scrape_data.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.4"
    },
    "colab": {
      "name": "scrape_data.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jcaguirre89/scrape-reuters/blob/master/scrape_data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a-TD3vas-MiQ",
        "colab_type": "code",
        "colab": {},
        "outputId": "47b7ef04-b6cb-4875-d67b-d914cabd4c5c"
      },
      "source": [
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "import pandas as pd\n",
        "\n",
        "import plotly as py\n",
        "from plotly.offline import init_notebook_mode\n",
        "init_notebook_mode(connected=True)\n",
        "import plotly.graph_objs as go"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "        <script type=\"text/javascript\">\n",
              "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
              "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
              "        if (typeof require !== 'undefined') {\n",
              "        require.undef(\"plotly\");\n",
              "        requirejs.config({\n",
              "            paths: {\n",
              "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
              "            }\n",
              "        });\n",
              "        require(['plotly'], function(Plotly) {\n",
              "            window._Plotly = Plotly;\n",
              "        });\n",
              "        }\n",
              "        </script>\n",
              "        "
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ros3uTP0-MiZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def scrape_reuters(ticker, name='placeholder'):\n",
        "    \"\"\" Scrapes reuters for financial data \"\"\"\n",
        "    url = f'https://www.reuters.com/finance/stocks/financial-highlights/{ticker}'\n",
        "    response = requests.get(url)\n",
        "    soup = BeautifulSoup(response.content, 'lxml')\n",
        "    \n",
        "    divs = soup.find_all('div', attrs={'class': 'moduleBody'})\n",
        "    tables = [div.find('table') for div in divs]\n",
        "\n",
        "    dataframes = {}\n",
        "    for idx, table in enumerate(tables):\n",
        "        if table is not None:\n",
        "            trs = [tr for tr in table.find_all('tr')]\n",
        "            headers = [th.text.strip() for th in table.find_all('th')]\n",
        "            rows = [headers]\n",
        "            for tr in trs:\n",
        "                row = [td.text.strip() for td in tr.find_all('td')]\n",
        "                rows.append(row)\n",
        "            dataframes[idx] = pd.DataFrame(rows)\n",
        "            dataframes[idx].columns = dataframes[idx].iloc[0]\n",
        "            dataframes[idx].drop([0, 1], inplace=True)\n",
        "\n",
        "    # Useful ones: 3, 4, 5, 6, 7, 8, 9\n",
        "    keep_these = [3, 4, 5, 6, 7, 8, 9]\n",
        "    dataframes = {k:v for k, v in dataframes.items() if k in keep_these}\n",
        "    \n",
        "    for idx in keep_these:\n",
        "        dataframes[idx].set_index('', inplace=True)\n",
        "        dataframes[idx].dropna(inplace=True)\n",
        "        \n",
        "    df = pd.concat([df for df in dataframes.values()])\n",
        "    df['Ticker'] = ticker\n",
        "    df['Company Name'] = name\n",
        "        \n",
        "    return df"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0vtJ_BAi-Mid",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Each tuple must be a valid ticker and any name you want\n",
        "companies = [\n",
        "    ('9613.T', 'NTT Data Corp'),\n",
        "    ('T.TO', 'Telus Corp'),\n",
        "    ('MMS', 'Maximus Inc'),\n",
        "    ('ACN', 'Accenture Plc'),\n",
        "    ('CTSH.O', 'Cognizant Technology Solutions Corp'),\n",
        "    ('GIB', 'CGI Inc'),\n",
        "    #('TTM', 'TATA Motors'),\n",
        "    #('TCS.NS, 'TATA Consulting Services Ltd'),\n",
        "    ('DXC', 'DXC Technology Co'),\n",
        "    ('IBM', 'IBM')\n",
        "]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fUDqMcay-Mim",
        "colab_type": "code",
        "colab": {},
        "outputId": "6368c41b-403a-4875-dd9d-23e5cd5fb153"
      },
      "source": [
        "# Scrape data\n",
        "import time\n",
        "\n",
        "master_df = pd.DataFrame()\n",
        "for ticker, name in companies:\n",
        "    print(f\"Scraping data for {name}\")\n",
        "    # Sleep for good measure\n",
        "    time.sleep(1)\n",
        "    single_company_df = scrape_reuters(ticker, name)\n",
        "    master_df = pd.concat([master_df, single_company_df])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Scraping data for NTT Data Corp\n",
            "Scraping data for Telus Corp\n",
            "Scraping data for Maximus Inc\n",
            "Scraping data for Accenture Plc\n",
            "Scraping data for Cognizant Technology Solutions Corp\n",
            "Scraping data for CGI Inc\n",
            "Scraping data for DXC Technology Co\n",
            "Scraping data for IBM\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7nCAXWHC-Mis",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "master_df.to_csv('financial_data.csv')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FgcQz7M6-Miv",
        "colab_type": "code",
        "colab": {},
        "outputId": "05566705-3b40-469d-a779-13ca2ecf55c9"
      },
      "source": [
        "print('Ratios Available')\n",
        "print('\\n')\n",
        "import pprint\n",
        "pprint.pprint(list(master_df.index.unique()))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Ratios Available\n",
            "\n",
            "\n",
            "['P/E Ratio (TTM)',\n",
            " 'P/E High - Last 5 Yrs.',\n",
            " 'P/E Low - Last 5 Yrs.',\n",
            " 'Beta',\n",
            " 'Price to Sales (TTM)',\n",
            " 'Price to Book (MRQ)',\n",
            " 'Price to Tangible Book (MRQ)',\n",
            " 'Price to Cash Flow (TTM)',\n",
            " '% Owned Institutions',\n",
            " 'Dividend Yield',\n",
            " 'Dividend Yield - 5 Year Avg',\n",
            " 'Dividend 5 Year Growth Rate',\n",
            " 'Payout Ratio(TTM)',\n",
            " 'Sales (MRQ) vs Qtr. 1 Yr. Ago',\n",
            " 'Sales (TTM) vs TTM 1 Yr. Ago',\n",
            " 'Sales - 5 Yr. Growth Rate',\n",
            " 'EPS (MRQ) vs Qtr. 1 Yr. Ago',\n",
            " 'EPS (TTM) vs TTM 1 Yr. Ago',\n",
            " 'EPS - 5 Yr. Growth Rate',\n",
            " 'Capital Spending - 5 Yr. Growth Rate',\n",
            " 'Quick Ratio (MRQ)',\n",
            " 'Current Ratio (MRQ)',\n",
            " 'LT Debt to Equity (MRQ)',\n",
            " 'Total Debt to Equity (MRQ)',\n",
            " 'Interest Coverage (TTM)',\n",
            " 'Gross Margin (TTM)',\n",
            " 'Gross Margin - 5 Yr. Avg.',\n",
            " 'EBITD Margin (TTM)',\n",
            " 'EBITD - 5 Yr. Avg',\n",
            " 'Operating Margin (TTM)',\n",
            " 'Operating Margin - 5 Yr. Avg.',\n",
            " 'Pre-Tax Margin (TTM)',\n",
            " 'Pre-Tax Margin - 5 Yr. Avg.',\n",
            " 'Net Profit Margin (TTM)',\n",
            " 'Net Profit Margin - 5 Yr. Avg.',\n",
            " 'Effective Tax Rate (TTM)',\n",
            " 'Effective Tax Rate - 5 Yr. Avg.',\n",
            " 'Revenue/Employee (TTM)',\n",
            " 'Net Income/Employee (TTM)',\n",
            " 'Receivable Turnover (TTM)',\n",
            " 'Inventory Turnover (TTM)',\n",
            " 'Asset Turnover (TTM)',\n",
            " 'Return on Assets (TTM)',\n",
            " 'Return on Assets - 5 Yr. Avg.',\n",
            " 'Return on Investment (TTM)',\n",
            " 'Return on Investment - 5 Yr. Avg.',\n",
            " 'Return on Equity (TTM)',\n",
            " 'Return on Equity - 5 Yr. Avg.']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EHLegu9M-Mi0",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "\n",
        "def plot_ratio(df, ratio, size=(600,400)):\n",
        "    if ratio not in df.index:\n",
        "        raise KeyError('Ratio not available')\n",
        "    \n",
        "    df = df.loc[ratio]\n",
        "    trace = go.Bar(\n",
        "        x=df['Company Name'],\n",
        "        y=df['Company'],\n",
        "    )\n",
        "\n",
        "    data = [trace]\n",
        "\n",
        "    layout = go.Layout(\n",
        "        title=ratio,\n",
        "    )\n",
        "\n",
        "    fig = go.Figure(data=data, layout=layout)\n",
        "\n",
        "    py.offline.iplot(fig)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8adgWwNi-Mi5",
        "colab_type": "code",
        "colab": {},
        "outputId": "be8907c8-4242-46ce-bd2b-381c1303223a"
      },
      "source": [
        "plot_ratio(master_df, 'EBITD Margin (TTM)')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.plotly.v1+json": {
              "config": {
                "linkText": "Export to plot.ly",
                "plotlyServerURL": "https://plot.ly",
                "responsive": true,
                "showLink": false
              },
              "data": [
                {
                  "type": "bar",
                  "uid": "19f19bea-8487-42db-b7f4-02de54ecadf1",
                  "x": [
