_z_BQL_String.ipynb

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    "# Import the BQL library\n",
    "import bql\n",
    "\n",
    "# Instantiate an object to interface with the BQL service\n",
    "bq = bql.Service()"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "# BQL String Interface Basics\n",
    "\n",
    "You can use Bloomberg Query Language (BQL) via the PyBQL API to request Bloomberg data from within BQuant notebooks. There are two main ways to use BQL: the object model and the string interface. This notebook provides an introduction to the string interface. We'll start with a simple example and build on it to learn how to construct more complex requests.\n",
    "\n",
    "<a href = \"#A\">Example A: Requesting a Single Data Item</a>  \n",
    "<a href = \"#B\">Example B: Requesting Multiple Data Items</a>  \n",
    "<a href = \"#C\">Example C: Requesting Time Series and Point-In-Time Data</a>  \n",
    "<a href = \"#D\">Example D: Requesting Data for Multiple Securities</a>  \n",
    "<a href = \"#E\">Options Examples</a>  \n",
    "<a href = \"#F\">ETF Examples</a>  \n",
    "<a href = \"#G\">Additional (Portfolio interop, technicals)</a>  \n",
    "<a href = \"#J\">Cross Asset</a>  \n",
    "<br>"
   ]
  },
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    "## Example A: Requesting a Single Data Item <a name=\"A\"></a>\n",
    "In this example, we'll create and execute the simplest possible request: a single data item for a single security. We'll build on this request in later examples. For now, let's request the last price for AAPL US Equity. To do this, we'll define a variable for the request and pass it to the BQL execute function.\n",
    "\n",
    "- **Request syntax**:  \n",
    "        `get(data fields)for([security or universe])`\n",
    "- **BQL execute function**:  \n",
    "        `bq.execute(request)`\n",
    "\n",
    "_Note: For more information on finding data fields that can be queried with BQL, see <a href = \"#related\"> Related Resources</a> ._\n"
   ]
  },
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   "source": [
    "### Basic Last Price Request"
   ]
  },
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>PX_LAST</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL US Equity</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>303.01001</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     DATE CURRENCY    PX_LAST\n",
       "ID                                           \n",
       "AAPL US Equity 2020-05-15      USD  303.01001"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define the request string \n",
    "request = \"get(PX_LAST)for(['AAPL US Equity'])\"\n",
    "\n",
    "# Execute the request\n",
    "response = bq.execute(request)\n",
    "\n",
    "# Display the response in a DataFrame\n",
    "response[0].df()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  },
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   "source": [
    "## Example B: Requesting Multiple Data Items <a name=\"B\"></a>\n",
    "Now that we've seen how to request a single data item, let's expand the previous example to request additional data items. We'll again use AAPL US Equity, but this time we'll request the last price, high price, and low price.\n",
    "\n",
    "### Example Code"
   ]
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      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>PX_LAST</th>\n",
       "      <th>PX_HIGH</th>\n",
       "      <th>PX_LOW</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</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>AAPL US Equity</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>303.200012</td>\n",
       "      <td>306.119995</td>\n",
       "      <td>300.209991</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     DATE CURRENCY     PX_LAST     PX_HIGH      PX_LOW\n",
       "ID                                                                    \n",
       "AAPL US Equity 2020-05-15      USD  303.200012  306.119995  300.209991"
      ]
     },
     "execution_count": 4,
     "metadata": {},
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   "source": [
    "# Define the request string\n",
    "request = \"\"\"\n",
    "get(PX_LAST, PX_HIGH, PX_LOW)\n",
    "for(['AAPL US Equity'])\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response = bq.execute(request)\n",
    "\n",
    "# Display the response in a DataFrame\n",
    "# Use the combined_df function to display the three returned values in a single DataFrame \n",
    "bql.combined_df(response)\n",
    "\n",
    "# Note that you can also display a single data item from the response \n",
    "# by running response[0].df(), response[1].df(), or response[2].df(),\n"
   ]
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   "execution_count": 4,
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   "source": [
    "#Define utility BQL function to \n",
    "def query_bql(s):\n",
    "    resp = bq.execute(s)\n",
    "    df = bql.combined_df(resp)\n",
    "    return df"
   ]
  },
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   "execution_count": 5,
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   "outputs": [],
   "source": [
    "request = \"\"\"\n",
    "get(PX_LAST, PX_HIGH, PX_LOW)\n",
    "for(['F US Equity'])\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>PX_LAST</th>\n",
       "      <th>PX_HIGH</th>\n",
       "      <th>PX_LOW</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</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>F US Equity</th>\n",
       "      <td>2020-05-07</td>\n",
       "      <td>USD</td>\n",
       "      <td>4.93</td>\n",
       "      <td>4.98</td>\n",
       "      <td>4.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  DATE CURRENCY  PX_LAST  PX_HIGH  PX_LOW\n",
       "ID                                                       \n",
       "F US Equity 2020-05-07      USD     4.93     4.98    4.88"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df_response = query_bql(request)\n",
    "df_response"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  },
  {
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   "source": [
    "## Example C: Requesting Time Series and Point-In-Time Data <a name=\"C\"></a>\n",
    "In the examples above, we didn't specify a data date so BQL returned data for today's date by default. If we want to return data for a specific date or date range, we can pass start and end values as arguments to the BQL range function. Note that the dates are associated with the data fields, not the request.\n",
    "\n",
    "_Note: To request point-in-time data (for a single date), pass the same value for the start and end parameters._\n",
    "\n",
    "\n",
    "### Example Code"
   ]
  },
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>#PX_LAST</th>\n",
       "      <th>PX_HIGH(dates=#date_range)</th>\n",
       "      <th>PX_LOW(dates=#date_range)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</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>TSLA US Equity</th>\n",
       "      <td>2018-06-05</td>\n",
       "      <td>USD</td>\n",
       "      <td>291.13</td>\n",
       "      <td>297.8000</td>\n",
       "      <td>286.740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-06</td>\n",
       "      <td>USD</td>\n",
       "      <td>319.50</td>\n",
       "      <td>322.1700</td>\n",
       "      <td>297.480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-07</td>\n",
       "      <td>USD</td>\n",
       "      <td>316.09</td>\n",
       "      <td>330.0000</td>\n",
       "      <td>313.580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-08</td>\n",
       "      <td>USD</td>\n",
       "      <td>317.66</td>\n",
       "      <td>324.4800</td>\n",
       "      <td>317.150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-09</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-10</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-11</td>\n",
       "      <td>USD</td>\n",
       "      <td>332.10</td>\n",
       "      <td>334.6600</td>\n",
       "      <td>322.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-12</td>\n",
       "      <td>USD</td>\n",
       "      <td>342.77</td>\n",
       "      <td>354.9700</td>\n",
       "      <td>338.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-13</td>\n",
       "      <td>USD</td>\n",
       "      <td>344.78</td>\n",
       "      <td>347.2000</td>\n",
       "      <td>339.800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-14</td>\n",
       "      <td>USD</td>\n",
       "      <td>357.72</td>\n",
       "      <td>358.7500</td>\n",
       "      <td>346.600</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>358.17</td>\n",
       "      <td>364.6700</td>\n",
       "      <td>351.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-16</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-17</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-18</td>\n",
       "      <td>USD</td>\n",
       "      <td>370.83</td>\n",
       "      <td>373.7300</td>\n",
       "      <td>354.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>USD</td>\n",
       "      <td>352.55</td>\n",
       "      <td>370.0000</td>\n",
       "      <td>346.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-20</td>\n",
       "      <td>USD</td>\n",
       "      <td>362.22</td>\n",
       "      <td>364.3800</td>\n",
       "      <td>352.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-21</td>\n",
       "      <td>USD</td>\n",
       "      <td>347.51</td>\n",
       "      <td>366.2139</td>\n",
       "      <td>346.270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-22</td>\n",
       "      <td>USD</td>\n",
       "      <td>333.63</td>\n",
       "      <td>352.2500</td>\n",
       "      <td>332.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-24</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-25</td>\n",
       "      <td>USD</td>\n",
       "      <td>333.01</td>\n",
       "      <td>338.4700</td>\n",
       "      <td>327.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-26</td>\n",
       "      <td>USD</td>\n",
       "      <td>342.00</td>\n",
       "      <td>343.5500</td>\n",
       "      <td>325.799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-27</td>\n",
       "      <td>USD</td>\n",
       "      <td>344.50</td>\n",
       "      <td>350.7900</td>\n",
       "      <td>339.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-28</td>\n",
       "      <td>USD</td>\n",
       "      <td>349.93</td>\n",
       "      <td>357.0200</td>\n",
       "      <td>346.110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-29</td>\n",
       "      <td>USD</td>\n",
       "      <td>342.95</td>\n",
       "      <td>353.8600</td>\n",
       "      <td>342.410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-06-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-07-01</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-07-02</td>\n",
       "      <td>USD</td>\n",
       "      <td>335.07</td>\n",
       "      <td>364.7800</td>\n",
       "      <td>329.850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-07-03</td>\n",
       "      <td>USD</td>\n",
       "      <td>310.86</td>\n",
       "      <td>332.4900</td>\n",
       "      <td>309.690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TSLA US Equity</th>\n",
       "      <td>2018-07-04</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>1670.43</td>\n",
       "      <td>1676.9500</td>\n",
       "      <td>1619.680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-01-31</td>\n",
       "      <td>USD</td>\n",
       "      <td>1718.73</td>\n",
       "      <td>1736.4110</td>\n",
       "      <td>1679.082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-01</td>\n",
       "      <td>USD</td>\n",
       "      <td>1626.23</td>\n",
       "      <td>1673.0600</td>\n",
       "      <td>1622.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-02</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-03</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-04</td>\n",
       "      <td>USD</td>\n",
       "      <td>1633.31</td>\n",
       "      <td>1649.6300</td>\n",
       "      <td>1613.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-05</td>\n",
       "      <td>USD</td>\n",
       "      <td>1658.81</td>\n",
       "      <td>1665.2600</td>\n",
       "      <td>1642.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-06</td>\n",
       "      <td>USD</td>\n",
       "      <td>1640.26</td>\n",
       "      <td>1672.2600</td>\n",
       "      <td>1633.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-07</td>\n",
       "      <td>USD</td>\n",
       "      <td>1614.37</td>\n",
       "      <td>1625.5390</td>\n",
       "      <td>1592.910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-08</td>\n",
       "      <td>USD</td>\n",
       "      <td>1588.22</td>\n",
       "      <td>1588.5900</td>\n",
       "      <td>1566.756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-09</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-10</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-11</td>\n",
       "      <td>USD</td>\n",
       "      <td>1591.00</td>\n",
       "      <td>1609.2900</td>\n",
       "      <td>1586.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-12</td>\n",
       "      <td>USD</td>\n",
       "      <td>1638.01</td>\n",
       "      <td>1639.3950</td>\n",
       "      <td>1598.880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-13</td>\n",
       "      <td>USD</td>\n",
       "      <td>1640.00</td>\n",
       "      <td>1656.3800</td>\n",
       "      <td>1637.106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-14</td>\n",
       "      <td>USD</td>\n",
       "      <td>1622.65</td>\n",
       "      <td>1637.9000</td>\n",
       "      <td>1606.061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>1607.95</td>\n",
       "      <td>1628.9100</td>\n",
       "      <td>1604.500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-16</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-17</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-18</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-19</td>\n",
       "      <td>USD</td>\n",
       "      <td>1627.58</td>\n",
       "      <td>1634.0000</td>\n",
       "      <td>1600.560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-20</td>\n",
       "      <td>USD</td>\n",
       "      <td>1622.10</td>\n",
       "      <td>1634.9300</td>\n",
       "      <td>1610.120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-21</td>\n",
       "      <td>USD</td>\n",
       "      <td>1619.44</td>\n",
       "      <td>1623.5600</td>\n",
       "      <td>1600.910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-22</td>\n",
       "      <td>USD</td>\n",
       "      <td>1631.56</td>\n",
       "      <td>1634.9400</td>\n",
       "      <td>1621.170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-24</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-25</td>\n",
       "      <td>USD</td>\n",
       "      <td>1633.00</td>\n",
       "      <td>1654.6000</td>\n",
       "      <td>1630.387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-26</td>\n",
       "      <td>USD</td>\n",
       "      <td>1636.40</td>\n",
       "      <td>1639.9900</td>\n",
       "      <td>1616.134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-27</td>\n",
       "      <td>USD</td>\n",
       "      <td>1641.09</td>\n",
       "      <td>1641.8100</td>\n",
       "      <td>1615.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>2019-02-28</td>\n",
       "      <td>USD</td>\n",
       "      <td>1639.83</td>\n",
       "      <td>1651.7700</td>\n",
       "      <td>1633.830</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>538 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     DATE CURRENCY  #PX_LAST  PX_HIGH(dates=#date_range)  \\\n",
       "ID                                                                         \n",
       "TSLA US Equity 2018-06-05      USD    291.13                    297.8000   \n",
       "TSLA US Equity 2018-06-06      USD    319.50                    322.1700   \n",
       "TSLA US Equity 2018-06-07      USD    316.09                    330.0000   \n",
       "TSLA US Equity 2018-06-08      USD    317.66                    324.4800   \n",
       "TSLA US Equity 2018-06-09      USD       NaN                         NaN   \n",
       "TSLA US Equity 2018-06-10      USD       NaN                         NaN   \n",
       "TSLA US Equity 2018-06-11      USD    332.10                    334.6600   \n",
       "TSLA US Equity 2018-06-12      USD    342.77                    354.9700   \n",
       "TSLA US Equity 2018-06-13      USD    344.78                    347.2000   \n",
       "TSLA US Equity 2018-06-14      USD    357.72                    358.7500   \n",
       "TSLA US Equity 2018-06-15      USD    358.17                    364.6700   \n",
       "TSLA US Equity 2018-06-16      USD       NaN                         NaN   \n",
       "TSLA US Equity 2018-06-17      USD       NaN                         NaN   \n",
       "TSLA US Equity 2018-06-18      USD    370.83                    373.7300   \n",
       "TSLA US Equity 2018-06-19      USD    352.55                    370.0000   \n",
       "TSLA US Equity 2018-06-20      USD    362.22                    364.3800   \n",
       "TSLA US Equity 2018-06-21      USD    347.51                    366.2139   \n",
       "TSLA US Equity 2018-06-22      USD    333.63                    352.2500   \n",
       "TSLA US Equity 2018-06-23      USD       NaN                         NaN   \n",
       "TSLA US Equity 2018-06-24      USD       NaN                         NaN   \n",
       "TSLA US Equity 2018-06-25      USD    333.01                    338.4700   \n",
       "TSLA US Equity 2018-06-26      USD    342.00                    343.5500   \n",
       "TSLA US Equity 2018-06-27      USD    344.50                    350.7900   \n",
       "TSLA US Equity 2018-06-28      USD    349.93                    357.0200   \n",
       "TSLA US Equity 2018-06-29      USD    342.95                    353.8600   \n",
       "TSLA US Equity 2018-06-30      USD       NaN                         NaN   \n",
       "TSLA US Equity 2018-07-01      USD       NaN                         NaN   \n",
       "TSLA US Equity 2018-07-02      USD    335.07                    364.7800   \n",
       "TSLA US Equity 2018-07-03      USD    310.86                    332.4900   \n",
       "TSLA US Equity 2018-07-04      USD       NaN                         NaN   \n",
       "...                   ...      ...       ...                         ...   \n",
       "AMZN US Equity 2019-01-30      USD   1670.43                   1676.9500   \n",
       "AMZN US Equity 2019-01-31      USD   1718.73                   1736.4110   \n",
       "AMZN US Equity 2019-02-01      USD   1626.23                   1673.0600   \n",
       "AMZN US Equity 2019-02-02      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-03      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-04      USD   1633.31                   1649.6300   \n",
       "AMZN US Equity 2019-02-05      USD   1658.81                   1665.2600   \n",
       "AMZN US Equity 2019-02-06      USD   1640.26                   1672.2600   \n",
       "AMZN US Equity 2019-02-07      USD   1614.37                   1625.5390   \n",
       "AMZN US Equity 2019-02-08      USD   1588.22                   1588.5900   \n",
       "AMZN US Equity 2019-02-09      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-10      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-11      USD   1591.00                   1609.2900   \n",
       "AMZN US Equity 2019-02-12      USD   1638.01                   1639.3950   \n",
       "AMZN US Equity 2019-02-13      USD   1640.00                   1656.3800   \n",
       "AMZN US Equity 2019-02-14      USD   1622.65                   1637.9000   \n",
       "AMZN US Equity 2019-02-15      USD   1607.95                   1628.9100   \n",
       "AMZN US Equity 2019-02-16      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-17      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-18      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-19      USD   1627.58                   1634.0000   \n",
       "AMZN US Equity 2019-02-20      USD   1622.10                   1634.9300   \n",
       "AMZN US Equity 2019-02-21      USD   1619.44                   1623.5600   \n",
       "AMZN US Equity 2019-02-22      USD   1631.56                   1634.9400   \n",
       "AMZN US Equity 2019-02-23      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-24      USD       NaN                         NaN   \n",
       "AMZN US Equity 2019-02-25      USD   1633.00                   1654.6000   \n",
       "AMZN US Equity 2019-02-26      USD   1636.40                   1639.9900   \n",
       "AMZN US Equity 2019-02-27      USD   1641.09                   1641.8100   \n",
       "AMZN US Equity 2019-02-28      USD   1639.83                   1651.7700   \n",
       "\n",
       "                PX_LOW(dates=#date_range)  \n",
       "ID                                         \n",
       "TSLA US Equity                    286.740  \n",
       "TSLA US Equity                    297.480  \n",
       "TSLA US Equity                    313.580  \n",
       "TSLA US Equity                    317.150  \n",
       "TSLA US Equity                        NaN  \n",
       "TSLA US Equity                        NaN  \n",
       "TSLA US Equity                    322.500  \n",
       "TSLA US Equity                    338.000  \n",
       "TSLA US Equity                    339.800  \n",
       "TSLA US Equity                    346.600  \n",
       "TSLA US Equity                    351.250  \n",
       "TSLA US Equity                        NaN  \n",
       "TSLA US Equity                        NaN  \n",
       "TSLA US Equity                    354.500  \n",
       "TSLA US Equity                    346.250  \n",
       "TSLA US Equity                    352.000  \n",
       "TSLA US Equity                    346.270  \n",
       "TSLA US Equity                    332.000  \n",
       "TSLA US Equity                        NaN  \n",
       "TSLA US Equity                        NaN  \n",
       "TSLA US Equity                    327.500  \n",
       "TSLA US Equity                    325.799  \n",
       "TSLA US Equity                    339.500  \n",
       "TSLA US Equity                    346.110  \n",
       "TSLA US Equity                    342.410  \n",
       "TSLA US Equity                        NaN  \n",
       "TSLA US Equity                        NaN  \n",
       "TSLA US Equity                    329.850  \n",
       "TSLA US Equity                    309.690  \n",
       "TSLA US Equity                        NaN  \n",
       "...                                   ...  \n",
       "AMZN US Equity                   1619.680  \n",
       "AMZN US Equity                   1679.082  \n",
       "AMZN US Equity                   1622.010  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                   1613.500  \n",
       "AMZN US Equity                   1642.500  \n",
       "AMZN US Equity                   1633.340  \n",
       "AMZN US Equity                   1592.910  \n",
       "AMZN US Equity                   1566.756  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                   1586.000  \n",
       "AMZN US Equity                   1598.880  \n",
       "AMZN US Equity                   1637.106  \n",
       "AMZN US Equity                   1606.061  \n",
       "AMZN US Equity                   1604.500  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                   1600.560  \n",
       "AMZN US Equity                   1610.120  \n",
       "AMZN US Equity                   1600.910  \n",
       "AMZN US Equity                   1621.170  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                        NaN  \n",
       "AMZN US Equity                   1630.387  \n",
       "AMZN US Equity                   1616.134  \n",
       "AMZN US Equity                   1615.100  \n",
       "AMZN US Equity                   1633.830  \n",
       "\n",
       "[538 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define the request string, specifying the date range for each field\n",
    "# Since we're using the same range for all of the fields, we can use\n",
    "# a BQL let clause to define a local variable \n",
    "request = \"\"\"\n",
    "let(\n",
    "    #date_range = RANGE(2018-06-05, 2019-02-28);\n",
    "    )\n",
    "get(\n",
    "    PX_LAST(dates=#date_range) as #PX_LAST,\n",
    "    PX_HIGH(dates=#date_range), \n",
    "    PX_LOW(dates=#date_range)\n",
    "    )\n",
    "for(\n",
    "    ['TSLA US Equity', 'AMZN US Equity']\n",
    "    )\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response = bq.execute(request)\n",
    "\n",
    "# Display the response in a DataFrame\n",
    "# Use the combined_df function to display \n",
    "# the three returned values in a single DataFrame \n",
    "df =bql.combined_df(response)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(538, 5)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>#PX_LAST</th>\n",
       "      <th>PX_HIGH(dates=#date_range)</th>\n",
       "      <th>PX_LOW(dates=#date_range)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TSLA US Equity</td>\n",
       "      <td>2018-06-05</td>\n",
       "      <td>USD</td>\n",
       "      <td>291.13</td>\n",
       "      <td>297.80</td>\n",
       "      <td>286.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TSLA US Equity</td>\n",
       "      <td>2018-06-06</td>\n",
       "      <td>USD</td>\n",
       "      <td>319.50</td>\n",
       "      <td>322.17</td>\n",
       "      <td>297.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>TSLA US Equity</td>\n",
       "      <td>2018-06-07</td>\n",
       "      <td>USD</td>\n",
       "      <td>316.09</td>\n",
       "      <td>330.00</td>\n",
       "      <td>313.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>TSLA US Equity</td>\n",
       "      <td>2018-06-08</td>\n",
       "      <td>USD</td>\n",
       "      <td>317.66</td>\n",
       "      <td>324.48</td>\n",
       "      <td>317.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>TSLA US Equity</td>\n",
       "      <td>2018-06-09</td>\n",
       "      <td>USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               ID       DATE CURRENCY  #PX_LAST  PX_HIGH(dates=#date_range)  \\\n",
       "0  TSLA US Equity 2018-06-05      USD    291.13                      297.80   \n",
       "1  TSLA US Equity 2018-06-06      USD    319.50                      322.17   \n",
       "2  TSLA US Equity 2018-06-07      USD    316.09                      330.00   \n",
       "3  TSLA US Equity 2018-06-08      USD    317.66                      324.48   \n",
       "4  TSLA US Equity 2018-06-09      USD       NaN                         NaN   \n",
       "\n",
       "   PX_LOW(dates=#date_range)  \n",
       "0                     286.74  \n",
       "1                     297.48  \n",
       "2                     313.58  \n",
       "3                     317.15  \n",
       "4                        NaN  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = df.reset_index()\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>ID</th>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <th>TSLA US Equity</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>2019-02-19</th>\n",
       "      <td>1627.58</td>\n",
       "      <td>305.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-20</th>\n",
       "      <td>1622.10</td>\n",
       "      <td>302.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-21</th>\n",
       "      <td>1619.44</td>\n",
       "      <td>291.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-22</th>\n",
       "      <td>1631.56</td>\n",
       "      <td>294.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-23</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-24</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-25</th>\n",
       "      <td>1633.00</td>\n",
       "      <td>298.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-26</th>\n",
       "      <td>1636.40</td>\n",
       "      <td>297.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-27</th>\n",
       "      <td>1641.09</td>\n",
       "      <td>314.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-28</th>\n",
       "      <td>1639.83</td>\n",
       "      <td>319.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "ID          AMZN US Equity  TSLA US Equity\n",
