYvXW0v5D2FTOTHpwQKUCS\nDSH6bhEQP7u44jiXYTjbfnn0GPKEY2PN6vs/rn2EhtZ3mTT2LPze3t/odye25+RkTmRq2flUFi+i\nvXMT721cTjwexecZg8edSWPru8Ri3TS2vUdORiWdNa+Ue7PLQ57iKXS+dBfecXPIPvunYFl0rX28\nPw8LPLnFzVtCdf07eW9bGyLtg3Wtg2WO4GQjHgzXpfu9jlXyEgNjWRbba5s3m61dHRMCueP8Xs/+\nCiSYwM+TFZsQqUSSDSH6oCpQMg6YOCE9c8zE9KzeSxWJoTKECYdlbG16YkJ9y5vxSaXnWHnZU/d5\nncriRcya+FUKcmaS7i8kkH0Ik8aeRVe4kcb29zEMg/FFn+KTusdY/cGv8Xly8HvG0Nj2Hir7RIPW\n5o5Y02Y84+dimC484+cS3fZBfx4SANs3+QdtGVJ7zJv0alQugxGZbIQ6ultVWWH5QK8TiUS55S9P\ncs4ZN3D0nKs47cRfcsufnyQc3neRrvfXbuXSZbcy/4irOeGYa7numn/T2dm98/7GhnYu+eL/sWDu\nNVxy8f/R1Bjc6xpf+sLN3PLnJwca/ojV1NC+rXt7cPv4MTnlWen+7IM87XTaVxw7pIEJkYIk2RCi\nb04GoqcWlB5l9mycIA0qYs4AACAASURBVJJlSBIOX3rXaaYrPrU75LkzGGzvc+O/dL9dhTaSWEo1\nJmsyR065ksMnfwdV/lk21K2iNP9Y0n15/sL3NnQAGB57hsTw+LC6B9BTzzOmpLkmVN//C/SQllkQ\nDscig3Ktg2QaIzLXID1uBN1u14CfA/7428e4+84XuOybp7Di/m9z5Q8+zd3LX+BPv3us1+Nra5q5\ndNmtuN0ubl9+Kb/90xd4+cUPuebH1TuP+cufniAjw8fyf3yDrOw0brrxid2u8fADb7K9vp2LvrRw\noOGPOO1toebWmpatFZkZxfnZGQX9uITMbgjRR/JiSYiDVBUomQRUZrs93knp2TKr4ZxBTTg8vu7D\nTVf8sEiX9++xiGfj/jqNx60YH9c+QlP77jMRHV32Pu2eS68Mw+67Ud/yJvF4mOK8uQBku/IKAawu\ne8WS1dWO4R1YP8jtG/2D0qvCME3X1rpBSlwOkstgUKtqJUOwpbNuYmlB6WBc6+EH3+SMs+Zwwskz\nKCvP44STZ3Dm4sN59KE1vR7/7+rXiMXj/Pz685l6yFhmHTaO//nJOTz5+Lt88rH9q3vphQ/53NJj\nqBxfwHmfO4qXX/xwV+zBLn5/w0qu/MHp+Hyjp7ZFVyjc0bilaWOh25tbmpc9kN/dAtpXSF8lIfpA\nkg0hDt5J2LMasz2m2dsGQpE8g5NwGJbP7Y2eFI+Zb8ZirgbDjGcaZjzz463PfvTx1mdXWpZlra+5\nn49qHgTANFxEYyE+rn2Ixrb36Qo30xL8iI9rHyLNV0Bu5qTdxonGQmze/jSVxYswE9t73C4f6b4i\nwqsfDMVa6+j+4DncxVMG9MPAPWZsa23XoCQJ24NWUpvsucyRlWxYlkVxevqg/e00DAPXHhMkHq+L\nRIP7vXzyUT0TJhSSk7MrQZ171ER8fg+rX/kIgIbt7ZSU2AWySsbmUl/XtvPYm298kmnTS1l4/L6X\nCqaSaCQWqd/SuCE7anjH5eeOc5n7+MH2zZWDcA0hRg3pIC7EQagKlEwDygyIzs5OvEUtnDbgTuMT\nKqcfahj4/z979x0mSV3nD/xdqatz93T35LzLUgssYVdEggIrIMqRlTOnOwOC8cQz3J3IKXennp6e\neKc/9eREPM+VI4giQVZgFxbJAssWmyb0xJ7OubvC74/qmZ0ce6Y6fF7PMw8zvRW+PfR017u+4cPx\n2uk2Z3bGymKh5GPgR+x35QvxK6ePmNvcdhmCoccwMP4HFJQkeNYKr3MzupoumAoUkwbGd8Pj6IHH\n0Tvj8c1tl+PQ8F1i8r6vQ2g7EdZtF6+0+XOM9VkUT+uaD4M8v7HLuPJcWS7+NkwqnB7csql9zXM1\nJl3z9tfhjl/9CW968yk4cVs7jhwex333Po+rr5n/bUbVNHD8zHDCMAy8XjuCgxEAgD5tGgzDHFvv\n69DBUdx1x1P4nzs+Wa7mVyxN0/WJ0dhgs93q3xRo6Cnz4a9ActdxcF1zqMzHJaQmUdggZHnOAqCc\n62ve7OIFv9mNIVPWFDiO9L387c7WHX8GcC6AOROtDyf2YHPn69HVevoVKK25z7EWdDdfgO7mC5Y8\n/qbWS+Z93GFtxqmbPsrGmPTg6I7N5blw5X1t8dHRkKfFuppx6FNY0eqJxpOxBo+4IaGDZ6unh11V\nNGVzk6+sv5ePXHcBotE03vfO/wDPc1AUFW+95gx89Pr5X189PY145qmjyGYLsNmMDtZYLIPQeALp\ntDFJPOB3ITSeQGeXH+NjcTQ2uQAA37j5N3jP+18Pj9eOz336drz04iBaWrz4u69cieO21E4B9PB4\nfMjN8rZNPk/XOp2CBfA3AK5bp+MTUlOq5k2eELPs9Lc2AegFgLMbmqhXo/JsaB2OcvLqjk7n4eBA\nuY43dtRSKMdxhkL5eDmOsxwCVz0LLeRjmSG30+Yq5zFv/cmjeOD3L+IrN78Nt/3yOnz1n6/B7j+8\njP+85aF5t7/qba9FNlvAt77+W6RSOUTCKdz4pV1wOq3geaNn7fQzNuHeu59FsajinruexRmv24z7\nfvs8Rkdj+MCHzsOPf/AwGJbBPb//HC68eBu+euOd5XxKpolH06H0aHy02+1qb3Da1rtI5QeQ3BVY\n53MQUhOq5k2eEBO9AYDSa3N620TbFrMbQ+ZVtYGjLcq0crFErCwH433tibH8xFoPEy8KGzZzmK+S\nsFHIFdNSR1MZBqodE49n8INbHsK111+Ay67YgeO3tuKSy7bjuk++Cbf+5BFEo3NXKevs8uMb334X\nHn7wJew8+6u46tJv43VnHYee3kY0NDgAAB+9/gI8/dQRnP2aL+P5Z/vw7ve/Ht/51/umJoU/89RR\nvPmSUyEIHC674jV4+cXgjKVzq00mnUtEhyKDrVZrY7PXtVFdNDZQzwYhy1IVb/KEmGWnv9UC4EQA\nuLix7QxmoVmbpBJUZeBgGU7oOBhWoShqOY43eoRf81WjbnU2KopWlvYsheeqozAmm1UmRItQ1oUh\nggMRKIqKnt6ZI986u/xQFQ3Dwei8+53/xhNx/x+/hHsf+Fs89Ojf4R3vPgv9fSFskYzr7PYOH+75\n/efw+4e/gLvvuwH33PkMtp7QhnPPPwEAkEhk4XAYSy/bHRbouo5kIlfOp7YhCoViLhQM9/vAOzr9\n3s7yzP1ekeuR3LXhtWkIqTYUNghZ3NkAeAfHC8c73NvNbgxZUlUGDhtr8wf2DwTLcSyd87UnQrnw\nWo7BcJwwPL4xS+BaeLbi5w5mktnwlo6mso//b2oxasn1983sjOo7Gprx79MFByO4646nwXEMmls8\nEAQO+x4/hHxBwevOmrkamj/gwpHDY7jz10/hhi9cOvW402VFJGLUhImEU2AYBk5X9Vwzq6qmjgcj\n/bacpvcGGrp5jjUrsDYBeJ9J5yakalDYIGQBO/2tDIDtAPS3NLafYmG56vk0rm9VGTgCRXu3NTg6\nvNbjMAyDsUNCdq3HGYtrZZn/sRSeZyo+bHg5ocBxbNlvmzc2unHBRSfhRz/Yjd1/2I/gYASP/vEA\nfvzD3Tjz7C1obHTjf3/xBP7yyu9M7ZNO53DzTXfie/92P4aCEex7/CC+duOd+OCHzoPTOfct6hv/\n9Bu8673noLPr2LoWp7+2F/+360/o75vArT95FCdua5/q6ahkuq4jNBodZOO59KaAt9tmEWxmtwnA\n3yC5i3q8CVkEhQ1CFnYCAD8AbKflbqtNVQaOjpGil8lk11BO3KBxvo5kKL+m3o0ca5t7W30dVHrP\nRjKSHu5q8Zd1rsZ0X7n5bbjk0tPwL1+7G1df+m3cfNOdOP+NJ+Dr334nACAWTaPv6LGeD2lrG27+\nxtux9zEZb7v8O/jaV+7EO959Fv76IzvnHPuB+/6MoWAUH/jQeTMe/9BH3wiXy4Z3X3MLXnxhAF/5\n2lvX6+mVTTScHM2HUqFer6fTZbduyGtzmSQAl5ndCEIqGbMO8x0JqQk7/a0fBNB9TkNTzzvbet9v\ndnvIqvwQwKqWxQWAztYdF2KBZXEBYHPn60/taj39inLO5UnpmZHBHT0tDLu2O+mMOhHccibfsZZj\nnNyQTLpdYllXX5rt9EBW4zm2Im98aZqm+SDEA15ng9ltqVfJRDaqp/KZtrVV/V5vj8F1zblmN4KQ\nSlWRb/CEmG2nv7UBwGYAOIeWu61mVdfD4WTsrV55YM3L4Wqsvz01kY+s5RjBUH7+GcplomtaxQYN\nAMhEMoMUNMyRyxUy4WCkv4m3eCs8aADAG5DcRZ8ThCygYt/kCTHZeQCUDqvd1WG1bzW7MWRNqi5w\ntKQtncJ4JLSWYzAMw4wc4tY0JCua49f1M0LTtOJ6Hn8tlKKa39IaWFOBRLJySlEtjgcjfe4i+O6A\nt5szYYmpVbrB7AYQUqkobBAyy05/qwBgGwCc52vZxtJyt7WgqgIHw7BsZ3/SgkJhTcvYaqy/IxVe\nfe+EZnU2qqo27xCyctBVTVmvY6+VksiNOGyi3ex21AtN0/Xx4Ui/kC4UNgW8PRaBL+sywxvgaiR3\nrVfFckKqGoUNQuZ6HQALAEgO9zaT20LKp6oCh4UVPS0vDa5p+VmGYZiRg2xqtfuzPC+OhrJr6mFZ\njK5VZtjIZfKJrZ3NnWa3o16Ex+NDaiQd3eTzdjusosPs9qwSB+C9ZjeCkEpEYYOQaUrL3b4GgNZr\nc3p9FrHN7DaRsqqqwOHVHZ2OI8HBtRxDY/0d6Uhh1RXKR2PqmpfRXUilhg1rEQme56qi2GA1i8fS\nE+nR+Gi329Xe4LT7zG5PGbzH7AYQUokobBAy0yYAjQDwel/TSSa3hayPqgocbRGmmY0nVj0UimFY\nZuQgk1jt/hnYnKvdd0naxlQpX4l0PDN+XGfTmlbxIovLpHOJaDA62CpaA81eV4vZ7SmjrUjuOt3s\nRhBSaShsEDLTdgAKABzvcFPYqF1VEzg4hrN0vhpWdUVd9YW5yvg7M9FCfDX7MjZ7IJMpZlZ77kXp\n6zcfZLUarZVQJ642FQpKPhSM9PnAOzoDns7qmfu9IjSUipBZKGwQUrLT38oCOA4ANttdDQ2CuG6F\nvEhFqJrAYWNtgcD+/uBq92cYlhl+lVld2GAYDI7l1lQgcMFj63pF9Wwkw6lgW6O3yex21BpV1dTx\noUifLadqvQFvD8+xtTxE7R1I7qroQpWEbDQKG4QcczwAFwC8vqGJJobXh6oJHIGCrVsMjg2vdn+V\n8XdkYoVVDaeKZNfno4KpoJ4NVdXUXn9DJVWmrnq6riM0Ghtk47n0Jr+3x2YR6qHbqAnAm8xuBCGV\nhMIGIcecAqAIAFtoCFU9qYrAwTAMOkcKXjaTXVXtDIZh2WEZq5oorojOgKaVr47IVJtQ/mOuVi6a\nCXrddgobZRINJ8fy48nxXq+702W31tvvlYZSETINhQ1CMDWEajMASA633ytYmk1uEtlYVRE4eFaw\nt+0fSay2Q0BlAh2ZeHHFvRusINjGw9mJVZ10seMCFRE2CvliRmpvqqWJyqZJJrPR+HBsqNPhaA54\nnPU6JO0KJHfVW8AiZEEUNggxbAXgAICzG2gVqjpVFYHDydhbvfJA/2r2ZRiWHZH1Va1sNRJRyj5J\nnGUqo2eDSSshqyiIZrejmuVyhUw4GOlv4gRPu8/dbnZ7TGYD8FazG0FIpaCwQYjhFJRWodpid9F8\njfpVFYGjJW3pFEKRVRXbUxDoyCYKyZXul9LFso+3ZytgMaJsKhc9vrORCvitkqKoxVAw3O8ugu8O\neLs5lqXrCgPV3CCkhN4USN0rDaHaBAAnOD2NbsHSaHKTiLkqPnAwDMt29iUtKBQKq9iXGz6AyIr3\nszkbc7libqX7LYZjzO/YcIHLchxHn4UrpGm6Pj4cHRBShUJvoKHbIvAWs9tUYc5HchfVayEEFDYI\nAYATAdgB4CxvIw2hIkAVBA4LK3qaXxocW82+iu7vyCWLqZXswzAMExzLlXXeBs/C1L6NVDQ90tMW\naDOzDdUoPB4fVsPpyCafp8thFR1mt6dCsQDebXYjCKkEFDYIAbahNITqOFqFihxT8YGjQXd0Oo4E\nB1e6H8Ny3PABbcW1MybSTFmXquVYxrTPIF3X9TaXk+7Gr0A8lp5IjcRHut2utgaX3W92e6oADaUi\nBBQ2SJ3b6W/lUFqFqtfm9Lp5IWByk0hlqfjA0RZhmtl4YsVL2ha1QHsuVVzRMrpFi8O30vMshufM\n69lIhdODTT43XTAvQyadS0SHooOtojXQ0uCiYqfLtw3JXaeZ3QhCzEZhg9S7k2CsHILT3L5ek9tC\nKlNFBw6O4Sydr4YVXVVX1OvAsBw//Iq2omFRrEV0hiLZFc/3WAjPMaZUklYUtXBcs5+CxhIKBSUf\nGgz3+cA7Ov2eTpapgBn91edKsxtAiNkobJB6NzWEapPd2WNuU0gFq+jAYWNtgcD+/hUPp1pN78bw\nRHHFK1ktRODMGUZVjOeGXQ4rzTVYgKpq6vhQpN+WU7XexoYenmNNCYU14mKzG0CI2ShskLpVGkK1\nafLnFtFGPRtkMRUdOAJ5W7c4NDa8kn0YluOHD6ysdyOpWspWj8KMno18tpCSOppolaAFhEZjQSaW\nS23ye7ttFqHsyx3XodciuctrdiMIMROFDVLPjgNgBYAtdpfPxvEuk9tDKl/FBg6GYdA5XPAymeyK\niu8V1UBbLlVc/j42Z2OhoK54yd35CCaEDSGvRS0Cz2/0eStdNJwcy40lxnu97g63w+oxuz01hANw\nodmNIMRMFDZIPduC0hCqU2m+Blm+ig0cPCvY2/aPxHRt+dM3GJYTRg6o48vfnuWCY9lVFRScTeDZ\nDb3oTyeyE8d1UAG/6VLJbDQ+HBvqdDiaAx5nk9ntqVE0lIrUNQobpJ61T37TY6P5GmRFKjZwuBh7\nm+fVgf6V7FNQA+2F9PJ7N0IpI6SvlYVnNjRs+AWLQgWuDblcITMRjPQ3coKn3eduX3oPsgYUNkhd\no3ddUpd2+lt5AFNLOLaIth7zWkOqVMUGjtaUpZOfiCy794FheWHogLrs7Qu8vWGlbZqPIHBCOY6z\nHMlIaqij2deyUeerVIqiFseDkT5XEXxPwNvNUfraCJ1I7jrB7EYQYhZ6kyH1SgLAA8BWhztg5Tin\nye0h1akiAwfDsGzn0aQFheKy51YUlEBrIaNkl7MtK1rd0XhuxbU9ptN1Xd+oYVSapmndDd66Xn1K\n13R9fDg6wCcL+U0Bb48o8FTQcGNR7wapWxQ2SL3ahNJ8jVPcDT3mNoVUuYoMHCIreppfHhhb7vYM\ny1uGDyjL3j4YKsRX0p7ZNFUrrmX/lchEMoM+j6NuVwQKh+LDSjgd2eTzdDltIt1YMcebzG4AIWah\nsEHq1fT5GjQ5nKxVRQaOBs3RaT8yNLDc7fPFQGshq+SWs22iIKxpCJSuqWWZ97GUYkHJHd/W2LwR\n56o08Vh6IjUSH+l2udoaXHYqYmiu85DcVbZlowmpJhQ2SN3Z6W8VALQBAAOgmeZrkPKoyMDRHkEL\nl0guqxeCYXlx+JXl9W7oNmejoqw+MOiqtiFhQ0sVxuxWi3UjzlUpMul8MhKMDLaK1kBLg6t16T3I\nBrADeIPZjSDEDBQ2SD3aitJr/0Snt0lkObvJ7SG1o+ICB8dwlnZ5oqCr6rLWw80X/C3L6d1gOE4Y\nHl/9Eri6tv5hI5vOx6SOprpZ6rZQUPKhYKSvAaytK+DtZJlVvQzJ+qF5G6QuUdgg9WhqvsbJLm+P\nuU0hNajiAoedtTX69/cPLmdbhhPE4QPF0eVsOxbXV1/cT9fUVe+7THaNSfE8V/Ofc5qqaeNDkX5b\nTtV6A94egeOoaGFlorBB6lLNvwmvhCRJPZIkPb3ENrdIkvSsJEnudWzHKZIkHV/6/peSJNlWeZyT\nJUn6Y+krJ0nSY6XvL1/BMXhJkpZ14bHIMb4mSdK1azlGmU3N1+ii+hpkfVRc4GjM27rF4fGR5Wyb\nzwdai3k1v9R2Oc62+vdBbX3DRiqWGdvc3tixnueoBKHRWBDxXHKT39ttswir+qwgG+ZkJHfRsDZS\nd+jux8pdAmCHLMuJdTzH1QCeBvCqLMvvWO1BZFl+EcD5ACBJUh+At8iynCpD+6rWTn+rCKO+hgoA\nAYvYZm6LSA37KAC8fO6VHzvp0btWXCtjcOTZhzpbdwDAuQDmDIE6PLjnBQDoaj39CoZZerwMwzDo\nGMq7j3izGd1uW3ToIMMJ4vD+Ql/39sXnM7FWe0MimUy4XeKKQwej68svc75Cuq6jxWHn1uv4lSAa\nSY5Zi2B6ve6aD1Q15iIAPyv3QSVJ2gLgOwAaAXAAHgdwgyzLS940qASSJH0FwLsBDMG4Nj0C4G9k\nWZ6QJOkDAOKyLN9Z5nO+VZblO9br+OQYChsLkCTpVgDDAF4DoAvGH8EFMCYW/0aSpEsB/B2Ac2D8\nHm+RZfk2SZL+COCl0mEmAAQAHAdj6M7fA/grAD0wQssAgP8G0AHAAeArAPoBXAsgJEnSOIBfAdgG\nwAvgvwBYYFx4/DUAvbT/YQCnAnhOluUPLfP5bQPwvdKx4gA+KMtyXJKkLwK4CsbF+OdhvGFBkqSb\nAVwIYAzAFQC+CmPC21YAmwF8QpblByRJeieAT8EYpvQnWZb/ZtZ5vwXgdQAEAN+VZfkXkiRdDOBb\nAEYAHCz93rcD+HdZlh8p9ey8BOB4WZbXejd06+Q3DYLFaud4zxqPR8hiKipwCKzgaHtleDi4vdfO\nLFHLLZcPtCj5RIEXuUXrMQTH87ETVxE2sI5hIxVOD2zZ1N61Xsc3UyqZjanJXKrT56GQUZ3OQpnD\nhiRJHIA7YHwOPyJJEgPg3wF8GcZ1SrX4rizLtwBAKQDcA+BsWZZvLfeJJEnqAfBOAHesx/HJTBQ2\nFifKsnxxaQjQ+2RZ/rQkSdcDeAuAHQC2ybJ8jiRJDgB/liTprtJ+L8my/INSUvfJsvzm0sX6+0vf\nfxXA5QB+AeABWZb/W5KkTQB2ybL8GkmSfg/g17Is/0mSpMm2/COAn8iy/L+SJL0NRjC5EUYYejuA\ncQBBSZK8siwvp9jWLTACxlFJkj4J4FpJku4utetMAFsA/A2MsNEI4HZZlv9OkqSnAJxUOka7LMuX\nlILXRyRJ2gcjhJwqy3JakqT7JEmaWn1DkqQ3Atgiy/LrJUlyln5ndwP4Bow/+ldK57sHwG2l5/UI\njDtBvylD0ACM0KcCwIlOb91XEyYboqIChwuONs+rg/2Jrd3di23HcIJ16JVCX/dpi/duRPP8qnoQ\nWKxP2FAVTdnc5CtLhfNKkssVMqmJVKjT5+7kfGLd1gypAa9dh2NeBOCALMuPAIAsy7okSX+L0vuF\nJEmfAjA5SuIuWZa/vsAN1RcB/BxG778I4xrjAIzrkdNLx3oawOQ1yHhp/0YAXwfwQRg3WM8DkALw\n/2B85goAvizL8sPTb8jKsvzxhZ6QLMu3SpL0bkmSzoIx12UCxnXBr0ptEwFcL8vys5IkfRfGTUwF\nxs3aAIAbADgBfBZAd+m/CoCnZVn+LIDvAzhDkqQvwxiuOiHL8i2SJH0D899EfhDAG0vHvqz0u5tx\ns1iW5XunPT8ORm2VU2VZTkmSdA6Az8qyfPVCz7mW0ZyNxT1W+m8QwOw74KfDuBCGLMtpAPthXKAD\nwJ+mbTf5/QiA50rfj5WOFwXwWkmS9sJ40S62DvrpAP5Y+n43jDv/AHBIluVRWZY1GC/+5d6pPwPA\nT0t/GO8C0AIjQO2TZVmTDR8tbRuVZXl/6fuhaeeY/fvZCuCV0u8DpfZOtnPyOUz+zlIAZBi9Iu2y\nLL8oy7IC4HelbX8L4PzSHZsrANy+zOe1lKlhU902B4UNslEqag5HS0ro4CeiE0ttl8v5m5W8sugk\ncM3qDKiqtuLgwEBbcfBajnwsE3Q7ba71OLYZFEVVxoPhPlcRfE/A282xS3RJkUp3yjrU29gK4Pnp\nD8iynJVlOS9JUi+AD8BYdvcNAN4uSdLm0maiLMsXA/gugPcBOBlAQJblc2Fc4PuWOK8iy/IFMELK\n2bIsX1j6fieM64oRWZZ3ArgSxhCvSS8tFjSmeRrAidN+vgBAUJbl82GEoyZJki4E0CnL8pkAvgTj\nJiVKz+ViGNcZfw/gjbIsnwegs3Th/00Aj8iy/I+TB5ck6VyUbiLDCBZfkSRp8r0kUXqu98EY6u6D\ncbP4PAB/CeCmWc/vYwDuhHEDFzCuY36xjOdck+hNa3HTl2acfZGgz3pscngTAEz/cFYW+J6B8cfo\ng/EGcNUSbZl+vunnmr185HIvZpKyLJ9f+jpTluXPwLjjP99rYqFzzH4+i/1OsIx/n9wGsiwXATwM\n4w/+eFmWn1r6KS1up7+VhXEHBgDQbLHVZaEvYpqKCRwsw3KdRxM8CsVFgwTDWWzDB4rDix6L58XR\nUHZ8qXPObcNK91haIVdMSx1NNTEPS9d0PTQcHeCThdymQEOPKPCLDmcjVUMAcFqZj6nDuJM+n+0w\nbiIqpRt6e2EMuwbm3jA8AMAlSdJtMD57f7nEeRe7mXo2gCtLNzR/DcAmSZJl1n5LcaE0EqHkCQBn\nSZL0AwDHybL8exg3SfcCgCzLj8qy/A+lbV8ozVc5CUbPzf2ltmyB0dMxn8VuIs/+XS12s3jy+f0M\nx8LP+QDuXebzrjkUNlbvKRybfO2EcYf+4AqPEQBwtNQrcTWMi2/AuACfPcTtKRh3CwCji3LRVbOW\n4WVJki4CgFJX5c7SMd8gSRInSVKrJEm/XuExDwDYKkmSozRm9NxZ7Zx6DqXVvHpgzDeZkCTpuFIv\nxpumbX8bgJsB/GHlT29eTTC6XgEAfotIPRtko1VM4BBZ0dv88sCSK81ls/4mJa8WF9tmNKYuq+r4\ndByzsuKEy8FmlbBoEar+ojwcig8r4XS01+fpctpEp9ntIWVX7qFUB2CMVpgiSZJYmpu52E2+GTcM\nZVnOwBhG/UMY80p/XNp/OmHa94vdTC0AuHnaTc0tsixP3txY7pLZp+NYiIEsyyMwgtL/AfhYaQjU\nQjdJp5/rmWnt2C7L8kI9DMv+XWHxm8WFUnv/DKBFkqTXAnhZluUVv0/WCgobqyTL8h4Az0iS9CiM\nsXxfmDZ8aLnuAHCZJEl/AJCGMefiyzAS9L9LknTBtG2/DOB9kiQ9DKNL9MY1PoVPArhRkqRHYHRH\nPifL8mEA/1s6/x0wJpgtmyzLSQBfhPH7eAzG3ZR90/79jwBeKv3O7oexUkYWxgS2e0pfL6N0J0OW\n5Sdh9ESUq+txM4A8AAgMy7p4oXGJ7QlZDxUTOBo0R5f96NCi9TcYzmIfkQuL9m5kmJUPW+LK3LOR\nSWbDW6q8gF8ilg6nRuIj3S5XW4PLvtQQFlK9yh02HgTQLUnSZQAgSRILYw7F22FcrJ9VWsaehzG3\n4bn5DiJJ0g4A7ypd33wMxhCmBIBmSZIYSZJaYHyOLseTMIYOQZKkJkmS/mklT0iSpI8ACMuy/MK0\nxy4EcKEsyw8AnFGPqQAAIABJREFU+ASMMDL9JuZ2SZK+P+tQMoATJElqKm1zkyRJ7Vj4pu75pe2W\nuom80M3i2X4FY35IuYaCVyVmBcu0E7IuJEl6M4D9siwPSJL0EwD3y7L8K0mSTgDwndKY0jXb6W+9\nEqXu6xOdnsbrurdeV47jErJKPwSwqknjANDZuuNCLDBpHAA2d77+1OVMGld1tXDkeE9WdTsXnO+l\nq/nM5tekLLwwf7E4XddxWiCTdjoEx3Lbb0tN9J+62bXoJPWVsGTUka4WX1XWMMhk8slcJBNt97s7\nuWVM8idV7xW4rjlx6c2WT5KkVhgTslth3Fl/EMBNsixrpYVt3gXjBsXtpYnQt8KY+H1vaZGXtwH4\nDID/gTHhWQXwvdLSsD+FMQfiBQDHA3gvjAnik/v/K4x5CrdOfg9jovkPYAQWDsYE6vtKQ5k+Lsvy\n5Kqdk+3/Co4tfeuBcZF/vSzLodK/TcAYhvRzGL0MGoAbZVl+rLTK5WTPznUwhjR9XJblt5WOfTWM\n+Rx5GEHrEzDCwjMwbqzGcWyC+M0weisEAN+SZfnX09ssSdLHS/veCuMGaQjGSqGfKrXvjdOfnyRJ\nHTCGVXWUgkldorBBTCdJ0iUwhkslYYz9fA+Aj8BY3ve9siy/XI7z7PS3fgjGyhF4S2P7iX/R1HFN\nOY5LyBpURODIaNlQ/44uP8MtXG3bJg73d55iXzAc+NWJga297mUvN+vMTAxs63WVZXnaZCQ9vL2n\nrermahQLSj42Hh/paHB3UNXvuqIDcMF1zUpHQ5AqI0nSBwH0yLK81tEoVY3e3IjpZFn+HY6tQjXp\n+6WvcpoaNtUi2gJlPjYhq1ERy+LaWVtjYH9/X/jkTT0LbZNJ+wNKMaUs1LsRya5sYBTPMWUZxqtp\nmtbpdVdV5WxN1bSJ0dhgq9Pe2Bto6DG7PWTDMTB6CvYttSGpXpIk/QjG0r9Xmt0Ws9GcDVIXdvpb\nnTBWtgAA+AWR5muQSlERczgCeVuPODw+stC/M7zoGD1QGFro31XRGdC05XeV82x5hgtlIpnBgNdZ\nNXU1QqOxoB7LJjb5vd020bJoJXdS004xuwFkfcmy/GFZli8ozWetaxQ2SL3YjGlL6HkFC/VskEpi\neuBgGAYdQ3k3k81lFtomnfL51aI2b3FNVhBs4+HskrU7Jgk8s+aedaWo5re0BqrixkEskhrPjCXG\ne73uDo/DRkX5CIUNUjcobJB60YhS2GABxsXzFDZIpTE9cAis4GjbPxTTF6jRx/Cic0TOBRfafySi\nLHsMejmGUSmJ3IjDJlZ070AqmY3FhmLBDru9qcnjbDK7PaRinLr0JoTUBpqzQerF1DKS3Tanh2PY\nunjta7qOX6UnsCs9gWscAbzDeewmcE7XcFtyHE/kE8hoGnoFK/7K1YwtwsLD378XH8buXHzO452c\niO8GNgEAXilk8J+JEUQ0BWdb3bjW1YLpI2bimoJPTBzG570dOMmy7MWL6oXpczhccLR5Dg72J6Tu\neSeDp5M+v6ZkVJZn5xQRS+nWZV/4CxyzUBGyZcll8omtnc0Vu9RtPlfMJCeSoU6fu5Pzi9STQWY7\n2ewGELJRqGeD1IupMd3dNmdd9GokNAVfjQ3isVx83rLy344NYU8ugQ+7WvBv/k1o5Sy4KTqA8OL1\n2yAJNvwksGXG19d8xxYVuiUxgtdb3bjZ140XC2k8np85XPXnyXFsF50UNBZmeg9HS1Lo4MPReYdE\nMbx1wd4NxuZozOaK2eW0UxAYYemtFmYtIs7z3JoCy3pQFFUZD0b6nAWd6wl4uzmWpc9ZMh8PkrvK\ntvQzIZWM3gRJvZjq2fBbLG4zG7JRHskmwAH4hq8X3Ky4MaoU8HQhhXc5G3GW1Y1W3oKPu1thZ1jc\nl4kuelweDBo4fsaXq9RRNKYWEFKLuNLhRzdvxRusbjyfT03tKxeyeCKfxPtpNMlSTA0cLMNynUcS\nvF4ozps8UwmfT1Pmzt1gGIYJjuWWNW9D4FYfFNLxzPhxnZVVwE/XdD00Eh3gk4XspoC3R7Twotlt\nIhWP5m2QukBhg9S8nf5WGwDn5M8uXnAusnnNOMPqxJe8nXDMHe2CQTUPADhh2mI4LMPgNaITLxRW\nv/R7VFXgZjlYSsPxG1kBEU0BYAzp+nFyFNc4AvBxa7qpXS9MDRwiK3qbXx6Yd3Uqhre6Rl/Nzbsy\nVTjNLGv411p6NhqtlbXSbTiUGC6G05HeBk+X0yauuJq6mRRFxXf+8yGc/xffxLazbsQV77oFj+x9\nddF99u47hGve/wOcfPZXcM7F/4J//d79UJRj2fNwXwhvfd9/Yvu5/4jrb7gd2Vxhxv6FgoKLrvw2\n7rz32XV5TlWk1+wGELIRKGyQejDjDqiTq4+w0cxZsNDqolrpcnB2DHGzPMbUwpztl0sHZvShMAyD\nySvPB7MxFHQdl9p98+xJFmBq4PBpji7bkcHh+f4tGW/wasrcmeRFi9O/VLt0XYfAsasKG8lwarCt\n0VsRXWOJeDqcGomPdLucbT6XfcnnXYn+5d/uw09/vhfXf3gnfrfrk3jDWVtw/Wdvx/4D8/5vx59f\nCuIjn/oZersDuONnH8M/33g1fnXn0/jW9x+c2ubmb96Lk7a24Y6ffQwT4RRu++XMchI/+tljCPid\nuPIvtq/rc6sCFdU7R8h6obBB6kErgKnhIA6Or4uwsZh23gIAOFzMzXi8T8khq8+/EtGkuKbgO/Eh\nfDR0CH8VehXfiw8jqhq9Fw0sj4Smoli6dg2rRfhYHklNwe2pED7sbsagkscXI334UOggvhELIjP/\nSqrkmHUPHP0jT927UODoiLB+NpFIzX6c4W3u0Vfnzt1gLRZHKJwNL9YmXdMUll3501FVTe31N3hW\nvGOZZTP5VCQYGWi2WH0tDa5Ws9uzWrlcEb/8v6fw3neciWuuPB1dHX7c8ImLcfJJ7fjxzx6bd5/b\n/vcJBAJO/NOXr8LxxzXj3LOPx+c+eTF+/r/7kErlUFRUPPn0UXz4fW/App5GvO2K12DPvoNT+w+N\nRPHjnz2GGz9/GZYobF8PupbehJDqR2GD1IMZ4cLGcXUfNjp4EScJdvxPOoQBJQ9F1/FAJopXCtk5\n8zums5eGR223OPGlhg582NWC/cUMvhztR0HX0MwJ8LI89uTiyGoq9uYSONniwM9TIZxmcWCbxYHv\nlyaQ/yBwHHQAd6QXvS4lhnUNHEcG9z57dOjJB+cLHBzDie1yKK9r6pwUmow3eDR1bu/GcLi4aBEr\nTdUWX4VgAbloZtDrtps256pYUPKhwUifV2OtXQFvF1flV8v9wTCKRRWnb++Z8fjON2zF4386PO8+\nh4+GcOq2TvA8N2P7QkHB08/3IxJNQ1E1tLYYmbCtxYux8WMvh3/61u9w9aU7sPX4qs1o5UQ9G6Qu\nUNgg9WDGcpw2lsIGAHzG0wY/y+PT4SN45/gBPFtI4UqHD+555nhM+mt3C/49sBnn2Tzo5q04y+rG\nJ91tGFILeCKXBMMw+LC7GT9KjuG9oVfRxAlo4QTszSXwAVcTspqKw0oO51k94BkG51ndeHENc0Tq\nzLoGjr6hJ544PPTEo/MFDgfr8PtePjI2+3GGt3lG5fT47MeTqsW6WFt0beVho5AvZqT2JlOuUDVV\n08aHIv3WrKL2Nnp7BJ6riaWzNdX4X81xM18SvgYHorEMUqncnH1UTQM/a/sGrx0Mw2AgGMHkuMnJ\nHGb0YBkPPvr4q3juzwP41McuKPMzqVoUNkhdoLBB6sGMsCFSzwYAwMcJ+JqvB/8V2IJbG4/HF7yd\niGkqevhFrxPn6BWM7aOlieCniy7c1ng8ftq4BV/yduK/kmN4W2lSeLo0RMtW6iGxMRxSOg2jWoF1\nDRz9Q0/+8dDIE3vnCxxNeWeLODI6J1gkYj6Hpmozt7c5mwqFhSf/6NrKx84xGSVkFYUNX+FpYiwW\n1GPZxCa/t9smWiq6gOBKdXX6wHEsXn5l5lz/AwdHAQDpzNz/hb3dAbx8YATTXyLywVHouo50Oo8G\nrx0cx2IslAAAjI7H0RRwoVBUcPO//hY3fOJipNN5fPC6n+L1b/46PnjdTzE2nljHZ1nRWpHcVRPB\nlZDFUNgg9WDqAsHDCyLPrG5iai1RdB2PZeMIKnl4OR4OlkNR17Evl8BrxfmzmKLr+EFiBH/KzRwh\nc6Q076ONs0w9xjEMXCyPP2RjyOva1KTwyWFY8VIwiWkKHGur7VaP1i1wMAAGBp98/ODYk4/MDhwM\nwzAdwbyLyeUy0x9nBYdrTE7P6PVgWJYNjmVDCzZCK70AlimbykWP72ja0PHtsUhqPDOWGOvxuDs8\nDltNFuVz2EVc/pZT8dPbH8czz/dDVTU89MdX8PsHXwQA8PzcS4R3vvUM9A1M4Ps/2o1crojgcBRf\n/ea9sNst4HkOFguP7ad04v9+8ywKRQV3/fZ5nHnGZvzXbXvQ4HXgqku345+/fR+kLS3447034LjN\nTfiXf7tvo596peAAtJndCELWG4UNUg+mqsc1i7a66dVIaiqiqjI1eTuna1M/MwDuyoTxb/EhHCpm\nEVTy+G58CDaGxfm2Y/Nvvxsfxi1xY1UanmGQ0lT8R2IEj+cSGFMLeC6fwn8kRtDFi9gxK6QkNRW3\np0L4kLsFfGlIhZ3l0MuLuDsTwZCSx/3ZKE6m4n6rsZ6BI9s/8MT+g6GnH5gdOARWtLXtH5wzHyMR\na3Bo2sxtQyl94UChz53nsRgXuCzHrWJG+SqkUrl4bCga7LDbm5o8zuaNOKeZ/v6Gv8Brd/TgXR/6\nEbaddSN+evsefPLaC8BzLNzuuUsMv+70Tbjpi5fjJ7ftwfZz/xFv/+AP8Z6/PBMOuwhfg3Ff5/Of\nfgtu/9WTOPWcm5BK53Hh+Sfg//33sUnhTz5zFJe/5VTwPIer/mI79j19ZKOfdiWhoVSk5lH3Halp\nO/2tDKb1bPiFBW7b16BvxIJ4uXjsJvQ9mQjuyUQAAD8IbMbnvZ34UWIUN0YHAADbLQ7c2NAFgTl2\n/TmhFsFNu8T7uKcNv0qFcFtqHGFVgYNlscPixHtdTVOBYtIvUuM42eKYEyY+4W7D9xLDeDAbw2kW\nB97mqMoVQyvBRwHg5XOv/NhJj961rNoW0w2OPPtQZ+sOADgXwIyLf05HqG9wr5Vh2XuO8++4nJk2\nEdqlu5o9h/r648f1TFU/ZgSna+LQ8GDT8fapC6cC72hY8OQrGEaViqZHTutuW/e7v/l8MZsMJcc7\nfO5O3u8xfcWrjeJ0WnHLN9+FaCwDHTp8Xgf++38ex6aeRgj8/L2O73jrGbjq0u2IxjJoDLiQzuTx\n2b/fBWlLCwDglJM6sPf+zyMay8Dvc+KTf/s/uPKS03CCZEy5SSSzcDiMEXEOh4h4YllF52tVF4C9\nZjeCkPVEYYPUOgsAEaWlb32CpW7Cxld93Utu83cNi99Um30MK8Pifa5mvM+19A3fj7rnn8vbI1jx\nLf+mJfcny7J+gUPRhw4P7gEY5u7jfNuvmB44mmOWjkw0OlFsaAhMPhadcHkDxyk6WyruwopWdySW\niPm81jlDkBgssb5yia7repvLaVl6y9VTFFWJjMaC7W5Xqz/gXfqPpsY8uHs/mhvdOGVbx9Rjv3vg\nRbzxvK3zbi8fGoV8cBSXv+U0tDQbmey397+IliY3Ttp6LBOyLAu/z4m9+w7hqef6cP//fXrq31xO\nK8KRNLo7/ZgIp+B2rWyeWI2hng1S82gYFal1TkyrXeeuo7BB6sa6DKliAI0vaPFXh/YOH4o8N6Pw\nH8uwXOfhOIdicWpVKUZwucJHsjNmGg+FCvH5zsnoywsbqXB6sMnnXpeuL13T9dBIdIBPFrKbAg09\nooXf8MnnleDu3z2PT3/xl3jq2aMYCIbx1W/ci6HhKN7/zrMBAN+65QH89cdvndo+OBTF5/7h17j1\n9r0IDkfx+4dewrdueQCfuf6iOXUzioqKr37zXtzwiTfB7To2JOuM1/Titl8+gb6BCfz3Lx7Hma+t\n65sPVGuD1DwKG6TWNQGYGjvuooJ+pDatS+BggYSQV7gDo48fnB04LIy1oeWVgZHp20dDbrs2bWGq\nhCLMuxgDi/kLCE6nKGphS4t/XYJGOJQYKYZTkd4GT5fTJrrW4xzV4uZ/uArbT+nCxz/3C1z+jlvQ\nNxjGz3741/A1GMMfQxNJY0nbkgvOOwH/8LlL8fNf7cOb3/odfOc/H8KXPnsJrrjktDnH/unP98Lj\ntuHqy3bMePxLn70EE+Ekrnr3fyCezOKLn7lkfZ9kZaOeDVLzmAWKxhJSE3b6W88BcNHkz5/pOfGK\nzQ7X3E9FQmrDDwGsakgVAHS27rgQ8wypKvJsT97O953QdNaps4dUDTYqg+mujqkLpgbfcLBxs70D\nAHRVVc7sLICfXZciFu4/U3IuOmQpG073ndzb1rOa57GQRDwTZjLFfGuDi1YAIpXiObiu2bH0ZoRU\nL+rZILVuZkE/qrFBatu69HDwijYkFNSOV0L7Xpjdw9E2jiYulZoqlBAdd9smezcYjuOHxrJzanOw\nzOJ3ufLZQkrqaOpYbJuVyGbyqUgwMtBsEX0UNEiFoWFUpOZR2CC1bkbY4BmWFkUgta7sgYMBikJe\nTbNFrWF24OAYXuyQx3O6phq9IbzTHz6aDU7uO57Q51QL55b45BHyWtQi8Gv+Wy0WlHwoGO7zaqy1\nK+Dt4mZPKiDEfH4kd9VUsUhCZqOwQWrdjDdxlgFVkCP1oOyBg9URFXOKA5omzA4cNtibAgf6Bya3\nnd67kePsc5aR5Rgs2K50IjtxXEfjmsaxa6qmjQ9H+sWsovYGGnqE2cO4CKksNVk0kpBJFDZIrZtR\n5IEBQ695Ui/KHzg0PSjm1DboOmYHjkDG1i2OjRmVxHmnP9JnrEzFWm3eWDyXmn5sjl04bPgFUWHZ\n1f+ZTozFgnosm9jk83bbRQvdMSbVYG71REJqCF14kVo3402cZeg1T+pKWQMHA4AvauN8UW0BgFdC\n+16Qw089rOu6zjAM0zmYd7C5bA4AImOuqaVkg2O5GVXHeXb+4UzJcCrY0dzQspq2xiKp8cxoYqzH\n4+7wOGx0p5hUEwrFpKbRhRepdTOGTbHUs0HqT7kDR1bIqSqjai4AeHXi6T0Ho08+quu6zjMWZ+v+\nQSNY8K5A+GhmCADihZmlqHlu7t+hpmlat9+74gUcUqlcPDYUDXbY7U1NXufS1SYJqTzUs0FqGl14\nkVo3s1AZw9CcDVKPyho4OB0hMad4oessABwIPfPy0eRT9+m6rrt0d2PD4aODABAeNap/a3Z3g6Jq\nU8vpCtzcz55MJDPoczuW3SORzxezE8FIf4DlXR1+T9lWriLEBBQ2SE2jsEFq3ewiZfSaJ/WqvIFD\n0YctOaUdAKAjJE88OTKQfuZuXdf1xqilzRKLhcG7GyN9mWGW54XxUDY0eSyBY2ZM2C4WlNzxbY3L\n6pVQFVUZD0b6nHmd7Ql4u/m1TPAgpDLQMCpS0+hNmtS62T0b9Jon9axsgYMBVL6gxbii2gQwUIps\n4dX43kMD6WfuZsCynYdjLJRiMTzi5AFgLK7mJo8j8OyMHkYtVRizWy3Wxc6ta7oeGokOcMlCdlPA\n2yNaeHGx7QmpItSzQWoaXXiRWjfjoop6NggpX+BggaSQU1hG1Wy6jnGlwDYcTu19oS/9xKO8Lnrb\nXukf0Xl3U6QvNZGGbWo+Bs8dG86YTedjUkfTokvdRiYSI4VwOtzb4Oly2kTXatpNSAWjng1S0+jC\ni9S6GXdQGdCcDUJQxsDBaRi15NQm6IBSYIuqCvvR1J+eGsrue9iVd3S6gkPB8LCDhdXuT6cLaQAQ\neFaYPJZDY1I8P3+Zv0Q8E06OxIa7nM5Wv8seWE1bCakC1LNBahqFDVLrZg2jotc8ISUfBXDdanee\nDBwMwPKKNiwU1A5dx5hSYH0Akx7I7Ds8Xnj67tZRPcAXeDERzI4MhfIRABB4Y85GKpYZ3dTeOGdy\ndzaTT4WDkYFmi+hrbXC3rbaNhFQJChukptGFF6l1s4ZR0ZwNQgA8COCNJz161/fXcpBpgUMV8mqG\nKeo+pcgWNRU2VWMwnNvzQqjw3O/b5dHcRNDKRLLGn5/As4Ku62hx2GdOFC8qhfFguM+rsWJ3wNvF\nMfPX4yCkxtAwKlLT+KU3IaSqUc8GIQBKhffuBPDPJz1619PlOu7gyLMPdbbuAKvjXDGvtOc4brRY\nYJs5TlU0Hdbh3J4XWBQaAodP6462i5xSVBWOY/nkRGpwy6b2TsCosTExGhtscdgbNwUaesrVNkKq\nBPVskJpGYYPUOhaAfuwHmrNB6oum69rRTOrP908MPbg/Fb95d3gkXu5zTAYOTtXPE3NaR4Hn86pF\nTRVV+EReH44U9x1qjgmR3P5TTh7vzUTVFrFhc5PPCwATY7Gglxccm3ze7nK3i5AqQWGD1DQKG6Rm\n7fS3MjDChjr5GDNrWBUhtUrVNeXVdOLZe8eDj/dn03EYfwvvBXDLepxvMnDwRe0tak51FAXOq1gU\nVQR4hoEaUx77s70v7xo5enJnviuT1ryCPTOWyPR43FSQj9Q7GkZFahqFDVLL5vRiqLpe5BnGYkZj\nCNkIBU3L7U/FnrpnbHDfeCGXgfF3kALwJIAn1vPck4FDyKt/mRc4a9HKqLqgCwygAbAUC0/3NfQz\nSV/hhBN94AI297HlcAmpY9SzQWoahQ1Sy1jM6sko6lqeB0thg9ScnKqmX0hGnrhnbPDpuFLMw3h/\nj8IIGE/vDo9oG9GOycBhSWvvz1sZmyqikWGQOd0mnPCeBufxXj3o4vssjE2LOlVVV7M6m8rrXLYI\nvqDxgsZaRFYQRUG0iTabXXTyHEefU6TW0fBeUtPoTZzUsvnCRs4GUFEwUjPSihJ7JjGx956x4PM5\nTVVgvK+PAdgD4KXd4RF98SOU3+DIsw91tO4Q1ATz6XNaLS3Xtdp7N4l8BwCMO4XRloloIOFzRN1O\nscEJ3eOE4gEUADmgmASKAFKAruvIqEwmr3PpPLi8xgoqBAt4UeQtNqvVZhMdoigsWnmckCqQNrsB\nhKwnChukls1ZeaqoaXkzGkJIuSWKhdC+2MSe34WCLym6rsF4Pw8CeGR3eOSgmW2LX3sR8/IVfj6U\n0zY1Wtnjpv+b1ytyAgs+c2RYU0/qVjmOXfCuLsMwsPGw26DajalXBUBLA1kYXwAKKgpZjU3lweUU\nhld03qJxosgJomix2UW71So6WZaW0CUVjcIGqWkUNkgtK2DaSlSAMZ7dpLYQUhbhQj64Jzq256GJ\nEbn04mYBHAHwx93hkQEz2xa/9iIOwNsBfAHAyY3WmXlfYXTFbeP9AODRNP/okfH+9i0ta1qFSuBg\nETjNZ0wLKQLIAnkYXwlA03QtpbHJnM5miwyf11iLxlosLC+KvNVmNYZq8Zyw+FkIWVcZsxtAyHqi\nsEFq1u7wiLLT31rEtKFUBZ16Nkh1Gs1nj+wOjz62NzreV3qIAfAKgId3h0fGzWsZEL/2IhHABwF8\nDsCmhbZLWbmIh2WaJn9uTqW6R8cSoZZmd+N6tY1lGdbB6m4HVLfRO5I3RmwpmLqfnFX1TE7jMgVw\nOZW1qBAEnbNYedEmWq020W61Wmi1ILKeqGeD1DQKG6TWFQCIkz/kqWeDVBFd1/XBXObAgxPDe55L\nRIYnHwbwIoA/rEfNjJWIX3uRC8C1AD4DoHWp7TWPMOMOLsMwcA2H7DmvPWMVedMu6K0cY7dymn2q\nd0QDkCt9RYGipisZlU0VwGUURlA0XtA4i8gJVlGw2qx2m83iZFmWCoaS1aKeDVLTKGyQWpfHjLCh\nUs8GqXiThfjuCwX3HkgnJmD0YigAXgDw0O7wSNbM9sWvvSgA4FMArgfQsNz9eJdlzmRuKwPHxKtD\nw9aTuyu294BnGd7N6l5A8Rr/G7LGbYwCjKFauq6nFSaZA5cpgi+onKCyFpHhRItgtVqtNrvoFASe\nVsEjC6GeDVLTKGyQWleY/kNeValng1QsRdeKB41CfE9MK8SXA/AsjDkZhcWPsL7i117UAeAGAB/G\nKgqRedwW73yPB1Slbbh/or+tO1CVVcRZhmHsAlx2qK5jQ7VSx4ZqhYGcilxOY9N5cDmVFRTwFnCi\nyFmsomi1We1Wq+BgaB57vaKeDVLTKGyQWjejJyOrUdgglWepQny7wyOKme2LX3uRBODzAN4DYFWT\nqTO8Hm+08J6F/t0fibcnfM6I22X1rbKZFU3kYBU5zTo1VEvPHBuqFQNUTVezKpvM6VxWYfmixhkT\n2QWraLHarDabTXQutnIXqWrUs0FqGoUNUutm3AnOqjSMilSOnKqmXkhG9pldiG8h8Wsv2gHgiwCu\nxjxLSa9EzsEnACwYNngGfPrIMJRtPQrPsXX32cSxDOdkda9zaqhWzlhcqwggOVVzJJ3T2UwBfE7l\nLCojWBheFHnRJlptNtFpsQjiEqchlYl6NkhNq7s3dFJ3ZoSNjKpQzwYx3SKF+PYCeNGMQnzTxa+9\n6DwAXwLwpnIdk/VYlgxOHl33jR4a7W+X2qpyONV6KtUccdigOaYmjKgwLlNLl6p5Vc9nNTad17mc\nylqKuiDonGXaUC2bxcHSWK1KRD0bpKZR2CC1bkbYSKsK9WwQ08SLhfF9sdCe+0JDL08rxDcI4NFK\nKMQH4FIYPRlnlfv4To/oXM52Ldlsd2g8MdzY5G4rdxtqnYVjRAuni1Nr++o4VnMkDqiarqU1JpnX\n+EyR5QsaJ2isRWR5URSsNtGoOcJxdF2w8ahng9Q0elMhtW5G2EhRzwYxQTUV4luPcxShF9wOy7Ln\nYtiHQt6cx5axikLFrlBVjTiWYZ0s3E4o7mNDtZLGUK2UsU1GQSans+ki+LzCCgojWBjOGKol2mxW\nhygKNjOfQ42ing1S0yhskFo3I1wklAKFDbJhaqEQXzlk7GzYyzBL1uGYZGVgn3h1eFjc1mWnUT8b\ny8bDboM0MWtjAAAgAElEQVRmnxqqpaWBLIwvAAUVxazGpPI6l1U5oahxlsmhWhbRJtptNtHJsvQ/\nbYWoZ4PUNAobpNbN6NkYzmWTmq7rNG6ZrJdphfgeey4RGZl8GFVaiK8cVJew4uGLAVVpG+mf6G/r\naaT5GxVE4CAInN4AKA3z1hzRdD2lsYmcxmYVhi+ovEVlBQtbmshus9mtToHnVrWiWQ2jng1S0yhs\nkFo34yKnqGtaVlPjDo6fd71/QlZrkUJ8z8MIGZVSiO/jADb09S96xFUVtAtE4x1xnzPscdv85W4T\nWR8syzAOVnc7oLqP1RzBsZojALKqns1pXLoALqeyFhWCBZzFwllsVtFmEx1Wq6Wehs9poJ4NUuMo\nbJBal4UxPn5qJZyUUoxS2CDlMlmI7zdjwccHcukEKq8QXyeAz2KVhfjWStd1eNziqmpncAzDaUdG\nGeXk7rpcDrdWWTnGZuU021TNES19rOZIFChqupJV2dRkzRGdt2isRWQtVlEUrcZEdo5l17QUcwUZ\nhesaU5e4JmS90Zs3qXVxGK/zqQu+uFKMNIu2XvOaRGpBPRTiK4eMhYk2CVzDavd3Q/ONHhzpb9/a\nTsOp6gTPMryL1b2u6TVHpg/V0nU9rTKpnMaliwxfUDlBZS0WhrOIvGiz2ux20SkI/Kp600wwZHYD\nCFlvFDZIrQvNfiBazEfNaAipDZOF+O4eG3wqoRQLOFaI73EAz9RSIb5yyDv4JIBVhw0AaMnlusfH\nEkNNze72MjWLVDGWYRg7D6cdqnPOUK0MgDCQU5HLaWy6oHM5hRMU8BawFpETbaJotYl2q9XiqJCp\nexQ2SM2jsEFqXQbGUCpu8oGJAoUNsnJVUIjvfBgho2yF+MqB85TnBrNjONSQ9djSNqvgKMsBSU0T\nOVhFTrNODdXSM8dqjsQAVdPVrMqm8jqXKbJ8UeMsGmuxsIJVtFhtVpvNJjo5juWWOE05UNggNY/C\nBqlpu8Mj+k5/awLT7qwO5zIRE5tEqsxkIb7fjQ+9pELXUUeF+MrB6RFd5TiOlYF94uDwsHVbV6Xc\nkSZVjGMZzsnqHicUz7GaIzC+ksZco4zGpHMqmykwfF7lBIURRIYXRV60ilabXXRaLIJYhqYEy3AM\nQioahQ1SD2KYFjb6sinq2SBLmqcQHwfgICqnEN87YBTi22ZmWxZTZPScxy6saQjVdKXlcPvaehp7\nynVMQubDMAxsHBw2TnNMTRhR00ZfeQZABMireiGnsam8zmcVllcgWDA5kd1qs9qtNotjGcusU88G\nqXkUNkg9SEz/Ia4U83lNzYgsV0/LK5JlGs1nD+8Oj+6p90J85ZC2cxEvw7SV85iBaLyTlsMllcDC\nMRYLp/umukT07LGhWnFA1XQtrTHJvMZliqxQ1DhB5URRb27xR8FxDQDTwjAMhQ1S8yhskHowp4ha\nSlGiooXCBjFUSSG+j8EoxNdiZltWQnMLxXIfk2MYTj8ywion99ByuKSicSzDOlm4nVM1R3JAIQkM\nTEythqiD6WNOvcbEVhKy/uiNmtSDMGbV2kgqxYjfItLKNnVO03XtSCb55/tCQ3vkdCIMKsRXVtZV\nFvNbigt6Ay2HS2qABug0Z4PUPAobpB4MwKgzMFVNPFosRHtMaw4x2yKF+J4B8EiFFOK7AcCHYEIh\nvnLQdV33usR1G+pkLIcbH2pq9tBNA1KthplTbzL1vYaQjUBhg9SDOKYV9QOAcDFHK1LVoVIhvj/d\nPTbwZKiQnyzElwTwJwCP7w6PqGa2r1SI7wsA3g0TC/GVQ1pkIk6eXdd5FY7hiYasx07L4ZJqddTs\nBhCyEShskJq3Ozyi7fS3JgE4Jx8bzWdpRao6skAhvgiAJ1AZhfheA2P52qtQAYX4yiHv5NMA1jVs\nWBnYw68OjVhP7qblcEk1orBB6gKFDVIvYpgWNvqzaerZqANpRYk9HZ/Y+5vxOYX49gB4qUIK8X0J\nwEVmtmM98GUq5rcUv6a2DvdN9LX30nK4pOqYWqeHkI1CYYPUixnL347ks6mcqqasHOdcaAdSvRYo\nxDcA4LEKKcR3GYyejDPNbMt6cnusno06V2Ms3hmLOye8Hltgo85JSBm8ZHYDCNkIFDZIvZizdOlE\nIRfssDm2mtEYsj7ChVzwscj4Y38Ij7w6rRDfqzAK8Q2a2bZqKcRXDnkWGZ9N2LCwwTEMh6MjvLKt\np8jzbFXPdSF1hcIGqQsUNki9iMFY1nRq2MxQPkNho0YsUIhvP4DdFVCIz4pjhfh6l9i8JmTsbNS3\nwatouaB7Rw/RcrikamQAHDG7EYRsBAobpF4MALBg2vK3RzKpodd5G81rEVmTUiG+Vx6cGN5Dhfgq\ni74OxfyWoyWX6x4bjQ81t9ByuKTi7WdOvcnUhSkI2SgUNki9GINRR2FqyZo/JyLD72jt0Rlaxqaq\nVEkhvk8DuB5VWIivHOwe0WbWuZ2jIV/GY0/ZbQLNxyKVjIZQkbpBYYPUhdLyt2OYdoc5qSqFhFIM\neQRLk4lNI8uk6Frx1VTi2XvHqRBfJdN0XfO4RJ9Z57eCsYUPDY9Yt3U5WLqRQCrXi2Y3gJCNQmGD\n1JNxzBrOMl7IBSlsVDYqxFdd0lY24uJYU1eF8qtK60hfqK+9t6nHzHYQsgjq2SB1g8IGqSfDAE7F\ntEniwVx6aIvDvcO8JpGF5FQ19Xwi8sQ944NPTyvEFwXwOKgQX8UqOLk0ANOXoG2MJrpiDc4Jr9du\nelsImQeFDVI3KGyQevIKgMsBTA23kVOJ4E5/q3ktInNMFuK7Z3zwubymqaBCfFXF4hErInhxLMOi\nb5QrbusuCjxX9z1OpKJEmFNvGja7EYRsFAobpJ4kYNTbmJq8uj8VCymaVuBZdmPKHZMFxYuF8Sdi\noT33zSzENwjgUSrEVz1cHrFiJsW7oDeMHRwdaDuhvcvsthAyzfNmN4CQjURhg9SN3eERfae/dRzA\n1Dr8GqBHioXhJtHaY17L6hsV4qsdOVZP+a2Cy+x2TNecz3WNjcSCza3eDrPbQkjJ42Y3gJCNRGGD\n1JtRTAsbADCazw5R2Nh4o/ns4YcnRh57PBbqLz3EwBjq9jAV4qtOWScXA1BxS866RsOBjNeestss\nFdc2UpcobJC6QmGD1JsBAOfAqMsAAOjPpoKnuBvMa1EdmSzE98DE0J7nE1EqxFdrXBZTVwZbiMjA\nGjk4PGo9uZuWwyVm0wE8YXYjCNlIFDZIvTmEaatRAcBLyf/f3n3Ht1Wf+wP/HG3LluUp27EdO/Ob\nkGEChBDKSKBQXKClQAuF20IvHZRb2v5aWrpb997CpdyWQmkZZRfKKDsBAwFCEgjZCSHrZMrblrct\nWVvn98eRE287ia0jWZ/36+WX7aMzHjmxfB59v9/n6ai7PK9Yo3CSQwI04ssF8AMkcSO+8WDN0K6Z\n32iyIuH8hiPNzsLpLIdLmtorlVV0aB0EUSwx2aCksrq1wb88u6AFwNGhjDp/T7cnHOpI1Rt4kznO\nRmjEtwXqwu94aMT3EwA3IYkb8Y2HMJSwPc2crXUcI8nt6Jra3pHWnJlhzdU6FkpanEJFSYfJBiWj\nJvRJNgCgxus5MCfNvlijeCadBGjENwfA7WAjvnHjseha03VSXDfI1Osknc7ZaAzOLwkYDXpWoCMt\nMNmgpMNkg5JRE4A5fTfsdnfsZ7Jx8oZpxNcGdY5yvDTi+wWAK8BGfOMqmGbQdCrcWKVByWja31A9\n5ZQilsMlLTDZoKTDZIOS0X6oDdmOTuFZ3+468kVHcdCg0/Fd7hPgCQXbt3S2ro/jRnzLofbIYCO+\nCWLKMOu1jmGs8gL+qY0NHbX5LIdLsdUqlVXIWgdBFGtMNigZNQDoQZ////5IJNwY8B4usqQK7cJK\nPGzER73sdnNClXRLb2zN8dit3alWU1z1BaFJjVWoKCkx2aCks7q1IbI8u6AawPS+2w94uvcz2Rib\nOG/EZ4DaiO92sBFfTHgN6M4xGRLqpt0swdJ2sL4jZUFJGsvhUoys0ToAIi0w2aBkdRjADPQpg7uh\nvfnAsqw88L5jeEM04tMB2A21EV+zhqGxEZ+GvKn6DgAJlWwAveVwXc7C6XmlWsdCSeEtrQMg0gKT\nDUpW2wBcgj7N/er8Pd0doUBDptFcoF1Y8WeYRnwRALsQH4340qE24vsh2IhPE7p0k6YL/0+Go7N7\nant7miszMzWuK2lRwquVyip2aR0EkRaYbFBSWt3a0LM8u6AOQF7f7c4e9/5MO5MNgI34aOysdnOq\n1jGcKJ0k6fTOJnMwrSRgNLIcLk2Yt7UOgEgrTDYomTkxINnY3tW2f5E9+3xtwokPCdCIbyqA28BG\nfHEhBCVoTzVlaR3HyUiVFHvTgfrqKacUsxwuTRROoaKkxWSDktlOAOcACPZu2N7VVu8Lh90WvT5N\nu7C0MUIjvo0APmYjPhqKJ0XXatdJCT99LS8QmNpY316TPyWzWOtYxiISUXD/i7vwwEu7cctV83Dr\nVxYcfayprQd//tdOrN/ZiA53AFPz0vAf5bPw1YtnjXjON9dX45HX9sJZ343MdDM+u7gQt16zAGkp\n6q/bqk21+N8nt8PtDeK6i2fiB9cu7Hf8odpOfPkXq/DyXZ9DaUHCLeGZSCEAq7QOgkgrTDYomdUD\n6ABwdAqIAqDW5zkwMzV9kWZRxVgCNOI7A2r5Wjbii0Nhm9GndQzjxd7U5vBkpHalWk3pWscykvYu\nP35833rUuTzQDShoEQpH8M0/rIHVYsB9t52DTJsZr645gopHtiIr3YLPnTV0LlW5vho/vnc9fvTV\nMlx8VhEO1XbhVw9uQoc7gLu+dxa8/hB+8feN+NnXF2FmsR3fvmMNlp1eiLJZ2UfP8T+Pb8PXymcz\n0Rhsg1RWoenaNiIt8Q83Ja1oo7mqgdv3ujv3axBOzHlCwfYPWhtX/nL/tr88XX94fVcoGIHaiO95\nAH9d3dqwWctEo/Pmi5Z33nzROwA2A7gSfL2KSya7adKMMpkkmHsO1nsjEUXTJpSjeX2dEwa9Dv++\n82Lo9f2TjZ0H21Df4sEfvnsmFs3OQWmBDT+8diFKCmx4e8PwVakfXbEPF5xeiG9dMRcl+TZccEYh\nbrhU4M311QiFI/jkQCvSUoy46oLpKJuVjfMWFeDDTxqOHl+5vhrO+m7cfOUpE/a8ExinUFFS48gG\nJTsZwEL0qUq1vt11+POOorBekhKmI/LxGKYRXzWAdXHSiO8LUEcylmgZC42N3W5J6PUaA2VFwnkN\nR1zOwhnxWw73wsWF+Fr5bOh0g8t0nyZysPXJq4c8zqAfvqz3E79ejnCkf46VY7cgGIrA7Q2iucOL\ngpxjS6Sm5KaiqU2tEdHjC+Guf27Hz284DSlm3lYMgckGJTW+KlCy2w11es7Rv8Ld4VDA5fc5Cywp\nM7QLa/y1Bny1a9tc696P70Z8PwMwT8tYaOw8BnQ4jPpJVwnM0dVd0tae5sqK03K4RY6xLynz+kN4\nuvIAmtu8+Fr57GH3S7MOHqBavbUOJflpyEgzAwrQd8aWTgKU6ADQAy/txowi+7BTtJKcC2qpdaKk\nxWSDktrq1oZQtJt4Sd/tu93tn06WZKPB5z20urVfIz4JwB7ETyO+/4RaXYqN+BKMP03fhUlYdlgn\nSZKhqskSSCvxm4x6s9bxnKjzvvMamju8KHak4ZFfno8FM7NHPyjqlQ+O4N3NdfjTD5YCAHIyLEdH\nMgCgsc2LKTlWHK7vwjNvH8BL/3sxNuxqwl1PbUd7tx/nlhXgt986AwZ90s9+fF0qq4jraXlEEy3p\nXwWIABxBn5ENAFjV0rAnGIloWuL1ZCiKolR7PXseqdn/8B8O7Xw6mmhEAHwC4E+rWxue1zLR6Lz5\novTOmy+6HWr54b+BiUZC0qWbJu1NVCqU9NYDDS6t4zgZz/z+Qjz/h4tw7qICfPOONdiwq2lMx72+\n1olfPbgJ37hM4NLPqO/DLJyVjdZOHzbtcaG5w4s12+qxdEEe/uexrbj+klkozkvDT+77GN/78ny8\nde+l2F/TiRffOzyRTy9RPK91AERa48gGkTrEfRH6lMD1hENBp9e9a1Zq+mnahXX8oo34Pqlsrvso\njhvx/RDALZiE74gnm7QMy6QuO+QI+Isb69pr8gsToxzuQMV5aSjOS8PCmdlobvfizie347W7Lxnx\nmOfeOYiKR7fgW1+cix9dV3Z0e6rFiJ/dsAg3/c8HiEQUXLlsGlo7/ThS1437bzsXh+u64PWHceHi\nIgBA+dKp2LCrCddePHNCn2OcawawWusgiLTGZIOS3urWhq7l2QWNAPrNMVjf3rw9UZKN3kZ8K1w1\n62t8PfHciO+bAFK0jIXGR1BS/OlWY6bWcUw0u6vN4c60dqVZzXFdDrfXodpO7K/uRPnZ/fsTziq2\n44Nt9SMeu/LDKlQ8ugU//dqp+MZlcwY9fs1nZ+KK86bBHwzDaNDh0v/3Jm6/YRGsFgO6PAGkphy7\npUhNMaDTk7CDw+PlJamsQtP+RETxgMkGkWo/gKV9N2zubKn9Uv7UlnSDMUejmEYViIR9u7s7N73u\niutGfD8DcB3YiG9S6UnRtWVIUoHWcUw0kwRz+8GGDuv8EptuYFOLOLRNbsGvH9qM+TOyUJx3bCH5\n/upO5GUNn+fLVR34xQMb8cNrFw6ZaPQym/Qwm/S459mdKJ1iwyXRReE2qwmd7gDCkQj0Oh1aO31I\nTzWN3xNLTJxCRQQmG0S9PoTaTbzfzfme7o7tZ2XmXqRNSMNjIz7SWthm9GsdQ6xkRsJ5DYddzsKZ\n8VEOt8PtRzB07Fe8xxdCc4c6Q/KSpcV44KXd+OE9H+HnNyxCbmYK3t1Uh3c31+K26089eszt92+A\nXifhjlvUCtN3PbUd06ek48rl046eq5c9zQST4VglcGdDN/5ZuR8v/u/FR7dNL0xHaooBT76xH+eU\n5ePVNU7ccOnw1a+SQAOAtVoHQRQPJCW+excRxczy7IIbAZT23ZZvTkn9xYwFP9JJUlzcMHtCwfbN\nna0frXDV7PBHImGoSUYtgI8A7Io2KtRM580XXQA1yfislnHQxOsRtobcLOukH9noFVEUpask35Wd\nlZandSxf+9172Lxn6PoO795/GcIRBX965hNs3OVCIBRGSb4N118yC1dfMB1SdHDma797Dwa9Do//\nejkAYM5Xnhv2ek/+djmWzDv2tL91xxrMKcnAj68v67ffhl1N+N0/tqClw4fys4vxm5vOgNEQFy+d\nWrhfKqu4VesgiOIBkw2iqOXZBYugdqruN7rx8xkLvlposWr6Ft0wjfgOQ12PcVDT2NiIL+koigLT\nmbl+kyFxy8KeCA/QZZlXak7kcrgUM+dKZRUfah0EUTzgNCqiYz4BcAmAfjcSWztbt2uVbLQEfDXr\n2lwfxnEjvq8CuB1sxJdUPCapLc2gn1Sdw8ciFUh3HaivKTilOCGrU1HM9I42ExGYbBAdtbq1IbI8\nu2AvgFP7bn+/tWH/xTlTPBa9PjVWsSRII76fYMC0M0oOgTRDN4CkSzYAwBEIFDfWtdXkF2Yx4aDh\nvMBGfkTHMNkg6u9jAIvRp+dGSFEiB3u6ds63ZS4d/rCTpyiKUuPz7H2npf7DHV3tDb2bAXwK4N3V\nrQ1dE3n90XTefFE61P4YPwSg+bx10o7ebor7qkwTKcPVlufOSO1MSzXbtY6F4tJjWgdAFE+YbBD1\nsbq1oWl5dkEtBtxMr2lr2j5RyUZvI743m+s+2h/fjfj+CwBvrghpdvOkbuY3GqMkmdwH6zutC0oj\nOl18FI+guLFeKqvYrXUQRPGEyQbRYLsB5EMdVQAA7HV3NrcG/HXZJnPheF0k2ohv6wpXzcd9GvF5\nAWxF/DTi+wmAm8BGfBQVkBRvRsrkb+Y3mkwlkttwuMlZODO/VOtYKK48rHUARPGGyQbRYBsBLIc6\nwnDUzu72bcuz80862UiARnxzoS76ZiM+GsRj1bdlStK4Jd2JzNHtLmltczfFQzlcigsdAF7QOgii\neMNkg2iA1a0N/uXZBQcA9KtA9XZz3aefycy9yKTTW07kvAnSiO8XUBvxJfWcfBqekm4MaR1DvNBJ\nkmSsakoJ2FL8LIdLAJ6Ryio0nfZKFI+YbBANbSuAU6CunQAAuMOh4F535+ay9Kxzj+dEwzTiawQb\n8VECSrGbeVPdR6qEdNf++pqCeSyHS5xCRTQUJhtEQ9sPoB1Av4WwK1y1G+fbMs/WS5J+tBNEG/Gt\nq3TV7Y424tMDqAYb8VGCiiiKYk83J2XJ25E4goHihtq26oKirKlax0Ka2SSVVezUOgiieMRkg2gI\nq1sblOXZBXsw4Ea80e/1HO7p/mRWavppwx3LRnw0WXnMUqtNr8vROo54lNnclu/OZDncJMZRDaJh\nMNkgGt46AGehT1UqAHiruW79TKvtNEnqv6yhwec99H5rw7qP2YiPJqlAmtEDgMnGEIySZPIcrO9M\nWVAS0et0LIebXLoAPKd1EETxiskG0TBWtza4o6Mbc/tulz1drXX+HrnIkirYiI+SidFu5E30CDKU\nSG7jIZezcBbL4SaZJ6SyCo/WQRDFKyYbRCNbDWA+gH7laN9rafzwM5m5PUM04tsOdSSDjfho0rHZ\nLelaxxDvHG53SWuruzE7Oy1f61goJkIA/qx1EETxTFIUTQvhEMW95dkF3wBQMszDOgAesBEfTXJ+\nHXqyluRZtY4jEfQA3aZTSoxmk+GEymRTQnlWKqu4TusgiOIZRzaIRrcWwI3oP7qhh9rAiY34KCn0\nWHXtWQCTjTGwAjbX/vragvlTi7SOhSbcH7UOgCjeMdkgGsXq1oZDy7MLGgA4oP7OuBA/jfgWQy1f\ny0Z8NLHSjUGtQ0gkjlCwqKGmtbqgOJvlcCevd6Wyih1aB0EU75hsEI3NRwDOBvAh2IiPklBKhoXT\n8o5TZkt7QXdmaoctzZKhdSw0ITiqQTQGXLNBlEA6b77oCwB+ATbioxiKQImknOmIGPQ6vkF1nDok\nXXPGgpJslsOddHZIZRWLtA6CKBHwxY8osdwEJhoUYx6zrpWJxolRy+E2VWsdB427u7UOgChRMNkg\nShDlpQ7Dvw80Vmodx2QRURQ8fKQDS1ZX4+EjHcPu1+gL4fy1Nbh5e9Nxnf/u/W04c3U1trb7jm5r\nDYTx3e1NWBY9X1tgcF2Bb21rwj+OdB7XtSZawGbo0TqGROZwe0paWrobtY6Dxk0VgBe0DoIoUTDZ\nIIpz5aUOc3mpoxzAT1861DSl1u07pHVMia4jEMYPPmnG20090I2yrP7u/e0IRo5vuumeLj9ea3AP\n2v7Q4Q5Y9To8eUY+bAYdHh6QVLzZ6EGLP4yvT42vdhYmu0mvdQyJTCdJkrnGleYPhHyj700J4P+k\nsoqQ1kEQJQomG0RxqrzUIZWXOr4A4KcAzgJgAhB5/bBrjbaRJb7KJg/0EvDE6fnQj5BsrG7uwc4u\nP87JHvva6LCi4E65DZ/PSx302IY2H64ttqHEasSXC23Y0Has96M7FMFfD7XjR7MyYR4pKA2k2y1s\nDHmSrBLS2vfXt2gdB520KgAPax0EUSJhskEU34qh9vQ4+tb62vr2mgaP36lZRJPAeTlW/HlhLmzG\n4V8Ce0IR/OlAO74/IwOphrG/VL5Q2w1vWMH1Q4xOtATCyDergwT5Fj2a/cemUT18pBNzbSacmxNf\nRZ98enRbzQab1nFMBrlqOdwqreOgk1IhlVVo2ryVKNEw2SCKU5VOlwK1oeCghbmvHGp6P/YRTR6F\nKQbopJFHDx480olCiwGX5Q8eoRhOky+Eh4904qezs2Ac4vwKgN7NOulYBnnIHcDrDW78eFbWmK8V\nKz1WXXwtIElwWS3tU7rdvnat46ATsg/AU1oHQZRomGwQxbddAAatTF5b317j7PLu0yCepCB3B/BK\nvRs/E1mQRklK+vrTgXacl5OCM7MsQz6ebdLDFR3NcPnCyI2Octx9oB3XFdtgN+pw+65mXLa+Djdt\nbcQht/ZvoEp20+BV7HTCDJJkDB5qCIfDEf5cE89vpbIK/rsRHScmG0RxLDq68SGGGN14Wq5/N6Io\nmnYwn4wi0TUX1xXbMC3VOObj1rX0YFuHHz+YmTnsPqdnmPFGowehiIIVjR6ckWnBW00eNPpCuGGq\nHY86OyEBePWsKbjQYcUf5LZxeEYnx2o3x9e8rknArkRyGg811WgdBx2X7QD+rXUQRImIyQZR/NsB\nYNDC0l2t7ta9bZ7tGsQzqb1Y54Y7FMF/lox9TbQ3HMHd+9vx/ZkZyBqhcNO3p2Vga7sP56ypwSed\nflxXbMN9Bzvw4+ii8K0dfnwuLxUGnYTL8tOwuyuAnpB2+WQYSsieZs7WLIBJLM/jKW1p6W7QOg4a\ns19JZRXsgkx0AtikiSjOVTpdSnmpYw2AqwD0K7f4+N66D+48e9ZCo0439rfgaUSrm3tQ6w1h2bpj\nbzxHFHV9xdIPqvGrOVm4ND+t3zF7uwJo9Idxp9yGOweMRvzXDhempBjw8llTUJhiwKtLC9EaCCPb\npMe9B9shbEacm2MFAHQHI0jVq+8BWfUSFADdoQisx7FAfTx5LLrWdJ2Up8nFJzlJkmCpabb5bCle\ni9nA0aP49qFUVvGm1kEQJSomG0SJYQeApQAcfTfWun3ura6u9WflZ5yvTViTz6/mZMMX7j+a8MCR\nTjT7w/jNnCw4zINfNuemm/Ds4vx+25oDYXz/k2b8ck4WFtrN/R7LNulx2BPEq/Vu/LPPcWkGCW1B\ndUp4WzAMCUCaRokGAIRsBu/oe9GJSpGUtOYD9XX586cWah0LjegXWgdAlMg4jYooAUTXbrwDtQxu\nP4/vqVvvC4U9sY8qcXUGw2jxqx8A4A0rR7/Pt+gxI83U78Nm0CFFL6lfR8vl/u1QB27d4QIApOh1\ng46ZmqIONk2xGFBiHTzw9H/72/DVYhuKUo49dlqGBa/UuVHVE8RTVV04xWY6rrK7481kHyKzonGV\nGwYMJZkAACAASURBVAoW1le3sBxu/HpTKqtYp3UQRImMyQZRgqh0ug4CODxwe2cgFFhb385Gf8fh\n9l0t+Pz6Onx+fR0CEeCZmu6j3zf5xlZspiUQRp3vxJoIr2ryoM4XGtQp/KZSO2xGHb6+pRGfdgXw\n67naLpdIt5uHX+1O4ya7taOwq5vlcONQEMCPtA6CKNFJisL1TkSJorzUkQ/gFgD95vkYdZLub8tO\nuSXdZOBiXhoXXgO6chbnDe5MSBOiU9K12OeXZOr1uuErDFCs3SOVVTDZIDpJHNkgSiCVTlcjgN0D\ntwcjSqTS2fyeBiHRJOVN1bOZXwzZlUhO48HGWq3joKNcACq0DoJoMmCyQZR43sCx5tNHvXLYtbfW\n7TukQTw0CenSTezhEmN5PT0lzc3d9VrHQQDUUrdMuInGAZMNogRT6XS5AWwDMKi19SO7a98IRZQT\nW0hA1Eeq3ZyqdQzJRpIkWGtddp8/1KN1LEluM4BHtQ6CaLJgskGUmN4G4B+4cV+7p31jY8daDeKh\nSSQEBNPTTFz/owGLhNSOA/VcLK4RRVEiAG6Ryio4skc0TphsECWgSqcrAOBDDPE7/PDu2vUd/uCg\njuNEY+Wx6lp1kjRo5Ixig+VwtSNJ0j+ksootWsdBNJkw2SBKXB8CGJRU+MOR8PMHGley0hydqFCa\nwad1DMkuu7WzsKvb1zb6njSOWsAGfkTjjskGUYKqdLoiAF7HEL/Hq2vbquR2z47YR0WTgSXDbNI6\nhmRnkGAIHa5HOBwZW+MXGg+3SWUVTPCIxhmTDaIEVul0OQHsxBCLxR/4tOYdXyjMhaZ03OzpbOYX\nD+yKksVyuDHzplRW8eR4n1QIMUsI8YYQYpMQYqsQ4q9CCPN4X+dECCHyhRAPncBxV0U/3yiE+NJJ\nxvDfQogNQogPhBAfCSFOPcnzvXYyx9PEYLJBlPheB+AduLHJG/CuqmldpUE8lMB6jOgwG/UpWsdB\nqryenpJmVxfL4U4gRVE6AXx7vM8rhNADeAnAH2VZPhPAGdGHfjPe1zoRsiw3yrL8neM5RghRCuCr\n0eOfkGX5lRO9vhDifACLACyVZXkZgF8B+OmJni8a0xdP5niaGAatAyCik1PpdAXKSx3vAPgSgH5T\nLp6RG3ac4bCXFaSaSzUJjhKOL9XQBSBD6zhIJUkSrHXNGT57So/FbLRqHc9kJEnSj6SyiroJOPVF\nAPbJsrwGAGRZVoQQPwUQAQAhxA8AXBvd91VZlu8SQjwBtaHg6QByAdwF4BsAcgCcD/V1/vzo9/MA\n/BLqzf8pAK4H0ATgRVmWz4heYwuAqwH8DkB99LxTo/u29e4rhLgIwB1Q/4Y8J8vyX4QQ1wO4Nbpt\ntyzL3wbwNwBnCiF+A/UN6xZZlu8XQvwRwGeg3lfeL8vyP4UQHwBYBeCCaLyXy7Jc3efnkwEgFYAe\nQEiW5dUAVkfjPjcaTxBADYBvATgbwG0A0qL7KbIs/z66/2oAPwDwvizLOUKIRQD+Hv1Zr5dl+SdC\niFMA3A+1T1U3gBsBeAA8DaAAgBnAb2VZfmvkf1Y6XhzZIJoEKp2ubQCcQz32j901K0KRSDC2EVGi\n0ttju1wjoii4f20d5t+xGX9b2/9+r6k7gJ+vOIzz792BU+/agssf+hTPbXUd1/lveWE/5t2xGXUd\nxypFH27x4iuP78bi/9uK7794AN5g/2URgVAElzywE6/ujI+ibhYJVpbDnTBvSWUVj03QuecA6Ld2\nTpZlryzLfiHENKg3u+dGP64RQsyI7haSZflCAJ8COFuW5c9Gv14efXwWgC8AuBPAz6EmIHciOuIw\nArMsy58DcC+Ar/duFEJIUG/MPw81YfisECIFaiJwiSzLnwEwRwixAMDdANb03uRHjz8PwPzofhcA\n+J0QwhZ9uCv6XCoBXDkgnrcAhAAcFkI8KIQoj8YCAPcB+KIsyxdATaC+HN2+AMDnADwG4LLo9bMA\n5MmyvLPPue8D8J1oTHlCiBIAf41uuxDAOwD+K3q+HFmWz4ueN2uUnyGdACYbRJPHKxiis/ieNk/b\nezVt72gQDyWgVLs5LVbXau8J4jvP7ccbu1uhG7DqKBRR8O1n98PZ6sO9V83Ea9+aj8+KTPz321V4\nZ9/Y1vCu2teGjw53Ddp+56pqzMtPxQvfOAUtniCe2dI/gXl0QyNyUo344oL4aTWSGwoV1lexHO54\nUhSlC+o75hN2Cajv2g9lEYANsiyHZFkOAfgIQFn0sU3Rzw0Atke/bgJgj369RZZlJfr4TlmWwwMe\nH8666OfaAfvmAvDJstwsy3JYluXLZFn2Qh35eE0IsQbAXADD/UKcAaB39MYDYA/UhGika0KWZb8s\nyxdBTUKqANwD4AkhRF70+JejoyPLARRGD/skelwNAEUIUQDgUgCvDohJ9CYfsix/XZblKgBnAvhH\n9JxfA5AHYB8AmxDin1ATpeeGeY50EphsEE0SlU5XG4CPMcTv9eN767ZUd3sPxD4qSiRBSfHbrMaY\nLQ5fsasVep2E579xCvQDso1P691o6PLjvy+dhlOL0lCSZcEPlhWhJMuMd/aN/ia/xx/GnauqccXC\nnH7bg+EINlV14z/Pyse07BRcWZaLjw53Hn28vtOPxzY04FefK0G8tRrJbuss7Ozytmodx2QRnT41\nkQvw90G9wT1KCGEWQsyHmoj0/Q9mQnR6FdR3+zHE19IYHh/4hpNxlHMB6jSpfn83hBAmqFOmrpFl\n+XwAGzG8sT6Xfr9QQgi9EMIoy/IWWZbvhDrF64vRY+pkWV4W/Vgsy/Ifo4cF+pziVaijG18E8OKA\nmIZqytgDYHn0nEtlWf6+LMs9AM4C8BDUkZ1HRniedIKYbBBNLu9CfTdqkL/sqHrNFwp7YhwPJRCP\nVR/TZn4XzM7E378yC+mWwcsHFxXZsOm20zEzd/BadcPAYZAh3Le2DlMzLbh0Xv9ZEe09IYQiCgrs\nakGgKXYTXN3HZhn+76pqXLEgB3Py4m95hEGCIXK4UQqFI6HR96ZRvC2VVTw6wddYBaBECHE5AAgh\ndFDXYFwDdcRiqRDCIIQwAFiCY6MYJ6ML6rQhSQiRD2DGaAfIstwKQC+EKIwetxKADep0rkYhRDHU\n0YveJGLgL+xmAMuizzEtes2xvLlVAeC3fb7PBdAYjQfRNRYQQtwqhFg4xPEvQ00QZsqyvG3AY3uE\nEEuixz8qhJgL4BMAl0S3XSuEuFAIcRqA62RZ/hDAd6GufaFxxmSDaBKJ9t54DUP8btd7/J6XDjW9\nHvuoKFFEbMaYru0pyjBDN8bcxhsM45GPG+DqDuL6Mxwj7run0YMXtzfjN5eUDHqs923f3qvqIEGJ\nbl13qBM7at249fzCQcfFi3REspoONk7EYuakEYPpUwAAWZYjUNcBfDu6UPtDAJ1QFyE7ATwMdfrR\nOgCPRKf6nOw126G+6bQZwB8w9gTmFqijA+sBvBe94V8lhNgMNSH4I9RpTnsBnCaEuKfPNT8EsFUI\nsRZqgvWz6HSq0dwBYEq09O17AB4HcEP0sZsAPC6EWAfgHADyEM9VBjAd6vqLgX4A4E9CiA8BtMuy\nvDe67RfRaWE3Qv3ZHAHwH9HrrIK6JoXGmcQuw0STT3mp4/MAlmJAdSoA+PXiGZfNy047PfZRUbzr\nEbaG3CxrgRbXXnTXFnxzaQH+67zBN/rL79uBZncQRZlm3HHZNJxWbBviDKqIouDaJ/bgnOl2fP/8\nImyq6sI3npHxzi0LUZhhRiAUwRl3b8VbtyzEFLsZr+5swas7W/DwV2fjin/swrfOnoKzSm349Uon\nDrZ4MTMnBX+4fBrybPHV57B1Sm6dw5Eev1lRfLtWKqt4XusgiJIFRzaIJqe3oC4YHOSeHc63uwIh\nzvumfhRFUezp5risxPLU1+bgXzfOxbnT7fjO8/uxwTl40XevZ7e40O0L4zufmTLk4yaDDqcWpeHV\nnS0IhCN4/dMWLClNxxMbGpFpNeKKBdm4a1UNZjtS8O73yjAjNwV3v1szUU/thKXWNWd6fUFOizx+\nDzPRIIotJhtEk1B0OtXzGGKRnDsYDj6+p+7liKIMtYCOklSPSddmMujjorPxQMWZFiyckoZffq4E\nn5lmx13vVg+5n6s7gL+urcNvLimB2TD8n7efXFiMZ7e6cPoft8IdCOPC2Rl45ONji8I3V3fj8vnZ\nMOgkXLEgGxurhk9utGKRYO06UN/J2QljF1GUXVCn0hBRDLGpH9EkVel0NZeXOt6DuiCu33Sqjxs7\n6hfnpa85uyBz+dBHU7Lx2fQeDF/aMuYOtXhxwOXFJaf0H2yZlZuCNQc7hjxm/ZEudPvD+M5z+49u\n670VL39gJ86YasNj18/BgilpWPODU9HeE0J2qhE/fOkgvrAgB3Oji8K7fCFYTWrFUqtJj05vfK7H\nzgmHptRXtVQVluYOXpxC/UQiilenk74slVX4tI6FKNkw2SCa3NYDmA1g0M3I33bWrJuebp2en2rm\njQrBkB5faxK217rx2zedmFdgRXGm5ej2/c3eYddPXDA7A69+c16/bbsaPPjVG048cM1slGQdO49O\nkpCdasT6I53YWtONN25ecPSxNLMebT1BlGRZ0OoJDlktK17ktncWdWaltdrTU+ImUYxHOp10i1RW\nsU/rOIiSEadREU1ilU6XAuAFAP6Bj4UVRbl725F/9wTD3bGPjOKNzW5Oj/U1O7whNLuDaHarRbB6\nguGj339uTiYK0k348SuHsLW6G1VtPjy+oQHvye245rTco+f4+euH8auVRwAA6RYDZjms/T4KM9SZ\nYaVZFhRl9J8lFgxHcMfb1fjR8qJ+CcWZU214ZrMLVW0+PLWpCUtKh1+QrjW9JOkjR1gOdySRiPJP\nqaziCa3jIEpWTDaIJrlKp8sDYAWG6GRb5/F7HttT+0JYUQZVraLkEZAUr81qyoj1dX/40kEsu28H\nlt23A4Gwgic2Nh39vssXxqPXCUyxm/G9Fw/gqkd3Y8WuVvzu86W4cUn+0XM0dAXQ0BUY4SrDe3JT\nE9JT9IMa/91+0VS0eIK46tHd6PKF8NPPTj2p5znR0pVIlusAy+EOJRyOHNTppO9qHQdRMmPpW6Ik\nUV7quBrAAgzuMIsb5045/ZKS3MtiHxXFg440XX3hgtyhyzdRwmgtyKlz5NlZDjcqElH8Op10plRW\nsVPrWIiSGUc2iJLHawCGXFn7xN76rXvb3OPRvZYSUMRmPLGhAYorqfUtLIfbh04nfYuJBpH2mGwQ\nJYlKpysI4GkAQ87tvmvrkTdavIH62EZF8SAlw2wZfS+KdxYJ1u4D9V2csQCEI5G7pbKKf2odBxEx\n2SBKKpVOVzPUEY5Bv/u+cCT85+3O532hcE/sIyOtRBRFsdvMrGQ0SWSHQwUNVS1VWsehJX8gtEqv\n0/1M6ziISMVkgyjJVDpdn0ItiTtowfjhLm/X03LDvyN8azRp9FikVqNeZ9Q6Dho/Oe2dRR2d3hat\n49CCzx86bDYZrpLKKti0lChOMNkgSk5vA3AO9cC7Na3OtXXtq2IbDmnFn2bkHP9JRi9Jehxp0IdC\nkaDWscRSMBTutpgNF0llFSznTRRHmGwQJaFo/42nAQx5o/ngrpqPuWA8ORjtJv4dmIRsUDKbDjYk\nzRqsSESJSJCukMoqDmsdCxH1xz8yREmq0unyA3gGwJDTDe7YcnhlTbfvYGyjoliz2c12rWOgiZHv\n85U0NXYmRf8NfyD0Q+Pp//2+1nEQ0WBMNoiSWKXTVQ/gTQyxfiMYUSK/33TwBVaomrx8OsWTZjHG\nvHM4xU5aY3OW1xd0ax3HROruCTxhXXLHX7WOg4iGxmSDKMlVOl1bAGzFEAlHdzAcvGPL4X91B0Lt\nsY+MJpo31cB/10nOAimle39d92St+dDl8b9vs5q+qXUcRDQ8JhtEBACvQ10wLg18oN7j99yzw/k0\nS+JOQunGsNYh0MTLjoQL6p3NTq3jGG+dbt/O9FTzpVJZBf8fE8UxJhtEhEqnKwLgKQCtQz2+p83T\n9sju2mdDEWXIhoCUmFLsbOaXLHLbu6Z2dPZMmnK4XW5/lV6nO1cqq/BpHQsRjYzJBhEBONph/FEM\nU6Hqw4aO2hcONLzIHhyTQxhK2J5mYjO/JKHXSTocadQHQ+GEL4fr7gk0e3yBs21L7+zSOhYiGh2T\nDSI6qtLp8gB4HEBgqMdfP9Isv1Pd8kZso6KJ4LFIbQa9zqB1HBQ7NiiZrgOJXQ7X6wt21TR1LZty\n4Z8T+nkQJRMmG0TUT6XT1QLgWQBDjmA8sbd+68cNHR/ENCgad8E0I9fgJKF8v7+kqbGjVus4TkQg\nGPYdqm2/9JQr/rZH61iIaOyYbBDRIJVO1xEAL2OIBeMAcO8nVWs2NnasjW1UNJ5MdvOg6mOUHGwN\nLdk93kBClcMNhSNB2dl67YKrHvhQ61iI6Pgw2SCiIVU6XZ8CeAfDvE7cs6Nq9aamznWxjYrGS7rd\nnKF1DKQNsySleA40uBNl/VU4EgnvO9Ly3YVXP/Ca1rEQ0fFjskFEw6p0uj4CsAFD9OAAgD9vd76/\nuamT7zQmGK8e3VazIU3rOEg7WZFQfsOR5iqt4xhNKBwJbd3T8L0FVz3wqNaxENGJYbJBRKOpBLAT\nw7xe/Gm7870tTZ0fxTYkOhneVH2H1jGQ9nI7uqa2d/Q0ax3HcELhSOjD7dX/b8n1jzyodSxEdOKY\nbBDRiCqdLgXAiwB2Y5jXjP/b7nx3q4sJR6KQ7MaI1jGQ9vQ6SSc5G43xWA43FIoE3/7o0E+X3/Tk\n/VrHQkQnh8kGEY0qmnC8AGAPhnnduHub891trq71MQ2MTkhqusWqdQwUH2xQMpoPNDRoHUdfwVA4\n+Nrqfb+67NZ/3aN1LER08phsENGYRBOO5wHsxTCvHX/cdmTVNlfXxzENjI5LCEoonc38qI88v39q\nU0N8lMMNBMOBV97f9/Orb/v3H7WOhYjGB5MNIhqzaMLxHIB9GD7heGcLF43HLU+KrlWvk/jaT/3Y\nGltzeryBbi1jCATD/lfe2/fTa37y4p+0jIOIxhf/4BDRcYkmHM8CkDH8Go733q1pfUtJkNKaySRs\nM3q1joHij1mCxXOg3qNVOVyfP+R96d29P7729hfv1eL6RDRxmGwQ0XGLJhz/gppwDFkW95HdtRtf\nOtT0UjiihGMaHI3IZDcZtY6B4lNWJKxJOdxuj7/j8Vd33Hzdz176W6yvTUQTT+Ibj0R0ospLHRKA\n6wDMATBkUnFhUVbpDXMLrzXpdeaYBkdD0p+e02Mx6blAnIYUUZSIu7SgJTMz1RGL6zW39zT+7bnN\n36148INXY3E9Ioo9jmwQ0QnrM6VqL4YZ4Xivts15746qx3uCYU3ngxPQY1A6mWjQSHSSpNNVNZqD\nwXBgoq9V3dB5qOKBNTcw0SCa3JhsENFJqXS6IlATjk0YJuHY2tzVdMeWw492+oMtMQ2O+vGlGrq0\njoHiXxpgbz7Q0DiR19hzqHnH7X959xt/e37TOxN5HSLSHqdREdG4KS91nA/gQgBDNo3LSzGl/HLx\njOscVlNRbCMjAOiYmlJVWJheonUclBiaHVk1+VMyi8f7vB9/UrPmzkc/+v6KNfLO8T43EcUfjmwQ\n0bipdLrWAHh9uMebvAHvLz7e/1RVt3d/DMOiqDS7OU3rGChxpDe15Xp6AuM2GhaJKMobaw+8euej\nH/0nEw2i5MGRDSIad+WlDgHgKxhmWpVOgvTjRaUXnu6wfya2kSWvIJRA+ll5Rp0kSVrHQomjTadv\nyp5f4tDpTu7/TSAY9j9bueuZl97d+/MVa2TXeMVHRPGPyQYRTYjyUkcxgOsBWIbb55pZ+Qsun+b4\ngkEnGWIXWXLqtEoNU8ocBVrHQYmn0ZbmLJyRV3qix7d3eZv/8vTGh7bva7xrxRrZPY6hEVECYLJB\nRBOmvNSRBeA/AQw7fWdJnr3g2/OLr0016tNjF1nyacszOYunZ5ZqHQclnoiiRLpLC1qyTqAc7qGa\ntn3/849197d2eB9esUYOTkR8RBTfmGwQ0YQqL3WkALgJQC6AIV9wClPNqT85fdpX8q3mqTENLol4\nZtvqHdnWKVrHQYnJA6nLMq/EbDLqx9QvJ6IoypotVR/c+/TGhyKK8u8Va+Qhi0YQ0eTHZIOIJlx5\nqcMA4BqM0PzPqJN0P15UevGpuelLYhpcElAUBcbFuT6zUT/slDai0bhM5uqCU4pGfUPAHwj5nlqx\n8+UVa/Y/BeCdFWtk3mgQJTEmG0QUE9Fu48sBnI9hRjiA3nUcuZcbdDpjzIKb5DxGtDvOyMvUOg5K\nfM25WTX5hcOXw23r9LrufmL9M7sPNT+2Yo28K5axEVF8YrJBRDFVXuqYB+BLAIZdFH5abrrj5gXF\n16SbDFmxi2zyasswVBfPzeYUNTppAQX+iCj2p1pNg9ZY7a9q3f0/D697uqPb9xgrThFRLyYbRBRz\n5aUOB4D/AGDHMKMcdpPB9P9OLSmfk5V2akyDm4Q6S6zVU6bYmGzQuGjX6Zuy+pTDDYUiwTc/PPD2\nIy9vfxHAsyvWyAGNQySiOMJkg4g0UV7qMAG4FsAsDLOOAwCumpF3yhemOy4363Vcb3CCwgsz29NT\nTZxGReOmMS3NWTgzr7St0+v6y9MbX9ohN74KYBXXZxDRQEw2iEgzfdZxLAMwbLWaaekp6d8vK/lS\nQaq5NEahTRpBSfHZl+RZ2MuPxlNEUSJbIoaP7nth6/seb/BFrs8gouEw2SAizZWXOmYDuBqAabh9\ndBKkm+cXn33OlMwLdJKki110ia0jVVdfuDCXJW9p3HiDYc9z2+pee31302YAT69YI7doHRMRxS8m\nG0QUF8pLHWlQp1WVYIRpVWfm2QtuOqXoKrvZkB2z4BJYW4G5qrg0o0TrOGhycLb1yHe/f3BlfZd/\nA4BXV6yRQ1rHRETxjckGEcWN6LSq86BOrRpWmlFv/H+nln5uXnba6bGJLHH1zElvyM1MKdA6Dkps\n/lA4+Pa+5rcf31SzEcDKFWvkHVrHRESJgckGEcWd8lJHAdQmgFkYYS3HZaW5s740w3FpqtFgj1lw\nCURRFMV8piNoNOiGnZ5GNBpns3v/ve/se+eIO9guGQ33rFgjt2sdExElDiYbRAlCCFEK4FMAW/ts\n7gDwiSzLv52ga94IoFOW5VeGefwDAN+T5fFfHFpe6tAD+AKARRgh4bCbDKabFxQvL8uxLdFxFXQ/\nbhNa807P43QzOiHeQMjz2rbayuc2OPcA+AjAqpXba3nTQETHZdimWkQUl2RZlpfF8GJPxOpaA1U6\nXWEAr5SXOmQAXwRgHmq/zkAocNfWI28vybPv/PrcKZdnW0ycMhTlTzN4ADDZoOO2u65j+1/e2ruq\nudvfBODFldtrq7WOiYgSE5MNogQmhFgGdWThaiHEQQCvAvgM1BGPSwFMAfDP6O5GADfIsnxomH3T\nATwT/dwJdbH2bQBaADwI4EkARQBSAfxOluWVfeJYBODvAPzRj2tkWe4Yj+dY6XTtKS91HInGMx3D\nLB7f2NTZsMXV9Y+b5hUuOXdK5nKjjlOHDPak/xHQceryBtv+tf7Iyrc+ra8G8AmAV1dur+UicCI6\nYSwfSTR5TAfwlCzLSwFkAlgIoADA72VZXg7gMQC3jLDvbQDelmX5XADvAfhsn3NnAXhHluXzAXwF\nQMWAa38DwN+joy53AcgfzydW6XR5ATwBoBLAsDc+YUVRHt5Vu+F3Gw/+varbu388Y0hE6XYL17LQ\nmEQiSmTToZaPvvvExofe+rR+J4CnVm6vfZGJBhGdLI5sECUWEV0n0WtVn6+7ZFneGf26FoAdwGEA\n9wkhKqAmFVtH2Pc0AL8GAFmW74le7NToPu0AFgshvg11/cTAqTmvAXhACDEbwPOyLO87qWc5hEqn\nSwGwvrzU8QmAKwHMxjCjHIc6vZ23f7T/2Stn5M29rDS33GrU28Y7nnjn16EnK8XIZINGVd/e43xi\n3aG3Nh1udQHYBOBtJhlENF6YbBAlln5rNqLTqBZFvx14cyAB+D3U0YoHhRBXA7hshH3DGH608zqo\noxvnRj9vGRDUe0KIxdHzPymEuE2W5dXH8bzGrNLp8gD4Z3mpYx6AzwNIAzDkotWXDzXtXV3bevib\n84rOLctJX2LQSUnzmtdj1bVnAVat46D41eUNtr22rWbVS5urDwBohDplqk7ruIhockmaP7xESSoH\nwCEhhAR1kbV+hH03A7gAwGYhxHcA+Aac54gsyxEhxJUY0OlbCPE9AG/IsvxM9FqLAExIstGr0una\nXV7q2A+gHMDpGCbhaPeH/Hdvc747w56y+ca5hRfOtFsXJEPRKiXdGNQ6BopP/lDYt052rX3kgwOb\nfMFIEMBaAGtYaYqIJgKTDaLJ7SEAfwXgjH5+WAhx8TD73gvgqeg0rW6ooxk/jj72EoDXhRBnQV37\nUSuE+E2fYw8C+LcQohPqAvFvjPPzGFKl0xUE8Hp5qWMb1GQqHyNMrfr1hoMvL8mzf3zt7IKLC1LN\npbGIUStWuzlF6xgovkQiSmRnbfvWh94/8EFDh9cP9XXh5ZXba9k3g4gmDPtsENGk0Kf7+HkYeQQH\ngNoQ8LJpuRdlmI25Ex5cjEUUJZKyxBE26HVGrWOh+FDd6jn42JqDb++obm8D4IZaBGIbRzOIaKIx\n2SCiSaW81JEOtZTvXIzQDBAA9JIk/cecgtOWFWYtSzHo02ISYAx0m6WW/NMcOVrHQdpzdfnqXt9W\ns3rljrpDUH8fNgF4lwvAiShWmGwQ0aRUXuooBnAJgKkYZmpVL7vJYLpxbuHS0x3pS0163ZDNAxNJ\na7ahaurs7BKt4yDtuLp8dSt31K55fVvtAaiFH/YAWLlye61b49CIKMkw2SCiSa281DEfas+QbIyS\ndGSaDebrxJTFix3pSy0GfcJWcuqenlqTn5dWrHUcFHsDkgw9gBoAb67cXlurcWhElKSYbBDRgzE2\n4QAAC9lJREFUpBddz3E21PUcFgxTuapXmlFv/OrsgtOW5md8JiF7dCzK6kq1GNO1DoNiZ4iRjE6o\n6zI+4boMItISkw0iShrlpQ4jgIsAnIHhe4ocZdbr9NfOyi87Z0rmOTaTIXPCAxwHPp3izl6SP2nW\nn9DIhkgyvAA2Qi1lO+JIHhFRLDDZIKKkU17qSIPaEHAeRhnlANSF5F+emTd/WVHWufFevardpqst\nmp9bpHUcNHEiiqI4m91y5c76Dat2NVThWJKxGcAHXPxNRPGEyQYRJa3yUocd6nqOBWPZXwLwxemO\nOecXZi2J1z4d7UWWqqJiOxeHT0KBUNj/aU3H9n9vqtq4r6GrA8eSjE1QRzKYZBBR3GGyQURJr7zU\nYYWadJwKdVHtqC+MC7PTci6b5lg8JzO1LJ4qWPnn2V1Z6RaH1nHQ+OnyBts+PtC88V8bjuzo7AkG\nwCSDiBIIkw0ioqjyUocZwAUATgNgwhiSDptRb7xyRt6CM/Pti7MtpvyJjnEkYSjh1CUO6HW6UZsa\nUvyrbes5/O7uho2vba3ZH/2PyCSDiBIOkw0iogGiC8nPh7qQ3IpRmgP2Oqcgo+iiqTlnzLBb5xl0\nkmEiYxxKl1lyFZzm4KhGAuvxh7p31XXsfHNH3Y4d1e0t0c16AC0AtgLYwCSDiBIJkw0iomGUlzoM\nAJYCOB1ADoAx3eTlpZhSvjQjb9GpubZTY7mgvC3XWFU8M4vrNRJMKBwJHWl2y2tl147KT+oOhSJH\n/zAbABwC8DEAmSVsiSgRMdkgIhpFtE/HTABLAMzGGEc6AOD03PS85UVZ8+dkpc5PMxoyJipGAOie\nmVabn5vKSlQJwtXlq9t8uGXHK1trdrV0+33RzRLU5pO7oU6Vahn+DERE8Y/JBhHRcSgvdaRCbQ64\nAIANo3Ql7+vcKZlF507JXDArwzovxaBPHe/YdKdne1JMhnE/L40fty/Yubuu89M3dtTu2FnT0drn\nIQOADgDbAXy4cnutX5sIiYjGF5MNIqITUF7q0AFYCHVdRynGOMUKUPt2XFicNW1pfsb8GXbrXJNe\nZznZeLx6dOWcmceu4XGoze137W3o3Ltun2vfhkMtjX0ekqIfBwB8AuBTTpUiosmGyQYR0UkqL3Xk\nADgXwBwAqTiOxMOi1+kvnpo9sywnfVZpesqsVKP+hBKGdru+puiUnOITOZbGV0RRFFeXr3Z3bce+\n93Y37t1T39k+YBcDgEYAewCsX7m91jf4LEREkwOTDSKicRId7ZgLdYrVTABmHMc0KwA4NceWe1Z+\nxqzZmdaZeVbzVL0kjamMbXtxSlVRUToXh2skFI6E6ju8zp3V7fve/rR+X01bj2fALgYAbgD7oFaU\nahx8FiKiyYfJBhHRBCgvdeihTrOaD2A61PKlY15YDgB2k8G0rDBr2sIc26zSdMvMVKPBPty+gfkZ\nLZk2c85JBU1jFokokeZuX/3hZveRHVVth9fuc9V4g+GBiaUe6ijXEahrMXav3F57XP8HiIgSHZMN\nIqIJVl7qMEFtFHgK1PUdCsbQMHCgshxb7pI8+4xp9pSpeVZzqdWgTwGAEJSgbUmeXqeTdOMZNx0T\nURSlzR1ocra4j+ysaT+yZl9TVbSb90AGAD1QE4z9AHau3F4bjGmwRERxhMkGEVEMlZc6UgAsBjAN\nQDEAC45jjcdRZl3BvLx0/2mZaVMLs6w5pywumG23mnJ0kiSNb8TJKRSOhFrd/obatp46uaGres2+\nJmdTl887zO5GAF1Qe2LsAbCPIxhERComG0REGolOtZoFQAAoAZAHNfEY9YVZsurzdWZ9v3n/Wakm\n85nTc6bMLbQXTc1OLcy1mfNTzQY784+RhSNKuN3jdzV1+hqdLe76T2s6arc6W13BsDJcwiBBTTCa\noSYYOwFUsZIUEdFgTDaIiOJEeakjHcAiqInHVIww6qFLMxRKRl3daOe0W42msuLM3Jl5NkdhptWR\nZ7c4slLNuVazwTauwSeAiKIobl+oo6Mn0NrS7W+tafM07a3rbNhW1eYKhCKjjUSYoPbBqAVQDbVM\nbeeEB01ElOCYbBARxaHoqMdMqKMeUwDkQ303PQgJNl260STppNaRzjGSXJvZsqA40zHDkebIt6dk\n2a0me3qK0Z5mMdgtRn1qIk/H6vGHujt6Aq2tbn+rq8vXWtvW03rI1d26r6GrfQxJRS8TgG4AdQBq\nAHwKoJWjF0REx4fJBhFRAogmH9MAzIRBOlWXZtBLkpQKIIgTWGw+EpNBp5uem5ZenJ1qz7db7Dk2\niz0r1WS3WYw2i1FvMRt1FpNBbzEZdBajXmcaz2sPJxJRIr5g2NMTCLk9/pDb7Qu5u7zB7g5vwN3u\nDribu33uxk6fu7rV0+3xh453DYwO6sLudgBNABoA7AbQwOSCiOjkMNkgIkpAly0qkgBkQO3rUQB1\nvUcOgBSoCUhMFigb9ZIux2axZKWaLBlWkyXdarTYzEazQS/pdZIk6XSSTidB0kmSpJMknSRB0ukk\nSQdJ0umgC0WUsD8YCfqC4aA3EA54A6GgNxgOevyhgMcXCnb7ggG3PxTs9gaD4/TXqjex6Abgin7U\nA5BXbq91j88liIioF5MNIqJJIpqA2AHMAJALIBtAVvTDAiCAcR4FiWP66IcP6lqLDgCtUEctDqzc\nXtutYWxEREmDyQYR0SR32aIiHdSEYzrU0Y8MALboRxrUTucK1GQkkRihJhR+AJ04llR0QJ0OVQ3A\nzalQRETaYbJBRJTEoqMhqQAcUKdi9U1CehOR3g8D1Jt7HdQqWWMq0ztGvefVR7+PQJ0O1jPgwx39\n7IE6UtECoGvl9tqB3buJiCgOMNkgIqIxuWxRkRHqdKwUAOlQp2ylQK3cpIfaf6K3i3nv19KAjwjU\nJCWIYwlLAIAXxxIKX3RbD0cliIgSG5MNIiIiIiKaELrRdyEiIiIiIjp+TDaIiIiIiGhCMNkgIiIi\nIqIJwWSDiIiIiIgmBJMNIiIiIiKaEAatAyAiIopXQohSAC/KsnxGn22/A9Aiy/L9x3muFlmWc4QQ\nCwH4ZFneL4T4AMD3ZFneNcJxiwH8EWrZYROA1wH8XpZllpMkorjHkQ0iIqLYuhLA7LHsKIRIB/AM\ngFtlWV4K4CwApwL45sSFR0Q0fjiyQUREdIKEEP8F4DqozQpflWX5T0KIIgD/jO5iBHCDLMuHovsv\nAHAzgGYhhCu6z1eEEPcCyAbwBVmWq/tc4rroeXcBgCzLQSHE1wH0CCEMAJ4EUAS1C/zvZFleGR0t\n6R0p+TmAxwFkQv2bf6ssyzvH/QdBRDQMjmwQERGNTAghPuj9AHBjdOM0AFcDOAfAeQCuEkJMBVAA\ndZrTcgCPAbil90SyLH8K4C0AP5dleVN0s0uW5QsBVEId9ehrDoAdfTfIstwty3IYQBaAd2RZPh/A\nVwBU9NltlyzL3wPwQwBvRc//XQB/OqmfBBHRceLIBhER0chkWZaX9X4TXbMBAGcCmAVgdfR7G4BS\nAEcA3CeEqIA6orB1lPN/GP1cB3V0oy8FgH6Y49oBLBZCfBvqyErfY3sTmbMB5Aoh/iP6vXWUWIiI\nxhWTDSIiohMTAPCGLMvf6btRCPE4gLdlWX5QCHE1gMtGOU+oz9fSgMf2QU1qeqdlQQiRA3Xa1DKo\noxvnRj9vGRBb7+dbZVn+eCxPiIhovHEaFRER0YnZCmC5EMIqhJCEEPcKIVIA5AA4JISQAHwRagWp\nviIY+5t9zwC4VAhxJgAIIUwAHgTw2eh1jsiyHIE6/WrgdQBgI4AroseeIoT40XE9QyKik8Rkg4iI\n6AREF3L/BcBaABsANMqy7AXwEIC/Ql2D8RyA84UQF/c5dB3UaVYXjuEabgDlAP4ohNgI4AMAq2VZ\nfhTASwAuF0K8B8ADoFYI8ZsBp/grgJlCiHUAHonGSkQUM5KisEw3ERERERGNP45sEBERERHRhGCy\nQUREREREE4LJBhERERERTQgmG0RERERENCGYbBARERER0YRgskFERERERBOCyQYREREREU0IJhtE\nRERERDQhmGwQEREREdGE+P+jDOA8BHpIgQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "CGmqV66iFLef",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 597
        },
        "outputId": "e180e08e-ab34-4712-d031-12b2aa651ed0"
      },
      "cell_type": "code",
      "source": [
        "_ = sector_marcap.plot(kind='bar', color='orange', alpha=0.7)"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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SJEkNmpprhyRbAWcAPwc8AHgL8CXgg8DmwA3AC6pqVZKjgOOAtcBpVXV6ki36738EcBdw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\nT/KAqjp1sOIG5tGReflRVf3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YS1nyeG5zfQLwbco+koiYuD1tv0DSfzfX7wMuozSdm7IG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\nWvYjpvGmAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "R5eV24OiFPP4",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "# 섹터별 팩터 분석"
      ]
    },
    {
      "metadata": {
        "id": "RmTQ2_uDFOMv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "outputId": "4a7c3013-4d7d-46e9-d229-89ff428268ad"
      },
      "cell_type": "code",
      "source": [
        "sp500.groupby('Sector').describe()['PER'].sort_values('mean', ascending=False)"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sector</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Consumer Discretionary</th>\n",
              "      <td>59.00</td>\n",
              "      <td>206.37</td>\n",
              "      <td>1409.70</td>\n",
              "      <td>6.53</td>\n",
              "      <td>13.05</td>\n",
              "      <td>19.56</td>\n",
              "      <td>24.12</td>\n",
              "      <td>10850.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Health Care</th>\n",
              "      <td>55.00</td>\n",
              "      <td>68.62</td>\n",
              "      <td>231.75</td>\n",
              "      <td>9.27</td>\n",
              "      <td>18.70</td>\n",
              "      <td>31.45</td>\n",
              "      <td>48.61</td>\n",
              "      <td>1742.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Real Estate</th>\n",
              "      <td>31.00</td>\n",
              "      <td>64.36</td>\n",
              "      <td>101.03</td>\n",
              "      <td>11.59</td>\n",
              "      <td>27.59</td>\n",
              "      <td>40.92</td>\n",
              "      <td>64.25</td>\n",
              "      <td>588.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Information Technology</th>\n",
              "      <td>65.00</td>\n",
              "      <td>43.77</td>\n",
              "      <td>59.38</td>\n",
              "      <td>3.66</td>\n",
              "      <td>17.97</td>\n",
              "      <td>27.02</td>\n",
              "      <td>42.35</td>\n",
              "      <td>424.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Communication Services</th>\n",
              "      <td>23.00</td>\n",
              "      <td>27.80</td>\n",
              "      <td>29.96</td>\n",
              "      <td>5.22</td>\n",
              "      <td>11.89</td>\n",
              "      <td>20.97</td>\n",
              "      <td>29.73</td>\n",
              "      <td>144.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Energy</th>\n",
              "      <td>23.00</td>\n",
              "      <td>24.07</td>\n",
              "      <td>27.03</td>\n",
              "      <td>8.23</td>\n",
              "      <td>12.24</td>\n",
              "      <td>16.36</td>\n",
              "      <td>26.02</td>\n",
              "      <td>140.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Utilities</th>\n",
              "      <td>26.00</td>\n",
              "      <td>23.94</td>\n",
              "      <td>6.89</td>\n",
              "      <td>11.86</td>\n",
              "      <td>20.61</td>\n",
              "      <td>22.81</td>\n",
              "      <td>25.65</td>\n",
              "      <td>41.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Materials</th>\n",
              "      <td>26.00</td>\n",
              "      <td>22.88</td>\n",
              "      <td>11.92</td>\n",
              "      <td>7.35</td>\n",
              "      <td>12.62</td>\n",
              "      <td>22.21</td>\n",
              "      <td>29.81</td>\n",
              "      <td>56.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Consumer Staples</th>\n",
              "      <td>30.00</td>\n",
              "      <td>22.62</td>\n",
              "      <td>8.56</td>\n",
              "      <td>7.26</td>\n",
              "      <td>14.89</td>\n",
              "      <td>22.23</td>\n",
              "      <td>28.85</td>\n",
              "      <td>43.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Industrials</th>\n",
              "      <td>68.00</td>\n",
              "      <td>21.89</td>\n",