                    "NTT Data Corp",
                    "Telus Corp",
                    "Maximus Inc",
                    "Accenture Plc",
                    "Cognizant Technology Solutions Corp",
                    "CGI Inc",
                    "DXC Technology Co",
                    "IBM"
                  ],
                  "y": [
                    "14.08",
                    "35.45",
                    "14.73",
                    "16.17",
                    "20.20",
                    "18.32",
                    "24.07",
                    "20.55"
                  ]
                }
              ],
              "layout": {
                "autosize": true,
                "title": {
                  "text": "EBITD Margin (TTM)"
                },
                "xaxis": {
                  "autorange": true,
                  "range": [
                    -0.5,
                    7.5
                  ],
                  "type": "category"
                },
                "yaxis": {
                  "autorange": true,
                  "range": [
                    0,
                    37.31578947368421
                  ],
                  "type": "linear"
                }
              }
            },
            "image/png": "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",
            "text/html": [
              "<div>\n",
              "        \n",
              "        \n",
              "            <div id=\"a1887f7a-6e5d-413a-8e46-e30a1eb569ea\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                require([\"plotly\"], function(Plotly) {\n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    window.PLOTLYENV.BASE_URL='https://plot.ly';\n",
              "                    \n",
              "                if (document.getElementById(\"a1887f7a-6e5d-413a-8e46-e30a1eb569ea\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        'a1887f7a-6e5d-413a-8e46-e30a1eb569ea',\n",
              "                        [{\"type\": \"bar\", \"uid\": \"7d129133-e319-456d-8e47-f3d0c7bd346a\", \"x\": [\"NTT Data Corp\", \"Telus Corp\", \"Maximus Inc\", \"Accenture Plc\", \"Cognizant Technology Solutions Corp\", \"CGI Inc\", \"DXC Technology Co\", \"IBM\"], \"y\": [\"14.08\", \"35.45\", \"14.73\", \"16.17\", \"20.20\", \"18.32\", \"24.07\", \"20.55\"]}],\n",
              "                        {\"title\": {\"text\": \"EBITD Margin (TTM)\"}},\n",
              "                        {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('a1887f7a-6e5d-413a-8e46-e30a1eb569ea');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                });\n",
              "            </script>\n",
              "        </div>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "advgsa_K-Mi8",
        "colab_type": "code",
        "colab": {},
        "outputId": "b30ec319-1189-4966-dbe0-a6e6bf69de09"
      },
      "source": [
        "plot_ratio(master_df, 'Interest Coverage (TTM)')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.plotly.v1+json": {
              "config": {
                "linkText": "Export to plot.ly",
                "plotlyServerURL": "https://plot.ly",
                "responsive": true,
                "showLink": false
              },
              "data": [
                {
                  "type": "bar",
                  "uid": "a39a8d51-ff82-45e9-a5cb-517395ae68e4",
                  "x": [
                    "NTT Data Corp",
                    "Telus Corp",
                    "Maximus Inc",
                    "Accenture Plc",
                    "Cognizant Technology Solutions Corp",
                    "CGI Inc",
                    "DXC Technology Co",
                    "IBM"
                  ],
                  "y": [
                    "74.36",
                    "5.21",
                    "--",
                    "--",
                    "22.78",
                    "24.66",
                    "8.26",
                    "27.73"
                  ]
                }
              ],
              "layout": {
                "autosize": true,
                "title": {
                  "text": "Interest Coverage (TTM)"
                },
                "xaxis": {
                  "autorange": true,
                  "range": [
                    -0.5,
                    7.5
                  ],
                  "type": "category"
                },
                "yaxis": {
                  "autorange": true,
                  "range": [
                    0,
                    78.27368421052631
                  ],
                  "type": "linear"
                }
              }
            },
            "image/png": "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",
            "text/html": [
              "<div>\n",
              "        \n",
              "        \n",
              "            <div id=\"cc70c825-a715-42b4-97f8-c03df61db40d\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                require([\"plotly\"], function(Plotly) {\n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    window.PLOTLYENV.BASE_URL='https://plot.ly';\n",
              "                    \n",
              "                if (document.getElementById(\"cc70c825-a715-42b4-97f8-c03df61db40d\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        'cc70c825-a715-42b4-97f8-c03df61db40d',\n",
              "                        [{\"type\": \"bar\", \"uid\": \"581a2780-7507-4f71-a6df-6b3541eaf7f4\", \"x\": [\"NTT Data Corp\", \"Telus Corp\", \"Maximus Inc\", \"Accenture Plc\", \"Cognizant Technology Solutions Corp\", \"CGI Inc\", \"DXC Technology Co\", \"IBM\"], \"y\": [\"74.36\", \"5.21\", \"--\", \"--\", \"22.78\", \"24.66\", \"8.26\", \"27.73\"]}],\n",
              "                        {\"title\": {\"text\": \"Interest Coverage (TTM)\"}},\n",
              "                        {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('cc70c825-a715-42b4-97f8-c03df61db40d');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                });\n",
              "            </script>\n",
              "        </div>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j3XtbAdI-MjA",
        "colab_type": "code",
        "colab": {},
        "outputId": "85578f2e-7f16-48a9-817f-714803d56452"
      },
      "source": [
        "plot_ratio(master_df, 'Total Debt to Equity (MRQ)')\n",
        "print('Note that values are multiplied by 100, so 129 means Debt is 1.29 times Equity')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.plotly.v1+json": {
              "config": {
                "linkText": "Export to plot.ly",
                "plotlyServerURL": "https://plot.ly",
                "responsive": true,
                "showLink": false
              },
              "data": [
                {
                  "type": "bar",
                  "uid": "4f4e32af-6855-4133-a400-0f05a1384c9d",
                  "x": [
                    "NTT Data Corp",
                    "Telus Corp",
                    "Maximus Inc",
                    "Accenture Plc",
                    "Cognizant Technology Solutions Corp",
                    "CGI Inc",
                    "DXC Technology Co",
                    "IBM"
                  ],
                  "y": [
                    "66.64",
                    "138.42",
                    "11.25",
                    "0.28",
                    "6.97",
                    "30.62",
                    "68.59",
                    "247.97"
                  ]
                }
              ],
              "layout": {
                "autosize": true,
                "title": {
                  "text": "Total Debt to Equity (MRQ)"
                },
                "xaxis": {
                  "autorange": true,
                  "range": [
                    -0.5,
                    7.5
                  ],
                  "type": "category"
                },
                "yaxis": {
                  "autorange": true,
                  "range": [
                    0,
                    261.0210526315789
                  ],
                  "type": "linear"
                }
              }
            },