       "DATE                                      \n",
       "2019-02-19         1627.58          305.64\n",
       "2019-02-20         1622.10          302.56\n",
       "2019-02-21         1619.44          291.23\n",
       "2019-02-22         1631.56          294.71\n",
       "2019-02-23             NaN             NaN\n",
       "2019-02-24             NaN             NaN\n",
       "2019-02-25         1633.00          298.77\n",
       "2019-02-26         1636.40          297.86\n",
       "2019-02-27         1641.09          314.74\n",
       "2019-02-28         1639.83          319.88"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df3 = df2.pivot(index='DATE', columns='ID',values = '#PX_LAST')\n",
    "df3.tail(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>ID</th>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <th>TSLA US Equity</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>2019-02-14</th>\n",
       "      <td>1622.65</td>\n",
       "      <td>303.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-15</th>\n",
       "      <td>1607.95</td>\n",
       "      <td>307.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-19</th>\n",
       "      <td>1627.58</td>\n",
       "      <td>305.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-20</th>\n",
       "      <td>1622.10</td>\n",
       "      <td>302.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-21</th>\n",
       "      <td>1619.44</td>\n",
       "      <td>291.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-22</th>\n",
       "      <td>1631.56</td>\n",
       "      <td>294.71</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-25</th>\n",
       "      <td>1633.00</td>\n",
       "      <td>298.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-26</th>\n",
       "      <td>1636.40</td>\n",
       "      <td>297.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-27</th>\n",
       "      <td>1641.09</td>\n",
       "      <td>314.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-02-28</th>\n",
       "      <td>1639.83</td>\n",
       "      <td>319.88</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "ID          AMZN US Equity  TSLA US Equity\n",
       "DATE                                      \n",
       "2019-02-14         1622.65          303.77\n",
       "2019-02-15         1607.95          307.88\n",
       "2019-02-19         1627.58          305.64\n",
       "2019-02-20         1622.10          302.56\n",
       "2019-02-21         1619.44          291.23\n",
       "2019-02-22         1631.56          294.71\n",
       "2019-02-25         1633.00          298.77\n",
       "2019-02-26         1636.40          297.86\n",
       "2019-02-27         1641.09          314.74\n",
       "2019-02-28         1639.83          319.88"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chartdf = df3.dropna()\n",
    "chartdf.tail(n=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25c72ff0518>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x25c72f5a278>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "chartdf.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a6e1babf1fc145eab8618eabc40d86d4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "GridBox(children=(Figure(animation_duration=500, axes=[Axis(color='white', grid_color='#3c3c3c', grid_lines='d…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import bqviz as bqv\n",
    "\n",
    "bqv.LinePlot(chartdf).set_style().show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Example D: Requesting Data for Multiple Securities <a name=\"D\"></a>\n",
    "Now that we know how to pull multiple data items across a range of dates for a single security, let's look at how we can request data for multiple securities by passing a list as part of the request string.\n",
    "\n",
    "### Example Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ORIG_IDS</th>\n",
       "      <th>#ID</th>\n",
       "      <th>#PCT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Unum Group:  UNM US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Unum Group:  UNM US Equity</td>\n",
       "      <td>0.026364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KLA Corp:  KLAC US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>KLA Corp:  KLAC US Equity</td>\n",
       "      <td>0.057574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNH Industrial NV:  CNHI US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>CNH Industrial NV:  CNHI US Equity</td>\n",
       "      <td>0.018525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sands China Ltd:  1928 HK Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Sands China Ltd:  1928 HK Equity</td>\n",
       "      <td>0.093946</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Highwoods Realty LP:  10180Z US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Highwoods Realty LP:  10180Z US Equity</td>\n",
       "      <td>0.028311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Union Pacific Corp:  UNP US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Union Pacific Corp:  UNP US Equity</td>\n",
       "      <td>0.455966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mondelez International Inc:  MDLZ US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Mondelez International Inc:  MDLZ US Equity</td>\n",
       "      <td>0.073488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MidAmerican Energy Co:  2454Q US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>MidAmerican Energy Co:  2454Q US Equity</td>\n",
       "      <td>0.133314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NIKE Inc:  NKE US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>NIKE Inc:  NKE US Equity</td>\n",
       "      <td>0.170246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DuPont de Nemours Inc:  DD US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>DuPont de Nemours Inc:  DD US Equity</td>\n",
       "      <td>0.232735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CNA Financial Corp:  CNA US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>CNA Financial Corp:  CNA US Equity</td>\n",
       "      <td>0.042488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trinity Health Corp:  27822Z US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Trinity Health Corp:  27822Z US Equity</td>\n",
       "      <td>0.014476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hess Corp:  HES US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Hess Corp:  HES US Equity</td>\n",
       "      <td>0.085758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Western Union Co/The:  WU US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Western Union Co/The:  WU US Equity</td>\n",
       "      <td>0.031299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oncor Electric Delivery Co LLC:  91021Z US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Oncor Electric Delivery Co LLC:  91021Z US Equity</td>\n",
       "      <td>0.172087</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  ORIG_IDS  \\\n",
       "ID                                                           \n",
       "Unum Group:  UNM US Equity                            None   \n",
       "KLA Corp:  KLAC US Equity                             None   \n",
       "CNH Industrial NV:  CNHI US Equity                    None   \n",
       "Sands China Ltd:  1928 HK Equity                      None   \n",
       "Highwoods Realty LP:  10180Z US Equity                None   \n",
       "Union Pacific Corp:  UNP US Equity                    None   \n",
       "Mondelez International Inc:  MDLZ US Equity           None   \n",
       "MidAmerican Energy Co:  2454Q US Equity               None   \n",
       "NIKE Inc:  NKE US Equity                              None   \n",
       "DuPont de Nemours Inc:  DD US Equity                  None   \n",
       "CNA Financial Corp:  CNA US Equity                    None   \n",
       "Trinity Health Corp:  27822Z US Equity                None   \n",
       "Hess Corp:  HES US Equity                             None   \n",
       "Western Union Co/The:  WU US Equity                   None   \n",
       "Oncor Electric Delivery Co LLC:  91021Z US Equity     None   \n",
       "\n",
       "                                                                                                 #ID  \\\n",
       "ID                                                                                                     \n",
       "Unum Group:  UNM US Equity                                                Unum Group:  UNM US Equity   \n",
       "KLA Corp:  KLAC US Equity                                                  KLA Corp:  KLAC US Equity   \n",
       "CNH Industrial NV:  CNHI US Equity                                CNH Industrial NV:  CNHI US Equity   \n",
       "Sands China Ltd:  1928 HK Equity                                    Sands China Ltd:  1928 HK Equity   \n",
       "Highwoods Realty LP:  10180Z US Equity                        Highwoods Realty LP:  10180Z US Equity   \n",
       "Union Pacific Corp:  UNP US Equity                                Union Pacific Corp:  UNP US Equity   \n",
       "Mondelez International Inc:  MDLZ US Equity              Mondelez International Inc:  MDLZ US Equity   \n",
       "MidAmerican Energy Co:  2454Q US Equity                      MidAmerican Energy Co:  2454Q US Equity   \n",
       "NIKE Inc:  NKE US Equity                                                    NIKE Inc:  NKE US Equity   \n",
       "DuPont de Nemours Inc:  DD US Equity                            DuPont de Nemours Inc:  DD US Equity   \n",
       "CNA Financial Corp:  CNA US Equity                                CNA Financial Corp:  CNA US Equity   \n",
       "Trinity Health Corp:  27822Z US Equity                        Trinity Health Corp:  27822Z US Equity   \n",
       "Hess Corp:  HES US Equity                                                  Hess Corp:  HES US Equity   \n",
       "Western Union Co/The:  WU US Equity                              Western Union Co/The:  WU US Equity   \n",
       "Oncor Electric Delivery Co LLC:  91021Z US Equity  Oncor Electric Delivery Co LLC:  91021Z US Equity   \n",
       "\n",
       "                                                       #PCT  \n",
       "ID                                                           \n",
       "Unum Group:  UNM US Equity                         0.026364  \n",
       "KLA Corp:  KLAC US Equity                          0.057574  \n",
       "CNH Industrial NV:  CNHI US Equity                 0.018525  \n",
       "Sands China Ltd:  1928 HK Equity                   0.093946  \n",
       "Highwoods Realty LP:  10180Z US Equity             0.028311  \n",
       "Union Pacific Corp:  UNP US Equity                 0.455966  \n",
       "Mondelez International Inc:  MDLZ US Equity        0.073488  \n",
       "MidAmerican Energy Co:  2454Q US Equity            0.133314  \n",
       "NIKE Inc:  NKE US Equity                           0.170246  \n",
       "DuPont de Nemours Inc:  DD US Equity               0.232735  \n",
       "CNA Financial Corp:  CNA US Equity                 0.042488  \n",
       "Trinity Health Corp:  27822Z US Equity             0.014476  \n",
       "Hess Corp:  HES US Equity                          0.085758  \n",
       "Western Union Co/The:  WU US Equity                0.031299  \n",
       "Oncor Electric Delivery Co LLC:  91021Z US Equity  0.172087  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define the request string, specifying the date range for each field\n",
    "# Since we're using the same range for all of the fields, we can use\n",
    "# a BQL let clause to define a local variable \n",
    "request = \"\"\"\n",
    "let(\n",
    "#NAME=VALUE(NAME,translatesymbols(members('LUACTRUU index'),instrumentidtype='Corp',targetIDtype='fundamentalticker'),mapby=lineage).value;\n",
    "\n",
    "#TICKER=VALUE(FUNDAMENTAL_TICKER,translatesymbols(members('LUACTRUU index'),instrumentidtype='Corp',targetIDtype='fundamentalticker'),mapby=lineage).value;\n",
    "\n",
    "#ID=CONCAT(CONCAT(#NAME,':  '), #TICKER);\n",
    "#wgt=ID().Weights;) \n",
    "\n",
    "get(groupsort(SUM(GROUP(#wgt,#ID))) as #PCT) \n",
    "\n",
    "for(Members('LUACTRUU Index')) \n",
    "\n",
    "with(fill=prev)\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response = bq.execute(request)\n",
    "\n",
    "# Display the response in a DataFrame\n",
    "# Use the combined_df function to display \n",
    "# the three returned values in a single DataFrame\n",
    "# To verify the output, use tail(3) to show the last three rows of the response\n",
    "bql.combined_df(response).sample(n=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Single Stock Option Open Interest Analysis <a name=\"E\"></a>\n",
    "#### Expiries with highest Open Interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>EXPIRE_DT</th>\n",
       "      <th>#OPEN_INTEREST</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-05-15T00-00-00Z</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>383349.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-22T00-00-00Z</th>\n",
       "      <td>2020-05-22</td>\n",
       "      <td>71517.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-29T00-00-00Z</th>\n",
       "      <td>2020-05-29</td>\n",
       "      <td>33884.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-05T00-00-00Z</th>\n",
       "      <td>2020-06-05</td>\n",
       "      <td>12035.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-12T00-00-00Z</th>\n",
       "      <td>2020-06-12</td>\n",
       "      <td>4245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-19T00-00-00Z</th>\n",
       "      <td>2020-06-19</td>\n",
       "      <td>401451.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-26T00-00-00Z</th>\n",
       "      <td>2020-06-26</td>\n",
       "      <td>856.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-17T00-00-00Z</th>\n",
       "      <td>2020-07-17</td>\n",
       "      <td>91505.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-21T00-00-00Z</th>\n",
       "      <td>2020-08-21</td>\n",
       "      <td>65118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-18T00-00-00Z</th>\n",
       "      <td>2020-09-18</td>\n",
       "      <td>94622.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-16T00-00-00Z</th>\n",
       "      <td>2020-10-16</td>\n",
       "      <td>37245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-20T00-00-00Z</th>\n",
       "      <td>2020-11-20</td>\n",
       "      <td>6015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-18T00-00-00Z</th>\n",
       "      <td>2020-12-18</td>\n",
       "      <td>26006.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-15T00-00-00Z</th>\n",
       "      <td>2021-01-15</td>\n",
       "      <td>442288.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-03-19T00-00-00Z</th>\n",
       "      <td>2021-03-19</td>\n",
       "      <td>41588.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-06-18T00-00-00Z</th>\n",
       "      <td>2021-06-18</td>\n",
       "      <td>70710.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-09-17T00-00-00Z</th>\n",
       "      <td>2021-09-17</td>\n",
       "      <td>10739.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-01-21T00-00-00Z</th>\n",
       "      <td>2022-01-21</td>\n",
       "      <td>114045.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-18T00-00-00Z</th>\n",
       "      <td>2022-03-18</td>\n",
       "      <td>4566.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-17T00-00-00Z</th>\n",
       "      <td>2022-06-17</td>\n",
       "      <td>90866.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      EXPIRE_DT  #OPEN_INTEREST\n",
       "ID                                             \n",
       "2020-05-15T00-00-00Z 2020-05-15        383349.0\n",
       "2020-05-22T00-00-00Z 2020-05-22         71517.0\n",
       "2020-05-29T00-00-00Z 2020-05-29         33884.0\n",
       "2020-06-05T00-00-00Z 2020-06-05         12035.0\n",
       "2020-06-12T00-00-00Z 2020-06-12          4245.0\n",
       "2020-06-19T00-00-00Z 2020-06-19        401451.0\n",
       "2020-06-26T00-00-00Z 2020-06-26           856.0\n",
       "2020-07-17T00-00-00Z 2020-07-17         91505.0\n",
       "2020-08-21T00-00-00Z 2020-08-21         65118.0\n",
       "2020-09-18T00-00-00Z 2020-09-18         94622.0\n",
       "2020-10-16T00-00-00Z 2020-10-16         37245.0\n",
       "2020-11-20T00-00-00Z 2020-11-20          6015.0\n",
       "2020-12-18T00-00-00Z 2020-12-18         26006.0\n",
       "2021-01-15T00-00-00Z 2021-01-15        442288.0\n",
       "2021-03-19T00-00-00Z 2021-03-19         41588.0\n",
       "2021-06-18T00-00-00Z 2021-06-18         70710.0\n",
       "2021-09-17T00-00-00Z 2021-09-17         10739.0\n",
       "2022-01-21T00-00-00Z 2022-01-21        114045.0\n",
       "2022-03-18T00-00-00Z 2022-03-18          4566.0\n",
       "2022-06-17T00-00-00Z 2022-06-17         90866.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Define the request string, specifying the date range for each field\n",
    "# Since we're using the same range for all of the fields, we can use\n",
    "# a BQL let clause to define a local variable \n",
    "request2 = \"\"\"\n",
    "get(\n",
    "      sum(group(znav(\n",
    "            OPEN_INT().value), \n",
    "            EXPIRE_DT)\n",
    "        ) as #OPEN_INTEREST\n",
    "    )\n",
    "for(\n",
    "    options(['TSLA US EQUITY'])\n",
    "    )\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response2 = bq.execute(request2)\n",
    "\n",
    "# Display the response in a DataFrame\n",
    "# Use the combined_df function to display \n",
    "# the three returned values in a single DataFrame\n",
    "# To verify the output, use tail(3) to show the last three rows of the response\n",
    "#bql.combined_df(response2).tail(3)\n",
    "newdf = bql.combined_df(response2)\n",
    "newdf = newdf.drop(['ORIG_IDS'], axis=1)\n",
    "newdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Volatility Smile\n",
    "#### Implied Volatility Curve filtered by Open Interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "BQL ERROR: No symbols met filter criteria in FILTER(options(['MSFT US Equity']),PUT_CALL==IF(PCT_MONEYNESS<100,PUT,CALL) AND YEAR(EXPIRE_DT)==2020 AND MONTH(EXPIRE_DT)==3 AND IVOL>0)., request_id=97879f49bc394c1887f9bfe88360a6d4 payload_id=None\n"
     ]
    },
    {
     "ename": "ResponseError",
     "evalue": "No symbols met filter criteria in FILTER(options(['MSFT US Equity']),PUT_CALL==IF(PCT_MONEYNESS<100,PUT,CALL) AND YEAR(EXPIRE_DT)==2020 AND MONTH(EXPIRE_DT)==3 AND IVOL>0).",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mResponseError\u001b[0m                             Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-24-8543569b3f48>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m \u001b[0;31m# Execute the request\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0mresponse3\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bqutil\\timing_utils.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    114\u001b[0m                               \u001b[0mpublish\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpublish\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m                               **decorator_kwargs):\n\u001b[0;32m--> 116\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    117\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\service.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, request, callback, error_callback)\u001b[0m\n\u001b[1;32m    241\u001b[0m             \u001b[0;31m# library-internal stack frames when they get an error from the\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    242\u001b[0m             \u001b[0;31m# BQL backend.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 243\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mex\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    244\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    245\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mtrace_it\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_logger\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\service.py\u001b[0m in \u001b[0;36mexecute\u001b[0;34m(self, request, callback, error_callback)\u001b[0m\n\u001b[1;32m    235\u001b[0m                     \u001b[0mrequest\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    236\u001b[0m                     \u001b[0mcallback\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 237\u001b[0;31m                     error_callback)\n\u001b[0m\u001b[1;32m    238\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mResponseError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mex\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    239\u001b[0m             \u001b[0;31m# Deliberately re-raise the exception here with a truncated stack\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\request_executor.py\u001b[0m in \u001b[0;36mexecute_string\u001b[0;34m(self, request_string, callback, error_callback)\u001b[0m\n\u001b[1;32m    238\u001b[0m                                      \u001b[0mitem_names\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    239\u001b[0m                                      \u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcallback\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 240\u001b[0;31m                                      error_callback=error_callback)\n\u001b[0m\u001b[1;32m    241\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    242\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msubmit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpreferences\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merror_callback\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\request_executor.py\u001b[0m in \u001b[0;36m__execute_string\u001b[0;34m(self, request_string, item_names, callback, error_callback)\u001b[0m\n\u001b[1;32m    460\u001b[0m                                                \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_execute_async_impl\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    461\u001b[0m                                                \u001b[0mcallback\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 462\u001b[0;31m                                                error_callback)\n\u001b[0m\u001b[1;32m    463\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    464\u001b[0m     def __submit_string(self,\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\request_executor.py\u001b[0m in \u001b[0;36m__route_request\u001b[0;34m(action, request, execution_context, sync_function, async_function, callback, error_callback)\u001b[0m\n\u001b[1;32m    526\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpromise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    527\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 528\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msender\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msync_send\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msync_function\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    529\u001b[0m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    530\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\request_executor.py\u001b[0m in \u001b[0;36msync_send\u001b[0;34m(self, function)\u001b[0m\n\u001b[1;32m    131\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mex\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    132\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__log_failure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 133\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mex\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    134\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    135\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__log_success\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\request_executor.py\u001b[0m in \u001b[0;36msync_send\u001b[0;34m(self, function)\u001b[0m\n\u001b[1;32m    128\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0msync_send\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfunction\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    129\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 130\u001b[0;31m             \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunction\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__request\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__execution_context\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    131\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mex\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    132\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__log_failure\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mex\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\request_executor.py\u001b[0m in \u001b[0;36m_execute_impl\u001b[0;34m(self, request, execution_context)\u001b[0m\n\u001b[1;32m    307\u001b[0m         json_fragments = [self._demarshal_response('execute', r)\n\u001b[1;32m    308\u001b[0m                           for r in partial_responses]\n\u001b[0;32m--> 309\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mResponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_execute_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson_fragments\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecution_context\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    310\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    311\u001b[0m     def _execute_async_impl(self,\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\response.py\u001b[0m in \u001b[0;36mfrom_execute_response\u001b[0;34m(cls, json_fragments, execution_context, raw)\u001b[0m\n\u001b[1;32m     65\u001b[0m             \u001b[0mResponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_SUPPORTED_BQLSVC_SCHEMA_MAJOR_VERSION\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     66\u001b[0m             \u001b[0mexecution_context\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 67\u001b[0;31m             \u001b[0mraw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     68\u001b[0m         )\n\u001b[1;32m     69\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\response.py\u001b[0m in \u001b[0;36m__from_response\u001b[0;34m(cls, json_fragments, expected_major_version, execution_context, raw)\u001b[0m\n\u001b[1;32m     88\u001b[0m         \u001b[0mjson_response\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m''\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson_fragments\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     89\u001b[0m         \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mjson\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloads\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjson_response\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 90\u001b[0;31m         \u001b[0m_check_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexpected_major_version\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     91\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;34m'ordering'\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     92\u001b[0m             \u001b[0;31m# There is ordering information in the response.  First walk\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\response_util.py\u001b[0m in \u001b[0;36m_check_response\u001b[0;34m(response, expected_major_version)\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_check_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexpected_major_version\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m     \u001b[0m__check_exceptions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m     \u001b[0m__check_version\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexpected_major_version\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\blp\\BQuant\\environments\\bqnt-1.281.1\\lib\\site-packages\\bql\\request\\response_util.py\u001b[0m in \u001b[0;36m__check_exceptions\u001b[0;34m(response)\u001b[0m\n\u001b[1;32m     28\u001b[0m     \u001b[0mresponse_exceptions\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'responseExceptions'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     29\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mresponse_exceptions\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 30\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mResponseError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse_exceptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     31\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mResponseError\u001b[0m: No symbols met filter criteria in FILTER(options(['MSFT US Equity']),PUT_CALL==IF(PCT_MONEYNESS<100,PUT,CALL) AND YEAR(EXPIRE_DT)==2020 AND MONTH(EXPIRE_DT)==3 AND IVOL>0)."
