examples/v3api.ipynb

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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Example of using the v3api directly\n",
      "This notebook gives examples of using the API directly. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from tia.bbg import LocalTerminal\n",
      "import pandas as pd"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Reference Data Requests"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Single SID, Multiple Valid Fields\n",
      "resp = LocalTerminal.get_reference_data('MSFT US EQUITY', ['PX_LAST', 'GICS_SECTOR_NAME', 'VOLATILITY_30D'])\n",
      "resp.as_frame()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>PX_LAST</th>\n",
        "      <th>GICS_SECTOR_NAME</th>\n",
        "      <th>VOLATILITY_30D</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>MSFT US EQUITY</th>\n",
        "      <td> 44.09</td>\n",
        "      <td> Information Technology</td>\n",
        "      <td> 38.422119</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "                PX_LAST        GICS_SECTOR_NAME  VOLATILITY_30D\n",
        "MSFT US EQUITY    44.09  Information Technology       38.422119"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Get the response as a dict\n",
      "resp.as_map()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "defaultdict(<type 'dict'>, {'MSFT US EQUITY': {'VOLATILITY_30D': 38.42211904056546, 'GICS_SECTOR_NAME': 'Information Technology', 'PX_LAST': 44.09}})"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Single SID, Invalid Fields\n",
      "# Ability to ignore errors\n",
      "resp = LocalTerminal.get_reference_data('MSFT US EQUITY', ['PX_LAST', 'GICS_SECTOR_NAME', 'BAD FIELD'], ignore_field_error=1)\n",
      "resp.as_frame()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>PX_LAST</th>\n",
        "      <th>GICS_SECTOR_NAME</th>\n",
        "      <th>BAD FIELD</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>MSFT US EQUITY</th>\n",
        "      <td> 44.09</td>\n",
        "      <td> Information Technology</td>\n",
        "      <td>NaN</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "                PX_LAST        GICS_SECTOR_NAME  BAD FIELD\n",
        "MSFT US EQUITY    44.09  Information Technology        NaN"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Multiple SID, Invalid Fields\n",
      "# allows for non-homogeneous security types to be batched together\n",
      "resp = LocalTerminal.get_reference_data(['ED1 COMDTY', 'MSFT US EQUITY'], ['PX_LAST', 'GICS_SECTOR_NAME'], ignore_field_error=1)\n",
      "resp.as_frame()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>PX_LAST</th>\n",
        "      <th>GICS_SECTOR_NAME</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>ED1 COMDTY</th>\n",
        "      <td> 99.7325</td>\n",
        "      <td>                    NaN</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>MSFT US EQUITY</th>\n",
        "      <td> 44.0900</td>\n",
        "      <td> Information Technology</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "                PX_LAST        GICS_SECTOR_NAME\n",
        "ED1 COMDTY      99.7325                     NaN\n",
        "MSFT US EQUITY  44.0900  Information Technology"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Retrieve data without override\n",
      "LocalTerminal.get_reference_data('SPX INDEX', 'CUST_TRR_RETURN_HOLDING_PER').as_frame()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>CUST_TRR_RETURN_HOLDING_PER</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>SPX INDEX</th>\n",
        "      <td> 17.00294</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "           CUST_TRR_RETURN_HOLDING_PER\n",
        "SPX INDEX                     17.00294"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Retrieve data with override (1 month total return)\n",
      "dt = pd.datetools.BDay(-21).apply(pd.datetime.now()).strftime('%Y%m%d')\n",
      "LocalTerminal.get_reference_data('SPX INDEX', 'CUST_TRR_RETURN_HOLDING_PER', CUST_TRR_START_DT=dt).as_frame()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>CUST_TRR_RETURN_HOLDING_PER</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>SPX INDEX</th>\n",
        "      <td> 4.471417</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "           CUST_TRR_RETURN_HOLDING_PER\n",
        "SPX INDEX                     4.471417"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "HISTORICAL DATA"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Single SID, Multiple Valid Fields\n",
      "resp = LocalTerminal.get_historical('MSFT US EQUITY', ['PX_OPEN', 'PX_LAST'], start='1/1/2014', end='3/1/2014')\n",