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAy8AAAHCCAYAAADmaPZFAAAgAElEQVR4Xu2dCbgdRZm/i2UwAiJxAxSDGGEgggvGKKvKCE4URtFRHJRFUZAMEh0wGkn+gxJFHYMEx4gbKCjoKEYliOIojooLRhxUMqDGBXAYEIwCSlQg/+et0Dfnnpzt3q6unNP99vPkgXtvd1X3219316++pTZZu3bt2uAmAQlIQAISkIAEJCABCUhgyAlsongZ8jvk6UlAAhKQgAQkIAEJSEACkYDiRUOQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpCABCQgAQlIQAISkIDiRRuQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpCABCQgAQlIQAISkIDiRRuQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpCABCQgAQlIQAISkIDiRRuQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpCABCQgAQlIQAISkIDiRRuQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpCABCQgAQlIQAISkIDiRRuQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpCABCQgAQlIQAISkIDiRRuQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpCABCQgAQlIQAISkIDiRRuQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpCABCQgAQlIQAISkIDiRRuQgAQkIAEJSEACEpCABEaCgOJlJG6TJykBCUhAAhKQgAQkIAEJKF60AQlIQAISkIAEJCABCUhgJAgoXkbiNnmSEpDAxiKwatWqMG/evPDyl788HHbYYRvrNMKyZcvCxz/+8fCud70rTJ8+faOdhx0PRmD16tXh5JNPDn/4wx9G5p4tWbIkLF++PMyZM2ej2vpghN1LAhJoKgHFS1PvvNctgSEkUAye+p3arFmzwsKFC8OUKVN67ppCeEykDQTG0qVLO57TGWecEWbOnNnv0rr+fSLiBY7XXHNNWLx4cZg6dWrfPidyjX0ba9uhGMTfeOONHQ/dZpttKh3cF/3vsMMOYzYzEZYTvd5i/073YM2aNeH0008PV111VTjkkEPC3LlzN2h+xYoVYf78+aGdSzfbevSjH93zPnc6rtfzU+xf1l4ny83jJCABCfQjoHjpR8i/S0ACG41AMahmMDeZgX+KQflE2ug2KC4GpP0Gmr1AT2TAPYzi5YlPfGLHwXrVxrUxxEtxv9sFQKt46STaev290/0v9r/uuus2EIDdPD+tfXQSKMXfuS+DTBBUff9sXwISkEA7AcWLNiEBCQwtgbqIFwAXg0n+f1CPSOuNUbykM9OJsJxor70G/8Xf7rrrrtjsYx/72HGCDtGDoHjKU54SfvCDH4wTJN3OuXhGDjjggHFtIWC/8Y1vdPVq9fp7N/E1URbuLwEJSKAKAoqXKqjapgQkkIRAL/HSKRypdSa5OPaOO+4Ydy5FuE4xQGs/0fbZ6BSel6KPos/2nILW2fBi3/Z9isHrW9/61nDhhRfG0CO2dm9Op9C7XqFZ/Ti1Cq/W0K9Bw4qK+zSo56XTfd19990DA/5W0cd13nrrrRt4B+B0ySWXjO3b3n+38Cuuh+vrllc0qODpZS+twmbGjBnhs5/97DhxwTWxTZs2bYPzmIh4GcRmBznPRzziERvFW5bk5WEjEpBAbQkoXmp7a70wCYw+gW7ipdPAq5Mw6DVAY/8rr7xyg5lvQtQ6iaBBEvb7DXA7hTB1mjnvNOAvBt3tQqRTiFjKsLFBWXeztomIl15ehPYcnsmKF86z233qdq6F6BhkMN/LBlrFy4knnhhOPfXUcOihh8bkeK590aJFYcGCBeFHP/rRwOKlk5dkkLyVTrbYeg8nakOj/7bxCiQggVEhoHgZlTvleUqggQQ6iZdeYTntA8dBZqBbsXYapE6kjX7ipWj/5ptvHvMM9BqEt3oB+s28t4qriQ48u13jRFj3Ey+DJOwPKkjoa9B9uwnBXh6WVs8NfU0kjKoX+3ael1122ZiX6Pzzz48ISeLvdK87/a6bAOlnh/TTyRZb72ERwmZ1uwa+eL1kCQw5AcXLkN8gT08CTSbQSbwUA7Zixrp9wNXqOeknPLpVwmqtBNWvjdb++w0a2weMHEs53U7X0n7tE/EWpBIvE2HdT7z0Cxvr1Vd7KFiV4qXT/e4mlDpdc69928XL3XffHe//4x73uJjjUhSm6CZe2ivZdQsH7GeHipcmv1W9dgmMPgHFy+jfQ69AArUl0Em89BIT7X/rtW8RWtMqVKr2vLTPlP/mN7+Ja8i05+W03tAihK3bgLTTOacSLxNhXVa89LtX7d6Qqjwv7cKouEeDVrybiHih1Hdhh63liwfxvBS8dtttt455PwidXnlJ/cLG9LzU9rXqhUlg5AkoXkb+FnoBEqgvgao8LxPJbUjpeWnPy+nlbWi/q3pe1ifhV+l5oe1WuyPcjfs2aNngiYSNIV462fgg4oXzLOypfd2WQWy23z6Kl/q+V70yCYw6AcXLqN9Bz18CNSZQNuelmzjol+PRmpjdb5DXin/QZO1iIDyRNTX65by0egY6hVn1MpNunFLmvPQLG+vXVyfPS6eFOPtVGysG/XgluuVztJ4L+Umdwvq68ZyoDXRqZ1DxwrGdPIiFuOtXKrnXQqYT9d7V+DXkpUlAAkNGQPEyZDfE05GABNYT6FdtrHVti07VxroNiDv9vtvq5ynES69FKruF/3A+Z555Zjj88MPD9OnTxwapraFA3UJ/JpJgDu1ewqFTBbBuJZ872e5Eqo11Ou9u7HpV2WotH92p/0Hu6WQXFu3V9qBidSLipRAqy5cvD63ltfstUtlpYcvi/k2kuprvKwlIQAK5CShechO3PwlIYGAC3cQLDfRb56XopH2/IselfW0Vkp+LNVTKeF7ak6qL8+iVf9BpnReOa83HKQa0nOdNN900xrB1n1awxYw8v+u1zks/ThNh3Uu8DFJtjOPb19/h+lj3pN3zwr6t18jPDN7Zeq3zUpxjez/t92ciIX2t1z3IIpXs3ysMbaLipZvw7sSo3a463bOJit+BH2h3lIAEJJCAgOIlAUSbkIAEJCCB6ghMNAwuxZkMUrGrWz/DOvgfxAs2qHcoBWPbkIAEJDAZAoqXyVDzGAlIQAISyEYgt3gZZJDf7+KHNWek33mVEW39mPh3CUhAAikIKF5SULQNCUhAAhKojEBu8ZJiAN8t56QySBNoGAFDjgxba0hh8fvW3JkJNOuuEpCABLIQULxkwWwnEpCABCQgAQlIQAISkEBZAoqXsgQ9XgISkIAEJCABCUhAAhLIQkDxkgWznUhAAhKQgAQkIAEJSEACZQkoXsoS9HgJSEACEpCABCQgAQlIIAsBxUsWzHYiAQlIQAISkIAEJCABCZQloHgpS9DjJSABCUhAAhKQgAQkIIEsBBQvWTDbiQQkIAEJSEACEpCABCRQloDipSxBj5eABCQgAQlIQAISkIAEshBQvGTBbCcSkIAEJCABCUhAAhKQQFkCipeyBD1eAhKQgAQkIAEJSEACEshCQPGSBbOdSEACEpCABCQgAQlIQAJlCSheyhL0eAlIQAISkIAEJCABCUggCwHFSxbMdiIBCUhAAhKQgAQkIAEJlCWgeClL0OMlIAEJSEACEpCABCQggSwEFC9ZMNuJBCQgAQlIQAISkIAEJFCWgOKlLEGPl4AEJCABCUhAAhKQgASyEFC8ZMFsJxKQgAQkIAEJSEACEpBAWQKKl7IEPV4CEpCABCQgAQlIQAISyEJA8ZIFs51IQAISkIAEJCABCUhAAmUJKF7KEvR4CUhAAhKQgAQkIAEJSCALAcVLFsx2IgEJSEACEpCABCQgAQmUJaB4KUvQ4yUgAQlIQAISkIAEJCCBLAQUL1kw24kEJCABCUhAAhKQgAQkUJaA4qUsQY+XgAQkIAEJSEACEpCABLIQULxkwWwnEpCABCQgAQlIQAISkEBZAoqXsgQ9XgISkIAEJCABCUhAAhLIQkDxkgWznUhAAhKQgAQkIAEJSEACZQkoXsoS9HgJSEACEpCABCQgAQlIIAsBxUsWzHYiAQlIQAISkIAEJCABCZQloHgpS9DjJSABCUhAAhKQgAQkIIEsBBQvWTDbiQQkIAEJSEACEpCABCRQloDipSxBj5eABCQgAQlIQAISkIAEshBQvGTBbCcSkIAEJCABCUhAAhKQQFkCipeyBD1eAhKQgAQkIAEJSEACEshCQPGSBbOdSEACEpCABCQgAQlIQAJlCSheyhL0eAlIQAISkIAEJCABCUggCwHFSxbMdiIBCUhAAhKQgAQkIAEJlCWgeClL0OMlIAEJSEACEpCABCQggSwEFC9ZMNuJBCQgAQlIQAISkIAEJFCWgOKlLEGPl4AEJCABCUhAAhKQgASyEFC8ZMFsJxKQgAQkIAEJSEACEpBAWQKKl7IEPV4CEpCABCQgAQlIQAISyEJA8ZIFs51IQAISkIAEJCABCUhAAmUJKF7KEvR4CUhAAhKQgAQkIAEJSCALAcVLFsx2IgEJSEACEpCABCQgAQmUJaB4KUvQ4yUgAQlIQAISkIAEJCCBLAQUL1kw24kEJCABCUhAAhKQgAQkUJaA4qUsQY+XgAQkIAEJSEACEpCABLIQULxkwWwnEpCABCQgAQlIQAISkEBZAoqXsgQ9XgISkIAEJCABCUhAAhLIQkDxkgWznUhAAhKQgAQkIAEJSEACZQkoXsoS9HgJSEACEpCABCQgAQlIIAsBxUsWzHYiAQlIQAISkIAEJCABCZQloHgpS9DjJSABCUhAAhKQgAQkIIEsBBohXpYsWRKWL18+BnTOnDnhsMMOG/u5/e/8oXWfZcuWhaVLl8b9Z82aFRYuXBimTJmS5QbZiQQkIAEJSEACEpCABCSwjkDtxcuaNWvCBz7wgXDUUUeFqVOnhlWrVoV58+aF+fPnh5kzZ0YIiBe2uXPnbmAXK1asiMJl8eLF8fhe+2pUEpCABCQgAQlIQAISkEB1BGovXtrRIWZOP/30KFwK70svQcLfpk2bNrZvu5ip7tbYsgQkIAEJSEACEpCABCTQSqBx4mX16tXh5JNPjmFhrZ6XTmFlnYQOnptFixaFBQsWhOnTp4f77rtPi5KABBpKYO3atQ298v6XvckmmwT59Oc00T3g6iYBCYw2gU033XS0L2Ajn33jxEu/sK/WsLI99tgjemnw0BRCp128/P73v9/It9DuJSCBjUXAgWR38ptttlm49957N9atqW2/CsLa3lovrEEEtt122wZdbfpLbZR4QbjceuutfRPui1Cx2bNnbxBi1i5e0t8SW5SABCQgAQlIQAISkIAEOhFojHgZVLgAqTXPxZwXHxwJSEACEpCABCTQn8AXrvnfsOrWu/rvWOM9HrHNlPCyp02r8RVu/EtrhHjpFSpGDsxll10WjjjiiHg32j0rVhvb+EbqGUhAAhKQgAQkMPwEXn3+ivCVlbcM/4lWeIaPf+Q24dKT9q+wB5uuvXgpEvRvvPHGcXe7WK+FX5LXctVVV439/YwzzhjLceGXrvPigyIBCUhAAhKQgAR6E1C8hKB4qf4pqb14qR6hPUhAAhKQgAQkIAEJKF4ULzmeAsVLDsr2IQEJSEACEpCABGpOQPGieMlh4oqXHJTtQwISkIAEJCABCdScgOJF8ZLDxBUvOSjbhwQkIAEJSEACEqg5AcWL4iWHiSteclC2DwlIQAISkIAEJFBzAooXxUsOE1e85KBsHxKQgAQkIAEJSKDmBBQvipccJq54yUHZPiQgAQlIQAISkEDNCSheFC85TFzxkoOyfUhAAhKQgAQkIIGaE1C8KF5ymLjiJQdl+5CABCQgAQlIQAI1J6B4UbzkMHHFSw7K9iEBCUhAAhKQgARqTkDxonjJYeKKlxyU7UMCEpCABCQgAQnUnIDiRfGSw8QVLzko24cEJCABCUhAAhKoOQHFi+Ilh4krXnJQtg8JSEACEpCABCRQcwKKF8VLDhNXvOSgbB8SkIAEJCABCUig5gQUL4qXHCaueMlB2T4kIAEJSEACEpBAzQkoXhQvOUxc8ZKDsn1IQAISkIAEJCCBmhNQvChecpi44iUHZfuQgAQkIAEJSEACNSegeFG85DBxxUsOyvYhAQlIQAISkIAEak5A8aJ4yWHiipcclO1DAhKQgAQkIAEJ1JyA4kXxksPEFS85KNuHBCQgAQlIQAISqDkBxYviJYeJK15yULYPCUhAAhKQgAQkUHMCihfFSw4TV7zkoGwfEpCABCQgAQlIoOYEFC+KlxwmrnjJQdk+JCABCUhAAhKQQM0JKF4ULzlMXPGSg7J9SEACEpCABCQggZoTULwoXnKYuOIlB2X7kIAEJCABCUhAAjUnoHhRvOQwccVLDsr2IQEJSEACEpCABGpOQPGieMlh4oqXHJTtQwISkIAEJCABCdScgOJF8ZLDxBUvOSjbhwQkIAEJSEACEqg5AcWL4iWHiSteclC2DwlIQAISkIAEJFBzAooXxUsOE1e85KBsHxKQgAQkIAEJSKDmBBQvipccJq54yUHZPiQgAQlIQAISkEDNCSheFC85TFzxkoOyfUhAAhKQgAQkIIGaE1C8KF5ymLjiJQdl+5CABCQgAQlIQAI1J6B4UbzkMHHFSw7K9iEBCUhAAhKQgARqTkDxonjJYeKKlxyU7UMCEpCABCQgAQnUnIDiRfGSw8QVLzko24cEJCABCUhAAhKoOQHFi+Ilh4krXnJQtg8JSEACEpCABCRQcwKKF8VLDhNXvOSgbB8SkIAEJCABCUig5gQUL4qXHCaueMlB2T4kIAEJSEACEpBAzQkoXhQvOUxc8ZKDsn1IQAISkIAEJCCBmhNQvChecpi44iUHZfuQgAQkIAEJSEACNSegeFG85DBxxUsOyvYhAQlIQAISkIAEak5A8aJ4yWHijRAvS5YsCcuXLx/jOWfOnHDYYYeN/bx69epw8sknhxtvvDH+7owzzggzZ84c+/uyZcvC0qVL48+zZs0KCxcuDFOmTMlxf+xDAhKQgAQkIAEJjAQBxYviJYeh1l68rFmzJnzgAx8IRx11VJg6dWpYtWpVmDdvXpg/f34UKPz99NNPj/+PoOHvixYtCgsWLAjTp08PK1asiMJl8eLF8XiEENvcuXNz3B/7kIAEJCABCUhAAiNBQPGieMlhqLUXL+0QO4mVs88+O5x22mlRnLT/HbEybdq0MU9Nu5jJcZPsQwISkIAEJCABCQw7AcWL4iWHjTZOvBQhYoSO4W3pJEYK78rxxx8/zivDDWn3zOS4SfYhAQlIQAISkIAEhp2A4kXxksNGGyde2sO+EC/ktLTmsbSLF8LJihyYdvHy5z//Ocd9sg8JSEACEpCABCQw1ATmXHRN+Op1vx3qc6z65Gbs8KCw7DVP69nNAx7wgKpPo9btN0q8IEpuvfXWcUKlrOflj3/8Y60NxIuTgAQkMBkCm2yySVi7du1kDvUYCUhgRAm89j9+Er52/W0jevZpTnv37bcOn3n1+qJPnVrdaqut0nTW0FYaI146CRfuOZ4Uc14aav1etgQkIAEJSEACyQgYNmbYWDJj6tFQI8RLrwphVhvLYWb2IQEJSEACEpBA3QkoXhQvOWy89uKlfQ2XAmrrei2u85LD1OxDAhKQgAQkIIE6E1C8KF5y2HftxUsOiPYhAQlIQAISkIAEmk5A8aJ4yfEMKF5yULYPCUhAAhKQgAQkUHMCihfFSw4TV7zkoGwfEpCABCQgAQlIoOYEFC+KlxwmrnjJQdk+JCABCUhAAhKQQM0JKF4ULzlMXPGSg7J9SEACEpCABCQggZoTULwoXnKYuOIlB2X7kIAEJCABCUhAAjUnoHhRvOQwccVLDsr2IQEJSEACEpCABGpOQPGieMlh4oqXHJTtQwISkIAEJCABCdScgOJF8ZLDxBUvOSjbhwQkIAEJSEACEqg5AcWL4iWHiSteclC2DwlIQAISkIAEJFBzAooXxUsOE1e85KBsHxKQgAQkIAEJSKDmBBQvipccJq54yUHZPiQgAQlIQAISkEDNCSheFC85TFzxkoOyfUhAAhKQgAQkIIGaE1C8KF5ymLjiJQdl+5CABCQgAQlIQAI1J6B4UbzkMHHFSw7K9iEBCUhAAhKQgARqTkDxonjJYeKKlxyU7UMCEpCABCQgAQnUnIDiRfGSw8QVLzko24cEJCABCUhAAhKoOQHFi+Ilh4krXnJQtg8JSEACEpCABCRQcwKKF8VLDhNXvOSgbB8SkIAEJCABCUig5gQUL4qXHCaueMlB2T4kIAEJSEACEpBAzQkoXhQvOUxc8ZKDsn1IQAISkIAEJCCBmhNQvChecpi44iUHZfuQgAQkIAEJSEACNSegeFG85DBxxUsOyvYhAQlIQAISkIAEak5A8aJ4yWHiipcclO1DAhKQgAQkIAEJ1JyA4kXxksPEFS85KNuHBCQgAQlIQAISqDkBxYviJYeJK15yULYPCUhAAhKQgAQkUHMCihfFSw4TV7zkoGwfEpCABCQgAQlIoOYEFC+KlxwmrnjJQdk+JCABCUhAAhKQQM0JKF4ULzlMXPGSg7J9SEACEpCABCQggZoTULwoXnKYuOIlB2X7kIAEJCABCUhAAjUnoHhRvOQwccVLDsr2IQEJSEACEpCABGpOQPGieMlh4oqXHJTtQwISkIAEJCABCdScgOJF8ZLDxBUvOSjbhwQkIAEJSEACEqg5AcWL4iWHiSteclC2DwlIQAISkIAEJFBzAooXxUsOE1e85KBsHxKQgAQkIAEJSKDmBBQvipccJq54yUHZPiQgAQlIQAISkEDNCSheFC85TFzxkoOyfUhAAhKQgAQkIIGaE1C8KF5ymLjiJQdl+5CABCQgAQlIQAI1J6B4UbzkMHHFSw7K9iEBCUhAAhKQgARqTkDxonjJYeKKlxyU7UMCEpCABCQgAQnUnIDiRfGSw8QVLzko24cEJCABCUhAAhKoOQHFi+Ilh4krXnJQtg8JSEACEpCABCRQcwKKF8VLDhNXvOSgbB8SkIAEJCABCUig5gQUL4qXHCbeKPGybNmycMMNN4S5c+eOY7tkyZKwfPnycb+bM2dOOOyww+LvOG7p0qXx/2fNmhUWLlwYpkyZkuP+2IcEJCABCUhAAhIYCQKKF8VLDkNthHhZsWJFmD9/fuR5yCGHdBQv/K1d1PA7jkW4LF68OEydOjUgdLrtm+OG2YcEJCABCUhAAhIYRgKKF8VLDrtshHgpQPbyvHQTJIiVadOmjXlh2sVMjptkHxKQgAQkIAEJSGDYCSheFC85bFTxEkL0prSGjRUhY2vWrAmnn356mDlz5ph4WbVqVVi0aFFYsGBBmD59eo57ZB8SkIAEJCABCUhg6AkoXhQvOYxU8dJGGXEyb968GGa2xx57RPFC7gsChq1dvNx111057pN9SEACEhgpAptuumm47777RuqcPVkJSKAcgdf+x0/CFT+9vVwjI3707ttvHT79qqf0vIqtt956xK9y456+4qUD/yJUbPbs2X09L3/5y1827h20dwlIQAISkIAEJDAEBE648L/DV6/77RCcycY7hRk7PCh87oSn9zyBLbbYYuOdYA16Vrz0EC94XMx5qYGVewkSkIAEJCABCVROwLAxw8YqN7IQQuPFy+rVq8Nll10WjjjiiMi7PSzMamM5zNA+JCABCUhAAhIYdQKKF8VLDhtuhHhpLZVcQD3jjDNiHkuRlH/VVVeN8S7+VvzCdV5ymKJ9SEACEpCABCQwygQUL4qXHPbbCPGSA6R9SEACEpCABCQggSYTULwoXnLYv+IlB2X7kIAEJCABCUhAAjUnoHhRvOQwccVLDsr2IQEJSEACEpCABGpOQPGieMlh4oqXHJTtQwISkIAEJCABCdScgOJF8ZLDxBUvOSjbhwQkIAEJSEACEqg5AcWL4iWHiSteclC2DwlIQAISkIAEJFBzAooXxUsOE1e85KBsHxKQgAQkIAEJSKDmBBQvipccJq54yUHZPkoT+P6vfhfuuW9t6XZGuYEdHvzA8JiHbjnKl+C5S0ACEpBAjQkoXhQvOcxb8ZKDsn2UJrDnaV8Od665p3Q7o9zAsfvtHBYeMmOUL8Fzl4AEJCCBGhNQvChecpi34iUHZfsoTUDxEoLipbQZ2YAEJCABCVRIQPGieKnQvMaaVrzkoGwfpQkoXhQvpY3IBiQgAQlIoFICihfFS6UGdn/jipcclO2jNAHFi+KltBHZgAQkIAEJVEpA8aJ4qdTAFC858NpHKgKKF8VLKluyHQlIQAISqIaA4kXxUo1ljW9Vz0sOyvZRmoDiRfFS2ohsQAISkIAEKiWgeFG8VGpgel5y4LWPVAQUL4qXVLZkOxKQgAQkUA0BxYvipRrL0vOSg6t9JCageFG8JDYpm5OABCQggcQEFC+Kl8Qm1bE5w8ZyULaP0gQUL4qX0kZkAxKQgAQkUCkBxYvipVIDu79xxUsOyvZRmoDiRfFS2ohsQAISkIAEKiWgeFG8VGpgipcceO0jFQHFi+IllS3ZjgQkIAEJVENA8Qf0VF8AACAASURBVKJ4qcayxreq5yUHZfsoTUDxongpbUQ2IAEJSEAClRJQvCheKjUwPS858NpHKgKKF8VLKluyHQlIQAISqIaA4kXxUo1l6XnJwdU+EhNQvCheEpuUzUlAAhKQQGICihfFS2KT6ticYWM5KNtHaQKKF8VLaSOyAQlIQAISqJSA4kXxUqmB3d+44iUHZfsoTUDxongpbUQ2IAEJSEAClRJQvCheKjUwxUsOvPaRioDiRfGSypZsRwISkIAEqiGgeFG8VGNZ41vV85KDsn2UJqB4UbyUNiIbkIAEJCCBSgkoXhQvlRqYnpcceO0jFQHFi+IllS3ZjgQkIAEJVENA8aJ4qcay9Lzk4GofiQkoXhQviU3K5iQgAQlIIDEBxYviJbFJdWzOsLEclO2jNAHFi+KltBHZgAQkIAEJVEpA8aJ4qdTA7m9c8ZKDsn2UJqB4UbyUNiIbkIAEJCCBSgkoXhQvlRqY4iUHXvtIRUDxonhJZUu2IwEJSEAC1RBQvCheqrGs8a3qeclB2T5KE1C8KF5KG5ENSEACEpBApQQUL4qXSg1Mz0sOvPaRioDiRfGSypZsRwISkIAEqiGgeFG8VGNZel5ycLWPxAQUL4qXxCZlcxKQgAQkkJiA4kXxktikOjZn2FgOyvZRmoDiRfFS2ohsQAISkIAEKiWgeFG8VGpg9zeueMlB2T5KE1C8KF5KG5ENSEACEpBApQQUL4qXSg1M8ZIDr32kIqB4UbyksiXbkYAEJCCBaggoXhQv1VjW+Fb1vOSgbB+lCSheFC+ljcgGJCABCUigUgKKF8VLpQam5yUHXvtIRUDxonhJZUu2IwEJSEAC1RBQvCheqrEsPS85uNpHYgKKF8VLYpOyOQlIQAISSExA8aJ4SWxSHZszbCwHZfsoTUDxongpbUQ2IAEJSEAClRJQvCheKjWw+xtXvOSgbB+lCSheFC+ljcgGJCABCUigUgKKF8VLpQameMmB1z5SEVC8KF5S2ZLtSEACEpBANQQUL4qXaixrfKuN8rwsW7Ys3HDDDWHu3LnjKKxevTqcfPLJ4cYbb4y/P+OMM8LMmTPH9uG4pUuXxp9nzZoVFi5cGKZMmZLj/tjH/QQUL4oXHwYJSEACEhhuAooXxUsOC22EeFmxYkWYP39+5HnIIYeMEy9r1qwJp59+ehQrhx12WFi1alVYtGhRWLBgQZg+fXrgWITL4sWLw9SpU8OSJUtiO+0CKMfNanIfihfFS5Pt32uXgAQkMAoEFC+Klxx22gjxUoDs5HlBrJx99tnhtNNOi+KkXcwgVqZNmxaFDVu7mMlxk+wjBMWL4sXnQAISkIAEhpuA4kXxksNCGy9eOomRwrty/PHHj/PKcEPaPTM5bpJ9KF6wgWP32zksPGSG5iABCUhAAhIYSgKKF8VLDsNUvKxYEfDItOaxtIsXvC5FDky7eCFfxq16Avuf9b1w15/vrb6jIe7hZTN3CKf83c5DfIaemgTWE9h8883DPffcIxIJSKBBBF7/2evC13/2uwZd8YaXutt2W4WLjnliTwZE+rhNnoDipS2nBZQT8bysXbt28vQ9cmACT3jL5eHONc0eCOF5WfC83Qdm5o4S2JgEeDdusskmG/MU7FsCEshM4LgLfhC+svKWzL0OV3ePf+Q2Yflr9+t5Ur4by92zxosXc17KGVCuo815MWwsl63ZjwQkIAEJTI6AYWOGjU3OciZ2VOPFi9XGJmYwG2tvxYviZWPZnv1KQAISkMBgBBQvipfBLKXcXo0QL62lkgtcrWu5uM5LOSPKcbTiRfGSw87sQwISkIAEJk9A8aJ4mbz1DH5kI8TL4Djcc1gJKF4UL8Nqm56XBCQgAQmsI6B4UbzkeBYULzko20dpAooXxUtpI7IBCUhAAhKolIDiRfFSqYHd37jiJQdl+yhNQPGieCltRDYgAQlIQAKVElC8KF4qNTDFSw689pGKgOJF8ZLKlmxHAhKQgASqIaB4UbxUY1njW9XzkoOyfZQmoHhRvJQ2IhuQgAQkIIFKCSheFC+VGpielxx47SMVAcWL4iWVLdmOBCQgAQlUQ0DxonipxrL0vOTgah+JCSheFC+JTcrmJCABCUggMQHFi+IlsUl1bM6wsRyU7aM0AcWL4qW0EdmABCQgAQlUSkDxonip1MDub1zxkoOyfZQmoHhRvJQ2IhuQgAQkIIFKCSheFC+VGpjiJQde+0hFQPGieEllS7YjAQlIQALVEFC8KF6qsazxrep5yUHZPkoTULwoXkobkQ1IQAISkEClBBQvipdKDUzPSw689pGKgOJF8ZLKlmxHAhKQgASqIaB4UbxUY1l6XnJwtY/EBBQvipfEJmVzEpCABCSQmIDiRfGS2KQ6NmfYWA7K9lGagOJF8VLaiGxAAhKQgAQqJaB4UbxUamD3N654yUHZPkoTULwoXkobkQ1IQAISkEClBBQvipdKDUzxkgOvfaQioHhRvKSyJduRgAQkIIFqCCheFC/VWNb4VvW85KBsH6UJKF4UL6WNyAYkIAEJSKBSAooXxUulBqbnJQde+0hFQPGieEllS7YjAQlIQALVEFC8KF6qsSw9Lzm42kdiAooXxUtik7I5CUhAAhJITEDxonhJbFIdmzNsLAdl+yhNQPGieCltRDYgAQlIQAKVElC8KF4qNbD7G1e85KBsH6UJKF4UL6WNyAYkIAEJSKBSAooXxUulBqZ4yYHXPlIRULwoXlLZku1IQAISkEA1BBQvipdqLGt8q3peclC2j9IEFC+Kl9JGZAMSkIAEJFApAcWL4qVSA9PzkgOvfaQioHhRvKSyJduRgAQkIIFqCCheFC/VWJaelxxc7SMxAcWL4iWxSdmcBCQgAQkkJqB4UbwkNqmOzRk2loOyfZQmoHhRvJQ2IhuQgAQkIIFKCSheFC+VGtj9jSteclC2j9IEFC+Kl9JGZAMSkIAEJFApAcWL4qVSA1O85MBrH6kIKF4UL6lsyXYkIAEJSKAaAooXxUs1ljW+VT0vOSjbR2kCihfFS2kjsgEJSEACXQi89ZKV4dwrf9loPttM2Tz86LTnlGKgeFG8lDKgAQ9WvAwIyt02LgHFi+Jl41qgvUtAAnUmoHgJQfGSxsIf/8htwqUn7Z+mMVvpSEDxUrFhPHfJN8PKm++ouJfhbv7gGduFDx41s9RJKl4UL6UMyIMlIAEJ9CCgeFG8pHpAFC+pSHZvR/FSMWPFSwiKlzRGdux+O4eFh8xI05itSEACEpDAGAHFi+Il1eOgeElFUvFSPckuPSheFC+pjE/xkoqk7UhAAhIYT0DxonhJ9UwoXlKRVLxUT1Lx0pWxnpc05qd4ScPRViQgAQm0E1C8KF5SPRWKl1QkFS/Vk1S8KF4qtjLFS8WAbV4CEmgsAcWL4iWV8SteUpFUvFRPUvGieKnYyhQvFQO2eQlIoLEEFC+Kl1TGr3hJRVLxUj1JxYvipWIrU7xUDNjmJSCBxhJQvCheUhm/4iUVScVL9SQVL4qXiq1M8VIxYJuXgAQaS0DxonhJZfyKl1QkFS/Vk1S8KF4qtjLFS8WAbV4CEmgsAcWL4iWV8SteUpFUvFRPUvGieKnYyhQvFQO2eQlIoLEEFC+Kl1TGr3hJRVLxUj1JxYvipWIrU7xUDNjmJSCBxhJQvCheUhm/4iUVScVL9SQVL4qXiq1M8VIxYJuXgAQaS0DxonhJZfyKl1QkFS89SS5ZsiQsX7583D5z5swJhx12WPzdsmXLwtKlS+P/z5o1KyxcuDBMmTJloLvz3CXfDCtvvmOgfeu6k4tUprmzipc0HG1FAhKQQDsBxYviJdVToXhJRVLx0le8sMPcuXM32G/FihVRuCxevDhMnTo1IHS67dupE8VLCIqXNA+y4iUNR1uRgAQkoHjZ0Aa2mbJ5+NFpzyllHK8+f0X4yspbSrUx6gcrXqq/g5usXbt2bfXdDHcPvQQJf5s2bdqYF6ZdzPS7MsWL4qWfjQz6d8XLoKTcTwISkMDECOh50fMyMYvpvrfiJRXJ7u0oXkKI3pTWsLEiZGzNmjXh9NNPDzNnzhwTL6tWrQqLFi0KCxYsCNOnT+97hxQvipe+RjLgDoqXAUG5mwQkIIEJElC8KF4maDJdd1e8pCKpeBmYJOJk3rx5Yf78+WGPPfaI4oXcFwQMW7t4ueeee3q2/Q/v+07jc14O2v0R4f0ve/LA94Ad2x2Ce73ta+HONb1ZT6iDEdz5FfvsFN48+29H8Mw9ZQlIQALDTeBtX7w+fPQ7vx7uk6z47Agb+8GpB5bq5YQL/zv85//cWqqNUT8Y8fL5OXv3vIzNN9981C9zo56/npcO+ItQsdmzZ/f1vNxxR+9k/Jd85Ifhulvu2qg3eWN3fuCuDw1n/eOMCZ3GJptsMm7/fRZ/u/Hi5chZjwrzDurv7ZsQaHeWQEUENt1003DfffdV1LrNSiAtgXdevip8/Pu/SdvoiLWGeLny5H1KnfVJn742XPHT20u1MeoH77791uFTr+w9YbvNNtuM+mVu1PNXvPQQL3hczHkpb58m7JdnSAuGjaXhaCsSkIAE2gkYNmbYWKqnwrCxVCS7t9N48bJ69epw2WWXhSOOOCJSag8Ls9pYeSNUvJRnqHhJw9BWJCABCXQioHhRvKR6MhQvqUgqXroSKJLyr7rqqrF9zjjjjLEcF37pOi/lDFHxUo5fcbSelzQcbUUCEpCAnpcNbcBSyWmeC8VLGo69Wmm856VqxFYbs9pYKhtTvKQiaTsSkIAExhPQ86LnJdUzoXhJRVLPS/Uku/SgeFG8pDI+xUsqkrYjAQlIQPHSbgN6XtI8FYqXNBz1vFTPsWsPihfFSyrzU7ykImk7EpCABBQvipdqngLFSzVcW1s1bKxixooXxUsqE1O8pCJpOxKQgAQUL4qXap4CxUs1XBUv1XMd60HxonhJZW6Kl1QkbUcCEpCA4kXxUs1ToHiphqvipXquipcWxlYbS2Nwipc0HG1FAhKQQDsBE/ZN2E/1VCheUpHs3o5hYxUz1vOi5yWViSleUpG0HQlIQAJ6XvS8VPMUKF6q4arnpXquel70vCS3MsVLcqQ2KAEJSCAS0POi5yXVo6B4SUVSz0v1JLv0oOdFz0sq41O8pCJpOxKQgAT0vOh5qeYpULxUw1XPS/Vc9bzoeUluZYqX5EhtUAISkICel/ttwHVe0jwMipc0HHu1Ys5LxYz1vOh5SWViipdUJG1HAhKQgJ4XPS/VPAWKl2q46nmpnqueFz0vya1M8ZIcqQ1KQAIS0POi5yXpU6B4SYqzY2N6XipmrOdFz0sqE1O8pCJpOxKQgAT0vOh5qeYpULxUw1XPS/Vc9bzoeUluZYqX5EhtUAISkICeFz0vSZ8CxUtSnHpeqse5YQ96XvS8pLI7xUsqkrYjAQlIQM+LnpdqngLFSzVc9bxUz1XPi56X5FameEmO1AYlIAEJ6HnR85L0KVC8JMWp56V6nHpeOjE+eMZ24YNHzSyFf8/TvhzuXHNPqTZG/WDFy6jfQc9fAukJfPHHN4fzv/Pr9A2PWIvnHvPUsOUWm036rF2k0kUqJ208bQcqXlKR7N6OCfsVMzZszLCxVCameElF0nYkUB8CH/7mL8OiS1fW54ImeSU/Ou05gXVKJrspXhQvk7Wd9uMUL6lIKl6qJ9mlB8WL4iWV8SleUpG0HQnUh4DiZd29VLyUt2kXqSzPkBYUL2k49mpFz0vFjBUvipdUJqZ4SUXSdiRQHwKKF8VLKmtWvKQhqXhJw1HxUj3Hrj0oXhQvqcxP8ZKKpO1IoD4EFC+Kl1TWrHhJQ1Lxkoaj4qV6joqXHoxN2E9jgIqXNBxtRQJ1IqB4UbyksmfFSxqSipc0HBUv1XNUvCheKrcyxUvliO1AAiNHQPGieElltIqXNCQVL2k4Kl6q56h4UbxUbmWKl8oR24EERo6A4kXxkspoFS9pSCpe0nBUvFTPUfGieKncyhQvlSO2AwmMHAHFi+IlldEqXtKQVLyk4ah4qZ6j4kXxUrmVKV4qR2wHEhg5AooXxUsqo1W8pCGpeEnDUfFSPUfFi+KlcitTvFSO2A4kMHIEFC+Kl1RGq3hJQ1Lxkoaj4qV6jooXxUvlVqZ4qRyxHUhg5AgoXhQvqYxW8ZKGpOIlDUfFS/UcFS+Kl8qtTPFSOWI7kMDIEVC8KF5SGa3iJQ1JxUsajoqX6jkqXhQvlVuZ4qVyxHYggZEjoHhRvKQyWsVLGpKKlzQcFS/Vc1S8KF4qtzLFS+WI7UACI0dA8aJ4SWW0ipc0JBUvaTgqXqrnqHhRvFRuZYqXyhHbgQRGjoDiRfGSymgVL2lIKl7ScFS8VM9R8aJ4qdzKFC+VI7YDCYwcAcWL4iWV0Spe0pBUvKThqHipnqPiRfFSuZUpXipHbAcSGDkCihfFSyqjVbykIal4ScNR8VI9R8WL4qVyK1O8VI7YDiQwcgQUL4qXVEareElDUvGShqPipXqOihfFS+VWpnipHLEdSGDkCCheFC+pjFbxkoak4iUNR8VL9RwVL4qXyq2srHj541/uDcd+9PuVn+ewd3DU3juF5+65w7CfpucngYEIKF4ULwMZygA7KV4GgDTALoqXASCV3GWTtWvXri3Zhof3IPDcJd8MK2++o9GMDp6xXfjgUTNLMdjztC+HO9fcU6qNUT+4rHi54+6/hie85fJRx1D6/BceMiPA0k0CdSCgeFG8pLJjxUsakoqXNBx7taJ4qZix4iUExUsaI1O8pOGoeEnD0VaGg4DiRfGSyhIVL2lIKl7ScFS8VM+xaw+KF8VLKvNTvKQhqXhJw9FWhoOA4kXxksoSFS9pSCpe0nBUvFTPUfHSg7GelzQGqHhJw1HxkoZj2VZ+98e/hOtvubNsMyN//BN23DZstcVmk74OxYviZdLG03ag4iUNScVLGo6Kl+o5Kl4UL5VbmeIlDWLFSxqOZVv58rX/F46/4Adlmxn54y89af/AYGeym+JF8TJZ22k/TvGShqTiJQ1HxUv1HBUvipfKrUzxkgax4iUNx7KtKF7WEVS8lLUkxUsagiEoXtKQVLyk4ah4Kclx2bJlYenSpbGVWbNmhYULF4YpU6YM1Ko5L+a8DGQoA+ykeBkA0gC7KF4GgJRhF8WL4iWlmf3otOfEwfdkt7desjKce+UvJ3t4LY5TvKS5jYqXNBwVLyU4rlixIgqXxYsXh6lTp4YlS5bE1ubOnTtQq4oXxctAhjLAToqXASANsIviZQBIGXZRvCheUpqZ4qU8TcVLeYa0oHhJw1HxUoIjYmXatGnhsMMOi620i5l+TSteFC/9bGTQvyteBiXVez/FSxqOZVtRvCheytpQ6/GKl/I0FS/lGSpe0jDs14rrvPQgtGbNmnD66aeHmTNnjomXVatWhUWLFoUFCxaE6dOn9+MbFC+Kl75GMuAOipcBQfXZTfGShmPZVhQvipeyNqR4SUnQnJdUNPW8pCLZvR3FywDiBa8LAoatXbxccMEFPe/S0lUPDjevmXwZzOpNoPoedn/QX8IR0+4q1dHbrpsa1ty7Sak2Rv3gfR66Jsze/k+Tvoy77wnh7dc/ZNLH1+VAGMJystuf79sk/O+aycfWT7bfYTvuEVvcE7bafG3X03rQgx4U7ryzeynklXf8TbjoxgcN22VlP58THvuH8MgH3jvpfq+8bUr40i1bTvr4uhz45t1Whwdu1t0e+13nF2/eMnznd4PlsvZra1T/PmXT+8Kpu/++1Ol/4oatw3V3blGqjVE/eIcp94Q50+/oeRlHHnnkqF/mRj1/xcsA4qWX5+X888/fqDfQziUgAQkMI4Gtt9463HVXuUmLYbwuz0kCEpBAWQJHHXVU2SYafbzipc/tL5vz0mjr8uIlIAEJSEACEpCABCSQkIDipQ/MstXGEt4rm5KABCQgAQlIQAISkECjCSheBrj9ZdZ5GaB5d5GABCQgAQlIQAISkIAEBiCgeBkAkrtIAAL33HNPuPvuuwOJyG4SkIAEJCABCUhAAvkJKF7yM98oPf7lL38Jl19+edh7773DQx/60I1yDqPe6Y033hhLZO+3337hZS97WdhySyv8TPae/uEPfwjf+MY3wt/93d/JcbIQPU4CEqglge9973thq622Co9//OPDJps0u8rmZG8wlWGXL18eXv7ylzvmmSzEIT5O8TLENyflqX37298O73jHO8JjH/vYuHaN3oPJ0f3Tn/4UPvGJT4QrrrgivOpVr4pCZostml0WcqIk165dGwjFfP/73x/mzJkztobSRNtx/3UE7rvvvnDllVfGD/Tuu+/uYGeChgG/H/7wh3EBYranPOUp4UlPelLYfHPLYU8EJRNkDLp//OMfx3fi/vvvH3bZZZew6aabTqSZxu976623hre85S2xzPjjHve48JrXvCY84hGPaDyXiQLgO/PJT34yfOpTnwovetGLwuGHH+63eqIQh3h/xcsQ35xUp8Ys92mnnRae/OQnh5tuuin8y7/8S5gypdn17Muw/eMf/xje/va3h9/85jfhAQ94QHjta1/rDNkEgOLBetvb3hamTZsWB9uso+Q2OQIMGD/ykY9EMf3gBz84TlDoWR2cJc/y+973vnDdddeFf/zHfwyUd/7qV78aSzy/8Y1vdNA4IMrbb789PtMIwUMPPTQedckll4Ttt98+nHjiiZGrW38CDLjPPffc8Lvf/S687nWvC9/97nfj8803BlHtNjiB//u//wsLFy4Mxx13XJg6dWpcVBy+eLL0Zg3OcVj3VLwM651JeF7Mcv/85z8Pz3/+88NnPvOZMfHCw33RRRfFhxsXtdtgBL785S+H//zP/wz/7//9v/DrX/86vPe97w0vfelLw7Oe9azBGmjwXvfee28455xz4seEgeMTnvCE8LSnPS0Swav1zW9+My4I6wC8v5H8/ve/D4sXL45eVGa5v/SlL4X58+c7MdEfXdyjGCgiXE499dSw7bbbjv3+61//evQOMvh5+MMfPmCLzdwNAf2ud70r2h1CpZgYI0eQ783KlSujEPQb098+2hfB5gjsk28MtogYdOtPoFUEvv71rx/zovJMf+tb3wr8bscdd+zfkHsMLQHFy9DemjQnVsxyv+ENbwh8ZD796