     ]
    }
   ],
   "source": [
    "# Define the request string, specifying the date range for each field\n",
    "request = \"\"\"\n",
    "get(groupsort(STRIKE_PX, order=ASC), OPEN_INT, IVOL) \n",
    "for(\n",
    "    filter(\n",
    "           options(['MSFT US Equity']), \n",
    "           PUT_CALL==IF(PCT_MONEYNESS<100,PUT,CALL)   AND \n",
    "           OPEN_INT > 10 AND \n",
    "           YEAR(EXPIRE_DT) ==2020 AND \n",
    "           MONTH(EXPIRE_DT)== 3 AND IVOL>0\n",
    "         ) \n",
    "    )\n",
    "\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response3 = bq.execute(request)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "# Display the response in a DataFrame\n",
    "# Use the combined_df function to display \n",
    "newdf = bql.combined_df(response3)\n",
    "newdf.sample(n=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Vega Weighting\n",
    "#### Average Vega weighted by Open Interest for monthly options on a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Define the request string, specifying the date range for each field\n",
    "request = \"\"\"\n",
    "get(\n",
    "    wavg(\n",
    "               group(znav(VEGA),UNDL_TICKER),  \n",
    "               group(OPEN_INT,UNDL_TICKER) \n",
    "    ) as #AVGVEGA_OI\n",
    ")  \n",
    "for(\n",
    "    filter(\n",
    "        options(\n",
    "            ['TSLA US EQUITY','CRM US EQUITY','IBM US EQUITY',\n",
    "            'GOOG US EQUITY', 'MSFT US EQUITY', 'ESL US EQUITY']\n",
    "            ), \n",
    "        EXPIRATION_PERIODICITY==Monthly\n",
    "        )\n",
    "    )\t\t\t\t\t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response4 = bq.execute(request)\n",
    "\n",
    "# Display the response in a DataFrame\n",
    "newdf = bql.combined_df(response4)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "newdf = newdf.drop([\"DATE\",\"EXERCISE_TYPE\", 'EXPIRE_DT', 'PUT_CALL', \"ORIG_IDS\", 'STRIKE_PX'], axis=1)\n",
    "newdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## ETF Fund Flows<a name=\"F\"></a>\n",
    "#### Fixed Income Fund Flows bucketed by Fund Objective"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "# Define the request string, specifying the date range for each field\n",
    "request = \"\"\"\n",
    "let(\n",
    "    #FLOW_30D = SUM(\n",
    "        FUND_FLOW(Dates=range(-1m,0d),\n",
    "        CURRENCY=USD,FILL=PREV)\n",
    "        );\n",
    ") \n",
    "get(\n",
    "    sum(group(#FLOW_30D, FUND_OBJECTIVE_LONG))  as #30D_FLOW\n",
    ") \n",
    "for(\n",
    "    Filter(Fundsuniv(['ALL','Primary']),FUND_TYP=='ETF' AND \n",
    "                FUND_GEO_FOCUS=='U.S.' AND \n",
    "                FUND_ASSET_CLASS_FOCUS=='Fixed Income' AND \n",
    "                SUM(FUND_FLOW(Dates=range(-1m,0d),CURRENCY=USD,FILL=PREV)) > 0)\n",
    ")\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response5 = bq.execute(request)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>FUND_OBJECTIVE_LONG</th>\n",
       "      <th>#30D_FLOW</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Aggregate Bond</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Aggregate Bond</td>\n",
       "      <td>8.774168e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Corporate</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Corporate</td>\n",
       "      <td>1.869025e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Government</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Government</td>\n",
       "      <td>1.112391e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Inflation Protected</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Inflation Protected</td>\n",
       "      <td>1.606794e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mortgage-Backed</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Mortgage-Backed</td>\n",
       "      <td>6.210221e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Muni National Intermediate</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Muni National Intermediate</td>\n",
       "      <td>3.673470e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Muni National Long</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Muni National Long</td>\n",
       "      <td>4.503543e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Municipals</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Municipals</td>\n",
       "      <td>1.876030e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NullGroup</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>2.799171e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Preferred</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>Preferred</td>\n",
       "      <td>3.107125e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>US</th>\n",
       "      <td>2020-05-15</td>\n",
       "      <td>USD</td>\n",
       "      <td>US</td>\n",
       "      <td>3.877709e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 DATE CURRENCY         FUND_OBJECTIVE_LONG  \\\n",
       "ID                                                                           \n",
       "Aggregate Bond             2020-05-15      USD              Aggregate Bond   \n",
       "Corporate                  2020-05-15      USD                   Corporate   \n",
       "Government                 2020-05-15      USD                  Government   \n",
       "Inflation Protected        2020-05-15      USD         Inflation Protected   \n",
       "Mortgage-Backed            2020-05-15      USD             Mortgage-Backed   \n",
       "Muni National Intermediate 2020-05-15      USD  Muni National Intermediate   \n",
       "Muni National Long         2020-05-15      USD          Muni National Long   \n",
       "Municipals                 2020-05-15      USD                  Municipals   \n",
       "NullGroup                  2020-05-15      USD                        None   \n",
       "Preferred                  2020-05-15      USD                   Preferred   \n",
       "US                         2020-05-15      USD                          US   \n",
       "\n",
       "                               #30D_FLOW  \n",
       "ID                                        \n",
       "Aggregate Bond              8.774168e+09  \n",
       "Corporate                   1.869025e+10  \n",
       "Government                  1.112391e+10  \n",
       "Inflation Protected         1.606794e+09  \n",
       "Mortgage-Backed             6.210221e+08  \n",
       "Muni National Intermediate  3.673470e+06  \n",
       "Muni National Long          4.503543e+07  \n",
       "Municipals                  1.876030e+09  \n",
       "NullGroup                   2.799171e+08  \n",
       "Preferred                   3.107125e+08  \n",
       "US                          3.877709e+07  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the response in a DataFrame\n",
    "newdf = bql.combined_df(response5)\n",
    "newdf = newdf.drop([\"ORIG_IDS\"], axis=1)\n",
    "newdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## ETF Performance\n",
    "#### Big moves recently"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "# Define the request string, specifying the date range for each field\n",
    "request = \"\"\"\n",
    "let(\n",
    "    #PctChg3day=pct_chg(dropna(px_last(start=-3d)));\n",
    "    #parent = parent_comp_name;\n",
    "    #name = long_comp_name;\n",
    ") \n",
    "get(#name, #parent, #PctChg3day) \n",
    "for(\n",
    "    filter(\n",
    "           fundsuniv(['PRIMARY','ACTIVE']),\n",
    "           fund_asset_class_focus == 'Equity' AND \n",
    "            #PctChg3day > 10\n",
    "     )\n",
    ") \n",
    "with(mode='cached')\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response6 = bq.execute(request)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "jupyter": {
     "source_hidden": true
    }
   },
   "source": [
    "# Display the response in a DataFrame\n",
    "newdf2 = bql.combined_df(response6)\n",
    "#newdf = newdf.drop([\"CURRENCY\"], axis=1)\n",
    "#-----\n",
    "\n",
    "#response6[0].df().sample(5)\n",
    "response6[2].df().sample(5)\n",
    "\n",
    "\n",
    "#import pandas as pd \n",
    "\n",
    "#newdf2 = pd.concat([x.df() for x in response], axis=1)\n",
    "#newdf2.sample(10)\n",
    "\n",
    "#newdf4 = pd.DataFrame({r.name:r.df()[r.name] for r in response})\n",
    "#newdf4\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "source": [
    "import pandas as pd\n",
    "\n",
    "temp0 = response6[0].df()\n",
    "temp1 = response6[1].df()\n",
    "\n",
    "temp2_ = response6[2].df()\n",
    "temp2 = temp2_.filter(like='day')\n",
    "\n",
    "\n",
    "#temp0_.head()\n",
    "newdf = pd.concat([temp0, temp1, temp2], axis=1, join = 'inner')\n",
    "newdf.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#PctChg3day</th>\n",
       "      <th>#name</th>\n",
       "      <th>#parent</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BEARH153 FH Equity</th>\n",
       "      <td>12.499995</td>\n",
       "      <td>BEAR OMXH15 X3 H</td>\n",
       "      <td>Handelsbanken Capital Markets</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HGU CN Equity</th>\n",
       "      <td>14.648364</td>\n",
       "      <td>BetaPro Canadian Gold Miners 2x Daily Bull ETF</td>\n",
       "      <td>Horizons ETFs Management Canad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XABEAR2 SS Equity</th>\n",
       "      <td>10.419026</td>\n",
       "      <td>XACT Bear 2</td>\n",
       "      <td>Xact Kapitalforvaltning AB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DRV US Equity</th>\n",
       "      <td>11.840566</td>\n",
       "      <td>Direxion Daily Real Estate Bear 3x Shares</td>\n",
       "      <td>Direxion ETFs/USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAF LN Equity</th>\n",
       "      <td>15.094340</td>\n",
       "      <td>British &amp; American Investment Trust PLC/Fund</td>\n",
       "      <td>British &amp; American Investment</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DODXF US Equity</th>\n",
       "      <td>15.340909</td>\n",
       "      <td>ELEMENTS Dogs of the Dow Linked to the DJ High...</td>\n",
       "      <td>ELEMENTS ETNs/Deutsche Bank AG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NUGT US Equity</th>\n",
       "      <td>15.401464</td>\n",
       "      <td>Direxion Daily Gold Miners Index Bull 2X Shares</td>\n",
       "      <td>Direxion ETFs/USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FNR CN Equity</th>\n",
       "      <td>16.666667</td>\n",
       "      <td>49 North Resources Inc</td>\n",
       "      <td>Union Securities Ltd/Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SILJ US Equity</th>\n",
       "      <td>12.327308</td>\n",
       "      <td>ETFMG Prime Junior Silver Miners ETF</td>\n",
       "      <td>ETF Managers Trust</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3DES LN Equity</th>\n",
       "      <td>10.632329</td>\n",
       "      <td>WisdomTree DAX 30 3x Daily Short</td>\n",
       "      <td>WisdomTree Multi Asset Issuer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3EUS LN Equity</th>\n",
       "      <td>12.985113</td>\n",
       "      <td>WisdomTree EURO STOXX 50 3x Daily Short</td>\n",
       "      <td>WisdomTree Multi Asset Issuer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>QQQS LN Equity</th>\n",
       "      <td>10.695880</td>\n",
       "      <td>WisdomTree NASDAQ 100 3x Daily Short</td>\n",
       "      <td>WisdomTree Multi Asset Issuer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JNUG US Equity</th>\n",
       "      <td>15.962693</td>\n",
       "      <td>Direxion Daily Junior Gold Miners Index Bull 2...</td>\n",
       "      <td>Direxion ETFs/USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3ITS IM Equity</th>\n",
       "      <td>12.265944</td>\n",
       "      <td>WisdomTree FTSE MIB 3x Daily Short</td>\n",
       "      <td>WisdomTree Multi Asset Issuer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PSMOLIN SV Equity</th>\n",
       "      <td>11.075988</td>\n",
       "      <td>PS Modra Linija</td>\n",
       "      <td>Primorski Sklad/Fund Parent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CEYTOUR SL Equity</th>\n",
       "      <td>10.762332</td>\n",
       "      <td>Ceylon Tourism Fund</td>\n",
       "      <td>Ceylon Asset Management/Sri Lanka</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEMMID MK Equity</th>\n",
       "      <td>11.304348</td>\n",
       "      <td>MyETF MSCI Malaysia Islamic Dividend</td>\n",
       "      <td>i-VCAP Management Sdn Bhd/Mala</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BEAROBOS NO Equity</th>\n",
       "      <td>18.622451</td>\n",
       "      <td>DNB - ETN Oil Service Bear</td>\n",
       "      <td>DNB ETNs/Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BULLELHA NO Equity</th>\n",
       "      <td>13.333335</td>\n",
       "      <td>BULL EL HA</td>\n",
       "      <td>Handelsbanken Fondforvaltning</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MIB3S IM Equity</th>\n",
       "      <td>11.820418</td>\n",
       "      <td>SG ETC FTSE MIB -3X Daily Short Collateralized</td>\n",
       "      <td>SG Issuer SA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SX5E3S IM Equity</th>\n",
       "      <td>12.486509</td>\n",
       "      <td>SG ETC EURO STOXX 50 -3x Daily Short Collatera...</td>\n",
       "      <td>SG Issuer SA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3BAS IM Equity</th>\n",
       "      <td>16.238214</td>\n",
       "      <td>WisdomTree EURO STOXX Banks 3x Daily Short</td>\n",
       "      <td>WisdomTree Multi Asset Issuer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DRIP US Equity</th>\n",
       "      <td>10.666669</td>\n",
       "      <td>Direxion Daily S&amp;P Oil &amp; Gas Exp. &amp; Prod. Bear...</td>\n",
       "      <td>Direxion ETFs/USA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3EMS IM Equity</th>\n",
       "      <td>10.580719</td>\n",
       "      <td>WisdomTree Emerging Markets 3x Daily Short</td>\n",
       "      <td>WisdomTree Multi Asset Issuer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BEAROBX5 NO Equity</th>\n",
       "      <td>12.746483</td>\n",
       "      <td>DNB - BEAR OBX X5 DNM</td>\n",
       "      <td>DNB ETNs/Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BEARAKBP NO Equity</th>\n",
       "      <td>15.748034</td>\n",
       "      <td>DNB - ETN BEAR AKERBP</td>\n",
       "      <td>DNB ETNs/Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG77 LN Equity</th>\n",
       "      <td>19.362364</td>\n",
       "      <td>SG DAX x5 DAILY SHORT</td>\n",
       "      <td>Societe Generale ETNs/Luxembou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG89 LN Equity</th>\n",
       "      <td>19.261092</td>\n",
       "      <td>SG S&amp;P x5 DAILY SHORT</td>\n",
       "      <td>Societe Generale ETNs/Luxembou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG91 LN Equity</th>\n",
       "      <td>10.298315</td>\n",
       "      <td>SG S&amp;P x3 DAILY SHORT</td>\n",
       "      <td>Societe Generale ETNs/Luxembou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SG87 LN Equity</th>\n",
       "      <td>16.612900</td>\n",
       "      <td>SG FTSE x5 DAILY SHORT</td>\n",
       "      <td>Societe Generale ETNs/Luxembou</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KSMF27 IT Equity</th>\n",
       "      <td>12.500000</td>\n",
       "      <td>KSM ETF 6A Short Leveraged TA-35 x2 Monthly</td>\n",
       "      <td>KSM Mutual Funds Ltd/Israel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KSMF116 IT Equity</th>\n",
       "      <td>12.020330</td>\n",
       "      <td>KSM ETF 6D Short Leveraged DAX 30 x2 Monthly</td>\n",
       "      <td>KSM Mutual Funds Ltd/Israel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PSGF161 IT Equity</th>\n",
       "      <td>14.970159</td>\n",
       "      <td>Psagot ETF 6A Short TA-90</td>\n",
       "      <td>Psagot Index Funds Ltd/Israel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLANPES BZ Equity</th>\n",
       "      <td>12.855434</td>\n",
       "      <td>Pesaro FIA</td>\n",
       "      <td>Planner Corretora de Valores SA/Fund Parent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SBA LN Equity</th>\n",
       "      <td>12.851096</td>\n",
       "      <td>GraniteShares 3x Short BAE Systems Daily ETP</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SBP LN Equity</th>\n",
       "      <td>17.408997</td>\n",
       "      <td>GraniteShares 3x Short BP Daily ETP</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3LRI LN Equity</th>\n",
       "      <td>16.349271</td>\n",
       "      <td>GraniteShares 3x Long Rio Tinto Daily ETP</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SRR LN Equity</th>\n",
       "      <td>33.667484</td>\n",
       "      <td>GraniteShares 3x Short Rolls-Royce Daily ETP</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SGL LN Equity</th>\n",
       "      <td>10.620327</td>\n",
       "      <td>GraniteShares 3x Short Glencore Daily ETP</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SDO LN Equity</th>\n",
       "      <td>14.480586</td>\n",
       "      <td>GraniteShares 3x Short Diageo Daily ETP</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SRD LN Equity</th>\n",
       "      <td>14.451292</td>\n",
       "      <td>GraniteShares 3x Short Royal Dutch Shell Daily...</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SLL LN Equity</th>\n",
       "      <td>17.456120</td>\n",
       "      <td>GraniteShares 3x Short Lloyds Banking Group Da...</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3SBC LN Equity</th>\n",
       "      <td>13.687696</td>\n",
       "      <td>GraniteShares 3x Short Barclays Daily ETP</td>\n",
       "      <td>Graniteshares Financial PLC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BEARTOM3 NO Equity</th>\n",
       "      <td>10.384615</td>\n",
       "      <td>DNB - ETN Tomra Bear</td>\n",
       "      <td>DNB ETNs/Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BEARAKE3 NO Equity</th>\n",
       "      <td>20.185923</td>\n",
       "      <td>DNB - ETN Aker X3 Bear</td>\n",
       "      <td>DNB ETNs/Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VITRXAC BZ Equity</th>\n",
       "      <td>13.202384</td>\n",
       "      <td>Vitreo Exponencial FIA IE</td>\n",
       "      <td>Pollux Capital Administracao de Recursos Ltda/...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRENMAS BZ Equity</th>\n",
       "      <td>12.052033</td>\n",
       "      <td>Trend Xp Inc Master FIA IE</td>\n",
       "      <td>Vista Investimentos Imobiliarios Ltda/Fund Parent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VICINQU BZ Equity</th>\n",
       "      <td>11.986309</td>\n",
       "      <td>Trend Xp Inc FIC FIA IE</td>\n",
       "      <td>Vista Investimentos Imobiliarios Ltda/Fund Parent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TRENDXP BZ Equity</th>\n",
       "      <td>11.931348</td>\n",
       "      <td>Trend Xp Inc Dominus FIC FIA IE</td>\n",
       "      <td>Vista Investimentos Imobiliarios Ltda/Fund Parent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89311204 JP Equity</th>\n",
       "      <td>11.591655</td>\n",
       "      <td>SBI Domestic REIT Double Bear</td>\n",
       "      <td>SBI Asset Management Co Ltd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FUEVFVND VN Equity</th>\n",
       "      <td>17.142857</td>\n",
       "      <td>VFMVN Diamond ETF</td>\n",
       "      <td>VietFund Management Ltd/Vietna</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    #PctChg3day  \\\n",
       "ID                                \n",
       "BEARH153 FH Equity    12.499995   \n",
       "HGU CN Equity         14.648364   \n",
       "XABEAR2 SS Equity     10.419026   \n",
       "DRV US Equity         11.840566   \n",
       "BAF LN Equity         15.094340   \n",
       "DODXF US Equity       15.340909   \n",
       "NUGT US Equity        15.401464   \n",
       "FNR CN Equity         16.666667   \n",
       "SILJ US Equity        12.327308   \n",
       "3DES LN Equity        10.632329   \n",
       "3EUS LN Equity        12.985113   \n",
       "QQQS LN Equity        10.695880   \n",
       "JNUG US Equity        15.962693   \n",
       "3ITS IM Equity        12.265944   \n",
       "PSMOLIN SV Equity     11.075988   \n",
       "CEYTOUR SL Equity     10.762332   \n",
       "MEMMID MK Equity      11.304348   \n",
       "BEAROBOS NO Equity    18.622451   \n",
       "BULLELHA NO Equity    13.333335   \n",
       "MIB3S IM Equity       11.820418   \n",
       "SX5E3S IM Equity      12.486509   \n",
       "3BAS IM Equity        16.238214   \n",
       "DRIP US Equity        10.666669   \n",
       "3EMS IM Equity        10.580719   \n",
       "BEAROBX5 NO Equity    12.746483   \n",
       "BEARAKBP NO Equity    15.748034   \n",
       "SG77 LN Equity        19.362364   \n",
       "SG89 LN Equity        19.261092   \n",
       "SG91 LN Equity        10.298315   \n",
       "SG87 LN Equity        16.612900   \n",
       "KSMF27 IT Equity      12.500000   \n",
       "KSMF116 IT Equity     12.020330   \n",
       "PSGF161 IT Equity     14.970159   \n",
       "PLANPES BZ Equity     12.855434   \n",
       "3SBA LN Equity        12.851096   \n",
       "3SBP LN Equity        17.408997   \n",
       "3LRI LN Equity        16.349271   \n",
       "3SRR LN Equity        33.667484   \n",
       "3SGL LN Equity        10.620327   \n",
       "3SDO LN Equity        14.480586   \n",
       "3SRD LN Equity        14.451292   \n",
       "3SLL LN Equity        17.456120   \n",
       "3SBC LN Equity        13.687696   \n",
       "BEARTOM3 NO Equity    10.384615   \n",
       "BEARAKE3 NO Equity    20.185923   \n",
       "VITRXAC BZ Equity     13.202384   \n",
       "TRENMAS BZ Equity     12.052033   \n",
       "VICINQU BZ Equity     11.986309   \n",
       "TRENDXP BZ Equity     11.931348   \n",
       "89311204 JP Equity    11.591655   \n",
       "FUEVFVND VN Equity    17.142857   \n",
       "\n",
       "                                                                #name  \\\n",
       "ID                                                                      \n",
       "BEARH153 FH Equity                                   BEAR OMXH15 X3 H   \n",
       "HGU CN Equity          BetaPro Canadian Gold Miners 2x Daily Bull ETF   \n",
       "XABEAR2 SS Equity                                         XACT Bear 2   \n",
       "DRV US Equity               Direxion Daily Real Estate Bear 3x Shares   \n",
       "BAF LN Equity            British & American Investment Trust PLC/Fund   \n",
       "DODXF US Equity     ELEMENTS Dogs of the Dow Linked to the DJ High...   \n",
       "NUGT US Equity        Direxion Daily Gold Miners Index Bull 2X Shares   \n",
       "FNR CN Equity                                  49 North Resources Inc   \n",
       "SILJ US Equity                   ETFMG Prime Junior Silver Miners ETF   \n",
       "3DES LN Equity                       WisdomTree DAX 30 3x Daily Short   \n",
       "3EUS LN Equity                WisdomTree EURO STOXX 50 3x Daily Short   \n",
       "QQQS LN Equity                   WisdomTree NASDAQ 100 3x Daily Short   \n",