      "resp.as_frame().head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th colspan=\"2\" halign=\"left\">MSFT US EQUITY</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th>PX_OPEN</th>\n",
        "      <th>PX_LAST</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-01-02</th>\n",
        "      <td> 37.350</td>\n",
        "      <td> 37.16</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-03</th>\n",
        "      <td> 37.200</td>\n",
        "      <td> 36.91</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-06</th>\n",
        "      <td> 36.850</td>\n",
        "      <td> 36.13</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-07</th>\n",
        "      <td> 36.325</td>\n",
        "      <td> 36.41</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-08</th>\n",
        "      <td> 36.000</td>\n",
        "      <td> 35.76</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "            MSFT US EQUITY         \n",
        "                   PX_OPEN  PX_LAST\n",
        "date                               \n",
        "2014-01-02          37.350    37.16\n",
        "2014-01-03          37.200    36.91\n",
        "2014-01-06          36.850    36.13\n",
        "2014-01-07          36.325    36.41\n",
        "2014-01-08          36.000    35.76"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Multiple SIDs, Multiple Valid Fields\n",
      "resp = LocalTerminal.get_historical(['IBM US EQUITY', 'MSFT US EQUITY'], ['PX_OPEN', 'PX_LAST'], start='1/1/2014', end='3/1/2014')\n",
      "resp.as_frame().head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th colspan=\"2\" halign=\"left\">IBM US EQUITY</th>\n",
        "      <th colspan=\"2\" halign=\"left\">MSFT US EQUITY</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th>PX_OPEN</th>\n",
        "      <th>PX_LAST</th>\n",
        "      <th>PX_OPEN</th>\n",
        "      <th>PX_LAST</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-01-02</th>\n",
        "      <td> 187.21</td>\n",
        "      <td> 185.53</td>\n",
        "      <td> 37.350</td>\n",
        "      <td> 37.16</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-03</th>\n",
        "      <td> 185.83</td>\n",
        "      <td> 186.64</td>\n",
        "      <td> 37.200</td>\n",
        "      <td> 36.91</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-06</th>\n",
        "      <td> 187.15</td>\n",
        "      <td> 186.00</td>\n",
        "      <td> 36.850</td>\n",
        "      <td> 36.13</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-07</th>\n",
        "      <td> 186.39</td>\n",
        "      <td> 189.71</td>\n",
        "      <td> 36.325</td>\n",
        "      <td> 36.41</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-08</th>\n",
        "      <td> 189.33</td>\n",
        "      <td> 187.97</td>\n",
        "      <td> 36.000</td>\n",
        "      <td> 35.76</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "            IBM US EQUITY           MSFT US EQUITY         \n",
        "                  PX_OPEN  PX_LAST         PX_OPEN  PX_LAST\n",
        "date                                                       \n",
        "2014-01-02         187.21   185.53          37.350    37.16\n",
        "2014-01-03         185.83   186.64          37.200    36.91\n",
        "2014-01-06         187.15   186.00          36.850    36.13\n",
        "2014-01-07         186.39   189.71          36.325    36.41\n",
        "2014-01-08         189.33   187.97          36.000    35.76"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Weekly data\n",
      "resp = LocalTerminal.get_historical(['IBM US EQUITY', 'MSFT US EQUITY'], ['PX_OPEN', 'PX_LAST'], \n",
      "                                         start='1/1/2014', end='3/1/2014', period='WEEKLY')\n",
      "resp.as_frame().head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th colspan=\"2\" halign=\"left\">IBM US EQUITY</th>\n",
        "      <th colspan=\"2\" halign=\"left\">MSFT US EQUITY</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th></th>\n",
        "      <th>PX_OPEN</th>\n",
        "      <th>PX_LAST</th>\n",
        "      <th>PX_OPEN</th>\n",
        "      <th>PX_LAST</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-01-03</th>\n",
        "      <td> 185.320</td>\n",
        "      <td> 186.64</td>\n",
        "      <td> 37.22</td>\n",
        "      <td> 36.910</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-10</th>\n",
        "      <td> 187.150</td>\n",
        "      <td> 187.26</td>\n",
        "      <td> 36.85</td>\n",
        "      <td> 36.040</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-17</th>\n",
        "      <td> 186.260</td>\n",
        "      <td> 190.09</td>\n",
        "      <td> 35.99</td>\n",
        "      <td> 36.380</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-24</th>\n",
