ml-finance-python

notebook.ipynb

(126165B)

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     "# Quandl: S&P 500 Volatility Index (VIX)\n",
     "\n",
     "In this notebook, we'll take a look at data set , available on [Quantopian](https://www.quantopian.com/data). This dataset spans from January, 1990 through the current day. It contains the value for the index VIX, a measure of volatility in the S&P 500. We access this data via the API provided by [Quandl](https://www.quandl.com). [More details](https://www.quandl.com/data/YAHOO/INDEX_VIX-VIX-S-P-500-Volatility-Index) on this dataset can be found on Quandl's website.\n",
     "\n",
     "To be clear, this is a single value for VIX each day.\n",
     "\n",
     "## Notebook Contents\n",
     "\n",
     "There are two ways to access the data and you'll find both of them listed below. Just click on the section you'd like to read through.\n",
     "\n",
     "- <a href='#interactive'><strong>Interactive overview</strong></a>: This is only available on Research and uses blaze to give you access to large amounts of data. Recommended for exploration and plotting.\n",
     "- <a href='#pipeline'><strong>Pipeline overview</strong></a>: Data is made available through pipeline which is available on both the Research & Backtesting environment. Recommended for custom factor development and moving back & forth between research/backtesting.\n",
     "\n",
     "### Limits\n",
     "One key caveat: we limit the number of results returned from any given expression to 10,000 to protect against runaway memory usage. To be clear, you have access to all the data server side. We are limiting the size of the responses back from Blaze.\n",
     "\n",
     "With preamble in place, let's get started:\n",
     "\n",
     "<a id='interactive'></a>\n",
     "#Interactive Overview\n",
     "### Accessing the data with Blaze and Interactive on Research\n",
     "Partner datasets are available on Quantopian Research through an API service known as [Blaze](http://blaze.pydata.org). Blaze provides the Quantopian user with a convenient interface to access very large datasets, in an interactive, generic manner.\n",
     "\n",
     "Blaze provides an important function for accessing these datasets. Some of these sets are many millions of records. Bringing that data directly into Quantopian Research directly just is not viable. So Blaze allows us to provide a simple querying interface and shift the burden over to the server side.\n",
     "\n",
     "It is common to use Blaze to reduce your dataset in size, convert it over to Pandas and then to use Pandas for further computation, manipulation and visualization.\n",
     "\n",
     "Helpful links:\n",
     "* [Query building for Blaze](http://blaze.readthedocs.io/en/latest/queries.html)\n",
     "* [Pandas-to-Blaze dictionary](http://blaze.readthedocs.io/en/latest/rosetta-pandas.html)\n",
     "* [SQL-to-Blaze dictionary](http://blaze.readthedocs.io/en/latest/rosetta-sql.html).\n",
     "\n",
     "Once you've limited the size of your Blaze object, you can convert it to a Pandas DataFrames using:\n",
     "> `from odo import odo`  \n",
     "> `odo(expr, pandas.DataFrame)`\n",
     "\n",
     "\n",
     "###To see how this data can be used in your algorithm, search for the `Pipeline Overview` section of this notebook or head straight to <a href='#pipeline'>Pipeline Overview</a>"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
     "collapsed": false
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    "outputs": [],
    "source": [
     "# import the dataset\n",
     "from quantopian.interactive.data.quandl import yahoo_index_vix as dataset\n",
     "# Since this data is provided by Quandl for free, there is no _free version of this\n",
     "# data set, as found in the premium sets. This import gets you the entirety of this data set.\n",
     "\n",
     "# import data operations\n",
     "from odo import odo\n",
     "# import other libraries we will use\n",
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 7,
    "metadata": {
     "collapsed": false
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    "outputs": [
     {
      "data": {
       "text/plain": [
        "dshape(\"\"\"var * {\n",
        "  open_: float64,\n",
        "  high: float64,\n",
        "  low: float64,\n",
        "  close: float64,\n",
        "  volume: float64,\n",
        "  adjusted_close: float64,\n",
        "  asof_date: datetime,\n",
        "  timestamp: datetime\n",
        "  }\"\"\")"
       ]
      },
      "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Let's use blaze to understand the data a bit using Blaze dshape()\n",
     "dataset.dshape"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/html": [
        "6651"
       ],
       "text/plain": [
        "6651"
       ]
      },
      "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# And how many rows are there?\n",
     "# N.B. we're using a Blaze function to do this, not len()\n",
     "dataset.count()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "text/html": [
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>open_</th>\n",
        "      <th>high</th>\n",
        "      <th>low</th>\n",
        "      <th>close</th>\n",
        "      <th>volume</th>\n",
        "      <th>adjusted_close</th>\n",
        "      <th>asof_date</th>\n",
        "      <th>timestamp</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>19.750000</td>\n",
        "      <td>21.160000</td>\n",
        "      <td>19.540001</td>\n",
        "      <td>20.980000</td>\n",
        "      <td>0</td>\n",
        "      <td>20.980000</td>\n",
        "      <td>2016-02-23</td>\n",
        "      <td>2016-02-24 08:01:58.351899</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>22.280001</td>\n",
        "      <td>22.870001</td>\n",
        "      <td>20.260000</td>\n",
        "      <td>20.719999</td>\n",
        "      <td>0</td>\n",
        "      <td>20.719999</td>\n",
        "      <td>2016-02-24</td>\n",
        "      <td>2016-02-25 08:02:33.397136</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>20.540001</td>\n",
        "      <td>21.260000</td>\n",
        "      <td>19.100000</td>\n",
        "      <td>19.110001</td>\n",
        "      <td>0</td>\n",
        "      <td>19.110001</td>\n",
        "      <td>2016-02-25</td>\n",
        "      <td>2016-02-26 05:01:23.226761</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>"
       ],
       "text/plain": [
        "       open_       high        low      close  volume  adjusted_close  \\\n",
        "0  19.750000  21.160000  19.540001  20.980000       0       20.980000   \n",
        "1  22.280001  22.870001  20.260000  20.719999       0       20.719999   \n",
        "2  20.540001  21.260000  19.100000  19.110001       0       19.110001   \n",
        "\n",
        "   asof_date                  timestamp  \n",
        "0 2016-02-23 2016-02-24 08:01:58.351899  \n",
        "1 2016-02-24 2016-02-25 08:02:33.397136  \n",
        "2 2016-02-25 2016-02-26 05:01:23.226761  "
       ]
      },
      "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# Let's see what the data looks like. We'll grab the first three rows.\n",
     "dataset[:3]"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Let's go over the columns:\n",
     "- **asof_date**: the timeframe to which this data applies\n",
     "- **timestamp**: the simulated date upon which this data point is available to a backtest\n",
     "- **open**: opening price for the day indicated on asof_date\n",
     "- **high**: high price for the day indicated on asof_date\n",
     "- **low**: lowest price for the day indicated by asof_date\n",
     "- **close**: closing price for asof_date\n",
     "\n",
     "We've done much of the data processing for you. Fields like `timestamp` and `sid` are standardized across all our Store Datasets, so the datasets are easy to combine. We have standardized the `sid` across all our equity databases.\n",
     "\n",
     "We can select columns and rows with ease. Let's go plot it for fun below. 6500 rows is small enough to just convert right over to Pandas."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 12,
    "metadata": {
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    "outputs": [
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t6G+7/0993Z6w27W1tZozZ45OPbxMm7eWa8vOZsfnZtr8rxaqZ9fU0/S8/L98\nOntx2l4bifPy80/2tdZVt10DJPIaGQ2CRo8eHfr78ccfV9++fTVv3jxNnDhRw4cP16RJk3TKKae4\neq3Bgwenq5m25syZk/H3RGbw3eaRl9dHbdqrWw8NHjwoajvfawosn3O6PsP20z6Rtu+SJHVo30Ha\nsSvqMU7vzXdbmArle11Ts1zSTkn2v+F358/Q6qotodvfG9hPgwcPkCQNOb5JF9/6viRp0KBjVZKN\nyi+W/f/Qww7XwX27pvRynnyvljZ9tih8MedC+M3kK8/22dbvN9nX6rhmuzRpq+1rxAqKsrpOkM/n\n029+8xu9+eabGjFihGpqanTeeedls0kA8kxTM+lw+YiUFhSqsrLYgUv7imD/c+/uHXT3lUN18Vn9\nQ/d17lChA/fpIkn6cvEW2+dnEnMuUciyloB6zTXXhP5+/vnns9UMAHmuqYWTdD4K2JTIBgpBjy7t\nJUk/+cF3bO/v2rlSkrRle50GHtoz6v5unSu1epN013Mz9fq9/6V2FdmbK9RIEIQCltWRIABIFYUR\n8lMgvC4CUDDMoL6PZd0fq0P23yvm860pcH5/dncOjq8oZARBAIAwpx9/QNrfwzoSRMlbFBLDjBsc\nqsB1qIw9suNUPS4bGAlCISMIAuCJxma/Ppi+WnvqM7vSOaX1vVdWlv5Tg/V7y3ZvN+AlcyTIKZYZ\nfHhvfX/gvrrjihNt7y+1jARN+HSl5+1LBHOCUMgIggB4YtzkJXri31/pyfGZXfWZy2fv+f3pT4Gx\nxq4USUAhMX/bTuM5ZaUlunHk8Tq2v/2SINZ0uJcnLrZ9TKbQQYFCRhAEwBPrq4JrY0ybt0EfzlqT\nuTfmHO25TKSnWYsh+APMO0DhMH/Zyaa17dxtv+5ZNjDSjkJGEATAc8++9XXG3ouTtPf8GR6ZyfT7\nAelkHpOSndrz7ertHrYmNeyZKGQEQQA8l8kTJydp7wUynAJDEIRC0tYvkzsFDpKV651MvR0q8AFu\nEAQB8ETWTpa5fY7OS/4Mf5e5lP4DpC64/5TkfwykXO+fyPUgDbmNIAiA5zJ5XmKhTe9lolABgQ8K\nlTnFLYcqXSct14OM3G4dcl1RB0FTZq/Vui27s90MoODUN7ZkuwlIQSYqQjU0UXoXhSpUGiGrrfDC\nU+MXaM7iLdluhiMj14eqkNOKNgjasLVWj7w6T79+4CNXj29qCWj6wo3krgMOspYNxy7pOWt1uFzv\nCQZyzeQ7SJxgAAAgAElEQVRZayUlPxI0/JSDPWxN6u58dka2m+DIvCTbuLVWDXS+IUFFGQT5/QEt\nWZNY9ZWZS2r1lxdmZ71mP5APjh/QOy2v26l9eVpeF+Gs6wRlcw0fRhSRb5au3aFFq4LXF8mWyD7v\nB9/1skkpq6woy3YTHO2ua9KO3Q268r4punb01Gw3B0nIZkdbUQZBT7+xUKNfmZfQcxatq5ckrdyw\nKx1NAgpKl44VGXsvBiq8Zx0Jyubo9+Ovzc/aewPJqNnTFPo72ZGg0hyrqNCuojTbTXDU3BLQ9l0N\nkoIZPsg/2UywKsogaMrstQk/J7QCdG4dm4CclK7AxJB0QJ/OEduIgrxmDXzSMRLkNrCqbWj2/L2B\ndLJeI2zZXpfUa5RYgqDuXdql2qSUtavM3ZEgiY6wvMdIUGYl