       "JNUG US Equity      Direxion Daily Junior Gold Miners Index Bull 2...   \n",
       "3ITS IM Equity                     WisdomTree FTSE MIB 3x Daily Short   \n",
       "PSMOLIN SV Equity                                     PS Modra Linija   \n",
       "CEYTOUR SL Equity                                 Ceylon Tourism Fund   \n",
       "MEMMID MK Equity                 MyETF MSCI Malaysia Islamic Dividend   \n",
       "BEAROBOS NO Equity                         DNB - ETN Oil Service Bear   \n",
       "BULLELHA NO Equity                                         BULL EL HA   \n",
       "MIB3S IM Equity        SG ETC FTSE MIB -3X Daily Short Collateralized   \n",
       "SX5E3S IM Equity    SG ETC EURO STOXX 50 -3x Daily Short Collatera...   \n",
       "3BAS IM Equity             WisdomTree EURO STOXX Banks 3x Daily Short   \n",
       "DRIP US Equity      Direxion Daily S&P Oil & Gas Exp. & Prod. Bear...   \n",
       "3EMS IM Equity             WisdomTree Emerging Markets 3x Daily Short   \n",
       "BEAROBX5 NO Equity                              DNB - BEAR OBX X5 DNM   \n",
       "BEARAKBP NO Equity                              DNB - ETN BEAR AKERBP   \n",
       "SG77 LN Equity                                  SG DAX x5 DAILY SHORT   \n",
       "SG89 LN Equity                                  SG S&P x5 DAILY SHORT   \n",
       "SG91 LN Equity                                  SG S&P x3 DAILY SHORT   \n",
       "SG87 LN Equity                                 SG FTSE x5 DAILY SHORT   \n",
       "KSMF27 IT Equity          KSM ETF 6A Short Leveraged TA-35 x2 Monthly   \n",
       "KSMF116 IT Equity        KSM ETF 6D Short Leveraged DAX 30 x2 Monthly   \n",
       "PSGF161 IT Equity                           Psagot ETF 6A Short TA-90   \n",
       "PLANPES BZ Equity                                          Pesaro FIA   \n",
       "3SBA LN Equity           GraniteShares 3x Short BAE Systems Daily ETP   \n",
       "3SBP LN Equity                    GraniteShares 3x Short BP Daily ETP   \n",
       "3LRI LN Equity              GraniteShares 3x Long Rio Tinto Daily ETP   \n",
       "3SRR LN Equity           GraniteShares 3x Short Rolls-Royce Daily ETP   \n",
       "3SGL LN Equity              GraniteShares 3x Short Glencore Daily ETP   \n",
       "3SDO LN Equity                GraniteShares 3x Short Diageo Daily ETP   \n",
       "3SRD LN Equity      GraniteShares 3x Short Royal Dutch Shell Daily...   \n",
       "3SLL LN Equity      GraniteShares 3x Short Lloyds Banking Group Da...   \n",
       "3SBC LN Equity              GraniteShares 3x Short Barclays Daily ETP   \n",
       "BEARTOM3 NO Equity                               DNB - ETN Tomra Bear   \n",
       "BEARAKE3 NO Equity                             DNB - ETN Aker X3 Bear   \n",
       "VITRXAC BZ Equity                           Vitreo Exponencial FIA IE   \n",
       "TRENMAS BZ Equity                          Trend Xp Inc Master FIA IE   \n",
       "VICINQU BZ Equity                             Trend Xp Inc FIC FIA IE   \n",
       "TRENDXP BZ Equity                     Trend Xp Inc Dominus FIC FIA IE   \n",
       "89311204 JP Equity                      SBI Domestic REIT Double Bear   \n",
       "FUEVFVND VN Equity                                  VFMVN Diamond ETF   \n",
       "\n",
       "                                                              #parent  \n",
       "ID                                                                     \n",
       "BEARH153 FH Equity                      Handelsbanken Capital Markets  \n",
       "HGU CN Equity                          Horizons ETFs Management Canad  \n",
       "XABEAR2 SS Equity                          Xact Kapitalforvaltning AB  \n",
       "DRV US Equity                                       Direxion ETFs/USA  \n",
       "BAF LN Equity                           British & American Investment  \n",
       "DODXF US Equity                        ELEMENTS ETNs/Deutsche Bank AG  \n",
       "NUGT US Equity                                      Direxion ETFs/USA  \n",
       "FNR CN Equity                             Union Securities Ltd/Canada  \n",
       "SILJ US Equity                                     ETF Managers Trust  \n",
       "3DES LN Equity                          WisdomTree Multi Asset Issuer  \n",
       "3EUS LN Equity                          WisdomTree Multi Asset Issuer  \n",
       "QQQS LN Equity                          WisdomTree Multi Asset Issuer  \n",
       "JNUG US Equity                                      Direxion ETFs/USA  \n",
       "3ITS IM Equity                          WisdomTree Multi Asset Issuer  \n",
       "PSMOLIN SV Equity                         Primorski Sklad/Fund Parent  \n",
       "CEYTOUR SL Equity                   Ceylon Asset Management/Sri Lanka  \n",
       "MEMMID MK Equity                       i-VCAP Management Sdn Bhd/Mala  \n",
       "BEAROBOS NO Equity                                    DNB ETNs/Norway  \n",
       "BULLELHA NO Equity                      Handelsbanken Fondforvaltning  \n",
       "MIB3S IM Equity                                          SG Issuer SA  \n",
       "SX5E3S IM Equity                                         SG Issuer SA  \n",
       "3BAS IM Equity                          WisdomTree Multi Asset Issuer  \n",
       "DRIP US Equity                                      Direxion ETFs/USA  \n",
       "3EMS IM Equity                          WisdomTree Multi Asset Issuer  \n",
       "BEAROBX5 NO Equity                                    DNB ETNs/Norway  \n",
       "BEARAKBP NO Equity                                    DNB ETNs/Norway  \n",
       "SG77 LN Equity                         Societe Generale ETNs/Luxembou  \n",
       "SG89 LN Equity                         Societe Generale ETNs/Luxembou  \n",
       "SG91 LN Equity                         Societe Generale ETNs/Luxembou  \n",
       "SG87 LN Equity                         Societe Generale ETNs/Luxembou  \n",
       "KSMF27 IT Equity                          KSM Mutual Funds Ltd/Israel  \n",
       "KSMF116 IT Equity                         KSM Mutual Funds Ltd/Israel  \n",
       "PSGF161 IT Equity                       Psagot Index Funds Ltd/Israel  \n",
       "PLANPES BZ Equity         Planner Corretora de Valores SA/Fund Parent  \n",
       "3SBA LN Equity                            Graniteshares Financial PLC  \n",
       "3SBP LN Equity                            Graniteshares Financial PLC  \n",
       "3LRI LN Equity                            Graniteshares Financial PLC  \n",
       "3SRR LN Equity                            Graniteshares Financial PLC  \n",
       "3SGL LN Equity                            Graniteshares Financial PLC  \n",
       "3SDO LN Equity                            Graniteshares Financial PLC  \n",
       "3SRD LN Equity                            Graniteshares Financial PLC  \n",
       "3SLL LN Equity                            Graniteshares Financial PLC  \n",
       "3SBC LN Equity                            Graniteshares Financial PLC  \n",
       "BEARTOM3 NO Equity                                    DNB ETNs/Norway  \n",
       "BEARAKE3 NO Equity                                    DNB ETNs/Norway  \n",
       "VITRXAC BZ Equity   Pollux Capital Administracao de Recursos Ltda/...  \n",
       "TRENMAS BZ Equity   Vista Investimentos Imobiliarios Ltda/Fund Parent  \n",
       "VICINQU BZ Equity   Vista Investimentos Imobiliarios Ltda/Fund Parent  \n",
       "TRENDXP BZ Equity   Vista Investimentos Imobiliarios Ltda/Fund Parent  \n",
       "89311204 JP Equity                        SBI Asset Management Co Ltd  \n",
       "FUEVFVND VN Equity                     VietFund Management Ltd/Vietna  "
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdf4 = pd.DataFrame({r.name:r.df()[r.name] for r in response6})\n",
    "newdf4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ORIG_IDS</th>\n",
       "      <th>#ID</th>\n",
       "      <th>#PCT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AmerisourceBergen Corp:  ABC US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>AmerisourceBergen Corp:  ABC US Equity</td>\n",
       "      <td>0.057162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AXIS Specialty Finance PLC:  0960932DLN Equity</th>\n",
       "      <td>AQ251879 Corp</td>\n",
       "      <td>AXIS Specialty Finance PLC:  0960932DLN Equity</td>\n",
       "      <td>0.006097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimmer Biomet Holdings Inc:  ZBH US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Zimmer Biomet Holdings Inc:  ZBH US Equity</td>\n",
       "      <td>0.096446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Teck Resources Ltd:  TECK/B CN Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Teck Resources Ltd:  TECK/B CN Equity</td>\n",
       "      <td>0.039399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adobe Inc:  ADBE US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Adobe Inc:  ADBE US Equity</td>\n",
       "      <td>0.072335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Host Hotels &amp; Resorts LP:  3662106ZUS Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Host Hotels &amp; Resorts LP:  3662106ZUS Equity</td>\n",
       "      <td>0.044344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Primerica Inc:  PRI US Equity</th>\n",
       "      <td>EJ280550 Corp</td>\n",
       "      <td>Primerica Inc:  PRI US Equity</td>\n",
       "      <td>0.006528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xylem Inc/NY:  XYL US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Xylem Inc/NY:  XYL US Equity</td>\n",
       "      <td>0.026126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Crane Co:  CR US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Crane Co:  CR US Equity</td>\n",
       "      <td>0.010510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana University Health Inc:  1262016DUS Equity</th>\n",
       "      <td>AS152683 Corp</td>\n",
       "      <td>Indiana University Health Inc:  1262016DUS Equity</td>\n",
       "      <td>0.007937</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                        ORIG_IDS  \\\n",
       "ID                                                                 \n",
       "AmerisourceBergen Corp:  ABC US Equity                      None   \n",
       "AXIS Specialty Finance PLC:  0960932DLN Equity     AQ251879 Corp   \n",
       "Zimmer Biomet Holdings Inc:  ZBH US Equity                  None   \n",
       "Teck Resources Ltd:  TECK/B CN Equity                       None   \n",
       "Adobe Inc:  ADBE US Equity                                  None   \n",
       "Host Hotels & Resorts LP:  3662106ZUS Equity                None   \n",
       "Primerica Inc:  PRI US Equity                      EJ280550 Corp   \n",
       "Xylem Inc/NY:  XYL US Equity                                None   \n",
       "Crane Co:  CR US Equity                                     None   \n",
       "Indiana University Health Inc:  1262016DUS Equity  AS152683 Corp   \n",
       "\n",
       "                                                                                                 #ID  \\\n",
       "ID                                                                                                     \n",
       "AmerisourceBergen Corp:  ABC US Equity                        AmerisourceBergen Corp:  ABC US Equity   \n",
       "AXIS Specialty Finance PLC:  0960932DLN Equity        AXIS Specialty Finance PLC:  0960932DLN Equity   \n",
       "Zimmer Biomet Holdings Inc:  ZBH US Equity                Zimmer Biomet Holdings Inc:  ZBH US Equity   \n",
       "Teck Resources Ltd:  TECK/B CN Equity                          Teck Resources Ltd:  TECK/B CN Equity   \n",
       "Adobe Inc:  ADBE US Equity                                                Adobe Inc:  ADBE US Equity   \n",
       "Host Hotels & Resorts LP:  3662106ZUS Equity            Host Hotels & Resorts LP:  3662106ZUS Equity   \n",
       "Primerica Inc:  PRI US Equity                                          Primerica Inc:  PRI US Equity   \n",
       "Xylem Inc/NY:  XYL US Equity                                            Xylem Inc/NY:  XYL US Equity   \n",
       "Crane Co:  CR US Equity                                                      Crane Co:  CR US Equity   \n",
       "Indiana University Health Inc:  1262016DUS Equity  Indiana University Health Inc:  1262016DUS Equity   \n",
       "\n",
       "                                                       #PCT  \n",
       "ID                                                           \n",
       "AmerisourceBergen Corp:  ABC US Equity             0.057162  \n",
       "AXIS Specialty Finance PLC:  0960932DLN Equity     0.006097  \n",
       "Zimmer Biomet Holdings Inc:  ZBH US Equity         0.096446  \n",
       "Teck Resources Ltd:  TECK/B CN Equity              0.039399  \n",
       "Adobe Inc:  ADBE US Equity                         0.072335  \n",
       "Host Hotels & Resorts LP:  3662106ZUS Equity       0.044344  \n",
       "Primerica Inc:  PRI US Equity                      0.006528  \n",
       "Xylem Inc/NY:  XYL US Equity                       0.026126  \n",
       "Crane Co:  CR US Equity                            0.010510  \n",
       "Indiana University Health Inc:  1262016DUS Equity  0.007937  "
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdf2 = pd.concat([x.df() for x in response], axis=1, join = 'inner')\n",
    "newdf2.sample(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2acf8da3d1094d929f7fa58c82edae62",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "DataGrid(column_defs=[{'filter': 'number', 'width': 100, 'headerName': '#PctChg3day', 'field': '#PctChg3day'},…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from bqwidgets import DataGrid\n",
    "\n",
    "newdf1 =newdf4.reset_index()\n",
    "dg = DataGrid(data=newdf4)\n",
    "dg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x25c74781c88>"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x25c74962eb8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "newdf4['#parent'].value_counts().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>#PctChg3day</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BEARH153 FH Equity</th>\n",
       "      <td>12.499995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HGU CN Equity</th>\n",
       "      <td>13.104635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XABEAR2 SS Equity</th>\n",
       "      <td>10.419026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DRV US Equity</th>\n",
       "      <td>12.055487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAF LN Equity</th>\n",
       "      <td>15.094340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    #PctChg3day\n",
       "ID                             \n",
       "BEARH153 FH Equity    12.499995\n",
       "HGU CN Equity         13.104635\n",
       "XABEAR2 SS Equity     10.419026\n",
       "DRV US Equity         12.055487\n",
       "BAF LN Equity         15.094340"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp1.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Exponential Moving Avg of Skew<a name=\"G\"></a>\n",
    "#### 5 day period, 30d 90/110"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "request = \"\"\"\n",
    "let(\n",
    "    #Skew=implied_volatility(EXPIRY=30D,PCT_MONEYNESS=90,fill=prev)-implied_volatility(EXPIRY=30D,PCT_MONEYNESS=110,fill=prev);\n",
    "    #EMAVG_Skew=emavg(close=#skew,period=5);\n",
    "    #SPX_EMAVG_Skew=wavg(group(#EMAVG_Skew),group(id().weights));\n",
    "    #Hist_SPX_EMAVG_Skew=rolling(#SPX_EMAVG_Skew,iterationdates=range(-2y,0d,frq=m));\n",
    ") \n",
    "get(\n",
    "    #Hist_SPX_emavg_skew\n",
    ") \n",
    "for(\n",
    "    members('spx index')\n",
    ")\t\t\t\t\t\t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response7 = bq.execute(request)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>ORIG_IDS:0</th>\n",
       "      <th>ORIG_IDS:1</th>\n",
       "      <th>ITERATION_DATE</th>\n",
       "      <th>ITERATION_ID</th>\n",
       "      <th>#Hist_SPX_emavg_skew</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-02-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-02-27</td>\n",
       "      <td>IdentityGroup:ITR0</td>\n",
       "      <td>6.545493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-03-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-03-27</td>\n",
       "      <td>IdentityGroup:ITR1</td>\n",
       "      <td>7.576934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>IdentityGroup:ITR2</td>\n",
       "      <td>6.667373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-05-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-05-27</td>\n",
       "      <td>IdentityGroup:ITR3</td>\n",
       "      <td>5.791063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-06-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-06-27</td>\n",
       "      <td>IdentityGroup:ITR4</td>\n",
       "      <td>6.165063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-07-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-07-27</td>\n",
       "      <td>IdentityGroup:ITR5</td>\n",
       "      <td>5.495049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-08-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-08-27</td>\n",
       "      <td>IdentityGroup:ITR6</td>\n",
       "      <td>5.766922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-09-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-09-27</td>\n",
       "      <td>IdentityGroup:ITR7</td>\n",
       "      <td>5.620474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-10-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-10-27</td>\n",
       "      <td>IdentityGroup:ITR8</td>\n",
       "      <td>7.595842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-11-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-11-27</td>\n",
       "      <td>IdentityGroup:ITR9</td>\n",
       "      <td>8.080054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-12-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2018-12-27</td>\n",
       "      <td>IdentityGroup:ITR10</td>\n",
       "      <td>8.645681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-01-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-01-27</td>\n",
       "      <td>IdentityGroup:ITR11</td>\n",
       "      <td>7.739962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-02-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-02-27</td>\n",
       "      <td>IdentityGroup:ITR12</td>\n",
       "      <td>7.468993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-03-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-03-27</td>\n",
       "      <td>IdentityGroup:ITR13</td>\n",
       "      <td>7.611469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-04-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-04-27</td>\n",
       "      <td>IdentityGroup:ITR14</td>\n",
       "      <td>6.830439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>IdentityGroup:ITR15</td>\n",
       "      <td>8.047241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>IdentityGroup:ITR16</td>\n",
       "      <td>7.218861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-07-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-07-27</td>\n",
       "      <td>IdentityGroup:ITR17</td>\n",
       "      <td>6.649103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>IdentityGroup:ITR18</td>\n",
       "      <td>9.061139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-09-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-09-27</td>\n",
       "      <td>IdentityGroup:ITR19</td>\n",
       "      <td>8.242433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-10-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-10-27</td>\n",
       "      <td>IdentityGroup:ITR20</td>\n",
       "      <td>7.443010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-11-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-11-27</td>\n",
       "      <td>IdentityGroup:ITR21</td>\n",
       "      <td>6.841168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-12-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2019-12-27</td>\n",
       "      <td>IdentityGroup:ITR22</td>\n",
       "      <td>6.821059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>IdentityGroup:ITR23</td>\n",
       "      <td>6.183642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>None</td>\n",
       "      <td>IdentityGroup</td>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>IdentityGroup:ITR24</td>\n",
       "      <td>8.797951</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    DATE ORIG_IDS:0     ORIG_IDS:1 ITERATION_DATE  \\\n",
       "ID                                                                  \n",
       "IdentityGroup 2018-02-27       None  IdentityGroup     2018-02-27   \n",
       "IdentityGroup 2018-03-27       None  IdentityGroup     2018-03-27   \n",
       "IdentityGroup 2018-04-27       None  IdentityGroup     2018-04-27   \n",
       "IdentityGroup 2018-05-27       None  IdentityGroup     2018-05-27   \n",
       "IdentityGroup 2018-06-27       None  IdentityGroup     2018-06-27   \n",
       "IdentityGroup 2018-07-27       None  IdentityGroup     2018-07-27   \n",
       "IdentityGroup 2018-08-27       None  IdentityGroup     2018-08-27   \n",
       "IdentityGroup 2018-09-27       None  IdentityGroup     2018-09-27   \n",
       "IdentityGroup 2018-10-27       None  IdentityGroup     2018-10-27   \n",
       "IdentityGroup 2018-11-27       None  IdentityGroup     2018-11-27   \n",
       "IdentityGroup 2018-12-27       None  IdentityGroup     2018-12-27   \n",
       "IdentityGroup 2019-01-27       None  IdentityGroup     2019-01-27   \n",
       "IdentityGroup 2019-02-27       None  IdentityGroup     2019-02-27   \n",
       "IdentityGroup 2019-03-27       None  IdentityGroup     2019-03-27   \n",
       "IdentityGroup 2019-04-27       None  IdentityGroup     2019-04-27   \n",
       "IdentityGroup 2019-05-27       None  IdentityGroup     2019-05-27   \n",
       "IdentityGroup 2019-06-27       None  IdentityGroup     2019-06-27   \n",
       "IdentityGroup 2019-07-27       None  IdentityGroup     2019-07-27   \n",
       "IdentityGroup 2019-08-27       None  IdentityGroup     2019-08-27   \n",
       "IdentityGroup 2019-09-27       None  IdentityGroup     2019-09-27   \n",
       "IdentityGroup 2019-10-27       None  IdentityGroup     2019-10-27   \n",
       "IdentityGroup 2019-11-27       None  IdentityGroup     2019-11-27   \n",
       "IdentityGroup 2019-12-27       None  IdentityGroup     2019-12-27   \n",
       "IdentityGroup 2020-01-27       None  IdentityGroup     2020-01-27   \n",
       "IdentityGroup 2020-02-27       None  IdentityGroup     2020-02-27   \n",
       "\n",
       "                      ITERATION_ID  #Hist_SPX_emavg_skew  \n",
       "ID                                                        \n",
       "IdentityGroup   IdentityGroup:ITR0              6.545493  \n",
       "IdentityGroup   IdentityGroup:ITR1              7.576934  \n",
       "IdentityGroup   IdentityGroup:ITR2              6.667373  \n",
       "IdentityGroup   IdentityGroup:ITR3              5.791063  \n",