        "      <td> 190.230</td>\n",
        "      <td> 179.64</td>\n",
        "      <td> 36.82</td>\n",
        "      <td> 36.805</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-01-31</th>\n",
        "      <td> 179.605</td>\n",
        "      <td> 176.68</td>\n",
        "      <td> 36.87</td>\n",
        "      <td> 37.840</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "            IBM US EQUITY           MSFT US EQUITY         \n",
        "                  PX_OPEN  PX_LAST         PX_OPEN  PX_LAST\n",
        "date                                                       \n",
        "2014-01-03        185.320   186.64           37.22   36.910\n",
        "2014-01-10        187.150   187.26           36.85   36.040\n",
        "2014-01-17        186.260   190.09           35.99   36.380\n",
        "2014-01-24        190.230   179.64           36.82   36.805\n",
        "2014-01-31        179.605   176.68           36.87   37.840"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# format response as panel\n",
      "resp.as_panel()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "<class 'pandas.core.panel.Panel'>\n",
        "Dimensions: 2 (items) x 9 (major_axis) x 2 (minor_axis)\n",
        "Items axis: IBM US EQUITY to MSFT US EQUITY\n",
        "Major_axis axis: 2014-01-03 00:00:00 to 2014-02-28 00:00:00\n",
        "Minor_axis axis: PX_OPEN to PX_LAST"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "RETRIEVING CURVES AND MEMBERS"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Retrieve the EURUSD Forward Curve\n",
      "resp = LocalTerminal.get_reference_data('eurusd curncy', 'fwd_curve')\n",
      "# must retrieve a frame from the first row\n",
      "resp.as_frame().ix[0, 'fwd_curve'].head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>Security Description</th>\n",
        "      <th>Settlement Date</th>\n",
        "      <th>Bid</th>\n",
        "      <th>Mid</th>\n",
        "      <th>Ask</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> EURON Curncy</td>\n",
        "      <td>2015-02-26</td>\n",
        "      <td> 0.084</td>\n",
        "      <td> 0.1085</td>\n",
        "      <td> 0.133</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> EURTN Curncy</td>\n",
        "      <td>2015-02-27</td>\n",
        "      <td> 0.094</td>\n",
        "      <td> 0.1120</td>\n",
        "      <td> 0.130</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> EURSN Curncy</td>\n",
        "      <td>2015-03-02</td>\n",
        "      <td> 0.231</td>\n",
        "      <td> 0.2600</td>\n",
        "      <td> 0.289</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> EUR1W Curncy</td>\n",
        "      <td>2015-03-06</td>\n",
        "      <td> 0.680</td>\n",
        "      <td> 0.7400</td>\n",
        "      <td> 0.800</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> EUR1M Curncy</td>\n",
        "      <td>2015-03-31</td>\n",
        "      <td> 3.600</td>\n",
        "      <td> 3.7500</td>\n",
        "      <td> 3.900</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 12,
       "text": [
        "  Security Description Settlement Date    Bid     Mid    Ask\n",
        "0         EURON Curncy      2015-02-26  0.084  0.1085  0.133\n",
        "1         EURTN Curncy      2015-02-27  0.094  0.1120  0.130\n",
        "2         EURSN Curncy      2015-03-02  0.231  0.2600  0.289\n",
        "3         EUR1W Curncy      2015-03-06  0.680  0.7400  0.800\n",
        "4         EUR1M Curncy      2015-03-31  3.600  3.7500  3.900"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# OR \n",
      "resp.as_map()['eurusd curncy']['fwd_curve'].head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>Security Description</th>\n",
        "      <th>Settlement Date</th>\n",
        "      <th>Bid</th>\n",
        "      <th>Mid</th>\n",
        "      <th>Ask</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> EURON Curncy</td>\n",
        "      <td>2015-02-26</td>\n",
        "      <td> 0.084</td>\n",
        "      <td> 0.1085</td>\n",
        "      <td> 0.133</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> EURTN Curncy</td>\n",
        "      <td>2015-02-27</td>\n",
        "      <td> 0.094</td>\n",
        "      <td> 0.1120</td>\n",
        "      <td> 0.130</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> EURSN Curncy</td>\n",
        "      <td>2015-03-02</td>\n",
        "      <td> 0.231</td>\n",
        "      <td> 0.2600</td>\n",
        "      <td> 0.289</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> EUR1W Curncy</td>\n",
        "      <td>2015-03-06</td>\n",
        "      <td> 0.680</td>\n",
        "      <td> 0.7400</td>\n",
        "      <td> 0.800</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> EUR1M Curncy</td>\n",