83mbzykhCgKyxjCMqF5SToDesxZG\nuOHxz/T5go0ev34g/oOU3VQ8IBnWFLjdllGhRJSWtl2a5cI+kOtXPf6Au+MJclM2f+FFGQQl85Gb\n6SElOTZMDRQTw5B8OX9Kzn/WdLiVG3fpvn/O9vT1WwiCUKCsRye3v/NI1o6eOubFxUUMlN+y2ZFZ\nlEFQSiNBBEFAFhlR3ZLfrNyWnabkiYXLq7V8/c6EnpPueUAtLktwx2rH0rU7VFuXXE87kC7WbJFk\nM0fKStue19TsV0NTdgOhQI4Pt1//+KfZbgJSQGGEPGB+R6WkwwG2MtFBYBjMy0vUzU99rusSrJoU\nSPM6QW57yJ3S5rbXtmjUo9OoBoWc47NeVSV5rCopCb80q0kyrc4rVdvr9PDYOareWZ/Vdrgx65vN\n2W4CEkQ6XIYl84GbPSHJlrwECp01CEpHz85NT36mhiY/+2AGpLvn1ykIilwfxWkkqGZPcKHVLdvr\n9Ni4xCp9AulkPT6VliR3iRXZn1TXkO2RIOmTuev19H8WZLUdbtz1/MxsNwEJYiQo0xw+8Gnz1jtW\ncwmE0uHS1Sggv1lHSdNxSPt6RTDtzS4EYkFPb6V7ovHC5dW22yPTh5ats0/js1YENBemBHKB9Rec\nbKnryI6eZOcWeY11u5AWzAnKLLvPe9XGXXrwpTn69f1T7J/DnCAgpnSO0FiDHLu3yZWLhELhT3M6\n3DNvLrTdXlri052/OjHu8yNjXoJg5ArrcdCrQyLBR2I4HuSXbM45K84gyObz3lXbKElqarG/mDJ3\nKkpkA/ZKLZN5ve7Zse6zdtXh6hv93r5hmmysrtVHX67LdjPisjspvfjeIs9ev6zM/tTz1rSVGnRY\nL9048viYz49s3bufr9JV901RHesKIcuslwjWUteJeuCakzXkiD6SpJuf/DzVZnkiX2ILqkrCraIM\ngpKxuz4YHDESBNizdhB4XV3M+mp2/RANedJTeuW9UzT6lblas6km202Jye77e33KMs9e3ynbzhzR\nK3cIkkyRF2Nj3lioDVtr9TWVApFl1uNgKlcLhx/UXYtWbU+9QR7Kl4Wpm8kMyCuUyM4jBEGAPeu+\n4Xl6muUouXjNjqi7J85cE7Vtd73f80U+vVKT46Wd050OFy9dpXf3DnGeb7+dkXpknc/h7yTsthwn\nmh2yVBAt3ccveMv6bWU6lZEgKEGUyAbsWYMgr0/YTofF4w7vLUl67cOlUfeN+WCL7vvnbC1Zk1u9\nqZIyNhH0iX9/ldTz0p2j3adH7CDngD6dY97vdKK0rq8CZEP4SJB3v8cduxtUtaNOTc3ZS/3Nao99\nAh8lc0TzjOWHlenfGEFQgnyMBAG2rLtGc4u3J2qnA+Oh++/l+Jza1hTW7TWNnrbFC5maCPrB9NVJ\nPS/dPaknH9M35v0+n0/f3X8vVZSX2t7v1DpG6pFt1n7SM4f08+x1R78yV5ffPbloFwZNpPAOQVB+\nsWZfZzrOJghKEOkWgL10jgQ5HRpr6/NzInyuVy8KpLlEtlOe0KVnHx76u2ZPk5qa/bbFDpw+PiZE\nwyszv96kjVtrE36edfSnZ7f2nrXHXCJgxfpdnr1mPknkmEk6XH4xwkaCSIfLCrefOzEQYC+dQVDk\nte0Lt52px0adqhUb4l8QmJUfc0mOx0BpH6lyOtH17dkp9HdV65ptYz9YbPN8+9f1uiAHitOO3Q26\n+x+zdOV99ktmxOJl8YALhh3i2Wvlu0R2bUaC8hfpcFnidoQn2cXPgEJnXR3d6yBoxfrwRTN7dG2v\ng/bt6upkl+y8mHTy6kDf2OzXJ3PXq6EpfnW8VRvd9yA79aR6NdLiFGTZLUa9dWe96+dvrt6TUrsA\nSdq5O/mOEy8v4oYdt793L+aBXB/BNhEE5ZfwnxUjQVlhzT0f9+ESx8eRcw7Ys54gvQ6C5iyust2e\nr+lPf35muv7x9jcpv87YDxbr4bFz9OJ730bdF3nBsmB5tavX9PsDjuuleTVC5PQydnn/e2xSHp2y\n9Z5+w34RViARdQ3Jl9z/eI5364Dt3zt2gZBMy2YMtPde7lMLGRHOL9ZzVaa/OoKgVtaT+0vvL9bm\nbfY9iswJAuxZT5Be98Q59UCeM/TAqMc98+ZCfbVsa9j2q+77UNU2IwrZ9J9Plqf8Gis3BEfIlq/b\nGXVfS8RoTucOFa5e05xnZVdpzauLC6eUIbtOpgXLq7V4dXiFv2yuMI7CV5/CumMLXXY2pOLp/ywI\npYsWjdZ9vszFArSUE88v1qP5hGkrMvreBEGtIk+qDKcCiUnnSNAnc9fbbj/9hH7q3KEiNAF51cYa\nTfh0pW55+ouwx23YukfvfLbS0zblAnPkxC5I9Cd5DDODoF7dostYJ/uakczmdu/SLmy7UyfTH/8W\nXhGLGAjJ2FXbqFuf/kJL14avNba9pkEfTF8dCvJTCYIy4d3PV+mhsXOy3YyMChjSPj066o0HzlWX\njrE7dCiMkF+s5y+7rIZ0IghqFZlW89wE+1QVeiABe4E0BkFbdziP4nRqXx7af4ut88IMGewOSy0R\nxzS3g9hm+tkJR/TRNT8dqHNPPjh0n1epCkbrC40acaxG/Kh/aHusdON3PlsZmhvGURhONm6t1T3/\nmGk78vufj5dr/rKtuv2ZGWHb//z36Xri31/p0/kbJOVWOtXAQ/a23b69piHm87bXNHi+VEF2GaED\n3uD+vSRJ+/XqZPvIYjsPIHkEQZJuefpz3fOPWWHbvvx2S5ZaA+Qn80K8rNSnFn/mTr4+X1tPUqyJ\nu+M/Tj39LJvmLq6KSnsz1y2zSy9LdtTGDCjLSkt01vcO1N5d23Lx6zwqSW5eY/p8vrDgLNZi1GPe\nWKhrR08N3mh9/g+Pz62J48i+R16dpxlfb9azE76Ous9caDTyOLF6U40kafuu1sAphc7ORNazSdfr\n1TU067I7Jur3j0zztC3ZZLTFQLr6p8fo7quG6rTB9vv/o+PmZa5hSFnaV2SIgSBI0lfLql0Pf+fr\nRGwg3cyRoIry0tBI0PylVZq/1L6ogVd8Pl/oorqQB2r//Mx0XffI1LBtsUaCPl+wMey228/G/B7b\nrr3anrgygQpzsZgXoT6Fp8C5KTzT4g+EWtSlY2XU/blYEh2Z09ga6JgBj1WLJcC343UA44Vk5iGb\nhR3M4M4r2awOZ6jt+6ksL9XAQ3o6Hi+2bK/zLHUX6edlWflEEQQB8IR5fqwoL1WL31AgYOjWMdN1\n65jpnr7PYf26hd0uKfGFOifinaNzKc3FC+ZFwbJ1O6PKZD81fkHYbbcXMObDSkLzjdru8yrNxHxJ\nn8+XcBD09zcWhtrUrXN0ELRwRfonpiN3mT8hu5+7eWFsV/RDavv9pXKUMFO1vFooNZm4zE3xgGRk\n8+hpGEbUZ0Gx3gKRxR8WQVCCCrmnGUiFeZFtTkrdkqbqRT8/47Cw2yXWdLg4R9NANsfdbaQyahEZ\n1Pz0pncTerwTM6AMFV2wuS9VZltKfL6w3vf2lWVxnztt3vpQq/ayCYJYy63IxSgW0twaBJU6jgSp\n9bnJv705T+XiM/vHeaQ7uTQ6FW8eUjoZhl1A6PzZcKmWP7L5XREEJYjCCIA98wJ5d12TJOm+F2en\n5X0i00N8PvcjQZFlo7Pt4zn2Ve/cuPjW9xOau+h2ECcQClBs7vMoCGpqDjbGVxJ+YdOja1u1uN9d\neIztc/c0tGjrruCol8/nU2VFadj9pXYrrqJohFJEbe5raYkzEuRBwGHuIl6tKejUplh7YrrSi2IV\nqElGIul1wYeGfxaxdnUu1fJHNtMsOVsA8ETkcWzD1trQ317OpYtKiSjxaU9Di6tFCnNtbY1Urtdr\nEyxS4LYDJzRKUxLdo/6vDxYn9J5O3mpdC8Kn8N+JdS2j9u3KHZ+/ZEN96Pl3/WqoThjQJ3QfC1oX\nN1+MKMgfZ06Q+dt574tVSb+/eazz6mfoJi4zDCP8QjIPAoC5S6o0/A8TtGD51vgPliRFp8PFGgnK\niw8BkrIbsBIEJYiRIMBe5L7R2NQ2MbnJw1KtkRe55s2/vjw3brrGNQ99bNvrlK2eqFjV0JzUNTTr\nhXfsS/jH4jodzlK5LZLXQWTke1i/20P238vxebvq2n5Phx/UXbdePiR0+45nZzApuoiZvym7c7VZ\nsMVptPDT+Rvk9we0ZM0O2/vdiOxESJWbQ8Ttz8zQqEfbKsF5dTTr1N65IyJVL08Mdqj8e8oyV483\njOhRsVgfMZdq+YPCCDku33pYgGyI1UGwq7bJs/eJvLiwXkjPWRw/PcyuEuSv7v1QD770pav39/sD\nmrN4iyejW24vlKzHoMfGzU+q3Lfb9oYqt3kwPyJeO0oiCiNY9erWQU/88TSH1wj+O+ubzbb3r7eM\nLqG42BQ1DDGD45Ubd+mf7y6Kuv/rFdv0fBIdDFaRc+pS5TSN0frqc5dUaVlr+fzGZr9nnTrdu7ZL\nayAkub+ksv0/xfiI6bDOI4wE5Z6Olh3fWhGJHQuwZ8TofP/lPZO1sdqbC9Oo3kBLIDFldltKXEWZ\nQy69zS68eVudps3bELW9uSWg2rrwAO7fHy/T7c/M0NiJqaeGlbjMh7PGL5Glr91auKJaDS6WAmhL\n53FegygVfstVnc8ndY6x+nuHGClxkrTVZkFMSaqt82Y9I+QfX4zfrbU65L8/sh+B+Gx+9HHASUNj\ni/7z8XLV7Gk7Rvg9Hgk67bj9bLfbFRGZtWizLrjxnbDjYKoBUYd2be/jZaZprGDVTrBEdvi2mHO4\nuFTLGxRGyEWWA0djs+Xqjh0LsBXvZDt/qdvc79isJ2XJ+UTYey/7C+jIdsYaIbn6wY900a3vh108\nrdwQXCtn+sLEghG73He3lWwTrez22VfRF3JfLNikv74y18V7Bf81LyY7xglEEvXKpCWhv0tKfDrv\n1O86PjZeZ7p1bkf3Lm2V4vZ4tKgr8s+3q7dLsu/s8KrEu+mlDxbrH+98o7+/sTC0LbLEfKpOGthX\nr959TtT2jjYjNJNnrpEkvTm1baQ41WUBDtq3q+U9nTssEpXoSFlwsdSILIBYj0+iTciObK6/SRDk\nwPqVWBddY8cC7MUbJfUqJe7AfbqE3XY6lzqVSo483sa6SNhUvSf4HMvoRbfOwQpm22sSK29tl/vu\nPh3O3XuY/5f7X7RP7Zv59aa4rxGI6Mk+c0g/HX5gd3cNcOF1y+fg8/liptvE+3xKLVW+Tjxq39Df\nzcwJgg03+1Eix6kVG4IpaNW72kYkvS6MINkHPHYjQeb+Yq2CmUrgZxjhHQ3ZzYQxoqKefXt2cn40\nWTsFzx8w9LuHP9FrHy5N+jUIghxY9x9rGVrS4QB78XaN2vrUg6D/+a8BUT2ITr1ITmlckSdHv4u1\ngwJG8ID71PivQiNBXvQqu1kXR3J/Qo/3fykrK415v/W9zIu4ivJS/eq8o1y9f6LaVcRuT7zedOsF\nWnlZ298URoDdLmM3HzBSIiMnZtqlNZD3ujCC6abLjg+7XV5WIr8/oOtGfxLaZh4brf9Pf0rLAoRX\nZEtHj73bdNtgYYTwbccc2lMjzznc8zYhs5INWLftqtfKjbv0r/e/Tfq9CYIkHdCnc9Q265cSVi6T\nGAiwFbeDwIN9x26Rw8UOlZycmhPZzvoGd/NkVqzfqfe+WB0z3SZd3Ha+xLtIcXNdZlcdLl3pCvHm\n/MRLmbEGPtbRKq/TnpB/7PYZr38XexqCQZB1pMbvcWEE09Cj99Xwkw8O3W7xB7Rle52Wr98V2mb3\njqn+n60dEdbPdE99sxqa4h8743F7HA3YTAry+Xw64Yg+to+nvzp/RH5Vf35muj6ctSbmcybNXBNa\naiEVeRsE7ahp0Ir1Oz15rSt+fGTUNuuXYi6wJjESBDiJ15vjxZ7jtMih7fs5vOHcxVWq2hEs9fzy\nxMUaecdE28ft3N2W7mYYRvS+n+CxwO6iyMUgVEJvFS9YcXNhFjkSJAVHg7wQeUFmjoQ9NupUjbnx\nh1GPj9ebPrh/r9DfQ4/eV6cff0Dr+3CcLnbrtuzWHx6bpnVbdoe2eZ0iVdc698w6TzEyndRLB/dt\nm5/j9xuu9ufI41Zzi1/jJi9xtfCpYTh3hvz8lvf005veddNsbxiGbZDnuJgs12r5I+Krmru4So+O\nmx/zKX97bb4mTFuZ8lvnbRA08o6Junb01LD5Osk64uC9o7ZZ9592LlNWgGKWiXOO3UiQE6f2PPLq\nPF1+92RJ4ZP0I31uKS4QCBiuJjpv3FqrVRt3xX2c9XXdcJ8OZ4RVqorkaiTI7Mm2PLifzWh5Mqwd\nSlLbSM5B+3a1ze+P114z6DEdc2hPSaTDQarZ06Qla3bouQlfh7Z5Xu699QWt6w6Z75HMGmDxWAOr\nFn8gaj6kfUdL+H/6/emr9dIHi3XnczPivp9hSD7LIdcuVXD6wvjzDL1gVx1OEduevH5Y2ONRmDZ6\nuARC3gZBplSHevfv3UnlZSV68c9n6YXbztRjo07VQft2CbvoGHbc/qG/s1nFAshlmRglPSiiKIIk\n/f7iY20fm2pp53LL6EfAcPf/u/K+Kfrtw5+4fg/XaW4JFEYwR7lsueo5Dv5rDfp8Pp++u1/XuHN4\n4r926qNnppISX1RQbM4RYiQIpkxP7G/rRPD+tUsjgiA3/53I0Wazk2T1phpX72ndA+2uf2a4KLZi\n+7oJxoh21eGk8OPU/r0768Sj9gk9Hvkh0a/qyvumePbeeR8EpRqTNLSuat+tSzv16NpeB+3bVR3a\nlau5JWBJC/G+RwcoNHGnBKVwVurSupZMf5sqZWUOo0PJtOfTeRvacvot2wMBI2qCsRfnWNcXZW5H\ngvzRI1a/u3BQ6G83I0Fti6WGP3j1pprQ8TJZ1ouoffbumNJrVZRFf+9mtTg3xS5QHKxFApzWj0o2\n3bOtnHzbtkAarxusI0F+v02Kro3Ix5Rbjpebt+2J+/zId/CqIzi0npPrlzMcRoK8SYf7atlW/eKu\nSa4+E3grm6mLeR8EpZr2sHfX9lHbzJNrc2vqxo6wuQEpvR1QsMyT7Z9/+T3PX7uyolS9ukXvq5Lz\nATTevnr93z6N2vbAS1/q9SnBcptdLIt4GoaR0Mnf9rE252q3r+l+JCj6eNg3LM0suTlBUtvoipsK\nW87ta/uPuJnfFWvkqdym0h0jQYi0YHl16O9ap/WjYhwsEl1nJ5CmwghSeGDVEghEZcLYvWPkMcZa\nTOSKv3wY8/18vuhFsHfXNenzr5JbsDkVAcP+M41OCQz+m+i12kNj56h6Z31YCX8UvvwPglLslbjq\n/KOjtpm9Qk1mEFTTELqPwghAkGEYWrO5JrQPGq3/Djxkb/Xv183mCc6vNW3eer1vqcIYCIQHHYZT\nQricA4RNO2IvmOlUVe7rFdVR2wKGERVgxDoUPPPmQj034Wut2rgr5rxFtykp8XrKThnUN9jOgBF1\nYdRiaXeJiyO+uTh0ecRIS8/WINTu/zNp5hp99OXauK8dCAuC4jfG5/PpiIN72N4X2T6pLV2IOUFI\nRKy9a72lsIKb55m/cad1ylJRGjES1Bg5MmvX0RJx7HCz35lKSnxRacVX3TdF9704u+0tk/xvms9L\ndTQ8csStorVzpHpn/MIPVt27mOu/NcR5JLyWzcvqvA+CUp0T1LVT9ArIoSCo9WTvRRlIoNBMm7dB\n1zz4sZ7+zwJJ1tQQn9pVRBcTiXWce/ClOXpy/ILQ7asf/EiX3zPZ8mT7ykDBu2IfQW8YeZx6dG0X\n8zFWZrnbessFRiBg1+Hi/L7vfL5Kb05dod8+/ImufvCj1teIfvybU1do8ZrtcdsU70LBLDXtDxih\nEWyTdcX3XbVNcUefauuCcwY6dQg/Ng44MBiMXPLnD3TuqLe0aNW20H1/e22+Rr8yL87/Qnrh3UWh\nvxMpciEFizP06t4hdLuiPPr55gUei6UiEbF2rxsejx4xlqSFy6tDQYh1hMIuRc4r1nS41ZtqNOrR\naWH3282ZiTUSFPf9fD59vWJb2DbH0bQEJZou6NgPFrFtzuLguo43P/VZQq9vrvW0x6P/H/JD3gdB\nqean2u2I5sm1LQiyXAwxEgRICuZQS9IH01dLats3fD6f2lVGpyol0jO6vqo2rCevocnvmBplF3BZ\nnTSwr677uX3xBDuVrZ0g1rSv4EhQxJwgl4eCzduChQrqGuxPrms2Ofc0u32v0AhIwIiqwNYpYrX5\nzxfETmXZ3TpvonOH8OdFXjw9ZQla3froy3Vtr5dgENSlY6XuvnJo6HZUL7gsc4JIh0MCYnWk7HFY\nR+yf77UF9Nbnm9cN6SiRHW9dranz1kdti7xGSqTzoaTEF9WpEsku8HIjNBLkukKmQ4phxNPN41d9\nY2LzF5n6nT3MCUpBqulwdgcqczjVPJhZL4Yi82OBYhU5gmEex0p8bfuQVbIXBYGAodr6Zsdg54Qj\n+uikgfvGfI2Bh/bU2UMPdPV+ZrnbBut+bxiqqXUuPe3G0rX265pZ5x45iXeSMIOgmj2NcUdB1ldF\nlxet2dOkXbXBuY9vfLJcktQ5YiQoMghym8rnJJEeaZM1kLbO1TS1zQniQF2sEr2Y/ee7i2JeRzgV\n8KhrCO8kMb3zeTCtt9RN7mmC7DJX4omXDhfr/370d/fWacftl/B7umF2QLsJgmKlt0Y+O5FRfysz\nwKKjO5xhGFq4vDqtx9RsfuJ5HwSl+sXY9Sy0pcMFX9t6MdTsT31dIqAQrNsSfjFtHQkqtZn0nmy1\npP+0XpQvWWs/h6e0xKf/+e8j4r6O2/c3H1a9q20kKhAw9Oi48HSvRA7cO1LMM49X7Mz8bG5/Zoaa\nW2Ifo+wCqhG3va9L/vxB2LbOHWMHQan69QUDXT0uNNFZhu3vysq8wEu1cwz5aeHy6oTnF/z7I+eJ\n8F07VTgW8DDTRiX7C/l0zAnq3b1jwvthvHS4WAHGyHMOT1t1XHMdMjdBh5lG+83KbXEeKf3mZ8dI\nkk4Y0Md1Wxav2a75S4OZDSwwFG7ukird/NTneuilOel7E+YEJS/ldDi7kaDWdLjGZr/mL63S4jU7\nZHZsf7EgMwuDAblsx+7oi3rDMEIVxewm3yZ7LrUuWurEzWu7OYFKbccE62rUqfYOzltaFXb7lz8+\nMqHXjrfm0drNwVGZ5pZA3PSVZevsR6QiRabeVKa4RlCkvjaLo8YTr3fdDJIYCSpOD7z0paev55PP\nsQNid5wgKB3pcOVlJfrP/ecm9Jy6xpawBZQjgzrbtvukww/srvKy0rhV7pI9rpvBlZtUqC9ipPBG\nPr/nXsECLrMWbXbdlj8+1jbvi5GgcEtaCwjFS6NORapr+qUi74Ogdz5bFf9BMdgdp8yRoOYWv24d\nM711KwmjgBQ8+Y+8fWLUdmvOtpsLgBZ/QDc9+Zkmz1wT83Fulnxxk5dulwZmx67n86YnPo9+YMTJ\nctk6+5EqSaraEV6p6IeWBZjNNLRY4s1xsea/xwuCvvx2S9z3k6J7srt0rAy73bYoYeZOYK5HgpgT\nVJQSqXzWs1t720qQVsFDgf1v6eC+bQVHMj3yeOgBe7l+7M1Pfq4Rt73v2Ea77YbajuHpWnMrlA7n\n4qOLPH7GUpbiiDVHjnArN+zKdhPSKu+DoEkz16R0ErZNh2vdiZosFxPlZdbqL+wmKF4X3/q+7faA\nYbQFQTb7VeTJbvXGGn29Ypsee21+aFvkvhUIuFsQ0E36fcDlybykxBeVIrLTJlCJ/P/EOlGP/WBx\n2O32lW3zm9wUGGi0KUt96dmHh/7+0YkHhl63KU4QFMusb4K9p3ZrMkXORzB7XFdtbJsbdNOTiVVk\ncsMMcA0jushDJDNwYySoOLlZe8q0dUe9bnrSpnOjVWVFcBTE6SL95GP6hv7eUdMYdexK52+wh836\nhvFs3BrsBIo8nNoGQZZNdgVIrJId8Uq0MIITc8TavG5LtlCDafm6nVzjWcz8xv2