       "IdentityGroup   IdentityGroup:ITR4              6.165063  \n",
       "IdentityGroup   IdentityGroup:ITR5              5.495049  \n",
       "IdentityGroup   IdentityGroup:ITR6              5.766922  \n",
       "IdentityGroup   IdentityGroup:ITR7              5.620474  \n",
       "IdentityGroup   IdentityGroup:ITR8              7.595842  \n",
       "IdentityGroup   IdentityGroup:ITR9              8.080054  \n",
       "IdentityGroup  IdentityGroup:ITR10              8.645681  \n",
       "IdentityGroup  IdentityGroup:ITR11              7.739962  \n",
       "IdentityGroup  IdentityGroup:ITR12              7.468993  \n",
       "IdentityGroup  IdentityGroup:ITR13              7.611469  \n",
       "IdentityGroup  IdentityGroup:ITR14              6.830439  \n",
       "IdentityGroup  IdentityGroup:ITR15              8.047241  \n",
       "IdentityGroup  IdentityGroup:ITR16              7.218861  \n",
       "IdentityGroup  IdentityGroup:ITR17              6.649103  \n",
       "IdentityGroup  IdentityGroup:ITR18              9.061139  \n",
       "IdentityGroup  IdentityGroup:ITR19              8.242433  \n",
       "IdentityGroup  IdentityGroup:ITR20              7.443010  \n",
       "IdentityGroup  IdentityGroup:ITR21              6.841168  \n",
       "IdentityGroup  IdentityGroup:ITR22              6.821059  \n",
       "IdentityGroup  IdentityGroup:ITR23              6.183642  \n",
       "IdentityGroup  IdentityGroup:ITR24              8.797951  "
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the response in a DataFrame\n",
    "newdf = bql.combined_df(response7)\n",
    "newdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>ITERATION_ID</th>\n",
       "      <th>#Hist_SPX_emavg_skew</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-02-27</td>\n",
       "      <td>IdentityGroup:ITR0</td>\n",
       "      <td>6.545493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-03-27</td>\n",
       "      <td>IdentityGroup:ITR1</td>\n",
       "      <td>7.576934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-04-27</td>\n",
       "      <td>IdentityGroup:ITR2</td>\n",
       "      <td>6.667373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-05-27</td>\n",
       "      <td>IdentityGroup:ITR3</td>\n",
       "      <td>5.791063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-06-27</td>\n",
       "      <td>IdentityGroup:ITR4</td>\n",
       "      <td>6.165063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-07-27</td>\n",
       "      <td>IdentityGroup:ITR5</td>\n",
       "      <td>5.495049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-08-27</td>\n",
       "      <td>IdentityGroup:ITR6</td>\n",
       "      <td>5.766922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-09-27</td>\n",
       "      <td>IdentityGroup:ITR7</td>\n",
       "      <td>5.620474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-10-27</td>\n",
       "      <td>IdentityGroup:ITR8</td>\n",
       "      <td>7.595842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-11-27</td>\n",
       "      <td>IdentityGroup:ITR9</td>\n",
       "      <td>8.080054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2018-12-27</td>\n",
       "      <td>IdentityGroup:ITR10</td>\n",
       "      <td>8.645681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-01-27</td>\n",
       "      <td>IdentityGroup:ITR11</td>\n",
       "      <td>7.739962</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-02-27</td>\n",
       "      <td>IdentityGroup:ITR12</td>\n",
       "      <td>7.468993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-03-27</td>\n",
       "      <td>IdentityGroup:ITR13</td>\n",
       "      <td>7.611469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-04-27</td>\n",
       "      <td>IdentityGroup:ITR14</td>\n",
       "      <td>6.830439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-05-27</td>\n",
       "      <td>IdentityGroup:ITR15</td>\n",
       "      <td>8.047241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-06-27</td>\n",
       "      <td>IdentityGroup:ITR16</td>\n",
       "      <td>7.218861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-07-27</td>\n",
       "      <td>IdentityGroup:ITR17</td>\n",
       "      <td>6.649103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-08-27</td>\n",
       "      <td>IdentityGroup:ITR18</td>\n",
       "      <td>9.061139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-09-27</td>\n",
       "      <td>IdentityGroup:ITR19</td>\n",
       "      <td>8.242433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-10-27</td>\n",
       "      <td>IdentityGroup:ITR20</td>\n",
       "      <td>7.443010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-11-27</td>\n",
       "      <td>IdentityGroup:ITR21</td>\n",
       "      <td>6.841168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2019-12-27</td>\n",
       "      <td>IdentityGroup:ITR22</td>\n",
       "      <td>6.821059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>IdentityGroup:ITR23</td>\n",
       "      <td>6.183642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IdentityGroup</th>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>IdentityGroup:ITR24</td>\n",
       "      <td>8.797951</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    DATE         ITERATION_ID  #Hist_SPX_emavg_skew\n",
       "ID                                                                 \n",
       "IdentityGroup 2018-02-27   IdentityGroup:ITR0              6.545493\n",
       "IdentityGroup 2018-03-27   IdentityGroup:ITR1              7.576934\n",
       "IdentityGroup 2018-04-27   IdentityGroup:ITR2              6.667373\n",
       "IdentityGroup 2018-05-27   IdentityGroup:ITR3              5.791063\n",
       "IdentityGroup 2018-06-27   IdentityGroup:ITR4              6.165063\n",
       "IdentityGroup 2018-07-27   IdentityGroup:ITR5              5.495049\n",
       "IdentityGroup 2018-08-27   IdentityGroup:ITR6              5.766922\n",
       "IdentityGroup 2018-09-27   IdentityGroup:ITR7              5.620474\n",
       "IdentityGroup 2018-10-27   IdentityGroup:ITR8              7.595842\n",
       "IdentityGroup 2018-11-27   IdentityGroup:ITR9              8.080054\n",
       "IdentityGroup 2018-12-27  IdentityGroup:ITR10              8.645681\n",
       "IdentityGroup 2019-01-27  IdentityGroup:ITR11              7.739962\n",
       "IdentityGroup 2019-02-27  IdentityGroup:ITR12              7.468993\n",
       "IdentityGroup 2019-03-27  IdentityGroup:ITR13              7.611469\n",
       "IdentityGroup 2019-04-27  IdentityGroup:ITR14              6.830439\n",
       "IdentityGroup 2019-05-27  IdentityGroup:ITR15              8.047241\n",
       "IdentityGroup 2019-06-27  IdentityGroup:ITR16              7.218861\n",
       "IdentityGroup 2019-07-27  IdentityGroup:ITR17              6.649103\n",
       "IdentityGroup 2019-08-27  IdentityGroup:ITR18              9.061139\n",
       "IdentityGroup 2019-09-27  IdentityGroup:ITR19              8.242433\n",
       "IdentityGroup 2019-10-27  IdentityGroup:ITR20              7.443010\n",
       "IdentityGroup 2019-11-27  IdentityGroup:ITR21              6.841168\n",
       "IdentityGroup 2019-12-27  IdentityGroup:ITR22              6.821059\n",
       "IdentityGroup 2020-01-27  IdentityGroup:ITR23              6.183642\n",
       "IdentityGroup 2020-02-27  IdentityGroup:ITR24              8.797951"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdf = newdf.drop(['ORIG_IDS:0', 'ORIG_IDS:1', 'ITERATION_DATE'], axis=1)\n",
    "newdf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Reading Public Portfolios<a name=\"H\"></a>\n",
    "#### e.g. using the FLNG number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "request = \"\"\"\n",
    "get(\n",
    "      ID\n",
    ") \n",
    "for(\n",
    "    members(Type=Holdings, symbols='SPY US Equity')\n",
    ") \t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response8 = bq.execute(request)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": true
    }
   },
   "source": [
    "request = \"\"\"\n",
    "get(\n",
    "      ID\n",
    ") \n",
    "for(\n",
    "    members(['H319705-10 Client'],Type=PORT)\n",
    ") \t\t\t\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response8 = bq.execute(request)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
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   "outputs": [
    {
     "data": {
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       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>POSITION</th>\n",
       "      <th>WEIGHTS</th>\n",
       "      <th>AS_OF_DATE</th>\n",
       "      <th>REPORTED_MKT_VAL</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>LATEST_CHANGE</th>\n",
       "      <th>ORIG_IDS</th>\n",
       "      <th>ID</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MSFT US Equity</th>\n",
       "      <td>82117353.0</td>\n",
       "      <td>5.812282</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.482465e+10</td>\n",
       "      <td>USD</td>\n",
       "      <td>-486628.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>MSFT US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAPL US Equity</th>\n",
       "      <td>44958208.0</td>\n",
       "      <td>5.456173</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.391636e+10</td>\n",
       "      <td>USD</td>\n",
       "      <td>-270632.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>AAPL US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN US Equity</th>\n",
       "      <td>4482935.0</td>\n",
       "      <td>4.198689</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.070906e+10</td>\n",
       "      <td>USD</td>\n",
       "      <td>-27000.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>AMZN US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FB US Equity</th>\n",
       "      <td>25909176.0</td>\n",
       "      <td>2.100814</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>5.358277e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-150280.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>FB US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOGL US Equity</th>\n",
       "      <td>3225975.0</td>\n",
       "      <td>1.716163</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>4.377196e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-18720.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>GOOGL US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GOOG US Equity</th>\n",
       "      <td>3217952.0</td>\n",
       "      <td>1.710973</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>4.363961e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-18720.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>GOOG US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JNJ US Equity</th>\n",
       "      <td>28335998.0</td>\n",
       "      <td>1.640231</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>4.183527e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-164424.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>JNJ US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BRK/B US Equity</th>\n",
       "      <td>21059635.0</td>\n",
       "      <td>1.411340</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.599723e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-122200.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>BRK/B US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>V US Equity</th>\n",
       "      <td>18428658.0</td>\n",
       "      <td>1.307057</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.333744e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-106912.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>V US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PG US Equity</th>\n",
       "      <td>26849605.0</td>\n",
       "      <td>1.198066</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.055754e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-155792.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>PG US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPM US Equity</th>\n",
       "      <td>33765636.0</td>\n",
       "      <td>1.158630</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.955168e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-195936.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>JPM US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNH US Equity</th>\n",
       "      <td>10200376.0</td>\n",
       "      <td>1.162222</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.964331e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-59176.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>UNH US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HD US Equity</th>\n",
       "      <td>11743260.0</td>\n",
       "      <td>1.079585</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.753560e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-68120.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>HD US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INTC US Equity</th>\n",
       "      <td>46823998.0</td>\n",
       "      <td>1.084604</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.766362e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-299848.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>INTC US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MA US Equity</th>\n",
       "      <td>9557775.0</td>\n",
       "      <td>1.039166</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.650467e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-55432.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>MA US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VZ US Equity</th>\n",
       "      <td>44527766.0</td>\n",
       "      <td>0.958616</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.445020e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-258336.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>VZ US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T US Equity</th>\n",
       "      <td>78679936.0</td>\n",
       "      <td>0.881635</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.248673e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-456248.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>T US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFE US Equity</th>\n",
       "      <td>59583039.0</td>\n",
       "      <td>0.885836</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.259389e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-345696.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>PFE US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MRK US Equity</th>\n",
       "      <td>27411280.0</td>\n",
       "      <td>0.860306</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.194273e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-159016.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>MRK US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NVDA US Equity</th>\n",
       "      <td>6587597.0</td>\n",
       "      <td>0.829644</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.116068e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-43472.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>NVDA US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NFLX US Equity</th>\n",
       "      <td>4718411.0</td>\n",
       "      <td>0.817582</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.085302e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-27352.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>NFLX US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DIS US Equity</th>\n",
       "      <td>19405454.0</td>\n",
       "      <td>0.805792</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.055232e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-112528.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>DIS US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XOM US Equity</th>\n",
       "      <td>45554149.0</td>\n",
       "      <td>0.755493</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.926941e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-264264.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>XOM US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEP US Equity</th>\n",
       "      <td>15018848.0</td>\n",
       "      <td>0.783631</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.998708e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-87048.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>PEP US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSCO US Equity</th>\n",
       "      <td>45674230.0</td>\n",
       "      <td>0.785241</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.002815e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-264992.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>CSCO US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAC US Equity</th>\n",
       "      <td>87161066.0</td>\n",
       "      <td>0.741899</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.892267e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-505648.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>BAC US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADBE US Equity</th>\n",
       "      <td>5211796.0</td>\n",
       "      <td>0.726198</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.852220e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-30264.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>ADBE US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WMT US Equity</th>\n",
       "      <td>15273208.0</td>\n",
       "      <td>0.739057</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.885019e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-88608.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>WMT US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KO US Equity</th>\n",
       "      <td>41515949.0</td>\n",
       "      <td>0.711310</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.814247e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-240864.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>KO US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CVX US Equity</th>\n",
       "      <td>20358082.0</td>\n",
       "      <td>0.718758</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.833245e+09</td>\n",
       "      <td>USD</td>\n",
       "      <td>-118144.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>CVX US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NWSA US Equity</th>\n",
       "      <td>4028211.0</td>\n",
       "      <td>0.016946</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>4.322270e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-24232.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>NWSA US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIM US Equity</th>\n",
       "      <td>4471660.0</td>\n",
       "      <td>0.016164</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>4.122871e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-26416.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>KIM US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAL US Equity</th>\n",
       "      <td>4252262.0</td>\n",
       "      <td>0.015255</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.890820e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-24336.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>AAL US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MOS US Equity</th>\n",
       "      <td>3751408.0</td>\n",
       "      <td>0.015296</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.901464e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-21840.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>MOS US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TPR US Equity</th>\n",
       "      <td>2973867.0</td>\n",
       "      <td>0.014470</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.690569e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-17264.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>TPR US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEG US Equity</th>\n",
       "      <td>1391253.0</td>\n",
       "      <td>0.014744</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.760557e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-8216.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>LEG US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SLG US Equity</th>\n",
       "      <td>887439.0</td>\n",
       "      <td>0.013705</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.495622e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-5096.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>SLG US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALK US Equity</th>\n",
       "      <td>1324531.0</td>\n",
       "      <td>0.013575</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.462324e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-7696.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>ALK US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RL US Equity</th>\n",
       "      <td>536012.0</td>\n",
       "      <td>0.013843</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.530711e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-3120.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>RL US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>XRX US Equity</th>\n",
       "      <td>2049563.0</td>\n",
       "      <td>0.012367</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.154277e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-11648.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>XRX US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FTI US Equity</th>\n",
       "      <td>4520933.0</td>\n",
       "      <td>0.011787</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.006420e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-26208.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>FTI US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HOG US Equity</th>\n",
       "      <td>1708455.0</td>\n",
       "      <td>0.013095</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.340030e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-9672.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>HOG US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HBI US Equity</th>\n",
       "      <td>3899519.0</td>\n",
       "      <td>0.013041</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.326290e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-22568.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>HBI US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HRB US Equity</th>\n",
       "      <td>2155828.0</td>\n",
       "      <td>0.012991</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.313508e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-12168.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>HRB US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PVH US Equity</th>\n",
       "      <td>796677.0</td>\n",
       "      <td>0.012878</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.284699e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-4680.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>PVH US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DISCA US Equity</th>\n",