              "      <td>10.06</td>\n",
              "      <td>8.87</td>\n",
              "      <td>16.29</td>\n",
              "      <td>20.30</td>\n",
              "      <td>24.45</td>\n",
              "      <td>57.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Financials</th>\n",
              "      <td>68.00</td>\n",
              "      <td>18.87</td>\n",
              "      <td>18.12</td>\n",
              "      <td>5.31</td>\n",
              "      <td>10.57</td>\n",
              "      <td>12.83</td>\n",
              "      <td>21.20</td>\n",
              "      <td>125.42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        count   mean     std   min   25%   50%   75%      max\n",
              "Sector                                                                       \n",
              "Consumer Discretionary  59.00 206.37 1409.70  6.53 13.05 19.56 24.12 10850.00\n",
              "Health Care             55.00  68.62  231.75  9.27 18.70 31.45 48.61  1742.99\n",
              "Real Estate             31.00  64.36  101.03 11.59 27.59 40.92 64.25   588.80\n",
              "Information Technology  65.00  43.77   59.38  3.66 17.97 27.02 42.35   424.66\n",
              "Communication Services  23.00  27.80   29.96  5.22 11.89 20.97 29.73   144.23\n",
              "Energy                  23.00  24.07   27.03  8.23 12.24 16.36 26.02   140.20\n",
              "Utilities               26.00  23.94    6.89 11.86 20.61 22.81 25.65    41.60\n",
              "Materials               26.00  22.88   11.92  7.35 12.62 22.21 29.81    56.09\n",
              "Consumer Staples        30.00  22.62    8.56  7.26 14.89 22.23 28.85    43.99\n",
              "Industrials             68.00  21.89   10.06  8.87 16.29 20.30 24.45    57.71\n",
              "Financials              68.00  18.87   18.12  5.31 10.57 12.83 21.20   125.42"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "metadata": {
        "id": "nvcWDRNJFUO7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "outputId": "a28976ba-e259-4639-affa-b4ab39a4b63f"
      },
      "cell_type": "code",
      "source": [
        "sp500[sp500['Sector']=='Consumer Discretionary'].sort_values(by='PER', ascending=False)[:10]"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Symbol</th>\n",
              "      <th>Name</th>\n",
              "      <th>Sector</th>\n",
              "      <th>Industry</th>\n",
              "      <th>MarCap</th>\n",
              "      <th>Dividend</th>\n",
              "      <th>PER</th>\n",
              "      <th>PBR</th>\n",
              "      <th>Beta</th>\n",
              "      <th>ROE</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>457</th>\n",
              "      <td>UAA</td>\n",
              "      <td>Under Armour Class A</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Apparel, Accessories &amp; Luxury Goods</td>\n",
              "      <td>9260000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>10850.00</td>\n",
              "      <td>4.80</td>\n",
              "      <td>0.43</td>\n",
              "      <td>-2.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>109</th>\n",
              "      <td>CMG</td>\n",
              "      <td>Chipotle Mexican Grill</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Restaurants</td>\n",
              "      <td>18650000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>110.20</td>\n",
              "      <td>12.91</td>\n",
              "      <td>0.65</td>\n",
              "      <td>12.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>AMZN</td>\n",
              "      <td>Amazon.com Inc.</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Internet &amp; Direct Marketing Retail</td>\n",
              "      <td>879980000000.00</td>\n",
              "      <td>nan</td>\n",
              "      <td>91.72</td>\n",
              "      <td>20.47</td>\n",
              "      <td>1.63</td>\n",
              "      <td>27.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>496</th>\n",
              "      <td>WYNN</td>\n",
              "      <td>Wynn Resorts Ltd</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Casinos &amp; Gaming</td>\n",
              "      <td>13020000000.00</td>\n",
              "      <td>2.48</td>\n",
              "      <td>77.26</td>\n",
              "      <td>6.41</td>\n",
              "      <td>1.68</td>\n",
              "      <td>36.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>185</th>\n",
              "      <td>EXPE</td>\n",
              "      <td>Expedia Group</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Internet &amp; Direct Marketing Retail</td>\n",
              "      <td>18150000000.00</td>\n",
              "      <td>1.03</td>\n",
              "      <td>46.94</td>\n",
              "      <td>4.49</td>\n",
              "      <td>0.95</td>\n",
              "      <td>9.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>228</th>\n",
              "      <td>HAS</td>\n",
              "      <td>Hasbro Inc.</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Leisure Products</td>\n",
              "      <td>10670000000.00</td>\n",
              "      <td>3.20</td>\n",
              "      <td>41.71</td>\n",
              "      <td>6.13</td>\n",
              "      <td>0.90</td>\n",
              "      <td>12.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>345</th>\n",
              "      <td>NKE</td>\n",
              "      <td>Nike</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Apparel, Accessories &amp; Luxury Goods</td>\n",
              "      <td>138620000000.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>34.25</td>\n",
              "      <td>15.94</td>\n",
              "      <td>0.67</td>\n",
              "      <td>23.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>319</th>\n",
              "      <td>MGM</td>\n",
              "      <td>MGM Resorts International</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Casinos &amp; Gaming</td>\n",
              "      <td>14680000000.00</td>\n",
              "      <td>1.93</td>\n",
              "      <td>33.84</td>\n",
              "      <td>2.18</td>\n",
              "      <td>1.41</td>\n",
              "      <td>6.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>236</th>\n",
              "      <td>HLT</td>\n",
              "      <td>Hilton Worldwide Holdings Inc</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Hotels, Resorts &amp; Cruise Lines</td>\n",
              "      <td>24900000000.00</td>\n",
              "      <td>0.70</td>\n",
              "      <td>33.59</td>\n",
              "      <td>45.63</td>\n",
              "      <td>1.17</td>\n",
              "      <td>89.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>423</th>\n",
              "      <td>SBUX</td>\n",
              "      <td>Starbucks Corp.</td>\n",
              "      <td>Consumer Discretionary</td>\n",
              "      <td>Restaurants</td>\n",
              "      <td>89950000000.00</td>\n",
              "      <td>1.99</td>\n",
              "      <td>31.82</td>\n",
              "      <td>nan</td>\n",
              "      <td>0.49</td>\n",
              "      <td>173.40</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    Symbol                           Name                  Sector  \\\n",
              "457    UAA           Under Armour Class A  Consumer Discretionary   \n",
              "109    CMG         Chipotle Mexican Grill  Consumer Discretionary   \n",
              "28    AMZN                Amazon.com Inc.  Consumer Discretionary   \n",
              "496   WYNN               Wynn Resorts Ltd  Consumer Discretionary   \n",
              "185   EXPE                  Expedia Group  Consumer Discretionary   \n",
              "228    HAS                    Hasbro Inc.  Consumer Discretionary   \n",
              "345    NKE                           Nike  Consumer Discretionary   \n",
              "319    MGM      MGM Resorts International  Consumer Discretionary   \n",
              "236    HLT  Hilton Worldwide Holdings Inc  Consumer Discretionary   \n",
              "423   SBUX                Starbucks Corp.  Consumer Discretionary   \n",
              "\n",
              "                                Industry          MarCap  Dividend      PER  \\\n",
              "457  Apparel, Accessories & Luxury Goods   9260000000.00       nan 10850.00   \n",
              "109                          Restaurants  18650000000.00       nan   110.20   \n",
              "28    Internet & Direct Marketing Retail 879980000000.00       nan    91.72   \n",
              "496                     Casinos & Gaming  13020000000.00      2.48    77.26   \n",
              "185   Internet & Direct Marketing Retail  18150000000.00      1.03    46.94   \n",
              "228                     Leisure Products  10670000000.00      3.20    41.71   \n",
              "345  Apparel, Accessories & Luxury Goods 138620000000.00      1.00    34.25   \n",
              "319                     Casinos & Gaming  14680000000.00      1.93    33.84   \n",
              "236       Hotels, Resorts & Cruise Lines  24900000000.00      0.70    33.59   \n",
              "423                          Restaurants  89950000000.00      1.99    31.82   \n",
              "\n",
              "      PBR  Beta    ROE  \n",
              "457  4.80  0.43  -2.30  \n",
              "109 12.91  0.65  12.50  \n",
              "28  20.47  1.63  27.00  \n",
              "496  6.41  1.68  36.60  \n",
              "185  4.49  0.95   9.80  \n",
              "228  6.13  0.90  12.60  \n",
              "345 15.94  0.67  23.10  \n",
              "319  2.18  1.41   6.50  \n",
              "236 45.63  1.17  89.30  \n",
              "423   nan  0.49 173.40  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "metadata": {
        "id": "rp-ZRAV9FbZV",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Outlier : UAA(언더 아머) - 스포츠 용품 브랜드, 기어라는 기능성 소재로 유명"
      ]
    },
    {
      "metadata": {
        "id": "OU9-nUF5GJM8",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "outputId": "1c59c060-fd25-4f72-ef53-2aa82a9a5649"
      },
      "cell_type": "code",
      "source": [
        "sp500.groupby('Sector').describe()['PBR'].sort_values('mean', ascending=False)"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sector</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Industrials</th>\n",
              "      <td>67.00</td>\n",
              "      <td>15.71</td>\n",
              "      <td>76.84</td>\n",
              "      <td>1.56</td>\n",
              "      <td>2.81</td>\n",
              "      <td>4.45</td>\n",
              "      <td>6.50</td>\n",
              "      <td>631.69</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Consumer Discretionary</th>\n",