        "      <td>2015-03-31</td>\n",
        "      <td> 3.600</td>\n",
        "      <td> 3.7500</td>\n",
        "      <td> 3.900</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "  Security Description Settlement Date    Bid     Mid    Ask\n",
        "0         EURON Curncy      2015-02-26  0.084  0.1085  0.133\n",
        "1         EURTN Curncy      2015-02-27  0.094  0.1120  0.130\n",
        "2         EURSN Curncy      2015-03-02  0.231  0.2600  0.289\n",
        "3         EUR1W Curncy      2015-03-06  0.680  0.7400  0.800\n",
        "4         EUR1M Curncy      2015-03-31  3.600  3.7500  3.900"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Retrive the EURUSD Vol Surface\n",
      "resp = LocalTerminal.get_reference_data('eurusd curncy', 'dflt_vol_surf_bid')\n",
      "resp.as_frame().ix[0, 'dflt_vol_surf_bid'].head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>Maturity Period</th>\n",
        "      <th>Maturity as Percent of Year</th>\n",
        "      <th>Delta Type</th>\n",
        "      <th>Delta</th>\n",
        "      <th>Volatility</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1D</td>\n",
        "      <td> 0.0037</td>\n",
        "      <td>      ATM</td>\n",
        "      <td> 0.50</td>\n",
        "      <td> 9.5650</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1D</td>\n",
        "      <td> 0.0037</td>\n",
        "      <td> 35D_CALL</td>\n",
        "      <td> 0.35</td>\n",
        "      <td> 9.3898</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1D</td>\n",
        "      <td> 0.0037</td>\n",
        "      <td>  35D_PUT</td>\n",
        "      <td> 0.65</td>\n",
        "      <td> 9.6700</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 1D</td>\n",
        "      <td> 0.0037</td>\n",
        "      <td> 25D_CALL</td>\n",
        "      <td> 0.25</td>\n",
        "      <td> 9.2089</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 1D</td>\n",
        "      <td> 0.0037</td>\n",
        "      <td>  25D_PUT</td>\n",
        "      <td> 0.75</td>\n",
        "      <td> 9.7224</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "  Maturity Period  Maturity as Percent of Year Delta Type  Delta  Volatility\n",
        "0              1D                       0.0037        ATM   0.50      9.5650\n",
        "1              1D                       0.0037   35D_CALL   0.35      9.3898\n",
        "2              1D                       0.0037    35D_PUT   0.65      9.6700\n",
        "3              1D                       0.0037   25D_CALL   0.25      9.2089\n",
        "4              1D                       0.0037    25D_PUT   0.75      9.7224"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# More complex example\n",
      "# Retrive all members of the S&P 500, then get price and vol data\n",
      "resp = LocalTerminal.get_reference_data('spx index', 'indx_members')\n",
      "members = resp.as_frame().ix[0, 'indx_members']\n",
      "# append region + yellow key = 'US EQUITY'\n",
      "members = members.icol(0).apply(lambda x: x.split()[0] + ' US EQUITY')\n",
      "resp = LocalTerminal.get_reference_data(members, ['PX_LAST', 'VOLATILITY_30D'])\n",
      "resp.as_frame().head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>PX_LAST</th>\n",
        "      <th>VOLATILITY_30D</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>A US EQUITY</th>\n",
        "      <td>  42.06</td>\n",
        "      <td> 26.464951</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>AA US EQUITY</th>\n",
        "      <td>  15.74</td>\n",
        "      <td> 38.774343</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>AAPL US EQUITY</th>\n",
        "      <td> 132.17</td>\n",
        "      <td> 29.148085</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ABBV US EQUITY</th>\n",
        "      <td>  60.87</td>\n",
        "      <td> 38.109767</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>ABC US EQUITY</th>\n",
        "      <td> 102.97</td>\n",
        "      <td> 12.183109</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "                PX_LAST  VOLATILITY_30D\n",
        "A US EQUITY       42.06       26.464951\n",
        "AA US EQUITY      15.74       38.774343\n",
        "AAPL US EQUITY   132.17       29.148085\n",
        "ABBV US EQUITY    60.87       38.109767\n",
        "ABC US EQUITY    102.97       12.183109"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# kind of pointless\n",
      "resp.as_frame().describe()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>PX_LAST</th>\n",
        "      <th>VOLATILITY_30D</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>count</th>\n",
        "      <td>  502.000000</td>\n",
        "      <td> 502.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