IWrLcfNyBgKEH\nX/pSn86zzwxJdr5+3gdBUlv1JdN9L87W+Bh5vn16tJVZtduBS0O9iW2fqvXYykJ8QDRrOpzdeai5\nxR92crHrYQwY4SdFfyDg6oTkZmHCWOdaa6pXSYnPNuiw8/lXGzXuwyX6xZ0T1T5OlTrTOUMPTLg8\ntN3aPNYS0b/47wGSpMMP6h53TpAkbdnedsy0VuG76/mZkuwDusi5BBurgyurX/fI1NC2yHK6gYCh\nT+dt0O66Jk+WGvD5fDryO8FS3TdednzU/WbxDJY1KD6GYURdC6TitsuHBBcLjTj+GIahv7+5UHMX\nt6W4zlq0WeM+XBr2uP16dfasLZHqIyrWfWe/rg6PbGMGM9FBUOT6Z+bcztb3ap0T7TTK1qtbB9vt\n8ZjXXqkGHF06Vuih356sZ285Q1J4B1OyZrscLUfmbN62R9PmbXBMeU12Ee+CCILe/qwtd7+x2a/P\nv9oYth5FpL06taV12HVilLVu/MsLbQuCdelQqqO+s7ckehkzzTAMjXljQagkM3JTwGib7GoXkrzz\n2Sq9OrntQsFuYCYQCF+UtMXvbiTIGgOZ6ayRfnb6oY7Pf/A3J4e9ltsgaOGKar30/mJV72rQJ3PX\nxa7fAl0AACAASURBVH+C2kZtTMcP6B33OXa9sdbPr7L14r+lJRBWInvEj/pLki45u3/Yc7dZij78\n4q5Jcd9fkvbpEV4l6+sV1Vq+fmfMntxp84Mnrfv+OVuTZ7YtpvrMzae7ek/JWnAjePsPIwbrgu93\n19DWdDyrju2Dn0NdPUFQJhmGoU/mrAv7XWVaQ4wRi2QutH0+n3w+nzZvq9N8y5y+9VW1evvTlZq3\nNPx89PanK8PS67wuJGJ1wQ8PCf198/+coJFnD4j7HHM/ipx/Ebn/htY5aj2Km0sGHHFwd9vXfffz\nVXrk1bmOSwA4aVssNaGn2TqsX3d16xysCrdX50rHc4BbK9YXdgpYrnGzf8YbcSzuIOjTlaHAxFqx\nxc47n60MWyneLm2nxKbHo31lSegE+9yEr2OuAg9vLV+/U+98tkq3PP1FtptS1JpbAloXa/V0y0iQ\n08jMyxPb0sLsKi0GjPDFPlv8gYTnBHVoZ98TOOKs/nr17nN07GG9wrafccIBYbcNo60yZDzW3tGP\n50Sv0RFpv16ddOA+XSRJ1/58kCRp9qL4vY52QZn1xFFa4lOJL/h5mZ/fHb86UT8/4zBJ0oWnH6Zf\n/eQo23a71bt7eI9vQ5Nf142eGvU4ayU88/fy9YpqjbV893162JcdtmOe3Mwe3h5d2+vIfh1sf2Pl\nZaUqLyvRngQvyJCahSuq9fDLc/WHiMU7MynWJZLbGOjuq9rWoSrx+ULHs7a5wQorMmDV2OzXhq17\n3L1RiqxpoScetY/KbRYOjnT7M8H/Q9RIUERmi3nL3L0uPedwnTmkn353of1aa9trGjRl9jpd+Kf3\nwrYvXbtDm7c5fx6JlMhO1EGtx9hEA7MQ0uFi8vsDev+LVdpps0xBMtx82vHOWcn+jgoiCJLaJm85\nHaBMY95YGHbb7kRaZpci5/OFvoSJM9borWkrkm0qEuT2ghTp9circ/XrBz4K22bmYRuGoUCgbU6Q\n0wWJ9UBm13P70ey1YemmLf6AZyNBJSU+dWxfru5dwteRmDxrbdgq6EbAcN3JkWhv7/eO3Cf0Gf3w\n+APiPLqNGQQNPCQ4Gn3Zfw2w/Vyqd9aHgqCKiLade/LBob+TGc2udJnuZw1AzFGpstKSpDP1zdQf\nt2kuHduVJ3/xg6Rs2xUMfKt3pVYKPhWxjhOG3PU2DzykZ9htu7TQv702L2qbFBytzdRcko4Rc+PM\n+XmxmIuIRl5xRn1uESOv3Tq3029+dox6dmuv7x3ZVnbarmferFIpSaMenaYr/vKhY3sSqQ73/aNj\nrwMXyVzeIDIwc2tbiksaFLpJs9bqyfELdM8/ZmbsPeNdB7QkWcAjr4OgXpaeSbO3cE99ckOyVnb5\n+s1+I+yizZpTj/SiZGVumGYzIXHAwcH5GS3+QFh1OHNyfucO5aE5HFJ4D2ajzYreT45fEDYXz+83\nXF3Qhp2Q4/xePpy9Nuz2wX27asCB3fXd1rz6qfPWu06Hi7XGiJ3IwMQcFYo3h8VMhzv5mP309sM/\n1gXDDgltsx7DqnbUh46FdgHasNaqdH6/oXNHvaVfxbhIieQ24LN+/OaJqbS0RO0dRujiMb+LyJLd\nTtpVlsZMjUJhitUTbBiGtiZQYUyK/r2brx9rtCdTVeIig6A+PTqqb093o6uR6XCRbTZv2hUYaGfp\niLA7HmxPIHgoSWCdoL1bg7zv7u+uKl6q67JFzrlCuKrW69/l690ttxCXi90m3s8k2YqgeR0EWS+W\nGpv8+mrpVr33xWrXz3/m5tPtR4JsKszsqG0JKy07ccYafbWUOSqZQKWW3GWOoJx/wzvyB4xQ7545\nTL73Xu1148i2CezWEsdOF/4Pv9y2KFuLP6BdtbFHd6XwkSdrdbQXbjsz7nPPP/W7Ki0t0e8vHiwp\n2GM6Y2F61gOL/CWv3hTsOR3zn4XRD7YwR6YqLWkvkWliZa2LmZnrl5SXRY+I7bN38ELJrPizKUa6\nip07rjgxocebJ6ay0pKkT1I3jDxOh+y/l35+hvOcLqvystKkRo+Z65m8XDhExwpANm/bo8vvmZzQ\n60UtKtoa0A+zlLePlEh1ulR0aN3nD963rSDC7S73zciPKaoSppniZPNfsY7G2qUnVZYH73dXzMa+\nPabmFn9U267+f+4WWLZ2ZO+OM0XCTjrWeCokXq+fa/5cYhX4iJfulmwHRJ4HQW3/6Xv/OVu3jPlC\nn86Pv7CiySkv3W4kqGvH6AuKW8YwRyUT0pEzDG8styy86fcHQiWKzbVvunVuF7bejPVvp9GWr5a1\nTS52e2CzdmZYfy9uSsmavarWE98XC9OzMNxuh3TdyNGpSOZnZU31M4MgsyKa2RP8RWsAZ9dTa37+\nyabzHtu/l+66MvbFVuScLil4IZLseiMDDuqhv177A9dlgSvKS+JWyHt9ylLd+MRnod/K1h31Ou/6\nt/XCO98k1UZk/xgd67r7y2+rnO9sNWrE4LDbketkmb/rnjbl402dO1Q43uel0tISvXr3OXr42lNC\n2/r06KgXbjtT1/z0GMfnbdtVH/VBRa4rdsMTwYVDIys9SlL/ft1Cf9sFfGYn14ezYh/PpLZjtlPA\ndP4N74QCV3O0yG1wYn1UotlBUS8AR151fpijk/36dInxXvGCoCJMh2tX2XZB4GUvnt2coHOO62bz\nSGQCMVDuam/ZBzdW7wmt1/N//+9o9e3ZSVf85MiwE1epZUEfN6XmW/yBUFWyW35xguPjrD1T8S6A\nf2qprCRJ/Q8MVj2yFklZt8XdwqqJspbijjTq0amOAb/ZI2pdCNBM+TK/A3O9HjNNzj4ISv2Qf8yh\nvWLeb73osF5gmVWmDnGZ0pKsirLSuGslvfjet/pm5TbVtQaSXy0LXiSP/3h5WtuG9ImVVlUZUTjg\n1xdEjyiceux+Ybcjs0RCx6sYh61Mpm53bF8eNRrTo2v70CiRnev/9mlU8zdHpPabaYN211SnDbYu\n8hzdodPiDxbPsa795sQMMo0YJ3hzrpl5XHQbBHWxVACOt3i0HTpe2ww4KHh+tC7QGwpgJc1eVqvX\nIsrDJ8rcbWIVP4jXIVqU6XDWFZvtJPPjl+xHgnrv5S4fHd7jgJS6uobmmD0pC1dU67Fx86LSD+KJ\n7J03A4nv7LeXnr7xh9qvV+ewiwnrSczN4qV+v6H2lWVqX1mmIUdGl0Q2tbNM2m+MkwplbfMNI48L\nzVPKdgrE0rU7Hct8micAa6A24kf91a9PZ113kX3VJrsgyKt0nbO+18/xvhpL+on1QsqcZH7RmYd5\n0gYn5WUlwVLrre+9bVe97n5+ptZX2VQ2bN0nXpuS2NwuhMuFdDi780SPrsEiKJHFUsojzvEn2pRb\n9/mkM4e0/c7N31Os/6oZKF2c5t94LGUx5u5V7aiP+q7Wx6j4GSneemxu5nAahqHn3/5GC5YHR/zd\nBI6hIMjl4ct6LP/1Ax8lPIc72QvqQmR+57YFhwxD787eqX+9/60n7xXr/BR/JKgIg6B4P9SN1cn1\n5kYOg5sih8vT4dm3vvbsB1UomBOUml21jbrwT+/pwZfm2N5vGIZufvJzTZ611jYFYufuRk2bZ1/+\n+dj+4aMCdoGEdZv1HOpmJGjRqm0KGEbcAMV6f78+sRcptJZ6tk7+tTu/H7Sv8/B8MuL9P+w6bppb\n/HrxvW+jnt+3Zyc9/sdhOqyf/foddr1qiS7S6mTQYc6jQdaUP7veZK/a4MTs2TbTKp+b8I1mfrNZ\nj7/+VdRjzd/gpurMlDZG+tgFQeaFW+QIbGQHgbkGoFWJz6ezLWt6NZtBUIzz0dS5wePkVIfjZSZU\nxCmXHdn+ZNdXsdPY7NcncZYK2LC1Vm98sjwUmLi5dk0lHU6S4/nLyQFxziFOmlv8+mbltoLquA3Y\ndMClq7vQbh6ryfqz7WhTZMdNp6qdvA6CmuP0Wif7Q3QakjOHBdPprWkrUh5aLDSFdEDxyvqq3ara\n4a53a9XGYPl4p/lyf7eUjfe1/vSXr9+ppWuD62ndOuYLxwDqf/4rfJE+u5Ky1oPn+qpa7dgdTHFw\n03NT39gSDIJczMQ0e5HMyf97d7FPC7FewPft1Sn0d6f20aO9ZoqZ6cnrh8VtRyrsgqD3LcVezLlW\nbthdMDh18CTKLmXYZP5uJKmlJfo7TvfkcbNy0Z+fmS6/PxD6zOwuXpPNI7f6/KuN2rA1PemTcM9u\nRMFMwYwc+Yk8x1uDpIvPPEy9urVXr+4dwiZquxkdMIsnZWq9IDvxqji++/mqsNuJZswcdkBwaoBd\nZ9NLH3yrdyJeP1Lkcd9NJ2ei6XCRnS+x0pDtRK6J5tbT/1moG5/4TJ/MzV4QnC5uzsHJMn8Dsc4N\n1v07YEQ/1k2nqp28DoJa4uy8yV48lzp8EV5dQDhhAVZ7xEDR/u/+j3T53e6qHdXblKKWpIkzVmvM\nGwvCTlolPp9efG+Rrhs9VaMenaa6huZQBTM75WWlYbnCdspKfWETaq+8N1iW2U3qXYs/uP6Qm6ks\nL991jsbeeXbopO50QC0t8empG4bp1suHhEpUS+5KMO/tYj2OWLpactXt2C0ga00vi3WMiPwe3Fa+\nTEas0ZzJlknRdvOzklmoNVljJy4OVcBrZzNXwjxxmj2/iR7jt+2q130vztZV901JsaX5LRcG62MF\nQZH3RJ7j21kuki86q7+eu+XM4NpWPp9+1DoaZF5Y53qnXHlp2//F7ti8bF14WeMJn65M6PXvvDK4\nCPOvzjsq6r4V63fFfX7kxbSbz9MuHTiWuogS1+1crnGWSJvsTG8tSrNkzfaknu+FR1+dp0dftV/L\nKhmhINX60bf+7dWeYL5OrHOD9TsxDEMlERcFRZkOF68YQrKTFCsdFlu0+4JqE6w88vR/Fujhsfa9\n6uMyOAJUtb0uY2sapIp1glJjLUVtrmuzdO0OPf76V3rns/Beu5ue/FyvW+ZHhBbYi+EHg/aLeb/P\n59ODv22rYmQGZW5+fy3+QDAIcnHya19Zpi4dK1zlj+/Xq7NOGNAnantkkPOrnxwVlgvttBCrW9b0\nGkm67+qTwm5PmrEm6jnWdJVYJ+d7rvp+2OvZ/f+7dIwdhLkVa1Tc2ntuN1qf7iDoih8fGfr79SnL\nQhO929n0BpuBuFnVa8BBPaIeE4t12YTilv1jdKx0uMjRhsjfYKyLZLPjIJHiS5cPP8L1Y73Wb5+2\nEZpLzz7c1XM2J1Aqv0O7co34UX/H6rqJinca2F3XFPpu3RZ2iUzxqygv1VPjv9K3q6KDE7uRqFSv\nOeLNnUqnD2evjVttNBF2H8X21oIV1vu8mLYQ63OzfieGojus8qo63AMPPKCf//znuuCCCzR58mRt\n2rRJl156qUaMGKFrr71WTU3u6rrHDYKSvMg302lM5toYdkOxF92S2IrE736+ynGoNFNpcMvX7dTl\n90zW6JfnZuT9UsWcoNQ0WhaO/Oe7izR3cZVGPTrN1XPf/MS5Wpa5RkWXjomXhb1tzBeu8ub9rYuw\nJlK0INRxlcSJ6K+/OyXsdp8eHcIunq0H3kd/f2rc17s6ogpVZBB1xME9wuZVjf94uabOXR+6KNm6\no17rNrdNXN6rczvH92pXWaYjDm67iLf7zLp3cX5+ImKNmllTSexG69M9on6gwzyujVv3BEsEW7RE\nzPNI9CdjN8+oGOXCIdrufG+mQUVeH0WOiDp1fEptF97vT18twzBUY5nzZlbAjHRsjDlz6WbdN2Pt\np9YAKZnFhXt166A///J7GnRoT/3iv90HfZEBRrxd7uJb3w9dMyVb3HLBsuAaktc//qkmzlgT9lux\nu45MNrUqFzoDPGfzBU22KYE+/A8TVJvEmkySEl4s1QgYUeeRcZOTu37OeBA0Y8YMLV++XK+++qqe\nffZZ3XPPPXrsscd0ySWXaOzYserXr5/Gjx/v6rXi/VCTTfe2HjhOPGofHXNoz9D2o78bPYEyHdLZ\nw7hodXDyezYnbybCKII1DAMBQ9eN/kSvTl7i6rEm8+KtxmH9GTt/fma668fGyu9+6Hcnu36dSPOW\nbnW1gnuzPyC/i8IIVoEkL2glqVOH8IsGn8+n26/4nspKfbrkR/3D7uvTIzxvvFP7cr14+1mh27/5\n2TGhY0cscxeHr2Hy0Ng5uuIvwZTB/717kuZZFmUeckT06JUTu2DDrJYV6UcRI1SJGHr0PjryO23B\nl3WOQTZGgqq22/+uVm+q0a0Ra7uZo5FtgXNam1awciGpwK4N5vyYyAvvyLTUWHNGzDlu73+xWl9+\nuyV0Adi9Szs9ef0wDT/5O1HP6WgzvzAbYv2/rB0yiVYFNR13eG/deeVQfSdOpV6ryGDVboTWqePT\n7Xkgcr0m60X746/PD6WtSW3Hq749O+m/TzpIUnTniFt2mWNuJVvNON1K4qznZLV4zY64j7FjrhMU\nefy1BqjW301TSyDhLCwnGQ+Cjj/+eD3yyCOSpM6dO6u+vl6zZ8/WsGHBCcennXaapk93d5EWb6TH\nizSqm//nhNCOV1ri0z3/9/2EX2PVxl0J/8DveHZGaEK71xoc5ojkKn8udDOm2e66Ji1fv0tjP1gs\nKfYBx5pG9vZnKzVp5hqNuO19xwXq0vXpmZVcku81C4ocebVqaQmmwyUyqmN+dskMOETmGZf4fDpk\n/25644HhuvCM8LK3kb3H7duVhW07/fgDwk7aD0eMMpms86Xit8/9f8ouhbCbw0iQ3YWIW0OO2Ef3\n/vokPfHH0yRJsxcFO3Bq9jTZzhFI994cax2idVtqw/at0DwPIzwYQmKSrczkbRuCX96PTjxQ1196\nnH5+xmGhi93IC6YD9+mikwbuG7odq6y0NZ3Yujj0Zf91uOP+WJngHBSvXX3BQP1g0H7qEWPk11pF\nLtXU+PI4FemsIgtM2KUYOzXH7ZygB35zUth8z0hbd9Zp3pIqvfT+t6FrswP6dNbg/r0lBav0Vu+s\n1/A/TNCbU90vLB1qdoLnntmLNuv8G94OVRe0U1vfrEkz18RdB89r5kfu5tiY7HqdTsGjdQ5suqZF\nZDwIKi0tVYcOwR7Uf//73/rBD36guro6lZcHe066d++uqqr4qztL8SPTZ95a6LqCVio2Vtfq1clL\nbA8kc5dU6bcPf6LHX4+/eFik7TUNMe9/fcpSfTzn/7N35oExnP8ff+9u7khIIveFIK64giAkqKPU\nraquVktLW3UU3ypKW6Wq9FC9tIo6ezmL1lHUzy1C3JHDGSKHSCSRa+f3x2Z2Z2Zndmc3Gxubz+uv\nZHdmdmafnWeez/X+3DL5uMZ0/Ksa1SEdjusdP5+cif7TtyMhKUN02zSOEtXJi/e0xs/BM+K/hcou\n5PWUiC4I4UZJuARxFNqE7DqqSUFRmWAEscaZvZ3pVpBwTSP2sZNeaIlZY9rqiQM4Oah4D2mlUsGL\nxjQMETd2Kkt6X8pwXD23p95rQkUpOUbRx+M7ol0TP0SXLya9PXSRseTbORg5d7fofpV9P3sZEa/o\nP3279u+yMgYlpWptDcHTUidZ1agK3xu7SHK0V6Fzy0CM5ERuT168x9tWoVBgUJf62v8NRSe5BhT3\nnjck52tIPfFJ8GyHOpg+KhI1XBzwYo9wTB3eSm8bB849X9Fm8w4GvgsuaZmPeEYlID7HSs0RclNp\ng3zc8PX0rgj0Fn+2qNUM5q44hl/3JeJmeZ8ktZrhpUku3aCp3V65/YKsz+Riair2rnIF0CUS9eIA\n8PVv8fj6t7MmGWWWQNsYlTMk3CbpXMyOZrHHFnxvj4vLUFJahsPxdyrNeW81YYR9+/Zh8+bNmDt3\nLu91uQ/IxnU8jVqGybcfYrmgczFbv/DjrO4mnK00Hm6OmPXtEaz/+4qoFv3V8vDgv6dNN1bsRBJg\nGYZBatpDlJWp8cuuy/jcjLqeqhp2laKqq/FYAu4V/lqeErdu9xXRbb/bnKD9W6lQ6OoZJNxP5qY6\nyKWVjJQvAPCQqGcRpi4IkasOxzJhcHO0b+aHvm3lR1hYhA8vMc9jj6hQdIjQLPzdOOlzjvYqPdUp\nOZEbPy9X9OtcT+91c8dt6eQYzBgVKfnZwga3gP6CTo5SXouG3nh/bJQ2+sX9vClfHJLcrzKlVgFN\nWqJcKfPSMjXGLdiLm+V1V5a4V3b+Xwpe+uBvrRR8daBKGEFq6TRYsfRy7u/Q0OKaWzvDXSRz93n/\n1SjePlIKs9Zg5LON0K1NiN7rdnbcdLjKjwTduJeL8Z/sx4JVJ3mvi2USSK0DTU2lHfpMA9HXuT/X\nn8uNnBMX7/HmQVNSzLWY6eARGoZisFHI2/efrBw/e59w19uhfuJRNlOM6XV/X8aQmX/xrl2h4Dfi\nLiouw+/7r2HxutP4aft5scNUGKvEbA8fPowffvgBK1euRI0aNeDi4oLi4mI4ODggPT0dPj7GiwoH\ntHHC6v3GOx1n5zxEXJzOuvaqoUBuPnAz5TLuXJeeqKYN8odCAd6+3L9ZiopLUFCkGfhzF5PgDn4U\n6/wVXfNJY8cSkpx8DaV5/BSn3/8vCxdvFsKnpm7o5ByLy527urxNU/e1BqmpOuWayjpfa38PhcW6\nyaMgXzPJ5eTmiZ7XxRTdbyovLxePS8rrgvJyRbe/flN+R3C5CO8NLqZ+lwV5hvOICx8XQ6UoM+m4\nzza3M+tchFxLStS7B3nnxlEhKi4qRHy8Tpo0Li4OBRzvlaFzuZ2mr1p04pT+9nKvxxVAXJz8usLi\nR/x5y1Fl2vdtChl3EpGZVvFFoiXO76fNp5Gdq+u9lJWju+cYxnAapnChFhcXh/zHZfh+iyYFa8P2\n42jfyLymi08bNzhzTEXHhbv/jftFuJNVjI6NjX+PtzI145hxPx1xcZq/GwU54cptfWM0Li4O9x7o\nFrlXLl/C/dviyyHucm/VX5e0fycnJ8OxRDPWQr/42bPxlW7sV5Qb11OhUgJlauDS5asofshXpvSt\nZS97LLPzpBfx7DGOnNQ474SpiQWFj/U+p1jCUZuQcNYkYZWbN8QzgW7f1jmskzgpu0nXdMX1N++Z\n/psuLW9xcP/+fZPug+wHujYUUvuxgmGZmVmS23ANFUvN348eab6HvDzd3PjokbiaYFJyqt4aWIpf\n92rGYM/BU3hcohnvtDtpiI1wR1amK04n5SP+3HnEX9KMz610feOvf5QH4pIe4U4W/zdlyrU/cSMo\nLy8Pixcvxpo1a+DurpleOnbsiL///hv9+/fHnj17EBMjnjvPJbpDW4TUy8Oqvy5qc9DFqFXTHZGR\nkfjn+HU0C6sNN7fHQHoR2kRKe0rFiIuLQ2RkedrKBs3gBfnUQE5eEQDNAPr7ByAyUlc3UFhUig82\n