U+HefPmhb/5m7+Jg0g+NLhUGTSaf9Cf+W233Rb+9V//NbDAVDHoZraRzfCI/vx+9KMfhQ9+8IPRE0j43b777hvFyrXXXhvtEW8WeVmtH5z+rTZvDzgx0z1r1qwY033ZZZeFX/ziF2Hu3LnNgzHJK77hhhuiHfJuxAPYujHwJqzxOc95Tth1110n2UMzDvvv//7vOLjGHtsH14Q+wfGYY47Ri9XHHAoRSGj3P/3TP415BxiIn3XWWTGEDK8WE0CrV6+OEzx6EDpD/dnPfhYF9Zvf/Oaw8847x50YCzHh+OxnPzvmW86YMSO8+tWvNudyRF9TipcRvXGDnHYxy41AeeUrXxl+8IMfjM0m/vKXv4yDRWYccekXeRzkIOyzzz4OxDsA7jabgwcBAQNHPybdLXPNmjVh0aJF0Utw4IEHhve85z1xcHj99dfH8IjnPve5MT659YMziJ03bR+eY8IWEXmEkxC6SOjTIx/5SEPwJmAMFDD5r//6rzij3SmMlmfaEJP+QD/84Q9Hrym22On9x3dos802i+9IxAwb3kIne8azJV/o/PPPj/kuD3vYw8b9ke/zX//61ygCi/cok46EgruNJ9BJBBZjIfYkh4ifP/vZz+oVHGHjUbyM8M3rd+r/8z//Ez7wgQ/EClm8DElIxcNy/PHHh3e+851RpDB4LDbyYc4444z4kfnnf/5n8zjaALe79AnbYQBOSB4bg0c8Bvy32G655ZZYYvlRj3pUv9tV+78zUPzKV74S7ZENW8NbwGwiwoXZxfZZx9pDmcAF8lziYSEJ9dhjjw3f+c53wq9+9atYOOJzn/tczNkoBjMIbfI28LCa39YZMiEkeF/0Vk3ACDvsumTJkpi/1i13DVtEcDMTzv+TzM/g8eijjw4HHXSQhRFCiKLurW99a/QKtH6Twc3kGB5CWB188MGRHeGiTADhtXZbRwDb4t/3v//9DUQgYyFE4UknnRQnfRDZ5GnxLSK36G//9m/juMfJitGxJsXL6NyrCZ0pszMMDlsFCuKFqkRU0qGEIC7U1qpjuFV5gfKCJKeDDxIhKTvttNOE+q7jzggQhMpDHvKQ6MXiA8LPzDiSZ8AHmQ/05z//+bH47mIGiHKXTU9KJwGVDzADbfJcmEUkHp6wJxIp22cdr7rqqvC///u/MZTRynjrnqjf/va34aMf/WgUKYRC8KEm3A6vC+GM//Zv/xYe85jHxNA7EvfZHzuF8QknnGDSdNuLiUEOYbSEgXbKx+CZR2zzTJMPQ6io1dw2fLsjApmEYBCIh6V9gzO2iUhk4IjHhYEjnn/ENRNlTc+HobgBngA80+0TXUz6kJvK3wqPDIKRiYoDDjgg4uY7xPuSyZ+merQYv8CIAkWveMUrxkQgYyEqrO6www6BiBM28n+vueaaQHgZf6PYCXZMBMCb3vSmmJPpNtwEFC/DfX9KnR0zNoSUFCU/ES98iPk97mcGkcXWya3KC5MkYGZ4mr6uCXHdhEcg+Chb+dOf/jTwAWEQSWlLPsBFtSdC7xB+DMiZJWfQzt+avmF3eAHaBzh8bAjdIQziGc94RhyUUwiBqk8kTmN7zEYaktfZgvAI/vu//3schMOWCQgGiS94wQviAXhl+FCbzD+eXzHBg+DDxlpLnvM+/NCHPhSTpQmHYmOwjY0+/elPb/qjPO76ESIMAPEMzJ49e9zguXi28Sj8wz/8w7jjEIdLly6N3Mk9YOskfpoAm4kuJgz55hJWizcaLggXviFUCG21O75F5LzAFdHDZCT8yZVp8mQPuUCEHt98880xtxdRDMOLL754bIkIlo0gD4tnGY8/36RiDTe8L3yvDASVtQAAIABJREFUmVBzG24Cipfhvj9Jz44Yb2bA8Ky0J0TjVj3zzDPj4PzRj370WL+ua7IOBQPqP//5z2MhOEUIHrONxYw4A25maMnZ4CXILNALX/jCscT+pDezRo0x4wVPBAwfbEIoEN18VKiIR34HoY54sNw2JEDyKR4C8tfg+IUvfGGcN4GBEbPfDH6aOjjsZjeE1jGQoZAEITgsPMvA8Y477ojvytb3Iftgq1TOMhRvPFEmcN797ncHQmmZFGOyhtlt8tnwFpLMX1Rzaz2SQSOz38985jPjfeD5b/JEGd9bvtN4YhCF2CQTja2VsfgW4bXmOUdkIxiZqGiyaGl/vpmY4BuCx59n+CUveUmcGCs2JiMJwT3llFOi2GZiosjJOuKII6IH2224CShehvv+JD07Pr6EmOAWLSpw0EHhVuVF2Sm8yXVNNrwNeF5IrmQgw0ejCOHhY/LEJz4xDnII6SkquyEOeSEyOHJbT6Coxc/s9m677RYFNOF3DGIInyBED88B4Y+ESOD2ZxCkW389wy9+8YtxppE8GGZkYcOsYuuGffLBZlYSG+XvhJM1NcSk/Rkk7O7qq6+OExQMBuHEew+PQOHxgx/PNR4sNgbmbMTLK2bWTfBgh4R8El6LB4Fnl7wsJnngSEgj4U2sWdJue7wLeF/ikSHErKjm6PtyHQEG15Sd5hknTI/nl8F3q+3xzcELSx4mExV4YLHh1jzMJvH8yU9+Eie/WMagVRS35l/yTSE3mOgJhDZMeYcy6YMnjNxCoilaI1WaxHBYr1XxMqx3pqLz6pSU1upW7RTe5LomG94MPrB8RChyQPUSBtrFIIePMGEUfLBZYbq1XLXu6PEsmWnkA8Nghg8vTAl7wg4Z6BC6A09mbon3xsvAaugmWY/nWFR0YtaWELF2zyqztISMIhIRfx//+McjT3KQXEl+w+e7XQQWOW94pRlU41Vl/RcmLvAc4DX02d6QI88r34+iohvChcIchJO1Lu7bGrZMvgLCRkG4jie2Rwjyxz72sTj5xTPL7wohXXAiXwNvId+jYs0xclzPO++8Ri9yyeQsEzx4qwiB32677WJ1VTwsRKEUFTARg3gPES+F55VnnIlKvkk+3xUNSifZrOJlkuDqclh7vkGnGUnXNel8txGCfDDwwBTeKWa4ivVz8BqwT+vPCBw+1AzaLa08nisfCTyDzGyzXkSnohMIF+KXqRLDR7tVjLM/oRbcg6bmx2CHVBLko0vYDnHx/I5nmEo7xXom/I71dpiNJIfLbTwBPKWEMZ188slxYgLhR04CIaEIG7yreKmxMzwwDICe97znxfAUvVnrWRb5MCziW+Rs8MwyoCakpxDZ3cKWtcsQPQCIEELHWOsFmyPPDe8guTC8B/Ec8k7EJturlcEWwUj4VJOrXpIPQ7VVvINEmVDwgJ+Z8OG5LhbtJgKA37N4NwLRCpjD+RQqXobzvmQ7K9zLeF6OPPLIcQmrnEC3dU2yndwIdsSHgkR+kv4YgLeXq+aS+N3ZZ58dSzc6cFx/k5lNJMzkwgsvjJ4YfiYnobUqHh9tBt3kwDCre+mll8ZBI4NwQioQkoif9nUSRtCUJn3KDHaYqYUNOVc8xxTeKKriFQ0XIhoxWFQhZJCJ4Gn61lrJjRAdxAqeVAaJhXewyOHgdzzvDHYILUFE483So7XOinhmqXxJcjT/8Kgi9hhsM5tdTFK0CsJO9seEjx6Z9UyLIh3YIQNw8t6ww/bKbTznDMYRj3qzNhTWTDLy3GKnvCPxxlBlFQ92t3V3mv5+HIbrV7wMw10Y0nNoX9ek12kya8FsGiKoNblwSC+tstP62te+Fj+wJKAyiKRkLWEmxWwYv8O1v+eee8bqO3Aj5pZy1JRybKrHoPWGUEYZLnAqSivzd8QM8fSscYDXilnGopQyngQKJ8BRhuPNG5GHhxAvQmvCPrPiCMN99913bLFQwslYcb41J66yh2UEG24t1IGdFRM8DMCLxe9Yz4TZWkS1izGuu8nYGvkDeK/YKIrAoBGG/cKWCzMhvJRJH0pWN30hZdYP4z3IYJv8DCbMmLBhEmfQjYkhcgtbq+wNemwd9sOeKGTCmIWJBr7NeGeYUIRNt3V36nDtdbgGxUsd7mIF19C+rkmvAWFRVpQZSmJFqQpF8nDTk9N5ETITRrhOES9LmUZCUJh1JF+GZEK8DLAjJIDZW2fH1hk0ydOsA0F4CaVAmV1kjSKEDcmVBVMGkAyMmNFtz/Wo4NEYuSaL0B1CmooF2rgISrDyj4EgzyseF8IkmOGeyCBo5ICUOGEmGgjLQ6jgKeC5RWRT6Y18GDxeJP/utddeMWn67rvvHlcghfcqeR9M8DQxvIyQMSYaHvjAB0aPC/8YJBZl0nvdmiI0l1Bnnv0TTzwxvh+auBXJ+4SBIV4It8XT316ooxsbjserQDJ6a+5RE1l2uubWCph+j4fTKhQvw3lfNvpZta9r0uuEWuOVSYaj7jyDdJI0ib1v6laEQ5CDwcARkUe4BLX48cZQDpPZH2a62QiHYqaWmSC39QQQeSTzM8hGELevLt1eEIEBJGFSVC5ikOQW4oCZuHcG3yStEhZBciqDHWYdqbKz6667Rhtl5hGvlhzHWw6DZ+yP8ETyYbBLNp5tnmkmbpisIPSO5xtRzSAIEVN4vbDVYsHGpicAk0BNEjqTXeRk9XtWWwvHcB8s+73ePnlW+e4yKTZoyeQiNPK9731vXJeMksxNzokpaLZWwLTC2PB+PRUvw3tvNuqZta9r0u1kilXkW5PaiplwPA/MUDb5I8MsNpWeiDkmrImXIYNqXPX8TNgO9edZNR1PA/8oM+rWnQCzjHxsCT0pFrojZIIBZOHuZ7DOQHybbbaJlclcI2YdTwQ1zyNsCvFCEj8zsUw4kG9EKApx9MyIFxyZ3WWmu6kc8aAw8YCXlDU18JrA69Of/vTYIrSt5dGLUBw8W6yBwuw24ZCIF0Lymuh16fREwwbhjBerPdG8dX/yitoLx/iOXE+gqH5J8Qhys3g/Dho+ix3zTuVbTr5Hk9fZgShefL7NlEc2b214nzLFy/Dem5E4s27xytT2Z6aXD45rcoQ4cGFwQzlGZsZuuOGGWO2EkB5Cx8iBOfroo7t+cBCEDMz5SDFD2WRX9re+9a3oQcBDxdpFeKyY8UbAIBR//OMfR28WISUkojPDS+nqQWckR+LBS3CSzGTz/CKmi+TzonobXsFWjoSXXHDBBbFkNeIa8cMib0996lNj6dEmbCzAiMeFxWjJrcIDg0elCGVsLY8ODwbmFOWguASTFrAm/LG1AEUTuJW9xk6FY8j5QGiTN9OpvH/ZPkfx+KL6JWKQ9yM2x3ux13uvtdoozzIlhK+77rpot+QVNnGDI/8ULsN99xUvw31/hvrsepVZJv+AxFVKEDZlcDPozSri5snPYIE7CiMg9Jjp7iT0itWrKSXM3+FOkjWDoqZ+YBg8IwiLGv3M2uLu52ONp6UoCUxYHoPFIn+GIgnU92+y+CvslA804XUU2mAAjleBmVfsrZ0jYptwJ8JSqGaEaCRmvqiqN6jtj/p+DKSZleX9Ro5aMTCEB4O+F7/4xXECoj2Rn4mH1pCyIgQKW21ygZNB7KG9cEzBlskgJiy4D+2r0A/Sbp33wcPK1u891ym3g/dqU3OJ6mwTdbs2xUvd7mim6yniuVkNvViArLVrZmWpvMUHmxch8eAkBA/qys50GRutG3I4iDVm4AIbki1J7G+f7SlCy5hFI6macBTc+5QUxqvAYLKpeUV8oPEIkIT+gAc8IJx77rlR0LCiNKFRRdEJBjfkcDCApPrbHnvsEfMS3NYRgBnCmFwXBoPtHIswUNZHICSFHDc8qnB84xvf2PjCHJ3siAF3kcjPM84gkd8VBSWKfAPK3SIamx6q04khni48LBQ44dtRVCdjUVAme/juYK9XXHFFLDzB5I85G4O/1QhhhBlrxRSTPUV5eiYoFDCDs3TP/AQUL/mZ16JHwp3wqjCAaa8sxswtHxZmuMnnoF468fV4CagSRdy8ImZd6V9CUPAKkCzdLlyKGUZmvclDaJ1FK/6GkDnhhBNqYVNlLgKvy5lnnhk/xAhBNpJYGdQgoIvQEsIiyF+gBDMM+Wf+wXrynTi2DsSpqEX4E+KZQTelb6m0tcsuu5S5fbU7lpAmnldEM4n9hNsRytiepH/nnXeG97znPTGMFGHd5PWJ2o0A4YL3HjasE8MkRJFjyTcEtmwUUiDMiSIUJlgP9ijhuWbxZDbyUnkHUlKdSnnFBBmFKA455BDDpwZD6l6ZCSheMgOvU3ckoxPDzUCGCkZ8UEisZIDIOicMEIsBOYNEZswYYOLiL1Zb5sPDx4nwKQeR462DEsEIRD4uhPW0b8xM4n0oBut1sq2y18KgkFlFPr4IaDZENYNIeDLTyCCc/JlTTjklem7cNiRQeK+Y0e5UUQv7I/zsQx/6UFyAUBEznmExSETIFJ4DeCEIv/jFL0aBTagedop3gTA+9sWb2C/kpwn2WnioWI8DcXL11VdvMCFBZUy8hTzv5G7xDSLnkqR1vNJOlG1oKa0VQpmQ4GcE4Jve9Kb4reG5ZsKR7/h+++3XBFPzGkeMgOJlxG7YMJ4uA0VmbaioRVng2bNnx1kywkyWLl0a+DuLCT772c+OScBf/epXx8oD8/8MIAl/8mM9/u4WuTB4Dlz1fGKWjzChig4J1cwk9stBmFjrzdmbQQ0FEXg+SdSnEg9rmxQV8yDRycPVHEK9rxTxxwKhTOxQaANxcvHFF8cQPcQgA8ViggdRA2+8WSyGiReRoh5u6wgQ9skAm8qMlKJma52kIA+QRVZhzN+pvDVjxgzXzmozIDz9hDTCBu8VdkcYHu9IQsmY7GEi4utf/3pM/Nez7xM4jAQUL8N4V2pwToV7/zGPeUwULXzAL7300viiPOigg+L6EgyK8NqQUL3//vvX4KrTXsIgRQ/YBwHIhkA05nvdPeBDzMCxiNtuD30q1t9oXdQSLyLHUArXbT1HBjtMLOAJJNeFsr+EORaDR4omPP/5z4/r8BS/Iw+BWVtKVbutI0B+FrPZVBXE09LqaW7PNWDgTU4c4aI+0+stqCi8UbCj8AGTZohrwpOpiIeN4nGBqWtndX76yHPDI4VwLrwsiGmq6DHpgwjEa/iKV7wiRkng3eIfIpxw0aIUOK0TAcBzbuSEb7qcBBQvOWk3qC9eaMySsTZEEedN5SfCS8iHwZOAq5+PNAnrlGmk9G3rS7FBuDpeahGygwBE7LV/HJjxXrJkSXje854XZ3IRgjAsQvKazq+4fgQznPgwd8tB6FSpTH7jCRB2Rzlg8tZ22223+MfW0tTFs9s6oNSbOp4ha1996lOfigPBYt2cYnFLPNVsrHnC807JW57nIplaexxPgPAwvNLHHXdcZETO0MyZM6Pnv9hgS46bFS+7Ww8ihfcjoqQIsSUkHFGILZIHA0cENwKRCTPCy/iGF/cA70xT14Dyudw4BBQvG4d77Xtl5pvVk5ltJNabgSMvSGZjKWvbOhPOhwV3NftQBphKJw561plIsQ4MITtUJCLxnEEiwgYRyCCn+ODAtAjxcU2T8Y9Y60wja5iw6jmVs1rL2nIEtlqEO/JhprQynkNF9TqeP/zhD2OCOWEliGYGj8zOUriDDWZ4YijjzYASmyR0lNwtQx/X2yRJ/GeffXZkiDeB9yReFmbCyQ3kb+Rv8IzjPWQASUiuXsH1DJmUYBHVHXbYIYaUIawZRLcXRaj9xzbBBfKcUhSB78mznvWsse8vExGEhPP88l3mu071N77TRx11VAwj5Zl3QccEN8EmJkRA8TIhXO48EQJ8XPgQM4PDOgi8/HDv8zGmisxjH/vYGPddJFTyEad0KCWAGRxRrWzLLbecSJe13JcQPFz5LLbIoIfEVFixujchEnBlozrP4sWL4yAI8YJni1CeYmBZSziTuCjEC/ZI9SdECXkGCOsit4jQHmyTIhSf/exnI1dyZwrOk+iyVocUi7iRb0DIJyKQAWN7XhE/I3TIP3I9ju4mQM4fIbVUbaMiIxMWDMQR0lTPKkpT8y5kBpxkfsqBFwuL1sq4JnkxeA/I29h5552jd9Uk/YmDxO6ozviVr3wlHHroofH7izeLMO/WpH2+R/BGOBblwEn6d5NATgKKl5y0G9wXC7hR0YmPCwPHD3/4w2PVYdqxEINLxTLKCLOOhIPGDQ2HATiJ0yxyV2ysrXPVVVdF8QJvBuOE4xEzbz7MeoZUuGOldMLuEHascUISMIOeYhBEcjXhKGzEf5OT1WlGl/1ZU6aJG+IEO2TAg33hLSXJF0HDYIYKUczMFgL78ssvj4usMvh2W0+A991HPvKRyI5Ec8LzyNkgHwsPKzPiTELgsWbgSOgtdkfuEYN0foc9N73aG2ti4fXjfUfoLM82Hmu3yRFgcgIRjRe1/d1XhDSzzhvvP0Ka8XrxbCscJ8fboyZGQPEyMV7unYAAgxheesx8EybBi5CyoQyEKJlM8i8hEu985zvD4YcfbixtB+a4+fFSIe4olUwYFDlGLHRJFZm3v/3tMURvr732ioKG6kXwNhxv/KARAUN1oiIsgg8vienwo2Ieaxhho/y+/aOMB4JBI96bJi8ySH4bApBcDio+FQuCtpeqhjwDdZgjrslPoJqWib7rbBI2VHfiuSanoFhTh0ISCMIiFJRJCqo24g0kxJGCHeTQtK5nlOA1PZJN8C1hAWDej4g9J74mfxsLTypefiZyWtcha52YIJSZ3FU81titYXuTZ+6RgxNQvAzOyj0TEWDmmxcdbmo+wMTPEhdPaVBmFP/jP/4jJgUyo8OAnGR0t/EE+LAQJ8/gmQ2mfGD4YCMOiwo8rWKlGKhT5hbPgtv4qmSE5SGameUmhp6QCZJYi8XwOvEi0R+eDJrwghUlXJvIlue5yFcjVp5Qx9bFVZkZZyaXtWAQ1VQgxG4NyRtvLYgYvNSEiPH+I7QWDypbURqYCR5CeVgjiwEjHi1Y77jjjk00Pa+5IgKFlxpByEQDdoc3q31ioijQUxRPwIYRO+0LL1d0mjbbQAKKlwbe9GG4ZAbfDHaI8SbGtjWBmoEgsbRUNOo2cKRqD+shMCAixIIkwyauTt1eYrW1Ak/ratPFoIc4ZQQipS0ZbFshZv3TgA0iWChliweB0EUGkFTX6rS1rlJN0joeBD1b69bjIKeNQXdRKauYxcW7SjgUYXj8jkVr8RAWg/NheDcNyzmQK4THlOe0GARS4puBZLHODj9TxZEKW4SeEbrT+tzDmMkhZscN5xmWOzt654E4wcvHxAOevvaJCWyVvC1CRFtzWilIgcdQ7+ro3fNhP2PFy7DfoQacH14WklWJU2Zmh5ASSrB2C4Mg5IyQMmbIGfQwIGf/l770pfEj3uQXJescMOBmFfnWXIzWkrZ8XCiKgIerWJW6AWY20CUiqM8777yYf0B+FuFkVDPqtLWvUj1QBw3dqZiZJQwPjwthZohEJiCY0T3ggAM6ksFbiDcHkd30wXd7Oe9BynszyUMeCBM7zIpb8a2hD2Ciy+40MdE+YcYzS3U8vKtMCFGqGu8g71M3CaQioHhJRdJ2ShHAM0BJRgaEhEMRSlIsetfaMCWVqVhGmUaqQRUDGgZHzPbOmjUrCqCmDnTwxDDbWizOCLtOgxwG6QgXZsFZR8ZtYgQIiyCRmnUQiupGfNgZLBK601T760YRLjyfp5xyShxAY3+U9UbEMBHRKTSUxHXCpng3kH+EIG9yCCkTE4TxUGmM7ZxzzokTFPzcq2gECf3kFDJZQall1uuwiuPEnnf37kyAbw1FOZiA5FuCfTLpyEQiIbT8vVgQmG96U4ubaD/pCShe0jO1xRIEGBQSKoEIaV9bgxchlXYIg2hdGb3oDuHzta99bQOvQ4nTGflDi3Ad1jlpHeSQ4MsieOQguCbMxG8zYRIXX3xx5EdITvERR3hTZIJSy3hsFDHr2BYL4SGUGUDjHYUZgq+T/RV2S/EESjGTw3X++efHiQuETBO31okJynfjUaEIx7Rp0/ri4FjyCq+++upYnYx1OZgcarKXui80d+hLgImxt73tbTFfFc9Ke1gjDVCNkImIojpe30bdQQIDEFC8DADJXYaDADOwJKUSbtIpRp4BD//8IK+/Xwg6BnyUsn3Vq14VBWGRCHzwwQfHBH+3wQkw2EZg47VqXSAUjyCeGBa1pAoZwgYbhblJq+v44h0lx4XZWcr6MthB5HXaqBbF4BzbLaoXkYNEG+QgMQDnHzlzTdyYwMErRU4B+X793nmUp3/ve98bxXZR5vZJT3pSOPLII5uIz2tOSKAoMIGgxr6YbCA3hq3wnlJumVwsQrxZf4xlEAgV5R3a6gX0G57wxtS8KcVLzW9wnS6P0BNc0pQDthxj/zvL4I5QHcpPM/NNYQQ+IAxkHFj359dpDyqSfexjH4s5GCSnUrWtGAyyvkSx6GoxI0msN793W0cAYYcwoXw31bJ22mmnDdAUdksFLRLQCy8N6+0UBRTI4Vq5cmUML20NkWwSZwaCeKIpjf7iF7+466UzuGRQSWnqogBKsdCowrpJFlPttfJdIV8VW8Tj3L5oLZXxKPmNDVKwA28qxSfw2hQlrSkEgFeb31Fxz00C3QgoXrSNkSHAR5jZ2L//+78ft+Jv6wX0m9kZmYtNcKJ4XahAtHDhwlhdjGoxzHgRzsSg0ZCmyUFmNpGQO/Jd8Fzx0SZ/A2FdVLxrD8tD4OBx4CPtgLE3dxJ+zz777Bgfj3eG5531T/BmIRjJe4E1VbiKamaTu5PNOIqy1RRGaF0rhjBS7BHPlfbYDDvIfZVMUlA1lGI8lKA/66yzwrbbbhte+cpXxm8PNki+G95DinbgTWzNl8l9vvY3WgQUL6N1vxp/tiyOxYCcWO927wsDnH4zO00D2OQV4HPcawaALGhJCN4znvGM2GWRzM8aMYceemgsRMHCg5RR5m+UVWZA3i/UJ8f5D1sfRUnvZz/72eGggw6KHhpEC4NsconwIhJ2wlYMgobtGobpfKgEheCjwAkJ1Ijoz33uc3FBUYQ07wdXRh+mO1afc7nwwgvjOw9PCxM+7TlaeFgJtUW84BUsEvs75bPWh4pXkoqA4iUVSdvJQgBXNKWSiZ1nVpaQHOJrWSuC2dpeMztZTtBOGkUAMUKS/t577z22xgthD8Wq6DfddFMM3SN8jIE3OTPMNhK2R36M23gCrAND6Ai5Lp1WR8ebuGTJkjhDu/3224uvB4GiiMQvfvGLsXVhsE3K2GKDj370o2PVN2bHEYK77rqrPCVQCQGqkbEwNc91Ua6bZ5lvNrlbf/7zn2Pif6dJyUpOyEZHnoDiZeRvYTMvgBlE4muvueaaGELGDE+vmR3c0ny0cV9T7chNAlUQaA19YDaRUAkENqVDi43QRhLPyVVwG0+gVyI+f2Ogveeee0bhR14R5X/JfWHygt9ZAng9T4pIMCAkL4gJHryEvCN5B/74xz8OL3/5y2PFMTxZlPemiIKbBKogwPeadyF29sIXvjAuLo0tEnZL6W6+zXzDEdGsC3PFFVcEJn54h/Lt1ktdxV0Z7TYVL6N9/zz7+wn0m9lhhpFKZbwg8c4w0CE0pb0cs0AlUIYASanMbpO4z0eYRGkq7VhgogzVdce2erQIhypCRBmA8zdyZXjGH/7wh5fvrCYtFJWgyDFoXWsHrxZrv1x++eUxlGzevHmx8hu5WvyjIAVhj8X7ES8Owpyy4ObK1cQ4Ml/Gn/70p0AoGWGL2NUxxxwTBTOTD0XOIHbGO3O77bYbS+p/yEMeEsv8m5uV+YYNeXeKlyG/QZ7eYAR6zewwu/OOd7wjzjLy/8zYEtZDVRReolSMcpNAagJFQiqVdYp8mNR9NKW9Th4tCk8U1d2KxfBI5scT67YhATwvhIvBrCh0wKQO62o9/elPjzPjVHNjJhyPNhNChDsS5kPydRH2Y/U8rSsVgaIID+9I8gbxArK2U5H3UuQPUlKZSpluEigIKF60hdoQ6Dazc+WVV47lILQuiEeVKBZuI86W+PlOMfa1geOFbBQCP//5z6Nw5uNLCARev6aW9i1zA/CqfOtb34oVxhAyhJwwwGldoJHyv3gF9Ax0Jw1Hyisfe+yxMe+qmM2mIhmFJd785jfH9yBi8POf/3xk/bKXvSy85z3vid5Dkq/lW8aSPbaVAPmCTCRid+S9UFyCxSyL/CsKSixevDgceOCB8f3pJgHFizbQCALFYm7MNrYubFnM+DCQ5GPNR51QMvbTPd0I08h2kYTrEKJz/fXXxw+zYU3l0LMYHh6EN77xjTG8xG1iBMglOO+882IltxNPPDF6Ban6RHW3Vq8VOUYMHpnkYZV0iiQQNuYmgVQEmHDAQ82aLr/61a+i9w8BwxpPbIThUs0RcUOuFmuVIaqZBKKCHh5ExXSquzFa7eh5Ga375dlOkACx8IRFMGPbKkqYaWSRLKqfkAdDKBkfZxbHsurOBCG7uwQyEmBAjfeA/xILb95aOfiUp+6Wm1WUrqbIBLwZVCJ4yIlxk0BKAkWIGCJ63333DURS4LUmTPFVr3pVXByYQhNMALEveTLPf/7zo+D2HZDyToxGW4qX0bhPnmVCAiT7IlSOO+64sTha4sEp2UgFHmNrE8K2KQlUQIDByyc+8Ylw6aWXxpLpJJzrhZkc6GIldMJ2eCe2TvJ84QtfiANGQmvxUhPmc8EFF8QqZiRSu0kgJQFEMiGK/JdvMsKEdYjIv6LSIEU6KPHNxoQjdsk3m7Ay7FYvTMq7MdxtKV6G+/54dokJFGsfIGDmzJkz9qFurTlP0q+bBCQw/AQo1MGg23y1cveKgeL73//+cO2118bStMxoE8rDJA9e6yLBnzAeBpF4rBGLiEgGjYbaluPv0esJ8I1mPSzKIxfPNQtYUl4ZT2shUIiqoFoeIWX8l2OOPPJIUTZBngolAAAJjElEQVSEgOKlITfay1xHgKo5fJCZNSREbKeddoprbhBXyyyPCwdqKRKQQFMJ8C68+eabw+Me97hw/vnnx3wEBoybbbZZTOK/6KKL4t9f97rXxTAyFmClxDKrpFMMxfU4mmo51V53u3hpj55g4Vrs8NBDD632RGx9aAgoXobmVngiVRNglhaXNDG0rGFAxSJmcZixoYqOyfpV3wHbl4AERoEAITlnnnlmnOChEmMx8YPX5dRTT42hOxQ5YXHBvfbaK1BVj3WNKK1MGJ+bBFISwOtCIj+5VgcccEAsNlGUVEZUkxsze/bssYpkv/zlL2PoGUV6zIdJeSeGpy3Fy/DcC8+kYgK33npr+OhHPxrLhLJ2AWIG4VJUHKu4e5uXgAQkMJIEWid+mORhPRg82C996UvD0572tOiVYXYcEXPyySdHT42bBMoSwO6+/e1vh1mzZgUqk5FzxT/CvJl8RCgX6xcdffTR8ecvfelL0UN40kknRTFjHkzZuzCcxytehvO+eFYSkIAEJCCBoSDAYJHqTuS6MPGDUCE/hkIJxcw25ZSZIKIalAPGobhtI38SCJP3ve99Y+GLW265ZfSy4O0r1hyiFD2lvknsp8AEJZdJ5Ke0slt9CShe6ntvvTIJSEACEpBAaQJ4ViiMUJSVp7QyeS+77LJLbBvRQrXG448/Puy5554xpIzZb7bDDz88PP3pTx+XD+OCoqVvSWMawFbwvlAe/fbbb4/2xL9CNJPHShUybPSZz3xmXP8FO+204clhzS0iMCgDTp4WIujFL35x12MaA3rELlTxMmI3zNOVgAQkIAEJbCwCLFp53XXXxQEfHpai1DKVx17zmtfE8tUsJFgsyEriP9XKqGBW7I/nhoEoxQDcJDBZAggbwsRYdBUxvc8++3T1+iFc8B7+8Ic/jBXKHvOYx8Sw8QsvvDD89Kc/jb/Dq+g2GgQUL6NxnzxLCUhAAhKQwNARYOa7SOSnvDKhZSxkWayXxRodVINicMjK6DfeeGNcJ4bQnunTpw/d9XhCo0EA4UF5bxLzBwkTwxu4dOnSmCtTrBXDlRZV9H7961+HU045JebAug0/AcXL8N8jz1ACEpCABCQwlASYuSZMh/Cbb37zm+GKK64I8+fPHwvrYW0YqjwS2rPNNtuEc845J0ydOjVWdzQ3Zihv6UicFDlXK1eujOWRu4WJFRdCyW9yZQhzpMhE+4YX8Gc/+1kMb3QbDQKKl9G4T56lBCQgAQlIYKgJsFggg0pCeIoQsda1YfgboTtUKnvYwx421NfiydWHAEn9lPgmlLFYcLU+V9fMK1G8NPO+e9USkIAEJCCBpARYH4YFf1/5ylfGsDESrVkLhjU6dtxxxxiys//++4fnPOc54U9/+lP00tx0002xpO2Tn/xkF7lMejdsrCDA4qsUlCCcsVuoIvkzrA+DF4YFLxXXw20/ipfhvj+enQQkIAEJSGBkCCBGzj777HDNNdfEQSADRhYX/PKXvxzDysiJodITFcu22267KGb4/UMe8pCYwL/55puPzLV6oqNB4N577+0ZrliUZKYQxROf+MTwk5/8JIaj8c/QxuG8x4qX4bwvnpUEJCABCUigFgRuu+22GCp23HHHxVLK55577tgK6YgVKpWxVseLXvSisUT/Wly4FzE0BH77299GwYyQPuKII2KZ5GKj+t1VV10VhfVWW20VxTX2eMwxx4Rdd911aK7BE1lPQPGiNUhAAhKQgAQkUBmBz3zmM7Eq1Jw5c8Idd9wRw8jIPygGhsyML168OBx44IExhMxNAlUQIFTx4osvjousIlBe8YpXhEMOOSQWk0CoPOlJT4rdUoHsrLPOil5B7bGKO1G+TcVLeYa2IAEJSEACEpBAFwKsscGAkDK0rIDOwBABQ9UxNiqSkStDOWUqkn3iE58IK1asiANHqkO5/oamlZIAtkioGFXKKJFMmCOewcIeWXQV+3z961+v5yUl+IRtKV4SwrQpCUhAAhKQgAS6EyhCxA466KCw7777xsR9ytg+6lGPCi95yUviIJLQHha1ZEFBKpiRN0P+jPkHWlZqAnhgKCSB54VKZMVilr/73e/CvHnzxkp+p+7X9soRULyU4+fREpCABCQgAQlMgAAhZKz9wn+ZAd9vv/3CCSecEC655JLw85//fNygkYpkH/7wh6PA2X777WNCvyJmArDdtS8BRDILqc6YMSPaJJXHFi5cGB7+8If3PdYdNg4BxcvG4W6vEpCABCQggcYSIHSHVdI33XTTmCRdeGRY7LLIPWAWHJFDeVt+/7nPfS4ec+SRRzaWmxdeDQHs7/rrr4+hjeRiWfWuGs6pWlW8pCJpOxKQgAQkIAEJTIpAJ/Hyve99L3zyk5+MoWQPfvCD4+w44WOUsHWTgASaS0Dx0tx775VLQAISkIAEhobAd7/73fC+970v5r4gUggXe8ELXhCe8YxnhL/+9a8xdGz27NljFaBYVJAwn6c+9anmJgzNXfREJFA9AcVL9YztQQISkIAEJCCBLgRYg4OKY3vttVe45ZZbwte//vXwne98J2y77bZh/vz5sSoUuTHvfOc7w9FHHx123nnn8KUvfSlcdNFF4aSTTopixjwYzUsCzSGgeGnOvfZKJSABCUhAAkNHAA8KwuTggw8Oz33uc2P52ne/+90xcX+XXXaJ57t69eq4cCCJ/V/4whdiyeU3vOEN4ZGPfGTH6yHpmkpS5NRsvfXWipuhu+uekAQmT0DxMnl2HikBCUhAAhKQQAIClEzGk0LFMRL4WWPjKU95ypjoWLVqVVxMkET/Zz7zmeGoo46KHplOG56ct7zlLeG2224LLIA5bdq02N6OO+6Y4ExtQgIS2NgEFC8b+w7YvwQkIAEJSEACXQngRSFM7Lzzzguve93rwj777NPTk4IAuvrqq2PIGdWjrrnmmrB48eLotdl77731wmhrEhhxAoqXEb+Bnr4EJCABCUigrgQojfz+978/Jub3ChNrvf5W8bLFFlvEP/3sZz+LZZfx3rBejJsEJDC6BBQvo3vvPHMJSEACEpBArQlce+21YeXKlbE8crcwsXYAhI0hUp7whCeEY489NlYiI9zspptuiqFjJvfX2mS8uAYQULw04CZ7iRKQgAQkIIG6E6CcMmFibLfeemssrcz6MKecckrMo3GTgATqQUDxUo/76FVIQAISkIAEGkvg9ttvD+ecc044/vjjw8Me9rDIgZAzBAzelle/+tVhs802ixXIWEl9yy23dCX1xlqLFz7qBP4/CS/nTrERHZ8AAAAASUVORK5CYII=",
            "text/html": [
              "<div>\n",
              "        \n",
              "        \n",
              "            <div id=\"313eb8fd-5f33-4c78-b764-51db306852b9\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
              "            <script type=\"text/javascript\">\n",
              "                require([\"plotly\"], function(Plotly) {\n",
              "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
              "                    window.PLOTLYENV.BASE_URL='https://plot.ly';\n",
              "                    \n",
              "                if (document.getElementById(\"313eb8fd-5f33-4c78-b764-51db306852b9\")) {\n",
              "                    Plotly.newPlot(\n",
              "                        '313eb8fd-5f33-4c78-b764-51db306852b9',\n",
              "                        [{\"type\": \"bar\", \"uid\": \"db0a7ca3-99c6-4360-87b4-893766b2dac4\", \"x\": [\"NTT Data Corp\", \"Telus Corp\", \"Maximus Inc\", \"Accenture Plc\", \"Cognizant Technology Solutions Corp\", \"CGI Inc\", \"DXC Technology Co\", \"IBM\"], \"y\": [\"66.64\", \"138.42\", \"11.25\", \"0.28\", \"6.97\", \"30.62\", \"68.59\", \"247.97\"]}],\n",
              "                        {\"title\": {\"text\": \"Total Debt to Equity (MRQ)\"}},\n",
              "                        {\"showLink\": false, \"linkText\": \"Export to plot.ly\", \"plotlyServerURL\": \"https://plot.ly\", \"responsive\": true}\n",
              "                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('313eb8fd-5f33-4c78-b764-51db306852b9');\n",
              "var x = new MutationObserver(function (mutations, observer) {{\n",
              "        var display = window.getComputedStyle(gd).display;\n",
              "        if (!display || display === 'none') {{\n",
              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
              "}}\n",
              "\n",
              "// Listen for the clearing of the current output cell\n",
              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })\n",
              "                };\n",
              "                });\n",
              "            </script>\n",
              "        </div>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Note that values are multiplied by 100, so 129 means Debt is 1.29 times Equity\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vxVEdAIg-MjD",
        "colab_type": "code",
        "colab": {},
        "outputId": "be7a5e49-a9a6-4cd5-952e-de21808572a6"
      },
      "source": [
        "# Single company data\n",
        "company = 'Telus Corp'\n",
        "master_df.loc[master_df['Company Name'] == company]"
      ],