       "      <td>1692908.0</td>\n",
       "      <td>0.013633</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.477233e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-9880.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>DISCA US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNM US Equity</th>\n",
       "      <td>2246393.0</td>\n",
       "      <td>0.012172</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.104515e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-12896.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>UNM US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLS US Equity</th>\n",
       "      <td>1376070.0</td>\n",
       "      <td>0.012398</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>3.162209e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-8216.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>FLS US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IVZ US Equity</th>\n",
       "      <td>4010888.0</td>\n",
       "      <td>0.010992</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.803611e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-23296.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>IVZ US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KSS US Equity</th>\n",
       "      <td>1713635.0</td>\n",
       "      <td>0.011213</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.860057e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-9776.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>KSS US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LB US Equity</th>\n",
       "      <td>2412461.0</td>\n",
       "      <td>0.009913</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.528259e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-14456.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>LB US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NCLH US Equity</th>\n",
       "      <td>2327862.0</td>\n",
       "      <td>0.009820</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.504780e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-15600.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>NCLH US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HP US Equity</th>\n",
       "      <td>1185638.0</td>\n",
       "      <td>0.008065</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>2.057082e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-6760.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>HP US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JWN US Equity</th>\n",
       "      <td>1131119.0</td>\n",
       "      <td>0.006923</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.765677e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-6656.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>JWN US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADS US Equity</th>\n",
       "      <td>441042.0</td>\n",
       "      <td>0.006810</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.736823e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-2600.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>ADS US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GPS US Equity</th>\n",
       "      <td>2317534.0</td>\n",
       "      <td>0.006515</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.661672e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-13312.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>GPS US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UAA US Equity</th>\n",
       "      <td>1954616.0</td>\n",
       "      <td>0.005909</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.507009e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-11752.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>UAA US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA US Equity</th>\n",
       "      <td>2083516.0</td>\n",
       "      <td>0.005645</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.439710e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-12168.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>UA US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NWS US Equity</th>\n",
       "      <td>1327684.0</td>\n",
       "      <td>0.005726</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.460452e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-7592.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>NWS US Equity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COTY US Equity</th>\n",
       "      <td>3233659.0</td>\n",
       "      <td>0.004260</td>\n",
       "      <td>2020-05-14</td>\n",
       "      <td>1.086509e+07</td>\n",
       "      <td>USD</td>\n",
       "      <td>-18512.0</td>\n",
       "      <td>SPY US Equity</td>\n",
       "      <td>COTY US Equity</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>505 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   POSITION   WEIGHTS AS_OF_DATE  REPORTED_MKT_VAL CURRENCY  \\\n",
       "ID                                                                            \n",
       "MSFT US Equity   82117353.0  5.812282 2020-05-14      1.482465e+10      USD   \n",
       "AAPL US Equity   44958208.0  5.456173 2020-05-14      1.391636e+10      USD   \n",
       "AMZN US Equity    4482935.0  4.198689 2020-05-14      1.070906e+10      USD   \n",
       "FB US Equity     25909176.0  2.100814 2020-05-14      5.358277e+09      USD   \n",
       "GOOGL US Equity   3225975.0  1.716163 2020-05-14      4.377196e+09      USD   \n",
       "GOOG US Equity    3217952.0  1.710973 2020-05-14      4.363961e+09      USD   \n",
       "JNJ US Equity    28335998.0  1.640231 2020-05-14      4.183527e+09      USD   \n",
       "BRK/B US Equity  21059635.0  1.411340 2020-05-14      3.599723e+09      USD   \n",
       "V US Equity      18428658.0  1.307057 2020-05-14      3.333744e+09      USD   \n",
       "PG US Equity     26849605.0  1.198066 2020-05-14      3.055754e+09      USD   \n",
       "JPM US Equity    33765636.0  1.158630 2020-05-14      2.955168e+09      USD   \n",
       "UNH US Equity    10200376.0  1.162222 2020-05-14      2.964331e+09      USD   \n",
       "HD US Equity     11743260.0  1.079585 2020-05-14      2.753560e+09      USD   \n",
       "INTC US Equity   46823998.0  1.084604 2020-05-14      2.766362e+09      USD   \n",
       "MA US Equity      9557775.0  1.039166 2020-05-14      2.650467e+09      USD   \n",
       "VZ US Equity     44527766.0  0.958616 2020-05-14      2.445020e+09      USD   \n",
       "T US Equity      78679936.0  0.881635 2020-05-14      2.248673e+09      USD   \n",
       "PFE US Equity    59583039.0  0.885836 2020-05-14      2.259389e+09      USD   \n",
       "MRK US Equity    27411280.0  0.860306 2020-05-14      2.194273e+09      USD   \n",
       "NVDA US Equity    6587597.0  0.829644 2020-05-14      2.116068e+09      USD   \n",
       "NFLX US Equity    4718411.0  0.817582 2020-05-14      2.085302e+09      USD   \n",
       "DIS US Equity    19405454.0  0.805792 2020-05-14      2.055232e+09      USD   \n",
       "XOM US Equity    45554149.0  0.755493 2020-05-14      1.926941e+09      USD   \n",
       "PEP US Equity    15018848.0  0.783631 2020-05-14      1.998708e+09      USD   \n",
       "CSCO US Equity   45674230.0  0.785241 2020-05-14      2.002815e+09      USD   \n",
       "BAC US Equity    87161066.0  0.741899 2020-05-14      1.892267e+09      USD   \n",
       "ADBE US Equity    5211796.0  0.726198 2020-05-14      1.852220e+09      USD   \n",
       "WMT US Equity    15273208.0  0.739057 2020-05-14      1.885019e+09      USD   \n",
       "KO US Equity     41515949.0  0.711310 2020-05-14      1.814247e+09      USD   \n",
       "CVX US Equity    20358082.0  0.718758 2020-05-14      1.833245e+09      USD   \n",
       "...                     ...       ...        ...               ...      ...   \n",
       "NWSA US Equity    4028211.0  0.016946 2020-05-14      4.322270e+07      USD   \n",
       "KIM US Equity     4471660.0  0.016164 2020-05-14      4.122871e+07      USD   \n",
       "AAL US Equity     4252262.0  0.015255 2020-05-14      3.890820e+07      USD   \n",
       "MOS US Equity     3751408.0  0.015296 2020-05-14      3.901464e+07      USD   \n",
       "TPR US Equity     2973867.0  0.014470 2020-05-14      3.690569e+07      USD   \n",
       "LEG US Equity     1391253.0  0.014744 2020-05-14      3.760557e+07      USD   \n",
       "SLG US Equity      887439.0  0.013705 2020-05-14      3.495622e+07      USD   \n",
       "ALK US Equity     1324531.0  0.013575 2020-05-14      3.462324e+07      USD   \n",
       "RL US Equity       536012.0  0.013843 2020-05-14      3.530711e+07      USD   \n",
       "XRX US Equity     2049563.0  0.012367 2020-05-14      3.154277e+07      USD   \n",
       "FTI US Equity     4520933.0  0.011787 2020-05-14      3.006420e+07      USD   \n",
       "HOG US Equity     1708455.0  0.013095 2020-05-14      3.340030e+07      USD   \n",
       "HBI US Equity     3899519.0  0.013041 2020-05-14      3.326290e+07      USD   \n",
       "HRB US Equity     2155828.0  0.012991 2020-05-14      3.313508e+07      USD   \n",
       "PVH US Equity      796677.0  0.012878 2020-05-14      3.284699e+07      USD   \n",
       "DISCA US Equity   1692908.0  0.013633 2020-05-14      3.477233e+07      USD   \n",
       "UNM US Equity     2246393.0  0.012172 2020-05-14      3.104515e+07      USD   \n",
       "FLS US Equity     1376070.0  0.012398 2020-05-14      3.162209e+07      USD   \n",
       "IVZ US Equity     4010888.0  0.010992 2020-05-14      2.803611e+07      USD   \n",
       "KSS US Equity     1713635.0  0.011213 2020-05-14      2.860057e+07      USD   \n",
       "LB US Equity      2412461.0  0.009913 2020-05-14      2.528259e+07      USD   \n",
       "NCLH US Equity    2327862.0  0.009820 2020-05-14      2.504780e+07      USD   \n",
       "HP US Equity      1185638.0  0.008065 2020-05-14      2.057082e+07      USD   \n",
       "JWN US Equity     1131119.0  0.006923 2020-05-14      1.765677e+07      USD   \n",
       "ADS US Equity      441042.0  0.006810 2020-05-14      1.736823e+07      USD   \n",
       "GPS US Equity     2317534.0  0.006515 2020-05-14      1.661672e+07      USD   \n",
       "UAA US Equity     1954616.0  0.005909 2020-05-14      1.507009e+07      USD   \n",
       "UA US Equity      2083516.0  0.005645 2020-05-14      1.439710e+07      USD   \n",
       "NWS US Equity     1327684.0  0.005726 2020-05-14      1.460452e+07      USD   \n",
       "COTY US Equity    3233659.0  0.004260 2020-05-14      1.086509e+07      USD   \n",
       "\n",
       "                 LATEST_CHANGE       ORIG_IDS               ID  \n",
       "ID                                                              \n",
       "MSFT US Equity       -486628.0  SPY US Equity   MSFT US Equity  \n",
       "AAPL US Equity       -270632.0  SPY US Equity   AAPL US Equity  \n",
       "AMZN US Equity        -27000.0  SPY US Equity   AMZN US Equity  \n",
       "FB US Equity         -150280.0  SPY US Equity     FB US Equity  \n",
       "GOOGL US Equity       -18720.0  SPY US Equity  GOOGL US Equity  \n",
       "GOOG US Equity        -18720.0  SPY US Equity   GOOG US Equity  \n",
       "JNJ US Equity        -164424.0  SPY US Equity    JNJ US Equity  \n",
       "BRK/B US Equity      -122200.0  SPY US Equity  BRK/B US Equity  \n",
       "V US Equity          -106912.0  SPY US Equity      V US Equity  \n",
       "PG US Equity         -155792.0  SPY US Equity     PG US Equity  \n",
       "JPM US Equity        -195936.0  SPY US Equity    JPM US Equity  \n",
       "UNH US Equity         -59176.0  SPY US Equity    UNH US Equity  \n",
       "HD US Equity          -68120.0  SPY US Equity     HD US Equity  \n",
       "INTC US Equity       -299848.0  SPY US Equity   INTC US Equity  \n",
       "MA US Equity          -55432.0  SPY US Equity     MA US Equity  \n",
       "VZ US Equity         -258336.0  SPY US Equity     VZ US Equity  \n",
       "T US Equity          -456248.0  SPY US Equity      T US Equity  \n",
       "PFE US Equity        -345696.0  SPY US Equity    PFE US Equity  \n",
       "MRK US Equity        -159016.0  SPY US Equity    MRK US Equity  \n",
       "NVDA US Equity        -43472.0  SPY US Equity   NVDA US Equity  \n",
       "NFLX US Equity        -27352.0  SPY US Equity   NFLX US Equity  \n",
       "DIS US Equity        -112528.0  SPY US Equity    DIS US Equity  \n",
       "XOM US Equity        -264264.0  SPY US Equity    XOM US Equity  \n",
       "PEP US Equity         -87048.0  SPY US Equity    PEP US Equity  \n",
       "CSCO US Equity       -264992.0  SPY US Equity   CSCO US Equity  \n",
       "BAC US Equity        -505648.0  SPY US Equity    BAC US Equity  \n",
       "ADBE US Equity        -30264.0  SPY US Equity   ADBE US Equity  \n",
       "WMT US Equity         -88608.0  SPY US Equity    WMT US Equity  \n",
       "KO US Equity         -240864.0  SPY US Equity     KO US Equity  \n",
       "CVX US Equity        -118144.0  SPY US Equity    CVX US Equity  \n",
       "...                        ...            ...              ...  \n",
       "NWSA US Equity        -24232.0  SPY US Equity   NWSA US Equity  \n",
       "KIM US Equity         -26416.0  SPY US Equity    KIM US Equity  \n",
       "AAL US Equity         -24336.0  SPY US Equity    AAL US Equity  \n",
       "MOS US Equity         -21840.0  SPY US Equity    MOS US Equity  \n",
       "TPR US Equity         -17264.0  SPY US Equity    TPR US Equity  \n",
       "LEG US Equity          -8216.0  SPY US Equity    LEG US Equity  \n",
       "SLG US Equity          -5096.0  SPY US Equity    SLG US Equity  \n",
       "ALK US Equity          -7696.0  SPY US Equity    ALK US Equity  \n",
       "RL US Equity           -3120.0  SPY US Equity     RL US Equity  \n",
       "XRX US Equity         -11648.0  SPY US Equity    XRX US Equity  \n",
       "FTI US Equity         -26208.0  SPY US Equity    FTI US Equity  \n",
       "HOG US Equity          -9672.0  SPY US Equity    HOG US Equity  \n",
       "HBI US Equity         -22568.0  SPY US Equity    HBI US Equity  \n",
       "HRB US Equity         -12168.0  SPY US Equity    HRB US Equity  \n",
       "PVH US Equity          -4680.0  SPY US Equity    PVH US Equity  \n",
       "DISCA US Equity        -9880.0  SPY US Equity  DISCA US Equity  \n",
       "UNM US Equity         -12896.0  SPY US Equity    UNM US Equity  \n",
       "FLS US Equity          -8216.0  SPY US Equity    FLS US Equity  \n",
       "IVZ US Equity         -23296.0  SPY US Equity    IVZ US Equity  \n",
       "KSS US Equity          -9776.0  SPY US Equity    KSS US Equity  \n",
       "LB US Equity          -14456.0  SPY US Equity     LB US Equity  \n",
       "NCLH US Equity        -15600.0  SPY US Equity   NCLH US Equity  \n",
       "HP US Equity           -6760.0  SPY US Equity     HP US Equity  \n",
       "JWN US Equity          -6656.0  SPY US Equity    JWN US Equity  \n",
       "ADS US Equity          -2600.0  SPY US Equity    ADS US Equity  \n",
       "GPS US Equity         -13312.0  SPY US Equity    GPS US Equity  \n",
       "UAA US Equity         -11752.0  SPY US Equity    UAA US Equity  \n",
       "UA US Equity          -12168.0  SPY US Equity     UA US Equity  \n",
       "NWS US Equity          -7592.0  SPY US Equity    NWS US Equity  \n",
       "COTY US Equity        -18512.0  SPY US Equity   COTY US Equity  \n",
       "\n",
       "[505 rows x 8 columns]"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the response in a DataFrame\n",
    "newdf2 =response8[0].df()\n",
    "#newdf2 = bql.combined_df(response8)\n",
    "newdf2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cross Asset Query <a name=\"J\"></a>\n",
    "##### What are the companies that I am the most exposed to within the US Corporate Bond Index (LUACTRUU)?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "request = \"\"\"\n",
    "let(\n",
    "#NAME=VALUE(NAME,translatesymbols(members('LUACTRUU index'),instrumentidtype='Corp',targetIDtype='fundamentalticker'),mapby=lineage).value;\n",
    "\n",
    "#TICKER=VALUE(FUNDAMENTAL_TICKER,translatesymbols(members('LUACTRUU index'),instrumentidtype='Corp',targetIDtype='fundamentalticker'),mapby=lineage).value;\n",
    "\n",
    "#ID=CONCAT(CONCAT(#NAME,':  '), #TICKER);\n",
    "#wgt=ID().Weights;) \n",
    "\n",
    "get(groupsort(SUM(GROUP(#wgt,#ID))) as #PCT) \n",
    "\n",
    "for(Members('LUACTRUU Index')) \n",
    "\n",
    "with(fill=prev)\t\t\t\t\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response9 = bq.execute(request)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ORIG_IDS</th>\n",
       "      <th>#ID</th>\n",
       "      <th>#PCT</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bank of America Corp:  BAC US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Bank of America Corp:  BAC US Equity</td>\n",
       "      <td>2.099665</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPMorgan Chase &amp; Co:  JPM US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>JPMorgan Chase &amp; Co:  JPM US Equity</td>\n",
       "      <td>2.099571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT&amp;T Inc:  T US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>AT&amp;T Inc:  T US Equity</td>\n",
       "      <td>1.753742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Citigroup Inc:  C US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Citigroup Inc:  C US Equity</td>\n",
       "      <td>1.686219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wells Fargo &amp; Co:  WFC US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Wells Fargo &amp; Co:  WFC US Equity</td>\n",
       "      <td>1.629509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Goldman Sachs Group Inc/The:  GS US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Goldman Sachs Group Inc/The:  GS US Equity</td>\n",
       "      <td>1.540419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Comcast Corp:  CMCSA US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Comcast Corp:  CMCSA US Equity</td>\n",
       "      <td>1.494459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Morgan Stanley:  MS US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Morgan Stanley:  MS US Equity</td>\n",
       "      <td>1.362673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Apple Inc:  AAPL US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Apple Inc:  AAPL US Equity</td>\n",
       "      <td>1.315639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Verizon Communications Inc:  VZ US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Verizon Communications Inc:  VZ US Equity</td>\n",
       "      <td>1.238190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CVS Health Corp:  CVS US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>CVS Health Corp:  CVS US Equity</td>\n",
       "      <td>1.175269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Microsoft Corp:  MSFT US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Microsoft Corp:  MSFT US Equity</td>\n",
       "      <td>1.163073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HSBC Holdings PLC:  HSBA LN Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>HSBC Holdings PLC:  HSBA LN Equity</td>\n",
       "      <td>1.045616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AbbVie Inc:  ABBV US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>AbbVie Inc:  ABBV US Equity</td>\n",
       "      <td>1.039327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abi Sab Group Holding Ltd:  SAB LN Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Abi Sab Group Holding Ltd:  SAB LN Equity</td>\n",
       "      <td>1.013033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oracle Corp:  ORCL US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Oracle Corp:  ORCL US Equity</td>\n",
       "      <td>0.917545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Charter Communications Inc:  CHTR US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Charter Communications Inc:  CHTR US Equity</td>\n",
       "      <td>0.790573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bristol-Myers Squibb Co:  BMY US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Bristol-Myers Squibb Co:  BMY US Equity</td>\n",
       "      <td>0.721365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UnitedHealth Group Inc:  UNH US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>UnitedHealth Group Inc:  UNH US Equity</td>\n",
       "      <td>0.694917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Walmart Inc:  WMT US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Walmart Inc:  WMT US Equity</td>\n",
       "      <td>0.690273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Energy Transfer Operating LP:  ETP US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Energy Transfer Operating LP:  ETP US Equity</td>\n",
       "      <td>0.671603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General Electric Co:  GE US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>General Electric Co:  GE US Equity</td>\n",
       "      <td>0.664064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>United Technologies Corp:  UTX US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>United Technologies Corp:  UTX US Equity</td>\n",
       "      <td>0.638596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>International Business Machine:  IBM US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>International Business Machine:  IBM US Equity</td>\n",
       "      <td>0.619489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Shell International Finance BV:  599327Z NA Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Shell International Finance BV:  599327Z NA Eq...</td>\n",
       "      <td>0.601015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pfizer Inc:  PFE US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Pfizer Inc:  PFE US Equity</td>\n",
       "      <td>0.585870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mitsubishi UFJ Financial Group:  8306 JP Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Mitsubishi UFJ Financial Group:  8306 JP Equity</td>\n",
       "      <td>0.585735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sumitomo Mitsui Financial Grou:  8316 JP Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Sumitomo Mitsui Financial Grou:  8316 JP Equity</td>\n",
       "      <td>0.567730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Home Depot Inc/The:  HD US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Home Depot Inc/The:  HD US Equity</td>\n",
       "      <td>0.541458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Enterprise Products Operating:  17249Z US Equity</th>\n",
       "      <td>None</td>\n",
       "      <td>Enterprise Products Operating:  17249Z US Equity</td>\n",
       "      <td>0.540376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lennox International Inc:  LII US Equity</th>\n",
       "      <td>AL001841 Corp</td>\n",
       "      <td>Lennox International Inc:  LII US Equity</td>\n",
       "      <td>0.006018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Eagle Materials Inc:  EXP US Equity</th>\n",
       "      <td>QZ008053 Corp</td>\n",
       "      <td>Eagle Materials Inc:  EXP US Equity</td>\n",