        "      <td>   86.554861</td>\n",
        "      <td>  26.793370</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
        "      <td>   92.274786</td>\n",
        "      <td>  10.935133</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
        "      <td>    7.860000</td>\n",
        "      <td>   2.057758</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
        "      <td>   43.022500</td>\n",
        "      <td>  19.967708</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
        "      <td>   67.220000</td>\n",
        "      <td>  24.565563</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
        "      <td>   97.326250</td>\n",
        "      <td>  30.091746</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
        "      <td> 1219.790000</td>\n",
        "      <td>  92.775252</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "           PX_LAST  VOLATILITY_30D\n",
        "count   502.000000      502.000000\n",
        "mean     86.554861       26.793370\n",
        "std      92.274786       10.935133\n",
        "min       7.860000        2.057758\n",
        "25%      43.022500       19.967708\n",
        "50%      67.220000       24.565563\n",
        "75%      97.326250       30.091746\n",
        "max    1219.790000       92.775252"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pxs = LocalTerminal.get_historical(members, 'PX_LAST')\n",
      "f = pxs.as_frame()\n",
      "f.columns = f.columns.get_level_values(0)\n",
      "# Show first 5 rows for last 5 days\n",
      "f.iloc[:5, -5:]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>VZ US EQUITY</th>\n",
        "      <th>UNP US EQUITY</th>\n",
        "      <th>XL US EQUITY</th>\n",
        "      <th>CBS US EQUITY</th>\n",
        "      <th>MU US EQUITY</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-02-25</th>\n",
        "      <td> 46.29</td>\n",
        "      <td> 89.350</td>\n",
        "      <td> 29.57</td>\n",
        "      <td> 65.76</td>\n",
        "      <td> 24.255</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-02-26</th>\n",
        "      <td> 46.35</td>\n",
        "      <td> 88.605</td>\n",
        "      <td> 29.82</td>\n",
        "      <td> 65.54</td>\n",
        "      <td> 24.220</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-02-27</th>\n",
        "      <td> 47.50</td>\n",
        "      <td> 89.250</td>\n",
        "      <td> 29.95</td>\n",
        "      <td> 66.40</td>\n",
        "      <td> 24.190</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-02-28</th>\n",
        "      <td> 47.58</td>\n",
        "      <td> 90.190</td>\n",
        "      <td> 30.40</td>\n",
        "      <td> 67.08</td>\n",
        "      <td> 24.190</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-03-03</th>\n",
        "      <td> 47.31</td>\n",
        "      <td> 89.755</td>\n",
        "      <td> 30.11</td>\n",
        "      <td> 65.95</td>\n",
        "      <td> 24.480</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "            VZ US EQUITY  UNP US EQUITY  XL US EQUITY  CBS US EQUITY  \\\n",
        "date                                                                   \n",
        "2014-02-25         46.29         89.350         29.57          65.76   \n",
        "2014-02-26         46.35         88.605         29.82          65.54   \n",
        "2014-02-27         47.50         89.250         29.95          66.40   \n",
        "2014-02-28         47.58         90.190         30.40          67.08   \n",
        "2014-03-03         47.31         89.755         30.11          65.95   \n",
        "\n",
        "            MU US EQUITY  \n",
        "date                      \n",
        "2014-02-25        24.255  \n",
        "2014-02-26        24.220  \n",
        "2014-02-27        24.190  \n",
        "2014-02-28        24.190  \n",
        "2014-03-03        24.480  "
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Intraday Tick Request"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import datetime\n",
      "sid = 'VOD LN EQUITY'\n",
      "events = ['TRADE', 'AT_TRADE']\n",
      "dt = pd.datetools.BDay(-1).apply(pd.datetime.now())\n",
      "start = pd.datetime.combine(dt, datetime.time(13, 30))\n",
      "end = pd.datetime.combine(dt, datetime.time(13, 35))\n",
      "f = LocalTerminal.get_intraday_tick(sid, events, start, end, include_condition_codes=True).as_frame()\n",
      "f.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>conditionCodes</th>\n",
        "      <th>size</th>\n",
        "      <th>time</th>\n",
        "      <th>type</th>\n",
        "      <th>value</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> AT</td>\n",
        "      <td>  858</td>\n",