7NT+HxkZqd1XeywuG/iRpNp+IahXvzbPg/7Bhm0AgPsPdZOO6LEMcOhqHIB8s/a1BpklN4ATmoVy\nZZwvb2ytRG5+MfBHGgDA06MWkHYPjo7ORn8nHh61NPtmFqOmu7vo9ik5iUC85erLXh8YgVbh3gjy\n0S1MxuXXwk/bNB41Q99loyP5esWTYXWDcPwqP+o1eVgrfPWrxqB4XMLAx0viuzCA2ePK+X7Dw8NF\nu8mzlHK2re1ZC23bRML7n2y0bOCNyMhWmgf+n5qFkqFzuZJxBfHJfFGM8MbNAKTxXrPY71Qw1zRr\n0hAvD/bF/QcF+H5zAl7t15Q3vnJx/vOe0Q70bdq0Mfm4QmSN7Qbjwi/J9/jNZzMeliKieUsolQqM\nnLsbsa2D8OaQFqL7lqkZYKOuAXFkZCSu3MgGoBnvwKBgREbyi+avXM+Gq7M9gn1tyzjizjEV+Y0K\nx/WDaZrn3ZjBHY1GjJ1Ts4A9GQgI8EdkpKaJ8/m7F3Hltr7CZWRkJG7czQV2axZsLVpEwMfDQINM\nkd9SvXphiOTUFXG3aWuB37jFEVxDvXr1MMYrACu3X0BQaF1ENg/gbefiIn/OzXpYCOy4J/peZGSk\nZlxbNMHGQ4f13s8rVCOwDl9y+//O3YFw7gOAdm1N+14LlHeAY/oOJn//AOCcfv+7iGZNgD36i3i5\n34Pyz3sASuHr64PISP0+SlI4HDgAoMTgZzn+vRfIL4Cnl6fkNiWlZdo5yVLPis0njwDpRXB1raE9\n5sYj/wFZ+pGyoKBgREbWlXfg8t9Z48aN8KigBPg3E4GBmjV0QtpFnE5KQlj9hjh/Jxm4rf9bAIDX\nXohB2Omb+GIjvy+S8NoNGUVPPB1u165dyMnJweTJkzF69Gi89NJLmDBhArZu3YqRI0ciNzcXgwYN\nknWsYF83zB3b3uA2DKMRJlj++zlMWLS/QspRLD/N7oEfZj4DBzuVwZQ8Q40N5aT9fbYuDi998I/F\nBRLkau1XFapDnyBz6yR46XASP2pLp6r061xPb4E8ICYM74xojeXTuxrc97WB+g+GPh31J83u7fjp\nG9byqpryqc3r14ZCocDK2T0waZh+Dr4hxNI2hJ3d3x8bpbeNuax6vyeim+sWcGxxso+HC+aObW+W\nAQTouslXBdo09jVrv/TsAjx8VISCx6XYXZ6rL4ZofxHevab//oyvD+PNxf/aXIpvZafDybkPdf3B\ndFvvMjB+XCeosTSrYd0b6n+eYPx7RoXqbVOVeF0w9yoUQEi5MZ58O0dsF9kYqo+Sw9pdl3n/38mw\nTMqXUiItUernKqyNNMbDR0WIu6LvhBemphu73+Wkw7G/N0PPwoqKFInB/sx5v3eJjzFnHlBAoSco\nwaoaFpWUGb03m9armGLzE18NDxs2DIcPH8batWuxdu1a/PLLLwgICMDPP/+M9evXY/HixVCpKnZD\ncUlIysSkpQe1/19I1qQSVaSZla+nCwK8a0CpNH/yN2W3D348Vv5QtoygwdPmhbS1BYMxTlwU96iJ\noVQqdGnIEj9pQ0Z0oLdlGt4BQNfIYIQaUOQBxB8y7q4O2PxpP72+O9wmrKZEbS2JsXmie1uNsfZS\nn8YYGBumt4+rkx2eaRuMKS8aNooc7FUYL+jAzm1a2yHCX7S5q7nUruWMmS+31f5vqE+KKUwfXPPh\n2wAAIABJREFUVXUiywEc1UFhvyZDPMh7LKtuUmxe4r5mSDDtaWlPIJeK1pQYw9Aj4FZ6HtbsvKQd\nM+5cYUhJi5tWZSzFylssSiQ4J0v14Kos+nWuxxOLUECBED/NWiA9Sz9tTKrGVAwHGcaDwV+I4KNy\ncovEtzMRqXGVWlNwn0+uTrpEKbH6oDsZjzBq3t/44MfjWhl1satc/vtZDJixHUUGnOJyiv51DWOl\nx4Vb02gpARpWvlrO8eSuq3n9hBTQfm3sb44V5ikqljaCxjynifZy+9KZw9MVEpBg8UTz+5VUBJVS\nye/ZInjf0OKdfe/arQeIv2o4hzI7twij5v2NYbNNa8wqRUnZUyaRXQXkVysbsfnl+t1c7DicAoZh\nwDAMft13lTPZalAqdV4UsemnpFSNowl3Rd7RFJB/+U4Xk3rEcIsWzSFEwgC3t1OiXmBNTBsZqW28\n5+aqK863lhFkzDiY+EJLrJzTA0OfaainFgdoHgpTXmyNZ9rqFyYL6dupHt5+oaXoe5V9/RWRyOYi\n7L9SFXB1ssOzHepg5ZwesrZ/VFDCazAshViEmtfVXPA+9/+UO5XT/sAa5BUUa/ubKZUK5OYXY+3u\nywYXfaZiaAE2fdl/+OPfa1rDkrsQ+9/otlK7mRQJEotMMIInPqtyKVcoxho4O3IqIBQ6yfz/zt7R\nX6+YMOUY6kekxcAaWji/GepPZwpSlyD2e2pevzbvd5D/WBed0aTn8ZmwaL/277uZ+eXHLf9czgf/\nc1xTa5WVI90Xr2YN4w3H2fERa1TKwo0EWcp3rI0EyTigsBm1FF9u0qWvcceI/d7Y5+7j4jLJTCAP\nd92zpncF+tzZhBFU0830jvWWQKlU8CJBl1KykHQrB1sPJYFhGINpXOx773z5H+auOGbwgcHtKG8J\nSkrEG1BVVSx5jsUlZVj++9lK68FkLsIHKsuKredxISULt+8/wrrdVzDtq/947ysVCq33h5vm+OFP\nx/HVpnicvsyPKnEfgus+6g0nBzu8NkC/47kUUvURchEzFLh0aR2EwV010rXX7+pytq2lOGvs4a5S\nKgzXEphIz6hQnnQvy5Fz4jnRFeWLqbEY27/pUxcdloPwjpI7To8KS1AoSE95VFCsXeiwiM1L3AhS\nviByz93cllJ81+7WpTLZKRX4ZM1J/LYvUatyaQkMPQMKyherjwo03zc321ss0s1GP7gLb2NOAJ7n\nupwGwfzUz84tAzHz5bb430vShpe1ceHM/0oFX8J/5NzduJyqXz8jB4VCge1L+mNsf+lnicFG4Iwm\n9enHrec1tVoWIueRuMKb2P03d1x7yXQ4Y5Eu9r43JdrFwjAMbtwzLl4kZ87gNxe1jPOYvffKeA5/\n8XPhZi8Y4totnTNXoVDoHc+REwmSijJzUzDdZRiRUtiEEWStGhelUsGbnOMTMzD1y0NYuf0iUu48\nxJ7jNyT3nfvDUew4nKL9P5+jmMINwwJAfoH8NLiCxyWY/d0RnDEQXeIqryRVMBf4SWDJVIsDcbfw\nz/EbmLT0oGgur7UwNL/l5RdLRgIU0C0CXJztyo/F4PTldOw7dZM3cU16oSUvXYl9ABrzgnIlYi0R\nkZArT/+Q8wB7ZMI9UFF6cOqRxBr5VTYvP9fkiUW+6gfVwsDY+hVKDzaFWm5PLlLUpbUmnfKl8rQJ\nQHMPGOP2/Ud4IOjRtuiXU3j9k328CI7YPcuNIAlTjHhZA7ZjA/HqpopL1dr6kopGgriNSa/eNN6J\nnv1OuTUTwiao3doE48PXOgAAatd0RpfIILz3sn7PLyFi1yJs8qxUKhDdPAA1nI3Ly1sL7nXaCepl\nHhWW4H/LdcIFL/VpDFNQKBSiUv9s1CXuivSaRK1m8M/x69h+OAUTlxww6XMNIdUrTsyodrRXSRpB\nxmqeimU0MJVKL5Tr5JWzHdcIsnSdniXnL+49qlDoH4997uY8KpKs3+capqb0EdQ7F7P3rEIIb+Yn\nhaHczNIyNf74V9oqvpSajRVbdbrnJaVqbTid7VrMIucBwPJf/B0kJGVi3opjktuUcCb0ijZJexJY\n8mYu5kTBPvjxuMWOW1EMpXswMFAMqdA1v2W9fNwHNjea0jDEA44ik7lSqcCnEzuJpnH0aBeCF0SK\ngiuCn5crFr3Vyeh23OtIyxSX5KwMuL83BxM6oVsKlcC5Aliur5k14NYyffR6hyf2uQ1DPLBlcT+e\n8EYPGcXrWw4mYeHqU9r/tx9OxrlrmQCAyZ8fxIkLd3ExJUvUM8t1MGUI0l+421syul3VmkkXltc3\nGFNzM8aNe7q5S9hbRgz2++U+l+0F9cWTXmiJ2uXNdJVKBaaNiERHjkCIFJaeA60FtwDfmPNYqheM\nIVRKBSYO5Tsa3vnqP9HfKFcM5r+zd0xy9sqlS+tgBPvqN0yVumWkHIIO9ipM/+o/zPr2iOj73/2p\nkf9mnSBix5d6hMtd38jZLpkj961WM3j4qIi3BjAH9r6SE62SjcSXwTrjWKNzzc5Lks3UuYZpRZyG\nNmEEWQtDKh1pmfl6WveGijSLiku1XlJZ+bUSyHkgcs/LGp5uU7GkEST0DD4VMIbrorSRoPIGl9yo\niUbCXYNSqYBC4vKb1PWCj6DA8MPXO2D84ObmnrVBGtfxNLrN4yLuA/vJOTpG9tIVD1tKMKAi9Gof\nypOPreoM6apL5/tmRlfMeqWd9v+6ATWf6LnIaa7YN9qwpOuPW/kd4z9edRIzv/k/niHDzqPcFBSh\ng4lbtMy9LyvC38euo//07cg0UG9gLSoaXDQ1OnnluiaVi1frI4gEGIv4SCE0CExVEasqcJsglxpJ\nlzJ3/Hq1D8WitzqhYUgtAJqI3ocb9WtqQnzdeEXtRxIsn/KrVCowdXhrvdedncS7w0jNFyl3HuLq\nzQc4n5wpuY7jGpiGmi6Xlalx/W6udq0m1yFS8Ni4gtyiX3TOG7Wawasf78XbSw7IUp+ThHN6xtof\nAPLWa9x1qoLX8F0D1/kotR7mrgmqvRHE1jmE+rlhSNf6kl2CLY2U/CIAfL7hjN5ryQaKYR9z0ihM\nKVQXIud24i6or17PRnZu5Xc2z80v5qX8mYKlhBEePirC4Xj9ybgqYMx2lZooE28+0E46LuUTex4n\nf539zr1qOiHIp4ZBw71TC75HtHW4j9YIWPRWJ3w/8xnDJ2kCSqUCY/s3Myj7zFVLe5Id6bnGoLWc\nBANidP1l/jGQVlsVGc4xIkP83KFSKjCiVyN0bhloxbPSsXRyDIY+0wAb5/fGrDFtRWuw5MCN7JSV\nqVFWphYUJvN/s9wmkRk54k0cTeWbP84BAP6vkmrGjGGoDUTijYqlWpu6CGe/X67xVFHpZi6v9muq\n/fun2fJENqoa3uVRMIBfH2RpmtbzQlRTf4PbqJRKvPuSru9P1kP9dYi/BZw/YoaNk4P4tUstprlR\nSW42CZe8fN39beh59eO2C3h7yQGt0WewVqoClKkZ7f0pR31OCu48Jqf2yZAByMIzgjivs7cu18kg\ntfxTcdbfFQmGP/FmqZWBi5M9Vs/tCTcXBzjYq5DxoFB2gVZFMLV3iSEjoOBxiXYgG1ag14acHwN3\nQf39lvP4fst57Fg6wOzPlMPIubsBwKzP4Z7vn/9ew5Bu5hm57317BLfSLRjStSCGJHlz8h5j/2lx\nRZh7nLoDezslsh4W8uQ82cXR6wMjoFAoDHpXWzb0wa8L+mD30et6UtdN63nJug5TYCWlpYhpFYT0\n7AL8Iugh8SSIbh6A+MT7siIJlUFapmX6ZFgDR3sVAr1r4OEjXbRjeM9wA3s8WRqGeGjn2A4RGsN/\n0gstEeLnhunL9Js5SsGda8vUDAb+bwfv/YLCUjAMo73nxn68V/ueuX2YpCgqqYCntwKILVxZTl6S\nL/Uvhpyn670s/TRZXk2QBVPla9fUGRBVXQ5biiZ1PfFK36ZwtFeiWXkT6A4R/jh2Xl9B1FHCUJCL\nsVRilUqBEE6ErUAQZejTsQ4upmRp/1/4RrRZ5yFWU2yqaIAHp5ZRSqBg9zGdop1YmQG7G9v/7Wxi\nBjq1CMSfB/Sb+VoCnpNGrUbB4xJeJFAMsW2ucWrz5NYlGXMeCr9+4VEdOM4LKSc499lckbIOm4gE\nAYBXTWftF+/t4Yw3TegLYS5yU3Sa19dMNleuS9f25AtCnbU5Hhtj/PHvNfy6r9ybIMMKetoUp7mT\n2Oqdl8w6xt4TN6qsAcQwDN74dL/k+99vOY9Tl4yLOJy7lokxH+3BD1sS9N5jH9rs76p2TfGHuIuT\nPYZ0a2B2o0lLY61yh5kvt8Wmj/tY58MhX8msqvLdu92wYX5va5+GbHpEhSI81HiKJhdjC4K7Wfn4\n6td40ff+PX3LpM+Sgn0Erdt95YlGS1kyZUrimoURJ2NeQTFeW7hP73VudMqSkSBDmR9PCwqFAoO7\n1sdznXQCBrPGtBPdtqKRoueMpJmqlApeurHwfiopVWsVFVuH+yCivnlNMcWUwwyllkU11e/Hxs3U\nyXhQKNo3iOt4F7sXhcaTnPS2VTsuot+0bXiQZ3q2Dvf73HE4BcNm78IZA+IUh8/ewbDZu7D6r4uS\n22gNEgMP5vzCUvxz/LrB1Dnu96NmGAi7pXKNKKkGsNxIUEWymWzGCBJSEd1wueQ8kpfXzWqnGwp7\n/lkuoiAWDjTGmp2XsG73FRQ8LsGl68YlLp8medYzV+/j7LUMyfdPX07H9K/+46WacHlcVIqV2y9g\n2W9nK+sUK8xv+xItsoA5fVljKN1K148i1A3U1GL4erpg8cTO+FLQmLSqYo2FHcuTUkwTg6vMVFUM\nUlMwFnWsqpiS/ihnHt1/SmPsGEsRKSktM0upk3t7HJCIFlcmcmoEzMXYr0eo4MeSnq2LjquUCtQx\n0sBZLqUyGujaEhVVqLS3U4kaFHIpKVNr06YqEpH38XDBNzO68upQpdYLAPDOCP0aIm4Wz+TPD2oz\nW6QQjz7xX5PKJOJ+1uaDmijR8QumR1W5z84t5ceRyigBoFUr5kamhK1EWIPE0My3cscFLP/9HNYY\ncFhzU/bVakZXE1T+lbhwarYSksTXf9wUP0PjaQybNYIA4O0XWqJDhOG81IpQ8FjeFy9nHXftVg4u\npmRpDWxzbvrc/GL8J6Pm5WnoDQQAF1OyMG/FMYONBT/86Tiu3nyAg3HintXth1Ow9VByZZ2i2ZxP\nytTWeuy0UGM4KRQKfoF/47qeVbKppRjVoVGuGNyUhFf6NjGwJWFJGgTXkr2tKbLtWQY8lVkPCzH4\n3b8w9YtDOFqB4vCTl9JNchr8tO0Cftx23viGBmAq8VlizIaW+uTeHevw/pejRCkHc7zx1R1uLY2Q\na+VGv9T8VlKq1lscm0uInzvmjWuvrRfPE4nksLg42euJBMmJ2nARE50QilZJiRRduaHvyL5mgkIw\nC3edpyxXAjTUBFrM6P1sXRzvfzlpZ6y0/U2ZanJlal2XIHaca3CUJS8kZ+nvBPC8JEI5d1MaU9u0\nEdQzKhQzRrUxvqGZlJbqT8PTR0bqvRYeak6Nj/6x2f4lwv4ELIbqSv49fRO/7NJY5uZEgn7adgGr\ndkiHSSuDmd/8n+jrq/+6yPP2AdI3d6Wma1SAWd8dwfLfz0KtZvDAQkpRUlirj5YlYL1lzpVYxFtV\nmf1KO4zq3cgmG5lWVbiF2saY/PlBWdut2HqeVw8khJXXBYBP1pyS3M4Yx87fxU9b5Rs12/5Lxvb/\nUpDxwPw5sjKzCoweWuJ94VxhqZ5b7HHrm2AoPy30lCEdbw73sqQFQLq3DTH42SUlatzJ0NR8nbhY\nsfoyAHB1tteKs+QJmt8KZZh/fI/fkqCgSNzhEd0iQDS1XMzRLHxJKhIkVp8lXO9w2X00VdSZwT0H\ntjbOkEqcWHlHkWB7do2pMFB3x6rnyTVc+etWzU6yUjE532dA7Ro8EY3+07fjj3+vIel2jtF5+uld\nHcmkMqUs2a7i3KI5sWaA5jT7ZB0Jjet4wsfDGTNGReKNIc2x8I1oLJ/eVXQfoZXO7bz8xcZ4bc6q\nKZGgnLwibNp7Fdv+S9aGZi3FsfNpOCkxuT00kGr454EkfLKG3zdCqjFfohkelCeJ0HPbo12ItobM\nUjwNvaCkeC66Llo29MZH459cf5mqQvtm/hjWPfypTCt7WvFwc9I6mcQcWmJI9bFg4TbF5sLOw2L1\nBebyl8yoMtdT+urHe8zODniSgVq55yg0etisioo2Me3eLhSvD4x4or2unhQTBjfHzJfaPtHPZGX/\n7SVSUOU0IDUVdj3IGkEdIvzRIcIf88d35G0n/A1x++9wYRgGHiIiGeLCCPJ+v+z3wo08CtPSuHz7\nZwK2/6c/x3DT2th7wJBKnJhRJrwOthEy91rC/Phr3uxczdotISlTnpBCqVrP4SHHcVFTUOsV1Yyf\nerlm5yVM/eKQ0ePYvBFUmbD50LHlnckBICxQvw+GOYtQ1sPm7eGMlXN6IqZVEOztVIioXxsO9iqM\n7q3fzfnqDf6Cf+KSA3p502VqxqSUieW/n8X6v6/w9rcEDMNg4epTmP/zCdH3t/1nOIWN7cbOTmpS\nUq0RYZY1KOSy+9h1TFi0D6lpD3HfgBdHWCswfnBzLHgj+qmsA6kMatZwxPzxHdHIxKJ1gjCXJZNi\nsGxaF8S2DpKlZmluD6c7GdZTABQ6jcyN6FRmarVw0ShMjZX7yfZ2Svw4q3uFZa1VSgX6da5X4Saw\nVRF7OyWiWxhvGmsqY/s3M7qNVOr/g9zH2joeYbqTubA1f0nlRk2wrxtmjWlnkhAVl7z8EriKKK6J\nrZOEr0kZRWxkZC1HFTVPIvWWW5MnPN6eE7rWCuz9bigSJOZrYw0a3XlojEeGcys6OUibEYvXnhZ9\nvT3HYIm7el9bB2WKvy9E0LvL3F6C1cIIqkjfHUOwKVjc8LuzyA1hb0Z9DzueUov7F7o3xPMCqWi2\nZwSX9AcFeMQJ/ZaWqU164KVl8iVIj523TD8KY43RxB6uPh66iYothGMnNalIkLeH+OTWLMwLCkXl\nRUm+/eMc7mTkY9LSgxi7QDoVRjgxOmqbLupf/+RhrXj/t2tiftEpQRDiuLs6mNTU1c3FvAjD/lOa\nImVrCNUI2zWYa8yUVeK5C+d0Ybq31CJS7Fr8vFzhWsFIUHVi1LONjG8kA2dHfpSHdVpyleOkFq9p\nmfmYN649Vs7ugaHPNLTI+QibX3tJqKTKJa+gWLQBu5gQijCaxED8t8qmk8kRHcnipPszjHRNI3vv\nSK2TAH70RUrIhc1q4s5ZhmToxdZ5N+7m8oQethxM0qpoViTnwdy012phBHGL4FbP7Ym1Hzxr0eM7\nOdihT8c66B9Tj3dDj+rdCJOHtcKYvk0N7C3O2y+0gquTHYb3lJ6M5ISLy8oYjJr3t/b/0lK1Vibx\n04nGC0aFE1R2eV+IuT8cxRJB0ZwpHDHQ3O/jn0+IaueLeYwc7dlIkPhNKzbJzBrTDm4uDmAYw72b\nngRSRtiZq/pSlsG+urSbLq2D8NbQypeBJ4jqzudTYgzOlUI5c64KlSHYOc5Qw9HKQjjv7TtlnrKc\nsRSf2d8dwWMzFeS8a/G/18Nn5TW6flqEf6oin7wZjRG9GmFYD8v09Ypq6g9nRzt0buqGUD83fDqx\nE3YsHYAJg5tL7tM63AeApk2Bq7O+SEFFEJZHdI0Mltx2/KAIow6Oh4+KtKqsABBTXnMkFglat1vQ\n744Rd4CwaxmpGm/umowrDc0wjNHaWUOZPNy062KJz75Z3maEexyVUoFxA6Qjfmo1g7OJ93HkXBoy\nHhRi4pID0icow47p3jYEK0WiuuYqCFYLI4grt+dV01m0bqciODvZ4Y0hLfDaAE2H+xe6N8TwnuEY\n1j0c3duFwNvDGfPGtdfbz1AuedN6Xti04DnUE0mvYymRWPgL4f5gueHQhiEeqBugCSl+tUm8n4VK\nYOWzevnxiRk4FH9b1ucLefioyGCHc1OKINk+ENzQLxcxwYQOEf7aZlzWrpe5KrNmqUtkEE++t3vb\nEL3iwRA/KqAnCEvTINgDTep6oWNzndIo19ARS6Ux1NixX2ddj5aCxyVITZNW0KosLqXyFajMLTwX\nGhzcZy2gqQu4LKNtgxjCYy3//ZwsA8fc9EQCaBZW26KNjWu5OeK3hc/hmRY1sXxGNzQINi4S9cFr\n7bFj6YBKyXQQRoIMGQ19O9XDhvl99GpPuIQKUrJmjG4DpVKhi5hwfq/ChsYMw39/cJf6AHROEal7\nkut4mP3dUe3fcmx