      "execution_count": 0,
      "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>Company</th>\n",
              "      <th>industry</th>\n",
              "      <th>sector</th>\n",
              "      <th>Ticker</th>\n",
              "      <th>Company Name</th>\n",
              "    </tr>\n",
              "    <tr>\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>P/E Ratio (TTM)</th>\n",
              "      <td>18.47</td>\n",
              "      <td>20.14</td>\n",
              "      <td>20.17</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>P/E High - Last 5 Yrs.</th>\n",
              "      <td>20.74</td>\n",
              "      <td>27.41</td>\n",
              "      <td>30.09</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>P/E Low - Last 5 Yrs.</th>\n",
              "      <td>16.72</td>\n",
              "      <td>18.70</td>\n",
              "      <td>20.01</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Beta</th>\n",
              "      <td>0.86</td>\n",
              "      <td>0.59</td>\n",
              "      <td>0.61</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Price to Sales (TTM)</th>\n",
              "      <td>2.11</td>\n",
              "      <td>3.01</td>\n",
              "      <td>2.80</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Price to Book (MRQ)</th>\n",
              "      <td>2.89</td>\n",
              "      <td>3.84</td>\n",
              "      <td>3.59</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Price to Tangible Book (MRQ)</th>\n",
              "      <td>--</td>\n",
              "      <td>4.11</td>\n",
              "      <td>3.94</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Price to Cash Flow (TTM)</th>\n",
              "      <td>7.64</td>\n",
              "      <td>8.18</td>\n",
              "      <td>7.82</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>% Owned Institutions</th>\n",
              "      <td>--</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dividend Yield</th>\n",
              "      <td>4.42</td>\n",
              "      <td>4.28</td>\n",
              "      <td>4.02</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dividend Yield - 5 Year Avg</th>\n",
              "      <td>4.16</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.37</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dividend 5 Year Growth Rate</th>\n",
              "      <td>8.66</td>\n",
              "      <td>0.42</td>\n",
              "      <td>1.39</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Payout Ratio(TTM)</th>\n",
              "      <td>78.31</td>\n",
              "      <td>5.26</td>\n",
              "      <td>9.34</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sales (MRQ) vs Qtr. 1 Yr. Ago</th>\n",
              "      <td>6.79</td>\n",
              "      <td>7.53</td>\n",
              "      <td>6.42</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sales (TTM) vs TTM 1 Yr. Ago</th>\n",
              "      <td>5.94</td>\n",
              "      <td>3.40</td>\n",
              "      <td>2.68</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sales - 5 Yr. Growth Rate</th>\n",
              "      <td>4.45</td>\n",
              "      <td>9.43</td>\n",
              "      <td>8.49</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EPS (MRQ) vs Qtr. 1 Yr. Ago</th>\n",
              "      <td>0.46</td>\n",
              "      <td>4.91</td>\n",
              "      <td>-127.79</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EPS (TTM) vs TTM 1 Yr. Ago</th>\n",
              "      <td>1.98</td>\n",
              "      <td>--</td>\n",
              "      <td>--</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EPS - 5 Yr. Growth Rate</th>\n",
              "      <td>5.90</td>\n",
              "      <td>7.86</td>\n",
              "      <td>7.41</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Capital Spending - 5 Yr. Growth Rate</th>\n",
              "      <td>6.91</td>\n",
              "      <td>9.40</td>\n",
              "      <td>7.95</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Quick Ratio (MRQ)</th>\n",
              "      <td>0.72</td>\n",
              "      <td>0.96</td>\n",
              "      <td>0.94</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Current Ratio (MRQ)</th>\n",
              "      <td>0.79</td>\n",
              "      <td>1.01</td>\n",
              "      <td>1.00</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LT Debt to Equity (MRQ)</th>\n",
              "      <td>129.30</td>\n",
              "      <td>50.77</td>\n",
              "      <td>55.90</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Total Debt to Equity (MRQ)</th>\n",
              "      <td>138.42</td>\n",
              "      <td>65.11</td>\n",
              "      <td>71.55</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Interest Coverage (TTM)</th>\n",
              "      <td>5.21</td>\n",
              "      <td>29.24</td>\n",
              "      <td>29.70</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Gross Margin (TTM)</th>\n",
              "      <td>54.82</td>\n",
              "      <td>62.75</td>\n",
              "      <td>61.87</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Gross Margin - 5 Yr. Avg.</th>\n",
              "      <td>55.44</td>\n",
              "      <td>68.58</td>\n",
              "      <td>65.95</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EBITD Margin (TTM)</th>\n",
              "      <td>35.45</td>\n",
              "      <td>--</td>\n",
              "      <td>--</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EBITD - 5 Yr. Avg</th>\n",
              "      <td>35.65</td>\n",
              "      <td>50.42</td>\n",
              "      <td>48.04</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Operating Margin (TTM)</th>\n",
              "      <td>20.13</td>\n",
              "      <td>32.50</td>\n",
              "      <td>29.05</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Operating Margin - 5 Yr. Avg.</th>\n",
              "      <td>19.61</td>\n",
              "      <td>34.85</td>\n",
              "      <td>31.71</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pre-Tax Margin (TTM)</th>\n",
              "      <td>15.44</td>\n",
              "      <td>28.51</td>\n",
              "      <td>25.03</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Pre-Tax Margin - 5 Yr. Avg.</th>\n",
              "      <td>15.26</td>\n",
              "      <td>31.93</td>\n",
              "      <td>28.59</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Profit Margin (TTM)</th>\n",
              "      <td>11.52</td>\n",
              "      <td>21.04</td>\n",
              "      <td>18.42</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Profit Margin - 5 Yr. Avg.</th>\n",
              "      <td>11.24</td>\n",
              "      <td>24.26</td>\n",
              "      <td>21.67</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Effective Tax Rate (TTM)</th>\n",
              "      <td>25.37</td>\n",
              "      <td>26.35</td>\n",
              "      <td>25.00</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Effective Tax Rate - 5 Yr. Avg.</th>\n",
              "      <td>26.36</td>\n",
              "      <td>24.13</td>\n",
              "      <td>22.86</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Revenue/Employee (TTM)</th>\n",
              "      <td>180,736</td>\n",
              "      <td>5,446,309,934</td>\n",
              "      <td>5,416,677,920</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Net Income/Employee (TTM)</th>\n",
              "      <td>20,824</td>\n",
              "      <td>1,176,765,506</td>\n",
              "      <td>936,515,039</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Receivable Turnover (TTM)</th>\n",
              "      <td>6.53</td>\n",
              "      <td>9.21</td>\n",
              "      <td>10.17</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Inventory Turnover (TTM)</th>\n",
              "      <td>16.85</td>\n",
              "      <td>69.42</td>\n",
              "      <td>64.22</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Asset Turnover (TTM)</th>\n",
              "      <td>0.44</td>\n",
              "      <td>0.59</td>\n",
              "      <td>0.58</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Return on Assets (TTM)</th>\n",
              "      <td>5.07</td>\n",
              "      <td>12.18</td>\n",
              "      <td>10.77</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Return on Assets - 5 Yr. Avg.</th>\n",
              "      <td>5.34</td>\n",
              "      <td>14.68</td>\n",
              "      <td>13.16</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Return on Investment (TTM)</th>\n",
              "      <td>6.00</td>\n",
              "      <td>18.05</td>\n",
              "      <td>15.92</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Return on Investment - 5 Yr. Avg.</th>\n",
              "      <td>6.37</td>\n",
              "      <td>21.77</td>\n",
              "      <td>19.49</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Return on Equity (TTM)</th>\n",