        "      <td>2015-02-24 13:30:02</td>\n",
        "      <td> AT_TRADE</td>\n",
        "      <td> 226.85</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> AT</td>\n",
        "      <td> 2000</td>\n",
        "      <td>2015-02-24 13:30:02</td>\n",
        "      <td> AT_TRADE</td>\n",
        "      <td> 226.85</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> AT</td>\n",
        "      <td> 2566</td>\n",
        "      <td>2015-02-24 13:30:02</td>\n",
        "      <td> AT_TRADE</td>\n",
        "      <td> 226.85</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> AT</td>\n",
        "      <td> 2562</td>\n",
        "      <td>2015-02-24 13:30:08</td>\n",
        "      <td> AT_TRADE</td>\n",
        "      <td> 226.85</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> AT</td>\n",
        "      <td> 2623</td>\n",
        "      <td>2015-02-24 13:30:08</td>\n",
        "      <td> AT_TRADE</td>\n",
        "      <td> 226.85</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "  conditionCodes  size                time      type   value\n",
        "0             AT   858 2015-02-24 13:30:02  AT_TRADE  226.85\n",
        "1             AT  2000 2015-02-24 13:30:02  AT_TRADE  226.85\n",
        "2             AT  2566 2015-02-24 13:30:02  AT_TRADE  226.85\n",
        "3             AT  2562 2015-02-24 13:30:08  AT_TRADE  226.85\n",
        "4             AT  2623 2015-02-24 13:30:08  AT_TRADE  226.85"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Intraday Bar Request"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import datetime\n",
      "sid = 'IBM US EQUITY'\n",
      "event = 'TRADE'\n",
      "dt = pd.datetools.BDay(-1).apply(pd.datetime.now())\n",
      "start = pd.datetime.combine(dt, datetime.time(13, 30))\n",
      "end = pd.datetime.combine(dt, datetime.time(21, 30))\n",
      "f = LocalTerminal.get_intraday_bar(sid, event, start, end, interval=60).as_frame()\n",
      "f.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "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>close</th>\n",
        "      <th>high</th>\n",
        "      <th>low</th>\n",
        "      <th>numEvents</th>\n",
        "      <th>open</th>\n",
        "      <th>time</th>\n",
        "      <th>value</th>\n",
        "      <th>volume</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 162.2500</td>\n",
        "      <td> 162.70</td>\n",
        "      <td> 161.51</td>\n",
        "      <td> 4005</td>\n",
        "      <td> 162.4900</td>\n",
        "      <td>2015-02-24 14:30:00</td>\n",
        "      <td> 110345672</td>\n",
        "      <td> 680888</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 163.3808</td>\n",
        "      <td> 163.46</td>\n",
        "      <td> 162.00</td>\n",
        "      <td> 2921</td>\n",
        "      <td> 162.2699</td>\n",
        "      <td>2015-02-24 15:30:00</td>\n",
        "      <td>  66801220</td>\n",
        "      <td> 410523</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 163.5100</td>\n",
        "      <td> 163.74</td>\n",
        "      <td> 163.05</td>\n",
        "      <td> 2587</td>\n",
        "      <td> 163.4000</td>\n",
        "      <td>2015-02-24 16:30:00</td>\n",
        "      <td>  60114624</td>\n",
        "      <td> 367710</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 163.8700</td>\n",
        "      <td> 163.94</td>\n",
        "      <td> 163.23</td>\n",
        "      <td> 1850</td>\n",
        "      <td> 163.5200</td>\n",
        "      <td>2015-02-24 17:30:00</td>\n",
        "      <td>  47967724</td>\n",
        "      <td> 293200</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 164.3600</td>\n",
        "      <td> 164.49</td>\n",
        "      <td> 163.87</td>\n",
        "      <td> 2910</td>\n",
        "      <td> 163.8836</td>\n",
        "      <td>2015-02-24 18:30:00</td>\n",
        "      <td>  70343296</td>\n",
        "      <td> 428363</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 21,
       "text": [
        "      close    high     low  numEvents      open                time  \\\n",
        "0  162.2500  162.70  161.51       4005  162.4900 2015-02-24 14:30:00   \n",
        "1  163.3808  163.46  162.00       2921  162.2699 2015-02-24 15:30:00   \n",
        "2  163.5100  163.74  163.05       2587  163.4000 2015-02-24 16:30:00   \n",
        "3  163.8700  163.94  163.23       1850  163.5200 2015-02-24 17:30:00   \n",
        "4  164.3600  164.49  163.87       2910  163.8836 2015-02-24 18:30:00   \n",
        "\n",
        "       value  volume  \n",
        "0  110345672  680888  \n",
        "1   66801220  410523  \n",
        "2   60114624  367710  \n",
        "3   47967724  293200  \n",
        "4   70343296  428363  "
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}