/QzLvvhxjU8oxw/Y3466bVEpgQEwY3F3Fv6e8gmK8/8MxLPrlFC6lSii9sceS\nkQ/XpXWQqGFM6XAGCLVQnwAh3dpovAjN6nnxXh/duzFG9OJHcNo09kVMq0Deay0aeGv/NscwYw2Y\nZ9pKezOEfLJapz6kVCi0uu9cT+DuY9fxdXlfHWFnbGFO6ZB3d+BoQhomLT2Au5n63bvF+PvYddnn\ny0WYmgfwVVPSRHLspfTjHYxEkCoLhmF40uqfrNYJPHDDynPHRvH2e7VvU94Ebmen5BlF3doE48up\nsdr/3+fsb0rvE4IgxBnSVZd+zF0olpaptcqdAODkoKnd5BpNXLgFyMNm79J7X8xbezDulmgNUaC3\nYVEGKYSp02LLh8fFpUZTcoRGiZiIh7lpKmJBJmNRs59m97CYGhzx5OAaGpUpBKMyI1rw8JG0cMlr\nA5th/Ue90SHCHzNf1ghLqJQKlKnVePioCKs4jUeLBGuNwqJS3M3SrWkGxoYBAK7fNewUkTJ2GIYx\nqqhoSEGYuwYtLlFLKtJlPSzkpcs52GnGSyqFbgtHUOuKEYcId3ymvNhKdJta7uJrZXPv+2qhO9s1\nMhj/HL+O0b0t229Dk+rWBB5u8vJKR/duzOvj81KfxvDxcIavpyuahXnx0tbk0DMqFF61nNG8fm0c\nO39XVMte+JDiRh6USoXoD/3b8gfkm0Oa63k5f99/jReCLS5Va2Vd1/99BdNH6SsqCc/B3EV5TKtA\n3vcnfEA/FkR9rlzP1usRxCo/sXm8laFAIwbDMFAoFFiyPo53DdxuyNyC24iw2mgYUgu92tdBxwh/\n1HBxQFmOLv9XpVLwbnrvWs6wt1Nh6vBWCPSuwatpWCwj7ZEgCMOEcKTKufdqYVEpJg1rhcvXs3H7\n/iM4l0cwZr7UFv2nb+cdw8FehUFdwgwKv6jVaqiUujnyyo1sLN1wBm4u9tgwv4/29WW/xpstrmCn\nUvDmHrFUktHz/sbj4jKD4hDCdB6xZYih3iSGYESkD1LSHqJJXY3TUWgsdojwh7eZBe6EdRk3IAJL\n15ufXm8t2OL8WWPaaV9j7635K0/w1lu1azrhYoouEnLy0j00raeLKHu4O8HHwxmXr2fjXpZhhzK7\nnuCiZhij9YUlEobKiq3neSqWxaVlkkZNSamaFwlihRFeH9QcX2w8o7f9Fs4azJh6JTea0zBEPGoo\njL7p9qV0OEncXR3w7f+esXjjVKVSIdsAAjRhelbVrV5ATbg42WNw1waIbhFgVvNKlUqJdk384ORg\nJ5kPmVtgWH6V61kT5neXqhlReW+2C7r++Yhb4sLokVCqtESmISIsLBQ+XIXH+XyD/g35Xrm3hk2H\n+2pTPPbE8zu1bz+cjJ+2XZB1TnLJKq+lMtTMdu5YXcqkk6Mdlk6ORc+oUG3jMEcHTiRIMN6sQdSt\nTQjCQz15uc8uImIdBEGYBrcAmtsrhpW0Z51QLo6a+03Mo13D2R5eNZ3RMES61wzXOMl6WIg95U2V\nuQpRx87fxd6TptXxHE1IQ3x5reHgrnxRHbHibtapZCgFTZjWLBY5Srqdo/eaudzLKsCCVSdw5sp9\nvcj/rDHtKAr0lNKldRBWzumB1XN7VvpnxbYKMr6RDKRaWaiUSqjVjF6q+/0HhXq9D1f9pend2LI8\nK+h+ec+uuT8cM/jZYrfk3B+O6fU/EiLlkBDK+BeXlPEyeyZy6o/Tswp4qnEh3pq1K5sZpXeuJtTo\ncSNBQgf85k/7YcvifpL7mru+rxaRoKrE890aoG+nuhZfmEr1mlhkpPke1yNYUqrmRWnKytSyDRRA\nk+Zx5up9hAXW5Bl1wgiNkwP/Z7du9xW80s+4eISTQGlGmBrBfQCXlal5oWYAaBTqoY2QsOlw127l\n4Jrgc37cqjGADBX7mUpufrFBGc4QPzejTfi4Y+PkwP8uhAsufjOzauHrIIhKxU6lxIevd9CqVG5d\n3A+5+cXaPiGsIWGohoBV3Uq8qW8YRDX1w4mL93ge2DEf7RE9jpjH1RhsxH7H0gF6aTFS3lVAk9Mv\n5aQ7m5ih/XvZtC6YtPSg3jYZDwpx5FwamoV5meTsE3Nqn7h4F8cv3OOpSxG2gVBgpLKYPioS9QJr\n6tWcmQo3+sNFqVQYNUaECEslhGsXIf+euqlXFyO39u7Hbee19etS5OQV4eNVulT9Hu1Csfx3TYbQ\nnB90dUhfT++KrDThCsp8uCUBzo52mDaiNZZuOIMmdT2N9vxks3xMhVZHTxilUiFpAMW2CkJTQX1R\nZfPDTF1nZKEXr6RUbTCHVEjq3YeYt+IY3l3O93YIjyvs9yBXHMBfUPAqFDVYyon8ZOTod0F34hRB\nsoIKhpAKBwv5+rezeHPxfoMeD2MpIW1l9AVy4EwCwgikIQdoZTYMJojqROtwHwT5aNLiVColr1Hi\nrJfbon0zPwzhtC6YN649z7nRIyoUAETnedZAuJSajX+O38D55EzJ8zC3CBjQGFBbBI2vDc1d55ON\nNz0cN6CZnqw469U/duEuFv1yCvN+NOzdlkOhSMo3QZjK4K71K9Q6ZerwVpKS67n5xdrMD7lElEeV\nuM94sfYerFDWst/OYs73R/Xel8P2/1J4inZiCNd9SqWCl4nCUsfC9fbClLYukcH4ZV4vLHyz8lL6\naXVUhZg+KhKL3qr4YJvSGdvH0wW92msezMIbt7Co1KCKm5CM8lCuME9d+OAqFaTYCcVgFEDrAAAg\nAElEQVQXpJgyvDXv/4NnbvPSH3LydCFaYfQJAK+pmdAwEJN63XX0OmZ+83+8iNOdjEf4YXOCNkL2\n7R/nsOfEDdxKf4Rfdl3SfgfCCfLgmVsGleh6d6wr+R6LQqFAiJ8bwoJqao//zojWcLBTikp9zh/f\nAaOebWRxNUSCIPQJC6qF2a9E8eqF2jT2xRdTYjG2fzMM667rdTLzpbZ6+7MpMfN/PoHlv5/FrG+P\nSH6WUPCFLap2dlSJCitsPaQzeliFJy5CxxSXT385jQ3/XJF8H9AofgphHU2sHLcwndkYYnNyPCfy\nRBBPAu765I9FffHt/7qhW5sQA3uYjldNjcHDTYnPeFAId1cHnuBRTQkFNi7czA9vD2dMFaybAOPi\nVDki9/MQQQqtGBWVMxcrqfBwd5Lt9GnbxPQm82QE2Qjf/q8b3n6hJdbM64XOLQONbj+ka33t36wH\n78a9XF704+a9PIuc2+zvdQ/zowlpeg9cuWFpR3sVdiwdoJVy3LjnqqSH8pFIOJrrkXUQGEEnReQo\nV2w9j4spWYi7ko7ikjKcuHAXExbtx19HUrHnhCYff/ex69rt/zyQhPGL9uFeVr5eH45dR6/reV+5\nSMlLCln2ThcsnRSj/b9rZDD+/LSf6OTTsqGPxfo9EARhPgNjwzCqt67rvVjKnFRjZy437+Vq63q4\njOzVCA2Ca6GwqAyvzuen0JWUlmHl9ot6+3ARSmYL+XVfosH3xQQJKAJN2AJLyp+3b7/QEo72KgT7\nGm5F8fYLLU06vp1Kqb1XAgRqj7n5xbwIqxwnQGmZGrPGtMNHr3fAT7N6QExsz5gk/l//l6L3mnDN\nJMbQbsYNJUNUNHX/XRHn0o+zuotsqYNmKRsh2NcNPaNC4enuhIFdwvTe71mehsHCbeDKRo4+33CG\nFw2yREGrWs3wVOs+WXMK18v7YrCFhWkZ8qS1WYR1SuwEwqaYPCoswQNO4Z69nRJjnmuCATG6/hzC\naJShlLyFq09hyMy/eDmyjwrFc35LStX44Mfj2v/ffF5XUChlVDo72hltcsaiUinNkvkkCKLqoFAo\n9DqtyzEa3vrsAOau0E8rUyoVWo81V70TAP45Lt5DDdAogALAxZQso41PWbIeFmLql4dwMSVLWx/V\nQ/B8AeQtmgxBLU+JqoC3hzN2LB2gt4aSontb06JE3AwRtlaZC5vt4uSgEk3BE5Pi7xDhj1bhPlAq\nFfCqKZ5pc+6atEHF7V3Gfr4cVV9zJfuFn2Uu9oK10ZQXWxntG0arKRskoHYNnopG/8718FIfnRdS\n+EPjLsDHLtir/TtRZq0Oi9gztEikr8OD8rQ1tr/R+eRMMAyjjd64OtnB0UGFn+eIK8WUlPI/iL3x\nXJ3swTAMhs/ZhcXrTmvf/3FWdwzp1oBXB/Qgj79Q+H3/NRwxIfXv6Lm7kjVD3HRAbk+QW/fFjSBj\nvTgIgrA9fl3wnLbBceeWgQYbYxtDoVBopaMBIDVNl3omJZoDAK3CfbR/G5uH+k3bhtV/XcSOwylI\nupWDmd/8HxwdVHB3ddB6cMf2bwpPdyesntsTKpVS71nzIO+xXvQ+/up9HDsvMveaYAVR1ImoKiiV\nCtHoixykfsffvdsNy6Z1xTxOuhxLsI/hyFREWG1MebEVfp7Tk3f8eSuO4WhCmmQ/IJZnylXf5BhB\nzcK8MLxnOEb0DMdz0cZT/IUEmCluwKJUKvDR6x3w7f+6YcfSAXhGhkFKM4eNwg0rRrcI4OWpuwqE\nGaSs77gr+mkXYrCNA7mKKAWPS/D95gRRvXs2isI9j9cW7sPw93fjyvVsMAACa9eAt4czXhuor9Am\nlINnz7+ktEy0WFCs5uh5kbDt95sTcNlIWgiLq7M9vtucYHS7wiJdWpypOfEEQdguDvYqvDu6DZrX\nr41xA5pBoVBg/Ue9zTqWUqmAJ8fjO2npQfSbtg3f/nnOYF2ns6MdolsEABB3WAn580ASbzF0K/0R\nz5M9MLY+1szrpa1xEBo8L33wD6+BJADMXXEMC1frq5iK9Qnioir3cs98qS2+f/cZo+dOEE8KmUFV\nPaQMjSAfN/jXdkXjup7Y9HEf3nvG0vMUCgWeaRsCbw9nrJzdQ/t6mZrBJ2tOYRzH8W2IiDDjol0K\nhQIjejXC8F6NMGFwc9FthEp4XIxFbeTQKtzH6HfChYygakDjOp5QKhVY8V53uLs64N3RbXjvN6rj\nKbGnjlA/6R8Vt+CXZfqyw9h5JFVUMvXcNY3qETeti/VG/Hf2jmYCKbfL2jb2EzkXviIJ+xDOyClE\nQpK+opJYvw4xqdacR0X4dK1hSXGW88mZBtNMAGD8oAhZ6noVLSYkCOLpJMTPHQveiNY6atxdHbBh\nfm+tY0kuSoWmZlLI7qPX4ewo7cF1crTTRrR/338Ny36Nx72sfL32A1xOCZSlxJp0G4LbwJptzK05\nTgmu3imUlZY3f3wHbP2sP1bP7YXoFgE0hxJVit7lynMhgnUTV7Rq+khNY/mukbq+RXJqYoQpceGh\n4k1FxTBHJIm9HQO8a2DjfNOcNJOHtdJ7LbKR6eIFlQkZQTbM890aaD2MgEZHff1HvdGioTdvuxrO\n9gab900e1hLLZ3QT3eaZtsGiNSq30o2LKtipFLwmXICmaVdhUak2nOxf2xUv9WmMz97urN1m+shI\nXsOzgselsLdT4vZ987qnczFV2lIKDzdH9O1UD31kqL7VlsjZJQii+uHm4oCIMH4jRm46MwvXI6xQ\nKCTlatmeRH5e+oaCo71KW2y943AK9p68idcW7sOQmX9Jnl/SLcs1P+UKywybvQsbD2Vh056rAHSL\nL7H+Hy0b+ui9RhBVhTeGNMe6D5/Fl1O7YGR5bzCAr+oY2zoIO5YOwDsjInn7znxZV9z/Sl/x/okf\nvKZJiwuo7Qo/L1fMGKU7xgYDhoqYQ9gY3P6MNVzkCTixdG8XghmjIjEwNkzrSPeVcFhwv6cnCTVL\ntWFefq6J7G3FmvexdG+nKQic/UoUdh1J1SoFRbcIwMShpimhcGEY6ZuKe6sOfYYfafJwd8L0UZFw\nc7HHX0dSkV9YYlI/I0uz6eM+yMwpxMQlB7SvtSnv++PqbI8N83tjxPu79fZb+EY01u6+jGkjI/Xe\nIwii+iJMCxHreyb0CBtrFvjR6x3x+if79PY31sOsMvjn+A1tawYhv+1PxIs9w3HjrqY4u2tkMAZ1\nCUN27mOM/2S/1RZLBCEXhUKhzTZ5sUc41v+tk5h/Z0Rrg2qw0c0DtH9LKf1GNvLF1sX9tA7omPIe\nk0XFZbzSBzEmDm2J5b+flXUdXSKDMLIX/34b3jMcG/dcNdrcnSWmVRBiWgUh62EhEm8+QJO6nlj0\nVie4ONlhxteHUVRchm//182kFDZLQpEgAgDwxZRY0de5HklPdye8yEnTeLlPE5MkDdleFiz+tV1F\nUzgAQE5loVv5RGKooFesHwfLx+M7inpYTcXV2R6h/u482XFunZWbi4NeWBzQNEhb/HbnJ9YpmyCI\npwOuXLazowrZggi1WAoyAHwzo6vkMX08XdC3ky4yvfp9jfBMVFP9lGOWETLS8pxEmigaY/nvZ7F0\nfZzoe6VlDAb9bwd+3HYBgOZR4ORgh4DaNbBj6QC8SLL/xFNM18hgoylhK97rjikvtjIomy/MwPGq\n6awnsS1Ghwh9NTkxurQOwrQRkXqO6hG9GmHp5BgsmNBR1nG459chIgAKhQJN63mhbkBN/PFJX2xf\n0t9qBhBARhBRTv3gWti+pD/qB9XEC5wHrDCFgmv0uHG8GaveF1dy4x5nUJf6gtdcRSUhAaCo2Hie\nuZymsGLykSwtGnqjWxv9JqNCmtevjc2f9hPNrQ8L0ik6cY0xYd8hbjofQRCEXD6d2Bltm/ANlb6d\n6oluG+InnhLXprEvVEoFTxDGqVwV1FAk2sPdyaAh1KSuJzYKCrW5rJ7bU7JPx8EztyX3E2v4ShBP\nK33LldIcZToM/Gu7ylI2MwdD5zDq2UYYU55BNH5QhOR2DUM84OJkfP0lB3NS9CwJGUGEFoVCgS+m\ndsHo3o2xbFoXPBddF+MG6KuzsbhwpLXFFNgWvhmNsf01+z8XXZcnz/j1dI3HMi+/RG8/wLCsK0vH\n8rDx6wMj9KJMANCnYx2jNxhXNpsLW6czqncjLHgjGvZ2SnzwWgc0FohIcCNo3CiZMKffyYGfeWpK\nMSNBENWPET3DUT+4FkJ83dA6nF8DwxY4Tx8ZqRfNbiWo+QSA0+ViBu6ujrBTKXmpaIZ6lHm4OWJ4\nr0bYvqS/3nujnm2ERW91MpgN4FXTGX5ertp6JVMFHwDI7hZPEFWVV/o1Ra/2oVg80frOUEd7Fd4f\nGyX6XvsIfwzp1gA7lg4wuf7naYVqgghR6gbUlJQ4bF6/Nm7fz+OlfCmVCnw5NRZTvjikfS0irDaa\n1vVCy4beCPF146n+sA/F5g34xgLLw0fGjaDatZyxfUl/raHTr3M9xF+9j8fFZejfuZ4sD4O7qwMG\ntvdAUHAovv3jLFgH5OdTY+HsYKf1lgJAk7peWPx2Z/Sbtg0AMLp3Y95neLg5Yd2Hz2L3sevo35nv\nqRXKkFNfC4IgDDG8XGoW0KTHbV/SH1sOJvPUpGJbB+nt9/7YKHy5MR52dkr8e/oW7z17OyU2f9pX\ntvfVr7zOSLh9/5h6GGZCWtrnU2JRWFSKnSKd6I3hYYaiFUFUJRzsVRWqn7Y07ZqIp8BWtNnp0wgZ\nQYTJLHgjWvT1sCBdodzo3hrvpFLJVS1S4LNJnXmFe24uDmjRoLZWNttUuA9nHw8X9Gpfx+RjtKzn\nisjIUPRqH4qk2zlIvp0DDzdpxbYZoyJFDR1AI70tJ2f9redbGN2GIAiCRaFQYHDX+ka3s7dTYcbo\nNkhIytAzgtjjyGHu2CheO4Kpw1th1Y5LWDolxuQ6Rns7JeztHNCrQx1sKFd/k4unu3RdBEEQ5tG+\nmR+OX9Cl7f/w3jMm1XjbCtXviolK5beFz2HC4OY8kQAujUI99bwN3P9ZGe7atazz4KsfVMuoIRXT\nKgifvNmJFyWSw+q5urqpICNdngmCICoC19gx1h9kxXvdMX1kJFycdHOasA6pW5sQrP3w2QoJuXi6\nO2HFe93RpK4nGslMCa7hYpnaA4IgdMx+JQqfTuyk/d+YqpytQpEgwqI4O9rhuWjjvXG4cOty2Fqg\nJjIauD5teNV0xqwx7UT7dRAEQViSZvV0Hd6XTeticFv/2q7wr+2K6BYBWLIuDrGtpbu6VxT/2q74\ndGJnfPfnOVy58cDo9t5WcogRhK3TpK4XPnkzGtfv5pIRRBDWwk6l81g+F10PK7dfQPd2laOMYm3k\nylMSBEFUBIVCgR1LB4BhGNkpcHYqJa9ZY2US1cwfu45eR5O6nriUmo2JQ1tCVXQPX23XpOjU8XdH\nxwh/eIiI7hAEYRmahdVGszDx2uzqABlBhNVJTdM0xfP3ckX/zvXQNTJI22iMIAiCMB9rS9BK0Trc\nB59PiYG/lytcne2hUCgQF5eJL6bEwtnJrloWaRME8WQhI4iwOvmFGpns1o18oFQqyAAiCIKoBjQI\n1q8LktuJniAIoqKQMAJhdaaPikTPqFC8XN6kiyAIgiAIgiAqE4oEEVbHz8sVb79QdTT0CYIgCIIg\nCNuGIkEEQRAEQRAEQVQryAgiCIIgCIIgCKJaQUYQQRAEQRAEQRDVCjKCCIIgCIIgCIKoVpARRBAE\nQRAEQRBEtYKMIIIgCIIgCIIgqhVkBBEEQRAEQRAEUa0gI4ggCIIgCIIgiGoFGUEEQRAEQRAEQVQr\nyAgiCIIgCIIgCKJaQUYQQRAEQRAEQRDVCjKCCIIgCIIgCIKoVpARRBAEQRAEQRBEtYKMIIIgCIIg\nCIIgqhVkBBEEQRAEQRAEUa0gI4ggCIIgCIIgiGoFGUEEQRAEQRAEQVQryAgiCIIgCIIgCKJaQUYQ\nQRAEQRAEQRDVCjKCCIIgCIIgCIKoVpARRBAEQRAEQRBEtYKMIIIgCIIgCIIgqhVkBBEEQRAEQRAE\nUa0gI4ggCIIgCIIgiGoFGUEEQRAEQRAEQVQryAgiCIIgCIIgCKJaQUYQQRAEQRAEQRDVCjKCCIIg\nCIIgCIKoVpARRBAEQRAEQRBEtYKMIIIgCIIgCIIgqhV21j4BloULFyIhIQEAMHv2bERERFj5jAiC\nIAiCIAiCsEWqRCTo5MmTuHnzJjZt2oQFCxZgwYIF1j4lgiAIgiAIgiBslCphBB0/fhzdu3cHAISF\nheHhw4fIz8+38lkRBEEQBEEQBGGLVAkjKDMzEx4eHtr/PT09kZGRYcUzIgiCIAiCIAjCVqkSRpAQ\nhmGgUCisfRoEQRAEQRAEQdggCoZhGGufxPLly+Ht7Y1hw4YBALp3747t27fDxcVFdPu4uLgneXoE\nQRAEQRAEQTyFREZGir5eJdThoqOj8fXXX2PYsGG4ePEifH19JQ0gQPpiCIIgCIIgCIIgjFEljKBW\nrVqhadOmePHFF6FSqTB37lxrnxJBEARBEARBEDZKlUiHIwiCIAiCIAiCeFJUSWEEgiAIgiAIgiCI\nyoKMIIIgCIIgCIIgqhVkBBEEQRAEQRAEUa0gI4ioFuTl5Vn7FIhKhEobCeLpIT09HQDdtwTxNGDL\n6ycygsrJy8tDamqqtU+DsDB5eXlYsmQJ1qxZg+LiYmufDmFBcnNzsXLlSqSkpCA/Px8ALapsgdzc\nXHz99dc4dOgQsrOzAdC42gp5eXn44osv8Pzzz+Pu3bvUFN1GoPWTbVId1k9kBAEoLS3FmDFjsGLF\nCty+fdvap0NYiA0bNuDll1+Gu7s7XnvtNTg4OFj7lAgLcfToUbzxxhvIyMjArl27sGjRIgCgRdVT\nzv79+/Hmm2+ioKAAR48exZIlSwDQuNoCmzZtwoQJEwAAw4YNg1KpJOPWBqD1k21SXdZP1doIYifg\nW7duwdnZGfb29rh8+bLNWrzViczMTMTHxyMqKgqvv/46HB0dkZubq32fHr5PJ2q1GoAmnaZt27aY\nOXMmJk6ciLi4OOzZs4e3DfH0UFpaCgC4c+cOBg0ahHfffRc9evRAvXr1tNvQPfv0kpSUhPv372PJ\nkiWYOnUqzp07h+LiYigUChrXp5y0tDRaP9kYaWlpSEhIqBbrJ9UHH3zwgbVP4kmTmJiIVatWIT09\nHQ0bNoRKpULnzp3BMAzOnDmDkJAQeHp6Wvs0CRNJTEzEzz//jIyMDLRs2RJOTk5IT09HZmYmVq9e\njUOHDuHEiROIiYkhz/JTBveeDQ8PR3x8PBQKBQICAuDm5obExET8/vvvGD16NI3tU0RiYiJWrFiB\n1NRUNG7cGPfu3UP79u1RUlKCKVOmwN7eHunp6WjevDmN61NGYmIifvjhB6SmpqJDhw6Ijo6Gm5sb\nAOD27duwt7dHnTp1aFyfMm7evIkDBw6gUaNGADQOjJiYGACg9dNTDHdc3dzcoFAokJ6ejuzsbKxa\ntcpm10/VxghiGAYKhQJXrlzBRx99hM6dO+PcuXM4d+4c6tSpg9DQUISGhuLAgQNgGAaBgYFwcnJC\nWVkZlMpqHTCr0oiNa3x8PK5cuYL69evj/v372Lx5M3r37o2XXnoJv/zyC9LS0tCuXTuo1Wqbuplt\nDamxTU5Ohp+fH65du4Zjx47hzJkzCAwMxK1bt1BQUICWLVtq9yWqHuzYpKam4oMPPkBMTAwSEhJw\n5swZxMbGIjg4GJmZmfDy8kK/fv2wYsUK3LlzB1FRUXTPVnGkxvb48eMIDAyEl5cXSktL8e+//yI8\nPByBgYH0jH0K4M6nc+bMwdGjRxEUFITg4GCoVCp4eXlp109qtZrWT08JYuMaGBiIkJAQuLi4IDEx\nEVu3brXp9VO1+XWWlJQA0HinateujYEDB2LatGlITU3FwYMHkZubCxcXF3Tt2hVnz57Fw4cPAVBq\nTVVHalyvXLmCS5cuoXXr1nj77bfx3HPPoVatWvjwww+xc+dOFBUV0eRcxREb2+nTp+P8+fPIzs7G\n888/j6ioKNSoUQOjR4/GuHHjkJaWZjOTs63CjmtSUhI8PT0xaNAgzJ49G05OTjh48CCys7MRHByM\noUOHom7duvjwww+xZ88ePH78mO7ZKo7Y2M6aNQvu7u44fPgw7t+/Dzs7OwQGBmLNmjUAAJVKZc1T\nJmTAjmtKSgocHBwwaNAgbNu2DWq1Go6OjigtLYWzszOtn54yDI2rn58funbtivHjx6Nv3742u36y\n+UjQsWPH8OWXX+Ly5cvw8PBAcHAwDhw4gPr16yMwMBDnzp3DjRs34O/vj4CAANSrVw+XLl3C/v37\nsXTpUjg5OaFZs2bWvgxCgKFxDQoKQnx8PG7duoWmTZuiY8eOKCwshIODAy5evAilUokuXbpY+xII\nCeSMbUpKCiIiItC5c2eEh4fDyckJu3btgo+PD1q2bGntSyBEOH78OD799FPEx8ejRo0aaNCggTb9\nws/PD0qlEhcuXIC9vT3UajWys7Ph6emJhIQEMAyDrl27knFbRZE7to6Ojqhbty7CwsKwd+9eBAYG\nws/PjyK3VRTuuLq6uqJp06YIDw9HWFgYzpw5gwcPHqBJkyZQq9VQKpWoV68eLl++TOunKo6hcY2P\nj0d2djaaNm0KT09PNGjQwKbXT3bWPoHK5ObNm/jqq6/w5ptvIj8/Hzt37kSdOnXQvXt3zJkzBw0b\nNtQq1CQnJ6NNmzbIz8/HkSNHkJ+fj2nTpqFHjx7WvgxCgNxxLS0tRWpqKjw9PbFhwwZcu3YNKpUK\nY8eOtfYlEBLIHVsAuHLlCurUqYOVK1fixIkTsLe3x9SpU618BYQY9+/fx5dffok33ngDubm52LZt\nG/z9/RETE4N///0XYWFhiIqKwsmTJ5GRkYGysjLs3bsXWVlZKCsrw6uvvkqL5CqKKWN769YtABoP\ndMOGDREfH4+WLVvS2FZBuOOal5eHLVu24Pr163j++edRUFCA2NhY7NixA507d4avry8AoLi4GIcP\nH0ZBQQGtn6oocsc1JiYGvr6+OHfuHHbv3o1Lly7Bzs7O5tZPNhcJUqvViIuLg5eXFxITE5Gfn4/R\no0cjJCQEN27cwMGDBzFp0iS0a9cOnp6eeO211+Do6Ii1a9fi+eefx7Fjx+Dr64tFixYhLCzM2pdD\nlGPOuDo4OGDTpk0YO3YsmjdvDm9vb0ydOhUhISHWvhyCg7n37Lp16zBixAhERUXB398fkydPhr+/\nv7UvhyinrKwM33zzDRITE5GSkoKQkBAMHjwYoaGhqFWrFjZu3IimTZvi3r17UKlUCAoKQnFxMTZu\n3Ijp06ejU6dO8Pb2xuTJkxEaGmrtyyE4mDO2paWlWLduHYYOHQpnZ2eEhIRoC+qJqoGhca1ZsyZ+\n/vlndOvWDe7u7nB0dMTNmzeRnp6OFi1aIDk5GRcvXoS/vz+tn6oY5ozrvXv30KJFCzx69AidOnWC\nj4+PTa6fbCOpj8P8+fPx+eef4/z586hTpw6OHj2KixcvwtHREYCm38TatWvRoEEDuLq6AgBu3LiB\n2NhYAEDnzp0xevRoq50/IY4543rz5k107NgRDMOgVq1a6N69uzUvgZDA3Hs2JiZGm0YTHR1tzUsg\nBKSnp2PKlCnIy8uDk5MTPv74Y2zfvh0FBQVwcnJCy5Yt0bZtW8TFxSEiIgLffPMNiouLkZubi2bN\nmqGwsBDOzs60SK6CmDu2OTk5iIyMRFFREQAgICDAyldCcDE0ro6OjoiMjETz5s2xcuVKAEBQUBCe\ne+45rF+/HtHR0Th//jw6deqEUaNGWflKCC7mjuuGDRvQqVMnxMfHw9PT02bXTzYVCSooKMCmTZsQ\nERGBzMxMdOnSBQzDYN++fVi1ahXKysrQpUsXpKamIiYmBhs3bsT69euRkJCAcePGwcvLi8LyVZCK\njOtrr70GLy8va18CIYEl7lmi6nH79m3s3bsXX3zxBZo2bYobN27g9OnTyMrKQteuXbWOiXPnzmHk\nyJFIS0vDjh07cPz4cUyYMEGbXkNUPSo6tj4+Pta+BEIEOePq5eWFY8eOoXnz5sjLy8OkSZPg7++P\n+fPnIzY21maK5W2Jio5rt27drH0JlYpN1QS5uLhg+vTpKC0txbZt27B//36MHj0axcXFSEpKQpMm\nTZCQkID9+/cDAKZMmYIHDx7QA7eKQ+Nqu9DY2iaenp6YMGECysrKwDAMgoODsWLFCsycORMXLlxA\ns2bN4OrqCjs7O7i6umLy5MkoKCiAu7u7tU+dMAKNrW0iZ1xr1KgBR0dH1K5dGzk5ORg/fjz69etn\n7VMnDEDjahibigQBgLe3N3x9fXHjxg1cv34d7u7u8Pf3R1JSEnJzc/Hff/+huLgYnTp1goODA2rU\nqGHtUyZkQONqu9DY2h6urq4ICQmBUqnU5qOPGTMGrq6u2LRpE7y9vREXF4eUlBR069YNjo6O2vRH\nompDY2ubyBnX06dPIzk5GV26dEGtWrUQHh5u7dMmjEDjahibigRxiY6Oxu+//47r16+jadOmSEpK\nQnJyMrKzs/H+++/DwcHB2qdImAGNq+1CY2ubXLt2DQzDoGbNmhg9ejScnZ1x4sQJ3L9/H/PmzYOL\ni4u1T5EwExpb28TYuJIj6umExlUfBcMwjLVPorI4fPgw/vzzT1y7dg2dOnXCO++8Qx4pG4DG1Xah\nsbU9Dhw4gLt376J79+6YO3cumjdvjjfeeIPqL20AGlvbhMbVNqFx1cdmI0EAsHnzZpw/fx4TJkzA\n0KFDrX06hIWgcbVdaGxtj5ycHCxcuBD79u3DwIED0b9/f2ufEmEhaGxtExpX24TGVR+bjQTdvXsX\n//zzD0aMGEFpNDYEjavtQmNrm5w8eRKXLl2icbVBaGxtExpX24TGVR+bNYIIgiAIgiAIgiDEIFF3\ngiAIgiAIgiCqFWQEEQRBEARBEARRrSAjiCAIgiAIgiCIagUZQQRBEARBEARBVD8S3xEAAAhBSURB\nVCvICCIIgiAIgiAIolpBRhBBEARBEARBENUKMoIIgiCqIffv30ezZs2wYsUKix1z8uTJGDx4MNLT\n03mvN2rUCKNHj8bo0aMxfPhwzJs3Dzk5OUaPt2PHDpjaxWHLli34+OOPTdrHELm5uejbty8mTpwo\ne5/p06djy5YtBrc5dOgQHj58KPn+7du3MWLECOTn58v+XIIgCEI+ZAQRBEFUQ7Zu3Yp+/foZXayb\nwt69e7Fp0yb4+vrqvbdmzRqsXbsW69evR2BgIMaOHQu1Wm3weMuXLze6DZe7d+9ixYoVmDlzpsnn\nLkViYiJcXFywfPly2fsoFAooFAqD26xZs8agERQUFISBAwfis88+k/25BEEQhHzsrH0CBEEQxJPn\nzz//xLfffosZM2YgPj4erVq1AgAsWbIEJ06cgIODA3x9fbFo0SJed/GysjIsXLgQFy9ehEKhQPv2\n7TF58mTMnj0barUaY8eOxeLFi+Hv7y/6uUqlEq+//joOHDiAw4cPIyYmBnPnzkVycjLKysoQERGB\nOXPmYNmyZbhx4wbGjBmD5cuX4/Lly/jmm28AAHZ2dpg/fz6CgoJ4x165ciWGDRsGOzs7MAwjetz8\n/HxMmzYNeXl5KC0tRdeuXTFhwgRkZmZi9uzZKCgoQElJCcaNG4eOHTti/vz5uHPnDiZNmoRly5aJ\nXpNarcbs2bORmJiIwMBAFBQUaN/76quvcOzYMSiVSvj6+uKzzz7Db7/9htOnT2PGjBlYuHAhSkpK\nsHjxYpSUlKC0tBRz585F48aNMWjQIHz99deYNGkSPD09KzTeBEEQhACGIAiCqFacPHmSGTBgAMMw\nDPPjjz8yc+bMYRiGYXJycphWrVoxarWaYRiG2blzJ5OWlsbbd8eOHcz48eMZhmGYsrIyZujQocyp\nU6cYhmGY8PBwpqysTO/zxF5ftGgRs2LFCiYnJ4f55ZdftK8/++yzzLVr13j7FRQUML169WIePnzI\nMAzD7N27l3n77bf1PqdXr15MUlKS9lqEx01MTGT27NnDjBs3jmEYhlGr1cyqVasYtVrNvP/++8zK\nlSsZhmGYrKwsJjo6msnPz2dOnDjBDB8+3OD3efjwYWbYsGEMwzBMYWEhEx0dzWzZsoUpLS1lfvjh\nB6a0tJRhGIZ59dVXmQMHDjAMwzBdu3Zlbt68yTAMw/Tt21f79+XLl5lBgwZpjz1p0iRm586dBj+f\nIAiCMB2KBBEEQVQz/vjjD/Tp0wcA0KdPHwwYMABz5sxBzZo10alTJ4wcORI9evRAnz599FLbEhIS\n0LFjRwCaqE5kZCQSEhLQpk0bk84hLy8PPj4+cHNzw7179/Diiy/C3t4eGRkZePDgAW/ba9euISMj\nA2+99RYATeRFqdTP5r537x78/PwAQPS4OTk5iIyMxLJlyzBlyhTExsZi2LBhUCgUSEhIwIgRIwAA\nnp6e8PX1RUpKiqyapMTERG0kzcnJCS1atAAAqFQqKJVKjBo1CnZ2dkhJSdGrhcrKykJqaipmzZql\nfY1bBxQQEIDbt28bPQeCIAjCNMgIIgiCqEY8evQIe/bsQUBAAHbt2gVAk+L2999/Y8CAAVi2bBlS\nU1Nx8OBBjBo1Cl9//TUaNWqk3V+hUPAMA4ZhRA0SQzAMg3PnzqF///7466+/cOHCBWzYsAFKpRJD\nhgzR297BwQEBAQFYu3at7M+QOq6npye2b9+O+Ph47N+/H0OGDMGWLVv0anhMvS7u/mVlZQCAuLg4\nbN68GZs3b4aTkxMmTZokem0ODg4mXRtBEARRcUgYgSAIohrx119/ISoqCjt37sTWrVuxdetWfPTR\nR9i8eTNu3bqF1atXo27dunjllVfQo0cPXLlyhbd/ixYtcPToUQBAaWkpTp06pY18GII1nBiGwfLl\ny+Hm5oZ27dohOzsbdevWhVKpxIULF3Djxg0UFRUB0BgWJSUlqFOnDh48eIBr164BAE6dOoXffvtN\n7zP8/Pxw7949AJA87pEjR3DgwAG0bt0aM2bMgIuLC7KystCiRQscPnwYAJCeno6MjAzUrVtX1nca\nFhaGc+fOAdAYmQkJCWAYBtnZ2QgMDISTkxPu3LmDs2fPaq9NqVSiuLgYbm5uCAwMxKFDhwAAqamp\n2tonALhz545e7RNBEARRcRSMnFg/QRAEYRMMHToUEydORGxsrPa14uJidOvWDevWrcN3332HlJQU\nuLq6ombNmli0aBGcnZ212zIMg4ULF+LChQtQq9VaYQEAaNy4MS5evKgXQWnUqBHatm0LAMjJyUFE\nRATee+89bcrahAkT4OrqipYtW8LV1RU7duzAr7/+iunTp+Pu3bv49ttvcfv2bXzxxRdwdHQEAMyf\nPx916tThfc6CBQsQGBiIMWPGSB535cqVePfdd7UpdZGRkZgyZQqys7Mxa9Ys5Ofno7i4GG+++SZi\nY2Nx8uRJfPXVV1i//v/buUNUVYM4jMOvQQSbYLK6AF2DoBtxDQqCYDEJYrOJllss8m3CbBGzILiJ\nDz35wr3pHDjg9zx1YObPTPqV+fPfO329XplOp7nf7+l0OinLMsPhMKPRKOPxOO/3O91uN/1+P9vt\nNvv9PofDIefzOavVKo1GI8vlMrVaLWVZZjabpdfrpSzLDAaDFEWRVqv1rXcH4G8iCICP8Hw+Mx6P\nUxRF6vX6b4/zbcfjMbfbLYvF4rdHAfg4IgiAj3E6nXK9XjOfz39038vlkvV6/c+1zWaTdrv9o+c9\nHo9MJpPsdrs0m80f3RsAEQQAAFSMjxEAAIBKEUEAAECliCAAAKBSRBAAAFApIggAAKgUEQQAAFTK\nF8ydTTX8xfwpAAAAAElFTkSuQmCC\n",
       "text/plain": [
        "<matplotlib.figure.Figure at 0x7fe1057a5e50>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "# Convert it over to a Pandas dataframe for easy charting\n",
     "vix_df = odo(dataset, pd.DataFrame)\n",
     "\n",
     "vix_df.plot(x='asof_date', y='close')\n",
     "plt.xlabel(\"As of Date (asof_date)\")\n",
     "plt.ylabel(\"Close Price\")\n",
     "plt.axis([None, None, 0, 100])\n",
     "plt.title(\"VIX\")\n",
     "plt.legend().set_visible(False)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "<a id='pipeline'></a>\n",
     "\n",
     "#Pipeline Overview\n",
     "\n",
     "### Accessing the data in your algorithms & research\n",
     "The only method for accessing partner data within algorithms running on Quantopian is via the pipeline API. Different data sets work differently but in the case of this data, you can add this data to your pipeline as follows:\n",
     "\n",
     "Import the data set here\n",
     "> `from quantopian.pipeline.data.quandl import yahoo_index_vix`\n",
     "\n",
     "Then in intialize() you could do something simple like adding the raw value of one of the fields to your pipeline:\n",
     "> `pipe.add(yahoo_index_vix.close, 'close')`"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {
     "collapsed": true
    },
    "outputs": [],
    "source": [
     "# Import necessary Pipeline modules\n",
     "from quantopian.pipeline import Pipeline\n",
     "from quantopian.research import run_pipeline\n",
     "from quantopian.pipeline.factors import AverageDollarVolume"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "# For use in your algorithms\n",
     "# Using the full dataset in your pipeline algo\n",
     "from quantopian.pipeline.data.quandl import yahoo_index_vix"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Now that we've imported the data, let's take a look at which fields are available for each dataset.\n",
     "\n",
     "You'll find the dataset, the available fields, and the datatypes for each of those fields."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
       "Here are the list of available fields per dataset:\n",
       "---------------------------------------------------\n",
       "\n",
       "Dataset: yahoo_index_vix\n",
       "\n",
       "Fields:\n",
       "low - float64\n",
       "high - float64\n",
       "adjusted_close - float64\n",
       "volume - float64\n",
       "close - float64\n",
       "open_ - float64\n",
       "\n",
       "\n",
       "---------------------------------------------------\n",
       "\n"
      ]
     }
    ],
    "source": [
     "print \"Here are the list of available fields per dataset:\"\n",
     "print \"---------------------------------------------------\\n\"\n",
     "\n",
     "def _print_fields(dataset):\n",
     "    print \"Dataset: %s\\n\" % dataset.__name__\n",
     "    print \"Fields:\"\n",
     "    for field in list(dataset.columns):\n",
     "        print \"%s - %s\" % (field.name, field.dtype)\n",
     "    print \"\\n\"\n",
     "\n",
     "for data in (yahoo_index_vix,):\n",
     "    _print_fields(data)\n",
     "\n",
     "\n",
     "print \"---------------------------------------------------\\n\""
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Now that we know what fields we have access to, let's see what this data looks like when we run it through Pipeline.\n",