       "      <td>0.005991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Main Street Capital Corp:  MAIN US Equity</th>\n",
       "      <td>ZS258480 Corp</td>\n",
       "      <td>Main Street Capital Corp:  MAIN US Equity</td>\n",
       "      <td>0.005947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Allina Health System:  68907Z US Equity</th>\n",
       "      <td>ZS800054 Corp</td>\n",
       "      <td>Allina Health System:  68907Z US Equity</td>\n",
       "      <td>0.005861</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Prospect Capital Corp:  PSEC US Equity</th>\n",
       "      <td>EJ587828 Corp</td>\n",
       "      <td>Prospect Capital Corp:  PSEC US Equity</td>\n",
       "      <td>0.005813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Bon Secours Mercy Health Inc:  24585Z US Equity</th>\n",
       "      <td>AW031726 Corp</td>\n",
       "      <td>Bon Secours Mercy Health Inc:  24585Z US Equity</td>\n",
       "      <td>0.005797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oshkosh Corp:  OSK US Equity</th>\n",
       "      <td>AS503589 Corp</td>\n",
       "      <td>Oshkosh Corp:  OSK US Equity</td>\n",
       "      <td>0.005667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wintrust Financial Corp:  WTFC US Equity</th>\n",
       "      <td>ZS974039 Corp</td>\n",
       "      <td>Wintrust Financial Corp:  WTFC US Equity</td>\n",
       "      <td>0.005640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Webster Financial Corp:  WBS US Equity</th>\n",
       "      <td>AX779959 Corp</td>\n",
       "      <td>Webster Financial Corp:  WBS US Equity</td>\n",
       "      <td>0.005617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rayonier Inc:  RYN US Equity</th>\n",
       "      <td>EJ048881 Corp</td>\n",
       "      <td>Rayonier Inc:  RYN US Equity</td>\n",
       "      <td>0.005604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Janus Henderson Group PLC:  JHG US Equity</th>\n",
       "      <td>UV380214 Corp</td>\n",
       "      <td>Janus Henderson Group PLC:  JHG US Equity</td>\n",
       "      <td>0.005596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>First American Financial Corp:  FAF US Equity</th>\n",
       "      <td>EK586364 Corp</td>\n",
       "      <td>First American Financial Corp:  FAF US Equity</td>\n",
       "      <td>0.005525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aspen Insurance Holdings Ltd:  AHL US Equity</th>\n",
       "      <td>EJ921373 Corp</td>\n",
       "      <td>Aspen Insurance Holdings Ltd:  AHL US Equity</td>\n",
       "      <td>0.005511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Memorial Health Services:  3240434ZUS Equity</th>\n",
       "      <td>ZQ943115 Corp</td>\n",
       "      <td>Memorial Health Services:  3240434ZUS Equity</td>\n",
       "      <td>0.005510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MedStar Health Inc:  20076Z US Equity</th>\n",
       "      <td>ZP410685 Corp</td>\n",
       "      <td>MedStar Health Inc:  20076Z US Equity</td>\n",
       "      <td>0.005476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sompo Japan Nipponkoa Insuranc:  1228123DJP Equity</th>\n",
       "      <td>EJ388405 Corp</td>\n",
       "      <td>Sompo Japan Nipponkoa Insuranc:  1228123DJP Eq...</td>\n",
       "      <td>0.005404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York Community Bancorp Inc:  NYCB US Equity</th>\n",
       "      <td>AV435464 Corp</td>\n",
       "      <td>New York Community Bancorp Inc:  NYCB US Equity</td>\n",
       "      <td>0.005370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Air Liquide SA:  AI FP Equity</th>\n",
       "      <td>EK331653 Corp</td>\n",
       "      <td>Air Liquide SA:  AI FP Equity</td>\n",
       "      <td>0.005369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Healthcare Realty Trust Inc:  HR US Equity</th>\n",
       "      <td>AQ214314 Corp</td>\n",
       "      <td>Healthcare Realty Trust Inc:  HR US Equity</td>\n",
       "      <td>0.005359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SL Green Realty Corp:  SLG US Equity</th>\n",
       "      <td>EJ439772 Corp</td>\n",
       "      <td>SL Green Realty Corp:  SLG US Equity</td>\n",
       "      <td>0.005334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Trustees of Boston College:  4144477ZUS Equity</th>\n",
       "      <td>ZQ193295 Corp</td>\n",
       "      <td>Trustees of Boston College:  4144477ZUS Equity</td>\n",
       "      <td>0.005298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Regency Centers Corp:  REG US Equity</th>\n",
       "      <td>EJ415633 Corp</td>\n",
       "      <td>Regency Centers Corp:  REG US Equity</td>\n",
       "      <td>0.005262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Domtar Corp:  UFS US Equity</th>\n",
       "      <td>EJ056093 Corp</td>\n",
       "      <td>Domtar Corp:  UFS US Equity</td>\n",
       "      <td>0.005257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington Real Estate Investm:  WRE US Equity</th>\n",
       "      <td>EJ362259 Corp</td>\n",
       "      <td>Washington Real Estate Investm:  WRE US Equity</td>\n",
       "      <td>0.005248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kite Realty Group Trust:  KRG US Equity</th>\n",
       "      <td>QZ580190 Corp</td>\n",
       "      <td>Kite Realty Group Trust:  KRG US Equity</td>\n",
       "      <td>0.005228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Associated Banc-Corp:  ASB US Equity</th>\n",
       "      <td>AT939535 Corp</td>\n",
       "      <td>Associated Banc-Corp:  ASB US Equity</td>\n",
       "      <td>0.005167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Suntory Holdings Ltd:  SUNTZ JP Equity</th>\n",
       "      <td>EJ193380 Corp</td>\n",
       "      <td>Suntory Holdings Ltd:  SUNTZ JP Equity</td>\n",
       "      <td>0.005161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Synovus Financial Corp:  SNV US Equity</th>\n",
       "      <td>AP740283 Corp</td>\n",
       "      <td>Synovus Financial Corp:  SNV US Equity</td>\n",
       "      <td>0.005145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PNM Resources Inc:  PNM US Equity</th>\n",
       "      <td>AR661789 Corp</td>\n",
       "      <td>PNM Resources Inc:  PNM US Equity</td>\n",
       "      <td>0.005133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BancorpSouth Bank:  BXS US Equity</th>\n",
       "      <td>ZQ608645 Corp</td>\n",
       "      <td>BancorpSouth Bank:  BXS US Equity</td>\n",
       "      <td>0.005073</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>850 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         ORIG_IDS  \\\n",
       "ID                                                                  \n",
       "Bank of America Corp:  BAC US Equity                         None   \n",
       "JPMorgan Chase & Co:  JPM US Equity                          None   \n",
       "AT&T Inc:  T US Equity                                       None   \n",
       "Citigroup Inc:  C US Equity                                  None   \n",
       "Wells Fargo & Co:  WFC US Equity                             None   \n",
       "Goldman Sachs Group Inc/The:  GS US Equity                   None   \n",
       "Comcast Corp:  CMCSA US Equity                               None   \n",
       "Morgan Stanley:  MS US Equity                                None   \n",
       "Apple Inc:  AAPL US Equity                                   None   \n",
       "Verizon Communications Inc:  VZ US Equity                    None   \n",
       "CVS Health Corp:  CVS US Equity                              None   \n",
       "Microsoft Corp:  MSFT US Equity                              None   \n",
       "HSBC Holdings PLC:  HSBA LN Equity                           None   \n",
       "AbbVie Inc:  ABBV US Equity                                  None   \n",
       "Abi Sab Group Holding Ltd:  SAB LN Equity                    None   \n",
       "Oracle Corp:  ORCL US Equity                                 None   \n",
       "Charter Communications Inc:  CHTR US Equity                  None   \n",
       "Bristol-Myers Squibb Co:  BMY US Equity                      None   \n",
       "UnitedHealth Group Inc:  UNH US Equity                       None   \n",
       "Walmart Inc:  WMT US Equity                                  None   \n",
       "Energy Transfer Operating LP:  ETP US Equity                 None   \n",
       "General Electric Co:  GE US Equity                           None   \n",
       "United Technologies Corp:  UTX US Equity                     None   \n",
       "International Business Machine:  IBM US Equity               None   \n",
       "Shell International Finance BV:  599327Z NA Equity           None   \n",
       "Pfizer Inc:  PFE US Equity                                   None   \n",
       "Mitsubishi UFJ Financial Group:  8306 JP Equity              None   \n",
       "Sumitomo Mitsui Financial Grou:  8316 JP Equity              None   \n",
       "Home Depot Inc/The:  HD US Equity                            None   \n",
       "Enterprise Products Operating:  17249Z US Equity             None   \n",
       "...                                                           ...   \n",
       "Lennox International Inc:  LII US Equity            AL001841 Corp   \n",
       "Eagle Materials Inc:  EXP US Equity                 QZ008053 Corp   \n",
       "Main Street Capital Corp:  MAIN US Equity           ZS258480 Corp   \n",
       "Allina Health System:  68907Z US Equity             ZS800054 Corp   \n",
       "Prospect Capital Corp:  PSEC US Equity              EJ587828 Corp   \n",
       "Bon Secours Mercy Health Inc:  24585Z US Equity     AW031726 Corp   \n",
       "Oshkosh Corp:  OSK US Equity                        AS503589 Corp   \n",
       "Wintrust Financial Corp:  WTFC US Equity            ZS974039 Corp   \n",
       "Webster Financial Corp:  WBS US Equity              AX779959 Corp   \n",
       "Rayonier Inc:  RYN US Equity                        EJ048881 Corp   \n",
       "Janus Henderson Group PLC:  JHG US Equity           UV380214 Corp   \n",
       "First American Financial Corp:  FAF US Equity       EK586364 Corp   \n",
       "Aspen Insurance Holdings Ltd:  AHL US Equity        EJ921373 Corp   \n",
       "Memorial Health Services:  3240434ZUS Equity        ZQ943115 Corp   \n",
       "MedStar Health Inc:  20076Z US Equity               ZP410685 Corp   \n",
       "Sompo Japan Nipponkoa Insuranc:  1228123DJP Equity  EJ388405 Corp   \n",
       "New York Community Bancorp Inc:  NYCB US Equity     AV435464 Corp   \n",
       "Air Liquide SA:  AI FP Equity                       EK331653 Corp   \n",
       "Healthcare Realty Trust Inc:  HR US Equity          AQ214314 Corp   \n",
       "SL Green Realty Corp:  SLG US Equity                EJ439772 Corp   \n",
       "Trustees of Boston College:  4144477ZUS Equity      ZQ193295 Corp   \n",
       "Regency Centers Corp:  REG US Equity                EJ415633 Corp   \n",
       "Domtar Corp:  UFS US Equity                         EJ056093 Corp   \n",
       "Washington Real Estate Investm:  WRE US Equity      EJ362259 Corp   \n",
       "Kite Realty Group Trust:  KRG US Equity             QZ580190 Corp   \n",
       "Associated Banc-Corp:  ASB US Equity                AT939535 Corp   \n",
       "Suntory Holdings Ltd:  SUNTZ JP Equity              EJ193380 Corp   \n",
       "Synovus Financial Corp:  SNV US Equity              AP740283 Corp   \n",
       "PNM Resources Inc:  PNM US Equity                   AR661789 Corp   \n",
       "BancorpSouth Bank:  BXS US Equity                   ZQ608645 Corp   \n",
       "\n",
       "                                                                                                  #ID  \\\n",
       "ID                                                                                                      \n",
       "Bank of America Corp:  BAC US Equity                             Bank of America Corp:  BAC US Equity   \n",
       "JPMorgan Chase & Co:  JPM US Equity                               JPMorgan Chase & Co:  JPM US Equity   \n",
       "AT&T Inc:  T US Equity                                                         AT&T Inc:  T US Equity   \n",
       "Citigroup Inc:  C US Equity                                               Citigroup Inc:  C US Equity   \n",
       "Wells Fargo & Co:  WFC US Equity                                     Wells Fargo & Co:  WFC US Equity   \n",
       "Goldman Sachs Group Inc/The:  GS US Equity                 Goldman Sachs Group Inc/The:  GS US Equity   \n",
       "Comcast Corp:  CMCSA US Equity                                         Comcast Corp:  CMCSA US Equity   \n",
       "Morgan Stanley:  MS US Equity                                           Morgan Stanley:  MS US Equity   \n",
       "Apple Inc:  AAPL US Equity                                                 Apple Inc:  AAPL US Equity   \n",
       "Verizon Communications Inc:  VZ US Equity                   Verizon Communications Inc:  VZ US Equity   \n",
       "CVS Health Corp:  CVS US Equity                                       CVS Health Corp:  CVS US Equity   \n",
       "Microsoft Corp:  MSFT US Equity                                       Microsoft Corp:  MSFT US Equity   \n",
       "HSBC Holdings PLC:  HSBA LN Equity                                 HSBC Holdings PLC:  HSBA LN Equity   \n",
       "AbbVie Inc:  ABBV US Equity                                               AbbVie Inc:  ABBV US Equity   \n",
       "Abi Sab Group Holding Ltd:  SAB LN Equity                   Abi Sab Group Holding Ltd:  SAB LN Equity   \n",
       "Oracle Corp:  ORCL US Equity                                             Oracle Corp:  ORCL US Equity   \n",
       "Charter Communications Inc:  CHTR US Equity               Charter Communications Inc:  CHTR US Equity   \n",
       "Bristol-Myers Squibb Co:  BMY US Equity                       Bristol-Myers Squibb Co:  BMY US Equity   \n",
       "UnitedHealth Group Inc:  UNH US Equity                         UnitedHealth Group Inc:  UNH US Equity   \n",
       "Walmart Inc:  WMT US Equity                                               Walmart Inc:  WMT US Equity   \n",
       "Energy Transfer Operating LP:  ETP US Equity             Energy Transfer Operating LP:  ETP US Equity   \n",
       "General Electric Co:  GE US Equity                                 General Electric Co:  GE US Equity   \n",
       "United Technologies Corp:  UTX US Equity                     United Technologies Corp:  UTX US Equity   \n",
       "International Business Machine:  IBM US Equity         International Business Machine:  IBM US Equity   \n",
       "Shell International Finance BV:  599327Z NA Equity  Shell International Finance BV:  599327Z NA Eq...   \n",
       "Pfizer Inc:  PFE US Equity                                                 Pfizer Inc:  PFE US Equity   \n",
       "Mitsubishi UFJ Financial Group:  8306 JP Equity       Mitsubishi UFJ Financial Group:  8306 JP Equity   \n",
       "Sumitomo Mitsui Financial Grou:  8316 JP Equity       Sumitomo Mitsui Financial Grou:  8316 JP Equity   \n",
       "Home Depot Inc/The:  HD US Equity                                   Home Depot Inc/The:  HD US Equity   \n",
       "Enterprise Products Operating:  17249Z US Equity     Enterprise Products Operating:  17249Z US Equity   \n",
       "...                                                                                               ...   \n",
       "Lennox International Inc:  LII US Equity                     Lennox International Inc:  LII US Equity   \n",
       "Eagle Materials Inc:  EXP US Equity                               Eagle Materials Inc:  EXP US Equity   \n",
       "Main Street Capital Corp:  MAIN US Equity                   Main Street Capital Corp:  MAIN US Equity   \n",
       "Allina Health System:  68907Z US Equity                       Allina Health System:  68907Z US Equity   \n",
       "Prospect Capital Corp:  PSEC US Equity                         Prospect Capital Corp:  PSEC US Equity   \n",
       "Bon Secours Mercy Health Inc:  24585Z US Equity       Bon Secours Mercy Health Inc:  24585Z US Equity   \n",
       "Oshkosh Corp:  OSK US Equity                                             Oshkosh Corp:  OSK US Equity   \n",
       "Wintrust Financial Corp:  WTFC US Equity                     Wintrust Financial Corp:  WTFC US Equity   \n",
       "Webster Financial Corp:  WBS US Equity                         Webster Financial Corp:  WBS US Equity   \n",
       "Rayonier Inc:  RYN US Equity                                             Rayonier Inc:  RYN US Equity   \n",
       "Janus Henderson Group PLC:  JHG US Equity                   Janus Henderson Group PLC:  JHG US Equity   \n",
       "First American Financial Corp:  FAF US Equity           First American Financial Corp:  FAF US Equity   \n",
       "Aspen Insurance Holdings Ltd:  AHL US Equity             Aspen Insurance Holdings Ltd:  AHL US Equity   \n",
       "Memorial Health Services:  3240434ZUS Equity             Memorial Health Services:  3240434ZUS Equity   \n",
       "MedStar Health Inc:  20076Z US Equity                           MedStar Health Inc:  20076Z US Equity   \n",
       "Sompo Japan Nipponkoa Insuranc:  1228123DJP Equity  Sompo Japan Nipponkoa Insuranc:  1228123DJP Eq...   \n",
       "New York Community Bancorp Inc:  NYCB US Equity       New York Community Bancorp Inc:  NYCB US Equity   \n",
       "Air Liquide SA:  AI FP Equity                                           Air Liquide SA:  AI FP Equity   \n",
       "Healthcare Realty Trust Inc:  HR US Equity                 Healthcare Realty Trust Inc:  HR US Equity   \n",
       "SL Green Realty Corp:  SLG US Equity                             SL Green Realty Corp:  SLG US Equity   \n",
       "Trustees of Boston College:  4144477ZUS Equity         Trustees of Boston College:  4144477ZUS Equity   \n",
       "Regency Centers Corp:  REG US Equity                             Regency Centers Corp:  REG US Equity   \n",
       "Domtar Corp:  UFS US Equity                                               Domtar Corp:  UFS US Equity   \n",
       "Washington Real Estate Investm:  WRE US Equity         Washington Real Estate Investm:  WRE US Equity   \n",
       "Kite Realty Group Trust:  KRG US Equity                       Kite Realty Group Trust:  KRG US Equity   \n",
       "Associated Banc-Corp:  ASB US Equity                             Associated Banc-Corp:  ASB US Equity   \n",
       "Suntory Holdings Ltd:  SUNTZ JP Equity                         Suntory Holdings Ltd:  SUNTZ JP Equity   \n",
       "Synovus Financial Corp:  SNV US Equity                         Synovus Financial Corp:  SNV US Equity   \n",
       "PNM Resources Inc:  PNM US Equity                                   PNM Resources Inc:  PNM US Equity   \n",
       "BancorpSouth Bank:  BXS US Equity                                   BancorpSouth Bank:  BXS US Equity   \n",
       "\n",
       "                                                        #PCT  \n",
       "ID                                                            \n",
       "Bank of America Corp:  BAC US Equity                2.099665  \n",
       "JPMorgan Chase & Co:  JPM US Equity                 2.099571  \n",
       "AT&T Inc:  T US Equity                              1.753742  \n",
       "Citigroup Inc:  C US Equity                         1.686219  \n",
       "Wells Fargo & Co:  WFC US Equity                    1.629509  \n",
       "Goldman Sachs Group Inc/The:  GS US Equity          1.540419  \n",
       "Comcast Corp:  CMCSA US Equity                      1.494459  \n",
       "Morgan Stanley:  MS US Equity                       1.362673  \n",
       "Apple Inc:  AAPL US Equity                          1.315639  \n",
       "Verizon Communications Inc:  VZ US Equity           1.238190  \n",
       "CVS Health Corp:  CVS US Equity                     1.175269  \n",
       "Microsoft Corp:  MSFT US Equity                     1.163073  \n",
       "HSBC Holdings PLC:  HSBA LN Equity                  1.045616  \n",
       "AbbVie Inc:  ABBV US Equity                         1.039327  \n",
       "Abi Sab Group Holding Ltd:  SAB LN Equity           1.013033  \n",
       "Oracle Corp:  ORCL US Equity                        0.917545  \n",
       "Charter Communications Inc:  CHTR US Equity         0.790573  \n",
       "Bristol-Myers Squibb Co:  BMY US Equity             0.721365  \n",
       "UnitedHealth Group Inc:  UNH US Equity              0.694917  \n",
       "Walmart Inc:  WMT US Equity                         0.690273  \n",
       "Energy Transfer Operating LP:  ETP US Equity        0.671603  \n",
       "General Electric Co:  GE US Equity                  0.664064  \n",
       "United Technologies Corp:  UTX US Equity            0.638596  \n",
       "International Business Machine:  IBM US Equity      0.619489  \n",
       "Shell International Finance BV:  599327Z NA Equity  0.601015  \n",
       "Pfizer Inc:  PFE US Equity                          0.585870  \n",
       "Mitsubishi UFJ Financial Group:  8306 JP Equity     0.585735  \n",
       "Sumitomo Mitsui Financial Grou:  8316 JP Equity     0.567730  \n",
       "Home Depot Inc/The:  HD US Equity                   0.541458  \n",
       "Enterprise Products Operating:  17249Z US Equity    0.540376  \n",
       "...                                                      ...  \n",
       "Lennox International Inc:  LII US Equity            0.006018  \n",
       "Eagle Materials Inc:  EXP US Equity                 0.005991  \n",
       "Main Street Capital Corp:  MAIN US Equity           0.005947  \n",
       "Allina Health System:  68907Z US Equity             0.005861  \n",
       "Prospect Capital Corp:  PSEC US Equity              0.005813  \n",
       "Bon Secours Mercy Health Inc:  24585Z US Equity     0.005797  \n",
       "Oshkosh Corp:  OSK US Equity                        0.005667  \n",
       "Wintrust Financial Corp:  WTFC US Equity            0.005640  \n",
       "Webster Financial Corp:  WBS US Equity              0.005617  \n",
       "Rayonier Inc:  RYN US Equity                        0.005604  \n",
       "Janus Henderson Group PLC:  JHG US Equity           0.005596  \n",
       "First American Financial Corp:  FAF US Equity       0.005525  \n",
       "Aspen Insurance Holdings Ltd:  AHL US Equity        0.005511  \n",
       "Memorial Health Services:  3240434ZUS Equity        0.005510  \n",
       "MedStar Health Inc:  20076Z US Equity               0.005476  \n",
       "Sompo Japan Nipponkoa Insuranc:  1228123DJP Equity  0.005404  \n",
       "New York Community Bancorp Inc:  NYCB US Equity     0.005370  \n",
       "Air Liquide SA:  AI FP Equity                       0.005369  \n",
       "Healthcare Realty Trust Inc:  HR US Equity          0.005359  \n",
       "SL Green Realty Corp:  SLG US Equity                0.005334  \n",
       "Trustees of Boston College:  4144477ZUS Equity      0.005298  \n",
       "Regency Centers Corp:  REG US Equity                0.005262  \n",
       "Domtar Corp:  UFS US Equity                         0.005257  \n",
       "Washington Real Estate Investm:  WRE US Equity      0.005248  \n",
       "Kite Realty Group Trust:  KRG US Equity             0.005228  \n",
       "Associated Banc-Corp:  ASB US Equity                0.005167  \n",