              "      <td>58.00</td>\n",
              "      <td>10.21</td>\n",
              "      <td>24.10</td>\n",
              "      <td>0.96</td>\n",
              "      <td>2.19</td>\n",
              "      <td>4.18</td>\n",
              "      <td>6.88</td>\n",
              "      <td>163.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Information Technology</th>\n",
              "      <td>61.00</td>\n",
              "      <td>8.05</td>\n",
              "      <td>5.98</td>\n",
              "      <td>1.23</td>\n",
              "      <td>3.64</td>\n",
              "      <td>6.57</td>\n",
              "      <td>11.79</td>\n",
              "      <td>24.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Consumer Staples</th>\n",
              "      <td>29.00</td>\n",
              "      <td>6.96</td>\n",
              "      <td>6.27</td>\n",
              "      <td>0.61</td>\n",
              "      <td>2.35</td>\n",
              "      <td>4.83</td>\n",
              "      <td>8.97</td>\n",
              "      <td>27.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Health Care</th>\n",
              "      <td>59.00</td>\n",
              "      <td>6.17</td>\n",
              "      <td>5.53</td>\n",
              "      <td>0.79</td>\n",
              "      <td>2.67</td>\n",
              "      <td>4.28</td>\n",
              "      <td>7.43</td>\n",
              "      <td>30.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Financials</th>\n",
              "      <td>68.00</td>\n",
              "      <td>4.87</td>\n",
              "      <td>14.24</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.09</td>\n",
              "      <td>1.52</td>\n",
              "      <td>2.24</td>\n",
              "      <td>83.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Communication Services</th>\n",
              "      <td>26.00</td>\n",
              "      <td>4.39</td>\n",
              "      <td>5.82</td>\n",
              "      <td>0.65</td>\n",
              "      <td>1.85</td>\n",
              "      <td>3.25</td>\n",
              "      <td>4.88</td>\n",
              "      <td>31.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Real Estate</th>\n",
              "      <td>30.00</td>\n",
              "      <td>4.09</td>\n",
              "      <td>3.67</td>\n",
              "      <td>1.34</td>\n",
              "      <td>2.10</td>\n",
              "      <td>2.79</td>\n",
              "      <td>4.48</td>\n",
              "      <td>16.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Materials</th>\n",
              "      <td>25.00</td>\n",
              "      <td>3.76</td>\n",
              "      <td>2.66</td>\n",
              "      <td>0.84</td>\n",
              "      <td>1.91</td>\n",
              "      <td>2.98</td>\n",
              "      <td>4.52</td>\n",
              "      <td>10.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Utilities</th>\n",
              "      <td>27.00</td>\n",
              "      <td>2.30</td>\n",
              "      <td>0.56</td>\n",
              "      <td>1.45</td>\n",
              "      <td>2.01</td>\n",
              "      <td>2.18</td>\n",
              "      <td>2.45</td>\n",
              "      <td>3.79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Energy</th>\n",
              "      <td>29.00</td>\n",
              "      <td>1.92</td>\n",
              "      <td>1.04</td>\n",
              "      <td>0.38</td>\n",
              "      <td>1.27</td>\n",
              "      <td>1.70</td>\n",
              "      <td>2.38</td>\n",
              "      <td>5.48</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        count  mean   std  min  25%  50%   75%    max\n",
              "Sector                                                               \n",
              "Industrials             67.00 15.71 76.84 1.56 2.81 4.45  6.50 631.69\n",
              "Consumer Discretionary  58.00 10.21 24.10 0.96 2.19 4.18  6.88 163.77\n",
              "Information Technology  61.00  8.05  5.98 1.23 3.64 6.57 11.79  24.68\n",
              "Consumer Staples        29.00  6.96  6.27 0.61 2.35 4.83  8.97  27.30\n",
              "Health Care             59.00  6.17  5.53 0.79 2.67 4.28  7.43  30.88\n",
              "Financials              68.00  4.87 14.24 0.00 1.09 1.52  2.24  83.24\n",
              "Communication Services  26.00  4.39  5.82 0.65 1.85 3.25  4.88  31.49\n",
              "Real Estate             30.00  4.09  3.67 1.34 2.10 2.79  4.48  16.94\n",
              "Materials               25.00  3.76  2.66 0.84 1.91 2.98  4.52  10.76\n",
              "Utilities               27.00  2.30  0.56 1.45 2.01 2.18  2.45   3.79\n",
              "Energy                  29.00  1.92  1.04 0.38 1.27 1.70  2.38   5.48"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "metadata": {
        "id": "JeU3x3HHGM3E",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "outputId": "50693618-275f-4686-a555-f5d423d1a7de"
      },
      "cell_type": "code",
      "source": [
        "sp500.groupby('Sector').describe()['ROE'].sort_values('mean', ascending=False)"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sector</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Consumer Discretionary</th>\n",
              "      <td>63.00</td>\n",
              "      <td>45.42</td>\n",
              "      <td>133.93</td>\n",
              "      <td>-100.30</td>\n",
              "      <td>12.35</td>\n",
              "      <td>22.80</td>\n",
              "      <td>34.75</td>\n",
              "      <td>805.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Industrials</th>\n",
              "      <td>68.00</td>\n",
              "      <td>33.48</td>\n",
              "      <td>101.17</td>\n",
              "      <td>-215.10</td>\n",
              "      <td>13.02</td>\n",
              "      <td>24.55</td>\n",
              "      <td>32.02</td>\n",
              "      <td>785.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Financials</th>\n",
              "      <td>66.00</td>\n",
              "      <td>28.94</td>\n",
              "      <td>69.19</td>\n",
              "      <td>0.00</td>\n",
              "      <td>9.40</td>\n",
              "      <td>12.00</td>\n",
              "      <td>15.93</td>\n",
              "      <td>402.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Communication Services</th>\n",
              "      <td>22.00</td>\n",
              "      <td>22.64</td>\n",
              "      <td>21.35</td>\n",
              "      <td>-13.90</td>\n",
              "      <td>12.47</td>\n",
              "      <td>20.10</td>\n",
              "      <td>27.58</td>\n",
              "      <td>82.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Information Technology</th>\n",
              "      <td>64.00</td>\n",
              "      <td>20.38</td>\n",
              "      <td>58.13</td>\n",
              "      <td>-274.60</td>\n",
              "      <td>9.33</td>\n",
              "      <td>23.05</td>\n",
              "      <td>41.78</td>\n",
              "      <td>172.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Materials</th>\n",
              "      <td>26.00</td>\n",
              "      <td>16.66</td>\n",
              "      <td>18.06</td>\n",
              "      <td>-50.10</td>\n",
              "      <td>8.88</td>\n",
              "      <td>17.30</td>\n",
              "      <td>27.25</td>\n",
              "      <td>45.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Health Care</th>\n",
              "      <td>60.00</td>\n",
              "      <td>14.99</td>\n",
              "      <td>37.30</td>\n",
              "      <td>-202.20</td>\n",
              "      <td>5.70</td>\n",
              "      <td>15.40</td>\n",
              "      <td>25.50</td>\n",
              "      <td>92.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Real Estate</th>\n",
              "      <td>31.00</td>\n",
              "      <td>12.49</td>\n",
              "      <td>14.33</td>\n",
              "      <td>-1.60</td>\n",
              "      <td>4.65</td>\n",
              "      <td>8.00</td>\n",
              "      <td>16.25</td>\n",
              "      <td>72.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Energy</th>\n",
              "      <td>28.00</td>\n",
              "      <td>11.22</td>\n",
              "      <td>10.95</td>\n",
              "      <td>-15.50</td>\n",
              "      <td>3.43</td>\n",
              "      <td>11.00</td>\n",
              "      <td>18.75</td>\n",
              "      <td>34.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Utilities</th>\n",
              "      <td>27.00</td>\n",
              "      <td>8.61</td>\n",
              "      <td>12.01</td>\n",
              "      <td>-40.10</td>\n",
              "      <td>6.55</td>\n",
              "      <td>10.10</td>\n",
              "      <td>11.30</td>\n",
              "      <td>37.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Consumer Staples</th>\n",
              "      <td>32.00</td>\n",
              "      <td>-0.69</td>\n",
              "      <td>142.67</td>\n",
              "      <td>-736.20</td>\n",
              "      <td>9.25</td>\n",
              "      <td>22.45</td>\n",
              "      <td>38.33</td>\n",
              "      <td>109.30</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        count  mean    std     min   25%   50%   75%    max\n",
              "Sector                                                                     \n",
              "Consumer Discretionary  63.00 45.42 133.93 -100.30 12.35 22.80 34.75 805.30\n",
              "Industrials             68.00 33.48 101.17 -215.10 13.02 24.55 32.02 785.10\n",
              "Financials              66.00 28.94  69.19    0.00  9.40 12.00 15.93 402.10\n",
              "Communication Services  22.00 22.64  21.35  -13.90 12.47 20.10 27.58  82.80\n",
              "Information Technology  64.00 20.38  58.13 -274.60  9.33 23.05 41.78 172.20\n",
              "Materials               26.00 16.66  18.06  -50.10  8.88 17.30 27.25  45.40\n",
              "Health Care             60.00 14.99  37.30 -202.20  5.70 15.40 25.50  92.60\n",
              "Real Estate             31.00 12.49  14.33   -1.60  4.65  8.00 16.25  72.80\n",
              "Energy                  28.00 11.22  10.95  -15.50  3.43 11.00 18.75  34.90\n",
              "Utilities               27.00  8.61  12.01  -40.10  6.55 10.10 11.30  37.00\n",
              "Consumer Staples        32.00 -0.69 142.67 -736.20  9.25 22.45 38.33 109.30"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "metadata": {