     "\n",
     "\n",
     "This is constructed the same way as you would in the backtester. For more information on using Pipeline in Research view this thread:\n",
     "https://www.quantopian.com/posts/pipeline-in-research-build-test-and-visualize-your-factors-and-filters"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "# Let's see what this data looks like when we run it through Pipeline\n",
     "# This is constructed the same way as you would in the backtester. For more information\n",
     "# on using Pipeline in Research view this thread:\n",
     "# https://www.quantopian.com/posts/pipeline-in-research-build-test-and-visualize-your-factors-and-filters\n",
     "pipe = Pipeline()\n",
     "       \n",
     "pipe.add(yahoo_index_vix.open_.latest, 'open')\n",
     "pipe.add(yahoo_index_vix.close.latest, 'close')\n",
     "pipe.add(yahoo_index_vix.adjusted_close.latest, 'adjusted_close')\n",
     "pipe.add(yahoo_index_vix.high.latest, 'high')\n",
     "pipe.add(yahoo_index_vix.low.latest, 'low')\n",
     "pipe.add(yahoo_index_vix.volume.latest, 'volume')"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
    "outputs": [
     {
      "data": {
       "image/png": 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       "text/plain": [
        "<IPython.core.display.Image object>"
       ]
      },
      "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# The show_graph() method of pipeline objects produces a graph to show how it is being calculated.\n",
     "pipe.show_graph(format='png')"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "metadata": {
     "collapsed": false,
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
       "text/html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th>adjusted_close</th>\n",
        "      <th>close</th>\n",
        "      <th>high</th>\n",
        "      <th>low</th>\n",
        "      <th>open</th>\n",
        "      <th>volume</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th rowspan=\"30\" valign=\"top\">2013-11-01 00:00:00+00:00</th>\n",
        "      <th>Equity(2 [AA])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(21 [AAME])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(24 [AAPL])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(25 [AA_PR])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(31 [ABAX])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(39 [DDC])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(41 [ARCB])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(52 [ABM])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(53 [ABMD])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(62 [ABT])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(64 [ABX])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(66 [AB])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(67 [ADSK])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(69 [ACAT])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(70 [VBF])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(76 [TAP])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(84 [ACET])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(86 [ACG])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(88 [ACI])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(99 [ACO])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(100 [IEP])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(106 [ACU])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(110 [ACXM])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(112 [ACY])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(114 [ADBE])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(117 [AEY])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(122 [ADI])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(128 [ADM])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(134 [SXCL])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(149 [ADX])</th>\n",
        "      <td>13.75</td>\n",
        "      <td>13.75</td>\n",
        "      <td>14.02</td>\n",
        "      <td>13.28</td>\n",
        "      <td>13.83</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th rowspan=\"30\" valign=\"top\">2013-11-25 00:00:00+00:00</th>\n",
        "      <th>Equity(45864 [CDX])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45865 [XNCR])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45866 [ZU])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45867 [EROS])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45873 [IR_WI])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45874 [ALLE])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45875 [HFIN])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45880 [CACQ])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45882 [TKF_WD])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45883 [IIF_WD])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45885 [EGF_WD])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45891 [OXFD])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45892 [TLOG])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45893 [VTL])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45894 [RTGN])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45895 [EMSH])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45896 [AMZG])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45902 [WBAI])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45903 [GOMO])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45904 [IPWR])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45905 [GFIS])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45906 [VNCE])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45907 [RITT_W])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45914 [EVGN])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(45915 [NVGS])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(48504 [ERUS])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(49010 [TBRA])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(49131 [OESX])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(49259 [ITUS])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Equity(49523 [TLGT])</th>\n",
        "      <td>12.26</td>\n",
        "      <td>12.26</td>\n",
        "      <td>12.91</td>\n",
        "      <td>12.24</td>\n",
        "      <td>12.69</td>\n",
        "      <td>0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>134806 rows × 6 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "                                                  adjusted_close  close  \\\n",
        "2013-11-01 00:00:00+00:00 Equity(2 [AA])                   13.75  13.75   \n",
        "                          Equity(21 [AAME])                13.75  13.75   \n",
        "                          Equity(24 [AAPL])                13.75  13.75   \n",
        "                          Equity(25 [AA_PR])               13.75  13.75   \n",
        "                          Equity(31 [ABAX])                13.75  13.75   \n",
        "                          Equity(39 [DDC])                 13.75  13.75   \n",
        "                          Equity(41 [ARCB])                13.75  13.75   \n",
        "                          Equity(52 [ABM])                 13.75  13.75   \n",
        "                          Equity(53 [ABMD])                13.75  13.75   \n",
        "                          Equity(62 [ABT])                 13.75  13.75   \n",
        "                          Equity(64 [ABX])                 13.75  13.75   \n",
        "                          Equity(66 [AB])                  13.75  13.75   \n",
        "                          Equity(67 [ADSK])                13.75  13.75   \n",
        "                          Equity(69 [ACAT])                13.75  13.75   \n",
        "                          Equity(70 [VBF])                 13.75  13.75   \n",
        "                          Equity(76 [TAP])                 13.75  13.75   \n",
        "                          Equity(84 [ACET])                13.75  13.75   \n",
        "                          Equity(86 [ACG])                 13.75  13.75   \n",
        "                          Equity(88 [ACI])                 13.75  13.75   \n",
        "                          Equity(99 [ACO])                 13.75  13.75   \n",
        "                          Equity(100 [IEP])                13.75  13.75   \n",
        "                          Equity(106 [ACU])                13.75  13.75   \n",
        "                          Equity(110 [ACXM])               13.75  13.75   \n",
        "                          Equity(112 [ACY])                13.75  13.75   \n",
        "                          Equity(114 [ADBE])               13.75  13.75   \n",
        "                          Equity(117 [AEY])                13.75  13.75   \n",
        "                          Equity(122 [ADI])                13.75  13.75   \n",
        "                          Equity(128 [ADM])                13.75  13.75   \n",
        "                          Equity(134 [SXCL])               13.75  13.75   \n",
        "                          Equity(149 [ADX])                13.75  13.75   \n",
        "...                                                          ...    ...   \n",
        "2013-11-25 00:00:00+00:00 Equity(45864 [CDX])              12.26  12.26   \n",
        "                          Equity(45865 [XNCR])             12.26  12.26   \n",
        "                          Equity(45866 [ZU])               12.26  12.26   \n",
        "                          Equity(45867 [EROS])             12.26  12.26   \n",
        "                          Equity(45873 [IR_WI])            12.26  12.26   \n",
        "                          Equity(45874 [ALLE])             12.26  12.26   \n",
        "                          Equity(45875 [HFIN])             12.26  12.26   \n",
        "                          Equity(45880 [CACQ])             12.26  12.26   \n",
        "                          Equity(45882 [TKF_WD])           12.26  12.26   \n",