       "Suntory Holdings Ltd:  SUNTZ JP Equity              0.005161  \n",
       "Synovus Financial Corp:  SNV US Equity              0.005145  \n",
       "PNM Resources Inc:  PNM US Equity                   0.005133  \n",
       "BancorpSouth Bank:  BXS US Equity                   0.005073  \n",
       "\n",
       "[850 rows x 3 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the response in a DataFrame\n",
    "newdf3 =response9[0].df()\n",
    "#newdf2 = bql.combined_df(response8)\n",
    "newdf3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cross Asset Query <a name=\"H\"></a>\n",
    "##### Break out the average Equity Implied Volatility by Credit Rating for the US Corporate Index?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "request = \"\"\"\n",
    "let(#buckets=if(in(BB_COMPOSITE,['BB','BB+','BB-']),'BB',\n",
    "if(in(BB_COMPOSITE,['BBB','BBB+','BBB-']),'BBB',\n",
    "if(in(BB_COMPOSITE,['B','B+','B-']),'B',\n",
    "if(in(BB_COMPOSITE,['AA','AA+','AA-']),'AA',\n",
    "if(in(BB_COMPOSITE,['AAA','AAA+','AAA-']),'AAA',\n",
    "if(in(BB_COMPOSITE,['A','A+','A-']),'A',\n",
    "'NR/Other'))))));\n",
    "\n",
    "#INT_RATIO=VALUE(IMPLIED_VOLATILITY,translatesymbols(members('LUACTRUU index'),instrumentidtype='Corp',targetIDtype='fundamentalticker'),mapby=lineage).value;\n",
    "\n",
    "#wgt=ID().Weights;\n",
    "\n",
    "#AVG_IVOL=groupsort(WAVG(group(#INT_RATIO,#buckets),group(#wgt,#buckets)),order=desc);\n",
    "\n",
    "#count=count(group(id,#buckets));) \n",
    "\n",
    "get(#AVG_IVOL,#count) \n",
    "for(Members('LUACTRUU Index'))\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response_z = bq.execute(request)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ORIG_IDS</th>\n",
       "      <th>#BUCKETS</th>\n",
       "      <th>#AVG_IVOL</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BB</th>\n",
       "      <td>None</td>\n",
       "      <td>BB</td>\n",
       "      <td>33.196572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BBB</th>\n",
       "      <td>None</td>\n",
       "      <td>BBB</td>\n",
       "      <td>28.845065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AAA</th>\n",
       "      <td>None</td>\n",
       "      <td>AAA</td>\n",
       "      <td>28.075831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NR/Other</th>\n",
       "      <td>None</td>\n",
       "      <td>NR/Other</td>\n",
       "      <td>27.142966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td>None</td>\n",
       "      <td>A</td>\n",
       "      <td>26.176715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AA</th>\n",
       "      <td>None</td>\n",
       "      <td>AA</td>\n",
       "      <td>24.433039</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         ORIG_IDS  #BUCKETS  #AVG_IVOL\n",
       "ID                                    \n",
       "BB           None        BB  33.196572\n",
       "BBB          None       BBB  28.845065\n",
       "AAA          None       AAA  28.075831\n",
       "NR/Other     None  NR/Other  27.142966\n",
       "A            None         A  26.176715\n",
       "AA           None        AA  24.433039"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Display the response in a DataFrame\n",
    "newdf4 =response_z[0].df()\n",
    "#newdf2 = bql.combined_df(response8)\n",
    "newdf4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Example ETF Fund Flow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "request = \"\"\"\n",
    "let(#ff = FUND_FLOW(Dates=range(\"2019-01-01\",\"2020-01-30\"),CURRENCY=\"USD\")/10^7;\n",
    "#ff_fam = sum(dropna(group(#ff,ULT_PARENT_TICKER_EXCHANGE),true));)\n",
    "\n",
    "get(groupsort(#ff_fam) as #FundFlowsbyFamily)\n",
    "\n",
    "for(filter( FundsUniv(['Active','Primary']), FUND_TYP=='ETF' AND ULT_PARENT_TICKER_EXCHANGE!='STT US' and ULT_PARENT_TICKER_EXCHANGE!=NA))\n",
    "      with(MODE=CACHED)\n",
    "\n",
    "\"\"\"\n",
    "\n",
    "# Execute the request\n",
    "response_z = bq.execute(request)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CURRENCY</th>\n",
       "      <th>ORIG_IDS</th>\n",
       "      <th>ULT_PARENT_TICKER_EXCHANGE</th>\n",
       "      <th>#FundFlowsbyFamily</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</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>BLK US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>BLK US</td>\n",
       "      <td>17948.124788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5125Z US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>5125Z US</td>\n",
       "      <td>13485.337942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SCHW US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>SCHW US</td>\n",
       "      <td>2555.066597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IVZ US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>IVZ US</td>\n",
       "      <td>1862.377179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8604 JP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>8604 JP</td>\n",
       "      <td>1512.261590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1621709D US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>1621709D US</td>\n",
       "      <td>1429.856483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JPM US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>JPM US</td>\n",
       "      <td>1221.805384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DBK GR</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>DBK GR</td>\n",
       "      <td>1065.256150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8601 JP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>8601 JP</td>\n",
       "      <td>903.358763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4068781Z FP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>4068781Z FP</td>\n",
       "      <td>886.843418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8309 JP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>8309 JP</td>\n",
       "      <td>758.464646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>006800 KS</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>006800 KS</td>\n",
       "      <td>643.679769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1764579D CN</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>1764579D CN</td>\n",
       "      <td>634.663371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UBSG SW</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>UBSG SW</td>\n",
       "      <td>562.707910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2891 TT</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>2891 TT</td>\n",
       "      <td>524.557483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GS US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>GS US</td>\n",
       "      <td>472.803497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALV GR</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>ALV GR</td>\n",
       "      <td>472.657306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5079Z US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>5079Z US</td>\n",
       "      <td>401.654548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8306 JP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>8306 JP</td>\n",
       "      <td>369.269221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2882 TT</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>2882 TT</td>\n",
       "      <td>364.701661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2881 TT</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>2881 TT</td>\n",
       "      <td>359.674465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2883 TT</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>2883 TT</td>\n",
       "      <td>346.776272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BEN US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>BEN US</td>\n",
       "      <td>344.138752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6005 TT</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>6005 TT</td>\n",
       "      <td>312.027436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0913382D US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>0913382D US</td>\n",
       "      <td>298.476062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0357289D US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>0357289D US</td>\n",
       "      <td>282.483366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CIX CN</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>CIX CN</td>\n",
       "      <td>257.753481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0001 JP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>0001 JP</td>\n",
       "      <td>256.637911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0964696D US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>0964696D US</td>\n",
       "      <td>202.085344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601211 CH</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>601211 CH</td>\n",
       "      <td>197.154642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601166 CH</th>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>USD</td>\n",
       "      <td>510890 CH Equity</td>\n",
       "      <td>601166 CH</td>\n",
       "      <td>-7.166685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZRITCZ CH</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>ZRITCZ CH</td>\n",
       "      <td>-7.361902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105560 KS</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>105560 KS</td>\n",
       "      <td>-10.324835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3887338Z US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>3887338Z US</td>\n",
       "      <td>-13.191532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>071050 KS</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>071050 KS</td>\n",
       "      <td>-13.425796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BNP FP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>BNP FP</td>\n",
       "      <td>-14.792151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>088350 KS</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>088350 KS</td>\n",
       "      <td>-15.659620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RY CN</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>RY CN</td>\n",
       "      <td>-16.526301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600036 CH</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>600036 CH</td>\n",
       "      <td>-17.309548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26026Z US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>26026Z US</td>\n",
       "      <td>-17.650825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3833548Z US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>SNLN US Equity</td>\n",
       "      <td>3833548Z US</td>\n",
       "      <td>-18.768900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0560750D CH</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>0560750D CH</td>\n",
       "      <td>-23.032548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8411 JP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>8411 JP</td>\n",
       "      <td>-25.316233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1697916D IT</th>\n",
       "      <td>2020-01-13</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>1697916D IT</td>\n",
       "      <td>-25.905034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WETF US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>WETF US</td>\n",
       "      <td>-29.307162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFG US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>PFG US</td>\n",
       "      <td>-29.790885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2318 HK</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>2318 HK</td>\n",
       "      <td>-34.689435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0852790D US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>0852790D US</td>\n",
       "      <td>-35.919099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2141Z US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>2141Z US</td>\n",
       "      <td>-98.227737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SSNC US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>SSNC US</td>\n",
       "      <td>-106.179996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1030Z GR</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>1030Z GR</td>\n",
       "      <td>-113.478759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600030 CH</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>600030 CH</td>\n",
       "      <td>-128.061365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>601688 CH</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>601688 CH</td>\n",
       "      <td>-130.796397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600000 CH</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>600000 CH</td>\n",
       "      <td>-136.998253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600369 CH</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>600369 CH</td>\n",
       "      <td>-146.156676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600999 CH</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>600999 CH</td>\n",
       "      <td>-158.840037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600837 CH</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>600837 CH</td>\n",
       "      <td>-177.757873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRCH CH</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>PRCH CH</td>\n",
       "      <td>-233.117800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3273888Z US</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>3273888Z US</td>\n",
       "      <td>-253.953514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GLE FP</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>USD</td>\n",
       "      <td>None</td>\n",
       "      <td>GLE FP</td>\n",
       "      <td>-605.603528</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>259 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  DATE CURRENCY          ORIG_IDS ULT_PARENT_TICKER_EXCHANGE  \\\n",
       "ID                                                                             \n",
       "BLK US      2020-01-30      USD              None                     BLK US   \n",
       "5125Z US    2020-01-30      USD              None                   5125Z US   \n",
       "SCHW US     2020-01-30      USD              None                    SCHW US   \n",
       "IVZ US      2020-01-30      USD              None                     IVZ US   \n",
       "8604 JP     2020-01-30      USD              None                    8604 JP   \n",
       "1621709D US 2020-01-30      USD              None                1621709D US   \n",
       "JPM US      2020-01-30      USD              None                     JPM US   \n",
       "DBK GR      2020-01-30      USD              None                     DBK GR   \n",
       "8601 JP     2020-01-30      USD              None                    8601 JP   \n",
       "4068781Z FP 2020-01-30      USD              None                4068781Z FP   \n",
       "8309 JP     2020-01-30      USD              None                    8309 JP   \n",
       "006800 KS   2020-01-30      USD              None                  006800 KS   \n",
       "1764579D CN 2020-01-30      USD              None                1764579D CN   \n",
       "UBSG SW     2020-01-30      USD              None                    UBSG SW   \n",
       "2891 TT     2020-01-30      USD              None                    2891 TT   \n",
       "GS US       2020-01-30      USD              None                      GS US   \n",
       "ALV GR      2020-01-30      USD              None                     ALV GR   \n",
       "5079Z US    2020-01-30      USD              None                   5079Z US   \n",
       "8306 JP     2020-01-30      USD              None                    8306 JP   \n",
       "2882 TT     2020-01-30      USD              None                    2882 TT   \n",
       "2881 TT     2020-01-30      USD              None                    2881 TT   \n",
       "2883 TT     2020-01-30      USD              None                    2883 TT   \n",
       "BEN US      2020-01-30      USD              None                     BEN US   \n",
       "6005 TT     2020-01-30      USD              None                    6005 TT   \n",
       "0913382D US 2020-01-30      USD              None                0913382D US   \n",
       "0357289D US 2020-01-30      USD              None                0357289D US   \n",
       "CIX CN      2020-01-30      USD              None                     CIX CN   \n",
       "0001 JP     2020-01-30      USD              None                    0001 JP   \n",
       "0964696D US 2020-01-30      USD              None                0964696D US   \n",
       "601211 CH   2020-01-23      USD              None                  601211 CH   \n",
       "...                ...      ...               ...                        ...   \n",
       "601166 CH   2020-01-22      USD  510890 CH Equity                  601166 CH   \n",
       "ZRITCZ CH   2020-01-23      USD              None                  ZRITCZ CH   \n",
       "105560 KS   2020-01-30      USD              None                  105560 KS   \n",
       "3887338Z US 2020-01-30      USD              None                3887338Z US   \n",
       "071050 KS   2020-01-30      USD              None                  071050 KS   \n",
       "BNP FP      2020-01-30      USD              None                     BNP FP   \n",
       "088350 KS   2020-01-30      USD              None                  088350 KS   \n",
       "RY CN       2020-01-30      USD              None                      RY CN   \n",
       "600036 CH   2020-01-23      USD              None                  600036 CH   \n",
       "26026Z US   2020-01-30      USD              None                  26026Z US   \n",
       "3833548Z US 2020-01-30      USD    SNLN US Equity                3833548Z US   \n",
       "0560750D CH 2020-01-23      USD              None                0560750D CH   \n",
       "8411 JP     2020-01-30      USD              None                    8411 JP   \n",
       "1697916D IT 2020-01-13      USD              None                1697916D IT   \n",
       "WETF US     2020-01-30      USD              None                    WETF US   \n",
       "PFG US      2020-01-30      USD              None                     PFG US   \n",
       "2318 HK     2020-01-30      USD              None                    2318 HK   \n",
       "0852790D US 2020-01-30      USD              None                0852790D US   \n",
       "2141Z US    2020-01-30      USD              None                   2141Z US   \n",
       "SSNC US     2020-01-30      USD              None                    SSNC US   \n",
       "1030Z GR    2020-01-30      USD              None                   1030Z GR   \n",
       "600030 CH   2020-01-30      USD              None                  600030 CH   \n",
       "601688 CH   2020-01-30      USD              None                  601688 CH   \n",
       "600000 CH   2020-01-23      USD              None                  600000 CH   \n",
       "600369 CH   2020-01-23      USD              None                  600369 CH   \n",
       "600999 CH   2020-01-23      USD              None                  600999 CH   \n",
       "600837 CH   2020-01-30      USD              None                  600837 CH   \n",
       "PRCH CH     2020-01-30      USD              None                    PRCH CH   \n",
       "3273888Z US 2020-01-30      USD              None                3273888Z US   \n",
       "GLE FP      2020-01-30      USD              None                     GLE FP   \n",
       "\n",
       "             #FundFlowsbyFamily  \n",
       "ID                               \n",
       "BLK US             17948.124788  \n",
       "5125Z US           13485.337942  \n",
       "SCHW US             2555.066597  \n",
       "IVZ US              1862.377179  \n",
       "8604 JP             1512.261590  \n",
       "1621709D US         1429.856483  \n",
       "JPM US              1221.805384  \n",
       "DBK GR              1065.256150  \n",
       "8601 JP              903.358763  \n",
       "4068781Z FP          886.843418  \n",
       "8309 JP              758.464646  \n",
       "006800 KS            643.679769  \n",
       "1764579D CN          634.663371  \n",
       "UBSG SW              562.707910  \n",
       "2891 TT              524.557483  \n",
       "GS US                472.803497  \n",
       "ALV GR               472.657306  \n",
       "5079Z US             401.654548  \n",
       "8306 JP              369.269221  \n",
       "2882 TT              364.701661  \n",
       "2881 TT              359.674465  \n",
       "2883 TT              346.776272  \n",
       "BEN US               344.138752  \n",
       "6005 TT              312.027436  \n",
       "0913382D US          298.476062  \n",
       "0357289D US          282.483366  \n",
       "CIX CN               257.753481  \n",
       "0001 JP              256.637911  \n",
       "0964696D US          202.085344  \n",
       "601211 CH            197.154642  \n",
       "...                         ...  \n",
       "601166 CH             -7.166685  \n",
       "ZRITCZ CH             -7.361902  \n",
       "105560 KS            -10.324835  \n",
       "3887338Z US          -13.191532  \n",
       "071050 KS            -13.425796  \n",
       "BNP FP               -14.792151  \n",
       "088350 KS            -15.659620  \n",
       "RY CN                -16.526301  \n",
       "600036 CH            -17.309548  \n",
       "26026Z US            -17.650825  \n",
       "3833548Z US          -18.768900  \n",
       "0560750D CH          -23.032548  \n",
       "8411 JP              -25.316233  \n",
       "1697916D IT          -25.905034  \n",
       "WETF US              -29.307162  \n",
       "PFG US               -29.790885  \n",
       "2318 HK              -34.689435  \n",
       "0852790D US          -35.919099  \n",
       "2141Z US             -98.227737  \n",
       "SSNC US             -106.179996  \n",
       "1030Z GR            -113.478759  \n",
       "600030 CH           -128.061365  \n",
       "601688 CH           -130.796397  \n",
       "600000 CH           -136.998253  \n",
       "600369 CH           -146.156676  \n",
       "600999 CH           -158.840037  \n",
       "600837 CH           -177.757873  \n",
       "PRCH CH             -233.117800  \n",
       "3273888Z US         -253.953514  \n",
       "GLE FP              -605.603528  \n",
       "\n",
       "[259 rows x 5 columns]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdf3 =response_z[0].df()\n",
    "#newdf2 = bql.combined_df(response8)\n",
    "newdf3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "<div style=\"text-align: right\"><a href=\"#BQL-String-Interface-Basics\">Return to Top ↑</a></div>"
   ]
  }
 ],
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