        "id": "81JFoDaLGPYG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "outputId": "98f147b8-09c0-410c-ad5c-5c251d535a6a"
      },
      "cell_type": "code",
      "source": [
        "sp500.groupby('Sector').describe()['Beta'].sort_values('mean', ascending=False)"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sector</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Energy</th>\n",
              "      <td>28.00</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.42</td>\n",
              "      <td>0.61</td>\n",
              "      <td>0.98</td>\n",
              "      <td>1.21</td>\n",
              "      <td>1.40</td>\n",
              "      <td>2.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Materials</th>\n",
              "      <td>24.00</td>\n",
              "      <td>1.25</td>\n",
              "      <td>0.46</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.91</td>\n",
              "      <td>1.23</td>\n",
              "      <td>1.54</td>\n",
              "      <td>2.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Information Technology</th>\n",
              "      <td>66.00</td>\n",
              "      <td>1.22</td>\n",
              "      <td>0.43</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.97</td>\n",
              "      <td>1.17</td>\n",
              "      <td>1.39</td>\n",
              "      <td>3.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Industrials</th>\n",
              "      <td>69.00</td>\n",
              "      <td>1.19</td>\n",
              "      <td>0.31</td>\n",
              "      <td>0.47</td>\n",
              "      <td>1.01</td>\n",
              "      <td>1.19</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Financials</th>\n",
              "      <td>67.00</td>\n",
              "      <td>1.17</td>\n",
              "      <td>0.35</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.97</td>\n",
              "      <td>1.15</td>\n",
              "      <td>1.42</td>\n",
              "      <td>2.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Health Care</th>\n",
              "      <td>62.00</td>\n",
              "      <td>1.10</td>\n",
              "      <td>0.40</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.89</td>\n",
              "      <td>1.10</td>\n",
              "      <td>1.24</td>\n",
              "      <td>3.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Communication Services</th>\n",
              "      <td>22.00</td>\n",
              "      <td>1.06</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.49</td>\n",
              "      <td>0.84</td>\n",
              "      <td>1.06</td>\n",
              "      <td>1.36</td>\n",
              "      <td>1.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Consumer Discretionary</th>\n",
              "      <td>63.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.68</td>\n",
              "      <td>1.01</td>\n",
              "      <td>1.26</td>\n",
              "      <td>1.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Real Estate</th>\n",
              "      <td>31.00</td>\n",
              "      <td>0.71</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.49</td>\n",
              "      <td>0.63</td>\n",
              "      <td>0.89</td>\n",
              "      <td>1.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Consumer Staples</th>\n",
              "      <td>32.00</td>\n",
              "      <td>0.62</td>\n",
              "      <td>0.29</td>\n",
              "      <td>0.13</td>\n",
              "      <td>0.42</td>\n",
              "      <td>0.64</td>\n",
              "      <td>0.76</td>\n",
              "      <td>1.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Utilities</th>\n",
              "      <td>28.00</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.22</td>\n",
              "      <td>-0.03</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.36</td>\n",
              "      <td>1.08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        count  mean  std   min  25%  50%  75%  max\n",
              "Sector                                                            \n",
              "Energy                  28.00  1.28 0.42  0.61 0.98 1.21 1.40 2.27\n",
              "Materials               24.00  1.25 0.46  0.03 0.91 1.23 1.54 2.27\n",
              "Information Technology  66.00  1.22 0.43  0.54 0.97 1.17 1.39 3.39\n",
              "Industrials             69.00  1.19 0.31  0.47 1.01 1.19 1.35 2.51\n",
              "Financials              67.00  1.17 0.35  0.32 0.97 1.15 1.42 2.03\n",
              "Health Care             62.00  1.10 0.40  0.32 0.89 1.10 1.24 3.08\n",
              "Communication Services  22.00  1.06 0.33  0.49 0.84 1.06 1.36 1.59\n",
              "Consumer Discretionary  63.00  1.00 0.41  0.11 0.68 1.01 1.26 1.90\n",
              "Real Estate             31.00  0.71 0.33  0.19 0.49 0.63 0.89 1.72\n",
              "Consumer Staples        32.00  0.62 0.29  0.13 0.42 0.64 0.76 1.54\n",
              "Utilities               28.00  0.32 0.22 -0.03 0.19 0.28 0.36 1.08"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "metadata": {
        "id": "-clboNgdGTDg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 421
        },
        "outputId": "12973416-e339-4f35-f720-4ec2bdf454a0"
      },
      "cell_type": "code",
      "source": [
        "sp500.groupby('Sector').describe()['Dividend'].sort_values('mean', ascending=False)"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sector</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Real Estate</th>\n",
              "      <td>29.00</td>\n",
              "      <td>3.75</td>\n",
              "      <td>1.24</td>\n",
              "      <td>1.85</td>\n",
              "      <td>2.89</td>\n",
              "      <td>3.56</td>\n",
              "      <td>4.18</td>\n",
              "      <td>6.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Utilities</th>\n",
              "      <td>28.00</td>\n",
              "      <td>3.16</td>\n",
              "      <td>0.93</td>\n",
              "      <td>0.28</td>\n",
              "      <td>2.86</td>\n",
              "      <td>3.07</td>\n",
              "      <td>3.71</td>\n",
              "      <td>5.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Communication Services</th>\n",
              "      <td>14.00</td>\n",
              "      <td>2.91</td>\n",
              "      <td>2.26</td>\n",
              "      <td>0.76</td>\n",
              "      <td>1.56</td>\n",
              "      <td>1.86</td>\n",
              "      <td>3.97</td>\n",
              "      <td>8.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Consumer Staples</th>\n",
              "      <td>32.00</td>\n",
              "      <td>2.79</td>\n",
              "      <td>1.18</td>\n",
              "      <td>0.95</td>\n",
              "      <td>2.08</td>\n",
              "      <td>2.65</td>\n",
              "      <td>3.42</td>\n",
              "      <td>5.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Consumer Discretionary</th>\n",
              "      <td>50.00</td>\n",
              "      <td>2.72</td>\n",
              "      <td>1.78</td>\n",
              "      <td>0.14</td>\n",
              "      <td>1.49</td>\n",
              "      <td>2.49</td>\n",
              "      <td>3.48</td>\n",
              "      <td>9.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Energy</th>\n",
              "      <td>29.00</td>\n",
              "      <td>2.57</td>\n",
              "      <td>1.55</td>\n",
              "      <td>0.33</td>\n",
              "      <td>1.13</td>\n",
              "      <td>2.52</td>\n",
              "      <td>3.92</td>\n",
              "      <td>5.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Financials</th>\n",
              "      <td>66.00</td>\n",
              "      <td>2.46</td>\n",
              "      <td>1.12</td>\n",
              "      <td>0.52</td>\n",
              "      <td>1.66</td>\n",
              "      <td>2.50</td>\n",
              "      <td>3.08</td>\n",
              "      <td>6.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Materials</th>\n",
              "      <td>26.00</td>\n",
              "      <td>2.29</td>\n",
              "      <td>1.29</td>\n",
              "      <td>0.35</td>\n",
              "      <td>1.44</td>\n",
              "      <td>2.03</td>\n",
              "      <td>2.87</td>\n",
              "      <td>5.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Information Technology</th>\n",
              "      <td>44.00</td>\n",
              "      <td>2.14</td>\n",
              "      <td>1.15</td>\n",
              "      <td>0.03</td>\n",
              "      <td>1.35</td>\n",
              "      <td>1.99</td>\n",
              "      <td>2.81</td>\n",
              "      <td>5.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Industrials</th>\n",
              "      <td>65.00</td>\n",
              "      <td>1.82</td>\n",
              "      <td>0.87</td>\n",
              "      <td>0.15</td>\n",
              "      <td>1.23</td>\n",
              "      <td>1.87</td>\n",
              "      <td>2.29</td>\n",
              "      <td>5.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Health Care</th>\n",
              "      <td>36.00</td>\n",
              "      <td>1.67</td>\n",
              "      <td>1.27</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.72</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2.43</td>\n",
              "      <td>5.27</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                        count  mean  std  min  25%  50%  75%  max\n",
              "Sector                                                           \n",
              "Real Estate             29.00  3.75 1.24 1.85 2.89 3.56 4.18 6.93\n",
              "Utilities               28.00  3.16 0.93 0.28 2.86 3.07 3.71 5.11\n",
              "Communication Services  14.00  2.91 2.26 0.76 1.56 1.86 3.97 8.26\n",
              "Consumer Staples        32.00  2.79 1.18 0.95 2.08 2.65 3.42 5.62\n",
              "Consumer Discretionary  50.00  2.72 1.78 0.14 1.49 2.49 3.48 9.56\n",
              "Energy                  29.00  2.57 1.55 0.33 1.13 2.52 3.92 5.25\n",
              "Financials              66.00  2.46 1.12 0.52 1.66 2.50 3.08 6.06\n",
              "Materials               26.00  2.29 1.29 0.35 1.44 2.03 2.87 5.19\n",
              "Information Technology  44.00  2.14 1.15 0.03 1.35 1.99 2.81 5.14\n",
              "Industrials             65.00  1.82 0.87 0.15 1.23 1.87 2.29 5.11\n",
              "Health Care             36.00  1.67 1.27 0.02 0.72 1.35 2.43 5.27"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        }
      ]
    }
  ]
}