        "                          Equity(45883 [IIF_WD])           12.26  12.26   \n",
        "                          Equity(45885 [EGF_WD])           12.26  12.26   \n",
        "                          Equity(45891 [OXFD])             12.26  12.26   \n",
        "                          Equity(45892 [TLOG])             12.26  12.26   \n",
        "                          Equity(45893 [VTL])              12.26  12.26   \n",
        "                          Equity(45894 [RTGN])             12.26  12.26   \n",
        "                          Equity(45895 [EMSH])             12.26  12.26   \n",
        "                          Equity(45896 [AMZG])             12.26  12.26   \n",
        "                          Equity(45902 [WBAI])             12.26  12.26   \n",
        "                          Equity(45903 [GOMO])             12.26  12.26   \n",
        "                          Equity(45904 [IPWR])             12.26  12.26   \n",
        "                          Equity(45905 [GFIS])             12.26  12.26   \n",
        "                          Equity(45906 [VNCE])             12.26  12.26   \n",
        "                          Equity(45907 [RITT_W])           12.26  12.26   \n",
        "                          Equity(45914 [EVGN])             12.26  12.26   \n",
        "                          Equity(45915 [NVGS])             12.26  12.26   \n",
        "                          Equity(48504 [ERUS])             12.26  12.26   \n",
        "                          Equity(49010 [TBRA])             12.26  12.26   \n",
        "                          Equity(49131 [OESX])             12.26  12.26   \n",
        "                          Equity(49259 [ITUS])             12.26  12.26   \n",
        "                          Equity(49523 [TLGT])             12.26  12.26   \n",
        "\n",
        "                                                   high    low   open  volume  \n",
        "2013-11-01 00:00:00+00:00 Equity(2 [AA])          14.02  13.28  13.83       0  \n",
        "                          Equity(21 [AAME])       14.02  13.28  13.83       0  \n",
        "                          Equity(24 [AAPL])       14.02  13.28  13.83       0  \n",
        "                          Equity(25 [AA_PR])      14.02  13.28  13.83       0  \n",
        "                          Equity(31 [ABAX])       14.02  13.28  13.83       0  \n",
        "                          Equity(39 [DDC])        14.02  13.28  13.83       0  \n",
        "                          Equity(41 [ARCB])       14.02  13.28  13.83       0  \n",
        "                          Equity(52 [ABM])        14.02  13.28  13.83       0  \n",
        "                          Equity(53 [ABMD])       14.02  13.28  13.83       0  \n",
        "                          Equity(62 [ABT])        14.02  13.28  13.83       0  \n",
        "                          Equity(64 [ABX])        14.02  13.28  13.83       0  \n",
        "                          Equity(66 [AB])         14.02  13.28  13.83       0  \n",
        "                          Equity(67 [ADSK])       14.02  13.28  13.83       0  \n",
        "                          Equity(69 [ACAT])       14.02  13.28  13.83       0  \n",
        "                          Equity(70 [VBF])        14.02  13.28  13.83       0  \n",
        "                          Equity(76 [TAP])        14.02  13.28  13.83       0  \n",
        "                          Equity(84 [ACET])       14.02  13.28  13.83       0  \n",
        "                          Equity(86 [ACG])        14.02  13.28  13.83       0  \n",
        "                          Equity(88 [ACI])        14.02  13.28  13.83       0  \n",
        "                          Equity(99 [ACO])        14.02  13.28  13.83       0  \n",
        "                          Equity(100 [IEP])       14.02  13.28  13.83       0  \n",
        "                          Equity(106 [ACU])       14.02  13.28  13.83       0  \n",
        "                          Equity(110 [ACXM])      14.02  13.28  13.83       0  \n",
        "                          Equity(112 [ACY])       14.02  13.28  13.83       0  \n",
        "                          Equity(114 [ADBE])      14.02  13.28  13.83       0  \n",
        "                          Equity(117 [AEY])       14.02  13.28  13.83       0  \n",
        "                          Equity(122 [ADI])       14.02  13.28  13.83       0  \n",
        "                          Equity(128 [ADM])       14.02  13.28  13.83       0  \n",
        "                          Equity(134 [SXCL])      14.02  13.28  13.83       0  \n",
        "                          Equity(149 [ADX])       14.02  13.28  13.83       0  \n",
        "...                                                 ...    ...    ...     ...  \n",
        "2013-11-25 00:00:00+00:00 Equity(45864 [CDX])     12.91  12.24  12.69       0  \n",
        "                          Equity(45865 [XNCR])    12.91  12.24  12.69       0  \n",
        "                          Equity(45866 [ZU])      12.91  12.24  12.69       0  \n",
        "                          Equity(45867 [EROS])    12.91  12.24  12.69       0  \n",
        "                          Equity(45873 [IR_WI])   12.91  12.24  12.69       0  \n",
        "                          Equity(45874 [ALLE])    12.91  12.24  12.69       0  \n",
        "                          Equity(45875 [HFIN])    12.91  12.24  12.69       0  \n",
        "                          Equity(45880 [CACQ])    12.91  12.24  12.69       0  \n",
        "                          Equity(45882 [TKF_WD])  12.91  12.24  12.69       0  \n",
        "                          Equity(45883 [IIF_WD])  12.91  12.24  12.69       0  \n",
        "                          Equity(45885 [EGF_WD])  12.91  12.24  12.69       0  \n",
        "                          Equity(45891 [OXFD])    12.91  12.24  12.69       0  \n",
        "                          Equity(45892 [TLOG])    12.91  12.24  12.69       0  \n",
        "                          Equity(45893 [VTL])     12.91  12.24  12.69       0  \n",
        "                          Equity(45894 [RTGN])    12.91  12.24  12.69       0  \n",
        "                          Equity(45895 [EMSH])    12.91  12.24  12.69       0  \n",
        "                          Equity(45896 [AMZG])    12.91  12.24  12.69       0  \n",
        "                          Equity(45902 [WBAI])    12.91  12.24  12.69       0  \n",
        "                          Equity(45903 [GOMO])    12.91  12.24  12.69       0  \n",
        "                          Equity(45904 [IPWR])    12.91  12.24  12.69       0  \n",
        "                          Equity(45905 [GFIS])    12.91  12.24  12.69       0  \n",
        "                          Equity(45906 [VNCE])    12.91  12.24  12.69       0  \n",
        "                          Equity(45907 [RITT_W])  12.91  12.24  12.69       0  \n",
        "                          Equity(45914 [EVGN])    12.91  12.24  12.69       0  \n",
        "                          Equity(45915 [NVGS])    12.91  12.24  12.69       0  \n",
        "                          Equity(48504 [ERUS])    12.91  12.24  12.69       0  \n",
        "                          Equity(49010 [TBRA])    12.91  12.24  12.69       0  \n",
        "                          Equity(49131 [OESX])    12.91  12.24  12.69       0  \n",
        "                          Equity(49259 [ITUS])    12.91  12.24  12.69       0  \n",
        "                          Equity(49523 [TLGT])    12.91  12.24  12.69       0  \n",
        "\n",
        "[134806 rows x 6 columns]"
       ]
      },
      "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# run_pipeline will show the output of your pipeline\n",
     "pipe_output = run_pipeline(pipe, start_date='2013-11-01', end_date='2013-11-25')\n",
     "pipe_output"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Taking what we've seen from above, let's see how we'd move that into the backtester."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "# This section is only importable in the backtester\n",
     "from quantopian.algorithm import attach_pipeline, pipeline_output\n",
     "\n",
     "# General pipeline imports\n",
     "from quantopian.pipeline import Pipeline\n",
     "from quantopian.pipeline.factors import AverageDollarVolume\n",
     "\n",
     "# Import the datasets available\n",
     "# For use in your algorithms\n",
     "# Using the full dataset in your pipeline algo\n",
     "from quantopian.pipeline.data.quandl import yahoo_index_vix\n",
     "\n",
     "def make_pipeline():\n",
     "    # Create our pipeline\n",
     "    pipe = Pipeline()\n",
     "\n",
     "    # Add pipeline factors\n",
     "    pipe.add(yahoo_index_vix.open_.latest, 'open')\n",
     "    pipe.add(yahoo_index_vix.close.latest, 'close')\n",
     "    pipe.add(yahoo_index_vix.adjusted_close.latest, 'adjusted_close')\n",
     "    pipe.add(yahoo_index_vix.high.latest, 'high')\n",
     "    pipe.add(yahoo_index_vix.low.latest, 'low')\n",
     "    pipe.add(yahoo_index_vix.volume.latest, 'volume')\n",
     "\n",
     "    return pipe\n",
     "\n",
     "def initialize(context):\n",
     "    attach_pipeline(make_pipeline(), \"pipeline\")\n",
     "    \n",
     "def before_trading_start(context, data):\n",
     "    results = pipeline_output('pipeline')"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
     "Now you can take that and begin to use it as a building block for your algorithms, for more examples on how to do that you can visit our <a href='https://www.quantopian.com/posts/pipeline-factor-library-for-data'>data pipeline factor library</a>"
    ]
   }
  ],
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    "display_name": "Python 2",
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    "name": "python2"
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     "name": "ipython",
     "version": 2
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    "file_extension": ".py",
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