              "      <td>16.26</td>\n",
              "      <td>18.51</td>\n",
              "      <td>15.94</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Return on Equity - 5 Yr. Avg.</th>\n",
              "      <td>17.28</td>\n",
              "      <td>23.28</td>\n",
              "      <td>20.87</td>\n",
              "      <td>T.TO</td>\n",
              "      <td>Telus Corp</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "0                                     Company       industry         sector  \\\n",
              "                                                                              \n",
              "P/E Ratio (TTM)                         18.47          20.14          20.17   \n",
              "P/E High - Last 5 Yrs.                  20.74          27.41          30.09   \n",
              "P/E Low - Last 5 Yrs.                   16.72          18.70          20.01   \n",
              "Beta                                     0.86           0.59           0.61   \n",
              "Price to Sales (TTM)                     2.11           3.01           2.80   \n",
              "Price to Book (MRQ)                      2.89           3.84           3.59   \n",
              "Price to Tangible Book (MRQ)               --           4.11           3.94   \n",
              "Price to Cash Flow (TTM)                 7.64           8.18           7.82   \n",
              "% Owned Institutions                       --           0.00           0.00   \n",
              "Dividend Yield                           4.42           4.28           4.02   \n",
              "Dividend Yield - 5 Year Avg              4.16           0.20           0.37   \n",
              "Dividend 5 Year Growth Rate              8.66           0.42           1.39   \n",
              "Payout Ratio(TTM)                       78.31           5.26           9.34   \n",
              "Sales (MRQ) vs Qtr. 1 Yr. Ago            6.79           7.53           6.42   \n",
              "Sales (TTM) vs TTM 1 Yr. Ago             5.94           3.40           2.68   \n",
              "Sales - 5 Yr. Growth Rate                4.45           9.43           8.49   \n",
              "EPS (MRQ) vs Qtr. 1 Yr. Ago              0.46           4.91        -127.79   \n",
              "EPS (TTM) vs TTM 1 Yr. Ago               1.98             --             --   \n",
              "EPS - 5 Yr. Growth Rate                  5.90           7.86           7.41   \n",
              "Capital Spending - 5 Yr. Growth Rate     6.91           9.40           7.95   \n",
              "Quick Ratio (MRQ)                        0.72           0.96           0.94   \n",
              "Current Ratio (MRQ)                      0.79           1.01           1.00   \n",
              "LT Debt to Equity (MRQ)                129.30          50.77          55.90   \n",
              "Total Debt to Equity (MRQ)             138.42          65.11          71.55   \n",
              "Interest Coverage (TTM)                  5.21          29.24          29.70   \n",
              "Gross Margin (TTM)                      54.82          62.75          61.87   \n",
              "Gross Margin - 5 Yr. Avg.               55.44          68.58          65.95   \n",
              "EBITD Margin (TTM)                      35.45             --             --   \n",
              "EBITD - 5 Yr. Avg                       35.65          50.42          48.04   \n",
              "Operating Margin (TTM)                  20.13          32.50          29.05   \n",
              "Operating Margin - 5 Yr. Avg.           19.61          34.85          31.71   \n",
              "Pre-Tax Margin (TTM)                    15.44          28.51          25.03   \n",
              "Pre-Tax Margin - 5 Yr. Avg.             15.26          31.93          28.59   \n",
              "Net Profit Margin (TTM)                 11.52          21.04          18.42   \n",
              "Net Profit Margin - 5 Yr. Avg.          11.24          24.26          21.67   \n",
              "Effective Tax Rate (TTM)                25.37          26.35          25.00   \n",
              "Effective Tax Rate - 5 Yr. Avg.         26.36          24.13          22.86   \n",
              "Revenue/Employee (TTM)                180,736  5,446,309,934  5,416,677,920   \n",
              "Net Income/Employee (TTM)              20,824  1,176,765,506    936,515,039   \n",
              "Receivable Turnover (TTM)                6.53           9.21          10.17   \n",
              "Inventory Turnover (TTM)                16.85          69.42          64.22   \n",
              "Asset Turnover (TTM)                     0.44           0.59           0.58   \n",
              "Return on Assets (TTM)                   5.07          12.18          10.77   \n",
              "Return on Assets - 5 Yr. Avg.            5.34          14.68          13.16   \n",
              "Return on Investment (TTM)               6.00          18.05          15.92   \n",
              "Return on Investment - 5 Yr. Avg.        6.37          21.77          19.49   \n",
              "Return on Equity (TTM)                  16.26          18.51          15.94   \n",
              "Return on Equity - 5 Yr. Avg.           17.28          23.28          20.87   \n",
              "\n",
              "0                                    Ticker Company Name  \n",
              "                                                          \n",
              "P/E Ratio (TTM)                        T.TO   Telus Corp  \n",
              "P/E High - Last 5 Yrs.                 T.TO   Telus Corp  \n",
              "P/E Low - Last 5 Yrs.                  T.TO   Telus Corp  \n",
              "Beta                                   T.TO   Telus Corp  \n",
              "Price to Sales (TTM)                   T.TO   Telus Corp  \n",
              "Price to Book (MRQ)                    T.TO   Telus Corp  \n",
              "Price to Tangible Book (MRQ)           T.TO   Telus Corp  \n",
              "Price to Cash Flow (TTM)               T.TO   Telus Corp  \n",
              "% Owned Institutions                   T.TO   Telus Corp  \n",
              "Dividend Yield                         T.TO   Telus Corp  \n",
              "Dividend Yield - 5 Year Avg            T.TO   Telus Corp  \n",
              "Dividend 5 Year Growth Rate            T.TO   Telus Corp  \n",
              "Payout Ratio(TTM)                      T.TO   Telus Corp  \n",
              "Sales (MRQ) vs Qtr. 1 Yr. Ago          T.TO   Telus Corp  \n",
              "Sales (TTM) vs TTM 1 Yr. Ago           T.TO   Telus Corp  \n",
              "Sales - 5 Yr. Growth Rate              T.TO   Telus Corp  \n",
              "EPS (MRQ) vs Qtr. 1 Yr. Ago            T.TO   Telus Corp  \n",
              "EPS (TTM) vs TTM 1 Yr. Ago             T.TO   Telus Corp  \n",
              "EPS - 5 Yr. Growth Rate                T.TO   Telus Corp  \n",
              "Capital Spending - 5 Yr. Growth Rate   T.TO   Telus Corp  \n",
              "Quick Ratio (MRQ)                      T.TO   Telus Corp  \n",
              "Current Ratio (MRQ)                    T.TO   Telus Corp  \n",
              "LT Debt to Equity (MRQ)                T.TO   Telus Corp  \n",
              "Total Debt to Equity (MRQ)             T.TO   Telus Corp  \n",
              "Interest Coverage (TTM)                T.TO   Telus Corp  \n",
              "Gross Margin (TTM)                     T.TO   Telus Corp  \n",
              "Gross Margin - 5 Yr. Avg.              T.TO   Telus Corp  \n",
              "EBITD Margin (TTM)                     T.TO   Telus Corp  \n",
              "EBITD - 5 Yr. Avg                      T.TO   Telus Corp  \n",
              "Operating Margin (TTM)                 T.TO   Telus Corp  \n",
              "Operating Margin - 5 Yr. Avg.          T.TO   Telus Corp  \n",
              "Pre-Tax Margin (TTM)                   T.TO   Telus Corp  \n",
              "Pre-Tax Margin - 5 Yr. Avg.            T.TO   Telus Corp  \n",
              "Net Profit Margin (TTM)                T.TO   Telus Corp  \n",
              "Net Profit Margin - 5 Yr. Avg.         T.TO   Telus Corp  \n",
              "Effective Tax Rate (TTM)               T.TO   Telus Corp  \n",
              "Effective Tax Rate - 5 Yr. Avg.        T.TO   Telus Corp  \n",
              "Revenue/Employee (TTM)                 T.TO   Telus Corp  \n",
              "Net Income/Employee (TTM)              T.TO   Telus Corp  \n",
              "Receivable Turnover (TTM)              T.TO   Telus Corp  \n",
              "Inventory Turnover (TTM)               T.TO   Telus Corp  \n",
              "Asset Turnover (TTM)                   T.TO   Telus Corp  \n",
              "Return on Assets (TTM)                 T.TO   Telus Corp  \n",
              "Return on Assets - 5 Yr. Avg.          T.TO   Telus Corp  \n",
              "Return on Investment (TTM)             T.TO   Telus Corp  \n",
              "Return on Investment - 5 Yr. Avg.      T.TO   Telus Corp  \n",
              "Return on Equity (TTM)                 T.TO   Telus Corp  \n",
              "Return on Equity - 5 Yr. Avg.          T.TO   Telus Corp  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J_DZFfxG-MjJ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}